IN F O R M A T IO N TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleed through, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand corner and continuing from left to right in equal sections with small overlaps. Each original is also photographed in one exposure and is included in reduced form at the back of the book. Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6” x 9" black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMI directly to order. A Bell & Howell Information Company 300 North Z e e b Road. Ann Arbor. Ml 48106-1346 USA 313/761-4700 800/521-0600 A SY ST E M OF M O D ELS FOR E S T IM A T IN G R E C R E A T I O N A L B O A T I N G U S E IN M IC H IG A N C O U N T IE S By T su n g -c h iu n g W u A D IS S E R TATION S u b m itte d to M ichigan State U niversity in partial fulfillm ent o f the req u irem e n ts for the d egree o f D O C T O R O F P H IL O S O P H Y D e p a rtm e n t o f Park, R e creation and Tourism R e so u rce s 1995 UMI N um ber: 9619928 UMI Microform 9619928 Copyright 1996, by UMI Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. UMI 300 North Zeeb Road Ann Arbor, MI 48103 ABSTRACT A SY STEM OF M O D ELS FOR E S T IM A T IN G R E C R E A T I O N A L B O A T I N G U S E IN M IC H I G A N C O U N T IE S By T su n g -c h iu n g W u R eliable a n d tim ely e s tim a te s o f the a m o u n t and geog ra p h ic distribution o f recreational b o a tin g use are im p o rta n t to a gencies an d b u sin e sse s that m a k e recreational boating decisions. C urrently there is no reliable and cost effective m eth o d for predicting the a m o u n t o r location o f recreational boating use w ith o u t c o n d u c tin g costly surveys. T he p rim ary pu rp o se o f this study w a s to d e v e lo p a system o f m o d e ls w hich utilizes various seco n d a ry data s o u rc e s to p ro d u ce reliable bo a tin g use estim a tes at the count} level, f h e m o d e lin g ap p ro a c h is different from p rev io u s atte m p ts to m odel bo atin g use in that types (m arinas, second h o m e s ) and locations o f boat storage are key c o m p o n e n ts o f the system . T h e system o f m o d els inclu d e s a classification m odel, boat a llo c atio n m odels, a trip ge n e ra tio n m o d el, a n d trip distribution m odels. T h e classification m o d el categorizes registered boats into types o f sto rag e segm ents. T h e boat allocation m o d e ls e stim ate the n u m b e r o f boats in different types o f storage that are kept in M ic h ig a n c ounties d u rin g the boating season. T h e trip ge n e ra tio n and trip distrib u tio n m o d els e s tim a te the n u m b e r o f boat days in the d e stin a tio n counties. T h e m o d e ls w ere e stim a ted u sing the 1994 M ichigan B o a tin g Survey, boat registration data, a G re a t Lakes m arina inventory, and inventories o f w a te r reso u rces an d boating facilities. T he system p r o d u c e s estim a tes of: the n u m b e r o f boats in different types o f storage, the n u m b e r o f bo a ts (in different types o f storage) kept in M ichigan counties, and the n u m b e r o f boat days in d e stination counties by boat storage segm ents. C o m p a re d to survey b a sed estim ates, the system p rovides s o m e w h a t m o re robust e stim a tes o f boating use at the c o u n ty level by in corporating several in d ep e n d e n t sources o f data, and linking v arious types o f m odels. L inking different m o d e ls a llo w s the system to generate various types o f bo a tin g use e stim a tes and also red u c e s external data requirem ents. T h e m odel p r o d u c e d estim a tes o f b o a tin g use m irro r the spatial patterns o f M ic h ig a n b o a tin g use. T he system o f m o d els c o n firm s the p re d o m in a te "south-to-north" spatial travel patterns o b se rv e d in prev io u s M ic h ig a n bo atin g studies. M odel generated e stim a tes o f boat days are w ithin 10% o f the 1994 survey based estim a tes for most regions o f the state. ACKNOW LEDGMENTS This dissertation and m y doctoral p ro g ra m w a s p o ssible only by the excellent assistance from several individuals. I w ish to thank in pa rticu la r Dr. E dw ard M. M ahoney, m y a c ad e m ic a d v is o r and ch a irm a n o f m y g u idance c o m m ittee for providing e x te n siv e su p p o rt a n d ex c ep tio n a l g u idance th ro u g h o u t the c o u rse o f m y doctoral program . 1 am especially indebted to Dr. D aniel J. S tynes for m a n y m o n th s o f sincere dedicatio n and e n c o u ra g e m e n t du rin g this study and the progress o f this dissertation. I w ould also like to e x p re ss m y sincere a p p reciatio n to Dr. D o n a ld F. H olecek, and Dr. G o rdon E. M iracle for their valuable assistance, not only in term s o f dissertation, but also in o th er aspects o f m y doctoral pro g ra m as well. 1 wish to thank also the faculty m e m b e rs in the D e p a rtm e n t o f Park. R ecreation, and T o u rism R e sources for their guid an c e and a ssistance d u rin g m y m aste r and doctoral p ro g ra m s at M ic h ig a n State U niversity. 1 w o u ld also like to th an k p e rsonally m y friends in the dep a rtm e n t for their s u p p o rt and friendship. Finally, I w ish to a c k n o w le d g e m y parents an d m y family. W ith o u t their love and assistance, m y grad u a te studies at M ic h ig a n Sate U n iversity w o u ld not have been possible. TABLE OF CONTENTS Page LIST O F T A B L E S .................................................................................................................... viii L IST O F F I G U R E S ................................................................................................................... xi CHAPTER I. I N T R O D U C T I O N ....................................................................................................... 1 P ro b le m S tatem en t ............................................................................................. P u rpose and O b je c tiv es o f T h e Study ......................................................... T h e O rg a n iz a tio n o f T he S t u d y ...................................................................... 3 8 9 II. L I T E R A T U R E R E V I E W ........................................................................................ 10 P re v io u s S tudies a n d M o d e lin g o f R e c rea tio n B o a tin g in M ic h ig a n . Spatial P atterns o f R ecreational B o a tin g in M ic h ig a n ................... 1994 R ecreational B oating S u r v e y ........................................................ A n Early A tte m p t to M o d e l Spatial Patterns o f R ecreational B oating in M i c h i g a n .................................................................................... C o n c lu s io n s fro m P re v io u s S tudies and R E C S Y S S y s te m R ecreational T ravel ............................................................................................ Key Travel and T rip D istribution E l e m e n t s ....................................... D i s t a n c e .................................................................................................... D estination characteristics ................................................................ O rigin c h a racteristics .......................................................................... A p p ro a c h e s o f E stim atin g Recreational " D e m a n d " ............................... R ecreational T ra v el M o d e ls ............................................................................ 10 11 13 20 24 25 28 28 29 31 32 34 III. T H E S Y S T E M O F M O D E L S ............................................................................... 42 D ata S ources ......................................................................................................... B oat R e g istra tio n D ata ............................................................................... 1994 M ic h ig a n G reat L akes M arina C e n su s ...................................... 1994 M ic h ig a n B o a tin g Survey ............................................................. 42 42 44 44 v The System o f M o d e ls ...................................................................................... C lassification M odel .................................................................................. Storage A llocation M o d e ls ...................................................................... T rip G e n e ratio n and Trip D istribution M o d e ls ................................ 47 47 50 54 IV. M O D E L S P E C I F IC A T I O N S A N D R E S U L T S ............................................. 60 B oat Storage C lassification ............................................................................. M odel Specification .................................................................................... R esults and M odel E valuation ................................................................ Interpretation ................................................................................................. Boats Stored in C o u n t i e s .................................................................................. M odel Specification ................................................................................... A s s u m p t i o n s .................................................................................................. R esults .............................................................................................................. M odel E v aluation ........................................................................................ B oat D ays in C o u n t i e s ....................................................................................... Trip G e n e ratio n M odel .............................................................. .............. M odel specification and a s su m p tio n s .......................................... R esults and eva lu a tio n ....................................................................... Trip D istribution M odel for Boats at Stored M a rin a s in Coastal C o u n ties .......................................................................................................... M odel s p e c i f i c a t i o n ............................................................................. A s s u m p t i o n s ........................................................................................... R e s u l t s ...................................................................................................... M odel e v a lu a tio n ................................................................................. Trip D istrib u tio n M odel for Boats Stored at N o n w a te rlro n l H o m e s .............................................................................................................. M odel specification ............................................................................. A s s u m p t i o n s ........................................................................................... R e s u l t s ...................................................................................................... M odel ev a lu a tio n ................................................................................. Boat D a y s in C o u n tie s by Boat Storage S e g m e n ts ......................... R e s u l t s ...................................................................................................... M o d e l ev a lu a tio n ................................................................................. 60 60 63 68 72 72 76 77 83 90 91 91 92 V. 97 97 100 101 104 109 109 115 116 120 125 125 130 C O N C L U S I O N S ....................................................................................................... 138 T h e System o f M o d e ls ...................................................................................... T h e M o d e ls and E stim ates o f B oating Use ................................................ L im itations and R e c o m m e n d a t i o n s .............................................................. A pp lica tio n s ......................................................................................................... 139 140 146 148 VI A P P E N D IX A. A p p lica tio n for C ertificate o f W atercraft Title a n d /o r R egistration ........ 150 B. 1994 M ic h ig a n R ecreational B oating Survey Q u e stio n n a ire .................... 155 C. Indices o f B o a tin g O p p o rtu n itie s ....................................................................... 157 D. E. N u m b e r o f B oat Days G e n e rate d by B oats in D ifferent S torage S e g m e n ts at D ifferent C o u n t i e s ................................................................................................ 159 N u m b e r o f B o a t Days in Storage R e g io n s and D e stin a tio n R e g io n s by B oats in D ifferent S torage S e g m e n ts ................................................................ 161 ....................................................................................................... 165 LIST OE R E F E R E N C E S VI I L IS T O F T A B L E S TABLE Page 1. B oat O w n e r C ha ra cte ristic s ........................................................................................... 14 2. C h a ra cte ristic s o f W a te rc ra ft ......................................................................................... 16 3. S u m m a ry by B oat S torage C a te g o rie s ....................................................................... 17 4. N u m b e r o f B oats in R e s id e n c e R e g io n s and S torage R e g io n s ......................... 19 5. N u m b e r o f B oat D ays in S torage R egions and D e stin a tio n R e g io n s .............. 21 6. 1994 M ic h ig a n B o a tin g S u rv e y S a m p le Sizes for D ifferent Storage S e g m e n ts 62 7. C h a ra cte ristic s o f Boat and Boat O w n e r by Storage C a te g o ries ...................... 64 8. C la ssific a tio n M atrix for C o m p a rin g N u m b e r o f Boats in S torage S e g m en ts P redicted by the M o d e l w ith M ic h ig a n B o a tin g S u rvey ...................................... 65 9. P rofiles o f B oats (and O w n e rs ) C orrectly and Incorrectly C lassified into S torage S e g m e n ts ................................................................................................................. 66 10. D isc rim in a n t L o a d in g for Ind ep e n d e n t V ariables C o m p ris in g T h e D isc rim in a n t F u n c tio n s .................................................................................................... 69 11. W ilk s ' L a m b d a and Partial F for Independent V a ria b les in T h e D isc rim in a n t A n a l y s i s ................................................................................................................................. 71 12. E stim ated N u m b e r o f B oats in S torage S e g m e n ts by Size C la sse s ................ 74 13. N u m b e r and P e rcentage o f B o a ts in Different S torage S e g m e n ts by R egion W h e re B oat Is K ept D u rin g B o a tin g S e a s o n ............................................................ 75 14. N u m b e r and P e rcentage o f B o a ts in M ichigan C o u n ties by S torage S e g m e n ts 78 15. N u m b e r o f B oats by R e g io n o f R esidence, R e g io n o f S torage and Storage T ype ........................................................................................................................................ 82 vi i i 16. R egional D istribution o f B oats by S torage S egm ent; S a m p lin g Errors at A 9 5 % C o n fid en c e Interval ................................................................................................ 85 17. N u m b e r o f B o a ts Stored in C o u n tie s ; A C o m p a ris o n o f Survey E stim ates and A llo ca tio n M odel E stim ate s ............................................................................. 87 18. A ve ra g e N u m b e r B o a t D a y s by B oat Size C lass and S torage S e g m e n t 93 19. N u m b e r o f B oat D ays G e n e rate d by S torage S e g m e n t and Storage R egion . 94 20. V a riations in A v e ra g e Boat D ays by Boats W ithin S iz e-S to ra g e S egm ents and S torage R e g i o n s .......................................................................................................... 96 21. D istribution o f B oat D ays by D estination Z one and S torage R egion; M arina S e g m e n t .................................................................................................................................. 98 22. B oat D ays by C o u n ty o f O rig in (S torage) and D e stination (U se); M arina S e g m e n t .................................................................................................................................. 102 23. N u m b e r o f B oat D ays by S torage R egion and D e stination Region; M arina S e g m e n t ..................................... 103 24. M a rin a B oat D ays by S torage R egion an d D e stination Z o nes; S a m p lin g Errors at A 9 5 % C o n fid e n c e Interval .......................................................................... 106 25. M a rin a Boat D ays by C o u n ty o f D estination; A C o m p a ris o n o f Survey and M odel E s t i m a t e s .................................................................................................................. 108 26. D istribution o f B oat D a y s by S to ra g e R egion and Time D istance D estination Zone; N o n w a te rfro n t H o m e S e g m en t ........................................................................ 112 27. Boat D ays by C o u n ty o f O rigin (Storage) and D e stin a tio n (U se); N o n w a te rfro n t H o m e S e g m e n t ..................................................................................... 11 7 28. N u m b e r o f B o a t D ays by S torage R e g io n and D e stin a tio n R egion; N o n w a te rfro n t H o m e S e g m en t ..................................................................................... 119 29. N o n w a te rfro n t H o m e B oat D ays by S torage R e g io n a n d D e stin a tio n Zone; S a m p lin g E rrors at A 9 0 % C o n fid e n c e Interval ................................................... 121 30. N o n w a te rfro n t H o m e B oat D ays by C o u n ty o f D e stination; A C o m p a ris o n o f Survey and M odel E stim ate s .................................................................................... 123 31. N u m b e r o f B oat D ays by Storage S e g m en t and D e stin a tio n C o u n t y .............. 126 ix 32. N u m b e r o f B oat D ays by S torage R egion and D e stination R egion ................ 13] 33. B oat D ays by C o u n ty o f D e stination: A C o m p a ris o n o f S u rv ey and M odel E stim ate s ............................................................................................................................... 133 34. B oat D ays by S torage R egion and D estination R egion: A C o m p a ris o n o f Survey and T rip D istribution M odel E stim ates ..................................................... 136 x LIST O F F IG U R E S F IG U R E Page 1. M io s s e c 's M odel o f T o u rist S pace .............................................................................. 27 2. 1994 M ic h ig a n B o a tin g Survey S a m p lin g R e g io n s ............................................... 46 3. The System o f M o d e ls ...................................................................................................... 48 4. S torage T y p e C la ssification M o d e l ............................................................................. 49 5. M ic h ig a n B o a tin g R e g io n s ( I ) ....................................................................................... 52 6. Storage A llo ca tio n M o d e ls for B oats Stored at M a rin a s a n d S eco n d 1lom es. 53 7. S torage A llo ca tio n M o d e ls for B oats Stored at W a terfront H o m e s and N o n w a te rfro n t H o m e s ........................................................................................................ 55 8. T rip G e n e ratio n and D istribution M o d e ls for B oats Stored at M a rin a s in C oastal C o u n tie s and N o n w a te rfro n t H o m e s ............................................................ 58 M ic h ig a n B o a tin g R e g io n s (II) ..................................................................................... 110 10. D istribution o f B oat D ays by D e stination Z one and S torage Region; N o n w a te rlro n t H o m e S e g m e n t ..................................................................................... 113 9. xi CHAPTER I IN TR O D U C TIO N M ic h ig a n has an a b u n d a n c e o f w ater reso u rc es - G reat Lakes, inland lakes and rivers - for recreation. T h e G re a t L akes a c count for 40 p ercent o f the s ta te 's 96,791 square m iles o f surface area. T h e state has 3,288 m iles o f G reat Lakes coastline w h ic h is equal to the length o f the A tlantic coast o f the U nited States ( D 'ltr i. 1995). In addition. M ichigan has ap p ro x im ate ly 3 5 ,0 0 0 lakes that are grea ter than on e -te n th o f an acre in surface area, and 3 6 ,3 5 0 m iles o f rivers. T hese w ater reso u rc es su p p o rt a variety o f recreation and to u rism activities. R ecreational bo atin g is clearly one o f the m o st p opular and e c o n o m ica lly im p o rta n t o f these recreational activities. A c c o rd in g to the U S C o a s t G uard, M ichigan leads the nation in n u m b e r o f registered w atercraft. In D e c e m b e r 1994, 9 0 1 ,4 8 0 boats w ere registered in M ichigan. E x c lu d in g c o m m e rc ia l b o a ts and those w ith e x p ire d registrations, a p p ro x im ate ly 555,000 boats w ere actively used for recreation (Stynes et ah, 1995). It is e stim ated that during the 1994 bo atin g season, these registered craft logged an e stim ated 13.4 m illion boat days, 4.8 m illio n o n G reat L akes and co n n e ctin g w aters, a n d a b out 8.6 m illion on inland w aters (Stynes e t ah, 1995). R ecreational bo a tin g su p ports a m a jo r industry in M ic h ig a n that includes boat builders, boat dealerships, repair services and m arinas. In 1993, 2 0 ,8 5 0 people in M ic h ig a n w o rk e d in b o a ting-related b u siness in clu d in g 860 boat dealers and 115 boat T builders (N ational M a rin e M a n u fa c tu re rs A sso c ia tio n Statistics. 1994), T h e National M arine M a n u fa c tu re rs A sso c ia tio n (19 9 4 ) e stim a ted S247 m il li o n 1 o f boat sales in M ic h ig a n in 1993. Total bo a tin g related sales im pact in 1994 ( e x c lu d in g ne w boat p u rch a se s) w a s estim a ted to be a b out $2 billion sup p o rtin g 5 0 .0 0 0 j o b s (Stynes et ah. 1995). D u rin g the 1 9 6 0 ‘s. 7 0 's and early 80"s. participation in recreational boating increased steadily. Hfforts to clean up the G reat h a k e s and reduce w a te r pollution, p lan tin g o f new' fish spe cie s (e.g.. sa lm o n , steel head), d e v e lo p m e n t o f harbors o f refuge, additional public a ccess sites an d m arinas, and increasing d isp o sa b le in co m e contributed to c o n tin u e d increases in recreational boating “d e m a n d " and " su p p ly ." H o w e v er, som e e v id e n c e ex ists that b o a tin g a c tiv itie s m ay be leveling o f f (S ty n e s et ah. 1995). The a pparent d e c re a se in bo atin g can be attributed to a c o m b in a tio n o f factors: reduced catch rate o f G reat h a k e s llsh. fish c o n ta m in a n t w arnings, and the ag in g o f boaters and the boating fleet. P lanning, m a n a g e m e n t and m ark e tin g for recreational bo atin g requires up-to-date in fo rm a tio n on b o a tin g " d e m a n d " (a m o u n t o f use and location o f use), as well as the n u m b e r and distrib u tio n o f b o a tin g facilities. A 1991 recreational boating w o rk sh o p identified a n u m b e r o f im p o rta n t issues an d d e c isio n s c o n fro n tin g the b o a tin g industry and v arious m a n a g e m e n t a g e n cie s (M a h o n e y . 1991). A m o n g the m o st im portant and potentially c o n te n tio u s issues are: approval and perm ittin g o f n e w bo atin g facilities: d e v e lo p m e n t a n d m a in te n a n c e o f recreation boating facilities; fees and taxes related to boating; the allo c atio n o f fuel tax revenues; m a n a g e m e n t o f the a m o u n t o f recreational 1 The S 2 4 7 m i ll i o n i n c l u d e s s a l e s o f b o th new b o a t s an d u s e d boats. boating access: regulation o f conflicts a m o n g types o f'b o a te rs , and b e tw een boaters and other (w a te r-re so u rc e ) users, an d the e sta b lish m e n t o f a statew ide inform ation system to assist in m a n a g e m e n t and m a rk e tin g plans. In addition, industry a s so c ia tio n s and boating b usinesses m u st d e v e lo p p ro d u c t a n d m ark e tin g strategies to deal w ith increasing inactivity and de c lin e in boat use since 1986. increasing v a c an c ies at m arinas, the aging o f boat o w n e rs a n d the fleet, rec ru itm e n t o f n e w boaters, and m o d ific a tio n and up-grading o f ex istin g facilities in response to c h a n g es in b o a te rs' prefe re n c e s and behavior. PROBLEM STA TEM EN T M any boating-related issues, as well as investm ent, plan n in g , m arketing and m a n a g e m e n t de c isio n s require current b o a tin g use in form ation such as: n u m b e r o f (active) boats registered in different regions and counties; n u m b e r o f boats stored in regions and c o u n tie s du rin g the boating season; n u m b e r o f b o a ts stored at m arinas, second h o m e s , and p e rm a n en t h o m es; the spatial d istrib u tio n and p a tte rn s o f storage and m o v e m e n t (e.g.. trailering) o f bo a ts w ithin the state, and; b o a tin g use by different boat(ing) segm ents. Both public and private sectors require this in form ation for use in policy form ation, law s and regulations, facility feasibility asse ssm e n t, m an a g e m e n t, and m ark e tin g strategies. A lth o u g h bo atin g data are collected on a reg u la r basis through a variety o f m ea n s including sta te -w id e bo a te r surveys, special studies, registration data and inventories, p la n n e rs/m an a g e rs currently lack the ability to p ro d u ce reasonably accurate estim ates o f b o a tin g activity in regions a n d co u n tie s w ith o u t c o n d u c tin g costly large-scale studies. In large part, this is bec au se m o d els that can efficiently utilize secondary 4 in form ation to e stim ate and predict boating use on a geographic level c o m p a tib le with tbe scope o f boating related d e c isio n s have not been d eveloped. O v e r tbe last three d e c ad e s m any different studies has been c o n d ucted to provide recreational boating inform ation. I he studies have included regular surveys o f registered boat o w ners, state-w ide and local e stim a tes o f use and e c o n o m ic im pacts, special boating issues such as carrying capacity, and inventories o f bo atin g facilities and resources. S tatew ide surveys o f registered boaters in M ichigan have been co n d u c te d e v e n ' 5 to X years (1964. 1965. 1968, 1971, 1974, 1980, 1986. and 1995). T h e se surveys generated d e scriptive in fo rm a tio n (e.g., days boated that year, w h e re boats are stored and used) p ro v id in g a sn a p sh o t o f boating "a c tiv itie s" at those “ m o m e n ts o f tim e". H o w e v er, there are p ro b le m s associated with relying on the results o f state-w ide boater surveys co n d u c te d five to eight years apart, f ir s t, the boating m arket and behavior o f boaters are d y nam ic and significant c h a nges can o c c u r w ithin a live year period. The e stim a tes o f bo a tin g use based on state-w ide boating surveys only reflect boating use situations for a short period o f tim e. B udget cutbacks, c o m p e titio n for available funds, and increased cost o f c o n d u c tin g surveys have increased the length o f tim e betw een state­ w ide boating studies. S econd, even w ith relatively large sa m p le sizes (e.g., 6 ,000 for the 1994 M ic h ig a n B o a tin g Survey), it still is difficult to estim a te or describe local, or even regional b o a tin g activity an d b e h a v io r w ith a rea so n a b le level o f confidence. M any de c isio n s such as p ro p o sa ls for ne w facilities or regulations require specific and local boating inform ation. Surveys o f m a n y m o re than ten th o u sa n d boaters w ould be necessary to p rovide accurate e stim ates o f boating activity for different bo atin g se gm ents (size classes, storage s e g m e n ts) for all eighty-three M ic h ig a n counties. P re vious boater surxeys did not have sufficient s a m p le sizes to p rovide accurate e stim a tes at the co u n ty level. The increasing co sts a ssociated w ith de sig n in g and im p le m e n tin g state-w ide bo a te r surxevs will further lim it ou r ability to c o n d u c t sufficiently large scale studies on a tim ely basis. In a d d itio n to the s ta te -w id e bo a te r surveys, con c en tra te d on pa rticu la r b o a tin g issues and topics. o ther bo a tin g studies haxc H o lecek ct. al.. (1976) and Humphry's (1 989 and 1987) have focused on specific w a te r bodies or boating areas. Several studies have co n c en tra te d on types o f bo atin g activity and particular boater se g m e n ts such as m a rin a users and transient boaters (Bell and Leew orthy, 1987: Stewart and Stynes, 1990: T a lh e lm . 1986). O th e r studies a n d reports have e x a m in e d specific issues, such as e c o n o m ic im pact (Stynes. 1983), identification o f m arket areas (Peterson. 1991). and c a rrying c a pacity (H u m p h ry s, 1990, 1991; A shton, 1983). These studies c o n tributed to u n d e rsta n d in g b o a tin g use for particular s e g m e n ts o f boaters or particular geographical areas, a n d /o r e x p lo re d specific factors that influence bo atin g use and boating behavior. T h e results o f these studies, lim ited by their p u rp o se s (e.g., e c o n o m ic impact, feasibility a sse ssm e n t) and s a m p le sizes, w e re insufficient to estim a te state-w ide boating use. Rarely have the results from these studies been used to d e v e lo p m e th o d s for projecting or e stim a tin g boating activities bey o n d the p eriod o f tim e du rin g w hich the d ata w ere collected. B o a tin g reg istrations are a potentially im p o rta n t so u rc e o f data for e stim a tin g and predicting b o a tin g use. In M ichigan, all m o to riz e d boats and n o n -m o to riz e d craft ox er 16 feet in length m u st be registered. T h e O ffice o f the Secretary o f State m aintains 6 in form ation on these registered boats (9 0 1 .4 8 0 in 1994) including: length, type o f em it (pontoon, canoe), m o d e o f p o w e r (e.g.. n o n -m o to riz ed . sail, outboard, inboard) and the location o f the o w n e rs residence. There are som e o b v io u s a d v a n ta g e s associated with boat registration data: (1) the data are gathered on a c o n tin u o u s basts: (2) im portant in form ation is c o llected a b o u t boats and boat ow n e rs; and (3) since all boat ow n e rs m ust co m p le te a registration form it p ro v id e s a c curate in fo rm a tio n on the n u m b e r and type o f boats registered in each county. R egistration data h o w e v e r do not p rovide direct e s tim a tes o f bo atin g activity or behaviors. First, the registration data only p rovide in fo rm a tio n on w here the boat o w n e r resides, not w h e re boats are stored during the bo atin g season, o r the c ounties w here they are used. A large n u m b e r o f registered boats are not stored or used in the o w n e r 's residence county. S econd, the d ata collected on registered b o a ts and boat ow n e rs do not provide a d e q u ate in fo rm a tio n to estim ate or allocate use to different regions or counties. In addition, c urrent boat registration data include boats w h ic h are inactive and boats w h o s e registrations have expired. D irect application o f this in fo rm a tio n (e.g.. 9 0 1 .4 8 0 x days o f boating) can result in inflated e stim ates o f the n u m b e r o f active recreational boats, boat days, " need " for facilities, and the e c o n o m ic im pact o f boating. C urrent in form ation on boating facilities and se rvices is not available from any single source. Several d ata sets pro v id e in fo rm a tio n on the "supply'”, location and use o f so m e recreational bo atin g related resources and facilities-services. T h e M ichigan T o u rism R eso u rce D a ta b ase includes in form ation related to b o a tin g op p o rtu n itie s such as nu m b ers and acres o f lakes, n u m b e r o f boating access sites and m iles o f stream s/rivers (Spotts. 7 1995). T he 1994 G reat Lakes M arin a Inventory identified and collected detailed inform ation from 627 G reat L akes m arin as w ith 10 or m ore slip s/sp a c e s (T alhelm et al. 1995). T h e d a ta base c o n ta in s in fo rm a tio n on n u m b e r o f seasonal rental and transient slips and spaces (e.g.. m o o rin g s, dry stack), the n u m b e r o f o c c u p ie d spaces, and m arina services. The M ichigan D e p a rtm en t o f N atural R e so u rce s m ain ta in s inform ation on m arinas that require perm its, and the n u m b e r o f nights transient slips at publicly operated Great L akes m arin as are rented/occupied. M ost o f these data are on a co u n ty level, and they p rovide in fo rm a tio n that is useful in u n d e rsta n d in g b o a tin g use and its spatial patterns. H o w e v er, these s e co n d a ry data sets are lim ited in th eir scope. F or e xam ple, the 1994 G reat L akes M a rin a Inventory only included G reat Lakes coastal m arin as with 10 or m ore slips, not all m arinas. M o re im portantly, no system o r m eth o d is available for c o m b in in g and utilizing different supply d ata to e s tim a te the a m o u n t o r distribution o f boating activity in different regions or counties. It is clear that reliable a n d tim ely estim a tes o f recreational bo atin g use and locations o f use are im portant to age n cie s and busin e sse s m a k in g d ecisions about recreational bo atin g facilities. A variety o f seco n d a ry d ata sets are a v ailable and could be used to e stim ate boating use and its spatial patterns. E v idence sh o w s a g ro w in g need to integrate ex istin g bo atin g in fo rm a tio n /k n o w le d g e in o rd e r to d e v e lo p a system o f m odels than can relate and utilize available d ata to p ro d u c e c o st-effective a n d reliable e stim ates o f recreational boating use, and the locations o f this use. T he in fo rm a tio n from the 1994 M ichigan B oating Survey (Stynes et al., 1995) an d p rev io u s sta te -w id e and regional 8 b o a tin g studies alo n g w ith various seco n d a ry d a ta pro v id e an ex c elle n t basis for d e v e lo p in g such a system . P U R P O S E A N D O B JE C T IV E S OF TH E ST U D Y T h e prim a ry p u rp o se o f this study is to p ro d u c e reliable co u n ty level e stim a tes o f boating use by different bo a t segm ents. T h e ob jec tiv e is to g e n e ra te reliable and cost effective e s tim a tes of: (1) n u m b e r o f bo a ts ke p t in c o u n tie s d u rin g the bo atin g season. (2) n u m b e r o f boats in d iffe re n t types o f storage in c o u n tie s (e.g., m arinas, second hom es), and (3) boat days in different c o u n tie s by bo a t storage s e g m e n ts. T h e re are two m ain rea so n s for using type o f storage as the basis for the system o f m odels, f irst, bo atin g use and spatial p a tte rn s o f use d iffer be tw e en boats in different types o f storage, l'o r e x a m p le, boats stored at coastal m a rin a s are larger an d m o re likely to be used on the G reat Lakes. A single m odel that does not se g m e n t by storage type can not satisfactorily m odel the b o a tin g use patterns o f different boat storage segm ents. S e g m e n ta tio n increases the efficiency o f m odeling. S econd, use estim a tes by storage type better m eet the in fo rm a tio n ne e d s o f public an d private sector providers. F o r e x a m p le , n u m b e r o f boats stored at m arin as in a cou n ty is m u c h m o re relevant to the feasibility o f a p ro p o se d m arina th an an e stim ate o f all bo a ts stored (or registered) in the county. A system o f m o d e ls u tiliz in g ex istin g secondary d ata s o u rc e s and the recent b o a te r survey is d e v e lo p e d to a c c o m p lis h the study objectives. T h e system o f m odels: 9 1. In corporates boat registration inform ation (length, location o f o w n e r 's residence) to p ro d u c e reliable estim ates o f the n u m b e r o f boats in different types o f storage in different counties. 2. U tilize s “ m o d el p r o d u c e d ’' estim ates o f th e n u m b e r o f b o a ts in different types o f storage in different counties to e s tim a te the n u m b e r o f boat days in M ichigan counties. T H E O R G A N IZ A T IO N OF T H E S T U D Y T h e study is prese n ted in five chapters. The n e x t c h a p te r rev ie w s p revious boating studies and literature relating to m odeling recreational use and spatial patterns o f recreational uses w ith a n e m p h a s is on trip allocation concepts, trip allocation m ethods, and distance functions. T h e third chapter describes the d a ta sets used to estim ate the m o d els and the overall structure o f the system o f m odels. T h e fourth c h a p te r presents the process o f e stim a tin g the m odels, and the results o f the m o d e ls including e stim ates o f boats in different storage se g m e n ts, n u m b er o f boats kept in different types o f storage in c ounties and. boat days in co u n tie s by boats kept in different types o f storage. T he fifth and final ch a p te r p ro v id e s a o v e rv ie w o f the model d e v e lo p m e n t process, evaluates the pe rfo rm a n c e o f the m o d els a n d offers rec o m m e n d a tio n s for im p ro v in g the m o d els and inform ation used by the m odels. CHAPTER II L I T E R A T U R E R E V IE W The pu rp o se o f this c h a p te r is to review literature and studies that (1) have e x a m in ed boating activities a n d spatial patterns o f recreational bo a tin g in M ichigan. (2) present c o n c ep ts and th eo ries o f recreational travel, ap p ro a c h e s to/for m o d e lin g recreational use. and (3) d iscu ss relevant The disc u ssio n inclu d e s a review o f M ichigan bo atin g studies and p rev io u s a ttem pts to m odel M ichigan boating use. Special e m p h a sis is placed on the 1994 M ichigan B oating Survey, the principal data used to de v e lo p the m odels. The c h a p te r also review s theories and m ajo r c o m p o n e n ts o f recreational travel that serve as the conceptual basis for bo a tin g m odels. This chapter co n c lu d e s w ith a rev ie w o f use estim a tio n and trip distribution m odels. P R E V IO U S S T U D IE S A N D M O D E L IN G O F R E C R E A T I O N A L B O A T IN G IN M IC H IG A N T his section rev ie w s studies that p rovide a d e scription o f b o a tin g spatial patterns in M ichigan o v e r the past three d e cades, the results o f 1994 M ic h ig a n B oating Survey with e m p h a s is on current boating use patterns, and a boating use system based on spatial distribution n a m e d R E C S Y S S Y M A P . 10 Spatial Patterns o f Recreational B o a tin g in M ichigan N in e m ajo r statew ide recreational boating surveys have been c o n d u c te d over the past thirty years ( M O R I). 1964: M ichigan W a terw ays D ivision. 1965: D e partm ent o f Park and R ecreation R esource. M S U . 1968; R ecreation R eso u rce C onsultants. 1971: R ecreation R e source C o n su lta n ts. 1974: M ichigan W ate rw a y s D ivision. 1977: M ichigan Sea Chant. 1980: Travel. T o u rism and R ecreation C enter. M S U . 1986: D e partm ent o f Park. R ecreation and Tourism R esources. 1994). Those studies sa m p le d boats from the M ichigan boating registration lists m ain ta in e d by the O ffice o f the M ichigan Secretary o f State. They c o llected in fo rm a tio n on: characteristics o f fleet (e.g.. size, type and age o f boats), characteristics o f boat ow ners, boat storage, n u m b e r and locations o f boat launchings, v o lu m e and locations o f boat use. boating related spending, and special to p ics/issues (e.g.. law en fo rc e m e n t, pum p-outs). Inform ation from these studies provides d e scrip tio n s o f bo atin g use characteristics and patterns at the tim e o f the studies. 'The findings from three m a jo r studies p rovide a description o f the spatial patterns o f recreational boating in the years 1965. 1974. and 1986. S o m e o f the relevant findings include: The 1965 B oating Survey (M ic h ig a n W aterw ay D ivision. 1965) sa m p le d 13.670 boats. It found that the bo a ts/b o a te rs in the co u n tie s in the southeast o f the slate h ave highest level o f bo atin g use. O n the o th e r hand, the U p p e r Peninsula, plus six areas alo n g the c o a stlin e o f L o w er M ic h ig a n p rovided the highest lew d o f bo atin g "supply". T h e low est " s u p p ly " w as in the c e n tral/south L o w er Peninsula. T his w a s on e o f the first studies that identified the extent o f the south-to-norlh flow o f recreational boats. T h e study found that the m ajority o f boats used in s outhern M ichigan c o u n tie s w ere registered in the local area — these w ere not d e stin a tio n counties. F or ex a m p le. 9 8 % o f boats o p erated in W ayne county were registered by o w n e rs resid in g in the county. C o nversely, only a sm all portion (8 % ) o f the recreational craft used in R o s c o m m o n county w ere registered bv residents o f the county, 14% o f boats used in R o s c o m m o n county w ere ow ned b\ a pe rso n residing in W a y n e county. T he 1974 studies ( C h u b b and C hu b b . 1975) sa m pled 13.600 registered boats and sh o w e d a sim ilar d istrib u tio n o f bo a tin g origins, d e stination patterns and Hows. B oats registered in southern M ic h ig a n c ounties c o m p rise d the largest share o f recreational bo atin g use. S o u thern M ichigan c ounties “e x p o rte d " boat days to northern counties. B oats registered by o w n e rs residing in northern c ounties were generally used in northern M ichigan. For ex a m p le, m ore than 9 5 % o f boat days generated by boats registered in the n o rthern lo w e r p e n in s u la o f M ic h ig a n and UP w ere used in the region. O nly 6 8 % o f boat days by boats registered in southern M ichigan co u n tie s occurred in the region. 2 9 % o f the days o c c urred in northern M ichigan. The 1986 statew ide study (T alhelm et. al.. 1988) sa m pled 10 .089 registered boats w ith findings that w ere consistent with the prev io u s b o a tin g studies. The study s h o w e d that m ore po p u late d southern M ichigan co u n tie s and c o u n tie s with m ore boating op p o rtu n itie s located near population centers exp e rien c e d the highest am o u n t o f recreational bo atin g use. Fifty-eight percent o f all recreational boat days occurred in c ounties c o m p risin g the southern h a lf o f low er Peninsula. 33% o f boat days w ere in the northern h a l f o f low er M ichigan, an d 9 % w ere in the U pper Peninsula. C o u n tie s in southeast, the th u m b , an d central L o w er Peninsula generated and e x p o rte d m o re boat days than w e re “ im p o rte d " by boaters from o u tsid e the regions. All o ther counties im ported m o re boat days than days by boats registered in the counties. The findings from these and o th er previous b o a tin g studies p rovide relevant inform ation on the spatial distribution and patterns o f recreational bo atin g use. They reveal that the basic spatial patterns o f bo a tin g use and flow o f recreational boats have been fairly stable o v e r years. T he studies s h o w e d that: (1) B oats registered in southeastern M ichigan co u n tie s gen e ra te the m ajority o f boat days in the state. (2) Boating op p o rtu n itie s a n d reso u rc es are u nevenly d istributed ac ro ss the state. (3) T h e U pper Peninsula, northern L o w e r Peninsula, coastal counties and lake areas pro v id e d relatively m ore bo a tin g op p o rtu n itie s an d as a result attract a greater share o f boat days from outside these regions and counties. (4) T h e m ajority o f boat days in southern M ichigan counties are by boats registered in the county or nearby counties. T here is relatively little n orth-to-south recreational boating travel. V ery few o f the boats that are operated in 13 southern M ichigan arc registered in northern counties. (5) A com p a rativ ely high pe rcentage o f boat days in northern M ichigan co u n tie s arc by boats registered in southern counties. 1994 M ic h ig a n B o a tin g Survey T h e 1994 M ic h ig a n B o a tin g S u rvey pro v id e s the m o st c urrent inform ation on statew ide b o a tin g activities. T h e data c o llected from boaters are crucial in estim ating the m o d els d e v e lo p e d in this study. T h e study p ro v id e s in fo rm a tio n on the characteristics o f boat o w n e rs (T a b le 1). ch a ra c te ristic s o f the fleet (T abic 2). b o a tin g use by storage type ( Table 3). and spatial patterns o f boating activities ( fa b le s 4 and 5). Boat o w n e rs arc co n sid e rab ly o lder than the rest o f the M ic h ig a n 's population with m ed ia n age a ro u n d 56. A b o u t h a lf o f all boat o w n in g h o u s e h o ld s have one or m ore children in the family. T h e m e d ia n in co m e is j u s t u n d e r $ 4 0 ,0 0 0 a year w hich is so m e w h a t hig h er than the state average. A p p r o x im a te ly a third o f boat o w n e rs ow n som e type o f seasonal h o m e or cottage (T able 1). M o s t o f M ic h ig a n 's registered recreational w a te rc raft are sm all boats. Highly percent are tw enty feet or shorter. O v e r h a lf o f the registered boats are pow ered by outboard m otors, a q u a rte r are eith e r inboards o r inb o ard -o u tb o a rd s. and ro w b o a ts c o m p rise 16% o f the fleet. P ontoons, canoes, S ailboats rep re sen t only four percent o f the registered fleet. A b o u t sixty p ercent o f registered boats are stored at the o w n e r 's perm anent residence d u rin g the bo a tin g season. A b o u t a qu a rte r are kept at seasonal ho m es and about 12 p ercent at m arinas. O v e r h a l f o f the bo a ts are stored on land du rin g the boating 14 Table 1. B oat O w n e r C haracteristics. Percentage AGE OF BO AT O W NER y o u n g e r than 4 0 2r o 4 1- 5 0 I 9° 51 - 6 0 I 7no 6 1- 6 5 11% 14° o 66-70 O ld e r than 7 0 n 19" „ 100% N O O F A D U L T S IN T H E H O U S E H O L D 1 IX".. 2 7 0°,, 3 85,, 4 3° ,. 5 or m o r e l"„ 100",. H O U S E H O L D W ITH C H IL D R E N n o c h ild re n 53° „ 1 c h i ld 20 ",, 2 c h ild r e n I 55,. 3 c h ild r e n 8" „ m o r e than 4 c h i ld r e n 4",. 100",. H O U S E H O L D IN C O M E Under $ 2 0 ,0 0 0 22"„ $2 0 ,0 0 0 -5 3 9 ,9 9 9 34% $ 4 0 ,0 0 0 -5 5 9 ,9 9 9 23% $ 6 0 ,0 0 0 -$ 9 9 ,9 9 9 16% O ver $ 100,000 6% 100% SEA SO NA L HOME O w n a s e a s o n a l h o m e in MI D o n o t o w n a s e a s o n a l h o m e in MI 69“o 100% a. U n it o f a n a l y s i s in this t a b le is the b o a t o w n e r . S a m p l e o f b o a t s w a s w e i g h t e d in v e r s e to n u m b e r o f b o a t s o w n e d b y e a c h r e s p o n d e n t . 15 season, c o m p a red to 40 percent in the w ater or in a dry stack storage space. Just over 40 percent o f w atercraft are kept at n o n-w aterfront locations du rin g the boating season (T able 2). Boats stored at p e rm a n e n t h o m e s are transported/traiicred greater distances — ap p ro x im ate ly 47 m iles one w a y to the locations w here they are used than boats kept in o ther Ivpcs o f storage (T able 3). O n average, the m arinas w here boats are stored during the season are 87 m iles from the o w n e r 's p e rm anent residence. T h e distance betw een the boat ow n e rs p e rm a n en t residence and second ho m es w h e re they store their boats averages 225 miles. M ic h ig a n registered bo a ts generated an estim ated 13.4 m illion boat days in 1994. 4.8 m illion on G re a t Lakes and 8.6 m illio n on inland waters. O n average, boats kept at m arin as are used m o re frequently. O v e r 70% o f the days by boats kept at perm anent h o m es or second h o m e s o c c u r o n inland lakes or rivers. T h e tw o m ost frequent uses o f boats are fishing (5 6 % o f use o r days) an d pleasure cru isin g (3 9 % o f use o r days). The type o f boating activities differ a m o n g boats kept at different types o f storage du rin g the boating season. Seventy percent o f the use o f boats kept at perm a n en t residences is for fishing. In contrast. 70 percent o f the use for boats kept at the m arinas involves pleasure c ruising (T able 3). T he study estim a ted that about 2.5 m illion boat lau n c h in g s take place on inland w aters each year a n d 1.4 m illio n launchings o c cur on G reat Lakes waters. B oats kept at perm a n en t residences account for over eighty percent o f G reat Lakes lau n c h in g s and about 90 percent o f launchings on inland lakes and stream s. S even percent o f the 16 T able 2. C ha ra cte ristic s o f W atercraft. Percent B O A T SIZE <16' 5 2°., l6 '- 2 0 ' 28" « 21 '-28' 16% >29' 2% 10 0 ° „ BOAT TYPE In board I n b o a r d /o u tb o a r d Outboard 19" „ 6" 56" o S a il, u n p o w e r e d 1% S a il, w ith p o w e r 5" „ Pontoon 8% C a n o e or R o w 8" ii P e r s o n a l w a te rc r a ft 0° „ O th e r 0% 100" „ S T O R A G E F A C IL ITY Perm anent resid en ce 59" „ C o t t a g e or s e c o n d h o m e 25% P u b l i c m arin a 3% R e n t e d s p a c e in c o m m e r c i a l m arin a 6" „ O w n e d s p a c e in m a r in a /d o c k a m in iu m 1% Y a c h t / b o a t c lu b 2% O th e r 4% 10 0 % ST O R A G E L O C A T IO N O n land In a dry s t a c k fa c ility In th e w a te r ( w e t slip , m o o r i n g o r d o c k s i d e ) 55" o 1% 3 9 ° ii A t t a c h e d to or o n a larger boat 1% O th e r 4% 100% TY PE O F ST O R A G E L O C A T IO N A rive r o r str eam w ate rfr o n t A n o n - w a t e r f r o n t site C 24" c> C A w a te r f r o n t s it e w / a c c e s s t o th e G re at L a k e s A n inla nd la k e w a te rfr o n t site 3" u 41% 10 0% 17 Table 3. S u m m a ry by B oat Storage Categories. P er m a n e n t Second R esidence 1l o m c (11-327.561 ) (n- 138.7971 M arina 27.817 192 1.581 0 O '; R om p d ( 'nlum h p t l . Central hast North West 3.264 0 84 R om p c i 6 .5 "; 0 0%, 0 .2 " ; ( O lu m n p a . 5 .5 ’%, 0.0'%, 0 .5 '%, 727 0 0 Central West R om p a . < o lu m n p a South Inland R om p a ( ’o lu m n p e t North Inland R om p c i. ( o lu m n p a P South < 'olum n p a pa < o lu m n p a Total ip a x c n h m ile i j.r ,; , !.'/% , 0 .0 " ; 0.1% , 2 6 6%, 108 0 40 816 0 .4 %, 0.0'%, 0.1% , 5 o%, o il" ., 0 5 .0 "; 0 0 13 5 , 0 .5 %■ o.o";, o y%t 2 ‘6%, 18.438 2.379 0 0 0 1.906 It). 3 ", 0.0'%, 0.0'%, 0 .0 " ; V4 ’%, u r , 0.0% , 0.0",, 0 .0 " ; 166.855 0 0 ' J 3 .t r , 0 .0 ’%, 0 0 ’%, 0.0 " ; 0 .0 % 0.0% , 0.0% , o r%, 213 0 324 0 1,565 s .: \ 0.1";, 0.0% , 0 0",. 0 i.e ., 0 o.s'%. <1.0%, 1.1% , O.0"„ r. K".. ~ i.< r , 0 0%, 0 0'%, 0 0"; } 6 0'%, 2.933 0 0 1.146 127 23.162 33.274 0 0 4.051 ~.0"„ 4 .2 % 0.0% . 0 0" ; 1.0"; 3 3 .3 1;, 4 ~.'/%, 0.0'%, 0 0" ; s S'%, 4 4 5" S'). 478 : o%', 1 .5 '%, 0.0'%, 0 D’%, 1 4 .2 ’%, 12.332 171 4.251 5 2 .0 '%, 0. ~'%, h .r % , 05 i . 5 ‘%, 14 ■)•%, 2.627 1.300 819 13.061 1.380 15 .5 "; 6 ft%, 4 2 ’%, 6 6 2'%< ‘ i r ., 6.2"« O S ./ " ; 4 S'%, 1.1" " 5 5" 311 40 5 * 0 0 0%. : 15 6 272 2" ; 0 0 ’%, 4 0 5 %, 0 }'% o o -, 0 1"; O D" , 235.171 37.080 13.166 13.316 . J '. 4 } . 4 ■■ f< S 26.669 4 . J"; 32.392 f,0 ''„ 52,095 •If,"., 27.178 3 tr . 22,736 4 . 2 "; 179.510 33. r „ 69.527 1 2 .x ; , 23.440 4 3 "; 19.717 3.r „ i 5.V"o 108 I f, 3 "; 6 "'%, 4.819 4.833 ryr I p c l.l 88.136 ^ 2.731 0.0% , Out of State Rom - r, s%. 5.734 UP North R om p t 1 0 1.367 V 1"; ~v R om p i t . < o lu m n p c i. " o 14 6%, 0.0" „ o .r „ 0 4 '%, 7.620 „ 0 .0 " i, o ir , 10 0 0 .0 % 95 0.0'%, 1 O' r Total 4 2 "; 0 .0 " ; >0": 0 .0 % 0 0 “v ~'%, o. 00% , 0.0". 0 0.0'%, 273 703 0 .0 % 0."%, 0 .4 %, 1 5 '%, 0 S"„ ( 'olum n p a . 5 5 "; 4.720 : ti.x ; , 21.380 0 0% 0 n 10.825 10 2."%, 0.0'% <> 5 ' 0 4 '%, 5 5 .4 0 0.2% , 14 % R om p a . South West V -5 . 155 / 671 ()'■-, 28.595 542.071 1) l"„ 20 generated by bo a ts stored in northern M ichigan (including northeast, n o rth w e s t and l.I.P. regions) are from w ith in the region. In c o m p a riso n , only 8 0 % to 9 0 % o f boat days generated by so u th e rn M ichigan boat o w n e rs (including southeast, so u th w e st, south inland, central w est and central east regions) are c a ptured w ithin the regions ( f a b l e 5). S outhern M ic h ig a n c o n tin u e s to generate and a c c o m m o d a te the greatest n u m b e r o f boat days. There is a very evident s o u th -to -n o rth pattern from locations w h e re boat ow ners reside to locations w here boats are stored du rin g the season. M ore boats o w ned by p ersons re sid in g in the southern part o f the state are stored in o ther regions. A high p e rcentage o f theses boats are stored in northern counties. T h e so u th -to-north pattern exists, but is less p ro m in e n t for m o v e m e n t o f boats from w here they arc stored to where they are used. An Early A ttem p t to M odel Spatial Patterns o f R ecreational Boating in M ic h ie an A lth o u g h the p revious studies p ro v id e in fo rm a tio n on the pattern o f recreational boating use in M ichigan, there has been only one m ajo r a tte m p t to m odel spatial patterns. T h e R E C S Y S ( M ic h ig a n Recreation S ystem ) w a s on e o f the earliest a tte m p ts to model recreational travel How s for use in p la n n in g purposes. R E C S Y S w as d e v e lo p e d as part o f an effort "to pro v id e a balanced an d orderly ap p ro a c h to the p roblem s o f m ee tin g current and future recreation needs, and to assure that m a x im u m benefits are o b tain e d from state, county, m u n ic ip a l, and private in v estm e n t in o u td o o r recreation land and d e v e lo p m e n t" (M ic h ig a n D e p a rtm e n t o f C on se rv atio n , 1966). It w as proposed as a m eth o d q u antifying rec re atio n "n e e d s" on a c o u n ty -by-county basis. for It was intended to provide T able 5. N u m b e r o f B oat D ays in S to ra g e R e g io n s and D estination Regions. REGIONS OI- STORAGE Boat Days’ 000' Destination North Central- Regions South-East 2.004.4 South East C entral-East N orth-East N oith-W est West .i 4.1 0.2 0.4 0.1% 0.2 % 0.0% 0.0% i U I’ South 11 P N orth Total (pci ) 1.7 69.7 2.2 0.1 0.0 2.084.0 17 0% 0 1% 3.3% 0 1% 0 0%, 0.0% 0 074 445.7 3 6% 742.1 6 .0% 1.360.6 11 174 524.3 4.3% 571.7 4. 774 3.513.1 28 6% 1.778.7 145% 695.5 5. 7% 573.7 4 774 S outh-W est South Inland Inland Row pet. 96 1% C olum n pet. 90 5% 0.3% 0.6 % 0.0% 0.1% 0.3% 18% 0 1% 0 07, 17.8 353.0 1.6 1.8 0.0 0.5 69.3 1.3 0.5 Row pet. 4 0% 79.2% 0.4% Q.4°/b nn % 0.1% 15.5% 0 37o o r, 0 Ol’G Colum n pet. 0.8% 82 .1 % 0.2 % 0.1% 0.0% 0.1% 1.8% 0.1% o /% 0.0% 10.6 28.5 635.9 3.4 1.4 0.2 47.8 14.0 0.2 0.1 Row pet. 14% 3.8% 8 5 .7% 0.5% 0.2% 0.0% 6 .4% 1.971, 0 07, 0.074 C olum n pet. 0.5% 6.6 % 97 8 % 0.3% 0 3% 0.0% 1.2% 0 876 0 076 0.0% 19.5 2.8 2.8 1.206.5 7.4 19.5 73.1 0.3 0.0 Row pet. 14% 0 .2% 0.2% 88. 7% 0.5% 1.4% 5 .4% 28.7 : /% 0 0% 0.0% Colum n pet. 0.9% 0 .7% 0 .4 % 98.3% 1.4% 3.4% 1.9% 1 776 0 07, 0.074 1.5 0.1 0.6 0.4 456.8 17.3 46.2 1.3 0.0 0.3 Row pet. 0.3% 0.0 % 0.1 % 0.1% 87.1% 3.3% 8.8% 0 27b 0 07, 0.174 C olum n pet. 0 1% 0.0 % 0.1 % 0.0% 84 4% 3.024, 1.2% 0 17b 0 0", 0.1% 2.0 0.0 0.0 1.1 24.2 486.9 57.5 0.0 0.0 0.0 R ow pet. 0.3% 0.0% 0.0% 0 .2% 4.2% 85.1% /ft/% 0 07b 0 07b 0 074 C olum n pet. 0.1% 0.0% 0.0 % n. i% 4 5% 85.2% 1.5% 0.076 0 07, 0.0% 90.0 14.3 0.4 3.0 21.2 37.4 3.337.2 9.5 0.0 0.0 Row pet. 2 6% 0.4% 0 0% 0.1% 0.6% 1.1% 95.0% 0 37b 0 07, 0 0% C olum n pet. 4.1% 3.3% 0.1% 0.2% 3 9% 6.5% 8 5 .6 % 0.674 0 0% 0.074 35.5 25.5 0.3 2.8 6.5 0.0 151.9 1.556.0 0.0 0.1 Row pet. 2.0% 1.4% 0.0% 0 2% 0 4% 0 0% S. 5% S 7.476 0 076 0.074 C olum n pet. 1.6% 5 .9% 0.0% 0.2% 12% 0.0% 3 .9% 94.0% 0 0°:, 0.07-6 3.2 5.6 6.7 0.5 11.8 6.2 654.2 1.6 0.22b C entral East N orth East N orth W est Central West South West South Inland N orth Inland 4.7 U P South 1.0 0.0 Row pet. 0.7% 0.1% 0 .5% 0 8% 1.0% ft/% 1.7% 0.97b 93 8 7 , C olum n pet. 0.2% 0.2% 0.5% 0 5% 12% 0.1% 0.3 % 0 47b 9S 174 0.4% 28.5 3.6 1.4 2.7 16.6 7.5 35.1 35.7 11.7 430.8 5.0% 0.6% 0.2% 0 5% 2 9% 1.3% 6.1 % 2 0", 75.07b U P N orth Row p e t C olum n pet. Total (percen t) 1.3% 0.8% 0.2% 0 22',, 3.1% 1.3% 0.921, A 0 . „10/n l ")<)■ 1 8"6 99 5% 2.214.5 430.1 650.3 1.227.5 541.2 571.6 3.899.5 1.654.8 667.0 432.8 18.0% 3 5% 5 32,, 10 0",„ 4 4%, 4.6% 31 7% 13 576 5 4", 3.5% a Cases tailed to report the location of boating destination, storage location and t\pes of boat storage are excluded from anaUsis I eu respondents indicate the\ used or stored their boats out of the state are also excluded 12.289.4 predicted “ d e m a n d " and relate it to “ supply ca p ac ity ” (M ic h ig a n D e partm ent o f C o n se rv atio n . 1966). R H C S Y S is based on the spatial distribution o f the location w here boating activities take place (destinations), the area distribution o f potential population sources (origin) and the location o f the h ighw ays c o n n e c tin g origins and d e stinations (C hubb. 1967). It predicts the spatial distribution o f recreation d e m a n d by sim ulating the m o v e m e n t o f recreation users from origin areas to destin a tio n s o v e r the highw ay travel netw ork. 1'his sim u latio n m odel is based on linear system s theory. R H C S Y S system a s su m e s that recreational trips to a destination from any origin is so m e function o f a tim e-d ista n c e factor and the d ra w in g p o w e r o r attractiveness at the destination. The RHCSYS system d e v e loped by Hllis (1 9 6 4 ) included three c o m p o n e n ts: 1. O rigin c o m p o n e n t (O), O (boat days generated by each origin) = a d e te rm in a b le quantity. 2. Transportation link c o m p o n e n t (H). 11 (for any h ig h w a y link)= 1/R*P|, W here R is a resistance factor, and R ^ k i* ('f ) + k : * ( C ) |i. - T = tim e in hours e stim ated to travel a lo n g the link, a n d T = distance/speed. - C = the direct cost o f traveling alo n g the link. - k*= constant. - P = exponent. W h e re P|, is the d e m a n d p ressure a lo n g the link. 3. D e stin a tio n c o m p o n e n t (D), D (into the de stin a tio n ) = A *I\|. W h e re A is the attractiveness o f the destination. W h e re P j is the d e m a n d p ressure into the d e stin a tio n area. m ajor O n c e all the c o m p o n e n ts w ere identified and quantified, linear g rap h s2 were d e v eloped to build and solve the ap p ro p riate m odel for the recreation activity under a specified actual structure o f the recreation sy ste m 3. C h u b b (1 9 6 7 ) utilized R H C S Y S and bo atin g use data from a 1965 survey o f recreational boat o w n e rs to predict use at various destinations. “ First ru n ” predictions o f the m odel w ere very different from actual use e stim a ted by the survey. A fter calibration runs, the R H C S Y S s im u latio n for 1965 recreational boating use retained a 19.2 percent standard deviation. For 4 3 % o f d e stination counties, predicted use w as w ithin five percent o f survey estim a ted use4. F or 2 8 % o f d e stination counties, predictions o f use varied 5 -1 0 % from survey estim a ted use. T h e largest disc re p an c y w a s -82.6% for H m m et county. C h u b b identified three m a jo r p ro b le m s o r d isa d v a n tag e s w ith R H C SY S as a m ethod for sim u latin g recreational bo a tin g use patterns. First, the tech n iq u e requires a large am o u n t o f d a ta on both boating " s u p p ly " and “d e m a n d " . T his inform ation is n orm ally o b tain e d th ro u g h large scale surveys. D esign and testing o f R H C S Y S also requires highly specialized personnel. Finally, (at the tim e) RECSYS required sophisticated c o m p u te r facilities. In a ddition, R E C S Y S only e stim a tes n u m b e r o f boat days in a destination, not types or a m o u n ts o f different bo a tin g uses. Type o f and d istrib u tio n o f boat uses are crucial to p lan n in g a ccess an d facilities, and m an a g in g recreational boating. For exa m p le : Linear gr a p h s d e r iv e fr om the m a t h e m a t ic a l d i s c i p l i n e o f t o p o l o g y . ' f h e structure o f a r ec r e a t io n s y s t e m is b a s e d o n the sp atial a r r a n g e m e n t o f c i t i e s , c o u n t i e s an d h i g h w a y s . It d o e s not vary a c r o s s r ec re a tio n a c t iv it ie s . 4 B e c a u s e C h u b b ’s report d id not p r o v i d e s a m p l i n g errors for s u r v e y e s t i m a te s , it is d if f ic u lt to d e te r m in e the a c c u r a c y o f s u r v e y b a s e d e s t i m a te s . 24 estim a tes o f only total n u m b e r o f boat days do not provide ade q u ate inform ation (e.g.. use by different size o f boats) to e stim a te “ n e e d s '’ for lau n c h in g facilities. R H C S Y S also failed to incorporate in fo rm a tio n on w h e re the boat w a s stored o r types o f storage (m arina, se co n d hom e). T h e R E C S Y S system e stim a tes n u m b e r o f boat days generated in the co u n tie s w h e re registered boat o w n e rs lives, not necessarily w h e re the boats are kept du rin g the season. S tudies in 1986 and 1994 clearly s h o w that w here boats are kept d u rin g the season, and type o f storage are im p o rtan t in estim a tin g and d istrib u tin g boating use. C o n c lu s io n s from P re vious S tudies A n d R E C S Y S System T he R E C S Y S system a n d p revious studies o f recreation boating activity and spatial patterns p rovide fin d in g s and co n c lu sio n s that can im prove the reliability ami efficiency o f recreational b o a tin g m odels. First, boats kept in different types o f storage have distinct bo a tin g use patterns. T hus, storage type should be incorporated as an im p o rtan t e le m e n t in bo atin g m o d els. S econd, efforts to m odel (estim ate) bo atin g related travel and tra nsportation o f b o a ts from the o w n e r 's resid e n ce (origin) to boating d e stinations can be im proved th o u g h a tw o -ste p process w hich first allocates boats to storage locations, and from there to use (d estination) locations. Third, the long established, an d often verified " so u th -to -n o rth ” patterns o f recreational bo atin g and tra nsportation o f boats should be in co rp o rated into boating use m odels. Fourth, the a s su m p tio n o f d istance decay h o ld s well in the R E C S Y S system . D istance is a key factor in distrib u tin g bo a t days from origins to va rio u s (use) destinations. Finally, it is financially unrealistic to a s s u m e that w e will be able to regularly c o n d u c t large-scale 25 surveys to p ro v id e data to estim a te b o a tin g use at the local (county) level. It is necessary to d e v e lo p m o d e ls that can utilize s e co n d a ry d ata that are c o llected on a regular basis. R E C R E A T IO N A L TR A V EL T his section o f the literature r e v ie w will focus on c o n c ep tu a l m o d e ls o f recreation and tourist travel, and factors that have been identified as influ e n cin g the spatial m o v e m e n t o f recreational travel. T he p u rp o se is to p ro v id e a theoretical basis for the variables that are con sid e red for inclusion o f the m odel d e v e lo p e d in this study. Low e a n d M o ry a d a s (1 9 7 5 ) prese n t a con c ep tu a l fra m ew o rk o f the causes o f spatial m o v e m e n t. T h e four m a jo r factors in their f ra m e w o rk are: place and tim e utility, c o m p le m e n tarity , in te rv en in g o p p o rtu n itie s, and transferability. A lth o u g h the fram ew ork proposed by L o w e and M o ry a d a s is helpful in u n d e rs ta n d in g reaso n s o f m o v e m e n t, travel is far m o re c o m p le x than distrib u tio n o f p ro ducts. S o c io e c o n o m ic differences, cultural variations, diffe re n c es in a ttitudes a n d p e rc eptions, interpersonal c o m m u n ic a tio n , contextual differences, different d e c is io n -m a k in g rules (i.e., habitual vs. benefit m a x im iz in g d ecisions), variation in p u rp o se /m o tiv a tio n , and level o f in v o lv e m e n t all influence travel d e c isio n s (M u rd ie, 1965; W olpert, 1965; T ie d e m a n n and M ilstein. 1966; Ray, 1967; M a rb le a n d B o w lb y , 1968; Sea, 1969; G o lled g e , 1969, 1979; M ayo, 1973; H unt, 1975; K elly, 1980; S m ith, 1985; F e se n m a ier, 1990; U m a n d C ro m p to n , 1990; J o h n s o n and M e ss m e r, 1991; D a d g o s t e r a n d Isotalo, 1992). Since the late 1960s, rese a rc h e rs have a tte m p te d to form u la te m o d e ls de a lin g with various aspects o f the spatial structure o f recreational travel. A lth o u g h e m p h a s is is 26 placed on different c o m p o n e n ts o f the system , the basis o f m o st m o d els is an oriuinlinkaj’c -d estination system . M ariot (cited in M atley. 1976) p ro p o se d three different routes w hich m ay link a place o f p e rm a n e n t resid e n ce (origin) to a tourist c enter (d estin a tio n ) - an a ccess route, a return route, and a recreational route. C a m p b e ll (1 9 6 6 ) p ro p o se d a “ recreational and vacational travel m o d e l” o f different patterns o f m o v e m e n t aw ay from an urban center. C am pbell d istin g u ish e d b e tw e en v arious traveler gro u p s based on the relative im portance assigned the travel c o m p o n e n t (vacationist) a n d stay c o m p o n e n t (recreationist) o f their trips. L undgren (1 9 8 2 ) fo rm u la ted a m odel focusing on the spatial hierarchy o f tourism Hows. D estin a tio n s w ith different d egrees o f m utual travel attrac tio n s w ere m o d ele d and tourist Hows w ere classified b a sed on four different types o f destinations: m etropolitan destinations, peripheral u rban destinations, peripheral rural d e stinations, natural e n v iro n m e n t destinations. Several rese a rc h e rs have c o n c en tra te d on factors that im pact the v o lu m e o f tourist travel (M ercer, 1970; R ajotte, 1975; R uppert, 1978; G re e r and W all, 1979). T heir research indicates that the v o lu m e o f visits from origins to different destinatio ns decreases as the travel costs (tim e, m o n e y and effort) increases. T h e ir w ork also indicates that do m estic travel is typically seen in term s o f co n c en tric zo n e s su rro u n d in g an origin (city) defined o n the basis o f blo ck s o f available leisure tim e: a day-trip zone, a w e ekend zone, and a holiday or va c atio n zone. Y o keno (1974) an d M o isse c (1 976 and 1977) c o n c en tra te d on incorporating m o difications to h y p o th esiz ed c o n c en tric zones. M o is s e c ’s m odel (F igure 1) presents 27 Figure 1. M io s s e c 's M odel o f T o u rist S pace II III * *★+ * S p e c i a l A ttr a c ti o n s IV in s 2 8 different travel zone co n fig u ratio n s as effected by different factors and features. In Section I. the origin is s u rro u n d e d by four concentric tim e zones. V o lu m e o f visits to the outer z o n e s is less bec au se travel cost is higher. H o w e v er, in the real w orld, these theoretical “ regular c o n c entric z o n e s ” are subject to different types o f m odification. In Section II. the zones are e x te n d e d and com p re sse d reflecting positive or negative factors, such as clim ate, political boundary, o r historic links. S ector III o f the m odel show s that in reality a series o f (origin) cores exist giving rise to co n c u rre n t spatial d e m a n d s. Sector IV incorporates the im pact o f the “ attrac tiv e n e ss" o f d e stinations. T he n u m b e r o f visitations to the d e stination generally declines w ith distance, but the concentration o f v isitation m ay change due to p e rception o f the d e s tin a tio n 's supply ( op p o rtu n ity ) factors. Key Travel A nd Trip D istribution E lem en ts T hree key e le m e n ts or co n stru c ts - d ista n c e , destination c h a ra c te ristic s, and origin (p o p u latio n ) characteristics - are im portant in m o d e lin g and un d e rsta n d in g recreational travel and trip distribution. A n u m b e r o f a uthors and research studies have e x a m in ed the m e a s u re m e n t and im p act o f these e le m en ts on the spatial patterns o f recreational travel. D istance R ese a rc h has sh o w n repeatedly that distance is on e o f the m o st significant predictor variables for forecasting travel patterns b e tw een regions. D istance usually represents a m a jo r constraint on travel behavior. In m o st recreational travel studies, the general pattern is for the intensity o f travel flow s (n u m b e r o f visitations) to decline with greater dista n c es be tw e en the origin a n d destination. T his is the w e ll-k n o w n distance 29 decay f u n c tio n 5. T h e influ e n ce s o f distance on recreational travel vary. In review ing m any research projects. Sm ith (1 9 8 4 ) found distance ex p lain ed 3 0 % to 9 5 % variances in predicting n u m b e r o f trips from origins to destinations. P re v io u s recreational travel studies, have utilized four m ea su res o f distance. ‘"Physical d ista n c e ” is the spatial interval betw een tw o points. In m o st zone to zone recreational travel studies, d istance is the spatial interval b e tw e en po p u latio n centers and a lternative de stin a tio n s (C h e u n g , 1972; Freund and W ilson, 1974; D u rd e n and Siiberm an. 1975; K im . 1988). “ A m o u n t o f travel tim e ” , such as h o u rs o f driv in g tim e, is often used as a m ea su re o f dista n c e effect (Ellis. 1966; L entnek, V an D oren and Trail, 1969; 1'legg. 1975; Saunders. S enter and Jarvis. 1981). E c o n o m ic cost o f travel (cost per m ile) is also used as a m eth o d to m easure in fluences o f distance. “ E c o n o m ic d ista n c e ” represents a budgetary constrain to the a m o u n t and location o f travel/trips (Ellis, 1966; D urden and Siib e rm a n , 1975; W itt a n d W itt, 1990; M orley, 1994). “ Perceptual d ista n c e ” has been p roposed by a n u m b e r o f different au th o rs (C a d w a lla d e r, 1981; W a lm sle y & Jenkins. 1992). P erceptual distance is m e a s u re d based on p e o p le 's subjective p e rception o f travel distance. R e se a rc h e rs argue that p eople m a k e travel d ecisions based on their perceptions o f distance, not actual (physical, tim e, o r e c o n o m ic) distance. D estination C haracteristics T h e n u m b e r and quality o f attractions available at a d e stination is a m ajo r factor in fluencing travel de c isio n s (M c In to sh a n d G o e ld n e r, 1990). It is a ssu m e d that in d ividuals will allocate their rec re atio n travel in a m a n n e r that is c o nsistent w ith the ' T h e d i s t a n c e d e c a y f u n c t i o n in p r e v i o u s s t u d i e s h a s b e e n s p e c i f i e d in m a n y d if f e r e n t m a t h e m a t ic a l form s, s u c h as P areto f u n c t i o n ( Y = a * D _|i ), e x p o n e n t i a l f u n c t i o n ( Y - = a * e |!U), P a r e t o - e x p o n e n t i a l f u n c t io n ( Y = a * d l'*e 'D) ( M o r r il l an d Pitt, 1 9 6 7 ) . 10 perceived utility associated H ow ever, p revious w ith recreational alternative travel recreation studies have d e stinations not been (Luce. able to 1959). do c u m e n t con c lu siv ely the effect o f d e stin a tio n attractions on trip d ecisions and behavior. For e x a m p le, in 1974 F reund and W ils o n 's study o f T e x a s statew ide recreational travel, the coefficients for attributes o f attraction m ea su res ranged from 4.2 to -3.44. The negative sign o f attributes o f destination attractiveness raised interpretation difficulty because it d o es not confirm the d e stin a tio n choice theory. H o w e v er, the negative sign o f destination attractions m ay be e x p la in ed by m ulticollincarity in the data set use d in the T e x a s study. T h e o th er reason m ig h t be that attributes o f the d e stination choice are not directly relevant to the particular recreation activity u n d e r study. T h e a ttractiveness or “ d raw in g capacity" o f a destination and Ritchie. 1993). “ pulls in” visitors (H u A ttractiv en ess m ay include attributes, such as natural resources, accessibility, facilities, T im m e rm a n s, 1992). pro g ra m s, The pro b le m m ain te n a n c e , and is that is no there social use universal (Louviere m ea su rem e n t and of a ttractiveness. In so m e recreational travel studies, attractiveness o f d e stinations has been em pirically dete rm in e d , e stim ated as a p a ra m ete r in the m odel (C esario, 1974. 1975: B axter a n d E w ing, 1979; B axter, 1981; E w ing, 1983). N ielson, 1970) O th e r studies (W e n n e rg re n and have utilized a single supply variable as a m e a su re o f attractiveness. S o m e researchers have utilized a c o m b in a tio n o f supply variables to form ulate an attractiveness index (C h e u n g , 1972; Freund and W ilson, 1974; G earing. Sw art and Var. 1974; Bell, 1977; Sluyter. 1977; Sm ith, 1985; G o o d rich , 1978; K im , 1988). C o m p lic a te d statistical m eth o d s, such as factor analysis, have b e e n e m p lo y e d to d e v e lo p destination 31 attraction co n stru c ts that w e re then in co rporated into recreational travel m odel (V an D oren, 1967; Lin. P erterson an d R o g e rso n . 1988; L o v in g o o d an d M itchell. 1989; H aid er and E w in g . 1990; D a d g o s ta r and Isotalo, 1992; H sieh, O ’Leary. Louviere and T im m e rm a n s. 1992; M o rriso n an d C h a n g . 1993; K lenosky, G e n g le r and M ulvcy. 1993). N o t only is the quality and quantity o f attractions im portant, but also the spatial structure o f d e stination attractions. B o th c o m p e titio n and a g g lo m e ra tio n effects have b e e n re c o g n iz e d in p rev io u s studies (K im , 1988; K im a n d F e s e n m a ie r, 1990; H anson. 1980; F o th e rin g h a m , 1985). D e stin a tio n c o m p e titio n is a fu n ctio n o f the n u m b e r o f a ttractions w ith in a certain d ista n c e that c o m p e te for visits from a certain origin. The a g g lo m e ra tio n effect o c c u rs w h e n the “c o llective a ttrac tio n ” o f nearby destinations d raw m o re visits to individual d e stin a tio n s th an o th erw ise w o u ld occur. O rigin C haracteristics O rig in c h a racteristics in fluence the a m o u n t o f recreation c o n s u m p tio n (d em a n d ) from that origin. C hara cte ristic s o f the o r ig in ’s po p u latio n as w ell as local recreation op p o rtu n itie s are im p o rta n t factors influ e n cin g variation in the spatial interactions from an origin area. M any factors in fluence recreational travel pro p en sitie s o f origin p o p u lations: s o c io -e c o n o m ic a ttributes su ch as in co m e, fam ily size, o c c u p atio n , age. race, fam ily life cycle, m arital status, e d u c atio n , culture, g e n d e r (F e se n m a ie r, 1985; Fiske. 1974; C h u b b , 1968; D a d g ista r and Isotalo, 1992; Ja ckson, 1980; A nsari, 1971; Kelly. 1980; W itt and W itt, 1990; M o rle y , 1994); trip p u rp o se /u s e situ a tio n (Lentnek, V an D o re n and Trail, 1969; Ja ak so n , 1988; P erdue an d G ustke, 1985; F esenm aier, 1985; Station and B o n n e r, 1980; J u n e a n d Sm ith, 1987; R a tn e sh w a r a n d Schocker, 1991), 32 attitude (U m and C ro m p to n . 1990; T h o m p s o n and C o o p er. 1979; D ebb a g e . 1991). and level o f in v o lv e m e n t (Kelly. 1980; L o o m is and D itton. 1993). M e g n a c k (1971). C h u b b (1 9 6 8 ) an d D onnlly, V a sk e a n d G raefc. 1986) e x a m in e d th e re la tio n s h ip s be tw e en fleet characteristics and trave l/tra n sp o rta tio n patterns and found that boat size, boat type, and type o f storage in fluenced th ese patterns. The size o f an origin po p u latio n or the c o m b in a tio n o f p o p u latio n size a n d s o c io -e c o n o m ic attributes, are o ften incorporated as part o f gravity type recreational travel m odels. A P P R O A C H E S O F E S T IM A T IN G R E C R E A T I O N A L “ D E M A N D " T h e B ureau o f O u td o o r R ecreation (1 9 7 5 ) identified three different levels o f d e m a n d im p o rta n t in p la n n in g and m a n a g in g o u td o o r recreation: the " d e m a n d " for recreation in the c o n te x t o f b ro ad social and e c o n o m ic policy; the “ d e m a n d " for site specific recreation, an d the “ d e m a n d " for alternative types o f recreation, a p p ro a c h e s are used to e stim a te the “d e m a n d " (use) for f o u r prim ary o u td o o r recreation: (1) a p p lication o f s ta n d a rd s . (2) pro je c tio n s o f u s e . (3) structural m o d els o f d e m a n d and su p p ly , and (4) e x p re ssio n o f p e rc e iv e d w a n ts (B ureau o f O u td o o r R ecreation, 1975). T h e ap p lic atio n o f p o p u la tio n -b a s e d standards is the m o st p o p u la r tech n iq u e used by park, rec re atio n an d p la n n in g age n cie s for estim a tin g the “d e m a n d ” (and “ ne e d ") for recreation re so u rc e s and facilities. A lth o u g h straight forw ard, a n d easy to understand and apply, sta n d a rd s ignore m an y crucial factors affecting the d e m a n d (use) for recreation o p p o rtu n itie s su c h as the in d iv id u al diffe re n c es w h ic h m ay affect in d iv id u a l’s recreation 33 participation, different types o f users, and the spatial characteristics o f recreation “ supply" and “ dem a n d .". T he p ro jectio n o f use tec h n iq u e estim a tes d e m a n d (use) by e x tra p o la tin g from use counts, such as visitor days, recreation occasions, p e rm its/re g istra tio n s or so m e other m ea su res o f participation. T he m eth o d a s su m e s that all factors affecting the recreation de c isio n s o f in d iv id u als ch an g e at the sa m e rate as the po p u latio n (or w h a te v e r variable is used), and that the supply o f recreation op p o rtu n itie s c h a nges at the sa m e rate. Structural m o d e ls o f d e m a n d and supply require specification o f the variables a ssu m e d to be a ssociated w ith the “ d e m a n d " for and “ su p p ly " o f o u td o o r recreation. There arc lim itations asso c ia te d w ith this approach. O ne is that the a s su m p tio n o f causal relationship b e tw e e n recreation participation and the ind ep e n d e n t v a riables m ay be artificial. U n o b s e rv e d variables, highly correlated in d ep e n d e n t variables, lack o f strong variation in the in d ep e n d e n t v a riables m ay also bias the e stim a tes p ro d u ce d by structural m odels. E x p re ssio n o f p erceiv ed w ants elicited direct e x p re ssio n s o f recreational use collected th ro u g h surveys is a n o th e r “d e m a n d " estim a tio n m ethod. S u rveys are used to collect d ata on recreation p articipation, preferences, and factors that m ay affect recreation participation (e.g., incom e, e q u ip m e n t o w nership). Several pro b le m s associated with u sing surveys to directly e s tim a te a m o u n ts o f r ecreation participation are present. First, re sp o n d e n ts m ay incorrectly state their recreation (activity) preferences. Second, there m ay be d isc re p an c ies b e tw e e n w h a t p e o p le say they do and w h at they actually do, not due to deliberate falsification, but to inaccurate perceptions. Finally an d m o st im portantly. 34 sa m p lin g errors o c c u r due to insufficient sa m p le size, in co m p le te and unrepresentative sa m p lin g fram e, inadequate sa m p le selection procedures, and n o n -response biases. The sa m p lin g errors, especially those associated w ith insufficient sam ple size, b e c o m e m ore o b v io u s a n d pro b le m atic w h e n survey d ata arc used to directly e stim ate recreational use by different s e g m e n ts o f the p o p u latio n a n d /o r recreational use at the local level, or for individual sites. T h is is a pro b le m associated with statew ide boater surveys c o n d u c te d in M ichigan o v e r the last 30 years. R E C R E A TIO N A L TR A V E L M O D ELS M any e m pirical studies have a tte m p te d to m odel recreational travel. T h e most c o m m o n m o d els are d e stin a tio n choice m o d e ls , c lassification m o d e ls , trip generation m o d e ls , an d trip d istribution m o d e l s . D e stin a tio n choice m o d e ls predict individual c h o ic e s o f destin a tio n s and/or e stim ate the total n u m b e r o f visits to a p a rticu lar destination. m o d els are d e v e lo p e d at the d isag g reg ate level (i.e.. data M ost d e stin a tio n choice about individuals or households). R egression a n d discrete choice m o d els are the m o st c o m m o n a p p ro a c h e s for m o d elin g (individual) d e stination c h o ic e s6. S o m e c o n s id e r these m e th o d s to have a broader range o f exp la n a to ry variables, and as a result p ro d u c e m o re reliable e stim ates for individual travel b e h a v io r e specially w h e n the role o f individual d ecision m ak in g is apparently crucial (Spear, 1975; B e n -A k iv a and L erm an, 1985). Individual recreational D i s c r e t e c h o i c e p r o b a b ility m o d e l s i n c lu d e th e bin a ry c h o i c e m o d e l an d th e m u l t i n o m i n a l c h o i c e m o d e l . T h e m o d e l is d e v e l o p e d b a s e d o n th e c o n c e p t o f r a n d o m utility th e or y. 35 travel b e h a v io r is best analyzed by studying individuals and utilizing b e h a v io r/psychology theories. D iscrete choice m o d els have been successfully used to m odel recreation and tourism travel m o d e s and d e stination c h o ices (Burdy. 1971; Flegg, 1976; Sluyter. 1977; Lin, P eterson and R o g erso n . 1988; L ouviere and T im m e rm a n s , 1990; H sieh, O 'L ea ry . M o rriso n and C h a n g , 1993; M orley, 1994). H o w e v er, there are p ro b le m s asso c ia te d with ch o ic e m o d els in situations w h e re a large n u m b e r o f ch o ic e (d estination) alternatives are present (L erm an and Adler, 1975). Large n u m b ers o f alternative c h o ic e s/d e stin a tio n s m ak e theoretically desirable m odels, such as m u ltin o m in a l m o d els, c o m p u ta tio n a lly intractable. A n o th e r p roblem is that general tourism and rec reation survey d ata frequently lack sufficient in fo rm a tio n on the attributes o f alternative d e stin a tio n s as perceived by cho ic e m ak e rs (O u m an d L em ire, 1991 )7. C la ssific a tio n m o d els c a tegorize p o p u latio n s into su b g ro u p s, b ased on distinct characteristics, prefe re n c e s o r b e h a v io r patterns. W h e n m o d e lin g recreational use, distinct m o d els m ust be d e v e lo p e d for different types o f users w hen large varia n ce s are present a m o n g g ro u p s o f users. C lu s te r analysis and d isc rim in a n t analysis are the m o st c o m m o n m e th o d s for classification. C lu ste r analysis is a m u ltivariate tec h n iq u e used to group individuals o r objec ts 7 If into gro u p s by m in im iz in g the in tra-group va ria n ce w hile s u r v e y data d o n o t c o n t a i n th e c h o i c e m a k e r ’s s u b j e c t i v e e v a l u a t i o n o f the attributes o f a lter n a tiv e d e s t i n a t i o n s , in o r d e r to e s t i m a t e the standard m u l t i n o m i n a l c h o i c e m o d e l , o n e c a n o n l y in c lu d e o b j e c t i v e l y m e a s u r e d v a l u e s o f the attributes o f a d e s ti n a t i o n . S e v e r a l p r o b l e m s are a s s o c i a t e d with this issu e . First, t h e o b j e c t i v e l y m e a s u r e d attrib utes are n o t p r o p e r v a r ia b le s to u s e for d e s c r i b i n g o n e ’s d e s t i n a t i o n c h o i c e . S e c o n d , th e u se o f o b j e c t i v e l y m e a s u r e d attrib utes s u g g e s t s n o variation in the data f o r a g i v e n d e s t i n a t i o n a c r o s s i n d iv i d u a ls in th e d a ta se t. T hird, d u e t o la ck data on s u b j e c t i v e e v a l u a t i o n o f the d e st i n a t i o n a lt e r n a t iv e s , th e m o d e l c a n not e x p l a i n w h y p e o p l e g o to a s p e c i f i c d e s t i n a t i o n . It s i m p l y s u m m a r i z e s attributes o f th e p e o p l e w h o c h o s e to g o to e a c h d e s t i n a t i o n ( O u m and L e m ir e , 1 9 9 1 ) . m a x im iz in g the inter-group variance. C lu ste r analysis has been utilized in recreation and tourism studies to se g m e n t a m ark e t based on psy c h o g ra p h ic factors and product attributes (K ikuchi. 1986; D avis. A llen and C o senza, 1988; S h o e m ak e r. 1989; Ou, 1990; G ladw ell. 1990; L oker and Perdue. 1992; F odness and M ilner. 1992). D isc rim in a n t analysis is sim ilar to the cluster analysis e x c ep t the " structure" or groups arc identified (h y p o th e siz e d ) prior to the analysis. D isc rim in a n t analysis i n v o k es d eriving the linear c o m b in a tio n o f tw o (or m ore) in d ep e n d e n t variables that will d iscrim inate best b e tw e en the " a priori" defined groups. This is a chieved by the statistical decision rule o f m a x im iz in g the be tw e en -g ro u p variance relative to the w ithin-group variance. D isc rim in a n t analysis can also be used to identify variables that contribute m ost to the classification. It has both predictive and de scrip tiv e functions. M arketing researchers have applied d isc rim in a n t analysis to g roup the in d iv id u als (cu sto m ers) into defined m ark e t s e g m e n ts (John, 1971; L evine. 1975; Perreault, B e h rm a n a n d A rm strong. 1979; B uchanan, C h riste n sen a n d B urdge, 1981; G ra m a n n and B urdge. 1981; Harris. D river a nd Bergersen, 1984). Trip generation m o d els estim a te the v o lu m e s o f trips/visits generated by different origins. T hey c a n be used to identify factors that influ e n ce n u m b e r o f trips/visits from different origins. T im e series and structural regression m o d e ls are the m o st often used trip generation m odels. T im e series is used to identify a pattern o r trend that m ay be extended into the future, a ssu m in g that the pattern o f causal forces und e rly in g a trend rem ain c onstant o v e r tim e. It has been a pplied prim arily to recreation and to u rism activities for w h ic h historical series o f p a rticipation are available (C la w s o n and K netsch, 1966; BarOn. 37 1972. 1973: Cieurts and Ibrahim . 1975: Stynes and Spotts. 1980: Stynes and Szcodronski. 1980: W a n d e r and V an Erdcn. 1980; C a n a d ian G o v e rn m e n t O ffice o f T ourism . 1983). Structural regression m o d e ls relate recreation participation to a set o f independent variables, such as participant or population characteristics, m ea su res o f recreation op p o rtunities, and so m e interaction term s. A n u m b e r o f recreation and tourism studies have regression utilized m o d e ls to estim a te (and ana ly z e ) participation or visits (C icchetti. Fisher, a n d S m ith . 1973; Fiske, 1974; C h riste n sen and Y oesting, 1976; Y oung and Sm ith. 1979; A rcher. 1980; Fesenm aier, 1985). Trip destinations. d istribution m o d e ls allocate recreation participation from origins to They are also used to e x a m in e factors (e.g.. supply characteristics) that influence the d istrib u tio n o f trips/visits. G ravity m o d els are the principal type o f aggregate spatial interaction m o d e ls used to e x p la in /p re d ic t m o v e m e n t o v e r space, such as travel to w ork, m ig ratio n , in fo r m a tio n /c o m m o d ity Hows and recreational and tourism travel (H aynes, an d F o th e rin g h a m , 1984). G ravity m o d els p r e s u p p o s e a form ula - tourist Hows or travel d e m a n d (use) are m o d ele d as functions o f distance, cost, tourist incom e, recreation op p o rtu n itie s in the g eographic area, a n d /o r o th e r in d ep e n d e n t variables. O v e r the past thirty years, gravity type o f m o d els h a v e been used to d escribe and study statew ide travel patterns, origin (sites) specific travel patterns, d e stination (sites) specific travel patterns, and the spatial structure o f recreation opp o rtu n itie s (Ellis, 1966; V an D oren, 1967; W e n n e rg re n and N e lso n , 1970; R ugg, 1972; F reund a n d W ilson, 1974; Bell, 1977; P e rd u e a n d G u stk e , 1985; F e se n m a ie r and Lieber, 1987). 38 G ravity m o d e ls have several a d v a n ta g e s w hich co n trib u te to their w id e -sc a le use in de scrib in g and estim a tin g recreational travel d e m a n d , and allocating use to alternative destinations/sites. G ra v ity m o d e ls arc especially good in the co n te x t o f aggregated m ass m o v e m e n t. They are sim ple to c o m p u te , easy to und e rsta n d , and sufficiently flexible to a c c o m m o d a te c h a n g e s in any. or all. o f the v a riables involved. H o w e v er, rese a rc h e rs have identified a n u m b e r o f d isa d v a n tag e s associated with the gravity m o d e ls (T ie d c m a n n and M ilstein. 1966; L ow e and M o ry a d a s. 1975; Kwing. 1980; LIysal and C ro m p to n . 1985; C a la n to n c . B e n e d e tto and B ojanic. 1987). ( I ) T h e G ravity m odel as initially derived was based on N e w to n ia n physics and so m e argue that the m o d el is w e a k e r in theoretical basis to explain the h u m a n spatial interaction. (2) T here can be e stim a tio n biases caused by the pro b le m o f m ulticollinearity. (3) A lth o u g h b oundary areas are critical to a spatial m o d e l's perfo rm a n c e, origin and d e stin a tio n zo n e s in gravity m o d els are frequently arbitrarily d eterm ined. (4) It is often difficult to incorporate individual e x p la n a to ry variables. (5) G ravity m o d els norm ally a s su m e that the recreational sites (d estinations) have ade q u ate capacity to serve all th o se c o n s u m e r w h o desire to visit. (6) G ravity m odels are unable to a c co u n t for either m u ltip le p u rp o se or m u ltip le d e stination trips. (7) S o m e view gravity m o d els as too sim plistic, b ecause w ithout m od ific a tio n they d o n ’t account for c h a n g es in the num ber of trips to e x istin g de stin a tio n s caused by the d e v e lo p m en t/av a ila b ility o f n e w c o m p e tin g (substitute) destinations. In general “ gravity type m o d e ls ” a trip d istrib u tio n e le m en t is inco rp o rate d that allocates use/visitation from origins to destinations. For e x a m p le, in this study, several trip d istribution/allocation m o d e ls are utilized to distribute boats and boat days to regions 39 and counties. W c n n erg ren and N ie lse n (1970) d e v e lo p e d a probability m odel based on the general gravity type fo rm u la tio n to project m o v e m e n t o f recreational w atercraft and to estim a te visitation across d estinations. T h e ir sam p le w a s c o m p rise d o f recreational boaters living in eight cities (origin) that visited 22 w a te r based recreation sites in northern Utah. was A probability m odel utilizing distance an d a m o u n t o f w a te r at each site form u la ted to generate probabilities o f visitation from the different origins. Probability m o d els b ased on L u c e ’s choice a x io m (1959) an d H u f f s m odel (1962), took the fo llow ing form: - V d /.. ES/Vdi/' w here P,j = p robability o f a b o a te r from origin i selecting b o a tin g site j ; S, = surface area o f the bo a tin g site j; djj = d istance from the origin i to the bo a tin g site j; a = a p a ra m ete r w hich reflects the effect o f surface a re a o f the site on the n u m b er o f trips to the site; and p = a p a ra m ete r w h ic h reflects the effect o f d istance on the n u m b e r o f trips to the site. T h e exp e cte d n u m b e r o f trips by boaters from origin i to bo atin g site j is a product o f the total trips taken by b o aters from the origin i and the p robability o f boaters selecting the site (Pij), i.e., Tjj = Oi*Pij w here T h e key = e x p e c te d n u m b e r o f trips per se a so n from the origin i to b o a tin g site j; and O j = total n u m b e r o f trips per season taken by all b o a te r from the origin i . T,j issue in this a p p ro a c h is th e m e th o d for e stim a tin g exponential p a ra m ete rs for travel distance a n d lake area for e a ch o f the e ig h t origins. T h e a uthors used 40 an iterative p ro ce d u re that m in im iz e s the difference betw een actual and e xpected n u m b er o f trips*. T h e e x p o n e n ts for travel d istance ranged from 1.25 to 4 .00 and e x p o n e n ts for lake area from .25 to 1.00 T h e coefficients o f d e te rm in a tio n (r2) for the m odel ranged from 0.351 to 0 .9 9 9 for individual origins. Saunders. Senter. and Jarvis (1981) c o n d u c te d a study to forecast recreation d e m a n d in the U p p e r S ava n n a h R iver located in G eorgia. A gravity m odel w as used to allocate d e m a n d a m o n g alternative recreation sites. Travel tim es from po p u latio n centers to recreation sites w ere the prim ary d e m a n d allocation factors. A c c o rd in g to the authors, " d e m a n d ” w a s calculated for recreation sites at a (tim e) distance o f 0.5. 1.0. 2.0. 2.5 and greater than 2.5 hours from the population centers. D e m a n d w as allocated w ithin each travel tim e radius before p ro ce e d in g to the next travel tim e radius. W h e n m ore than one recreation sites c a p ab le o f supplying a particular activity occurred w ithin a single travel tim e radius, d e m a n d w a s equally allocated a m o n g the c o m p e tin g sites. T h e authors c o n c lu d e d that their allocation m odel is a relatively sim ple technique a n d re c o m m e n d e d that it can be used by state, local, and regional planners. T h e a uthors did not report the p e rfo rm a n c e o f the allocation m odel. D e stin a tio n travel patterns on V a n c o u v e r Island w ere e x a m in e d and m o d ele d by M urphy a n d K e lle r (1990). D a ta for the study w ere collected from 5.1 2 0 visitors to the Island. T h e study e stim ated a distance decay function, e x a m in e d p e rc e p tio n o f the destination area as an e x p la n a tio n o f the distortion b e tw e en reported and actual travel h T h e statistic al m e a s u r e is r . T h e larger the r: th e c l o s e r the p r e d i c t e d n u m b e r o f trips is to the actual o b s e r v e d n u m b e r o f trips. 41 behavior, and d e v e lo p e d a probability m atrix for m o d e lin g spatial travel patterns for island visitors. T he au th o rs p ro p o se d a m e th o d to m o d el the actual d istrib u tio n o f visitors which a g g regated survey collected d ata into a m atrix based on existing region travel behavior. T h e m atrix indicated h o w m any tourists entering each ga te w ay district (origins) traveled to o th er districts on the Island. T h e m atrix w a s then c o n v e rted into a probability matrix o f trip distribution by translating the actual visits into percentages. The “ matrix p e rcentage v a lu e s" are p robabilities that visitors arriving through different gatew ays will visit o th er districts. A lth o u g h d e scriptive in nature, the m atrix p rovides considerable in fo rm a tio n reg a rd in g the spatial d istribution o f travel patterns o f visitors to the Island. The a uthors co n c lu d e d that the probability m atrix c o n firm e d the distance relatio n sh ip s and p ro v id e d a useful tool for p lan n in g and m a rk e tin g strategies. decay C H A P T E R III T H E S Y S T E M OE M O D E I.S The system o f m o d els used to estim a te bo atin g use in M ic h ig a n c ounties by storage se g m e n ts is describ ed in this chapter. T he c h a p te r is div id ed into tw o m ajor sections. T he first section describ es the d ata sets that w e re used to e s tim a te the m odels including the m e th o d s p o p u latio n /sa m p le s. The e m p lo y e d se co n d to section collect the data, survey specifies the structure instrum ents, o f m o d els, and model c o m p o n e n ts, and processes o f co n stru c tin g the m odels. E m p h a sis is placed on the fu n ctio n /p u rp o se o f each m o d el and the linkages b e tw e en m odels. A m ore detailed description o f the p ro cess o f e s tim a tin g the m odels, in clu d in g variable specification, p a ra m ete r e stim ation, and m odel a s su m p tio n s is provided in the next ch a p te r along with estim ates from the m odels. DATA SOURCES Three m a jo r data sets w e re used to e stim ate and ev a lu a te m o d els c o m p risin g the system : (1) M ic h ig a n Secretary o f State Boat R egistrations, (2) 1994 M ichigan Great Lakes M arinas C e n su s, and (3) 1994 M ic h ig a n B oating S u rvey9. Boat R euistration Data In 1958 the State o f M ic h ig a n b e g a n requiring that "all m o to rb o a ts, sailboats, privately o w n e d ro w b o a ts o v e r 16 feet in length, rental o r c o m m e rc ia l canoes, and all 4 D i s t a n c e an d m o s t o f th e b o a t i n g o p p o r t u n i t y i n fo r m a tio n , su clt as the lake, sh o r e l in e , river, p u b lic a c c e s s s i t e s in c o u n t i e s , are from o t h e r s e c o n d a r y s o u r c e s . 42 43 rental and c o m m ercial v essels p ro p elled by any m ea n s and principally used in M ichigan, m ust be reg iste red " ( M D N R L a w E n fo rc e m e n t D ivision. 1995). Initially registration was intended as a p e rm a n en t id en tification and no renew al w a s required. C urrently, registrations are valid for only three years and then m u st be renew ed. T he c o m b in a tio n o f n e w reg istrations and re n e w a ls pro v id e s tim ely in fo rm a tio n on the type and size characteristics o f M ic h ig a n 's recreational bo atin g fleet. The O ffice o f S ecretary o f State u p d a te s and m a in ta in s the registration in form ation in a c o m p u te r system . It generates m o n th ly reports on the n u m b e r o f c urrently registered boats by county, type, length, a n d prim a ry use (e.g., recreation, c o m m e rc ial), as well as th e n u m b e r o f boats w ith expired registrations that had not been renew ed. B oats w ith ex p ired reg istrations are m ain ta in e d on the c o m p u te r system for two years a fter their registrations ex p ire , even th o u g h they ca n n o t be legally ope ra ted w ithout a current registration. T h e registration ap p lic atio n /re n ew al form collects in fo rm a tio n that could be useful for v arious p lanning a n d forecasting p u rp o se s including: location o f the o w n e rs ' residence; the age (date o f birth) o f the ow ner; d riv e r license n um ber; type, age and length o f the boat; type o f po w e r and fuel (e.g., diesel, gasoline); m an u fa ctu rer, and; inform ation relating to purch a se and d isposal o f boats. In form ation on the c o u n ty w h e re the boat is stored d u rin g the bo atin g se ason, type o f storage, a m o u n t o f use, o r the c o u n tie s wdiere it is used are not included as p a rt o f boat registration data. A co p y o f the W atercraft C ertificate A p plication F o rm is inclu d e d in A p p e n d ix A. 44 1994 M ic h ig a n G reat L akes M a rin a C e n su s In 1994. th e D e p a rtm e n t o f Park. R e c rea tio n , an d T o u ris m R e s o u rc e s at M ic h ig a n State U n iv e rs ity c o n d u c te d a study to identify, locate (m a p co o rd in a te s), and describ e all G reat L akes C oastal M a rin a s w ith ca p ac ity for 10 or m o re bo a ts that regularly use the G reat L akes (T a lh e lm et al. 1995). O n -site in terview s w ith m a rin a ope ra to rs w ere c o n d u c te d b e tw e e n July and O c to b e r 1994 to collect in fo rm a tio n ab o u t each m arina. An initial list o f 6 4 6 m arin as w a s d e v e lo p e d fro m a variety o f d iffe re n t lists including: m arin a perm its, bo atin g industry m e m b e rs h ip lists, and v arious nautical charts and m arine service directories. S o m e o f th e m arin as id en tified w ere found to be no longer in business a nd others had been m erg e d to form larger m arinas. A d d itio n a l m a rin a s w ere located th ro u g h w o r d -o f-m o u th a n d field ob se rv a tio n s. T h e fo llo w in g in fo rm a tio n w a s c o lle cte d a b out the 6 2 6 o p e ra tin g m arinas: (1) type o f o w n e r s h ip - public, c o m m e rc ia l, or private club, (2) n u m b e r and s i/ e o f seasonal rental, c o n d o m in iu m and tra n sie n t slips, (3) n u m b e r o f m o o rin g s and dry stack storage spaces, (4) o c c u p an c y rates for d iffe re n t size slips, m o o rin g s and dry stack spaces, and (5) m a rin a services provided. 1994 M ic h ig a n B o a tin g Survey In ad d itio n to the M a rin a Inventory, the D e p a rtm e n t o f Park, R ecreation, and T o u ris m R e s o u rc e s also c o n d u c te d a s ta te -w id e survey o f the o w n e rs o f recreational w atercraft w ith valid M ic h ig a n reg istra tio n s as o f July 1, 1 9 9 4 10. A s a m p le o f 6 .000 10 B o a t s w h o s e r e g is t r a t io n c e r t if i c a t e s w o u l d not e x p i r e b e f o r e th e e n d o f th e 1 9 9 4 b o a t i n g s e a s o n . The p r o c e d u r e o f e s t i m a t i n g b o a t s w ith v a l id r e g istr a tio n s w a s d i s c u s s e d in d e ta il in th e report o f 1 994 M i c h i g a n B o a t i n g S u r v e y ( S t y n e s et al., 1 9 9 5 ) . 45 registered boats, stratified by length (< 16 feet. 16-20 feet. 21-28 feet, and 2 9 + feet) and g eographic regions (ten bo a tin g regions) w as draw n from the S ecretary S ta te 's list o f registered b o a t s " . T h e sam ple w a s stratified to assure ade q u ate sa m p le s for different regions and size classes. A four page que stio n n a ire w a s m ailed to the 6 .0 0 0 registered boat o w n e rs at the end o f the 1994 b o a tin g se aso n s (O c to b e r 7th. 1994). A fo llo w -u p que stio n n a ire w a s sent by certified mail three w e e k s later to n o n -respondents. O f the 6 ,0 0 0 qu e stio n n a ires sent. 5.638 w ere delivered and 3,909 (6 9 % ) w ere returned. R e tu rn s included 2 ,980 boats that w ere used d u rin g the 1994 season, 743 boats that w ere not used d u rin g the season, and 186 un u sa b le qu e stio n n a ires (e.g., significantly incom plete, c o m p le te d for tw o boats). T h e qu e stio n n a ire co lle cte d in fo rm a tio n on: (1) characteristics o f boats, boat ow ners, and boat o w n e r h o u se h o ld s, (2) w h e re the boat w as stored du rin g the 1994 boating season in clu d in g cou n ty and type o f storage, e.g., m arina, second hom e. (3) seasonal and tem porary use o f m arin as and launching facilities, (4) 1994 boat days on the G reat L akes a n d inland lakes and rivers in different c o unties, and (5) sp e n d in g on e q u ip m e n t, repairs, insurance, storage, and fuel (A p p e n d ix B). A b r ie f su m m a ry o f the findings w'as p resented in C h a p te r two. F or a m o re detailed disc u ssio n o f the s u rv e y 's m e th o d s and findings see Stynes et al., 1995. 11 B o a t i n g r e g i o n s are a d o p te d fr om the G reat L a k e s m arket r e g i o n s u s e d in the 1 9 8 0 M i c h i g a n B o a t e r S u r v e y ( S t y n e s and S a f r o n o f f 1 9 8 2 ) . ( s e e F ig u re 2 ) Figure 2. 1994 Michigan Boating Survey Sampling Regions. Sam pling R egions (1 9 9 4 M ichigan B oating Survey) Southeastern M ichigan £;’■ Southw estern M ichigan T hum b R egion T W est Central M ichigan N ortheast M ichigan i ; N orthw est M ichigan I Straits I U P Lake Superior v U P Lake M ichigan V V y' y 47 TH E SY STEM OF M ODEES T here is no direct w ay to e stim ate county level boating use. or the n u m b e r o f boats stored by co u n ty from any e x istin g d ata source. N o age n cy or org an iz atio n collects inform ation that pro v id e s estim a tes o f boat use by region or county. B oat registration data p rovide no in form ation a b out storage o r use. T h e sam ple size for the 1994 M ichigan B oating Survey is too sm all to yield reliable e stim ates o f bo atin g use for m o st counties. H o w e v er, a system o f m o d els can be d e v e lo p e d from a c o m b in a tio n o f different data sources. T h e m o d els can be used to estim ate: (1) the n u m b e r o f registered boats kept in different types o f storage d u rin g the bo atin g season, (2) the n u m b e r and sizes o f boats kept in c ounties du rin g the bo a tin g season. (3) the n u m b e r o f boat days by boats kept in counties, and (4) ultim ately the location(s) w h e re these boat days take place. The different types o f m o d els c o m p risin g the system relate boat registration in form ation first to types o f storage and co u n tie s w here the boats are kept d u rin g the bo atin g season, and ultim ately to the c ounties w here the boats are used (Figure 3). The system o f m o d els utilizes and c o m b in e s a variety o f different types and sources o f “d e m a n d " and “ su p p ly " data including e stim ates p ro d u ce d by o ther m o d els in the system . In m o st instances the secondary d ata p rovide a m e a n s or basis for estim ation or allocation, rather than direct estim ates. For e x a m p le, d ata on bo a tin g facilities and a m o u n t o f recreation bo atin g w a te r (n u m b e r o f lakes) are used to geographically allocate (estim ates of) days o f boating by boats kept in (origin) c o u n tie s since no source o f in form ation is available on h o w boat days are distributed th ro u g h o u t the state. F o u r different types o f m o d e ls c o m p rise the system o f m o d e l s : (1) a classification m odel, (2) storage allocation m o d els, (3) a trip g e neration m o d el, and (4) trip distribution Figure 3. The System o f M odels. DATA BASES MODELS BOATING USE INFORMATION * 1994 Michigan Boating Survey Michigan Registered Boats * Boat Registration Data * 1994 Great Lakes Marina Census * Other Secondary Data Sources / Classification Model : 1 I ...s I I 1 Classify Boats into One o f The Storage Segments * Boat Storage T ype Classification Marina Second Waterfront Non- H om e Waterfront Home H ome (M) (WH) (SH) (NW) Storage Allocation Models * Regional Level Allocation * County Level Allocation Estimates o f The Num ber o f Boats Stored in Different Locations - Regions - Counties Trip Generation Model * Num ber o f Boat Days Generated in (Storage) Counties Estimates o f The Number o f Boat Days in Different Locations Trip Distribution Models - Regions - Counties * Distribute to Destination Zones * Distribute to Counties in a Zone 49 m odels. T h e s e q u en c e and linkages be tw e en m o d els is sh o w n in Figure 3. The figure also sh o w s the v arious types o f e s tim a te s p ro d u ce d by the m odels. C lassification M odel T h e function o f the c lassification m odel is to classify registered boats into different types o f storage w here the boats are kept d u rin g the b o a tin g season. T he four types o f storage are: (1) m arin as. (2) seasonal h om es. (3) p e rm a n en t w aterfront hom es, and (4) n o n -w a te rfro n t p e rm a n e n t h o m e (Figure 4). Figure 4. S torage T y p e C la ssific a tio n M odel A. M O D E L SP E C IF IC A T IO N * D e p e n d e n t V a r ia b le s : boat s t o r a g e ty p e (m a r in a , s e c o n d h o m e , w a te rfr o n t h o m e & n o n w a t c r fr o n t h o m e ) * I n d e p e n d e n t V a r i a b l e s : len g th o f boat, ty p e o f b oat, r e s i d e n c e l o c a t i o n o w n e r s h i p o f s e c o n d h o m e , in c o m e , and age. * M e t h o d : d i s c r im i n a n t a n a ly sis . B. A C C U R A C Y O F C L A SSIFIC A T IO N * C l a s s i f i c a t i o n M a trix * M a x i m u m c h a n c e criterion * P r o p o r tio n a l c h a n c e criterion C. A SS E S S M E N T O F C O N T R IB U T IO N S O F V A R IA B L E S T O C L A SSIF Y ST O R A G E TY PE SE G M E N T S * W ilk s’ Lambda * D i s c r im i n a n t l o a d i n g * Partial F -v a lu e 50 A d isc rim in a n t a nalysis is em p lo y e d to classify individual boats into the four “ types o f storage s e g m e n ts " on the basis o f in fo rm a tio n /v a ria b le s from the Boat R e g istra tio n D a ta and the 1994 M ic h ig a n B o a tin g Survey. T h e d isc rim in a n t analysis also identifies w h ic h of the ( in d e p e n d e n t) variables co n trib u te to the classification. D isc rim in a n t a nalysis includes both p redictive and de scrip tiv e functions and i n v o k e s three steps/stages: (1) de riv a tio n . (2) validation, and (3) interpretation. T h e “derivation stage" consists o f selecting v a riables and d e te rm in in g w h e th e r o r not a statistically significant function can be d e riv e d to separate groups. In the “validation stage" a classification m atrix is d e v e lo p e d to e v aluate the pred ic tiv e a c curacy o f the discrim inant function. T h e “interpretation sta g e " in v olves d e te rm in in g w hich in d ep e n d e n t variables co n trib u te the m o st to d isc rim in a te a m o n g the groups. T h e m o d el pro v id e s classification o f boats in d iffe re n t storage segm ents. S torage A llo ca tio n M o d e ls T h e p u rp o se o f the se co n d set o f m o d e ls is to allocate boats w ith in each storage se g m e n t to the c o u n tie s w h e re they are kept du rin g the bo atin g season. A two step a p p ro a c h is utilized to estim a te th e n u m b e r o f boats in different storage se g m e n ts kept in different counties. B o a ts are first a llocated to o n e o f the regions w h e re the boats are kept, and then to the co u n tie s w ithin e a c h region. A tw o step p ro ce ss is required be c au se even the 3 0 0 0 u seab le returns to the 1994 M ic h ig a n B oating Survey are not sufficient to generate reliable e stim a tes o f bo a ts stored in all 83 counties. Sm all sa m p le sizes for m any c ounties w o u ld have resulted in large s a m p lin g errors. H o w e v e r, an a d e q u a te n u m b e r o f surveys are a v ailable to generate rea so n a b ly reliable estim a tes o f boats stored in different 51 regions. T h e ten regions include six coastal regions, tw o inland regions and two U pper Peninsula regions. T he regions are m a p p e d in Figure 5. T he d istribution (p ercentage) o f boats w ithin different storage se g m e n ts and size classes is e stim a ted from the 1994 M ic h ig a n Boating Survey. T his distrib u tio n is used to e stim ate n u m b e r o f b o a ts stored in the regions. There are tw o reasons to incorporate boat size into the allocation schem e: (1) th e B oat R egistration D ata pro v id e s inform ation on the size o f boats registered in c o u nties, and (2) length o f boats is an im p o rta n t factor in estim a tin g the ave ra g e n u m b e r o f days boats are used. B oats are a llocated to storage c ounties w ithin reg io n s based on the c o u n ty 's share o f b o at-sto rag e o p p o rtu n itie s av a ilab le in the region. The follow ing form ula is used to allocate b o a ts to counties: E S, i g R e g io n r w h e re T (t|r) : total n u m b e r o f boats kept in county i. given region r; and Sj : availability o f boat storage opp o rtu n itie s in county i. D ifferent m ea su res o f a v a ilab le boat storage are used for each storage segment. B oats stored at m arinas in the G reat L akes coastal regions, are distributed to the counties based on the c o u n ty 's share o f m a rin a spaces in the region (Figure 6). B o a ts stored at m arinas in the inland regions, are a llocated to co u n tie s on the basis o f the n u m b e r o f inland lakes o v e r 50 a cres an d total acres o f inland lakes in the county (F igure 6), because there is no available e stim a te o f the n u m b e r o r capacity o f in la n d m arinas. A c re s o f large lakes is con sid e red a rea sonable in d ic a to r o f the n u m b e r o f inland m arin as spaces in the counties. B oats stored at seasonal h o m e s are distributed ac co rd in g to the estim ated Figure 5. M ichigan Boating Regions (I) Michigan Boating R egions (I) ( 1 9 9 4 M ic hi g an Boat ing S u r v ey ) I South hast ■\ Centra] hast !!;,] North hast North W est - Central W est - - South W est South Inland North Inland , South I iP Z i N oth C P Figure 6. Storage Allocation M odels for Boats Stored at M arinas and Second Homes. M ichigan R egistered B oats S tored a t M a rin as M ichigan R egistered B oats S tored a t Seasonal Hom es A llo c a te B o a ts to R e g io n s A llo c a te B o a ts to R e g io n s ❖ Group boats into three size classes 0 20*or less. 2 21'*28*. 3 20*ot larger) ❖ Estimate distribution by repons where the boats are kept for each size class ❖ Allocate boats to the regions where the boats are kept for each size class A llo c a te B o a ts to C o u n t) C oastal R egion s <• Allocalc boats to counties based on the countv's share of manna spaces in each region •> Group boats into three size classes ( I less than 16*. 2 16’-20‘. 1 2 s' or larger) ••• Estimate distribution by regions where the boats are kept for each size class ❖ Allocate boats to the repons where the boats are kept for each size class A llo c a t e B o a ts to C o u n ty •> Allocate boats to counties based on the county's share of " the number of second homes" in each repon Inland Regions ❖ Allocate boats to counties based on the county's share of •boat storage opportunity index" in each region B o a tin g I s e In fo r m a tio n * Number of boats stored at second homes in regions/counties by size classes B o a tin g I s e In fo r m a tio n ❖ Number of boats stored at mannas mregions, counties by size classes 54 n u m b e r o f seasonal h o m e s in each co u n ty (Figure 6). Finally, bo a ts stored at w aterfront and n o n w a te rfro n t p e rm a n e n t h o m e s are allocated to c ounties based on the n u m b e r o f boats o f different sizes registered in the county (Figure 7). C o u n ty o f registration is used because w ith few ex c ep tio n s the p e rm a n en t h o m e is the sam e as the registration address. T rip G e n e ra tio n and T rip D istribution M o d e ls T he final c o m p o n e n t o f the system o f m o d els consists o f a trip generation model a nd a set o f trip distribution m odels. The function o f these m o d els is to: (1) estim ate the n u m b e r o f bo a t days in (destination) co u n tie s by boats in d iffe re n t types o f storage, and (2) m o d el trip patterns from origin c ounties (boat storage locations) to destination c ounties (boat use location). T he trip generation m o d els e stim a te the n u m b e r o f boat days generated by boats stored in ea ch cou n ty by storage segm ents. T h e trip distribution m o d els distribute these boat days to different (destination) counties. T otal days by b o a ts in e a c h storage se gm ent is c o m p u te d by m u ltip ly in g the average n u m b e r o f boat days w ith in different size classes and storage s e g m e n ts tim es the n u m b e r o f boats kept in each county. T he average n u m b e r o f bo a t days for different size c lasses and storage se g m e n ts is estim a ted from the 1994 M ic h ig a n B oating Survey data. E stim ates o f total days g e n e ra te d in each county are the prim a ry input to the trip d istrib u tio n m odel. D ifferent ap p ro a c h e s are em p lo y e d to distribute days by b o a ts in different storage se g m e n ts to (destination) counties. T h e m o d els to distribute days by boats stored at second h o m e s and p e rm a n e n t w a terfront h o m es are relatively straightforw ard. Results o f 1994 M ic h ig a n B o a tin g Survey s h o w that alm ost all o f these boat days (9 7 % for boats kept at second h o m e s and 9 5 % for boats stores at p e rm a n e n t w ate rfro n t h o m e s ) are Figure 7. Storage A llocation M odels for Boats Stored at W aterfront Hom es and Nonvvaterfront Homes. M ichigan R eg istered B oats S tored at W a te rfro n t Hom es M ic h ig a n R e g i s t e r e d B o a ts S to r e d a t N o n w a tc r fr o n t H o m es A llo c a te B o a ts to R e g io n s A llo c a te B o a ts to R e g io n s ❖ Group boats into three size classes (1 16 ‘ or less. 2 l 6 ‘- 2 0 \ 3 21' or larger) ❖ Estimate distribution by regions where the boats arc kept for each size class ♦!*Allocate boats to the regions where the boats are kept for each size class *>Group boats into two size classes (1 less than 16 feet. 2 16' or larger) ♦> Estimate distribution by regions where the boats are kept for each size class ❖ Allocate boats lo the regions where the boats are kept for each size class A llo c a te B o a ts to C o u n ty A llo c a te B o a ts to C o u n ty *> Allocate boats to counties based on the county's share of" the number of registered boats in that size class" within each region •> Allocate boats to counties based on the countv’s share of" the number of registered boats in that size class" within each region B o a tin g I ’se In fo r m a tio n B o a tin g C sc I n fo r m a tio n ❖ Number of boats stored at waterfront homes in rcgions counties by size classes * Number of boats stored at nonwatcrfront homes in regions-counties by size classes 5f> inside the eou n ty w h e re they are stored du rin g the bo atin g season. Thus, the m odel distrib u tes all boat days by boats in these tw o storage s e g m e n ts to the co u n tie s w here they are kept d u rin g the b o a tin g season. Boat d a y s by boats kept at m arin as located in inland c o u n tie s are all allocated to the eo u n ty w h e re the m arin a is located. G iven that it is generally in co nvenient and ex p e n siv e to m o v e and transport large-sized m a rin a b o a ts to o th e r counties, it is a ssum ed that alm ost all bo a t days g en erated by b o a ts stored at inland m arin as stay within the co u n ty o f storage. A m o re c o m p le x tw o -ste p trip d istribution m odel is required for boats stored at m arin as in G reat L akes coastal counties, and boats stored at p e rm a n e n t n o n-w aterfront hom es. Boats stored at n o n -w a te rfro n t h o m e s are frequently trailered to different counties w here they are used. B oats stored at G reat L akes m a rin a s arc often op e ra ted in adjacent co u n tie s a n d /o r a lo n g po p u lar G re a t Lakes cru isin g routes. Inform ation (e.g., trip origins) on boats that rent transient slips indicates that larger craft stored on the G reat Lakes often travel c o n sid e ra b le d ista n c es on G reat L akes cruises (S te w a rt an d Stynes, 1990). T h e tw o step a p p ro a c h first d istributes boat d ay s to c o n c entric (destination) /.ones a ro u n d each (storage) county an d then to the c o u n tie s w ithin these zones. A n estim ated d istrib u tio n o f boat days w ith in different d e stin a tio n z o n e s is used to distribute days o f b o a tin g to e a c h d e stin a tio n zone. T h e e s tim a tes are d e riv e d from the 1994 M ic h ig a n B oating Survey. B oat days are d istributed to c o u n tie s w ith in a d e stination z o n e based on the c o u n ty ’s share o f b o a tin g use opp o rtu n itie s a v ailable in the zone. T h e follow ing form ula is used to distribute boat days to c o u n tie s w ithin d e stin a tio n zones: 57 I9 (,u > ~ U , z u, i f D e s tin a tio n z o n e / w h e re D (li/) : n u m b e r o f boat days in destination cou n ty i. given destination / o n e z. and U, : availability o f b o atin g -u se op p o rtu n itie s in county i. P re vious b o a tin g studies indicate that the p ropensity to travel and boating use patterns d iffer a m o n g b o a ts in different storage segm ents. Based on these findings different (concentric) d e stin a tio n zones and different m ea su res o f c o u n ty boating use op p o rtu n itie s are form ulated for boats kept at coastal m arin as and those stored at n o n w a tc rfro n t p e rm a n en t h o m es (Figures 8). T h re e d e stination z o n e s arc e sta blished for bo a ts stored at coastal m arinas -- (1) within county . (2) nearby counties . and (3) more distant counties. R esults from the 1994 M ic h ig a n B oating S urvey sh o w e d the tw o prim ary uses o f boats kept at G reat Fakes m arinas are pleasure b o a tin g in the cou n ty w h e re the m arin a is located or adjacent c ounties, or “ c ruising” to m o re distant counties. M iles o f G re a t Fake shoreline are used to distribute boat days to nearby counties. A cruising a ttrac tio n /o p p o rtu n ity index that c o m b in e s the n u m b e r o f transient slips in co u n tie s and the n u m b e r o f nights these transient slips are rented is used to distribute boat days to the c ounties w ithin " m o re distant c o u n tie s " destination zone. T h e m odel that distributes days by boats stored at n o n w a te rfro n t p e rm a n en t hom es utilizes 30 m in u te/m ile d riv in g zones. It is b ased on the a s su m p tio n that: (1) boating use decreases as trailering d istance from storage county increases, and (2) propensity to Figure 8. Trip G eneration and D istribution M odels for Boats Stored at M arinas in Coastal C ounties and N onw aterfront Homes. B oats S to red a t M a rin a s in th e C oastal C ounties by Size C lasses B oats S tored a t N o n w aterfro n t Hom es by Size C lasses G e n e r a te B o a t D a y s Generate Boat Days •> E stim ate average b oat d ays for b oats in ea ch s iz e cla ss ❖ E stim ate average boat d ays for boats in each siz e cla ss. •> Estim ate total boat d ays generated by the b oats kept in the cou n ties ❖ E stim ate total boat d avs generated b \ the b oats kept in the cou n ties -----------------------------------------------------D is tr ib u te B o a t D a y s to D e stin a tio n Z o n es D is tr ib u te B o a t D a y s to D e s tin a tio n Z o n e s ❖ Komi 13 ” 3 0 m in u tes d riving d ista n ce” destin ation zo n es for each county •> Form three d estin ation zo n es - "w ithin cou n ty zo n e ” , "nearby co u n ties z o n e ” and "m ore d istant z o n e ” for each cou n ty ❖ E stim ate d istrib u tion o f b oat d ays w ithin d estin ation zo n es b y (storage) region s. ❖ D istribute b oat d avs to d estin ation zon es cou n ts in the zon e D is tr ib u te B o a t D a y s to C o u n tie s W ith in C ou n ty Z on e •> D istrib u te boat d ays to the (storage) county. • E stim ate distribution o f boat d ays w ith in d estin a tio n zo n es by istorage) regions ■ D istribute boat davs to destination zones N earb y C o u n tie s Zone •> D istribute boat days to the co u n ties based on the c o u n ty 's share o f "Great F a k es shoreline” in that zon e. M ore D istant Z on e ❖ D istrib u te boat days to the co u n ties based on the “cru isin g op portun ity in d ex ” . D is tr ib u te B o a t D a y s to C o u n tie s ❖ D istribute B oat d ays to the cou n ties based on the co u n ty 's share o f "boating op portun ities index" in that zon e 3T B o a tin g E s c In fo r m a tio n B o a tin g E s c I n fo r m a tio n ❖ N um b er o f boat d ays used in destin ation reg io n s/co u n ties v N um ber o f boat d ays used in destination region s/cou n ties •> Travel flow s from origin s (storage location ) to d estin ation s •b 1 tavel Hows from orig in s (sto ia g e location ) to destin ation s 59 travel/trailer is co n sta n t w ithin zones. A boating o p p o rtunity index, based on w eighted m ea su res o f b o a tin g resources an d facilities in the county, is the basis for distributing boat days to the c o u n tie s w ithin the (30 m inute) d e stination z o n e s (Figure 8). C H A P T E R IV M O D E L S P E C I F IC A T I O N S A N D RE SI JETS T his c h a p te r presents e stim a tes o f bo a tin g use pro d u ced by the system o f m odels. T he m o d els are p resented in three m a jo r sections: (1) boat storage classification. (2) boats kept in the counties, and (3) bo a t days in the counties. Each section reports the results from one or m o re individual m odels. T he p resentation o f the individual m o d e ls includes: (1) m odel specification, (2) a ssu m p tio n s of m o d el. (3) results of m odel, and (4) eva lu a tio n o f m odel. A s u m m a ry o f the results and e v a luation o f all m o d els are provided at the end o f the section. B O A T S T O R A G E C L A S S IF IC A T IO N D isc rim in a n t analysis is used to classify boats into one o f four storage segm ents: (1) m arinas. (2) second h om es, (3) w a te rfro n t h o m es, and (4) n o n w a te rfro n t hom es. The results o f the disc rim in a n t analysis are p resented in three stages: (1) m odel specification. (2) results a n d m o d el e valuation, and (3) interpretation. M odel S p e cification T h e m o d e l specification stage identifies the d e p e n d e n t an d in d e p e n d e n t variables. Storage se g m e n t (m arina, se co n d hom e, w aterfront h o m e, and n o n w a te rfro n t h o m e) is used as the d e p e n d e n t variable in the analysis. Boats that w ere active in 1994 w hose ow ners returned 1994 M ichigan B oating Survey are a ssigned to o n e o f the four se g m e n ts 60 61 based on “types o f storage f a c ilitie s " 12 (m a rin a , second h o m e , and p e rm a n e n t residence) and “ type o f s to ra g e lo c a t io n " 13 (w a te rfro n t location vs. n o n -w a te rfro n t location). Boats kept at “o th e r" types o f storage facilities, and boats (cases) w ith m is s in g storage in fo rm a tio n are e x c lu d e d from the analysis. T h e resu ltin g “ storage s e g m e n ts " are: (1) m arinas, (2) se co n d hom es, (3) p e rm a n en t w a te rfro n t h o m e s, (4) p e rm anent n o n -w a te rfro n t h o m e s (T able 6). T h e four storage s e g m e n ts are m u tu a lly ex c lu siv e and exhaustive. T he c h a racteristics o f boats and boat o w n e rs that are used to predict boat storage s e g m e n ts include (1) length o f boat, (2) type o f b o a t 14, (3) location o f the o w n e rs ' r e s id e n c e 15, (4) o w n e rs h ip o f a second ho m e, (5) age o f boat o w n e rs and (6) incom e. T y p e and length o f boat, and o w n e r ’s add re ss are part o f the bo a t registration data collected by the O ffice o f S ecretary o f State. T h e c h a racteristics o f the boats and boat o w n e rs vary c o n sid e rab ly betw een storage segm ents. M o st boats stored at m a rin a s are large, a v e ra g in g 31 feet in length. M o s t (9 5 % ) o f the boats in this s e g m e n t are inboards o r sailboats. B oats stored at n o n w a te rfro n t h o m e s tend to be sm a lle r craft w ith an ave ra g e length o f 17 feet. 12 T h e 1994 M ic h ig a n B oating Survey c o lle cte d i n f o r m a t io n on five types of seasonal stora ge: ( 1 ) p e r m a n e n t r e s id e n c e , ( 2 ) a c o t t a g e or s e c o n d h o m e , ( 3 ) a r e n t e d s p a c e in a p u b l i c m a r in a , ( 4 ) a ren ted s p a c e in a c o m m e r c i a l m ar in a, ( 5 ) an o w n e d s p a c e in m ar in a o r d o c k a m i n i u m or ( 6 ) o th e r st o r a g e t y p e ( e . g . , fr ie n d s h o m e , c o m m e r c i a l rental fa c ility ). R e n t e d s p a c e s at p u b l i c , p r iv a te and c o m m e r c i a l m a r in a s, an d c o n d o m i n i u m o r d o c k a m i n i u m s p a c e s are c o m b i n e d into a m arin a s to r a g e c a t e g o r y . 13 T h e 1 9 9 4 M i c h i g a n B o a t i n g S u r v e y c o l l e c t e d i n f o r m a t io n o n the l o c a t i o n o f s e a s o n a l stor a ge: ( 1 ) at a w a te rfr o n t s it e w ith a c c e s s to the G r e a t L a k e s , ( 2 ) at an inland la k e w a te rfr on t site , ( 3 ) at a river or str ea m w a te r fr o n t site o r ( 4 ) n o n - w a t e r f r o n t site. T h e three w a te r fr o n t s i t e s are c o m b i n e d into a w ate rfr on t l o c a t i o n c a t e g o r y . M T y p e s o f b o a t are r e - g r o u p e d into i n b o a r d s, o u t b o a r d s , s a i l b o a t s , p o n t o o n b o a t s an d c a n o e s . " L o c a t i o n s o f r e s i d e n c e s are g r o u p e d into s e v e n r e g io n s : s o u t h - c o a s t r e g i o n , c e n t r a l - c o a s t r e g io n , n o r th - c o a s t r e g i o n . U p p e r P e n in s u la and o u t -o f -s ta t e . Fable 6. 1994 M ich ig an B o a tin g S urvey S am p le S izes for D iffe ren t S to rag e S egm ents. SAM PLE B o a t S t o r a g e S e g m e n ts" N u m b e r o f B oats PO P U L A T IO N EST IM A T E P e r ce n t N u m ber o f B oats P ercent M arina 984 35.7 59,077 1 1.6 Second Hom e 574 20.8 1 3 4,072 2 6 .3 W a te rfr o n t H o m e 593 21.5 1 19,187 2 3 .4 N onw aterfront H o m e 603 21 .9 196,686 38.6 2,754 100 50 9 ,0 2 2 100 T o ta l a. C a s e s w ith m i s s i n g s t o r a g e fa c ility or s to r a g e l o c a t i o n i n f o r m a t io n are e x c l u d e d from th e a n a ly s is . 63 T w o thirds (6 8 % ) o f these b o a ts are outb o ard m o to r boats. O w n e rs o f boats kept at s econd h o m es are the oldest w ith an average age o f 59. A p p r o x im a te ly 8 8 % o f th e m own a second h o m e, and 3 2 % are out-of-state residents. T h e o w n e rs o f boats stored at n o n w a te rfro n t h o m e s are the yo u n g e st av e ra g in g 51 years o f age. O n ly 13% o w n a second ho m e, and ab o u t h a lf o f them reside in southern M ic h ig a n (T a b le 7). Results and M odel E valuation O verall, 6 9 % o f the boats are correctly classified (T a b le 8). T h e d iscrim inant analysis correctly classifies 8 4 % o f bo a ts stored at second h o m e s , 7 6 % o f boats stored at m arinas, 6 9 % o f boats stored at n o n w a te rfro n t h o m es, but only 4 4 % o f boats stored at w aterfront hom es. T h e classification m atrix (T able 8) sh o w s correct cla ssifica tio n s in the diagonal cells and incorrect c lassifications in the off-diagonal cells. T a b le 9 profiles the e a se s that arc correctly and incorrectly classified for each storage segm ent. T h e m odel incorrectly classifies 10% o f m arin a b o a ts into the second h o m e s e g m e n t, and w aterfront h o m e segm ent. 11% into the T h e m is-classified m arin a boats are sm a lle r and m o re are o u tb o ard s o r p o n to o n boats. T h e ow n e rs o f the m is-classified bo a ts are on a v e ra g e older, they are m o re likely to o w n a se c o n d hom e, and h a v e a low er ave ra g e in c o m e s c o m p a red to the o w n e rs o f correctly c la ssified boats. T h e m odel incorrectly classifies 7% o f second h o m e boats into the m arina segm ent, and 6 % into the n o n w a te rfro n t h o m e segm ent. T h o s e m is-classified second h o m e boats are larger a n d /o r m o re are sailboats. T h e ir o w n e rs are younger, less likely to o w n a second h o m e, a n d /o r h a v e a low er average incom es c o m p a red to o th er group 64 T able 7. C h a racteristics o i'B o a t and B oat O w n e r by Storage Categories. STO RAGE SEG M ENTS ALL BOATS W ate rfr on t N onw aterfront M a rin a Second H om e H om e H om e Mean Mean Mean Mean Mean 30.77 20.28 21.76 16.66 23.59 60% 3% 35% 2% 0% 42% 2 8% 7% 17% 5% 41% 26% 8% 21% 3% 22% 68% 1% 1% 6% 44% 27% 16% 9% 26% U p p e r P e n in s u la 10% O u t o f State 10% 10% 7% 5% 36% 3% 7% 32% 17% 7% 24% N o r t h In land 16% 14% 15% 31% 4% 12% 13% 0% 13% 15% 14% 37% 10% 11% 0% 12% 39% 38% 15% 51% 24% 21% 12% 42% 45% 56% 15% 46% A g e o f O w n e r (y e a r s ) 52.75 59 .2 0 57.25 51.16 54.72 O w n a Second H ome 21% 88% 16% 13% 33% B o at L e n g t h ( f e e t ) B o at T y p e In board B o a t O utboard B oat Sail B oa t P ontoon Canoe 3% R e s i d e n c e L o c a tio n S o u th C o a s t C entral C o a s t N o r t h C o a s ta l S o u th In land 14% 1 1% 15% 32% 7% 10% 10" 0 In c o m e Under $ 2 0 ,0 0 0 $2 0 ,0 0 0 -$ 5 9 ,0 0 0 O ver $ 6 0 ,0 0 0 6% 33% 65 Table 8. C lassification M atrix for C o m p a rin g N u m b e r o f B oats in S torage S egm ents Predicted by the M o d e l w ith 1994 M ichigan B oating Survey. D ISC R IM IN A N T A N A L Y SIS P r e d i c te d S e g m e n t M e m b e r s Second H om e M a rin a W a te rfr o n t N onw aterfront H om e H om e I'otal 1994 S U R V E Y R E S U L T S 748 M arin a 102 10% 112 22 1% 2% (pet.) 76 % * 42 481 18 (pet.) 7% 84 % * 3% (pel) 18% Second H ome 107 W ate rfr on t H o m e Nom vaterfront H o m e (pet.) M o d e l P r e d i c t e d (to ta l) 10 2% 907 83 14% 71 * 143 106 416 69% * 737 496 69.1 7 % M a x i m u m c h a n c e c riter io n 35.70% P r o p o r t io n a l c h a n c e c riter io n 2 6 .49% 593 24% 18% Percent o f c a se s correctly c la ssified 574 6% 12% SUMMARY STATISTICS * p e r c e n t c o r r e c tl y c l a s s i f i e d in b o ld . 260 44 % 33 984 614 603 2.7 5 4 Table 9. Profiles o f Boats (and Ow ners) Correctly and Incorrectly Classified into Storage Segments. B O A T STORAGE SEG M ENTS Marina C orrectly Incorrectly C la ssified Boat Length (feet) C la ssified Second H om e S u rv ey O b served C orrectly Incorrectly C la ssified C la ssified Waterfront H om e Survey C orrectly Incorrectly O b served C la ssified 33.03 2 3 .3 4 3 0 .7 6 7 19.35 24.6 2 0 .2 8 2 1.25 57% 70% 60% 44 % 32% 42 % 0% 11 % 3% 28% 32% 43% 9% 35% 4% 23% Pontoon 0% 9% 2% 18% Canoe 0% 0% 0% 5% C la ssified Nonwaterfront Home Survey O bserved 22.1 2 1 .7 5 8 53% 30°o 28% 0% 46% 7% 2% 10% 17% 3% C orrectly Incorrectly C la ssified C la ssified Survey O bserved 15.43 19.27 16.66 41% 4% 64% 22% 26% 89% 23% 68% 13% 8% 0% 4% 1% 43 % 5% 21% 0% 4% 1% 5% 1% 5% 3% 7% 4% 6% Boat Type Inboard Boat Outboard Boat Sail Boat Residence Location South Coast 16% 17% 16% 11% 4% 10% 16% 18% 17% 14% 13% 13% Central Coast 15% 10% 14% 7% 12% 7% 3% 9% 7% 15% 12% 15% North Coastal 16% 14% 15% 5% 9% 5% 23% 25% 24% 14% 14% 14% South Inland 35% 21% 31% 34% 4 2% 36% 29% 24% 26% 37% 34% 37% North Inland 3% 6% 4% 3% 7% 3% 16% 11% 12% 11% 12% 10% Upper Peninsula 8% 14% 10% 5% 14% 7% 13% 12% 13% 9% 15% 11% Out o f State 7% 19% 10% 36% 12% 32% 0% 0% 0% 0% 0% 0% Income Under $ 2 0 ,0 0 0 5% 11% 6% 11% 16% 12% 17% 14% 15% 22% 20% 21% $20,000-559,999 40% 46 % 42% 38% 41% 39% 56% 47 % 51% 57% 51% 56% Over $ 60,000 47% 35% 45 % 39% 28% 38% 18% 29% 24% 12% 20% 15% 5 1.84 5 5 .5 2 52.751 6 0 .5 4 52 .52 5 9 .1 9 8 58.67 5 6.35 57.251 50 .39 5 3 .1 9 51.16 15% 42% 21% 98% 31% 88% 0% 30% 16% 1% 39% 13% A ge o f Owners (years) Own a Second Home 67 m e m b e rs. T he m odel incorrectly classifies 12% o f nonvvatcrfront h o m e b o a ts into the second h o m e se g m e n t and 18% into w a te rfro n t h o m e segm ent. T he m is-classified n o n w a tc rfro n t h o m e boats are larger a n d /o r are m ore likely to be inboards. T heir ow ners are older, m ore likely to o w n a second hom e, a n d /o r have a h ig h e r a v e rage incom es c o m p a re d to o th er gro u p m e m b e rs. O v e r 5 0 % o f bo a ts stored at w a terfront h o m es are incorrectly classified into other storage segm ents, flic d isc rim in a n t analysis can not a c curately classify boats kept at p e rm a n e n t w a terfront h o m e s b ased on the ind ep e n d e n t v a riables that w ere used in this analysis. A m a jo r reason for the inability to correctly classify w ate rfro n t h o m e boats is that the b o a ts and their o w n e rs have sim ilar characteristics w ith boats in o ther storage segm ents. B oats stored at w aterfront h o m e s are sim ilar in types a n d size to boats stored at second h o m es. T here are few diffe re n c es b e tw een boats stored at p e rm a n e n t w aterfront h o m e s a n d n o n w a te rfro n t h om es. Their o w n e rs have sim ila r in c o m e s and p ropensity for second h o m e o w nership. T h e re is no universal sta n d a rd for ac ce p tin g or rejecting a d isc rim in a n t function based on p redictive ac cu ra cy o f g ro u p classification. Two different criterion, the maximum chance criterion an d the proportion al chance criterion , suggested by flair. A n d e rso n and T a th a m (1987) are used to e v aluate predictive accuracy. The maximum chance criterion requires that the p ercent o f correct c lassification o f the discrim inant analysis is h igher than the p ercent o f g ro u p m e m b e rs in the largest g r o u p 16. In this study. W e c o u l d arbitrarily a s s ig n all s u b j e c t s to th e largest g r o u p a n d a c h i e v e c er ta in p e r c e n t o f a c c u r a c y , w h i c h is the s a m e a s p e r c e n t o f total s u b j e c t s in the largest g r o u p , w ith o u t th e a id o f d isc r im in a n t f u n c t i o n s . 'Therefore, i f the p e r c e n t o f c orr ec t c la s s i f i c a t i o n for the d is c r im i n a n t f u n c t i o n s d o not e x c e e d “ the p e r c e n t ” o f s u b j e c t s in the largest g r o u p , it ha s not h e l p e d us p r e d ict, b a s e d o n this criter io n . 68 the p ercent o f c o rrect classification o f the d isc rim in a n t analysis is 69% . ab o u t do u b le the m a x im u m c h a n c e criterion. 3 6 % (T a b le 8). A c c o rd in g to this criterion, the discrim inant analysis cla ssifies b o a ts into the storage se g m e n ts rea so n a b ly well. The p ro p o rtio n a l chance criterion takes into a c co u n t the ability o f discrim inant functions to classify correctly subje c ts/o b je c ts into sm a lle r size gro u p s as well as the largest group. The proportional chance criterion requires the percent o f correct classification from a disc rim in a n t analysis to be h igher than C proportional• T h e form ula for this criteria is C proportional = £ p i2 . w h e re p; = the p roportion o f subjects in g ro u p i . In this study, the percent o f c orrect classification (6 9 % ) is m u c h h igher than the proportion al chance criterion (2 6 % ) (T able 8). B ased on this criterion, the d iscrim inant analysis a d e q u a te ly predicts boats in different storage segm ents. Interpretation D is c rim in a n t loadings. W ilk s ' lam bda, and partial F are used to e v aluate the relative im p o rta n c e o f in d ependent v a riables to d isc rim in a te a m o n g the groups. The d isc rim in a n t lo a d in g , o r structure c o rrelation, m ea su res the sim p le linear correlation b e tw een in d e p e n d e n t variables and d isc rim in a n t fu n c tio n s 17 (T able 10). T h e greater the a bsolute v a lu e o f a d isc rim in a n t loading, the stronger the rela tio n sh ip b e tw e en that variable an d th e d isc rim in a n t function. T h e sign o f a d isc rim in a n t lo ad in g indicates the positive o r n e g a tiv e correlation b e tw e e n the in d ep e n d e n t variables and the discrim inant 17 T h r e e d i s c r im i n a n t f u n c t i o n s g e n e r a t e d b y d is c r im in a n t a n a l y s i s are u s e d to c l a s s i f y b o a ts into sto r a g e s e g m e n t s . T h e d isc r im in a n t f u n c t i o n s are lin ear c o m b i n a t i o n o f i n d e p e n d e n t v a r ia b le s that will d i s c r im i n a t e b e st b e t w e e n th e p r i o r i - d e f i n e d g r o u p s . T h i s is a c h i e v e d by the statistic al d e c i s i o n rule o f m a x i m i z i n g the b e t w e e n g r o u p v a r ia n c e r e la tiv e to th e w i t h i n - g r o u p v a r ia n ce . 69 T able 10. D isc rim in a n t L o ading for Ind ep e n d e n t V a ria b les C o m p ris in g The D isc rim in a n t F unctions. D i s c r im i n a n t F u n c tio n I II III .8 8 9 9 1 * 0 .1 5 4 4 0 0 .02614 -.5 3 2 0 8 * -0 .3 0 3 3 4 0 .4 6 6 7 9 S a il B o a t .38831* 0.05882 0 .16038 I n board B o a t .25932* 0 .1 2 4 1 9 -0 .0 8 9 6 8 Incom e O ver $ 6 0 ,0 0 0 .19134* 0.15846 0.15061 Canoe -.1 3 8 6 0 * -0 .0 1 7 4 5 0 .03407 Incom e Under $ 2 0 ,0 0 0 -.1 2 8 4 2 * -0 .0 6 9 2 9 -0 .1 0 9 7 6 S e c o n d H o m e O w nership -0 .2 4 6 7 6 .83913* 0.0 4 9 3 8 R e s i d e O u t o f Sta te -0 .0 4 3 4 4 .48713* 0.1 5 5 1 0 In co m e $ 2 0 , 0 0 0 to $ 5 9 ,9 9 9 -0 .0 8 1 8 1 -.1 1 7 9 9 * -0 .0 5 4 6 9 P ontoon Boat -0 .1 1 0 9 7 0.13042 - . 6 9 6 8 1* A g e o f Boat O w ner -0 .0 6 6 5 4 0.17825 -.3 8 5 6 4 * R e s i d e in C e ntr al C o a s t R e g i o n 0 .04454 -0 .0 6 2 2 2 .24834* R e s i d e in N o r t h In land R e g i o n -0 .0 8 8 2 9 -0 .0 8 1 1 8 -.2 1 0 8 0 * R e s i d e in N o r t h C o a s t R e g i o n 0.0 6 0 0 6 -0 .1 5 4 1 8 -.2 0 1 4 4 * R e s i d e in S o u t h In land R e g i o n -0 .0 3 7 9 5 0 .0 2 7 1 5 .17919* R e s i d e in U p p e r P e n in s u la R e g i o n 0.00067 -0.1 1 5 7 9 -.1 7 4 2 4 * R e s i d e in S o u t h C o a s t R e g i o n 0.0 4 7 2 9 -0 .0 5 9 7 3 -.0 8 4 9 9 * B o a t L e n g th ( f e e t ) O utboard Boat * I n d ic a t e s that th e c o r r e la t io n b e t w e e n the i n d e p e n d e n t v a r ia b le an d d is c r im i n a n t f u n c ti o n is s i g n i f i c a n t at 0 . 0 5 l e v e l. 70 functions. D isc rim in a n t function I m ay be interpreted as a function to differentiate b e tw e en boats stored at m a rin a s an d boats in o th er types o f storage. Boat length, sail, inboard p o w e re d , and in co m e o v e r $ 6 0 ,0 0 0 are positive correlated w ith the discrim inant function I. D is c rim in a n t function II m ay be interpreted as a function to differentiate b e tw e en boats stored at second h o m e s and boats in o th e r types o f storage. Second hom e o w n e rsh ip , and out-of-state residency are positively correlated w ith the discrim inant function II. D isc rim in a n t function III m ay be interpreted as a function to differentiate be tw e en b o a ts stored at n o n w a te rfro n t h o m e s an d boats in o th er storage segm ents. P o ntoon boats, age o f the o w ners, and w h e th e r the o w n e rs reside in northern-inland, northern-coastal or Upper P e n in su la regions, are negatively correlated with the d isc rim in a n t function III. W il k 's la m b d a and partial F v alue are utilized to d e te rm in e the im pacts o f in d ep e n d e n t variables on the c lassification (Table 11). T h e W ilk s ' lam bda w hich is the ratio o f the w ith in -g ro u p s s u m o f squ a re s to the total sum o f sq u ares m easures the disc rim in a tin g p o w e r o f a variable. T h e larger the W il k s ’ lam bda, the stronger the d isc rim in a n t p o w e r o f the in d e p e n d e n t variable. A partial F -value is o btained for each in d ep e n d e n t variable, w h e re it partitions out the va ria n ce in the variable that is already e x p la in e d by the o th e r variables. L arger F-values indicate in d e p e n d e n t variables with greater d isc rim in a tin g pow er. B o a t length, second h o m e o w n e rsh ip , and outb o ard p o w e r have the strongest in fluences in classifying boats into storage segm ents. T h e d isc rim in a n t m odel is a d isa ggregate level o f analysis, as it predicts storage o f individual boats (i.e., " d o e s the d isc rim in a n t m odel classify boat " x ” that is stored at a m arin a as a m arin a stored b o a t? ” ). For m o st p la n n in g an d m a rk e tin g de c isio n s it is 71 T able 11. W ilks' L a m b d a an d Partial F for Ind ep e n d e n t V a ria b les in The D isc rim in a n t Analysis. In d e p e n d e n t Variables" W ilk s' L a m b d a Partial V B o a t L e n g t h (f e e t ) 0.5 2 7 7 91.85 S e c o n d H o m e O w nership 0 .3 3 3 645.68 O u tb o a r d B o a t 0 .3 0 4 4 5 1.64 R e s i d e O ut o f State 0 .2 8 2 3 57.95 Pontoon Boat 0.261 304.52 S a il B o a t 0.2 5 2 260.53 A ge o f Boat O wner 0 .2 4 7 2 26.33 R e s i d e in S o u t h Inland R e g i o n 0.244 2 0 0 .2 9 R e s i d e in C e ntr a l C o a s t R e g i o n 0 .2 4 0 180.1 1 In board B o a t 0.2 3 8 162.99 R e s i d e in S o u t h C o a s t R e g i o n 0.2 3 7 148.57 a. T h e i n d e p e n d e n t v a r ia b le s e n t e r e d in s t e p w i s e d is c r im in a n t a n a l y s i s b a s e d o n th e rule o f m i n i m i z i n g o v e r a ll W ilk s' lam b d a. 72 necessary to predict boat storage at an aggregate level (i.e.. “ h o w m an y boats in size class “ x " are stored at m arinas?"). A t the disaggregate level, the d isc rim in a n t m odel correctly classifies 748 (7 6 % ) o f the 9 8 4 bo a ts stored at m arinas. A t the aggregate level, the disc rim in a n t m odel predicts 9 0 7 boats stored at m arinas. T h is is 8% less than the 1994 M ic h ig a n B oating S urvey e stim ate o f 984 boats. E xcept for the d isc rim in a n t m odel, other m o d e ls in the system (i.e.. storage allocation m o d e ls and trip distribution m o d e ls) are e stim a ted at the agg re g a te level and they are e v aluated accordingly. T he aggregate m o d els first gro u p individual boats into classes based on region, county, size class or se g m e n t and then m o d el b o a tin g use o f the group as a w hole. T h e e stim a ted para m ete rs from the d isc rim in a n t a nalysis can not be used directly in the allocation m o d e ls b ased on the B oat R egistration data, b ecause the prim ary in d ep e n d e n t variable, se co n d h o m e o w n e rsh ip , is not m ea su red in the d ata set. B O A T S S T O R E D IN C O U N T IE S Spatial allocation m o d e ls are used to allocate boats w ithin each o f the storage se g m e n ts to co u n tie s w h e re they are ke p t d u rin g the bo atin g season. A tw o step approach is em ployed: boats first are allocated to storage regions, and th en to co u n tie s w ithin each region. T h e allocation m o d els for each storage se g m e n t are su m m a riz e d in Figure 6 and 7 (on pages 53 an d 55). M odel Specification T h e n u m b e r o f b o a ts in each size class is e stim ated from 1994 M ic h ig a n B oating survey for ea ch storage segm ent. B oats stored at n o n w a te rfro n t h o m e s c o m p ris e alm ost 73 4 0 % o f the ac tiv e registered boats. T w o thirds o f these bo a ts are less than 16 feet. A lm ost h a lf o f M ic h i g a n 's registered b o a ts are stored at either second h o m e s (2 6 % ) or w aterfront h o m es (23% ). A p p ro x im a tely 12% o f active registered boats are stored at m arinas during the boating season. O v e r 7 0 % o f these boats are longer than 21 feet (T able 12). T he e stim a ted d istrib u tio n o f boats in different size and different types o f storage in (storage) regions is sh o w n in T able 13. Based on the survey, ab o u t h a l f o f M ichigan boats are stored in the so u th -in la n d and s o u th e a st regions. A high p ro p o rtio n o f m arina boats are stored in the so u th e a st region. T h e n orth-inland, n o rtheast and northw est regions are p o p u la r storage locations for b o a ts stored at second h o m es. A high percentage o f boats u n d e r 20 feet stored at w aterfront h o m e s are kept in the so u th -in la n d region. The southeast region hosts a greater p e rcentage (3 9 % ) o f larger boats stored at w aterfront hom es. M ost boats stored at n o n w a te rfro n t h o m e s are kept in so u th -in la n d and southeast regions w h e re m o st o f M ic h ig a n 's po p u latio n resides. M e a s u re s o f a c o u n ty ’s boat storage o p p o rtu n itie s (capacities) are used to allocate boats to the c o u n tie s w ithin ea ch region w h e re they are kept. T he n u m b e r o f m arina spaces in each county is used as an in d ic a to r (G M indicator) o f a c o u n ty 's storage opp o rtu n itie s for m arin a b o a ts kept in the coastal c ounties |o . T h e “ n u m b e r o f lakes over 50 a c re s" and "total acres o f inland lakes in the co u n ty " are c o m b in e d into an storage o p p o rtunity index (LM index) to allocate m a rin a boats to inland c o u n ti e s 19. T he n u m b e r l!i T h e n u m b e r o f m arin a s p a c e s in t h e c o a s t a l c o u n t i e s w a s c o l l e c t e d b y the 1 9 9 4 G re a t L a k e s M a rin a Census. |y A n in d e x o f inland c o u n t y ’s b o a t - s t o r a g e o p p o r t u n it y for m arin a b o a t s is c o n s t r u c t e d as f o l l o w i n g : a c r e s o f la k e s in th e c o u n t y G M in d e x = n o o f la k e s o v e r 5 0 a c r e s * - ....................................................... - .............. state a v e r a g e a c r e s o f la k e s T h e in fo r m a t io n o n the n u m b e r o f l a k e s o v e r 5 0 a c r e s a n d total a c r e s o f inla nd l a k e s w a s c o l l e c t e d in " M i c h i g a n L a k e s Inventory " ( M i c h i g a n D e p a r t m e n t o f N atu ra l R e s o u r c e s , 1 9 7 4 ) . 74 T ab ic 12. E stim ate d N u m b e r o f B o ats in S to rag e S e g m en ts by S ize C lasses. U n w eigh ted S to r a g e Segm ents Boat Size Percent Cases 59 ,0 7 7 11.6% 9S4 2 0 feet or s m a l l e r 16.105 3.2% 66 2 1 - 2 8 feet 2 7.354 5 .4 % 244 2 9 feet o r larger 15,618 3.1% 674 134,072 2 6.3% 574 M arin a S eg m en t S e c o n d H om e S eg m en t L e s s than 16 feet 73.1 5 3 1 4 .4 % 127 1 6 - 2 0 feet 39,3 2 5 7.7% 218 21 feet o r larger 21.594 4.2% 229 119,187 23.4% 593 W aterfront H om e Seg m en t L e s s than 16 feet 5 0,331 9.9% 104 1 6 - 2 0 feet 38.941 7.7% 193 2 1 feet or larger 29,915 5.9% 296 I9 6 .6 S 6 38.6% 603 L e s s than 16 feet 135,386 26.6% 264 16 feet or larger 61,300 12 .0 % 339 50 9 ,0 2 2 100.0% 2, 754 N o n w a terfro n i H om e S eg m e n t Tola! N o . o f Boats" a. C a s e s w ith m i s s i n g sto r a g e t y p e a n d /o r s to r a g e c o u n t y i n f o r m a t io n are e x c l u d e d from the a n a ly s is . note: E s t i m a t e s are b a s e d o n th e 1 9 9 4 M i c h i g a n B o a t i n g S u r v e y . T ab le 13. N u m b e r and Percentage o f B oats in D ifferent S torage S egm ents by Region W h e re Boat Is Kept D uring B oating Season. BO AT STORAGE SEG M ENTS Marina Storage Region 20' or S econd H om e 29' or less 2P -28' lamer All Boats Waterfront H o m e 2 E or <16' l6 '-2 0 ’ lamer Nonvvaterfront Home 2 1 ' or <16' 16-20' larger 16’ or < 16' larger N u m b e r o f b o a ts Southeast 5 .53 8 11.785 8.321 694 1.089 2.1 8 9 4 .1 6 2 5.035 11.635 16,807 13.726 80,981 East Central 1.566 3 .57 9 1.182 3.641 1.136 545 1.040 103 530 7,801 4 ,3 9 8 25,521 704 1.500 709 8 .7 0 0 5 .53 7 2.5 9 9 2.8 54 1.701 962 4 .1 4 4 2 .12 0 31 ,5 3 0 2,661 3 .13 0 1.435 10.302 7 .35 6 2 .67 4 5,5 96 3.041 1.952 7,869 3,7 4 0 4 9 ,7 5 6 W est Central 220 2 .6 64 1.784 3.1 37 659 1.124 476 659 1.486 8.153 5,811 26,1 73 Southw est 243 1.203 1.368 1.016 1.661 726 3.531 1,243 1.435 7,027 2,3 05 21.7 5 8 South Inland 3 .26 8 1.680 39 14.395 8 .2 84 3.6 8 0 18.810 2 2 .0 2 5 8 ,1 3 9 6 5 .6 6 6 22,711 168,697 North Inland Northeast Northwest 497 723 274 2 1 .9 4 8 7 .24 6 4 .26 3 6 ,4 4 2 3 .8 14 2 ,8 8 6 13,358 3 ,7 44 65 ,1 9 5 South UP 0 482 267 6 ,8 3 9 3.8 93 3 .0 9 0 2 ,5 7 2 455 534 2,4 95 1.261 21 .8 8 8 North UP 1,406 609 239 2 ,4 8 0 2,463 704 4 .8 4 7 865 355 2 ,06 8 1,484 17.520 16.103 27,3 5 5 15.618 7 3 ,1 5 2 3 9.3 2 4 2 1 .5 9 4 5 0 ,3 3 0 38,941 2 9 ,9 1 4 135,388 6 1 ,3 0 0 5 0 9 ,0 1 9 Southeast 34% 43% 53% 1% 3% 10% 8% 13% 39% 12% 22% 16% East Central 10% 13% 8% 5% 3% 3% 2% 0% 2% 6% 7% 5% Northeast 4% 5% 5% 12% 14% 12% 6% 4% 3% 3% 3% 6% Northw est 10% Total P er ce n t o f b o a ts 17% 11% 9% 14% 19% 12% 11% 8% 7% 6% 6% West Central 1% 10% 11% 4% 2% 5% 1% 2% 5% 6% 9% 5% Southw est 2% 4% 9% 1% 4% 3% 7% 3% 5% 5% 4% 4% South Inland 20% 6% 0% 20% 21% 17% 37% 57% 27% 49% 37% 33% North Inland 3% 3% 2% 30% 18% 20% 13% 10% 10% 10% 6% 13% South UP NA 2% 2% 9% 10% 14% 5% 1% 2% 2% 2% 4% North UP 9% 2% 2% 3% 6% 3% 10% 2% J% 2% 2% 3% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Total note 1: C ases with m issing storage type and/or storage county information are excluded from the analysis, note 2: Estimates are based on the 1004 M ichigan Boutina Survey. 76 o f second h o m e s in each county is used as an indicator (SH indicator) o f second hom e o p p o rtu n itie s -0. The n u m b e r o f registered bo a ts by size class used as an indicator (RS indicators) for boats kept at w a te rfro n t h o m e s and n o n w a te rfro n t h o m e s 21. Indices for all co u n tie s are pro v id e d in A p p e n d ix C. T he indicators (index) m ea su re a c o u n ty 's attrac tiv e n e ss as a potential storage location for boats in different storage segm ents. T h e indices are used to distribute boats to counties in each region for each storage type. T h e fo llo w in g county level allocation form ula is used: I S, i c R e g io n r w h e re T'(1|r) : total n u m b e r o f boats kept in cou n ty i, given region r; and S, : the availability o f storage opp o rtu n itie s in county i. Sj = N u m b e r o f m arina sp a ce s in the county for m a rin a boats kept in coastal counties. S| = T he v alue o f 1M index (n u m b e r o f lakes o v e r 50 acres and total acres o f inland lakes) in the cou n ty for m arina boats kept in inland counties. Sj = N u m b e r o f second h o m es in the county for boats stored at se co n d hom es. S, = N u m b e r o f registered boats in the cou n ty for different sized bo a ts stored at w aterfront h o m e s and n o n w a te rfro n t hom es, note - form ula allocates a share to each county w ithin the region in proportion to its share o f regional opportunities. A s s u m p tio n s T h e allocation m o d els m ak e five basic a ssu m p tio n s in ord er to estim ate the n u m b e r o f boats in different types o f storage ke p t in counties. 11 T h e n u m b e r o f s e c o n d h o m e s in c o u n t i e s c o m e s fr om 1 9 9 0 M i c h i g a n C e n s u s . :l T h e n u m b e r o f r e g i s te r e d b o a t s b y d iffe r e n t s i z e c l a s s e s in c o u n t i e s is p a n o f the M i c h i g a n B o a t R e g istr a t io n D a t a b a s e ( M i c h i g a n S e c r e ta r y o f S tate, 1 9 9 4 ). (1) T h e e s tim a tes o f the regional d istribution o f boats in storage se g m e n ts bv size classes from 1994 M ichigan B oating S urvey arc reliable. (2) It is a ssu m e d that co u n ty level m a rin a o c c u p an c y rates do not varv significantly w ithin a given region. The n u m b e r o f m arin a spaces reflects the distribution o f m a rin a b o a ts in coastal regions. (3) T he b o a t-storage op p o rtu n ity index based on n u m b e r o f inland lakes over 50 acre and acres o f inland lakes reflects the n u m b e r o f boats stored at m arin as in the inland counties. (4) T h e p ropensity o f se co n d h o m e s to p rovide storage for boats is sim ilar across c ounties w ithin a given region. In o th er w ords, the d istribution o f second h o m e s will m irro r the d istrib u tio n o f boats stored at second h o m es within a region. (5) T h e d istrib u tio n o f registered boats w ithin different size classes reflects the d istrib u tio n o f boats stored at w aterfront and n o n w a te rfro n t perm anent residences in a giv en region. R esults T h e predictions o f the allocation m o d els are reported in T a b le 14. T he total n u m b e r o f boats kept in M ic h ig a n co u n tie s ran g e s from 700 boats in K e w e e n a w county to 3 4,000 bo a ts in O a k la n d county. S o u theast co u n tie s hou se the largest n u m b e r o f boats. The few est n u m b e r o f b o a ts are kept in no rth e rn U p p e r P en in su la counties. The n u m b er o f boats kept in co u n tie s varies w ithin a region. For ex a m p le, in the southeast region. W ayne cou n ty h o uses alm ost four tim es the n u m b e r o f boats kept in M o n ro e county. T a b le 14. N u m b e r a n d P e r c e n ta g e o f B o a ts in M ic h ig a n C o u n t ie s b y S to ra g e S e g m e n ts. B O AT STORAGE SEGM ENTS Storage C o u n t) M arina N o o f B oats Col % S econd H om e R ow % N o o f B oats Col % rotai W aterfro n t H om e R ow % N o o f Boats Col % N om vaterfront H om e Row % No o f Boats Col % Row % N o o f Boats Col % M acom b 9.558 16 18% 35% 556 0 41% 2% 7.317 6 14% 27% 9.875 5 02% 36% 27.306 M onroe 4.920 8 33% 56% 308 0 23% 3% 1.417 1 19% t6 % 2.170 1 10% 25° o 8,816 1 73% St C lair 4.882 8 26% 41 % 2.028 151% 17% 2.005 1 68% 17% 2.932 1 49% 25% 1 1.847 " 5 3% W ayne 5 36% 6.284 10 64% 19% 1.080 0 81% 3% 10.092 8 47% 31% 15.556 7 91% 47% 33.012 6 49'% 25,644 43.41% 32% 3,972 2.96% 5% 20,832 17.48% 26% 30,533 15.52% 38% 80,981 15.91",, Bay 3.594 6 08% 47 % 177 0 13% 2% 479 0 40%, 6% 3.3 5 6 1 71% 44% 7.606 1 49% H uron 1.732 2 93% 31% 2.755 2 06% 49% 144 0 12% 3% 1.015 0 52% 18% 5.646 1 1 1% Saginaw 112 0 19% 2% 109 0 08% 2% 748 0 63% 11% 5.591 2 84% 85% 6.560 1 29", Sanilac 448 0 76% 14% 1.880 1 40% 60% 97 0 08% 3% 717 0 36% 23% 3.142 0 62% S outh east Tuscola 440 0 74% 17% 401 205 0 17% 8% 1.520 0 77% 59% 2.567 0 50% 6,327 10.71% 25% 5,322 3.97% 21% 1.673 1.40% 7% 12,199 6.20% 48 % 25.521 5.01% A lcona 96 0 16% 2% 3.876 2 89% 15% 566 047% 11% 644 0 33% 12% 5.18.3 1 02% A lpena 221 0 37% 6% 1.252 0 93% 33% 1.049 0 88% 28% 1,262 0 64% 33% 3.784 0 74” „ C en tral East 0 30% 16% A renac 693 1 17% 17% 1.669 1 24% 41% 852 0 72% 21% 845 0 43% 21% 4.059 (1 80'% C heboygan 695 1 18% 11% 3.341 2 49% 51% 1.173 0 98% 18% 1.327 0 67% 20% 6.5 56 1 28"„ Iosco 968 1 64% 12% 4.594 3 43% 56% 1.233 1 03% 15% 1.423 0 12% 17% 8,218 1 61% P resque Isle 240 041% 6% 2.105 1 57% 56% 643 0 54% 17% 763 0 39% 20% 3.751 0 74” ,, N ortheast 2,913 4.93% 9% 16,836 12.56% 53% 5,51 7 4.63% 17% 6.264 3.18% 20". 31.530 A ntrim 240 041% 4% 3.203 2 39% 53% 1.239 1 04% 21% 1.354 0 69% ""% 6.034 1 Benzie 796 1 35% 17% 2.145 1 60% 45% 861 0 72% 18% 982 0 50% 21% 4,785 0 94", 1.963 3 32% 29° o 2.642 1 97% 38% 1.102 0 92% 16% 1.165 0 59% 17% 6.872 1 55% 768 1 30% 12% 2.989 2 23% 48% 1.212 1 02% 19% 1.313 0 67% 21% 6.282 1 25% 1 77'0, C harlevoix Irmmct G rand Traverse 6.19% 384 0 65% 4% 2.248 1 68% 25% 3.083 2 59% 34% 3.317 1 69", 37% 9.032 Leelanau 1.069 1 81% 17% 2.846 2 12% 44% 1.201 1 01% 19% 1.305 0 66% 20° a 6.421 1 2n% M anistee 1.248 2 11% 23% 2.180 1 63% 41% 884 0 74% 17% 1.011 0 51% 19% 5.323 1 05'% M ason 758 1 28% 15% 2.077 1 55% 41% 1.008 0 85% 20% 1.162 0 49% 23% 5.006 0 98",, N orthw est 7,226 12 73% 15% 20.332 15.17% 41% 10,589 8.88% 21% 11.609 5.90",, 23% 49.756 9. 77",, M uskegon 1.664 2 82% 19% 899 0 67% 10% 967 0 81% 11% 5.321 2 71% 60% 8.851 1 74",, 118 0 20% 3% 2.693 2 01% 68% 147 o 12% 4% 988 0 50% 25'% 5.946 o 78",, O ceana O ttaw a 2.886 4 89% 22% 1.328 0 99% 10% 1.507 W est C en tral 4.6 68 7.90% 18% 4.920 3.67° i 19% 2.621 1 26" o 2.20% 1 1” , 7.653 3 89% 57",, 15.376 10% 13.964 7.10% 53% 26.173 5 14% 2 6 3" „ A llegan 64(1 1 08% 10% 869 0 65% 13% 1.977 1 66",, 50% 3 .0 0 7 1 5.3% 46°,, 6 .4 9 .5 1 28",, Berrien 1.578 2 67" „ 16% 1.416 1 06% 15% 2 6,89 2 26% 28'% 3 06 i 2 02" „ 41",, 9.646 1 9111' , Van B uten 596 1 01%, 11% 1.1 IS 0 83% 20% 1 1 29'% "7" r 2 362 1 20",, 42",, s 618 1 10% S outh w est 2.814 13% 3.403 2.54% 16% 29"., 9.332 4.74",, 21.758 4 27".. 4.76% 6.209 5.21"., 43". T a b le 14 (co n t'd ). BOAT STORAGE SEGMENTS Slorage C ountv M an n a N o o f B oats Col % S econd H om e R ow % No. o f Boats Col % W aterfront H om e Row % No o f B oats Col % N onw aterfront H om e Row % N o o f B oats Col % Row % N o o f Boats Col % B a rn 307 0.5 2 % 5% 2.057 1 53% 36% 1.142 0 96% 208b 2,232 1 13% 39% 5.738 1 13% Branch 246 042% 5% 2 .319 1 73% 46% 874 0 73% 17% 1.650 0 84% 32% 5.088 1 00"-, C alhoun 100 0.1 7 % 2% 9 0 01% 0% 1.444 1.21% 32% 3,010 1 53% 66% 4,563 0 90% Cass 375 0.6 4 % 6% 2.827 2 11% 43% 1.164 098% 18% 2.205 1 12% 34% 6.571 1 29% 2 0 00% 0% 41 0 03% 2% 827 0 69% 33% 1.625 0 83% 65% 2.495 0 49% 0 69% C linton Eaton G enesee G ratiot H illsdale Ingham Ionia 2 0.0 0 % 0% 132 0 10% 4% 1.150 0 97% 33% 2.241 1 14% 64% 3.525 56 0 10% 0% 708 0 53% 5% 4 .566 3 83% 34% 8.201 4 17% 61% 13.531 2 66% 7 0 01% 0% 95 0 07% 6% 464 0 39% 31% 938 0 48% 62% 1.504 0 30% 56 0 10% 2% 1.628 1 21% 46% 662 0 56% 19% 1.215 3,562 0 70% 0 00% 0% 311 0 23% 4% 2.331 1 96% 33% 4,471 0 62” b *> “>yo 0 34% 1 63% 7,113 1 40% 13 0.0 2 % 1% 350 0 26% 15% 662 0 56% 28% 1.365 0 69% 57% 2 ,390 0 47% Isabella 9 0 01% 0% 838 0 62% 33% 569 0 48% 22% 1.121 0 57% 44% 2 ,536 0 50% Jackson 346 0 59% 4% 1.655 1 23% 20% 2.154 1 81% 26% 4.025 2 05% 49% 8,181 1 61% K alam azoo 263 0 44% 3% 551 0 41% 7% 2.623 2 20% 31% 4.995 2 54% 59% 8,422 1 66% K ent 235 0 40% 1% 1.222 0 91% 7% 5.979 5 02% 32% 11.253 5 72° b 60% 18.689 3 67% L apeer 60 0 10% 2% 667 0 50% 20% 903 0 76% 28% 1.654 0 84“o 50% 3,284 0 65% Lenaw ee 76 0 13% 1% 1.954 1 46% 36% 1.213 1 02% 22% 2.215 1 13% 41% 5,458 1 07% 456 0 77% 6% 1.475 1 10% 19% 2.196 1.84% 28% 3.604 1 83“ , 47% 7.731 1 52% 14 0 02% 0% 374 0 28% 9% 1.282 1 08% 32% 2.358 1 20“ o 59% 4 .028 0 79% 173 0 29% 3% 2,577 1 92% 48% 854 0 72% 16% 1.815 0 92% 33% 5.418 I 06% 1.636 2 77% 5% 2.295 1 71% 7% 11.736 9 85% 34% 18.450 9 38", 54% 34,117 6 70% L ivingston M idland M ontcalm O akland 299 0 51% 6% 1.329 0 99% 26% 1.142 0 96% 23% 2.276 1 16” , 45% 5,047 I) 99% S hiaw assee Si Joseph 4 0 01% 0% 105 0 08% 4% 816 0 68% 32% 1 .6 1 1 0 82“ o 645, 2,535 0 50% W ashtenaw 250 0 42% 3% 839 0 63% 12% 2.220 1 86% 31% 3.849 1 96", 54% 7,159 1 41", 4 ,9 8 7 8.44% 3% 2 6 .3 5 9 19.6 6% 16% 4 8 ,9 7 4 41.09% 29% 8 8 ,3 7 7 32% 1 68,697 33 .1 4 % S o u th Inland 44.93% Cl3rc 78 0 13% 1% 3.735 2 79% 59% 1.047 0 88% 178b 1.452 0 74", 23% 6.312 1 24% C raw ford 18 0 03% 1% 1.764 1 32% 55% 681 0 57% 21% 766 0 39" o 24% 3.228 0 63% G ladw in 63 0 11% 1% 2.476 1 85% 48% 1.201 1 01% 23% 1.411 0 72“» 27% 5.151 1 01% K alkaska 54 0 09% 2% 1.563 1 17% 50% 632 0 53% 20% 862 0 44”, 28% 3.111 0 61% Lake M ecosta 30 0 05% 1% 3.364 2 51% 74% 501 0 42% 11% 652 0 33“ , 14% 4.546 0 89% 158 0 27% 4% 1.476 1 10% 34% 0 97% 27% 1.532 0 78", 35", 4 .322 0 85", 0 4.1% *itn 672 0 34" „ 29“ , 2.305 0 45", 0 44% 14% 771 1) .39",, , 10 _ I 0 3 653 0 72°,, 1 2* I " O 25% 1 08", >511o 6 ,137 1 21", II 6 8 % IS” ,, 2.121 1.087 0 55", 24", 4.534 O 89", 37 0 06% 2% 1.088 081% 47% 1.156 509 M ontm orency 164 0 28% 4 n,o 2.197 1 64% 60% 521 N ew asgo 176 0 30% 3% 2.280 1 70% 37% 1.560 Ogemaw 76 o 13% , "Ml ' .. O 2 560 1 9 |% 56° n 8] 1 M issaukee T a b le 14 (cont'd). BO AT STORAGE SEGMENTS Storage C ounty M arina N o o f Boats Col. % Second H om e Row % N o o f B oats C ol. % Tot;tl W aterfro n t H om e Row % No. o f B oats Col % N onw aterfront Home Row % No o f Boats Col % Row % N o o f Boats Col % O sceola 16 0.03% 1% 1.500 1.12% 51% 565 0 47% 19% 862 0 44% 29% 2.944 0 58% O scoda 19 0.03% 1% 2.038 1.52% 66% 444 0 37% 14% 565 0 29% 18% 3.066 0 60% 0 68% O tsego 91 0.15% 3% 1.673 1.25% 48% 715 0 .6 0 % 21% 1.000 0 51% 29% 3.478 472 0 80% 5% 4 ,770 3 .56% 54% 1.715 1 449 b 19% 1,922 0.9 8 % 22% 8.878 1 74% 42 0 07% 1% 976 0 73% 28% 1,084 0 91%, 31% 1,427 0 73% 40% 3.529 0 69% 1,494 2.53% 2% 33.45 7 24.95% 51% 13.142 11.03% 20% 17.102 8.69% 26% 65.195 12.81% 179 030% 4% 2.342 1 75% 53% 908 0 76% 21% 976 0 50% 22% 4.406 0 87% D ickinson 0 0 00% 0% 1.640 1 22% 55% 658 0 55% 22% 709 0 36% 24% 3.008 0 59% Iron 0 0 00% 0% 2.5 0 9 1 87% 71% 493 0 419b 14% 514 0 26% 15% 3.516 0 69% M ackinac 366 0 62% 7% 3.9 2 2 2 93% 71% 606 0 51% 11% 618 0 31% 11% 5.512 1 08% M enom inee 173 0 29% 6% 1.677 1 25% 58% 517 0 43% 18% 545 0 28% 19% 2.912 0 57% 1% 1.731 1.29% 68% 378 0 32% 15% 394 0 20% 16% 2.534 0 50% 3% 13.822 10.31% 63% 3.561 2.99% 16% 3.756 1.91% 17% 21,888 4.30%, 0 25% R oscom m on W exford N orth Inland D elta S choolcraft South I p p er P eninsu la Alger 31 0 05% 749 1.27% 60 0 .10% 5% 514 038% 41% 436 0 37% 35% 246 0 13% 20% 1.255 Baraga 326 0 55% 31% 316 0 24% 30% 249 021% 24% 147 0 07° 8 14% 1.033 0 20% C hippew a 883 1 49% 21% 1.323 0 99% 32% 1,190 1 00% 29% 729 0 37% 18% 4,124 0 81% (io g e b ic 82 0 14% 4% 699 0 52% 38% 681 0 57% 37% 382 0 19% 21% 1.844 0 36% H oughton 314 0 53% 14% 6 68 0 50% 29%) 803 0 67% 35% 495 0 25% 22% 2.280 0 45% K ew eenaw 172 0 29% 26% 355 0 26% 53% 85 0 07% ! 3°o 53 0 03% 8% 665 0 13% 0 0 00% 0% 307 0 23% 36% 364 031% 42% 193 0 10% 22% 864 O 17% M arquette 332 0 56% 7% 1.127 0 84% 25% 1,926 1 62% 43% 1.122 0 57% 25% 4.508 0 89% O ntonagon 84 0 14% 9% 338 0 25% 36% 334 0 28% 35% 186 0 09% 20% 942 0 18% Luce N orth I p p er P eninsu la STA TE TO TAL note 2.254 3.82% 13% 5.647 4.21% 32% 6.067 5.09% 35% 3,552 1.81% 20% 17.520 3.44% 59,076 100% 12% 134,070 100% 26% 119,185 100% 23% 196,688 100% 39% 509,019 100% th e to la 1 n um ber o f boats is less than the n um ber o f registered activ e recreational w atercraft (5 5 5 .0 0 0 boats), d u e to th e cases w ith m issin g storage v ariables are exclu d ed from the (survey based I estim ates ol boats in different storage segm ents by storage regions (T ab le 13 1 w hich arc used to allocate boats to storage regions in the allocation m odels 81 C o u n ties w h e re bo a ts are kept vary across storage segm ents. O v e r forty percent o f m arin a boats arc kept in s o u th e a st M ichigan. S ixteen p ercent o f boats stored at m arinas are in M a c o m b county. T h e n u m b e r o f b o a ts stored at m arin as is different across counties w ithin a region. In the n o rth w e s t region, only 2 4 0 boats are stored at m arin as in A ntrim c ounty, w hile a lm o st 2 .0 0 0 boats are stored at m arin as in n eig h b o rin g C h a rle v o ix county. A b o u t a third o f boats stored at second h o m e s are kept in northern inland or southern U p p e r P e n insula counties. T he few est n u m b e rs o f boats stored at second hom es are in so u th e a st an d s o u th w e st counties. R o s c o m m o n and M ack in a c c ounties have the largest n u m b e r o f bo a ts stored at second hom es. T h e re are m o re w ate rfro n t h o m e s in c ounties w ith w a te r resources and large p o p u latio n s and as a result m o re b o a ts stored at w ate rfro n t h o m e s in these counties. A lm o st 6 0 % o f all bo a ts stored at p e rm a n e n t w a terfront h o m e s are in southeast or south inland counties. A b o u t a q u a rte r o f all boats kept at w a terfront h o m e s are in W ayne. O a k la n d and M a c o m b counties. O v e r 6 0 % o f bo a ts at n o n w a te rfro n t h o m e s are kept in sou th e a st or south-inland counties. O a k la n d . W a y n e and K ent c ounties hou se m o re boats at n o n w a te rfro n t hom es than any o f the o ther counties. In large part, this is a function o f their po p u latio n sizes. For e x a m p le, there are 2.75 tim es m o re bo a ts stored at n o n w a te rfro n t ho m es in Ingham cou n ty than n eig h b o rin g C lin to n county. In g h am has m o re population. It is also useful to e x a m in e the ratio o f bo a ts kept in regions to the n u m b e r o f boats o rig in a tin g fro m regions (T a b le 15). T h e lo cations w h e re boat o w n e rs reside are the places from w h ic h the boats originate. R atio v alues grea ter than o n e indicate that the 8 2 T a b i c 1 5. N u m b e r o f B o a ts b y R e g io n o f R e sid e n c e , R e gion o f S to ra g e an d S to ra g e T ype. BO A T STORAGE SEG M ENTS M arina Second H om e W aterfront N onw aterfront Home Hom e Total R esid en ce R egion s S o u th e a st b a s t Central 17.088 23.352 19.417 3 0,862 9 0 .7 1 9 3.9 8 6 7,4 7 8 1 ,885 12,317 2 5 .666 N o r th e a st 1.122 1 .8 1 3 5,4 5 9 6,1 13 14,507 N orthw est 2 .9 4 2 2,468 1 0 ,6 6 3 11,396 2 7.469 C entral W e s t 2,703 3,5 2 7 2,6 0 8 13,637 2 2 ,475 Southw est 1.741 3,0 1 9 6,460 9,3 0 9 2 0,529 Inland S o u th 21,891 58,233 4 9 ,1 8 2 8 8,780 2 18,086 Inland N o r th 1 ,2 1 8 3 ,9 2 5 12,541 16,365 34.049 U p Sou th 413 4,121 3,5 5 7 3,755 1 1 ,8 4 6 IJP N o r th 1 ,6 2 7 1 ,0 7 2 6.103 3,5 5 1 12,3 5 3 54,731 109.008 1 17,875 196,085 47 7 .699 3,7 4 5 24,105 600 957 1 ,3 1 0 603 3,470 5 9 .0 7 6 134,070 1 19,185 196,688 5 0 9 ,0 1 9 2 5,644 3,9 7 2 2 0 ,8 3 2 30,533 80,981 6 ,3 2 7 5,3 2 2 1 ,67 3 12,199 25,521 State T o tal O ut o f state M issing Total 2 7.850 S to r a g e R eg io n s S o u th e a st Hast C entral N ortheast 2 ,9 1 3 16,836 5 ,5 1 7 6,2 6 4 3 1.530 Northw est 7 ,2 2 6 20,332 10,589 1 1,609 4 9 ,7 5 6 Central W e s t 4 ,6 6 8 4 ,9 2 0 2 ,6 2 1 13,964 26,1 7 3 Southw est 2,8 1 4 3,4 0 3 6,209 9,3 3 2 21,758 S o u th In land 4,9 8 7 2 6 ,3 5 9 48,974 8 8 ,3 7 7 168,697 N o r t h In land 1 ,4 9 4 33,457 13,142 17,102 65,195 3,561 3,7 5 6 21,888 S o u th U P North U P State Total 749 13,822 2,2 5 4 5,6 4 7 6,067 3,5 5 2 1 7,520 5 9 ,0 7 6 134,070 1 1 9 ,1 8 5 19 6 ,688 5 09,019 R a t i o o f N u m b e r o f B o a t s in S t o r a g e R e g i o n s t o N u m b e r o f B o a t s in R e s i d e n c e R e g i o n s S o u th e a s t 1 .5 0 0 .1 7 1.07 0 .9 9 Hast C entral 1 .5 9 0 .7 1 0.89 0.99 0.99 Northeast 2.60 9 .2 9 1.01 1.02 2.17 1.81 0 . 8 9 :l N orthw est 2 .4 6 8.24 0.99 1.02 Ce ntr al W e s t 1.73 1 .39 1.00 1.02 1.16 Southw est 1.62 1.13 0 .9 6 1 .0 0 1.06 S o u t h In lan d 0.23 0.45 1 .0 0 1 .0 0 0.77 N o r t h In land 1.23 8.52 1.05 1.05 1.91 South U P 1.81 3.35 1.00 1 .00 1.85 N orth U P 1 .3 9 5.27 0 .99 1 .0 0 1.42 State T o ta l 1.08 1.23 1.01 1 .0 0 1.07 a. T h e ratio, 0 . 8 9 , is e q u a l to th e n u m b e r o f b o a t s in s o u t h e a s t ( s t o r a g e ) r e g i o n , 8 0 , 9 8 1 , d i v i d e d by the n u m b e r o f b o a t s in s o u t h e a s t ( r e s i d e n c e ) r e g i o n , 9 0 , 7 1 9 . note: N u m b e r o f b o a ts in r e s id e n c e r e g i o n s is e s t i m a te d fr om th e 1 9 9 4 M i c h i g a n B o a t i n g su r v e y . 83 region is a net im p o rte r o f boats, w hile counties w ith ratios less than one are net e xporters. T he southeast, east-central an d so uth-inland regions are net e x p o rtin g regions. O th e r regions are net im p o rtin g regions, especially the northeast, n orthw est, north-inland and south U p p e r P e n in su la regions. T h e net flow s c apture the south-to-north boating travel patterns. T h e so u th -in la n d region is a “ net e x p o rtin g " region o f bo a ts stored at m arinas and second h om es. N o rth e rn M ic h ig a n regions are “net im p o rtin g " regions. T he general sou th -n o rth travel patterns a p p ly for these storage se g m e n ts, e x c ep t that the southeast region is a "net im p o rtin g " region for b o a ts at m arin as and “ net e x p o rtin g " region for boats stored at second h om es. T he so u th -to -n o rth patterns are m u c h m o re ob v io u s for boats stored at se co n d h om es. F o r ex a m p le, the n u m b e r o f bo a ts stored at second hom es in the n o rth east region is nin e tim es the n u m b e r o f boats stored at second hom es o rig in a tin g in the region. F or the boats stored at m arin as in the northeast region, the ratio is only 2.6. M odel E valuation T h e a llo c atio n m o d e ls are e v a lu a te d on the b ases o f b o th regional level estim ates and c o u n ty level estim ates. T h e tw o e stim ates are e v aluated separately. T h e percent o f boats in different size classes and types o f storage that are kept in regions is estim ated from the 1994 M ic h ig a n B o a tin g Survey. T h e m odel uses these estim a tes to allocate boats to the regions w here they are kept. S a m p lin g errors are c a lcu lated for the estim ated distribution. T h e sa m p lin g errors indicate the range o f ac cu ra cy for regional level 84 estim ates. C o u n ty level e stim ates are e v aluated by c o m p a rin g the allocation model e s tim a tes to direct survey estim ates. T a b le 16 p ro v id e s e stim ated sa m p lin g errors at a 95 p ercent c o n fidence l e v e l " for the e stim ated distribution o f bo a ts by storage se g m e n t and size class in the regions, f o r e x a m p le , based on the 1994 M ic h ig a n B oating Survey, it is estim a ted that 15.9% o f all registered boats are kept in the southeast region. The s a m p lin g error for this estim ate is 1.3% (absolute percent) at a 9 5 % co n fid e n ce level. T herefore, the 9 5 % confidence interval for the percent o f all registered boats kept in the so u th e a st region is betw een 14.6% and 17.2%. All sa m p lin g errors for the estim ated d istrib u tio n s are under 10%; the m ajority (9 0 % ) o f the sa m p lin g errors are u n d e r 5%. T h e largest s a m p lin g errors oc c u r for the small boat size c la sse s2' - boats under 20 feet stored at m arinas, boats less than 16 feet stored at second h o m es, and boats less than 16 feet stored at w aterfront hom es. The e stim a ted d istrib u tio n for boats under 20 feet stored at m arin as is less reliable, due to the large s a m p lin g errors ranging from 3% to 10%. For ex a m p le, based on survey estim ates. 3 4 % o f boats (5 .5 0 0 boats) u n d e r tw enty feet stored at m arin as are kept in the southeast region. W ith 9 % s a m p lin g e rro r at the 95 percent c o n fid e n ce level, the n u m b e r o f boats :: T h e s a m p l i n g error at 9 5 p e r ce n t c o n f i d e n c e interval for b i n o m i a l d ist r ib u tio n is fo r m u l a te d as: e: - Z -(P *(1-P )] N W here e - error Z 71 .9 6 at the 9 5 p e r c e n t c o n f i d e n c e lev e l P = p o p u l a t i o n p r o p o r tio n N = num ber o f cases t h e 1 9 9 4 M i c h i g a n B o a t i n g S u r v e y s a m p le d f e w e r sm a ll s i z e boats. Table 16. Regional Distribution o f Boats by Storage Segment: Sam pling Errors at A 95% Confidence Interv al. BOAT STORAGE SEGM ENTS Marina Storage S e c o n d H om e 29' or Regions 20' or less 21 ’-28' larger Waterfront H o m e 21' or <16' 16-20' larger Nonwaterfront H om e 21' or <16’ 16’-20' larger All Boats 16' or 16’ larger S a m p lin g E r r o r a t 9 5 % C o n fid e n c e In ter v a l Southeast 9.0% 5.1% 3.1% 1.5% 1.8% 3.0% 4.5% 3.1% 4.8% 3.5% 3.2% 1.3% East Central 7.9% 4.3% 2.6% 3.7% 2.0% 1.9% 2.6% 1.0% 2.0% 2.8% 2.8% 1.0% Northeast 6.4% 3.7% 2.3% 5.4% 4.6% 4.0% 5.4% 3.9% 3.2% 2.4% 2.4% 1.1% Northwest 10.3% 5.1% 2.9% 6.1% 5.3% 5.3% 6.8% 4.9% 4.2% 3.2% 3.2% 1.4% Central West 2.9% 3.8% 2.6% 3.7% 1.5% 3.0% 1.9% 1.7% 3.0% 3.0% 3.0% 1.0% Southw est 2.9% 2.5% 2.5% 2.2% 2.8% 2.2% 4.8% 2.4% 2.0% 2.6% 1.9% 0.9% South Inland 8.7% 1.8% 0.5% 6.7% 5.0% 3.4% 9.0% 7.0% 3.8% 6.0% 4.8% 1.4% North Inland 5.0% 1.8% 1.1% 8.1% 4.9% 4.4% 6.9% 5.0% 3.7% 4.1% 3.1% 1.1% South U P NA 2.8% 1.4% 4.9% 4.4% 5.4% 4.1% 3.1% 2.9% 1.5% 2.9% 1.0% North U P 9.0% 3.9% 1.6% 3.4% 4.1% 3.4% 5.4% 3.3% 2.7% 1.5% 3.0% 0.9% 15.9% D istr ib u tio n o f b o a ts in r eg io n s Southeast 3 4.4 % 43.1% 53.3% 0.9% 2.8% 10.1% 8.3% 12.9% 38.9% 12.4% 22.4% East Central 9.7% 13.1% 7.6% 5.0% 2.9% 2.5% 2.1% 0.3% 1.8% 5.8% 7.2% 5.0% Northeast 4.4% 5.5% 4.5% 11.9% 14.1% 12.0% 5.7% 4.4% 3.2% 3.1% 3.5% 6.2% Northw est 9.8% 16.5% 11.4% 9.2% 14.1% 18.7% 12.4% 11.1% 7.8% 6.5% 5.8% 6.1% Central W est 1.4% 9.7% 11.4% 4.3% 1.7% 5.2% 0.9% 1.7% 5.0% 6.0% 9.5% 5.1% Southwest 1.5% 4.4% 8.8% 1.4% 4.2% 3.4% 7.0% 3.2% 4.8% 5.2% 3.8% 4.3% South Inland 20 .3% 6.1% 0.2% 19.7% 21.1% 17.0% 37.4% 56.6% 27.2% 48.5% 37.0% 33.1% North Inland 3.1% 2.6% 1.8% 30.0% 18.4% 19.7% 12.8% 9.8% 9.6% 9.9% 6.1% 12.8% South U P NA 1.8% 1.7% 9.3% 9.9% 14.3% 5.1% 1.2% 1.8% 1.8% 2.1% 4.3% North U P 8/7% 12% U5% 14% 61% 13% 16% 12% 12% L5% 14% No. o f B oats N o o f Sa m p les o « nco/ 14% 16.103 27.335 15.618 73.152 39.324 2 1.594 5 0 .3 3 0 38.941 29.914 135.388 61,300 509.019 66 244 6~4 12~ 218 229 104 193 296 264 339 2754 ~ a. With a 95% o f co nfide nc e interval, the sam pling error is 1.3% for boats kept in southeast region which represent 16% o f boats in the state Therefore, the "population" percentage o f boats in the southeast region is between ( 1 6 % - 1.3%) and (16% * 1.3%). 86 under tw e n ty feet stored at m arin as in southeast region co u ld range a n y w h e re from 4.000 boats to 6 .9 0 0 boats (2 5 % to 43% ). T h e allocation m odel is also e v aluated on e s tim a tes o f the n u m b e r o f boats kept in counties. M odel e stim a tes are c o m p a re d w ith the direct e stim a tes from the 1994 M ic h ig a n B o a tin g Survey. Iirrors in m odel e stim a tes are likely the result o f using county b o a t-sto ra g e o p p o rtu n ity in d icators/index to allocate boats to c ounties w ithin the region w here the boats are kept. T h e su rv ey-based e stim ates are subject to sa m p lin g errors. Large sa m p lin g error are usually a ssociated w ith c o u n ty level estim a tes due to small sam ple sizes. Fifty one o f 83 c o u n tie s have s a m p le sizes o f less than 30 boats: only 32 c o u n tie s have sa m p le sizes o f m o re than 30 boats. S a m p le sizes are m u ch sm aller for individual storage s e g m e n ts at the cou n ty level. T h e p ercent diffe re n c e is c o m p u te d as the difference be tw e en m odel estim ates and direct survey e s tim a tes in pro p o rtio n to the survey estim ate. ranges from a low o f 1% The percent differences for R o s c o m m o n co u n ty to a high o f 7 9 9 % for I.uce county. O nly o n e boat w a s sa m p le d in L uce county, so the surv e y -b a se d e stim ate is quite unreliable. M o s t co u n tie s w ith grea ter than 100% percent difference have sam ple sizes o f less than 10 boats. T h e 32 c o u n tie s w ith sa m p le s o f 30 o r m ore boats provide a m ore valid ba sis for e v a lu a tin g the allo c atio n m o d e ls (T able 17). F or those percent d iffe re n c e range from 1% for 32 counties, the R o s c o m m o n county to 5 1 % for M a ckinac county. For ele v e n co u n tie s the p ercent difference is 10% or less. T h e percent difference is m ore than 30 % for five counties. T h e percent d ifferen ce only indicates d isc repancy b e tw e e n m o d el estim a tes and direct su rv e y estim ates. It d o e s not indicate w h ic h e s tim a te is m o re accurate. For Table 17. N um ber o f Boats Stored in Counties; A Com parison o f Survey Estimates and Allocation Model Estimates. A llocation M odel Survey Resu lts3 D ifferenceb M arina S eco n d H om e Percent Difference1 W aterfront N onu aterfron t H om e H om e All S eg m en ts C o u n t i e s W i t h S a m p l e S iz e s M o r e T h a n 3 0 B o a t s A lle g a n 6 .4 9 3 7 .8 3 2 ( 52 ) -3 1 3 -6 5 6 -1 8 3 3 1463 -1 3 3 9 A lp en a 3 .7 8 4 3 .5 6 5 ( 31 ) 87 44 -3 0 4 39 2 219 A ntrim 6 .0 3 5 7 .9 2 4 ( 49 ) -1 1 8 6 -5 9 0 -8 8 0 768 -1 8 8 9 -24% 10% - 17% 6% A renac 4 .0 5 9 3 .6 9 9 ( 33 ) -391 535 530 -3 1 4 360 Bay 7 .6 0 6 7 .3 8 9 ( 117 ) -3 2 4 164 50 327 217 3% Berrien 9 .6 4 6 8 .7 2 6 ( 64 ) 591 634 987 -1 2 9 2 920 11% C h arlevoix 6 .8 7 2 7 .1 9 4 ( 75 1 937 -1 5 2 5 248 18 -3 2 2 C h eb oygan 6 .5 3 6 7 .8 5 7 ( 91 ) -4 7 3 -9 0 7 -2 5 3 312 -1321 -17% C h ip p ew a 4 .1 2 4 5 .2 6 3 ( 34 ) 622 -2 2 2 2 -4 4 506 -1 1 3 9 -22% D elta 4 .4 0 6 4 .1 9 4 ( 44 ) 6 1425 -5 6 9 -651 212 5% Em m et 6 .2 8 2 4.821 ( 73 ) -5 9 6 1784 781 -5 0 8 1461 30% G en esee 13.531 9 .3 0 4 ( 37 ) -2 6 0 244 2619 1624 4227 45% Grand T raverse 9 .0 3 2 8 .4 8 9 ( 72 ) -1 3 6 164 -1 8 3 698 543 6% H oughton 2 .2 8 0 2 .6 7 5 1 37 ) -6 9 528 -601 -2 5 3 -3 9 5 -15% -4% Iosco 8.2 1 8 7.3 4 3 ( 49 ) 546 243 77 9 875 12% Jackson 8.181 12.3 4 7 ( 33 ) -4 2 7 -6 2 8 -8 7 4 -2 2 3 8 -4 1 6 6 -34% K alam azoo 8 .432 1 1 .8 2 9 ( 36 ) -1 6 3 -1 1 0 6 -501 -1 6 2 7 -3 3 9 7 -29% Kent 1 8 .689 15.5 6 5 ( 50 ) 235 -44 3632 -6 9 9 3124 lx e la n a u 6.421 7.2 5 3 ( 80 ) -141 131 -1 0 4 0 218 -8 3 2 M ack in ac 5.5 1 2 1 1 .1 5 6 1 97 ) -1 2 3 -5 0 0 6 -1 1 2 6 611 -5 6 4 4 M acom b 2 7 .3 0 6 2 4 .9 0 4 1 116 ) 2472 -1 9 3 -1 8 7 8 2001 2402 10% M an istee 5.3 2 3 5 .9 5 7 ( 52 ) -1 0 2 1967 7*) -2571 -6 3 4 -11% M arquette 4 .5 0 8 5.111 ( 57 ) -2 8 3 99 -9 9 -321 -603 -12% M on roe 8 .8 1 6 9 .4 7 9 ( 45 ) 1332 308 423 -2 7 2 7 -6 6 3 -7% M u skegon 8.851 9 .2 2 5 ( 91 ) -9 3 8 -551 -2 9 2 1407 -3 7 4 -4% N ew a y g o 6 .1 3 7 10.151 ( 37 ) -91 -3 3 6 5 -3 3 6 -2 2 2 -4 0 1 4 -40% 20% -1 1% -51% O ak lan d 3 4 .1 1 7 2 7 .3 4 2 ( 54 ) -5 6 8 694 158 6491 6775 25% O ttaw a 1 3 .3 7 6 1 4 .3 4 6 ( 116 1 846 21 339 -2 1 7 6 -9 7 0 - 7® / 0 R oscom m on 8 .8 7 8 8 .9 2 5 ( 51 ) -2 8 2 561 -1 1 4 6 821 -47 St C lair 11.847 16.325 ( 85 ) -9 3 3 -501 -3 2 6 8 224 -4 4 7 8 5 .6 1 8 5.201 ( 41 I -2 7 8 21 846 -171 417 8° .1 3 3 .0 1 2 5 0 .2 7 5 ( 124 ) -2X71 386 4 '2 2 502 2739 9",, V an Buren W ayne -i% -27" » Table 17 (cont'd). A llocation M odel Survey Resu lts3 Percent Difference' DifTerenceb M arina S eco n d H om e W aterfront N onw aterfront H om e H om e A ll S eg m en ts C o u n tie s W ith S a m p le S iz e s L e ss T h a n 3 0 B o a ts A lco n a 5 .1 8 3 5.491 ( 22 ) 72 -1 8 6 -9 -1 8 6 -3 0 8 -6% A lger 1.255 2 .141 ( 13 ) -5 3 0 319 -7 8 7 113 -8 8 6 -4 1 0 o Baraga 1.038 445 ( 13 ) 61 256 189 87 593 133% Bam ' 5 .7 3 8 8 .2 4 6 ( 28 ) -1 5 6 -6 6 -2 1 6 6 -1 2 0 -2 5 0 8 -30% B en zie 4 .7 8 5 4 .5 0 3 ( 25 ) 552 -1 3 4 7 488 588 282 6% Branch 5 .0 8 8 4 .0 9 5 ( 14 ) 246 1668 -1 4 8 9 569 993 24% C alhoun 4 .5 6 3 4 ,5 1 4 ( 10 ) 100 -7 7 5 1201 -4 7 7 49 1% C ass 6.571 6 .8 9 3 ( 26 ) -3 1 7 975 -2 6 4 4 1664 -3 2 2 -5% Clare 6 .3 1 2 5 .3 3 3 ( 18 ) 78 952 30 3 -3 5 4 979 18% C lin lon 2 .4 9 5 2 .9 5 4 1 10 ) 2 41 -4 4 -4 5 8 -4 5 9 -16% Crawford 3 .2 2 8 3 .4 5 4 ( 15 ) 18 121 282 -6 4 6 -2 2 6 -7% D ick in son 3 .0 0 8 1 .5 2 0 1 10 ) 0 471 577 439 1488 98% 66% Eaton 3 .5 2 5 2 .1 2 2 ( 6 ) 2 132 366 903 1403 G ladw in 5.151 5 .5 3 6 ( 22 ) 63 -1561 493 620 -3 8 5 -7% G ogebic 1.844 7 03 ( 15 ) -4 35 2 681 112 1141 162% Gratiot 1.504 2 .8 1 3 ( 6 ) 7 95 -5 6 -1 3 5 5 -1 3 0 9 47% H illsd ale 3 .5 6 2 2 .0 8 9 ( 6 ) 56 412 32 972 1473 71% Huron 5 .6 4 6 5 .5 1 9 ( 25 ) 1021 -1021 131 -4 127 Ingham 7 .1 1 3 2 .8 9 2 ( 7 ) 1 311 2088 1822 4221 Ionia 2 .3 9 0 2 .1 9 2 ( 9 ) 13 -2 9 7 360 122 198 9% Iron 3 .5 1 6 3.211 ( 11 ) 0 124 372 -191 3 05 10% Isabella 2 .5 3 6 3 .6 8 4 ( 17 ) -1 0 5 -8 9 3 98 -2 4 7 -1 1 4 8 -31% Kalkaska 3 .I l l 1.555 ( 7 ) 54 974 579 -51 1556 100% 259 ( 7 ) 166 162 25 55 406 157% K ew eenaw 665 2% 146% Lake 4 .5 4 6 2 .7 4 3 ( 10 ) 30 1213 396 165 1803 66% Lapeer 3 .2 8 4 2.201 ( 8 ) 60 667 690 -334 1083 49% L enaw ee 5 .4 5 8 6 .1 9 7 ( 12 ) 76 164 -1 7 4 -805 -7 3 9 Livingston 7.731 1 0 .930 I 20 ) 456 -331 -3 3 3 7 13 -3 1 9 9 96 1 1 ) 0 211 364 193 768 L uce 864 M ason 5 .0 0 6 3 .6 1 4 ( 19 ) 673 -5 8 6 515 7X0 1392 M ecosta 4 .3 2 2 6 .6 0 9 1 28 ) -2 1 9 -2 2 5 0 -6 4 2 46 -2 2 8 7 M enom inee 2 .9 1 2 1.253 ( 27 ) 86 1677 566 -4 76 1659 -12".. - 29% 79 9 ",, 59 " - 35% 1 42 " . . Table 17 (cont'd). A llocation M o del D ifference11 Survey Resu lts3 M arina S eco n d H om e Percent Difference3 W aterfront N o n w aterfront H om e H om e All S egm en ts M idland 4 .0 2 8 6 .0 8 3 ( 16 1 14 -1 9 9 549 -2 4 1 9 -2 0 5 5 -34% M issau k ee 2 .3 0 5 3 .2 7 8 ( 12 ) -5 9 -5 -7 2 0 -1 8 8 -9 7 3 -30% M on tcalm 5 .4 1 8 6 .4 2 6 ( 20 ) 173 404 -580 -1 0 0 4 -1 0 0 8 -16% M on tm oren cy 3 .6 5 3 2 .5 7 0 ( 12 ) 164 674 174 7! 1083 42% O cean a 3 .9 4 6 2 .6 0 4 ( 11 ) 92 52 9 -4 7 76 8 1342 52% O gem aw 4 .5 3 4 3 .0 1 3 ( 18 ) 76 1474 229 -2 5 8 1521 50% 823 ( 10 ) 35 29 8 274 -4 8 8 119 14% O n tonagon 942 O sce o la 2 .9 4 4 3 .1 8 6 ( II ) 16 53 -1 3 5 -1 7 7 -2 4 2 -8% O sco d a 3 .0 6 6 1 .3 9 6 ( 6 1 19 1423 129 99 1670 120% O tsego 3 .4 7 8 3 .2 6 4 ( 10 ) 91 .5 -5 134 214 75 b Presque Isle 3.7 5 1 3 .5 7 4 ( 20 ) 160 271 -4 2 -2 1 2 177 5% S agin aw 6 .5 6 0 5 .5 9 6 ( 19 | -6 6 9 -411 228 1816 964 17% S anilac 3 .1 4 2 2.101 ( 14 ) -1 1 5 1265 -9 3 -1 6 1041 50% 357% S ch oolcraft 2 .5 3 4 555 ( 5 ) 31 1307 378 263 1979 S h ia w a ssee 2 .5 3 5 1.348 ( 4 ) 4 105 816 263 1187 885, St Joseph 5 .0 4 7 4 ,0 4 7 ( 12 ) 299 -2 4 -768 1492 1000 25% T u sco la 2 .5 6 7 4 .9 1 3 i 24 ) 87 4 -3 1 5 -2 1 2 3 -2 3 4 6 -4 8 5 , W ashtenaw 7 .1 5 9 12.585 ( 21 ) 250 -1 5 5 0 23 -4 1 5 0 -5 4 2 6 -43% W exford 3 .5 2 9 4 .1 8 2 ( 19 ) 42 -2 5 7 -1 7 7 -261 -6 5 3 -16% a N um b ers in the p arentheses are th e u n w eig h ted cou n t o f b oats in the storage cou n ts from the 1994 M ich ig a n B o a tin g Survey b. D iffere n c e is caculated as estim ates from a llocation m o d el substract the estim a tes from survey observed. c. Percent o f d ifferen ce is caculated as the d ifferen ce o v er the estim a tes from survey observ ed 90 M a ck in a c county, the m odel predicts h a lf as m an y b o a ts stored as the survey based e stim ates. T he p rim a ry difference is the allocation o f boats stored at second hom es. The allocation m odel estim a tes 3,922 boats stored at se co n d h o m e s in the cou n ty ( f a b le 14). c o m p a re d to the survey e stim a te o f 8,928 boats. T h e n u m b e r o f second h o m e s in M ack in a c co u n ty is estim a ted to be 4 ,0 3 9 (M ic h ig a n H o u s in g C ensus, 1990). T he survey e stim ate o f boats stored at second h o m e s is m o re than tw o tim es the n u m b e r o f second hom es. It ap p e ars that the m odel e stim ate is m o re rea so n a b le for M a ck in a c county. F or N e w a y g o county, the m odel estim a te o f the n u m b e r o f boats kept in the county is 4 0 % less than the survey estim ate. A gain, there is a m a jo r difference in estim a tes o f boats stored at se co n d h om es. T he m odel e s tim a tes 2 ,280 boats stored at s econd h o m e s in the cou n ty (T able 14), and the survey e s tim a te s 5,645 boats. It appears that the survey o v e re s tim a te s the n u m b e r o f boats stored at second h o m es. T h e estim ate o f 5,645 boats is h ig h e r than the e stim ate o f the n u m b e r o f bo a ts stored at second ho m es in R o s c o m m o n county, and R o s c o m m o n co u n ty has tw ice as m an y second h o m e s as N e w a y g o county. It is un lik e ly that there are m ore boats at se co n d h o m e s in N e w a y g o than R o s c o m m o n . N e w a y g o cou n ty has 5,0 5 7 second h o m es; 500 less than the n u m b e r o f boats e stim a ted by the survey to be stored at second hom es. B O A T D A Y S IN C O U N T IE S A trip g e n e ra tio n m o d el a n d a set o f trip d istrib u tio n m o d e ls are used to predict the n u m b e r o f bo a t days in co u n tie s by bo a ts in different ty p es o f storage. T h e m odels also pro v id e orig in -d e stin a tio n patterns o f b o a ts in storage se g m e n ts. A trip generation 91 m odel first e s tim a tes the n u m b e r o f boat days generated by bo a ts kept in each county . The trip distribution m odel then d istributes these days to de stin a tio n (use) counties. B ecause a lm o st all bo a t days by boats kept at w ate rfro n t h o m e s , second h om es, and m arin as in inland counties, o c c u r in the county w here they are kept, all boat days are distributed to these counties. H o w e v er, distinct tw o -ste p trip d istribution m o d els are required for bo a ts stored at m arin as in coastal c ounties and those stored at n o n w a te rlro n t hom es. Figure 7 graphically d e scrib es these m o d els (on p a g e 57). T h e p resentation o f the m o d e ls is div id e d into four sections: (1) trip generation m odel w h ic h predicts n u m b e r o f boat days generated by bo a ts kept in the counties. (2) trip distribution m odel for boats stored at m arinas in coastal counties, (3) trip distribution m odel for boats stored at n o n w a te rfro n t h o m e s , an d (4) the s u m m a tio n o f overall trip d istrib u tio n m o d els w h ic h e stim ate n u m b e r o f b oat days in the (destination) c ounties by boats in different storage segm ents. Trip G e n e ratio n M odel Model Specification and A ssum ptions T h e n u m b e r o f days gen e ra te d by boats kept in c o u n tie s is estim a ted by m ultiplying (1) the n u m b e r o f bo a ts in each size-storage se g m e n t by (2) the average n u m b er o f boat days for that segm ent. T h e generation m odel is fo rm u la ted as: II 1 (ils) W h e re T (1|S): = £ c= l B ( i|s .c ) * D (S|C) total boat days generated by boats kept in cou n ty i, given storage se gm ent s. B (1S CI: n u m b e r o f boats kept in co u n ty i. given storage se g m e n t s and boat size c. D (s!c»: average boat days generated by b o a ts in storage se g m e n t s. given boat size c. K stim ates o f the n u m b e r o f boats in size-storage s e g m e n ts for each cou n ty are p ro d u ce d by the prev io u s allocation m odel. E stim ates o f a v e ra g e bo a t days are based on the 1994 M ic h ig a n B oating S urvey (T a b le 18). A ve ra g e boat days range from 17 days for boats u n d e r 16 feet stored at n o n w a te rfro n t h o m es to 37 d a y s for 1 6 '-2 0 ' boats at w a te rfro n t h om es. M a rin a b o a ts are used m o st often, a v e ra g e o f 31 days. B oats stored at no n w a te rfro n t h o m es are used least frequently (1 7 days). T h e trip g e neration m odel a s s u m e s that the average n u m b e r o f boat days for each se g m e n t do e s not vary significantly a c ro ss counties. In o th e r w o rd s, spatial variation in av e rage boat days is e x p la in ed by the d iffe re n c es in the m ix o f d iffe re n t boat sizes and types o f storage. Results and Evaluation A p p r o x im a te ly h a lf o f all boat days are g en erated by b o a ts kept in the southeast and so u th -in la n d regions. A b o u t 30 p ercent o f boat days are by bo a ts stored at north inland, no rth w est, and n o rth e a st regions. B oats ke p t in the U p p e r P e n in su la generate 8% o f all boat days, f if te e n p ercent o f boat days are by boats at m arin as, 2 7 % by boats at second h o m e s , and the o v e r h a lf (5 8 % ) by boats stored at p e rm a n e n t w aterfront and n o m v ate rfro n t h o m e s (T a b le 19). A p p e n d ix D p rese n ts c o u n ty level estim ates. A n a ly sis o f v ariance is used to test for the va ria tio n s in bo a t days across regions, and variations ac ro ss siz e-storage segm ents. T h e tests are p e rfo rm e d to v a lid a te the use o f T able 18. A v erag e N u m b e r B o a t D ays by B o at S ize C lass and S to rag e Segm ent. Storage S eg m en t Boat Size A verage N u m ber Boat D ays 31.23 Afarina S eg m e n t 2 0 feet or s m a l l e r 3 0 .2 6 21 - 2 8 feet 3 0 .9 0 2 9 feet or larger 32.83 2 5 .0 7 S e c o n d H o m e S eg m e n t L e s s than 16 feet 22.83 1 6 - 2 0 feet 25.65 21 feet or larger 31 .5 9 30.4-1 W aterfront H om e S eg m en t 26 .9 0 L e s s than 16 feet 1 6 - 2 0 feet 36 .5 8 21 feet o r larger 2 8 .2 2 17.5S N onw a terfro n t H om e S eg m en t L e s s than 16 feet 1 7 .1 4 16 feet o r larger 1 8 .5 5 note : E s t i m a t e s are b a s e d o n t h e 1 9 9 4 M i c h i g a n B o a t i n g S u r v e y . 94 T ab le 19. N u m b e r o f B oat D ays G e n e rate d by S torage S e g m en t and S to rag e R egion. BO AT STORAGE SEGM ENT STORAGE REG IO N M arina Second H om e TOTAL W aterfront N o n w a te r fr o n t H ome Hom e (Percent) Southeast 805,102 112,923 62 4 ,673 542,688 2 ,0 8 5 ,3 8 5 17 .0 % C entral East 19 6 ,810 1 2 9 ,475 46,761 215,287 588,333 4.8% 90 ,9 4 6 42 2 ,7 4 3 16 6,309 1 1 0 ,3 5 1 790,348 6.4% Northw est 22 4 ,3 8 0 5 08.346 317,183 2 0 4 ,2 4 5 1 .2 5 4 ,1 5 4 1 0 .2 % Central W e st 147,586 1 2 4 ,0 2 1 7 8,867 2 47,534 5 98.009 4.9% 8 9,469 88,736 181,154 163,193 522.55 1 4 .3% S o u t h In land 1 5 2,077 6 57,365 1,5 4 2 ,4 2 3 1 ,5 4 6 ,7 3 4 3 ,8 9 8 ,5 9 9 31.7% N o r th Inland 46,381 8 21,574 394,621 2 9 8 ,391 1,5 6 0 ,9 6 7 12.7%, South U P 2 3 ,6 6 6 3 53,594 101,052 6 6 ,1 5 4 5 44,466 4.4%, N o r th U P 69.213 142,035 172,334 62,973 44 6 ,5 5 5 3.6%, 1 ,8 4 5 ,6 2 9 3 ,3 6 0 ,8 1 2 3 ,6 2 5 ,3 7 5 3 ,4 5 7 ,5 5 0 1 2 ,2 8 9 ,3 6 6 100.0%, 1 5 .0 % 27.3% 29.5% 28.1% 100.0% N ortheast Southw est Total (Percent) n o le: B e c a u s e c a s e s w it h m is s in g s to r a g e v a r ia b le s are e x c lu d e d fro m th e (s u r v e y b a s e d ) e s t im a t e s o f b o a ts in d iffe r e n t s to r a g e s e g m e n ts b y sto r a g e r e g io n s (T a b le 1 3 ) that are u se d to a llo c a te b o a ts to s to r a g e r e g io n s in th e a llo c a tio n m o d e ls , th e to ta l n u m b e r o f b o a ts e s tim a te d b y s to r a g e a llo c a t io n m o d e ls is le s s th an th e n u m b e r o f r e g is te r e d a c tiv e r e c r e a tio n a l w a tercr a ft ( 3 5 5 ,0 0 0 b o a ts). B e c a u s e th e e s t im a t e s b y trip g e n e r a tio n m o d e l are b a se d o n th e e s tim a te s d e r iv e d from th e a llo c a tio n m o d e ls , th e m o d e l e s tim a te d n u m b e r o f b o a t d a y s is le s s th a n n u m b e r o f b o a t d a v s ( 1 3 4 m illio n d a y s) re p o r te d in 1 9 9 4 R e c r e a tio n a l B o a t in g S u r v e y (S t y n e s e t al , 1 9 9 5 ) 95 state a v e ra g e boat days for different s e g m e n ts to e stim ate the n u m b e r o f boat days generated by the boats kept in counties. Probabilities o f the F tests at the end o f each c o lu m n indicate regional variations in average boat days for different storage (si/e ) segm ents. P ro babilities o f the F test at the end o f each ro w indicate the variations o f boat days ac ro ss the storage (size) se g m e n ts for d ifferent regions (T able 20). E x c e p t for b o a ts 21 "-28' stored at m arinas, there is no significant regional variation in boat days. B ased on this result, it is a c ceptable to apply state average boat days for each se g m e n t to estim a te n u m b e r o f boat days generated by bo a ts kept in the counties. T h e re arc significant regional va ria tio n s in boat days by bo a ts 2 1 2 8 ' stored at m arinas. The n u m b e r o f days ran g e s from 21 days in the northeast region to 58 days in the south IJP re g io n 24. T h e ave ra g e boat days (58 days) in south UP region significantly differ from the state a v e rage (31 days). T h is m ea n s that a p p ly in g the state average boat days to boats 21 ’- 2 8 ' stored at m arin as w o u ld und e re stim ate the total n u m b e r o f boat days g en erated in s o m e c o u n tie s (e.g.. south U P) and ov e re stim ate days generated in other c o u n tie s (e.g.. n o rth e a st region). E x c e p t for boats kept in the northern U P region, there are significant variations in b oat days across size-storage segm ents. T h is c o n firm s the assu m p tio n that variations in boat days are e x p la in e d by the d ifferences in boat storage type and boat size, not by the location w h e re the boats are kept. It also su p p o rts the ap p ro a c h o f app ly in g state average boat days for each siz e -sto rag e se gm ent to e stim ate the total n u m b e r o f boat days gen e ra te d by boats kept in the counties. :4 T h e e s t i m a te d a v e r a g e b o a t d a y s fo r 21 ’- 2 8 ’ b o a t s st o r e d at m ar in a s in th e inland so u t h r e g i o n is 6 0 d a \ s. T h i s e s t i m a t e is q u e s t i o n a b l e as it is b a s e d o n a s a m p l e o f o n l y f e w boats. 96 Tabic 20 V a riations in A v e ra g e Boat D ays by B oats W ithin S ize-S torage S egm ents and S torage Regions. BO AT STORAGE SEG M ENTS M a r in a S to r a g e 2 0 ’ or R egion les s Second Hom e 29' or 21 '-28' larger W a te rfr o n t H o m e 21' or < 16' 16'-20' larger Nonw aterfront 21' or < 16' 16'-20' larger Hom e 16’ or <16' larger : prob. Southeast 35 30 30 10 43 27 22 43 31 13 24 0.0 1 5 Central East 16 29 34 16 22 8 11 30 33 15 11 0.001 N ortheast 25 21 34 15 20 35 26 29 23 16 14 0 .0 0 6 N orthw est 27 25 34 31 24 33 24 34 30 20 20 0 .0 0 9 Central W e s t 40 25 36 15 28 28 15 24 27 18 18 0.001 Southw est 25 29 38 58 26 28 30 29 23 31 12 0.0 3 0 S o u t h In land 32 60 24 24 24 27 30 38 26 16 18 0.0 0 0 N o r t h In land 35 35 37 22 22 30 31 31 25 20 16 0.044 58 42 21 36 46 42 41 25 22 14 0.000 29 30 33 28 36 27 15 26 29 12 20 0.089 30 31 33 23 26 32 27 37 28 17 19 0 .0 0 0 0.4 9 0 0 .0 0 2 0 .1 0 2 0.1 6 9 0.8 9 6 0.0 8 9 0 .6 1 1 0.778 0.9 1 0 0 .1 7 9 0.159 South U P North U P NA Segm ent .1 v e r a g e F prob. 97 Trip D istribution M odel For B oats Stored A t M a rin a s In C oastal C ou n ties M odel Specification For e a c h (storage) county, three ty p es o f d e stin a tio n z o n e s are defined: (1) “ within c o u n ty ” zone, (2) “ nearby c o u n tie s ” zone, and (3) ’’m o re d ista n t” zone. T he “ within c o u n ty " zone is the (storage) county. T h e “nearby c o u n tie s ” are coastal c o u n tie s bordering the (storage) county. T h e “ m o re d ista n t” z o n e c o n sists o f co u n tie s o ther than those bo rd erin g the (storage) county. F or e x a m p le, for St. C lair county, the “ w ithin county" zone is St. C la ir county; the “ nearby c o u n tie s ” z o n e includes Sanilac and M a c o m b counties; and the “ m ore d is ta n t” z o n e includes all coastal co u n tie s o th er than St. Clair. M a c o m b and S anilac counties. T h e regional d istrib u tio n o f boat days w ith in d e stin a tio n z o n e s w a s estim ated based on the 1994 M ic h ig a n B o a tin g Survey. M o st (8 3 % ) o f the bo a t days generated by bo a ts stored at m arin as in coastal co u n tie s are w ith in the c o u n ty w h e re the m arina is located, 10% in the “ne a rb y c o u n tie s ” zone, and the re m a in in g 7 % in the “ m o re distant" zone. O v e r 8 5 % o f boat days g en erated by boats kept in the U p p e r P eninsula, northeast, and n o rth w e s t reg io n s are w ith in the c o u n ty w h e re the b o a ts are kept. B oats kept in the central-east, c e n tral-w est, and n o rth east regions are m o re likely to take lo n g er distance trips. M o re th an 9 % o f boat d ay s generated by boats in th ese regions are in the “ m ore d ista n t” zone (T a b le 21). T h e e s tim a te d regional d istrib u tio n is used to distrib u te boat days generated by bo a ts in each storage co u n ty to on e o f the d e stination zones. F or e x a m p le, the southeast r e g io n ’s distrib u tio n is used for St. C la ir county. E ig h ty -o n e percent o f boat days 98 T a b l e 21 D istr ib u tio n o f B o a t D a y s b y D e stin a tio n Z o n e and S to r a g e R e g io n : M arin a S e g m e n t. D E ST IN A T IO N Z O N E S " W ithin C o u n ty " Z o n e "N earby C ounties" Z o n e " M o r e Distant" Z o n e Southeast 8 1.09% 12.37% 6 .54% C e ntr al East 77.4 7 % 6 .12% 16.42% N ortheast 86.0 8 % 4.96% 8.96% N orthw est 88.42% 7.25% 4 .3 2 " o Central W e s t 77.87% 13.00% 9.13% Southw est 8 4 .99% 7.64% 7.36% South U P 9 5.1 2 % 1.1 9 % 3.69% N orth U P 91.2 8 % 6.23% 2.49% Total 82.5 8 % 10.04% 7.38% Storage R e g io n s note: E s t i m a t e s are b a s e d o n the 1 9 9 4 M i c h i g a n B o a t i n g S u r v e y . 99 g enerated by b o a ts stored at m arin as in St. C lair cou n ty are d istributed to the St. Clair county. 12% to M a c o m b and Sanilac c ounties in “ nearby c o u n tie s " zone, and the re m a in in g 7% to o th e r c oastal c ounties in “ m o re dista n t" zone. Several m e a s u re s o f a c o u n ty 's bo a tin g o p p o rtu n itie s are used to distribute boat days to the c o u n tie s w ith in a destination zone. T he length o f G reat Lakes sh o relin es is used as an indicator (S L indicator) o f bo a tin g opp o rtu n itie s w ith in the “ nearby counties z o n e ." 25 T he “ n u m b e r o f transient slip s” and “ n u m b e r o f tra n sie n t nights in state- operated m a rin a s " are co m b in e d into an cruising o p p o rtu n ity index (CP index) to d istribute boat days to the co u n tie s w ithin a “ m ore d ista n t" z o n e 26. T he “ cruising o p p o rtu n ity ” index is c o n stru c te d as follow ing: CP, = W h e re 25 1/2 *(Nightj + Slipj) * W (j,r, the c ruising opp o rtu n ity index for county i; Night,: sta n d a rd iz e d transient nights in county i27; Slipj: sta n d a rd iz e d transient slips in county i; and W , i | r): the w e ig h ts assigned to cou n ty i. given region CPji r . In fo r m a t io n o n m i l e s o f G re a t L a k e s s h o r e l i n e s in c o u n t i e s c o m e s fr om M i c h i g a n T o u r i s m R e s o u r c e D ata b a se (Spotts, 1995). 2<’ T h e n u m b e r o f transient s l i p s in c o a s ta l c o u n t i e s w a s c o l l e c t e d b y t h e 1 9 9 4 G re a t L a k e s M arin a C e n s u s . T h e n u m b e r o f tran sie n t n ig h ts at s t a t e - o p e r a t e d m a r in a s in c o a s t a l c o u n t i e s w a s c o l l e c t e d by the M i c h i g a n D e p a r t m e n t o f N atu ra l R e s o u r c e s . 27 S t a n d a r d iz e d b o a t i n g o p p o r t u n i t y is c a lc u l a t e d a s the a m o u n t o f b o a t i n g o p p o r t u n i t i e s in the c o u n ts d i v i d e d b y the state a v e r a g e . 2S T h e w e i g h t s a s s i g n e d to c o u n t i e s initially are b a s e d o n th e a s s u m p ti o n that c o u n t i e s in north ern M ic h i g a n are m o r e a ttrac tiv e t o l o n g - d i s t a n c e b o a t i n g trips, g i v e n t h e s a m e b o a t i n g o p p o r t u n i t i e s . T h i s is s u p p o r t e d b y the ha b itu al “ s o u t h - t o - n o r t h ” b o a t i n g pattern s d e s c r i b e d in m a n y p r e v i o u s b o a t in g s tu d ie s . A f t e r s e v e r a l c a lib r a t io n s, the final w e i g h t s are “ 3 ” fo r c o u n t i e s in U p p e r P e n in s u la , n o r t h w e s t , c e n t r a l - w e s t , and s o u t h e a s t r e g i o n s , “ 2 ” for c o u n t i e s in s o u t h w e s t r eg io n , an d “ 1” for c o u n t i e s in c e n t r a l- e a s t an d nor the ast r e g i o n s . T h e r e are t w o r e a s o n s for a s s i g n i n g w e i g h t " 3 ” to c o u n t i e s in th e s o u t h e a s t r e g io n . First, 5 4 % o f all m a r in a s p a c e s are p r o v i d e d in s o u t h e a s t r eg io n . A p o r tio n o f s e a s o n a l s p a c e s w o u l d a l s o b e u s e d by transient b o a t s i f t h e y are not r en ted for the s e a s o n . T h e r e f o r e , the c o m b i n a t i o n o f transient n ig h ts at s t a t e - o p e r a t e d m a r in a s and the transient s l i p s in t h e c o u n t y u n d e r e s t i m a t e s th e c a p a c i t i e s o f t h e c o u n t i e s in s o u t h e a s t r e g i o n to p r o v id e transient b o a t i n g use. S e c o n d , travel d i s t a n c e is not in c lu d e d in th e c r u is in g o p p o r t u n it y in d e x , and th e 4 3 % o f m a r in a b o a t s are kept in s o u t h e a s t r e g i o n . A s s i g n i n g a w e i g h t o f 3, to the c o u n t i e s in th e s o u t h e a s t r e g i o n m a y s i m p l y r efle c t the e f f e c t s o f travel d i s t a n c e an d the m a s s o f c o u n t y ’s population. 100 T he d istrib u tio n s o f b o a tin g o p p o rtu n ity in d ices are p ro v id ed in A p p en d ix C. T hey s h o w a c o u n ty 's a ttractiveness as a bo atin g destination. T hey are used to distribute b oat days into (destination) co u n tie s w ithin different d e stination zones. T h e follow ing c o u n ty level d istribution fo rm u la is used: T(i|/)= U, X Ui i g D e s tin a tio n z o n e Z w h e re T (j|Z) : n u m b e r o f boat days in cou n ty i, given d e stin a tio n z o n e z; U, : availability o f bo a tin g op p o rtu n itie s in cou n ty i. Ui = the m iles o f G reat Lakes sh o relin es in the cou n ty for " n e a rb y c o u n tie s " zone. Uj T h e v alue o f C P index (c o m b in a tio n o f n u m b e r o f transient slips and transient nights) in the co u n ty for " m o re distant" zone. note: the fo rm u la distributes a share o f boat days to each co u n ty in the destination z o n e in p ro p o rtio n to its share o f total b o a tin g op p o rtu n itie s in the zone. A ssum ptions T h e trip d istrib u tio n m odel for b o a ts stored at m arin as in coastal co u n tie s is based on three basic assu m p tio n s. (1) T h e d istributions o f boat days w ithin the three d e stination z o n e s for each (storage) region are reliable. (2) T h e d istribution o f G reat L akes shoreline c a ptures the d istrib u tio n o f boat days w ithin the " n e a rb y c o u n tie s ” d e stination zone. (3) T h e d istribution o f the c ruising o p p o rtunity index reflects the n u m b e r o f boat days in c o u n tie s w ithin the " m o re d ista n t” d e stination zone. In other w ords, the n u m b e r o f boat days attributed to lo n g -d ista n c e c ruising trips is a function o f the destination c o u n ty 's c ruising o p p o rtu n ity index. O ther factors, such as distance and directions do not have a significant impact. Results I able 22 s u m m a riz e s the results from the trip distribution m odel for boats stored at m arinas in coastal counties. A b o u t 5 7 % o f all boat days by b o a ts stored at m arinas in coastal co u n tie s take place in southeast an d central-east regions. S ix te e n percent are in M a c o m b county, w h ic h is m o re than the total n u m b e r o f m a rin a bo a t days in any o f the o th er regions. T able 22 also sh o w s the ratio o f the n u m b e r o f bo a t days rec e iv e d in co u n tie s to the n u m b e r o f d ays generated by boats stored at m arinas located in the counties. Ratios g reater than one indicate that the region is a net im p o rte r o f boat days. R egions with ratios less than one arc net exporters. The southeast, east-central, and central w est regions are “ net e x p o rtin g " regions. T he o th er regions are “ net im p o rte rs," especially northeast, northw est, and U p p e r P e n in su la regions. T he net flow s c o n firm the south-to-north bo a tin g (use) travel patterns. T able 23 presents the origin (storage location) - d e stination (use location) m atrix for bo a tin g by boats stored at m arin as in the coastal counties. O v e r 9 0 % o f boat days in southeast, central-east, and c e ntral-w est regions are by boats stored at m arin as w ithin the sam e region. T h e so u th e a st region receives 766,000 boat days. A b o u t 9 7 % o f them are by boats kept in the region, 1.2% are by bo a ts kept in th e c e n tral-ea st region, and the re m a in in g 1.4% are by boats kept in o th e r regions. C o m p a ra tiv e ly , less boat days in northeast, n o rth w e s t and U P s o u th regions are by bo a ts kept w ithin th o se regions. The 102 T able 22 B o a t D a y s by C o u n t y o f O r i g in ( S t o r a g e ) a n d D e s t in a t io n (U s e ); M a r i n a S e g m e n t. C o u n tie s /R e g io n s M acom b T o ta l B o a t D a v s b v C o u n ts ' o f T o ta l B o a t D a v s b v C o u n ty o f D e s tin a tio n " O r ig in ( S to r a g e )h (A) (B ) P e rc e n t 16 4 % ) R a tio ( A )/(B 1 3 0 0 .0 7 7 1 5 4 .4 6 9 9(1% 1 5 3 .2 7 7 1 9 7 .2 7 8 1114"., 99 " 005.102 95% ( M o n ro e 2 (19.454 1 42.99(1 S t ( la ir 1 5 8 .7 8 4 W ayne S O C T H E A S T R E G IO N 1 9 4 .3 6 8 7 4 5 .5 9 5 ( ( 11 8% ) ( 46.5% ) 8 7 .8 7 7 ( 5 3% 1 1 1 1 .8 0 9 79% 4 5 .2 5 3 ( ( 2 .7 % ) 0 2% ) 5 3 .8 7 4 84" „ 3 .4 8 8 78" n ( 1 6% 1 3 .9 5 0 194"',, I 0 l" „ , H ay H u ro n S a g in a w S a n ila c ( 2 .7 3 2 2 7 .0 2 9 8 7% ) 9 6% ) ) 9.3% 1 3 .8 3 9 ( 0 8% ) 1 3 .6 9 0 / 7 4 , 710 ( 10.7% ) 196,010 90% A lc o n a 4 .3 8 8 ( 0 3% 14 6 % A lp e n a ( A re n a c 7 .5 2 1 2 4 .7 4 8 ( 0 5% I 1 5% ) 3 .0 0 6 6 .9 0 4 2 1 .6 3 5 1 14% C heboygan 2 4 .4 0 1 ( 1 5% 1 2 1 .6 9 5 1 12",, Io s c o 29.2(iO 1 0 .4 2 4 ( 1 X% I ( 0 6% 3 0 .2 0 6 7 .4 9 9 9 7 " ,, 1 .39" „ 90,946 III", , T u s c o la ( K N T R A I. E A S T R E G IO N I’r e s q u e Isle 1 1 109% 100,742 < 6.1% ) A n trim 9.19(1 ( 0 6% ) 7 .4 4 0 1 2 4 “ ,, B e n / ie 27.77(1 ( C h a rle v o ix ( 2 4 .7 1 6 6 0 .9 5 0 1 12% 10 7 ",, 1u n m e t (iS .4 (il 29 .1 18 1 7% ) 4 ()“ „ ) ( 1 8% ) G ran d T ra v e rse 1 5 .2 5 7 ( 0 9% ) 2 3 .8 3 3 11 ,9 3 8 12 2 ",, 1 2 8 “ ,, 1.e e la n a u 4 0 .5 0 7 M a n is te e M ason 3 9 .0 9 7 ( ( 2 5% ) 2 4% ) N O R T H E A S T R E G IO N N O R T H W E S T R E G IO N 2 6 .8 0 6 ( 2S.1.H06 ( 1 2 2 ",, 3 8 .7 5 6 102'!,, 2 3 .5 3 9 1 14% 15.4% ) 224,380 113",, 5 2 ,6 1 3 3 ,7 2 6 1 6% 1 M u sk e g o n 5 0 ,8 9 0 ( 3 1% ) ( Ic e a n a 8 .7 8 2 8 1 .0 1 8 ( ( 0 5% 1 4 9% ) 140,690 < 0.5% ) A lle g a n 2 5 .5 1 2 ( B e rrie n 4 4 .9 6 7 2 4 .9 8 7 ( V an B u ren S O I 1 IIW E S 1 R E G IO N ( llla w a 3 3 .2 0 7 9 1 ,2 4 6 9 7 " ,, 2.36",, 89" „ 147,506 95",, 2 0 .3 5 8 125",, ( 1 5% 1 2 7% 1 1 5% ) 9 5 .4 4 4 ( 5.0°,, > 09,469 7.1 33 0 4% ) 5 .6 6 4 126% 2 2 .5 5 6 ( ( I 4% 1 11 .555 19 5 ",, M e n o m in e e 6 .3 4 2 ( (1 4 % ) 5.461 S c h o o lc ra f t 1 .5 0 7 ( 0 1% 1 986 1 16 “ „ 1 5 3 “ ,, 5 7 ,5 5 # W E S T C E N T 'R A E R E G I O N D e lta M a c k in a c 5 0 .1 5 6 9 0 ” ,. 1 8 .955 1.32",, 1 07",, ( 2.3% 1 23,666 2 .4 9 7 1 0 ,1 4 4 ( < 0 2% ) ( G o g e b ic 3 0 .0 9 3 2 .7 2 4 0 6% 1 8% 1,844 1 0 .0 1 9 1 lu u g h to n 1 1 .1 0 6 ( ( 0 2% 1 0 7% ) K ew eenaw 7 ,0 1 4 ( 0 4% ) l.u c e M a r q u e tte 191 1 0 0% 1 ( 0 6% ) S O I 1 11 C 1 T E R P E N T N S l 'E A A lger B a ra g a C h ip p e w a O n to n a g o n N O R T H I 'P P E R P E N I N S l 'l . A TOTAL 10.21 1 1 ) 2 7 .1 0 7 2 .5 2 0 159",, 135% 101% 1 1 1% 9 ,6 5 0 5 .2 8 6 ll ) 8 “ „ 1 15% 133%, 0 10,2 0 4 10 0",, NA 2 ,6 4 2 ( 0 2% ) 2 ,5 8 2 102% 76,623 < 4.7 % ) 69,213 111",, 1 .6 4 7 ,1 7 1 1 100% ) 1 ,6 4 7 ,1 7 1 1(111% a T o t a l n u m b e r o f b o a t d a y s in t h e c o u n t i e s w h e r e t h e b o a t s a r e u s e d b T o t a l n u m b e r o f b o a t d a y s g e n e r a t e d by b o a t s k e p t m t h e c o u n t i e s . n o te B e c au s e ca se s w ith m issing storage variables are ex c lu d ed from the (survey based) estim ates o f boats m different storage s e g m e n t s b y s t o r a g e r e g i o n s ( f a b l e 13 ) t h a t a r e u s e d m t h e a l l o c a t i o n m o d e l s , t h e n u m b e r o f b o a t s e s t i m a t e d by s t o r a g e a l l o c a t i o n m o d e l s is le ss t h a n t h e n u m b e r o f r e g i s t e r e d a c t i v e c r a t l ( 5 5 5 , 0 0 0 b o a t s ) B e c a u s e t h e e s t i m a t e s by t r i p d i s t r i b u t i o n m o d e l a r e b a s ed o n th e e s tim a tes d eriv e d from the g e n e ra tio n a n d allo ca tio n m o d els, the model e s tim ate d n u m b e r o f b o a t d a s s w o u l d b e l o w e r t h a n to ta l n u m b e r o f b o a t d a y s r e p o r t e d in 10 ^ 4 K e e r e a t i o n a i B o a t i n g S u r v e y (Sty li es el al . I ) Table 23. N um ber o f Boat Days by Storage Region and Destination Region: M arina Segment. B oat Days R E G IO N S OF S T O R A G E D E S T IN A T IO N Central Southeast R E G IO N S Central East Northeast N orthw est West Southw est South UP North UP 7 4 5 ,3 9 3 8 .88 4 2 .2 0 9 2.801 3 .7 9 0 1.806 242 470 Row pet. 9 7 .4 % 1.2% 0 .3 % 0 .4 % 0 .5 % 0 .2 % 0 0% 0.1%, Column pet. 9 2 .6 % 4 .5 % 2 .4 % 1.2% 2 .6 % 2 .0 % 1.0% 0 “% 14,141 1 60,047 919 493 667 318 43 83 8 .0 % 9 0 .6 % 0 .5 % 0 .3 % 0 .4 % 0 .2 % 0 .0 % 0.0%, 0 . 1%, South East Central East Row pa. C olumn p a North East Row pet. Column pet. 8 1 .3 % 1.0% 0 .2 % 0 .5 % 0 .4 % 0 .2 % 8,065 8 2 .2 0 9 1.478 1.471 701 94 6 .5 % 8 .0 % 8 1 .6 % 1.5% 1.5% 0 .7 % 0 .1 % 0 .2 % 0 .8 % 4 .1 % 9 0 .4 % 0 .7 % 1.0% 0 .8 % 0 .4 % 0 .3 % 18.737 9 .51 3 2 .9 5 0 215.361 4 .4 4 6 2 .0 0 7 269 522 182 Row p a 7.4% 3 .7 % 1.2% 8 4 .9 % 1.8% 0 .8 % 0 .1 % 0 .2 % Column p a 2 .3 % 4 .8 % 3 .2 % 96 0 % 3 .0 % 2 .2 % 1.1% 0 .8 % 5 .3 7 0 2.726 704 1.767 128.383 1.514 Row pet 3 .8 % 1.9% 0 .5 % 1.3% 9 1 .3 % 1.1% 0 .1 % 0 1% Column pet 0 .7 % 1.4% 0 .8 % 0 .8 % 870% 1.7% 0 .3 % 0 2% 3 ,8 85 1.972 509 646 Row pa. 4 .1 % 2 .1 % 0 .5 % Column pa. 0 .5 % 1.0% Central West South West South U P 77 150 6 .3 4 9 81.941 0 .7 % 6 .'% 8 5 .8 % 0 .1 % 0 .1 % 0 .6 % 0 .3 % 4 .3 % 9 1 .6 % 0 .2 % 0 .2 % 661 2 2 ,7 0 8 1,649 56 108 6 .1 6 8 3 .1 3 2 80 8 1.025 1.387 Row p a 1 6 .4 % 8 .3 % 2 .2 % 2 .7 % 3J% 1.8% 6 0 .5 % 4 .4 % Column p a 0 .8 % 1.6% 0 .9 % 0 .5 % 0 .9 % o .~ % 9 6 .0 % 2 .4 % 4 .8 6 6 2 ,4 7 0 638 809 1.094 521 Row pet 6.3%, 3 .2 % 0 .8 % 1.1% 1.4% 0 .7 % 0 .2 % 86 2%, Column pet 0.6%, 1.3% 0 . '% 0 .4 % 0. ~%, 0.6%, 0. 7% 95.4%, 8 0 5 .1 0 2 196.810 9 0 .9 4 6 2 2 4 .3 8 0 147.586 8 9 .4 6 9 2 3 .6 6 6 69,213 48.9% , 11.9%, 5.5%, 13.6%, 9.11%, 5.4%, 1.4%, 4.2%, North U P Total tpercentI 177 6 6 ,0 4 9 (pa.> 76 5 ,5 9 5 4 6 .5 % 17 6,710 10%%, 100.742 6.1%, 2 5 3 ,8 0 6 15.4%, 14 0,690 8 .5 % 9 5 ,4 6 6 5 .8 % 3 7 ,5 3 8 2 .3 % 76,6 2 3 4. ~%, 1.647.171 103 North West 1 .8% 6.542 Total 104 northeast region receives 101.000 boat days. A b o u t 8 2 % are by boats kept w ithin the region. 15% by bo a ts in s o u th e a st and central-east regions, and the o th er 4 % by boats kept in o ther regions. T h e origin - destination m atrix also reveals s o m e potential p ro b le m s associated with d istrib u tin g bo a t days to c o u n tie s in the “ m o re d ista n t" z o n e w ith o u t incorporating the im pact o f travel distance. F o r e x a m p le . 16% o f bo a t days (6 .0 0 0 days) in the south U P region are by boats kept in the so u th e a st region. O nly 5 % (1 .8 0 0 days) are by boats kept in the n o rth east an d n o rth w e s t regions. It is q u e s tio n a b le w h e th e r b o a ts kept in the southeast region w o u ld a c c o u n t for three tim es m o re bo a t days than boats kept in northeast and n o rth w e s t regions, given that these reg io n s are m u c h closer. H ow ever, the so u th e a st region is a m a jo r e x p o rte r o f boat days to n o rth e rn regions in clu d in g the U pper Peninsula, so it is possible. Model Evaluation T h e d istrib u tio n m odel is ev a lu a te d on its ability to d istribute boat days (1) first to de stinatio n z o n e s and (2) then to counties. E stim ates from the tw o steps are evaluated separately. T h e p e rcentage o f bo a t d ay s w ithin each d e stin a tio n z o n e by (storage) regions is e s tim a te d fro m the 1994 M ic h ig a n B oating Survey. T h e m o d e l uses these e stim ates to distribute boat days to de stin a tio n zones. S a m p lin g errors are ca lc u la te d for the estim ated distribution. T h e s a m p lin g e rrors indicate the range o f ac cu ra cy for n u m b e r o f boat days in the d e stin a tio n zone. T h e e s tim a tes o f n u m b e r o f bo a t days in re g io n s/c o u n tie s are e v aluated by c o m p a rin g the distrib u tio n m odel estim a tes and direct survey estim ates. 105 T abic 24 p ro v id e s e stim a ted sa m p lin g errors at a 95 p ercent co n fid e n ce level for the e stim a ted d istribution o f bo a t days by (storage) regions. Tor e x a m p le, the m odel e stim ates that 8 2 .6 % o f all boat days by boats stored at m arin as in coastal c ounties occur in the “w ith in c o u n ty ” d e stination zone. T h e sa m p lin g error for this estim a te is 2.4% at the 9 5 % co n fid e n ce level. T h erefore, at the 9 5 % c o n fid e n ce level, the p e rcentage o f m arin a boat days o c c u rrin g at the “ w ithin c o u n ty ” de stin a tio n z o n e is b e tw e en 8 0 % to 85%. M o st o f the s a m p lin g errors are a ro u n d 5%. T he largest s a m p lin g errors (1 0 -1 3 % ) are in the south IJP region due to the sm all sam ple size (50 boats). B e c a u se o f these large s a m p lin g errors, the e stim ated d istrib u tio n o f m arin a boat days w ithin destination zones in the south U P region is less reliable than for o ther regions. T h e 13% s a m p lin g error at a 95 percent c o n fid e n c e level m e a n s that the n u m b e r o f boat days in the "w ith in c o u n ty ” zone c o u ld range from 19.000 days (8 2 % ) to 2 3 .6 6 6 days (1 0 0 % ) for boats kept at m arinas in the s o u th U p p e r P e n in su la region. T h e second stage o f th e ev a lu a tio n is an e x a m in a tio n o f the m odel p ro duced estim a tes o f n u m b e r o f boat days in counties. T h e m odel e s tim a tes are c o m p a re d with survey b ased estim ates. Two types o f m odel e s tim a tes (A an d B) are m ade, d e p e n d in g on the form o f m odel input: (1) survey based e stim ates o f boat days g e n e ra te d by boats kept in c ounties (m odel e stim a tes A ), and (2) estim a tes o f boat days in the storage counties p ro duced by the trip g e neration m o d el (m odel e stim a tes B). The m a rin a boat days allo c atio n m o d el, m a rin a trip g e neration m odel, and m arin a trip d istrib u tio n m odel are linked together. T h e n u m b e r o f boats stored at m arin as in Table 24 M arina Boat Days by Storage Region and Destination Zone: Sampling Errors at A 95% Confidence Interval. S T O R A G E R E G IO N S DESTIN ATIO N ZO NES Southeast Central East Northeast N orthw est Central West ALL Southwest South UP Notth UP S a m p li n g E r r o r at 9 5 % C o n f i d e n c e In ter va l "Within County" Z o n e 5.1 7% 6.47% 7.13% 5.30 % 6.51% 7.68% 12.93% 8.97% 2.40% "Nearby Counties" Zone 4.66% 4.62% 5.37% 4.2 6 % 5.39% 6.34% 9.62% 7.48% 1.96% "More Distant" Zone 3.83% 6.03% 6.89 % 4 .7 6 % 5.58% 6.64 % 10.65% 7.12% 2.08% D is tr ib u t io n o f B o a t D a y s in D e s t in a t io n Z o n e s "Within County" Z one 81 .1% 77.5% 86.1% 88.4% 77.9% 85.0% 95.1% 91.3% 82.6% "Nearby Counties" Zone 12.4% 6.1% 5.0% 7.3% 13.0% 7.6% 1.2% 6.2% 10.0% 6.5% 16.4% 9.0% 4.3% 9.1% 7.4% 3.7% 2.5% 7.4% 805.102 196.810 90,946 2 2 4 .3 8 0 147.586 8 9.469 23.666 69.213 l.64~l~l 354 228 188 341 225 162 50 114 1662 "More Distant" Zone No. o f B oat Day s No. o f S am ples 107 c ounties e stim a ted by the m arin a bo a t allocation m odel is an input to the trip generation m o d e l. T h e n u m b e r o f boat da y s g en erated by boats kept in c o u n tie s e stim ated by the trip generation m o d el is an input to the trip d istribution m o d e l. T he potential prob lem a ssociated w ith c o n n e c tin g the set o f m o d e ls is that the system atic errors p ro d u ce d by one m odel can carry o v e r to the ne x t m odel. In o rd e r to in d ep e n d e n tly e v aluate the pe rfo rm a n c e o f the trip d istrib u tio n m odel w ith o u t a c c u m u la te d errors (influences) c ontributed by o ther m odels, su rv ey-based e s tim a tes o f boat days by bo a ts kept at m arinas are also used as the initial inputs to the trip d istrib u tio n m odel. T h e p ercent difference b e tw e e n m o d el e stim a tes (A ) and direct survey estim ates range from 1% in M o n ro e cou n ty to 1730% in S c hoolcraft county. O nly one boat w as sa m pled in S c h o o lcra ft county, so the su rv e y-based estim a te is quite unreliable. T w enty one o f 42 coastal c ounties have sam ple sizes o f less than 30 boats. O n ly 21 co u n tie s have sam ple sizes greater than 30 boats. M ost co u n tie s w ith m ore than a 100% percent d ifference b e tw e e n the tw o e s tim a te s have a s a m p le size o f less than 30 boats. T h e tw e n ty -o n e c o u n tie s w ith sa m p le sizes greater than 30 boats p ro v id e a better basis for e v a lu a tin g the trip d istrib u tio n m odel (T able 25). F o r all o f these counties, the percent d iffe re n c e b e tw e en direct survey estim a tes and m odel e s tim a tes (A) are 2 0 % or less, a n d for tw o thirds o f them the difference is less than 10%. T h e m o d el e stim ates (A) are 2 0 % less th an direct survey estim a tes o f the n u m b e r o f bo a t days in H u ro n and Iosco counties. T h e trip distribution m odel for boats kept at m arin as in coastal co u n tie s p e rform s reasonably w ell for c ounties in the southeast, northeast, no rth w est, and so u th w e st regions. 108 Tabic 25 M arina Boat Days by C ounty o f Destination; A C om parison o f Survey and M odel Estimates. N l ’M B E R O P B O A T D A Y S S u r ve y E stimate M o d e l E stimate M o d e l Input from 1994 Survey* RL Cd ON/ C'Ot M Y M o d e l Input f t o m I rc v i o u s M o d e l Percent No ( a s cs (A) Percent Dif fe re nc e' ! D ifl cr cnc c' 128 1.047.17! N m t h w c s l R e gi on ( ential W est R e g io n C ounty "6.%S95 «?""'• 237,932 / IM S I"i, ioo. 1*0 253.806 -I": 5% 9.5 jr ■is. f.rn ;-/% 3 ~ 53.V "V.2'/V I"., " 6 ,6 23 1 .6 47 ,1 71 0*0 8% -J U O .ftW I H ll. 414 1 .0 47 . | 7 | IS",, O'S. l e v e l L s t u n a l c s L o r C o u n t i e s W i th S a n p i c S i z e s l a r g e r T h a n 3 0 He a l s Al leg an 32.250 At cnn c 34.478 98.719 Bay B cm cn ( ' ha il cvo ix 30.525 40.090 48 39 3 0 .5 1 3 -5% 25.512 3 1 ,5 8 4 • 8% 24.748 - 2 1*.. -28'-n 108 91.803 -7 no 87,877 -11% 45 3 7 .4 0 3 44,967 05 4 2.878 2 3 410 6.3% 7*'o 9*o 6 5 .4 6 1 24 .4 0 1 -1 7*0 -l " o 9*n 29.1 18 -34*., 15.257 -20% 4 5.233 -12",i 135"o ( 'he bt n gan 29.242 55 32.017 Emmet 4 3.807 00 43.517 ( ha nd I ta v c ts c I luion 1 7 .3 3 0 35 1 8 .8 0 7 1 9 .4 3 0 34 ItlSCO 1 2 .3 3 0 45 1 5 .5 0 7 9.899 l.cclan au 38 .2 8 1 73 40.424 -20% 6*o 40,507 M ac ki n ac 33,222 204.719 54 89 30.094 9*o 22,556 2 2 9 .7 2 1 12*« 2 6 9 . 4 51 Marquette 21,442 34 21.903 2*o M an is tee 40,840 37 -3*o 45 -1*0 10,2 1 1 39.697 142.990 -52*,, -15% 1 0 9 .1 4 4 45,435 1 0 8 .4 7 0 84.805 82 71.784 -15% 50,890 -40 *o O tta w a 55.490 80 88 l7* o -7*0 46*0 238,070 04.938 220.617 81.018 St Cla n 1 5 8 .7 8 4 - 35 *0 19*o 2 4,987 -11% -l3*o 1 9 4 ,3 6 8 -2 8 *o 205*o Macomb Momoe Muskegon V an B ut cn Wayne 2 8,143 39 3 3.497 2 71,428 99 237.33 1 29.260 l37*o *,. 6 -32*,. 5 2* o 5|*o C o u n t y L e v e l E s t i m a t e s L o r C o u n t i e s W ith S a m p l e S i z e s S m a l l e r T h a n 31) B o a t s 10 7 2.257 56*«> 4,388 10.070 1. 4 4 7 10 .1 43 1*0 2.497 -75 *o A lp en a 2 .Ilo 13 3.255 54% 255*o Anti im 25,072 13.507 27 23.340 -7°0 7.52 1 9,190 13 13.871 2uo 1 0 .1 4 4 -25* o 19 . 7 8 5 20 -25% 27.770 20 14. 80 4 15,91 1 -10“o 30.093 40*,, 59% 21 8,220 4 1, 8 4 8 29% 22% 7.133 2 .7 2 4 l2*o 79*,, 11, 97 2 2. 3 61 5 6 no 1 1. 1 06 45*o -50% 50 *o 8,720 NA I 3 8 u0 7.014 191 26,806 632*o 3.706 8,327 3l*u 50*o 6.342 8 .7 8 2 l2l*o SH% I97*.. Alcona Algci B a iu g a B en /ie C h ip p cw a De lla 18,900 0.389 (iogebic 1.521 1l o ug h to n Keweenaw 4,679 Luce 7,65 1 • Mason 3. 66 1 M enom inee O ce a n a 2.865 Ontonagon P re squ e Sag ina w Isle S anilac S cl io ol c ia tt T us c ol u 21 15 2 11 15 237 -(*5*o NA 992 11% 5.777 22 6 10 7 ,3 5 4 27 *o 10 ,4 24 80 * o 4,772 4 7, 9 6 5 6 7* o -43% 1 0 .3 1 8 16 27.672 ]68°o 2.732 27,029 l62*o I730*o 11 5 80 9,308 1. 5 07 1 3 ,8 3 9 4658*o I2 6 * o 5.548 890 32 I 6.12 1 52% 2 .6 4 2 a T h e m o d e l input, n u m b e i o f boat d a y s in the st o rage co un tie s, are gen er ate d direc tly f i o i n tbe 19 94 M i c h i g a n B o a t i n g Su r \e > b I'he m o d e l input, n u m b e i o f boat day s in the sto rage co un tie s, m e g e n e i a te d t i o i n p i e v i o u s boat d ay s g e n e i a t i o u inod e) c Pei cent dil T ei eu ce s a i e calc ula te d as ( m o d e l es tim at e - s u i \ e y es t im a te ) •' s u n cy es tim at e 109 D ifferen ces b e tw e e n direct survey e s tim a tes and m odel estim a tes (A ) arc w ithin 5% for these regions. P e rc e n t d iffe re n c es at regional level are larger for the c e n tral-ea st (9% ) and south U p p e r P e n in su la regions (14% ). D ifferen ces b e tw e e n direct survey estim a tes and m odel e s tim a tes (B) are generally larger than d iffe re n c es b e tw e en direct survey estim a tes and m odel e s tim a te s (A). This is largely du e to the c o m p o u n d in g effects (errors) from the prev io u s m o d e ls associated with m odel estim a te (B). T h e p ercent differences ran g e from 6 % to 137%. The percent d iffe re n c es are less than 3 5 % for 15 o f 21 c ounties w ith s a m p le sizes o f m ore than 30 boats. R egional e s tim a te s directly from the survey are sim ilar to m o d el estim a tes (13). T h e tw o e s tim a te s are w ith in 10% for the southeast, n orthw est, w est central, southw est, and north U p p e r P e n in su la regions. T h e largest regional p ercent diffe re n c es betw een survey e s tim a te s and m odel e stim a tes (B) are for the c e n tral-ea st ( 2 7 % ) and northeast regions (18% ). Trip D istrib u tio n M o d e l for B o a ts Stored at N o n w a te rfro n t H o m e s M odel Specification T h e regions used in the trip distribution m o d el for bo a ts stored at nonw aterfront h o m e s are slightly different from the regions in o th er m odels. T h e regions are show n in the Figure 9. Inland c o u n tie s are gro u p ed into the so u th -in la n d , c e n tral-in la n d , and north inland regions. T h e c e n tral-inland region has few w a te r resources, su ch as lakes and rivers. I'he south and n o rth U p p e r P e n in su la regions are c o m b in e d into o n e region. 01 1 Figure 9 M ichigan Boating Regions (II). Michigan Boating R eg ions (II) (for nonwaterfront hom e boars) I Southeast Central Fast Li Northeast L ; N orthw est -4 Central W est M S outhw est : South Inland B Central Inland North Inland Upper Peninsula For each (storage) county. 13 tim c-d ista n c e destination zo n e s w ere defined: “ w ithin 20 m iles". “ 21 -6 0 m ile s ” . “ 61-90 m iles". “ 91 -120 m iles". “ 121 -1 50 m iles". “ 151180 m iles". “ 181-210 m iles". "211 -240 m iles". “ 2 4 1 -2 7 0 m iles". “ 2 7 1 -3 0 0 m iles". “ 301 360 m iles". “ 3 6 1 -4 2 0 m iles", and “over 421 m iles". E ach zone includes one or m ore (d estination) counties. T h e d istrib u tio n o f boat days in d e stination z o n e s w ithin (storage) regions was estim a ted from the 1994 M ic h ig a n B oating Survey (T a b le 26 and Figure 10). A s w ould be e x p ected, the p e rcentage o f boat days in each z o n e g e nerally de c lin es as distance increases since b o a ts kept at no n -w a te rfro n t h o m e s m u st be trailered to w aterfront locations. T he greater the dista n c e the h ig h er the travel cost - tim e and m o n ey costs associated w ith u sin g these boats. A lthough the n u m b e r o f boat days generally decreases as distance increases, s o m e fluctuations o c cur in the distance de c ay curve. T hese fluctuations m ay be the result o f several factors, such as the availability o f boating opp o rtu n itie s and facilities, b o a te r travel habits, an d ag g lo m e ra tio n effects o f counties in the d e stin a tio n zone. T h e patterns o f boat da y s distribution w ithin d e stin a tio n z o n e s vary so m e w h at across regions. In northern M ichigan, o v e r 8 5 % o f boat days by boats stored at n o n w a te rfro n t h o m e s take place in the “ w ithin 20 m iles" zone. In southern M ichigan regions, less than 5 5 % o f boat days o c c u r in the “ w ithin 20 m ile s " zone. Travel p ropensity is in fluenced by the a m o u n t and quality o f boating opp o rtu n itie s w ithin the origin (storage) counties. O w n e rs o f boats kept in co u n tie s that h a v e m o re a n d /o r higher T abic 26. D istribution o f Boat D ays By S torage R e g io n a n d T im e D ista n c e D estination Z one; N o n w a te rfro n t H o m e Segm ent. T im e-d ista n c e South Central N o r th N o r th C entral South S o u th Central N o r th East" East East W est W est W est Inland In land Inland D estination /.o n es U .P. Total W ith in 2 0 m i l e s 44% 52% 92% 87% 70% 55% 54% 38% 59% 8 5 ° .. 56",. 2 1 - 6 0 m i le s 25% 7% 5% 6% 9% 32% 20% 12% 15% 0% 16",, 6 1 - 9 0 m i le s 8% 18% 2% 1% 8% 3% 7% 17% 1 1% 4% 8",, 9 1 - 1 2 0 m iles 0% 3% 0% 2% 0% 0% 2% 3% 0% 8% 2% 121 - 1 5 0 m i l e s 2% 10% 0% 0% 1% 0% 1% 12% 1% 1% 3% 1 5 1 -1 8 0 m iles 1% 4% 0% 1% 0% 0% 5% 2% 0% 2% 2" I. 1 8 1 -2 1 0 m iles 1% 3% 0% 0% 1% 1% 1% 4% 0% 0% 110 (1 21 1 - 2 4 0 m i l e s 7% 0% 1% 0% 0% 1% 3% 4% 1% 0% •}(> 0 2 4 1 - 2 7 0 m iles 3% 2% 0% 1% 0% 0% 3% 2% 1% 0% TO 2 7 1 - 3 0 0 m iles 2% 0% 0% 0% 0° b 8% 1% 1% 0% 0% 1% 3 0 1 - 3 6 0 m iles 2% 0% 0% 0% 3% 0% 2% 3% 0% 0% 2% 3 6 1 - 4 2 0 m iles 4% 0% 0% 0% 1% 0% 0% 2% 0% 0% 1% O v er 4 2 0 m iles 3% 0% 0% 1% 5% 1% 0% 1% 13% 0% 1U a. For e a c h c o u n t y in th e s o u t h e a s t r e g i o n , 4 4 % o f the boat d a y s b y b o a t s k ept in n o n w a t e r f r o n t h o m e s are a l lo c a t e d t o th e "w ith in 2 0 m ile s" t i m e - d is t a n c e d e st i n a t i o n z o n e , note: E s t i m a t e s are b a s e d o n the 1 9 9 4 M i c h i g a n B o a t i n g S u r v e y . 113 F ig u r e 10. D i s t r i b u t i o n o f B o a t D a y s b y D e s t i n a t i o n Z o n e a n d S t o r a g e R e g i o n ; N o n w a t e r f r o n t H o m e S e g m e n t . S o u t h e a s t R e g io n S o u t h w e s t R e g io n T im e -d is ta n c e D e s tin a tio n Z o n e T tm e - d is ta m e D e s tin a tio n 7*>nt C e n t r a l H a st R e g io n S o u th I n la n d R e g io n 06 l i m r - r i t 't a n c r D e s tin a tio n /.n n r C e n t r a l I n l a n d R e g io n N o r t h e a s t R e g io n 04 oc 04 02 lim e - d i t l a t i c e D e s tin a tio n /.o n e T im e - d iita n c e D e s tin a tio n /.o n e N o r t h w e s t R e g io n N o r th I n la n d R e g io n 05 0 2 ■ tiiila iK r D e s tin a tio n /.o n e T im c - d is la n c e D e s tin a tio n Z o n e C e n t r a l W e s t R e g io n 08 06 04 02 T im e -d is ta n c e D e s tin a tio n Z o n e T iin r - d ik la n tr D e s tin a tio n Z t I 14 quality b o a tin g op p o rtu n itie s have a lo w e r propensity to travel than in c o u n tie s w ith fewer or lo w e r q uality bo a tin g o p p o rtunities. A s s u m in g the regional d istrib u tio n s apply to all c o u n tie s in the region, boat days generated by bo a ts stored at n o n w a te rfro n t h o m e s are distributed from each origin (storage) cou n ty to the d e stin a tio n zones. For e x a m p le , the northeast r e g io n 's distribution is used for A lc o n a cou n ty to d istribute boat days to d e stination zones. 8 2 % o f days to the “ w ithin 20 m ile s " zone. 5% to the “ 21 -6 0 m iles" zone. 2 % to the “ 6 1 -90 m ile s " zone, and 1% to the “ 211 -240 m ile s " zone. Step tw o o f the d istrib u tio n m odel is to d istribute boat days to co u n tie s within each d e stination z o n e in ord er to e s tim a te total n u m b e r o f bo a t days in the (destination) counties. A n index o f bo atin g o p p o rtu n itie s (T R index) — a w e ig h te d c o m b i n a ti o n ''1 o f “acres o f lakes", “ acres o f inland w a te r", “ m iles o f G reat L akes sh o re lin e s", "m ile s o f state or federally-designated w ild and scenic/natural riv e rs” , “ n u m b e r o f lakes o v e r 50 acres", " n u m b e r o f G reat L akes ac ce ss sites", and “ n u m b e r o f c a m p g r o u n d s " -- is e m p lo y e d to d istribute boat days to the c ounties w ithin d e stin a tio n z o n e s ’0. The index for e ach co u n ty is c o n stru c te d as follow ing: 2‘‘ In itially 4 0 v a r ia b le s m e a s u r i n g t h e q u a n tity a n d q u a lity o f b o a t i n g - r e la t e d r e s o u r c e s , f a c ilit ie s , and a c t i v i t i e s w e r e p o te n tia l c a n d i d a t e s to c o n st r u c t th e b o a t i n g o p p o r tu n i ty in d e x . N e t f l o w ratios for e a c h c o u n t y ( n u m b e r o f bo at d a y s in the c o u n t i e s d i v i d e d b y n u m b e r o f b o a t d a y s g e n e r a t e d by b o a ts k e p t in th e county') w h i c h s e r v e a s a p r o x y m e a s u r e o f a c o u n t y ’s a t t r a c t i v e n e s s to b o a t s at n o n w a t e r f r o n t h o m e s are c a lc u l a t e d . T h e c o r r e la tio n a n a l y s i s a n d s t e p - w i s e m u l t i p l e r e g r e s s io n a n a l y s i s are u s e d to a ss is t th e d e c i s i o n s o n the v a r ia b le s an d w e i g h t s for t h e v a r ia b le s c o m p r i s i n g th e b o a t i n g o p p o r t u n i t y in d ex . ’u The a c r e s o f la k e s, and n u m b e r o f la k e s o v e r 5 0 a c r e s w e r e c o l l e c t e d in “ M i c h i g a n L a k e Inventory" ( M D N R , 1 9 7 4 ). M i l e s o f G re at L a k e s s h o r e l in e s , a c r e s o f in la n d w ater, m i l e s o f state o r f e d e r a l l y - d e s i g n a t e d w ild and sc e n i c / n a t u r a l riv ers, n u m b e r o f G re at L a k e s a c c e s s s it e s, an d n u m b e r o f c a m p g r o u n d s in the c o u n t i e s are a s s e m b l e d in the M i c h i g a n Tourism R e s o u r c e s D a t a b a s e ( S p o t t s , 1 9 9 5 ) . I 15 TR, - (4 * R ,+ 4 * G ,+ 2 .5 * W T ,+ 1.5*LK,+ 1.5*LK 50,+ I *AC, +1 *CM ,)* W (irl W h e re TR,: R ,: G,: WT,: LK,: ACj: the bo a tin g o p p o rtu n ity index for cou n ty i: stan d ard ized m iles o f sc enic/nature rivers in co u n ty i31: sta n dardized m iles o f G reat Lakes sh o re lin e s in county i: sta n d a rd iz e d acres o f inland w a te r in cou n ty i; s ta n d a rd iz e d a cres o f lakes in co u n ty i; sta n d a rd iz e d n u m b e r o f public a ccess sites on G re a t Lakes in county i; CM,: sta n dardized n u m b e r o f c a m p g ro u n d s in co u n ty i; and W (1|r): the w e ights a ssigned to county i, given region r32. T h e index m e a s u re s a c o u n ty 's a ttractiveness as a d e stination for boats stored at n o n w a te rfro n t hom es. T h e county level distribution form ula (on page 100) is applied to distribute boat days by boats stored at n o n w a te rfro n t h o m e s to c o u n tie s w ithin a d e stin a tio n zone. T h e T R index is used in the fo rm u la to m ea su re the availability o f boating o p p o rtu n ity in the county (Uj). A ssum ptions T h e trip d istrib u tio n m odel for boats stored at n o n w a te rfro n t h o m e s involves two basic assu m p tio n s. (1) T h e regional distribution o f boat days w ithin 13 d e stin a tio n z o n e s is reliable. (2) The d istribution o f bo a tin g o p p o rtunity index (T R index) reflects the n u m b er o f boat days that o c c u r in the c ounties w ithin a tim e-d ista n c e destination zone. ’ ’ T h e s ta n d a r d i z e d m e a s u r e o f a r e s o u r c e in a c o u n t y is c a l c u l a t e d as th e a m o u n t o f a r e s o u r c e in the c o u n ts d i v i d e d b y th e state a v e r a g e a m o u n t o f that r e s o u r c e . ° T h e w e i g h t s a s s i g n e d to c o u n t i e s are b a s e d o n th e a s s u m p t i o n - the c o u n t i e s in the n orthern M i c h i g a n are m o r e attrac tive, g i v e n th e s a m e b o a t i n g o p p o r t u n i t i e s — w h i c h c o u l d b e s u p p o r t e d b y th e "south to n o r th ” h ab itu al b o a t i n g p a ttern s f o u n d in m a n y p r e v i o u s b o a t i n g s t u d i e s . A f t e r s e v e r a l c a lib r a tio n s, the final w e i g h t s are ” 2 . 5 ” fo r c o u n t i e s in the U p p e r P e n in s u la , n o r t h w e s t r e g i o n , northeast, c en t r a l- e a s t , and n o r th - in la n d r e g i o n s , ” 0 . 5 ” for c o u n t i e s in th e c e n tr a l -in l a n d an d so u th e a st r e g i o n s , an d " 1 . 5 ” fo r th e o t h e r c o u n t i e s . Results T able 27 n o n w a te rfro n t s u m m a riz es h om es. About the 30% distribution of boat o f boat days days for boats stored at g e n e ra te d by b o a ts stored at n o n w a te rfro n t h o m e s take plac e in the south-inland region. E x c e p t for a c ouple o f c ounties w ith large pop u latio n s, m o st co u n tie s house 1% to 2 % o f these boat days. For e x a m p le . 7 % o f the da y s o c c u r in O a k la n d county and 5 % o f th e days take place in W ayne county. T h e ratios o f boat days that take place in a cou n ty by b o a ts stored at nonw aterfront h o m e s to the n u m b e r o f boat days g en erated by boats stored at n o n w a te rfro n t ho m es in the county indicates co u n tie s that either e x p o rt or im p o rt bo a t days. R atios greater than one indicate co u n tie s that arc net im porters o f boat days. R atios less than on e indicate co u n tie s that are net exporters. S o u theast and c e n tral-inland reg io n s are “ net exporters", and northeast, no rth w est, n o rth-inland and U p p e r P e n in su la reg io n s are “ net im porting" regions. T h e net flow s c apture the so u th -to -n o rth boating (use) travel patterns. T a b le 28 p rese n ts the origin (storage location) - d e stin a tio n (use location) m atrix for boats stored at n o n w a te rfro n t hom es. O v e r three q u arters o f boat days in the southern M ichigan regions - southeast, central-w est, south-inland and c e n tral-inland regions - are by boats kept w ithin the s a m e region. In the central-inland region, 9 2 % o f days are by the boats kept w ith in the region. But, less than h a lf (42% ) o f days g e n e ra te d by boats kept in this region stay w ithin the region. T his is because the cen tral-in la n d region has relatively few lakes and bo atin g opportunities. In com p a riso n , in n o rth e rn M ic h ig a n regions - northeast, central-east, no rth w est, north-inland and Upper P e n in su la regions - Table 27. B oat Days By C o u n ty o f O rigin (Storage) and D estination (Use): N o n w a te rfro n t H o m e Segm ent. C ou nties/ R egion s M acom b M onroe St Clair W ayne S o u th East Bay Huron S a n ila c Tuscola C e n tr a l East A lcona A lpena Arenac C heb oygan Iosco P r e sq u e Isle N ortheast A n trim B en zie C h a r l e v o ix Emmet G ran d T r a v e r se L e e la n a u M anistee M ason N orthw est M uskegon O ceana O tta w a C entral W est A llegan Berrien Van Buren S ou thw est Barry Branch C alhoun Cass H il l s d a l e Jackson K a la m a zo o K ent Lenawee L i v in g s t o n M o ntca lm O a k la n d Sain t J o s e p h W ashtenaw S o u th In la n d T o ta l B o a t D a y s b y C o u n t y o f T o ta l B o a t D a y s b y C o u n ty o f D e s tin a tio n " O r ig in ( S to r a g e ) 11 (A ) 1 0 5 .9 5 4 4 1 ,3 5 9 6 7 ,6 2 0 173.021 3 8 7 ,9 5 3 25 ,6 8 8 31 ,8 4 6 4 5 ,5 6 4 3 7 .8 1 8 39,165 22 ,6 7 7 2 0 2 ,7 5 7 3 0 ,2 3 2 2 6 ,9 9 3 35,537 2 9 ,8 6 6 72,242 3 5 .8 9 3 28 ,7 5 7 4 2 ,7 1 2 3 0 2 ,2 3 2 9 0 ,0 0 8 2 6 ,8 5 9 120.364 2 3 7 ,2 3 1 7 8 .1 8 9 4 6 ,0 0 7 5 0 ,8 8 7 1 7 5 ,0 8 3 3 8,964 2 8 ,8 0 9 4 1 ,9 0 8 41,045 18,547 7 3,402 6 8,222 153,637 3 3 ,2 2 0 1 11,396 3 8 ,0 4 9 24 6 ,7 3 7 3 5 ,2 7 6 9 1 ,1 8 0 1 ,0 2 0 ,3 9 1 ) ) ) ) 175.897 3 8 ,5 4 7 5 2 ,0 4 8 27 6 ,1 9 6 ) 5 4 2 ,6 8 8 ( ( ( ( 3.1% 1.2 % 2.0% 5.0% ( 1 1 .2 % ( ( ( ( 1.9% 1.0% 0.6% 1.1 % ) ) ) ) f 4 .6 % ) ( ( ( ( ( ( 0.7% 0.9% 1.3% 1 .1 % 1.1% 0.7% ) ) ) ) ) ) ( 5 .9 % ) ( ( ( ( ( ( ( ( 0.9% 0.8% 1 .0 % 0.9% 2.1% 1.0% 0.8% 1.2% ) ) ) ) ) ) ) ) ( 8 .7 % ) ( ( ( 2.6% 0.8% 3.5% ) ) ) ( 6 .9 % ) 65 .7 6 8 3 5.713 19,873 3 6,683 1 5 8 ,0 3 7 (B ) (p e t.) ( 2.3% ( 1.3% ( 1.5% ( 5 .1 % ( 1.1% ( 0.8% ( 1.2% ( 1.2% ( 0.5% ( 2.1% ( 2.0% ( 4.4% ( 1.0% ( 3.2% ( 1.1% ( 7.1% ( 1.0% ( 2.6% ( 2 9 .5 % ) ) ) 5 9,388 18,028 12,642 2 6,803 1 1 6 ,8 6 1 1 1.345 2 2,077 15,208 23,348 25,020 13,354 1 1 0 ,3 5 1 2 3 ,8 2 6 17,205 20,580 2 3,125 5 8,480 22,989 1 7,7 1 1 2 0 ,3 2 8 2 0 4 ,2 4 5 94,241 17,388 135,905 2 4 7 ,5 3 4 52,5 5 5 6 9,377 4 1 ,2 6 0 ) 1 6 3 ,1 9 3 ) ) ) ) ) ) ) ) ) ) ) ) ) ) 3 8,925 2 8 ,8 0 0 5 2 ,343 3 8 ,4 9 5 2 1,235 70,345 8 7 ,213 196,582 38,735 63,386 3 1,539 3 25,217 3 9 ,645 6 7,4 8 3 ) 1 ,0 9 9 ,9 4 4 R atio f A )/(B ) 60% 1 07 ° o 13 0 % 63% 7 1 " ,, I 1 1% 198".. 15 7 % 137 % 1 3 5 " ,, 226"., 144",, 300",, 162",, 157",, 170",, 184% 127'!,, 1 5 7% 1 73°,, 129°,, 124",, 15 6% 162",, 210% 1 4 8 " ,, 96% 154",, 89% 9 6 " ,, 149",, 66" „ 123% 1 0 7 " ,, 100% 10 0 % 80% 10 7% 87"/,, 104°,, 78% 78“o 86",, 1 76 % 121% 76% 89% 1 35 % 93% T able 27 (cont'd). C ou nties/ R egions C lin t o n Raton G enesee G ratiot In gham Ionia Is abella l .a p e e r M id la n d Sagin aw Sh iaw assee C e n tra l Inland C lare C raw ford ( i lad win K a lk a sk a Lake M ecosta M issa u k ee M ontm orency Newaygo O gem aw O sceola O scoda O tsego R oscom m on W exford N orth Inland D e lta D ickinson Iron M a c k in a c M en o m in ee Schoolcraft A lger Baraga C h ip p ew a G o g eb ic H o u g h to n K ew eenaw Luce M arq u e tte O ntonagon T o ta l M oat D a y s b y C o u n ty o f T o ta l M o at D a y s b y C o u n ty o f D e s tin a tio n * O r ig in (.S torage)*' (A ) 12.8 8 9 16.527 6 8 ,0 0 6 7.090 3 2 ,7 0 8 17.148 9.1 0 5 15.987 16.999 38,778 1 1.270 2 4 6 ,5 0 9 26.622 39 ,4 3 9 28.165 16.708 3 1.474 25.217 10 . 6 2 6 1 1,827 60 ,7 7 4 38.191 15 .6 3 1 3 0,988 2 4.803 47 ,0 8 7 2 3,452 4 3 1 ,0 0 3 12,195 9 ,5 1 I 4 9 ,7 5 5 25 .9 3 9 1 1,981 18,394 14,175 14,778 2 0 ,8 1 4 17,657 3 6 ,6 7 2 2 2 ,4 3 9 9,9 9 0 1 2 ,1 9 3 19,863 U pp e r Peninsula 2 9 6 ,3 5 4 STATE TO TA L 3,457,550 (B ) (p d .) ( ( ( ( ( ( ( ( 0 .4% 0 .5% 2.0% 0.2% 0.9% 0.5% 0.3% 0.5% 0.5% ) > ) ) ) ) ) ) ) ( ( 1.1% 0.3% ) ) ( ( 7 .1 % ) ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( 0.8% 1.1% 0.8% 0.5% 0.9% 0.7% 0.3% 0.3% 1 .8% 1.1% 0.5% 0.9% 0.7% 1.4% 0.7% ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ( 1 2 .5 % ) ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( 0.4% 0 .3% 1.4% 0.8% 0.3% 0.5% 0.4% 0.4% 0.6% 0.5% 1.1% 0.6% 0.3% 0.4% 0.6% ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ( 8 .6 % ) 2 8 .3 2 7 3 9,067 143,565 16.322 7 8 .0 2 9 2 3 ,7 4 5 19.530 2 8 ,9 2 3 4 1 ,2 1 6 9 8 ,4 2 6 2 8 ,0 6 6 R atio ( A )■'(»> 46" o 42",, 47% 43" „ 42".. 72",, 47",, 55"., 41% 39",, 40% 5 4 5 ,2 1 6 2 5.244 13,515 2 4 ,7 2 5 14,985 1 1 ,4 1 6 26.698 1 1 ,7 3 5 13,356 3 6 ,9 2 4 18,946 14,959 9,9 0 6 17,368 33,695 24,919 2 9 8 ,3 9 1 4,351 2,617 12,967 17,1 91 12.502 6,748 8,811 8,987 935 3 ,3 8 1 10,942 19,885 9,6 1 3 3,2 7 8 6 ,9 2 0 1 2 9 ,1 2 7 4 5 " ,, 105",, 292 ",, 1 14% 1 1 1% 27 6",, 94",, 9 1" „ 89",, 165",, 202",, 104",, 313",, 1 43 % 140",, 94",, 1 4 4 " ,, 2 80",, 3 63",, 3 84",, 151",, 96" o 273% 161",, 164" o 2226"„ 522% 335",, 11 3 % 104",, 372% 287" u 2 3 0 " ,, 3,457,550 a T o ta l n u m b e r o f b o a t d a y s in th e c o u n t ie s w h e r e th e b o a t s a r e u s e d b T o ta l n u m b e r o f b o a t d a y s g e n e r a te d b y b o a t s k e p t in th e c o u n t ie s n o te : M e c a u s e c a s e s w ith m i s s in g s to r a g e v a r i a b le s a r e e x c l u d e d f r o m th e (s u rv e y b a s e d ) e s t i m a t e s o f b o a t s in d if f e r e n t s to r a g e s e g m e n ts b> s to r a g e r e g i o n s ( T a b le IT ) th a t a r e u s e d in t h e a l lo c a t io n m o d e ls , th e n u m b e r o f b o a t s e s t i m a t e d by s to r a g e a l lo c a t io n m o d e ls is le s s th a n t h e n u m b e r o f r e g i s t e r e d a c tiv e c r a f t ( 5 5 5 , 0 0 0 b o a t s ) M e c a u s e th e e s ti m a t e s b y tr i p d is tr i b u tio n m o d e l a i e b a s e d o n th e e s ti m a t e s d e r n e d fro m th e g e n e r a tio n a n d a l lo c a t io n m o d e ls , th e m o d e l e s t i m a t e d n u m b e r o f b o a t day s w o u ld b e lo w e r th a n to ta l n u m b e r o f b o a t d ay s r e p o r t e d in I W T R e c r e a ti o n a l M o a tin g S u rv e y ( S ty n e s e l al . 10 0 5 1 Table 28. N um ber o f Boat Days by Storage Region and Destination Region; Nonvvaterfront Home Segment. R E G IO N S OF S T O R A G E Boat D ays D E S T IN A T IO N Central Southeast R E G IO N S Southeast R ow P ci C o lu m n P c i. Central East R ow P ci East TO'IAI. Central Northeast Northw est Southw est W est South Central North Inalnd Inland Inland (pet.) UP 3 0 7 .9 6 7 2 .4 2 4 9 0 57 212 6 1 .6 3 2 15.391 260 0 7 9 .4 % 0 6% 0 .0 % 0 .0 % 0 0% 0 1% 15 9% 0 .1 % 0 .0 % 5 6 7% 2 .1 % 0 .0 % 0 .0 % 0 .0 % 0 .1 % 5 .6 % 4 .0 % 9 H0A 0 1% 00% 9.202 7 7 .0 4 4 354 623 461 2.160 21.270 4 5 .1 7 5 1.745 5 .8 % 4 8 .8 % 0 .2 % 0 .4 % 03% 1 4% 13 5 % 2 8 .6 % 11% 0 .0 % 0 .0 % 3 87.953 11% 158.037 5% 2 0 2 ,7 5 7 6% 3 0 2 .2 3 2 9% 237,231 7% 175.083 5°b 0 1.020.391 30% 1 .7 % 6 5 .9 % 0 .3 % 0 .3 % 02% 1.3 % 1 9% 8 .3 % 0 6% 11.0 17 10,594 10 5.047 2 ,3 2 4 3 .40 5 1.207 26.340 3 4 .0 3 0 8 ,042 750 R ow P ci 5 4% 5 2% 5 1 .8 % 1 .1 % 1 7% 0 6% 13 o% 16 8 % 0 4% C o lu m n Pci. 2 .0 % 9 1% 9 5 .2 % 1 .1 % 14% o -% 2 4% 6 2% 4 0 7 .i ") -o.- C o lu m n Pci. Northeast N orth w est 787 973 19 0.036 7 .6 1 4 6 .5 15 43.997 2 3 ,0 7 5 3 .5 % i .i % 0 .3 % 6 2 .9 % 2 .5 % 2.2% 14 6 % 7.6% 5 1% 0 .3 % 0 .6 % 10.663 R o w Pci. 0 .6 % 15.360 3 .21 2 2 0% 2 .7 % 0 .9 % 9 3 .0 % 3 1% 4 .0 % 4 0% 4 .2 % 5 .1 % 6 .5 9 9 352 35 925 18 3.3 60 4 .72 3 2 6 .6 3 7 8.0 56 6 .5 4 4 0 R o w Pci. 2 .8 % 0 .1 % 0 .0 % 0 .4 % 7 7 .3 % 2.0% 11 2% 3 .4 % 2 8% 0 .0 % C o lu m n P c i 12% 0 .3 % 0 .0 % 0 .5 % 7 4 .1 % 2 9% 2 4% 1.5% *) 10,' 0 .0 % 167 5,8 26 113.608 46.481 5 .6 8 6 271 0 C o lu m n P c i Central W est Southw est 2 .9 0 3 136 R ow P ci I. 7% 0 .1 % 0 .0 % 0 .1 % 3 .3 % 6 4 .9 % 2 6 .5 % 3 2% 0.2% o.o% C o lu m n P e t 0 .5 % 01% 0 .0 % 0 .1 % 2 .4 % 6 9 .6 % 4 2% 1.0% 0 I% 0 .0 % 110 ,0 1 2 3,671 91 808 13,089 2 8 .1 0 9 7 7 5 .4 4 6 8 6 .3 4 9 2 .8 1 6 1 0 .8 % 0 .4 % 0 .0 % 0 .1 % 1 .3 % 2 .8 % 76.0% 8 .5 % 0 .3 % 0 0% 0 .1 % 0 .4 % 5 3% 1 7 .2 % 70 .5 % 1 5 .8 % 0 .9 % 0 0%, 51 236 79 12.886 2 27.649 466 0 South Inalnd Row P e l 5 20 3% 3 .1 % 4 .0 9 2 1.039 R o w Pci. 1 7% 0 .4 % 0 .0 % 0 .0 % 0 .1 % 0 0% 5 .2 % 9 2 .3 % 0.2% 0.0% C o lu m n P c i 0 .8 % 0 9% 0 .0 % 0 .0 % 0 .1 % 0 0% 1.2 % 4 1 .8 % 02% 0 0% 43.278 17.042 3 ,0 4 9 5 .6 8 6 12.843 5.6 09 6 3 ,5 3 3 5 8 ,4 8 7 2 2 1 .0 6 6 412 100% 4 .0 % 07% 1 .3 % 3 .0 % 1 .3 % / 4. / % 1 3 .6 % 5 1 .3 % 0.1% C o lu m n Pci. Central Inland North Inland Row ’ P e l C o lu m n Pci. UP R o w Pci. C o lu m n P e l Total (percent) 10 8.0% 14 6 % 2 .8 % 2 8% 5 .2 % 3 4% 5 8% 10 . 7% 74 .1 % 0 .3 % 3 6 ,9 5 4 1.347 778 3 .6 2 5 2 0 .6 4 3 971 21.721 4 1 .3 1 8 41.821 127,175 1 2 .5 % 0 .5 % 7 0% 7j % 13 9%, 14 .1 % 4 2 9% 03% 0 6.8% 1.2%, 0 '% 1.2% 18% 8.3% 0 (>«„ 2 I) % ' 6°„ 14 0 % 5 4 2 .6 8 8 116.861 110.351 2 0 4 .2 4 5 2 4 7 .5 3 4 163.193 1.099.9 44 5 4 5 .2 1 6 298.391 16° o 3% 3% 6% 7 °o 5°o 16% 9°o 32° o 2 4 6 .5 0 9 7% 4 3 1 .0 0 3 12% 2 9 6 .3 5 4 9% 98 5 " o 129,127 3 .4 5 7 .5 5 0 4°n 120 o v e r 4 0 % o f boat days o c c u rrin g in the region arc generated by boats kept in the other regions. F or e x a m p le. 5 2 % o f boat days in the n o rtheast region are by boats kept within region. 3 0 % by boats kept in the so u th -in la n d and cen tral-in la n d regions, and 11% by boats kept in the southeast a n d central-east regions. T h e orig in -d e stin a tio n m atrix also sh o w s a “ s o u th -to -n o rth " pattern o f m o v e m e n t by boats stored at nonw a te rfro n t hom es. Model Evaluation S im ila r to the e v a luation o f th e d istribution m odel for boats stored at m arinas, the trip d istrib u tio n m odel for b o a ts stored at n o n w a te rfro n t h o m e s is e v a lu a te d on its ability to d istribute (1) boat days first to d e stin a tio n zo n e s and (2) then to counties. T h e two steps are a gain ev a lu a te d separately. Fable 29 pro v id e s the estim a ted s a m p lin g errors at the 90 pe rc e n t c o n fid e n ce level for the distribution o f boat days w ithin 13 destination z o n e s by storage regions. For e x a m p le , there is a 3% s a m p lin g error (9 0 % confidence level) a s so c ia te d w ith the e s tim a te that 5 6 % o f boat days take place w ithin the "2 0 m iles" zone. T his m e a n s that w ithin the 9 0 % c o n fid e n ce level, the po p u latio n d istribution o f boat days o c c u rrin g in the “ w ithin 20 m ile s ” z o n e ranges from 5 3 % to 59% . E ighty pe rc e n t o f the s a m p lin g errors are 5% or less. T h e four largest sa m p lin g errors (1 1 % to 13%) are for the central-east, northeast and so u th w e st regions w hich have relatively sm all s a m p le sizes (41 o r few er boats in the regions,).. For e x a m p le , large sa m p lin g errors p ro d u ce less reliab le e stim ates for the p ercent (n u m b e r) o f boat days " w ith in 20 m ile s ” z o n e in the c e n tral-ea st region. W ith a 13% s a m p lin g error, the n u m b e r o f days that take place in the " w ith in 20 m ile s ” z o n e co u ld range from 4 6 ,0 0 0 days to 76,000 days. T ab ic 29. N o n w a tc rfro n t H o m e B o at D ays by S torage R egion and D e stin a tio n Zone: S a m p lin g E rrors at A 9 0 % C o n fid en c e Interval. T im e-d ista n ce D estination Zones South East Central East N orth N o r th Central S o u th S o u th C entral N o r th E ast W est W est W est Inland In land Inland IJ.P. Total S a m p lin g E r r o r at 9 0 % C o n fid e n c e In terval W it h in 2 0 m i le s 8.1% 1 3 .0 % 1 1 .1 % 8 .8 % 9.5% 12 .8% 5 .3 % 6.1% 7 .7 % 8.2" o 2.7% 21 - 6 0 m i l e s 7.2% 7.8% 7 .8 % 7 .7 % 7 .9 % 1 1.0% 4.3% 4.8% 6.6% 0.0° o 2.0"., 6 1 - 9 0 m iles 4.3% 9.9% 4.6% 2.9% 4.0% 6.7% 3.7% 5 .1 % 5 .3 % 6 .1 % 1.7% 9 1 - 1 2 0 m iles 0 .0% 6.8% 0.0% 2.1% 2.4% 0.0% 1.9% 3.3% 1.5% 6.1% 1.0" „ 1 2 1 -1 5 0 m iles 2 .3% 5 .7% 4.6% 2.1% 2.4% 4.0% 1.6% 3 .8% 2.9% 1.8% 0.9",, 1 5 1 -1 8 0 m iles 2.3% 4.0% 0.0% 2.1% 2.4% 4.0% 2.0% 2.5% 2.1% 2.5% 0.8",, 1 8 1 -2 1 0 m iles 2 .3% 4 .0% 0.0% 2 .1% 2.4% 6.7% 1.9% 3.1% 2.1% 1.8% 0.9" „ 21 1 - 2 4 0 m i l e s 4.0% 0.0% 4.6% 2.1% 0.0% 5 .5 % 2 .0% 2.9% 2.5% 1.8% 0.9",, 2 4 1 - 2 7 0 m iles 3.6% 4.0% 4 .6% 2.1% 0.0% 0.0% 2.2% 2.7% 2.1 °,0 0 . 0 % 0.9",, 2 7 1 - 3 0 0 m iles 3.6% 0.0% 0 .0% 0.0% 2.4% 4 .0% 2.0% 1.1% 0 .0% 0.0° „ 0.7",, 301 - 3 6 0 m i l e s 2.3% 4.0% 0.0% 0.0% 2.4% 0.0% 1.7% 2.5% 0 . 0 ° « 0.0" 0 0.7",, 3 6 1 - 4 2 0 m iles 2.9% 0.0% 0.0% 0.0% 2.4% 0.0% 0.7% 1.9% 1.5% 0 .0" 0 0.5" „ O ver 4 2 0 m iles 1.7% 0.0% 0.0% 2.9% 2.4'! o 4.0% 1.0% 1.6% 3.2% 0 .0" o 0.6",, 85“o 56% D i s t r i b u t i o n o f B o a t D a y s in D e s t i n a t i o n Z o n e s W ith in 2 0 m i le s 44% 2 1 -6 0 m iles 25% 6 1 - 9 0 m iles 8% 92% 87% 70% 55% 54% 38% 59“o 7% 5% 6% 9% 32% 20% 12% 15% 0% 16% 18% 2% 1% 8% 3% 7% 17% 1 1% 4% 8% 52% 9 1 - 1 2 0 m iles 0% 3% 0% 2% 0% 0% 2% 3% 0% 8% 2% 1 2 1 -1 5 0 m iles 2% 10% 0% 0% 1% 0% 1% 12% 1% 1% 3% 1% 4% 0% 1% 0% 0% 5% 2% 0% 2% u 1 5 1 -1 8 0 m iles 1 8 1 -2 1 0 m iles 1% 3% 0% 0% 1% 1% 1% 4% 0% 0% 11u 1) 2 1 1 - 2 4 0 m iles 7% 0% 1% 0% 0% 1% 3% 4% 1% 0% 3% 2 4 1 - 2 7 0 m iles 3% 2% 0% 1% 0% 0% 3% 2% 1% 0% 2% 2 7 1 - 3 0 0 m iles 2% 0% 0% 0% 0% 8% 1% 1% 0% 0% 1% 3 0 1 - 3 6 0 m iles 2% 0% 0% 0% 3% 0% 2% 3% 0% 0% 2"., 3 6 1 - 4 2 0 m iles 4% 0% 0% 0% 1% 0% 0% 2% 0% 01b 1% O v er 4 2 0 m iles 3% 0% 0% 1% 5% 1% 0% 1% 13% 0% 2",, N o. o f B o a t D a y s ( 0 0 0 ') 543 i n n o 204 248 163 /, W O 545 298 129 3 .4 5 8 T he se c o n d stage o f the e v a luation focuses on the e s tim a tes o f the n u m b e r o f boat d ays in the counties. T he m odel estim a tes o f hoat days in the co u n tie s are c o m p a red with the direct survey estim ates. A g a in , tw o types o f m odel e s tim a tes (A and B) are introduced by u sing tw o fo rm s o f m o d e l inputs: (1) survey b a sed estim a tes o f bo a t days generated by boats ke p t in c o u n tie s (m odel e s tim a te s A), and (2) estim a tes o f boat days in the storage co u n tie s p ro d u ce d by the trip generation m odel (m odel estim a tes B). In addition, the c o m p a ris o n b e tw e e n direct survey estim a tes and m odel estim a tes (A a n d B) is only at the regional level, not at the cou n ty level, be c au se only tw o c ounties have sa m p le sizes greater than 30. T h e trip d istrib u tio n m odel for boats stored at n o n w a tc rfro n t h o m e s estim a tes boat days in the reg io n s re a so n a b ly well. W ith the e x c e p tio n o f the so u th w e st region, the regional p ercent diffe re n c es b e tw e e n survey b ased e stim a tes an d m odel estim a tes (A ) are 5% o r less. T h e regional pe rc e n t difference b e tw e en the tw o estim a tes is about 11% in s o u th w e st region (T a b le 30). T h e 11% p ercent d ifferences b e tw e en the tw o e stim ates are a cce p tab le w ithin a 9 0 % c o n fid e n ce level du e to h ig h e r s a m p lin g errors (1 3 % ) in that region (T ahle 29). In general, the diffe re n c es be tw e en direct survey e s tim a tes and m odel estim ates (B) arc greater than the diffe re n c es b e tw e e n direct survey e s tim a tes and m odel estim ates (A). T his is largely d u e to the c o m p o u n d in g effects (errors) from the prev io u s m odels. E x c e p t for the s o u th w e st region, the regional p ercent d ifferences b e tw e en survey base e stim a tes and m o d e l e s tim a tes (B) are un d e r 15%. T h e pe rc e n t difference b e tw e en the tw o estim a tes is 2 8 % in the s o u th w e st region. 1 23 T ab le 30. N o n w a te rfro n t H om e B oat D ays By C o u n ty o f D estin atio n : A C o m p a risio n o f S urvey a n d M odel E stim ates. N UM BER OF BOAT DAYS M< id c l E s ti m a t e S u r v e y E s ti m a t e R egion/C oun ty M o d e l I n p u t fr o m 1 9 9 4 S u r v e y ’ C ases M o d e l I n p u t f r o m P r e v io u s M o d e l 1, I’e r c c n N o. (A ) D if f e r e n c e (B ) P e r c e n t D if f e r e n c e 1 R eg io na l E stim ates S o u th l a s t 3 4 1 .3 1 7 80 3 4 1 .8 1 5 0% 3 8 7 .9 5 3 C e n t r a l l: a s t 1 7 2 .8 4 4 56 1 7 0 .5 0 9 -1 % 1 5 8 .0 3 7 -9 " N o r th e a s t 1 8 2 .8 8 7 73 1 8 7 .9 2 3 3% 2 0 2 .7 5 7 1 1% -8 " ., 14"., N o r th w e s t 3 2 8 .0 6 1 115 3 1 8 .3 1 3 -3 % 3 0 2 .2 3 2 C e n tra l W e st 2 4 5 .1 7 3 80 2 4 9 .6 9 5 2% 2 3 7 .2 3 1 -3 " ., S o u th w e s t 2 4 4 .2 3 1 44 2 1 8 .3 3 9 -1 1 % 1 7 5 .0 8 3 -2 8 " ., S o u th In la n d 0 3 4 .0 2 7 5% 1 ,0 2 0 .3 9 1 2 3 3 .4 4 2 161 55 9 7 6 .6 9 5 C e n tr a l I n la n d 2 3 5 ,0 8 6 1% 2 4 6 .5 0 9 N o r th In la n d 4 8 1 .3 8 5 136 4 5 0 ,5 6 1 -6 % 4 3 1 .0 0 3 -1 0 % U p p e r P e n in s u la 2 9 4 .1 8 4 140 3 0 8 .6 1 3 5% 2 9 6 .3 5 4 l" o STA TE TO TA L 3 .4 5 7 .5 5 0 940 3 .4 5 7 .5 5 0 9% 6" 3 .4 5 7 .5 5 0 C o u n t y L e v e l E s t i m a t e s For C o u n t i e s W it h S a m p l e S i z e s L ar g er T h a n 3 0 B o a t s G r a n d T ra v e rs e O tta w a 9 2 .3 3 9 1 4 2 .5 5 5 31 46 7 9 .0 3 5 -1 4 % 7 2 .2 4 2 1 5 0 .2 8 1 5% 1 2 0 .3 6 4 - 1 6 " ,. C o u n t y L e v e l E s t i m a t e s F o r C o u n t i e s W ith S a m p l e S i z e s S m a l l e r T h a n 3 0 B o a t s A lc o n a 1 7 ,5 2 7 10 2 0 .4 2 7 17% 2 5 .6 8 8 4 7 " ,, A lg e r 1 0 ,2 0 7 8 1 2 .3 9 0 21% A lle g a n 8 7 ,3 8 9 13 6 6 ,5 6 9 -2 4 % 1 4 .1 7 5 7 8 .1 8 9 -II"., A lp e n a 3 6 ,2 1 4 13 2 2 .8 9 9 -3 7 % 3 1 .8 4 6 A n tr im 3 8 .6 2 8 8 2 7 ,6 3 2 -2 8 % 3 0 .2 3 2 A ren ac 2 9 .6 1 0 1 7 .3 0 3 10 9 4 7 ,5 9 7 B ara g a 1 7 .0 4 7 61% -1% 3 9 " ,, -1 2 % -2 2 " ,, 4 5 .5 6 4 5 4 " ,, 1 4 .7 7 8 -1 5 % -6 6 " ., 1 1 4 .4 6 2 17 3 6 .8 2 9 -6 8 % 3 8 .9 6 4 B ay 5 0 .6 7 5 27 5 2 ,8 2 3 4% 6 5 .7 6 8 3 0 " ,, B e n z ie 3 7 .3 5 0 16 2 1 ,8 5 7 -4 1% 2 6 .9 9 3 -2 8 % B e r r ie n 6 3 .5 7 6 15 8 5 .3 4 2 34% 4 6 ,0 0 7 - 2 8 ” ,, B ran c h 1 3 .7 8 6 4 1 6 .3 6 6 19% 2 8 ,8 0 9 109% 147% B a rr y C a lh o u n 1 6 .9 7 2 5 5 0 ,2 0 5 196% 4 1 ,9 0 8 C ass 4 0 .6 6 7 4 3 5 .2 9 1 -1 3 % 4 1 ,0 4 5 1% C h a r l e v o ix 1 4 ,4 5 3 8 2 6 .7 1 5 85% 3 5 .5 3 7 146" „ C heboygan 4 5 .9 5 0 15 3 4 .5 5 8 -2 5 % 3 7 .8 1 8 -18% 3 ,1 8 2 3 2 1 .1 0 1 563% 2 0 .8 1 4 5 5 4 " ,, 4 3 .9 4 0 7 2 4 8 .7 6 9 11 % 1 6 .0 0 5 90% 2 6 .6 2 2 1 2 .8 8 9 -3 9 " ,, 8 ,4 0 9 C raw fo rd 1 6 .8 7 0 5 4 8 .4 1 1 187% 3 9 ,4 3 9 13 4 °,, D e lta 2 3 ,1 7 7 6 1 6 .0 3 3 -3 1 % 1 2 .1 9 5 3 ,2 4 9 6 8 ,4 5 6 160% C h ip p e w a C la r e C li n to n D ic k i n s o n E a to n 9 .5 1 1 5 .V <> -4 7 " ,, 193% 8 3 3 " ,, 1,771 1 1 8 ,5 6 2 948% 1 6 ,5 2 7 Em m et 2 6 ,5 3 1 9 2 8 ,1 4 5 6% 2 9 ,8 6 6 13% G enesee 5 2 ,8 3 0 13 6 3 .3 4 8 20% 6 8 ,0 0 6 29“ o G la d w in 4 0 ,2 1 0 8 2 1 ,5 9 4 -4 6 % 2 8 ,1 6 5 -3 0 % G o g e b ic 4 ,7 7 6 3 1 3 ,5 6 4 184% 1 7 ,6 5 7 270% 3 5 ,1 5 9 3 2 3 1 ,8 9 0 -9 % 7 ,0 9 0 - 8 0 “ ,, 1 1 .8 1 8 170% 1 8 .5 4 7 3 2 4 “ ,, 1 8 0 “ ,, G r a ti o t 1 li lls d a l c 4 ,3 7 8 1l o u g h t o n 1 3 ,0 7 6 11 3 0 ,2 4 2 131% 3 6 .6 7 2 H u ro n 7 2 ,2 6 7 19 3 5 ,3 6 8 -5 1 % 3 5 .7 1 3 -5 1 % 3 1 1 ,6 3 7 419% 3 2 ,7 0 8 1358% 246% In g h am 2 ,2 4 4 Io n ia 4 .9 5 8 4 1 1 ,7 1 5 136% 1 7 ,1 4 8 Io s c o 3 0 ,9 5 0 3 1 ,1 5 6 1% 3 9 ,1 6 5 27% Iro n 5 5 ,0 7 1 17 TT 4 0 .1 5 6 -2 7 % 4 9 .7 5 5 -1 0 % 1 2 .2 9 3 1 6 6 ,5 2 1 5 19 1 4 ,7 5 6 1 1 8 .3 6 1 20% -2 9 % 9 .1 0 5 7 3 .4 0 2 - 2 6 “ ,, - 5 6 ” ,, I s a b e lla Jackson 124 Table 31 (co n t'd ). N U M D L R O f M OAT IM Y S S u r v e y L s ti m a t c R e g io n /C o u n ty M o d e l L s ti m a t c M o d e l In p u t fro m 199 4 S u rv e y " C ases M o d e l I n p u t fr o m P r e v io u s M o d e l 1, P ercen t N o. (A ) D if f e r e n c e 1 (U ) P e r c e n t D if f e r e n c e K a la m a z o o 7 8 ,2 0 6 13 5 5 .1 1 3 -3 0 % 6 8 .2 2 2 K a lk a s k a 2 0 .5 2 6 4 2 6 .0 6 3 1 6 .7 0 8 -1 3 % -1 0 % K ent K ew eenaw 5 1 .7 4 5 21 1 3 9 .2 8 3 27% 169% 1 5 3 .6 3 7 1 9 7 " ,. 7 0 .1 3 2 16 2 1 .4 2 7 -6 9 % 2 2 .4 3 9 - 6 8 " .. 3 2 7 .5 9 8 588% 3 1 .4 7 4 1 akc 4 .0 1 4 L apeer 2 2 .5 9 7 7 1 0 .8 0 5 -5 2 % 1 5 .9 8 7 6 8 4 " ., - 2 0 " ,, fe c la n a u 1 1 .8 1 9 12 2 2 .2 9 8 89% 3 5 .8 9 3 2 0 4 " ,, Lenaw ee 4 6 .3 8 4 7 3 3 ,0 1 0 -2 9 % 3 3 .2 2 0 - 2 8 " ,, L i v in g s to n 3 1 .1 0 1 10 9 0 .9 9 9 193% 11 1 .3 9 6 2 5 8 " ,, I ucc 1 6 .9 5 2 10 1 6 .0 0 7 -6 % 9 .9 9 0 -4 1 % M a c k in a c 4 7 .3 7 9 18 5 0 .0 4 8 6% 2 5 .9 3 9 - 4 5 " ,, M acom b 1 0 7 .6 4 0 17 8 5 ,1 5 6 1 0 5 .9 5 4 M a n is te e 8 7 .1 0 1 24 7 9 .6 3 4 -2 1 % , -9 % M a r q u e t te 1 1 ,2 8 6 9 2 2 .5 0 6 9 9 " ,, 1 2 .1 9 3 8% M ason 1 9 .8 4 1 7 3 2 .9 9 8 66% 4 2 .7 1 2 1 15% M e c o s ta 1 3 .6 5 6 9 1 7 .9 6 3 32% 2 5 .2 1 7 85% 1 .8 2 6 4 6 .1 0 6 234% 1 1 .981 55o% M e n o m in e e 2 8 .7 5 7 -0 7 % M id la n d 7 6 .6 6 2 7 4 0 .0 1 3 -4 8 % 1 6 .9 9 9 -7 S % M is s a u k e e 3 0 .3 4 1 5 1 1 .2 7 3 -6 3 % 1 0 .6 2 6 -0 5 % M o n ro e 6 9 .8 2 0 24 4 9 .3 5 6 -2 9 % 4 1 .3 5 9 -4 1 " .. M o n tc a lm 8 2 .9 0 2 12 5 3 .0 7 2 -3 6 % 3 8 .0 4 9 -5 4 % M o n tm o r e n c y 1 7 .6 0 0 6 8 .9 3 9 -4 9 % 1 1 .8 2 7 - 5 3 " .. M u sk eg o n 9 3 .1 0 5 28 8 3 ,5 8 3 -1 0 % 9 0 .0 0 8 - 3 " .. N ew aygo O a k la n d 5 4 ,0 2 0 18 8 3 ,7 5 5 5.4% 6 0 .7 7 4 15% 18 1 .0 9 0 26 3 0 " .. 1X 2% 2 0 1 .4 7 0 11% 2 4 6 ,7 3 7 O ceana 9 .5 1 3 6 1 5 ,8 3 1 66% 2 6 ,8 5 9 O gem aw 1 9 .4 7 3 6 3 4 ,2 2 0 76% 3 8 ,1 9 1 W „ 8 ,0 6 4 7 1 6 ,4 4 3 104% 1 9 .8 6 3 1 4 0 " ., O n to n a g o n O s c e o la 1 0 ,3 6 8 5 9 .4 5 5 -9 % 1 5 .6 3 1 5 1% O sco d a 1 4 ,2 0 8 8 2 3 ,4 0 7 65% 3 0 ,9 8 8 1 IK ".. 5 5 " .. O ts e g o 1 6 ,0 3 5 5 2 4 ,1 4 1 51 % 2 4 .8 0 3 P r e s q u e Is le 2 2 ,6 3 6 8 3 1 .2 8 6 38% 2 2 .6 7 7 0 " .. R oscom m on 1 2 6 ,9 2 1 26 4 0 .8 5 6 -6 8 % 4 7 .0 8 7 -0 3 % S a g in a w 1 0 ,9 3 7 8 1 2 .6 1 5 255% 7 .1 5 2 4 1 1 ,3 4 9 15% 59% 3 8 ,7 7 8 S a m i Jo se p h 3 5 ,2 7 6 393".i S a n il a c 6 ,9 8 2 1 2 3 ,8 1 2 241 % 1 9 ,8 7 3 1X 5% S c h o o lc r a f t 8 ,5 0 3 8 2 1 7 ,0 8 6 101 % 1 8 .3 9 4 I 10% 102 % S h ia w a s s e e 3 .7 4 0 -3 3 % 1 1 .2 7 0 St C la ir 4 8 ,9 3 5 14 5 2 ,9 4 3 8% 6 7 .6 2 0 38% T u s c o la 4 2 ,9 2 1 9 5 8 ,5 0 6 36% 3 6 ,6 8 3 -1 5 % V an B u ren 9 3 ,2 6 6 16 6 6 ,4 2 7 -2 9 % 5 0 ,8 8 7 -4 5 " .. W a s h te n a w 9 8 .6 5 8 17 1 2 3 .5 2 7 25% 9 1 ,1 8 0 -8 % 1 1 4 .9 2 2 5 3 ,2 0 4 25 1 5 4 ,3 6 0 2 4 ,1 1 6 34% 1 7 3 ,0 2 1 -5 5 % 2 3 ,4 5 2 5 1 " .. -5 6 % W ayne W e x fo r d 5 ,5 8 2 21 a The m o d e l in p u t, n u m b e r o f b o a t d a y s in th e s to r a g e c o u n t ie s , a r e g e n e r a t e d d ir e c tl y f r o m th e 1 9 9 4 M i c h i g a n B o a t in g S u i t e s h I h e m o d e l in p u t , n u m b e r o f b o a t d a y s in th e s to r a g e c o u n t ie s , a r e g e n e r a te d f r o m p r e v i o u s b o a t d a y s g e n e r a tio n m o d e l c P e r c e n t d if f e r e n c e s a re c a l c u l a t e d a s ( m o d e l e s ti m a t e - s u r v e y e s t i m a t e ) / s u r v e y e s t i m a t e B oat D ays In C o u n tie s By B oat S torage S eg m en ts This section presents and ev a lu a te s the overall results o f trip distribution m odels w hich are used to estim a te the n u m b e r o f bo a t days in the c o u n tie s by boats in different storage segm ents. T he su m m a tio n o f “ overall trip distribution m o d e ls " includes the trip generation m odel, trip d istrib u tio n m odel for boats stored at m arin as in the coastal counties, trip d istribution m odel for boats stored at n o n w a te rfro n t hom es a n d trip distribution s c h em e for boats ke p t at m arin as in the inland counties, w aterfront hom es an d se co n d h o m e s 3'1. Results T a b le 31 s u m m a riz e s the pred ic tio n s o f the overall trip d istribution m odels. The total n u m b e r o f boat days in co u n tie s ranges from 2 4 ,2 0 0 days in Gratiot cou n ty to 7 2 7 .8 0 0 days in O a k la n d county. Fifteen percent o f the s ta te 's total boat days o c c u r in four southeast counties. C o nversely, nine north U pper P e n in su la co u n tie s host only 5% o f s ta te 's total boat days. A b o u t 18% o f boat days take place in the n o rtheast and northw est regions, 2 9 % in the so u th -in la n d region, 19% in the n o rth-inland and south U pper P en in su la regions, 9 % in the cen tral-w e st an d so u th w e st regions, and the rem a in in g 5% in the central-east region. T h e spatial d istribution o f boating destinations vary across storage segm ents. O ver forty percent o f the boat days generated by boats stored at m arin as take place in the southeast region, a n d a n o th e r 2 2 % o f days o c c u r in the no rth w est (1 4 % ) and central-w est A s m e n t i o n e d in th e m e t h o d c h a p te r , all th e boat d a y s g e n e r a t e d b y b o a t s st o r e d at m arin as in inland c o u n t i e s , s e c o n d h o m e s a n d w a te rfr o n t h o m e s are a l lo c a t e d to their s t o r a g e c o u n t i e s , a s s u m i n g that all th e boat d a y s ta k e p l a c e w i t h i n s t o r a g e c o u n t i e s . Table 31. N um ber o f Boat Days by Storage Segm ent and Destination County. B O A T STORAGE SEGM ENTS B o at d ay s (0 0 0 ’s) M a rin a D E S T IN A T IO N C O U N T Y /R E G IO N N o o f B o at C ol. % S econd H om e R ow % D ays N o o f B o at Col % Total W a te rfro n t H o m e R ow “ o D ay s N o . o f B o at C ol % N o n w a te rfro n t H o m e R ow % D ays N o o f B o at Col % R ow % D ays N o o f B o at C ol % D ays M acom b 2695 1 4.6% 4 4 .3 % 15.8 0 .5 % 2 .6 % 217 7 6 .0 % 3 5 .8 % 106 0 3 .1 % 174% 6 0 8 .9 M o n ro e 14 3 .0 7 .7 % 6 0 .6 % 8 .8 0 .3 % 3 .7 % 428 1 .2 % 1 8 .1 % 4 1 .4 1.2% 17 5 % 235 9 1 9% S t C la ir 158.8 8 .6 % 4 6 .2 % 5 7 .6 1.7% 168% 5 9 .7 1.6% 1 7 .4 % 6 7 .6 2 .0 % 19 7 % 343 8 2 .8 % 5 0% W ayne 194 4 10.5% 27 7% 3 0 .7 0 .9 % 44% 3045 8 .4 % 4 3 .3 % 173 .0 5 .0 % 24 6% 7 0 2 .6 5 .7 % SO U TH EA ST 76S.6 41.5% 40.5% 112.9 3.4% 6.0% 624.7 17.2% 3 3.0% 388.0 11.2% 20.5% 1.891.1 15.4% B ay 8 7 .9 4 8% 5 1 .3 % 4 .3 0 .1 % 25% 13 4 0 .4 % 7 .8 % 6 5 .8 1 9% 38 4% 171.4 1 4% H u ro n 4 5 .2 2 .5 % 2 9 .8 % 6 7 .0 2 .0 % 4 4 1% 40 0 .1 % 2 .7 % 3 5 .7 1.0% 23 5% 1520 1.2% 2.7 0 .1 % 4 .2 % 2 .7 0 .1 % 4 .1 % 209 0 .6 % 32 1% 38 .8 1.1% 59 6% 6 5 .0 0 5% S a g in a w S a n ila c 2 7 .0 1.5% 2 8 .4 % 4 5 .7 1.4% 4 8 .0 % 2 .7 0 .1 % 2 .8 % 199 0 .6 % 2 0 .8 % 953 0 8% T u s c o la 13.8 0 .7 % 2 1 .0 % 9 .8 0 .3 % 14 .8 % 5 .7 0 .2 % 8 .7 % 3 6 .7 1.1% 55 6 % 660 0 5% 4.5% 176.7 9.6% 32.1% 129.5 3.9% 23.6% 46.8 1.3% 8.5% 196.8 5.7% 35.8% 549.8 A lc o n a 4 .4 0 .2 % 3 .0 % 9 7 .3 2 .9 % 674% 17.0 0 .5 % 118% 25 7 0 .7 % 17 8 % 1444 12% A lp e n a 7.5 0 .4 % 7 .4 % 314 0 .9 % 3 0 .9 % 309 0 .9 % 3 0 .4 % 3 1 .8 0 .9 % 313% 101 7 0 .8 % C E N T R A L EA ST A ren ac 2 4 .7 1 .3% 1 7 .7 % 41 9 1 .2 % 2 9 .9 % 2 7 ,8 0 .8 % 1 9 .9 % 4 5 .6 1 .3 % 32 5% 1400 1.1% C heboygan 2 4 .4 1.3% 1 3 .5 % 83 9 2 .5 % 464% 34 7 1.0 % 1 9 .2 % 37 8 1.1% 20 9% 180 8 1.5% Iosco 2 9 .3 1.6°/. 13 3 % 1 15.3 3 .4 % 522% 3 7 .0 1.0 % 1 6 .8 % 3 9 .2 1.1% 17 7 % 220 8 1.8% P re s q u e Isle 10.4 0 .6 % 99% 52 .9 1 .6 % 5 0 .4 % 18 8 0 .5 % 18 0 % 2 2 .7 0 .7 % 21 6 % 104 8 0 .9 % 100.7 5.5% 11.3% 4 2 2 .7 12.6% 47.4% 166.3 4.6% 18.6% 202.8 5.9% 22.7% 892.6 7.3° o A n trim 9 .2 0 .5 % 5 9% 80 1 2 .4 % 511% 3 7 .3 1.0 % 23 8 % 30 .2 0 .9 % 19 3 % 1568 13% B e n z ie 2 7 .8 1.5% 2 0 .7 % 5 3 .6 1.6% 4 0 .0 % 2 5 .8 0 .7 % 1 9 .2 % 2 7 .0 0 .8 % 2 0 1% 134 2 1.1% C h a rle v o ix 65 5 3 .5 % 32 7% 66.1 2 .0 % 3 3 .0 % 3 3 .0 0 .9 % 1 6 .5 % 35.5 1.0% 17 8 % 200.1 1.6% E m m et 29.1 1.6% 1 7 .1 % 7 4 .7 2 .2 % 44 0% 3 6 .3 1.0 % 213% 2 9 .9 0 .9 % 17 6 % 170.0 1.4% G ra n d T ra v e rse 15.3 0 .8 % 6 .5 % 5 6 .2 1.7% 2 3 .8 % 926 2 .6 % 3 9 .2 % 72 2 2 .1 % 3 0 .6 % 2363 1.9% N O R T H E A ST L e elan a u 4 0 .5 2 .2 % 2 2 .1 % 7 1 .2 2 .1 % 3 8 .7 % 36 I 1 .0 % 1 9 .7 % 3 5 .9 1.0% 19 5 % 183 7 1 5% M a n is te e 3 9 .7 2 .2 % 2 6 .6 % 5 4.5 1.6 % 3 6 .5 % 2 6 .3 0 .7 % 1 7 .6 % 2 8 .8 0 .8 % 19 3 % 1493 12% M aso n N O RTH W EST M u sk e g o n O ceana O tta w a CENTR A L W EST 2 6 .8 1.5% 17 7 % 5 1 .9 1.5% 3 4 .3 % 298 0 .8 % 1 9 .7 % 4 2 .7 1.2% 2 8 .2 % 151.3 1 2% 25 3 .8 13.8% 18.4% 508.3 15.1% 36.8% 317.2 8.7% 23.0% 302.2 8.7% 21.9% 1.381.6 11.2% 5 0 .9 2 .8 % 264% 2 2 .7 0 .7 % 11 .8 % 29 1 0 .8 % 1 5 .1 % 9 0 .0 2 .6 % 4 6 7% 192.7 16% 88 0 .5 % 8 .1 % 6 7 .9 2 .0 % 6 2 .9 % 4 .4 0 .1 % 4 .1 % 2 6 .9 0 .8 % 249% 1080 0 .9 % 81 0 4 .4 % 28 9% 3 3 .5 1.0% 11 .9 % 4 5 .3 1.2 % 1 6 .2 % 120.4 3 .5 % 4 3 .0 % 280.1 2 3% 140.7 7.6% 24.2% 124.0 3.7% 21.4% 78.9 2.2% 13.6% 237.2 6.9% 40.8% 580.8 4.7% 1.5% A lle g an 25 .5 14% 13 9 % 2 2 .7 0 .7 % 12 3 % 577 1.6 % 31 4 % 78 2 2 .3 % 42 5% 184 1 B errien 4 5 .0 24% 21 8 % 36 9 1.1% 17 9 % 78 5 2 2 ” ci 38 ()n o 4 6 (I 1 3% 22 3% 206 4 1 7% V an B u ren 250 1 4% 16 7 % 29 1 (1 9 % 19 4 % 45 0 1 2% 30 0% 50.9 1 5%, 33 9 % 150 0 1 2",. SO U TH W EST 9 5 .5 5 .2 % 17.7% 88.7 2.6% 16.4% 181.2 5.0% 33.5",, 175.1 3 2 .4 % 540.4 5.1% 4.4",, Table 31 (cont'd). BO AT STORAGE SEGM ENTS B o a t d ay s ( 0 0 0 's) M anna D E S T IN A T IO N C O U N T Y /R E G IO N N o o f B o at Col % Second H om e R ow % D ay s N o o f B o at C ol % Total W a te rfro n t H o m e R ow 8 o D ays N o o f B o at C ol 80 N o n w a te rfro n t H o m e R ow 0 0 D ay s N o o f B o at C ol % R ow 0 0 D ays N o o l B oat C ol % D ays B arry 9-1 0 5% 6 .9 % 5 1.3 1 .5 % 3 7 .9 8 8 35 7 1.088 264% 3 9 .0 1 1% 28 8 8 o 135 3 B ran c h 7 5 0 .4 % 6 .2 % 57 8 1 .7 % 4 7 .5 % 27 5 0 888 2 2 .6 % 2 8 .8 0 .8 % 23.7 8 8 1217 1 0% C a lh o u n 30 0 .2 °/o 3 .4 % 0 .2 0 .0 % 0 .2 % 44 8 1 28o 4 9 .8 8 o 419 12% 46 6% 90 0 0 7% 114 C ass 1 1% 0 .6 % 7 .2 % 7 0.5 2 . 1% 4 4 .2 % 365 1.088 2 2 .9 % 410 1.288 25.78o 159 5 1 3% C lin to n 0 1 0 0% 0 . 1% 1.0 0 .0 % 2.688 25 9 0 788 6 5 .0 % 12.9 0 .4 % 3 2 388 39 9 0 3% 0 5% E aton 0.1 0 0% 0 1% 3.3 0 1% 5 .9 8 0 36 1 1.088 64.588 16.5 0 5% 2 9 58o 55 9 G e n e se e 17 0 . 1% 0 .7 % 17.7 0 5% 7 .6 % 143 7 4.088 62 2 % 68 0 2 0% 29.488 231.1 1 9% G ra tio t 0 2 0 .0 % 0 .9 % 2 .4 0 . 1% 9.8 8 8 14 5 0.488 60.0 8 8 7.1 0 288 2 9 388 24 2 0 2% H illsd a le I 7 0 1% 2 . 1% 4 0 .6 1.2 % 49 .6 8 o 21 0 0.688 2 5 .6 % 18.5 0 .5 % 22 78 „ 81 9 0 7% In g h am 0 .0 0 .0 % 0 .0 % 7.7 0 .2 % 6.8 8 0 72 9 2.088 6 4 .3 % 3 2 .7 0.988 2 8 888 1134 0 9% Ionia 04 0 .0 % 0 .9 % 8.7 0 .3 % 18 688 20 6 0 688 4 3 988 17 1 0.588 36.688 46 9 0 4% Isab ella 0.3 0 .0 % 0 .6 % 2 0 .9 0 .6 % 4 3 .4 8 8 17.8 0 588 37.1 8 8 9.1 0.388 18 988 48 1 0 4% Jackson 106 0 .6 % 5 .5 % 413 1.2 % 21 .4 8 8 6 7 .4 1.988 35.0 8 o 7 3 .4 2 . 180 38.188 192 6 1 6% K a la m a z o o 8 .0 0 .4 % 4 .7 % 13.7 0 .4 % 8.088 S2 0 2.388 4 7 788 6 8 .2 2.088 3 9 .7 % 171.9 1 4% K ent 7.2 0 4% 1.9% 3 0 .5 0 .9 % 8.088 1872 5.288 4 9 .5 8 8 153 .6 4.488 4 0 683 378 5 3 1% L a p eer 18 0 . 1% 2 .9 % 16 6 0 .5 % 26.5 8 8 284 0.888 4 5 .2 8 8 16 0 0.588 25 488 62 9 0 5% L enaw ee 23 0 . 1% 1.9% 4 8 .7 1.5% 3 9 .8 8 8 383 1.188 31.2 8 8 3 3 .2 1.088 27.188 122 6 1 0% 13 9 0 .8 % 6 .0 % 368 1. 1% 15.988 69 6 1.988 3 0 .1 % 111.4 3.288 4 8 188 2 3 1 .7 1.9% M id la n d 0.4 0 .0 % 0 .6 % 9.3 0 .3 % 13.988 40 5 1.188 60.2 8 8 17.0 0.588 25 388 67 2 0 5% M o n tc a lm 5 3 0 .3 % 3 .9 % 64.3 1.9% 4 8 .0 8 8 263 0 788 19.788 3 8 .0 1.188 2 8 488 133 9 I 1% 49 9 2 .7 % 6 .9 % 5 7.2 1 .7 % 7.988 3 7 3 .9 10.388 51.488 2 4 6 .7 7.188 33.9 8 8 727 8 5 980 L iv in g sto n O a k la n d S h ia w a s s e e 9 1 0 .5 % 1 2 .6 % 2 .6 0 1% 3.688 2 5 .5 0.788 35.2 8 8 35.3 1.088 4 8 .6 % 72 6 0 680 S t J o se p h 0 1 0 .0 % 0 . 1% 3 3 .2 1.0 % 4 1 .3 % 3 5 .8 1.088 44.5 8 8 11.3 0.388 14 088 80 3 0 788 W a sh ten aw S O U T H IN L A N D 7 .6 0 .4 % 4 .0 % 2 0 .9 0 .6 % 11.0 % 7 0 .4 1 5 2 .1 8 .2 % 4 .2 % 6 5 7 .4 1 9 .6 % 1 8 .4 % 1 ,5 4 2 .4 4 2 .5 % 1.988 3 7 .0 % 9 1 .2 4 5 .1 % 1 ,2 2 8 .1 5 5 .5 % 2 688 47.9 8 3 5 4 .5 % 190 2 5 ,5 8 0 .0 1 588 2 9 .1 % C la re 2.4 0 . 1% 1.6 % 9 1 .7 2 .7 % 6 0 .5 % 309 0 .9 % 20.488 266 0.888 17.683 151.7 12% C ra w fo rd 06 0 .0 % 0 .5 % 4 3 .3 1.3 % 4 1 .2 % 2 1 .7 0.688 20.788 3 9 .4 1 188 37 6 % 105 0 0 9% G la d w in 2 .0 0 . 1% 1.5% 6 0 .8 1.8 % 4 7 .8 8 o 3 6 .3 1.0 % 2 8 .5 % 2 8 .2 0.888 2 2 . 1% 127 2 1 088 K a lk a sk a 1.7 0 . 1% 2 .2 % 3 8 .4 1. 1% 51.088 18 5 0.588 24.688 16 7 0.588 2 2 28o 75 3 0 6% L ake 0 .9 0 .0 % 0 .7 % 8 2 .6 2 .5 % 6 3 .2 8 8 15 7 0.488 1 2 .0 % 3 1 .5 0.988 2 4 .1 % 130 7 1. 1% M e c o sta 4 .9 0 .3 % 4 .9 % 3 6 .2 I 1% 3 6 .0 % 34 4 0 9% 34.188 2 5 .2 0.788 25 0 % 100 7 0 888 M is sa u k e e 11 0 1% 2 . 1% 267 0 8% 4 9 .5 % 15 5 0 4% 28 7% 10 6 0 3% 19 7% 54 1) 0 4 °,, M o n tm o re n c v 5.1 0 .3 % 5 .9 % 53 9 1.6 % 6 2 .9 % 14 9 0 .4 % 17 4 % 11 8 0 3% 13 8 % 85 8 0 7%, N ew aygo 5 5 0 3% 3 2% 560 17% 3 3 .2 % 46 5 I 3% 27 5% 60 8 1.8 % 36 0% 168 7 1 4% Table 31 (cont'd). BO AT STORAGE SEG M EN TS B o a t d ay s ( 0 0 0 ’s) M arina D ES TIN ATION C O U N TY /R E G IO N N o o f Bo at C ol . % Second Home Row % D ay s No . o f Bo at Col % Total W aterfront H o m e Row % D ay s N o o f B o at Col % N o n w a te r f r o n t H o m e Ro w 0 o D ays N o o f B oa t Col % Row ° o D ays N o o f Boat Col. % Davs Ogemaw 2.4 0.1% 1. 9 % 62 9 1 9% 492% 24 3 0.7% 1 9 .0 % 38 2 1 1% 29 9% 127 7 10% Osceola 05 0.0% 0.7% 36 8 1 1% 52.8% 16 8 0 5% 24 0 % 15 6 0 5% 224% 69 .7 0.6% Oscoda 0.6 0.0% 0.6% 50 0 1 5% 52 3 % 140 0.4% 14 6 % 31 0 0 9% 32 4 % 95 6 0.8% Otsego 2.8 0.2% 3.2% 41 1 I 2% 45.8% 209 06% 23 4 % 24 8 0 7% 2 7 7% 89 7 0 7% 14 7 0.8% 6.4% 117 1 3 5% 509% 51 3 1. 4% 22 3 % 47 1 1 4% 20 5% 230 1 1 9% 1.3 0 1% 1 6% 24 (I 0 7% 29.4% 33 0 0.9% 403% 23 5 0 7% 28 7% 81 7 0 7% 15.8% Roscommon W exford 46.4 2.5% 2.7% 821.6 24.4% 48.5% 594.6 10.9% 25.5% 451.0 12.5% 25.4% 1.695.6 D elt a 7 1 0.4% 6.0% 59 9 1 8% 504% 25 9 07% 21.8% 25 9 0 8% 21 8 % 118 8 1 0% D ic k i n s o n - 0.0% 0.0% 42 0 1 2% 57 7 % 18 7 0 5% 25 8% 120 0 3% 16.5 % 72 .7 0 6% - 0 8% N O R T H IN LA N D Iron M ackinac M enominee S c h o o lc r a f t S O I T H I .P . A lg er 0.0% 0.0% 64 2 1 9% 69 2 % 13 8 0.4% 149% 14 8 0 4% 15 9 % 92 8 22 6 1.2% 12 8 % 100 5 3 0% 56.7% 17 3 0.5% 9.8% 36 7 1 1% 20 7% 176.8 1 4% 6.3 0.3% 8.6% 42 9 1 3% 580% 14 7 0.4% 19 9 % 10 0 0 3% 13 5 % 73 9 0.6% I 5 0.1% 2.0% 44 3 1 3% 58 0 % 106 0.3% 14 0 % 19 9 0 6% 26 0 % 76 3 0 6% 37.5 2.0% 6.1% 555.6 10.5% 57.8% 101.1 2.8% 16.5% 119.2 5.4% 19.5% 611.4 5.0% 122 2.5 0.1% 6.3% 129 0.4% 32 4 % 0 3% 30 7% 122 0 4% 30 6% 39 8 0.3% Baraga 10 1 0.5% 29 3% 79 0 2% 22.9% 7 1 0 2% 20 4% 9 5 0 3% 27 4 % 34 7 0 3% Chippew a 30 1 1.6% 20.4% 33 3 10% 22.6% 34 1 0.9% 23.1% 49 8 1 4% 33 8 % 1472 12% 2 7 0.1% 4.7% 176 0.5% 30 4 % 192 0 5% 33.2% 184 0 5% 31 7 % 57. 9 0 5% 0 5% Gogebic H oughton II 1 0 6% 17.1% 16 8 0 5% 25.8% 22 9 0.6% 35.3% 142 0 4% 21 8 % 65 0 Keweenaw 7 0 0.4% 17 9 % 89 0 3% 22 8% 24 0 1% 6 2% 20 8 0 6% 53 1% 392 0 3% Lu c e 0 2 0.0% 0.5% 7 7 0.2% 21 6 % 10 1 0.3% 28.4% 177 0 5% 49 4% 35 7 0.3% M arquette 10.2 0.6% 8.8% 28 4 0 8% 24.5% 54 8 1 .5 % 47.3% 22 4 0 6% 19. 4% 115 8 0 9% O ntonagon 2 6 0.1% 8.1% 85 0 3% 25.9% 94 03% 28 8% 122 0 4% 37 2% 32.8 0 3% 76.6 4.2% 15.5% 142.0 4.2% 25.0% 172.5 4.8% 50.5% 177.1 5.1% 51.2% 5 68.1 4.6% 1,8 4 5. 6 100% 15.0% 3 J6 0 .8 100% 2 7.3% 3.625.4 100% 2 9.5% 3 . 4 5 7 .6 100% 2 8.1% 12 ,2 89 .4 100% NORTH TOTAL I .P. no te: B e c a u s e ca s e s w it h m i s s i n g s to r a g e v a r i a b le s ar e e x c l u d e d fr o m t h e (s urvey b a s e d ) e s t i m a t e s o f b o a t s in d if fe re n t s to r ag e s e g m e n ts b \ sto ra ge r eg io ns (T a b le I !) th a t are u s e d in th e al lo ca t io n m o d e ls , t h e n u m b e r o f b o a t s e s ti m a t e d b y sto r a g e a l lo c a t io n m o d e ls is less t h a n th e n u m b e r o f regi ste red ac ti v e cra ft ( 5 5 5 , 0 0 0 bo ats) B e c a u s e th e e s t i m a t e s b y tr ip d i s tr i b u ti o n m o d e l ar e b a s e d on th e e s ti m a t e s d e r i v e d from the g e n e r a t i o n a n d al lo ca t io n m o d e ls , the m o d e l e s ti m a t e d n u m b e r o f boat d a y s is lo w e r th a n total n u m b e r o f b o a t d a y s ( 1 3 . 4 m i ll i o n d ay s ) r ep o r te d in 1994 R ec r ea ti o n al B o a t i n g S u r v e y ( S tv n e s et a l . 19 9 s ) 129 regions (8% ). Fifteen p ercent (2 6 9 .5 0 0 days) o f the boat days by boats stored at m arinas take place in M a c o m b county. A p p ro x im a te ly 35 p ercent o f boat days generated by boats stored at second hom es o c c u r in the n o rth-inland and south U p p e r P en in su la regions, and only 3.4% at the so u th e a st region. C h e b o y g a n . R o s c o m m o n , and M a c k in a c c ounties individually host over 10 0 .0 0 0 boat days. A lm o st 60 p ercent o f bo a t days generated by boats stored at w aterfront h o m e s take place in the so u th -in la n d (4 3 % ) and southeast regions (17% ), and only 2 .8 % in the south U p p e r P e n in su la region. C ounties, such as O a k la n d . W ayne and M a c o m b , w ith high po p u latio n density and fair a m o u n ts o f w ater resources receive m ore than 2 00.000 davs each. A lm o s t h a lf o f all boat days generated by boats stored at nonw a te rfro n t hom es o c c u r in the so u th -in la n d an d so u th e a st regions. 18% in the central-east, c e ntral-w est and so u th w e st regions. W a y n e (2 4 6 .7 0 0 days), Kent (1 7 3 .0 0 0 days), and O a k la n d (153.600 days) c o u n tie s host o v e r a h a lf m illio n boat days by boats stored at n o n w a te rfro n t hom es. T h e reg io n s vary significantly in the a m o u n t o f bo a tin g use by boats in different storage segm ents. For e x a m p le, a lm o st 21 m illion boat days take place in the southeast region. T h e greatest n u m b e r o f days are by boats stored at m arin as (4 1 % ) and w aterfront h o m e s (33% ). In c o m p a riso n , there are 6 1 1,400 days o f bo a tin g in the south U P region o f w h ic h 5 8 % is by bo a ts stored at second hom es. In the north U P region, a lm o st tw o-thirds (62% ) o f the 5 6 8 ,0 0 0 days are by boats stored at w a te rfro n t h o m e s (3 0 % ) and n o n w a te rfro n t h o m es (31% ). 130 T able 32 p ro v id e s an origin (storage location) - d e stin a tio n (use location) matrix. T he m atrix reveals the a m o u n t a n d p ro p o rtio n o f bo a t days in d e stination reg io n s by boats kept in the d iffe re n t origin regions. T he m atrix also sh o w s the n u m b e r and proportion of days gen e ra te d by bo a ts kept in regions that take place in d iffe re n t d e stination regions. A lo w e r perc e n ta g e o f boat d ay s generated by boats kept in so u th e rn M ic h ig a n — southeast, central-east, c e n tral-w e st and so uth-inland regions — o c c u r w ithin these regions. A bout 8 7 % o f boat days by boats ke p t in the so uth-inland region rem ain w ithin the region. 13% are e x p o rte d to the o th e r regions. C o m p a ra tiv e ly , a lm o s t all (ov er 9 5 % ) o f boat days by bo a ts kept in th e N o rth e rn M ic h ig a n rem a in w ithin the region. T h e origin-dcstination m atrix clearly s h o w s the “so u th -to -n o rth ” travel patterns for M ic h ig a n bo a tin g use. An origin (storage location)- de stin a tio n (use location) m atrix b ro k en d o w n by storage se g m e n t is included in the a p p e n d ix E. It sh o w s h o w boats in d iffe re n t storage segm ents co n trib u te to the o rig in -d e stin a tio n Hows. M odel Evaluation T h e p red ic tio n s o f overall trip distribution m o d e ls are e v a lu a te d by co m p a rin g m odel e s tim a te s w ith direct survey estim ates. T h e percent diffe re n c es be tw e en direct survey e s tim a tes and m o d el estim a tes ran g e from 2 % in G ra n d T ra v e rs e cou n ty to 4 4 4 2 % in Ingham county. O nly 4 boats w ere sa m p le d in Ingham county, so the survey based estim a tes is qu ite unreliable. M o s t c ounties w ith o v e r 100% d iffe re n c e h a v e sam p le sizes o f less th an 15 boats. U sa b le resp o n se s to the 1994 M ic h ig a n B o a tin g S urvey w e re less Table 32. N um ber o f Boat Days by Storage Region and Destination Region. Boat Da ys Destination Regions Southeast R ow P ci C o lu m n p c i. Central East R o w P c i. C o lu m n p c i. Northeast R o w Pci. C o lu m n p c i. Northw est S T O R A G E R E G IO N S Total South Central North North Central South Inland Inland East East East W est W est W est South North 1 ,7 9 0 ,9 5 6 95% 12,504 l% UP U P South North (pet.) 2.218 2,801 3.8 47 2,018 75.827 260 242 470 0% n% 0% n% 4% 0% 0% 0% 0% 86% 2% 0% n% 2 3 ,3 7 5 463.046 1.275 1.117 4% 84% (1% 0% i% 1.129 0% 0% 2% 0% 0% 2,484 55,447 1,760 46 83 o% 10% 0% o% 0% 1% 79% 0% 0% 0% n% i% 0% 0% 0% 17,559 31 .2 6 2 7 7 6 .3 0 8 3 .8 0 2 4 .87 5 1.908 47.768 8,0 42 328 699 2% 4% 87% 0% 1% 0% 5°/o 1% 0% 0% 1% 5% 98% n% 29,400 17.027 3 .923 1.2 3 0,927 l% 12.060 0% 1% 1% 0% 0% 8 .5 2 2 62.770 15.360 743 835 0% R o w P ci 2% l% 0% 89% l% i% 5% 1% 0% C o lu m n p c i. 1% 3% 0% 98% 2% 2% 2% 1% 0% 0% 11,969 3.5 87 739 2.692 5 1 4 .6 3 2 6 ,2 3 7 34.184 6.544 77 150 2% 1% 0% n% 89% 1% 6% 1% 0% 0% Central W est Rcrw P c i C o lu m n p c i. Southw est R om P e t C o lu m n p e l. Inland South R o w P ci. C o lu m n p c i. Inland North R o m Pci. C o lu m n p e t. U P South R om P e t ( 'o lu m n p c i UP North R om Pet. ( 'o lu m n p et. Total (percent) 1% 1% 0% 0% 86% 1% 1% 0% 0% n% 6,788 2.481 514 812 12.176 465.439 51.794 271 56 108 l% 0% ri% 0% 2% S6% 10% n% 0% 0% 0% 0% 0% 0% 0% 0% 0%, 2% 89% 114.073 12.180 100 858 13.324 28.181 3 .4 0 8 .0 0 4 3 .2 6 8 0 0 3% 0% 0% 0% 0% 1% 95% 0% 0% 0% l% 87% 5% 2% 0% 0% 2% 5% l)% 11% 0% 43.278 3 0 .5 8 2 3.049 5.686 12.843 5 .6 0 9 10 8.480 1.483.641 27 2 139 3% 2% 0% n% i% 0% 6% 88% 0% n% 2% 5% 0% 0% 2% /10' /o 3% 95% 0% 0% 15.155 8.433 1.373 2 .2 3 2 9.711 953 23.929 6 .0 4 9 53 8 .5 0 5 5,0 66 2% l% ri% n% 0% 4% 88% 1% 1% i% n% 0% TO • «. /O .TO0' 32 .8 3 3 7.231 851 3 .2 2 7 13.412 1.200 6% 1% O'.'n /% 2% o% 2% 1% t)°0 n% o 2 . 0 8 5 .3 8 5 5 8 8 .3 3 3 7 9 0 .3 4 8 1.254.1 54 5 9 8 .0 0 9 522.551 3 , 8 9 8 .5 9 9 5®o 6°o 10°o 5°o 4% 32% 17® o n%. D”„ 1100■ 1% 0°i) 99% 1% 3 0 .3 9 6 35.771 4 .1 9 7 4 3 9 ,0 0 6 6°„ 1",, -~On r„ 98”,, 1.560.9 67 5 4 4 .4 6 6 446 .5 5 5 13% 4% 4% 17, 1.891,143 15% 5 4 9 ,7 6 0 4% 892,551 7% 1.3 81,56 7 11% 5 8 0 ,8 1 0 5% 5 4 0 ,4 3 8 4% 3 . 5 7 9 ,9 8 7 29% 1,693,5 78 14% 6 1 1 .4 0 7 5% 5 6 8 .1 2 4 5% 12.2 89.3 66 132 than 30 for 42 out o f the 83 c o u n tie s 34. O nly 12 c o u n tie s had q u e s tio n n a ire s representing m ore than 100 boats. S a m p le sizes are m u c h sm a lle r for individual storage se g m e n ts at the cou n ty level. T h e 41 (d estin a tio n ) co u n tie s w ith s a m p le size grea ter than 30 boats p rovide a firm er basis for ev a lu a tin g trip d istribution m o d el (T a b le 33). W ith the e x c e p tio n o f th e c entral-east region and n o rth east region, the differences be tw e en direct survey e s tim a te s and m odel estim a tes are less than 12%. T he percent differences b e tw e en the tw o e s tim a tes are 2 1 % in c e n tral-ea st region and 2 3 % in the northeast region. In the no rth e a st region, there is a m a jo r diffe re n c e in e stim a tes o f boat days by boats kept in the se co n d h om es. T h e trip d istrib u tio n m o d e ls e s tim a te m ore boat days by boats at se co n d h o m e s c o m p a re d to the survey b ased estim ate. This m ay suggest that the boats stored at se co n d h o m e s are used less frequently in the n o rth east region, or the second h o m e o w n e rs have less pro p en sity to use o r store their bo a ts w ith in the region. F or the 41 c o u n tie s w ith s a m p le sizes m o re than 30 boats, the pe rc e n t difference ranges from 1% to 2 3 5 % . T h e pe rc e n t diffe re n c e is less than 10% for 13 c o unties, and m o re than 5 0 % for s e v en c o u n tie s (Iosco, O ceana, M e n o m in e e , H o u g h to n , and M ackinac. Barry and K ent counties). For the Iosco, O ceana, M e n o m in e e , H o u g h to n , an d M a ckinac counties, d ifferences b e tw e e n the tw o estim a tes are largely a ttrib u tab le to d iffe re n c es in the e stim ates o f boat days by boats stored at se co n d h o m es. M ost o f the differences b e tw een the e stim a tes for B arry and K e n t co u n tie s are c a u se d by the diffe re n c es in e stim ates for boats stored at w a te rfro n t and n o n w a te rfro n t h om es. T h e p e rc e n t difference only indicates the disc re p an c y b e tw e e n the m o d el e s tim a te an d direct survey estim ate. It '4 T h e b o a t s s e l e c t the c o u n t y a s o n e o f their b o a t i n g d e s t i n a t i o n s . 1994 M ic h ig a n B oating Surve\ q u e s t io n n a i r e a l l o w e d r e s p o n d e n t s to i n d ic a te o n e to three c o u n t i e s a s their m o s t fr eq u e n t b o a t in g d e s tin a t io n s . Table 33. B oat D ays by C o u n ty o f D estination; A C o m p a ris o n o f S u rvey and M odel Estim ates. Percent D istrib u tio n Moat d a y s ( 0 0 ( f ) M odel D ilT ercnceb S u rv ey E stim ates'1 difference' Non- S eco n d W aterfront D estination C o u n ty /R e g io n M arina Home w atcrlront Home I lom c All R eg io n al E stim a tes 1 . 8 9 1 .1 2.1 5 2 . 7 ( 543 -57 8 -238.4 -1 2 . 1 46 6 -261 6 C e n tra l l ast 549 8 454 3 ( 278 37 4 36.2 8 9 13 0 95 5 2 1 " ,, N ortheast 89 2 .6 723.3 ( 400 1 15 3 1 16 2 17 8 19 9 169 3 N o rthw est 1.381.6 1.354 6 ( 71 1 1 18 9 2 7.6 6.3 -25 8 26 9 23",, TO 580.8 551.2 ( 335 ) -5 2 36 .1 6 7 -7.9 29 6 5",, -10",. Southeast C entral W est -12",, f, 540.4 598.2 ( 221 ) -15 -8 1 2 0.9 -69 1 -57 8 S o u th Inland 3 .5 8 0 .0 3.5 4 1 .4 ( 462 ) -0.1 32.5 -65.5 716 38 6 N o rth Inland 1.693.6 1.682.6 ( 351 1 0.1 59.2 2.1 -50 4 1 1 (I i"„ 6 1 1 .4 65 7 .4 ( 296 ) -5.0 -14.2 -415 14 6 -46.0 -7"„ 568.1 5 7 3 .6 ( 3 1 1 ) -2 2 - 4 7 .1 56.3 -12 5 -5 5 -1% 12.2 8 9 .4 12.289.4 ( S o u thw est S o u th 1)1’ N o r t h 11.1’ TO TA I. 3908 r„ ) C o u n ty L ev el E s tim a te s F o r C o u n tie s W ith S a m p le S iz e s L a rg e r Than 3 0 B oats A lcona 144 4 1(13 5 ( 40 ) 2 9 23 4 6 .5 8 .2 40 9 4 0 " ,, A llegan 2 5 6 .5 ( 86 1 ■6 7 -2 /9 -3 4 9 -9 2 -7 2 7 -2 8 " ,, A lpena /,5V / 1 0 /7 105 5 ( 41 1 5 4 -1 7 4 9 5 -4 4 -6 5 -6 "„ A ntrim 1 5 0 .5 2 0 3 .8 ( 69 ) ■15 9 -6 4 - 1 6 .3 -8 4 -4 ~ 0 -2 3 " ,, A renac 140 0 98 9 ( 65 1 - 9 .7 1 8 .4 16 5 1 6 (1 41 / 4 2 "„ Harry 1 3 5 .3 3 7 2 .9 ( 41 1 - 7 .0 - 3 2 .2 -1 2 2 9 -7 5 5 -2 3 7 6 - 6 4 " ,, 5" „ Hay 17/ 4 166 7 ( 146 1 - 1 0 .8 - 1 .2 16 15 / 4 6 H cn/ic 1 3 4 .2 1 4 4 .0 ( 54 1 8 .0 3 .0 - 1 0 .4 -1 0 4 -9 5 H crrien 206 4 1 5 8 .7 ( 71 t 8 .4 23. 7 33 1 - 1 7 .6 47 ' C harlevoix 200. / 1 8 2 .9 ( 129 1 2 5 .4 -3 9 . 7 1 0 .5 2 1 .1 17 2 3 0 " ,, 9"„ Cheboygan 150 5 2 1 /0 ( 126 ) - 4 .8 - 3 .8 -1 3 4 -8 1 -3 0 2 C hipp ew a 147 2 206 7 ( 85 ) 111 - 6 1 .5 -3 8 -5 3 - 5 9 .5 -1 4 " ,, -2 9 " ,, D elta 1 1 5 .5 1 1 4 .4 ( 58 ) 0 .7 3 4 .0 - 8 .8 -2 1 4 4 5 4"„ Em m et (ira n d t raverse 1 7 0 .0 1 2 4 .0 ( III ) -1 4 .7 3 0 .8 2 6 .7 3 3 46 1 -2 .1 2 3 .3 2 3 6 .3 232 7 ( 109 ) 2 6 -2 0 1 3 7 3 7 ,,„ **«>. H oug h to n 65 .0 39 .0 ( 46 > 3. 5 1 2 .9 5 .7 4 0 26 0 67",, 1l u r u n 152.0 ( 66 1 25.8 4 5 2 8 -36 6 lo seo 220.8 155.5 1 2 9. 1 ( 86 / 16 9 58.7 7.8 8 2 -3 4 91 7 71" „ Jackson 192.6 34 9 .8 ( 39 ) 0.3 -11.2 -53 2 -93 1 -157 2 -45",, K alam azoo 171.9 197.6 ( 32 J -113 -18 6 14 2 -1 0 .0 -25 6 -13"., Kent 378.5 158 7 ( 36 ) 7 6 101 9 219.8 1 38 " ., 24 1 25 7 23 .6 -21 1 2 -5 4 -1 0 6 9 l.celanau 153 7 1 5 8 .0 ( 133 1 7.2 i i 18 3 1 03. 1 -1 8 9 M ackinac 176.8 3 8 8 .0 ( 169 ) -10 7 -138 8 -85.3 1 6 "., M acom b 605 9 7 1 5 .8 ( 161 1 64 7 - 9 1 .7 - 7 8 .2 - 1 .7 M anistee 149.3 164 1 ( 74 1 -7 1 510 -0.4 -58 3 -14 8 -I5 "„ -9"„ M arquette 1 15 .8 168 8 ( 67 1 -1 1 2 -119 17 8 -47 7 -53 0 -3 1"„ M ason 151.3 145 3 12 5 22 9 6 0 4",, 159 5 1 J -52 6 100.7 7 3.9 32 34 23 1 M ecosta ( ( -14 -83 7 14 8 116 -58 7 -37",, 2 2 .1 ( 32 ) 3.5 51 9 2 3 5 .9 2 3 2 .(1 < 77 ) 3 3 .8 42.9 - 2 6 .9 -7.0 M onroe 2 5 .4 -2 8 5 3 9 235",, •><< -3 .1 M enom inee 12 5 M uskegon 192 7 2 3 2 .7 ( 130 ) - 3 4 .0 1 .8 - 4 .6 - 4 0 .0 -r°u N ewaygo 168.7 245.0 ( 53 ) -7.2 -68.3 -7.5 6.8 -76.3 -31"., O ak la n d 727.8 6 2 6 .7 ( 60 ) 3 1 4 6 27 .8 65 .6 1011 16",, O ceana 108 0 5 8 .8 / 38 1 3 2 - 2 .1 1 7 .3 4 9 .2 84" v O ttaw a 280 1 259.7 ( 167 ) 25.5 3 6 13 5 -22 2 20 4 8"„ I’ r e s q u e Isle 104 8 72.2 ( 42 ) 4 6 37.0 -9.0 0 0 3 2.6 45"„ 3 3 2 .9 547. 7 ( 75 1 -8.1 ( 151 ) - 7 9 .3 - 7 1 .0 Roscom m on 230 1 St C lair 3 4 3 .8 V an U uren / 5 0 .0 1 8 2 .8 ( 64 ) W ayne 7 0 2 .6 817 6 5 7 .2 86 8 ( 154 ) - 3 .2 -77 / ( 30 ) 13 W exford 3 0 .7 -40 4 -7 9 8 -1 0 2 8 - 7 2 .3 18. 7 -2 0 3 9 -3 l" u -3 " " „ - 1 0 .0 22. 7 -4 2 4 -3 2 8 - 1 8 " ,. - 4 8 .8 113 1 4 5 .3 22.3 1.0 58 1 -29 8 25 6 -5 1 -6"„ 134 T able 33 (cont'd). Percent D istrib u tio n M oat d a v s 10 0 0 ' > M odel S u r v e y L stintatcs" D i f f e r e n c e 1’ dillerence Non­ S e c o n d W aterfront D estin atio n C o u n ty /R e g io n M arina Home Home w aterfront Home All C o u n t y L e v e l E s t i m a t e s For C o u n t i e s W ith S a m p l e S i z e s S m a l l e r T h a n 3 0 B o a t s A lger 39 3 5 9 .0 24 Baraga 34 7 IS . 1 21 Branch 121 7 119 3 16 90 0 ■15.5 3 2 3 0 .3 27 C lare 1 5 9 .5 1 5 1 .7 114 1 19 C linton 39 9 2 6 .1 4 C r a w lo r d 105 0 4 2 .3 14 D ick in so n 72. 7 1 1 .3 3 I C alhoun Cass I ) ) S V‘ - 7 .6 3 7 -4 3 -1 1 0 -1 9 1 - 3 .4 6 .6 7 .0 16 5 7 .5 3 3 .5 - 5 3 .7 6 .3 1 5 .0 3 .0 2 7 .3 2 4 .9 44 4 -3 2 .4 - 1 1 .3 3 7 .7 - 7 6 .5 0 .4 - 7 0 .8 -3 1 ";, 2 .4 4 3 .5 9 .0 - 1 7 .3 0 .1 1 .0 3 .2 4 .5 3 7 .6 1 3 .7 5 3 " ,, - 9 1 ",, 2 3 93 3 3 " ,, -1 .3 3 2 .2 3 .3 22 6 62 2 1 4 5 ",, 0 .0 3 2 .9 1 7 .9 1 0 .2 60 9 5 1 8 " ,, 55.9 1.8 1 1 0.1 3.3 36 14 8 54 2 3059",, C ie n c s e c 2311 174 2 28 ) -9.7 2.2 4 9.3 15 .2 570 33" „ G ladw in 127.2 57.9 122.6 28 ) 2.0 23 .0 -1 2 .0 4 6 4"„ 38.5 17 ) 1.2 -8.3 -10.9 1 9 .2 9 9 19 4 5 0 ' ’,, -54",, Baton (iogebic tiratiot 24.2 52.5 5 ) 0.2 2.4 -2 8 -2 8 .1 -28 3 H illsdale 8 1.9 62 5 7 ) 1.7 -10.8 1 4 .3 1 4 .2 19 4 31",, Ingham 1 13.4 2.5 4 ) 0.0 7. 7 72.7 1 10 9 4442",, Ionia 4 6.9 51 9 -2 9 9 12 .3 - 5 (I -111",, 92.8 88 1 ) 1 0.4 I ro n 10 17 30.5 12 2 0 0 -4.5 11 7 -2 5 4 7 5",, Isabella 48 1 46 6 14 ) -0.8 -9.0 -3 2 1 5 K alkaska 75 3 30 4 1 ) 17 29 6 1 4 .6 17.4 -3.8 44.8 3"„ 1 47" ,, Keweenaw 39 2 17 0 27 1 2 3 -0 8 17 6 22 2 1 31 ", , Lake Lapeer 130.7 1218 12 ) 0.9 3.1 -23 8 4 3 27.5 8.9 7“ „ 62 9 36 7 10 ) 1.8 16 3 14. 7 -6 6 26.2 -38.7 7 1" ,, - 2 4 " ,, Lenawee 122 6 1613 16 ) -0.7 29 .4 -54.3 -13.2 Livingston 231.7 257.8 26 ) 1 3 .9 0.8 -121.1 -2 6 .0 -I0"„ Luce 35.7 9.4 5 ) 0.2 3.1 10.1 80.3 1 2 .9 26 3 280",, M id la n d 67.2 108 9 12 1 0.4 0. 5 1 7 .0 -59.7 -417 M issa u k ee 54.0 85.2 13 ) 0.8 112 -23.5 -19 7 -312 -3 8 " ,, -3 7 " ,, M o ntcalm 13 3 9 209 3 25 ) 5 .3 7. 2 -4 2 .9 -44 9 -75 3 -36",, M o n tm o re n cy Ogemaw 85.8 96.2 15 ) 4.8 -14.7 5.2 -5.8 -10 4 -1 l " „ 127.7 62.3 16 ) 2 4 36 7 7.7 18.7 65.5 O ntonagon 32.8 17.1 19 ) 18 7 8 5.2 0.9 15 .6 105 ", , 9 1“ „ O sceo la 6 9.7 94 .7 -43.3 5.3 -25.0 -26",, 2 4.7 > ) 1 2 .6 95 6 11 12 0.5 O scoda -15 45 5 1 0 .0 1 6. 8 70 9 287",, O tsego 89.7 6 3.6 12 ) 2.8 -12 15 .7 8.8 26.0 41",, Saginaw 65 .0 36 0 16 1 -2.0 -11.2 14 .4 2 9.0 81",, S anilac 95.3 317 24 1 16 7 42 0 -8.0 27.8 12 9 63.6 201",, S choolcrall 76.3 33 1 12 ) 15 Shiaw assee 72.6 84 3 13 1 9.1 St J o s e p h 80 3 5.6 2 1 T uscola W ashtenaw 66 0 190.2 64 4 158 7 26 26 ) ) 19 4 10 5 118 43 2 131 ", , -311 -17 8 28 1 -11 7 0 1 33.2 35 8 5 .7 74 7 -14",, 1339",, 7.7 7 6 2 1 -5.6 -1 9 -6 2 -7.5 16 3" „ 36 9 314 20",, a N u m b e r s in t h e p a r e n t h e s e s a r e t h e u n w e i g h t e d c o u n t o f c a s e s in t h e c o u n t y f r o m t h e 1 9 9 4 M i c h i g a n H o m i n g S u r v e v h D i l l e r e n c e is c a l c u l a t e d a s e s t i m a t e s f r o m t r i p d i s t r i b u t i o n m o d e l s u b s t r a c t t h e e s t i m a t e s f r o m s u r v e y o b s e r v e d c. P e r c e n t d i f f e r e n c e is c a c u l a t e d a s t h e d i l l e r e n c e o v e r t h e e s t i m a t e s f r o m s u r v e y o b s e r v e d 135 d o c s not reveal w h ic h estim a te is m o re accurate. F or e x a m p le, direct survey estim a tes are quite different for Barry and K a la m a z o o counties. B e c a u se these tw o a djacent counties h ave sim ilar po p u latio n sizes an d bo atin g opp o rtu n itie s, they are e x p e cte d to have sim ilar b o a tin g use in the counties. T h e survey e s tim a tes tw ice as m a n y d ay s in B arry county than K a la m a z o o county. T h e m o d el predicts a sim ila r n u m b e r o f days in both counties. It app e ars that m odel e stim ate is m ore reasonable. T able 34 is a c o m p a ris o n o f survey based and m odel estim a ted origin (storage) - destination (use) m atrices. T h e origin-destination m atrix e stim ated from the 1994 M ic h ig a n B o a tin g S u rvey is reported in T a b le 5 on page 21. T a b le 32 on page 131 show s the m odel e stim a ted m atrix. T h e m atrix is used to e v aluate h o w well the m odel predicts the Hows o f boat days. T h e cells report the a bsolute and p ercent d iffe re n c es betw een the survey based and m odel based estim ates. T h e diagonal cells h ighlight d iffe re n c es betw een the survey b ased and m odel estim a ted o rig in-destination m atrices. T h e d iag o n a ls are boat days that o c c u r w ithin the regions by boats stored in those regions. For ex a m p le, the difference b e tw e en the m odel based and survey b ased estim a tes o f boat days o c curring in the northeast region by boats stored in the region is 140,420 days. T his is a 22% difference. W ith th e e x c e p tio n o f central-east, northeast, and so u th e rn U p p e r Peninsula regions, the p ercent differences for the estim a tes in the d iagonal cells are less than 12%. The d ifferences b e tw e en the tw o e stim ates are largely a ttrib u ted to the differences b e tw e en survey and m odel e stim a tes o f the total n u m b e r o f bo a t d ay s in storage regions. For e x a m p le, the ave ra g e n u m b e r o f boat days by boats stored in the central-east region is less than the state average (T a b le 20). This results in a 3 7 % diffe re n c e b e tw e e n the m odel Table 34. Boat Days by Storage Region and Destination Region: A Comparison o f Survey and Trip Distribution Model Estimates. REGIONS OF STORAGE Boat Days (000') CentralDestination Regions South-East East CentralNorth-East North-West West South-West 8 8% -88 0% (23) (2) 2.00 -13.86 41 8 2% 3.43 4% (1) 1.69 1014 4 % -45 9 % 1193 8% 3.45 NA (5) (2) (I) (0) 5.61 110.04 -0.30 -0.72 P e rc en t D ifference 31 6 % 31.2% -19 0 % -39 2% 1.13 NA Xo. o f b o a ts su rv ey b a sed (21) (216) (12) (I) (0) P e rc en t D ifference Central East North East U .P . North 0.11 2.58 X o. o f boats survey b a sed U.P. South -1.91 -1.88 -213.46 -10.6% (505) North Inland 6.16 11.38 South East South Inland -192.81 82 2% (1) (0) (54% 0.48 -0.42 104.05 -20 0 % 37 1% -90 2% 0.08 NA (23) (3) (1) (0 ) (278] -0.02 -5.92 765 5° o 0 0% 4 2 4% 0.64 1027 0 % 20 3% (12) (2) (2 ) (4 0 0 ] -10.33 -13.37 0.44 20.93 -56 4% -14 1% -46 5°o 149 2% 0.83 NA (12) (24) (23) II) (0 ) (7111 2.73 140.42* 0.43 9 6% 22.1% 12 6 % S o . o f boats su rr e y b a sed (6) (57) (2 82) (12) (5) (1) (21) 9.87 14.22 1.13 24.47 4.69 -11.02 P ercen t D ifference 50 5 % 506 4% 40 3% 2.0% 63 5% S o . o f boats su rr e y b a sed (10) (5) (14) (591) (31) Central West 23 3% 0.08 I0., 6.98 65 9 % North West -9 3% 150.44 P e rc en t D ifference 23 7 Total 0.47 NA 0.28 lh 2°o 32 1 5% 3.53 0.13 2.26 57.87 -11.01 -11.97 5.25 0.08 -0.13 56.50 705 4 % 6 6 4 9 5% 21 8 % 521 T o 12.7% -63 8% -25 9 % 40 4 1% NA 4 5 9° „ H) 8% S o o f boats su rre y based (1) 4.81 (1) (3) (3) (269) (28) (26) (2) (0 ) (2 ) 2.48 0.51 -0.25 -12.03 -21.43 -5.73 0.06 0.11 -31.21 P ercen t D ifference 242 4 % NA NA -23 T o -49 7% -4.4% -10 0% 0.27 NA NA NA -5 5% S o . o f boats su rr e y b a sed (I) (0) (0 ) (0) (27) (180) (13) (0 ) (0) (0) (221) 24.09 -2.15 -0.32 -2.15 -7.92 -9.25 70.84 -6.23 0.00 0.00 66.90 P ercen t D ifference 26 .8 % -15 0 % -762% -71 5% -37 3% -24 7% 2.1% -65 6 % NA NA 1 9% Xo. o f boats su rv ey b a sed (20) (3) (1 ) (2) (4) (7) (421) (4) (0 ) (0 ) (462) South West South Inland 5.05 2.74 2.84 6.32 5.61 -43.43 -72.35 0.27 0.08 -85.12 19 8% 8 8 3 .3 % 99 8% 97 0 % NA -28 6 % 4.6 % NA 135 8% -4 8% (8) (8) (1) (3) (4) (0) (50) (276) (0) 10.44 7.39 -1.87 -3.35 3.03 0.46 12.10 -0.11 P ercent D ifference 221 7% 7 09 1% - 5 7, 7% -60 0 % 45 4 % 92 1% 102 3% Xo. o f boats su rvey b a sed (3) (4) (23) (29) (3) (2) (9) 4.30 3.60 -0.53 0.50 -3.18 -6.33 P ercen t D ifference 15 1% 98 9 % - 3 8. 6% 18 5% -19 1% Xo. o f boats s u n ey b a sed (5) (4) (14) (15) (3) -129.13 158.26 140.03 26.61 -5 8% (5 80) 36 8% 5% 2 2% (657) North Inland P ercen t D ifference Xo. o f boats s u n e y based U.P. South U.P. North Total P ercen t D ifference S o o f hoals s u rre t b a sed 7.75 21 8% 1335) (303) 21 (3 52) 1) (351) -1 15.65 3.42 -84.14 -1 8% -1 7 . 7 % 208 7% -12 !% (5) (208) ( ID ) (296) -4.66 0.10 -7.53 8.21 -5.53 -84 1% -13 3% 0 3% -64 2% 1.9 % -1 0 % (3) (13) (6 ) (19) (229) (311) 56.79 -49.01 -0.91 -93.80 -122.56 13.72 0.00 10 5% -8 6 % (I 0 % -5 7 % -18 4% (346) (238) (6 23) (333) (232) ( ’ ■)« 0 .0 % (244) (3908) 4 140.400 d a y s arc th e d iffe r e n c e b e tw e e n th e m odel e s tim a te (7 7 6 .5 0 0 d a y s in T a b le 5 2 ) a nd s u r\e v b ase d e s tim a te (6 3 5 .0 0 0 d a \ s in T a b le 5 ) o f b o a t d a \ s in d ie n o rth e a s t re g io n b \ b o a ts s to re d in the re g io n 136 10.48 P ercen t D ifference 137 e s tim a tes o f total boat days (5 8 8 .3 0 0 days) and survey e stim ates (4 3 0 .1 0 0 days) by boats stored in the central-east region. Since ap p ro x im ate ly 8 0 % o f those boat days rem ains w ithin the central-east region (T a b le 32), the difference be tw e en the tw o estim ates co n trib u te s to the 3 1 % diffe re n c e b e tw e en the m odel a n d survey e s tim a tes o f the n u m b e r o f boat days oc c u rrin g in the region by boats stored in the region. CHAPTER V C O N C LU SIO N S T im e ly and a c curate b o a tin g use in fo rm a tio n is im p o rtan t for planning, m a n a g e m e n t and m a rk e tin g u n d e rta k e n by agencies, bo a tin g organ iz atio n s, an d boating related businesses. T h e re is a special need for regular e stim a tes o f bo a tin g use (e.g.. n u m b e r o f b o a ts in different types o f storage, n u m b e r o f boats kept in c o u nties, boating days in c o u n tie s) for m a n a g e m e n t, feasibility a s se s s m e n t and planning. C urrently the only sou rc e s o f in fo rm a tio n a rc state registration data, state-w ide bo a te r surveys, and local and special pu rp o se studies. A lth o u g h boat registration d ata are potentially useful, they do not p ro v id e a direct m e a n s to e stim a te bo atin g use o r boat storage. T he p roblem s w ith sta te -w id e bo a te r surveys are that they are costly (av e ra g in g about $ 1 0 .0 0 p e r usable que stio n n a ire), they are c o n d u c te d five to eight years apart, an d s a m p le sizes are insufficient to p ro d u c e reliable e s tim a tes o f bo a tin g use for c o u n tie s o r Great Lakes ports. Local (e.g.. feasibility o f a pa rticu la r m arin a) o r special p u rp o se studies do not provide in form ation to e v a lu a te trends or spatial patterns o f b o a tin g use. O ften local o r special p u rp o se studies rely on sta te -w id e bo a tin g surveys o r registration d a ta as starting p oints to e s tim a te local bo atin g use. T h e p rim ary ob jec tiv e o f this study w a s to d e v e lo p a system o f m o d e ls w hich utilizes va rio u s seco n d a ry d a ta so u rces to p ro d u c e reliable cou n ty level estim a tes o f bo atin g use by boats in different types o f storage. T h is c h a p te r re v ie w s the structure and 138 139 c o m p o n e n ts o f the system , s u m m a riz e s and evaluates the p e rfo rm a n c e o f the system , and d isc u s s e s s o m e lim itations o f the system and re c o m m e n d a tio n s for im p ro v in g and im p le m e n tin g the system . T H E SY STEM OF M O D ELS T he system o f m o d e ls utilizes boat registration data and the recent survey to e s tim a te bo atin g use at regional and co u n ty levels. T he system include classification, boat allocation, trip g e n e ra tio n an d trip d istrib u tio n m odels. A d isc rim in a n t analysis is used to classify registered bo a ts into (type of) storage s e g m e n ts — m arin as, second hom es, p e rm a n e n t w a te rfro n t h o m e s a n d p e rm a n e n t n o n w a te rfro n t hom es. B oats in each storage s e g m e n t are th en a llocated to th e c o u n tie s w here they are stored u sin g a set o f allocation m odels. A llo c a tio n m o d e ls w e r e d e v e lo p e d for four storage segm ents. T h e n u m b e r o f boat days in (d estin a tio n ) c o u n tie s by boats in different storage se g m e n ts is e stim ated by a trip g e neration m o d el an d a set o f trip distribution m odels. A trip generation m odel is used to predict n u m b e r o f b o a t days in the county o f storage. Then th o se boat days are d istributed to the d e stin a tio n c o u n tie s by trip d istribution m o d e ls for boats at each storage segm ent. M o d e ls are linked to g e th e r into a system . T h e e s tim a tes o f o n e m odel are used as an input for the n e x t m odel. F o r e x a m p le, the n u m b e r o f bo a ts stored in each county is an input for the trip g e n e ra tio n m o d e l w h ic h is further input to the d istrib u tio n m odel. Both allo c atio n m o d e ls and trip d istrib u tio n m o d els are b a sed on the distinct boating use c h a racteristics a n d patterns o f b oats in different storage segm ents. F or e x a m p le, different 140 trip distribution m o d e ls are established for boats stored at m arin as in coastal c ounties and boats stored at n o n w a te rfro n t hom es. C o m p a re d to dire c t survey based estim ates, the system o f m o d els provides s o m e w h a t m o re ro b u st use e stim ates by d ra w in g upon several in d ep e n d e n t sources o f data and by linking va rio u s types o f m o d els together. B o a t registration counts, m arina inventories and o th er local boating o p p o rtu n ity indices help to ground the e stim ates at the county level. R ecreational travel theories (i.e., d istance d ecay) and in fo rm a tio n on boating use patterns identified in p revious boating studies p rovide the c o n c ep tu a l basis for the m odels. In particular, m o s t bo atin g occurs either close to h o m e, o r c lose to w here boats are stored du rin g the season. M a rin a s a n d second h o m e s are the p rim a ry types o f storage aw ay from the bo a t o w n e r 's p rim ary residence and therefore ex p la in a c o n siderable share o f inter-regional flow s fro m residence location to storage location. O n the o th er hand, three p rim ary reaso n s for boats traveling outside the storage c o u n tie s are (1) boats stored near co u n ty bou n d a rie s b o a tin g in nearby counties, (2) bo a ts on e x te n d e d overnight cruises, a n d (3) b o a ts kept at n o n w a te rfro n t h o m e s trailering to b o a tin g sites. T H E M O D E L S A N D E S T IM A T E S O F B O A T I N G U S E T his section e v a lu a te s the overall p e rfo rm a n c e o f the system o f m o d els including the b o a tin g use e stim a tes predicted by the system o f m odels, and the principal m o d elin g strategies used in the system . T h e m o d e ls sh o u ld p rovide c o st-effective e stim ates o f boating use that are (1) c urrent an d (2) reliable at the regional and county level. T he a pproach to m o d elin g b o a tin g use is different fro m prev io u s atte m p ts in that two different m o d e lin g strategies are e m ployed: (1) in corporating type(s) o f storage as the principal structure o f the system , an d (2) inserting storage location as an inte rm e d ia te stage be tw e en location o f the o w n e r 's resid en ce and (use) de stin a tio n location. T he bo a tin g use estim a tes p ro d u ce d by the system o f m o d e ls c apture the spatial patterns o f M ic h ig a n boating use. T he p red o m in ate “ s o u th -to -n o rth " spatial patterns predicted by the system o f m o d e ls c o n firm sim ilar travel pa tte rn s o b se rv e d in previous M ic h ig a n bo atin g studies. T h e system o f m o d els sh o w s that the “ s o u th -to -n o rth " spatial patterns o c c u r w h e n bo a ts are m o v e d from the o w n e r s ' resid en ce to lo ca tio n s w h e re boats are kept du rin g the bo a tin g season. T he pattern also exists w h e n boats are m o v ed from their storage location to the (use) destinations. T h e m o d els also reveal that southern M ic h ig a n has the largest n u m b e r o f boats registered, the largest n u m b e r o f boats kept in the region d u rin g the bo a tin g se ason, and the largest n u m b e r o f boat days (used) in the region. It is difficult to assess the a c curacy o f bo atin g use e s tim a te s p ro d u ce d by the system o f m o d els be c au se there is no reliable seco n d a ry so u rc e o f in fo rm a tio n on boating use — bo a ts stored o r used in regions or counties. Direct e s tim a te s from the 1994 M ic h ig a n B oating Survey are c o m p a re d w ith the m odel e stim ates, but the direct survey estim a tes are subject to s a m p lin g errors. C o u n ty level e s tim a tes are usually subject to large sa m p lin g errors, especially for the c ounties w here less than 30 1994 M ichigan B oating Survey q u e stio n n a ires w ere returned. For e x a m p le, based on que stio n n a ires rep re sen tin g 25 boats, the survey e stim a ted that boats kept in B enzie count)' average 30 days o f use. T h e sta n d a rd e rror o f m ea n is ±5 days for this estim ate. In c o m p a riso n , the 142 survey e stim ate o f bo a tin g use in the n o rth w est region is also 30 days, but it is based on 471 q u e stionnaires. T h e standard error o f m ea n is ±1 day for this estim ate. T he estim ate o f average hoat days at the regional level is m u c h m ore reliable than the e stim ate at the county level. A c o m p a ris o n o f m o d el p red ic tio n s w ith direct survey based estim a tes sh o w s that the m odel estim a tes o f bo a tin g use are w ithin 10% o f survey e s tim a te s for m o st regional estim ates. R egional e stim ates o f boat days by m a rin a stored boats p ro d u ce d by the distribution m odel are w ithin 10 % o f direct survey estim a tes for every region e x c ep t for the southern U p p e r Peninsula. T he estim a tes o f days by bo a ts kept at nonw aterfront h o m e s are w ithin 10% o f survey estim a tes for each region, e x c e p t for the south-w est. The regional estim a tes by overall trip distribution m odel are w ith in 12 % o f survey estim ates, except for the central-east and north-east regions. M o d e l e s tim a tes that differ m ore than 10% from survey e stim ates are for regions w h e re a relatively sm all n u m b e r o f 1904 surveys w ere returned. A c o m p a ris o n o f m odel predictions w ith survey estim a tes for co u n tie s with sam p le sizes m ore than 30 boats indicates that m odel e s tim a tes are reasonably accurate. Storage a llo c atio n s are w ithin 2 0 % o f survey estim a tes for 22 o f 32 counties. E stim ates o f total boat days predicted by the trip d istrib u tio n m o d els for the four storage s e g m e n ts are w ithin 10% o f survey e stim a tes for 13 ( o f 41) counties, and b e tw e e n 1 1-30% for 14 ( o f 41) counties. C o u n ty e stim a tes o f boat days by m a rin a stored boats are w ithin 2 0 % o f survey e s tim a tes for every cou n ty w ith a s a m p le size o v e r 30. 143 S a m p lin g errors at county level associated w ith survey e s tim a te s arc likely m uch larger than the errors in the m o d e l estim ates. For ex a m p le, direct survey e s tim a tes o f'th e n u m b e r o f boat days are quite different for Barry a n d K a la m a z o o counties. T h e se two adjacent co u n tie s h a v e sim ilar p o p u latio n s and boating o p p o rtunities. T h e survey e stim ates tw ice as m an y days in Barry c o u n ty than K a la m a z o o county. T he m odel predicts a sim ilar n u m b e r o f da y s in both counties. T he system o f m o d e ls im proves the efficiency o f e stim a tin g b o a tin g use by in corporating m u ltip le data sources, linking several types o f m o d e ls and generating various types o f bo a tin g use estim ates. T h e system o f m o d els is d e v e lo p e d based on a large state-w ide bo atin g survey, regularly collected d ata sets (e.g., boat registrations, transient slip rentals) and o th e r secondary data sets regarding the inventories o f boating related resources/facilities. T h e M ic h ig a n bo atin g survey pro v id e s a necessary basis for d e v e lo p in g and e v a lu a tin g the m o d els c o m p risin g the system . By c o m b in in g m odels e stim ated periodically from the state-w ide b o a tin g survey w ith d a ta th at are g a thered on a regular basis an d in form ation on c o u n ty ’s bo a tin g “su p p ly ” variables, the system o f m o d els can p ro d u ce u p -to-date use e stim ates and predict bo atin g use d o w n to the county level. l'he linkages o f m o d els c o m p risin g the system also im prove th e efficiency o f the estim ates. E stim ates from individual m o d els pro v id e im p o rtan t b o a tin g use estim ates. In addition these e stim a tes are use d as inputs to o th er m o d els in the system . L inking the different m o d els reduces d ata req u irem e n ts for the individual m odels. For e x am ple, estim a tes o f the n u m b e r o f boats stored in co u n tie s gen e ra te d by the a llo catio n m o d e ls are 144 input to the trip generation m odel. W ith o u t the allocation m odel e stim ates, it w ould he n ec essa ry to have a n o th e r source o f in fo rm a tio n on the n u m b e r o f bo a ts stored in counties. C urrently this in fo rm a tio n is not c o llected on a re g u la r basis by any agency or organization. In addition, the system o f m o d e ls pro v id e s v a rio u s bo a tin g use e stim ates sim u lta n e o u sly -- n u m b e r o f b o a ts stored in the c o u n tie s w ithin different storage se g m e n ts, and the n u m b e r o f bo a t days in the (destination) c o u n tie s by different storage s egm ents. T h e se estim a tes can easily be aggregated into regional e stim a tes (i.e.. various types o f p la n n in g regions). W hile linking the different m o d e ls has a n u m b e r o f benefits, the d o w n s id e is the potential pro p ag a tio n and m a s k in g (ca n c e lin g out) o f errors. I f sy stem atic errors exist in e s tim a te s p ro d u ce d by o n e m o d el, they w o u ld be in co rporated into e s tim a tes p ro duced by m o d els that rely on these p rev io u s e s tim a tes a s input. F or e x a m p le , i f there are errors in e s tim a te s p ro d u c e d by the regional a llo catio n o f boats, they will carry o v e r to the county level allocation. Also, so m e errors m ay not be o b v io u s be c au se they can be canceled or m a s k e d by errors in estim a tes p ro d u ce d by o th er m o d e ls in the system s. M o n te Carlo sim u latio n e x p e rim e n ts co u ld be c o n d u c te d to a ssess a g g re g a tio n /p ro p a g a tio n errors. The system o f m o d els s h o w s that type o f storage is very useful for p red ictin g type, a m o u n t, and d istrib u tio n o f b o a tin g activities. T h e re are significant diffe re n c es in size and type (e.g., inboards, sail) o f boats in different types o f storage. T h e m o d e ls also reveal that boats in different storage s e g m e n ts h a v e distinct use patterns in clu d in g counties w here they are kept du rin g the season, use locations, a v e rage n u m b e r o f boat days and 145 average travel distance. In co rp o ratin g types o f storage into the system o f m o d els im prove the estim a tes o f the am o u n t an d spatial distribution o f boating use. P ro d u c in g separate use estim a tes for boats in different storage s e g m e n ts also p ro v id e s better in form ation to assist public or private a g e n cie s w ith p lanning and m a n a g e m e n t decisions. For e x a m p le , the n u m b e r o f boats stored at m arin as in a county is m uch m ore useful in d e te rm in in g the feasibility o f a p ro p o se d m arin a than an aggregate e stim ate o f all boats stored (or registered) in the county. Sim ilarly, the spatial distribution o f use by b o a ts stored at n o n w a tc rfro n t h o m e s is especially rele v an t for a ssessing the need o f public a ccess sites. f h e strategy o f in co rp o ratin g the location o f storage into the system o f m odels im p ro v e s bo a tin g use estim ates. P re v io u s boating studies e x a m in e d the spatial patterns o f boating use only from the lo cations o f the boat o w n e r 's resid e n ce s to bo a tin g (use) destinations. The tw o-stage a p p ro a c h is e m ployed in the system o f m o d e ls — from o w n e r 's resid en ce to storage location, then from storage location to boating (use) d e stin a tio n — better captures v ariatio n s in spatial m o v em e n ts. A lm o st h a lf (4 6 % ) o f boat days o c c u r o u tsid e the co u n tie s w h e re boat o w n e rs reside, but only 17% o c c u r outside the county w h e re the boat is kept du rin g the season. Spatial m o v e m e n t from locations o f residence to use d e stin a tio n s is largely e x p la in ed by the m o v e m e n t from the location o f residence to the storage location. T his ap p ro a c h is also helpful to m odel the spatial m o v e m e n t for boats kept in different types o f storage. For e x a m p le , 8 3 % o f boat days by boats stored at second h o m e s o c cur o u tsid e the county w h e re the boat o w n e rs reside. A lm o st all o f those boat days o c c u r in the county w here the second h o m e is located. 146 Therefore, there is no need to m odel distribution o f days from storage location to use location. L IM IT A T IO N S A N D R E C O M M E N D A T I O N S T his section disc u sse s study lim itations and re c o m m e n d a tio n s . First, the 1994 M ic h ig a n B oating Survey w a s the prim a ry d ata source used to d e v e lo p and evaluate the system o f m odels. Several survey e s tim a tes such as the d istrib u tio n o f boats in storage regions by boats in different storage se g m e n ts, the ave ra g e n u m b e r o f boat days by storage se g m e n ts, and the d istribution o f boat days w ithin d e stin a tio n zones by (storage) regions are key c o m p o n e n ts o f the m odels. T herefore, the pred ic tio n s by the system o f m o d els arc subject to the s a m p lin g errors associated w ith these estim ates. W ith 3.000 returns for the 1994 M ic h ig a n B o a tin g S urvey, m o st e stim a tes at the regional level are reliable. H o w e v er, this sam p le size is insufficient to generate reliable e stim a tes o f use by boats in different storage s e g m e n ts for so m e o f the regions. For these regions, there is s o m e c oncern a b out u sing these estim a tes as a basis for the allocation and d istrib u tio n m odels. R e d u c in g the n u m b e r o f cate g o rie s and s e g m e n ts w o u ld low er sa m p lin g errors asso c ia te d w ith the survey estim ates. F or e x a m p le, few er destination z o n e s m ay be used for boats ke p t at n o n w a te rfro n t h om es. O n the o ther hand, further research should focus on m o d e ls (i.e., spatial distribution m o d e ls o r probability m odels) that can predict th o se regional distributions. T h e trip generation m odel utilizes statew ide a v e ra g e s o f boat days to estim ate n u m b e r o f days generated by b o a ts stored in c ounties for e a c h type o f storage. A lthough analysis o f variance indicates that there is no statistically significant difference across regions for boats in m o st o f the storage segm ents, there still is c o n sid erab le variation in the e s tim a te s o f average boat days. Instead o f state ave ra g e boat days, o ther estim ates such as ave ra g e boat days for different reg io n s (i.e.. U p p e r P eninsula, northern Low er Peninsula, and southern L o w er P eninsula) or average boat days for coastal c ounties and for inland co u n tie s sh o u ld be c o n sid e re d for the trip g e neration m odel. Future research should focus on testing the a p p lication o f m ore sophisticated causal m o d els to produce m ore reliable e stim ates than those generated directly from the surveys. T h e 1994 M ic h ig a n B o a tin g Survey p rovided im portant d ata for d e v e lo p in g and ev a lu a tin g the system o f m odels. B oaters should be surveyed periodically to identify c h a n g es in m ark e t structure, bo a te r b e h a v io r and use patterns in o rd e r to update model p aram eters. A m u c h sh o rte r a n d less costly survey than w as c o n d u c te d in 1994 could p rovide a d e q u ate in fo rm a tio n to u pdate the m odels. S econdly, the a c curacy o f cou n ty level e s tim a tes d e p e n d s on the m easures (indices) o f a c o u n ty 's b o a tin g opportunities. R e liance on secondary sources of in form ation on the “ su p p ly " o f boating op p o rtu n itie s in co u n tie s raises so m e concerns. T his is true especially w h e n th ere are no inventories or in fo rm a tio n a b out county boating opp o rtu n itie s that are in co rp o rated into the m odels. For e x a m p le, there is no accurate c o u n t o f the n u m b e r o f m arin as, storage facilities o r b o a tin g reso u rces in inland counties. N u m b e r o f lakes and acres o f lakes w a s used as a p roxy for m arin a spaces in inland counties. F urther research should be directed at co n stru c tin g recreational boating o p p o rtu n ity indices, ev a lu a tin g a p p ropriate m ea su res o f b o a tin g op p o rtu n itie s in a given 148 area, and d e te rm in in g the rela tio n sh ip s b e tw een such b o a tin g op p o rtu n ity indices and the type and a m o u n t o f b o a tin g activities (i.e.. the relatio n sh ip b e tw e e n various supply variables and the bo a tin g "d em a n d "). Third, the estim a tes o f boating use produced by the m o d e ls arc for boats w ith valid M ichigan R egistrations. The e s tim a tes do not include n o n -m o to riz e d boats and boats u n d e r 16 feet in length. In som e inland counties, days by n o n -registered boats could rep re sen t a relatively large share o f bo atin g activities. E stim ate s o f the n u m b e r o f n o n ­ registered boats and their u se are needed for the system to p ro d u c e c o m p re h en siv e estim a tes o f boat use. In addition, lo cations w h e re boats are kept du rin g the season and types o f storage should be collected as part o f R egistration Data. This w ould e lim in a te the need to estim a te this in form ation a n d it will e n h a n ce the ability o f the system o f m odels to pro v id e reliable, c o m p re h e n s iv e and u p -to-date estim ates o f bo atin g use. A P P L IC A T IO N S T h e m o d els p ro v id e im portant in form ation for m a n a g e m e n t, m arketing and e c o n o m ic im pact asse ssm e n t. M odel p ro d u ce d e stim ates o f the n u m b e r o f boats kept in different counties and the n u m b e r o f boat days by boats in different types o f storage can be used to assess the c urrent a d e q u ac y and " n e e d ” for bo atin g facilities/services. The M ic h ig a n L egislation an d D e p a rtm e n t o f N atural R e so u rce s also require reliable estim ates o f the a m o u n t an d lo cations o f boating use to form ulate an d assess regulations and policies. O rigin an d d e stin a tio n patterns are essential in fo rm a tio n for the design o f 149 m ark e tin g and m a n a g e m e n t strategies a im e d at a ttracting different types o f boaters and bo atin g use. C urrently this in fo rm a tio n is not available on a regular basis for regions and counties. T he system o f m o d els can be the b ases for a recreational bo atin g inform ation system to su p p o rt p la n n in g an d m a n a g e m e n t decisions. Such an in fo rm a tio n system can serve the M ic h ig a n bo atin g (industry) better by p ro v id in g reliable b o a tin g use inform ation m ore co n v e n ie n tly a n d by m a tc h in g in fo rm a tio n w ith the n e e d s o f plan e rs and m anagers. W ith so m e additional w orks, th e system o f m o d els can be m a d e m o re user-convenient. C u rren tly the system o f m o d e ls is d e v e lo p e d on M ic ro so ft Excel sp read sh eets. Additional p r o g ra m m in g is n e e d ed to m a k e the system m o re “ user friendly” including: (1) capability to generate standard reports, (2) the ability to m o d ify m o d el pa ra m ete rs. (3) u p d ating data on w h ic h m o d e ls are based, a n d (4) p ro v id in g different op tio n s for users. A dditional p ro g ra m m in g and instruction o n use o f the system will facilitate use by a gencies and o rganizations. A P PE N D IX A A P P L I C A T IO N F O R C E R T I F I C A T E O F W A T E R C R A F T TITLI A N D /O R R E G IST R A T IO N 150 APPLICATION FOR CERTIFICATE OF WATERCRAFT TITLE A N D /O R REGISTRATION *° *£T!»m MUkflPOMM * « (E nter Hull M aterial, T y p e, P ow er, U s e a n d F u e l F rom t h e L ist B e lo w ) J nv-H«RT> »4 r* wr>*4uR Idantrtrahon Nu>r**r j C ounty n( I t a M ltn r t H ,4 M M tnal OwWj UM ..I. -no^l C Om w G o n tp td e N « m e < s) a n d \M < » 4 s CD OW N ER W H>',* i nf rx f^ n tS on WATERCRAFT MC CD OTHER III PRESENTED: USE THIS SECTION FOR TAX EXEMPT TRANSACTIONS (S e e Instruction* On R everse Side) IF V OUN T ITLE IS N O T R E C E IV E D W IT H IN 6 0 DAYS F R O M T H E D ATE O F F IL IN G , C O N T A C T A S E C R E T A R Y O f STATE O F F IC E I Cort* j Uorial nr f +nm t O w n e m ’ C o m p te l e and j C 15! U P O N S A L E O F T H I S V E S S E L P R E S E N T T H IS R E G I S T R A T I O N 4A N D T I U L , IF I S S U E D ) t O T H E P U R C H A S E R O N TH IS O A T t f 1 I sold or transferrp'd W»s o w iw ) J ) [ ) IP reseol rtvs rryQrsfTiifion *o °®w S p Hphq P o c p S I c h a n g e d m y ad d re ss I d estroyed or ahandnned this vessrH *41 W O W M p r . C O M P l f I f NAMf M O f f T APT** V , C itv Z IP r.O O f stau I c e r t i f y m e a b o v e s t a t e m e n t »s in * * O w n e r's S ig n a tu re X _ ____________________ i n p i x m l e a \« o n e rl to Ifwv « e v < <•. jrv) ia r tm A h r h m V f 'i r t to any ofi«r» V f ' . v t optfw alt* n > e n > e r <1 lo a t u m t u r m *l a n y m a n rx t » « «rtr*>l to f»w f»r* «^1 ( n » * cittarM O a lr j»*» r *»r.i •* 'J v ~*I Wr*«. , <«*>iy r> ti *»r « u «1ant iM ttr'* USE TAX RETURN THE SECTIO N PR O V IDIN G F O R PAYMENT O F TAX IS C O M P L E T E D A S FO LLO W S: L i n e 1r . n t o i t h e lu ll p u r c h a s e p r i c e o r r e ta i l d o lla r v a l u e T h e lu ll p u r c h a s e p r t c e i n c l u d e s I h e lu ll a m o u n t p a i d l o t h e p r e v i o u s o w n e r t o g e t h e r w i t h a n y o u t s t a n d i n g d e b t n w ttd S u c h p a y m e n t m e a n s m o n e y , c r e d it, s e r v ic e s r e n d e r e d , t r a d e s , or a n y th in g o l v a lu e T h e a m o u n t a llo w e d lo r tr a d e - i n is n o t d e d u c t ib l e R eta il D ollar V alu e: tl a d e f in i t e d o lla r v a l u e h a s n o t b e e n e s t a b l i s h e d b e f o r e a p p l y i n g l o r h lk*. t h e p r i c e t o b o u s e d in c o m p u t i n g ta x s h a l l n o t b e l e s s t h a n tin* v e s s e l 's s u g g e s t e d r e t a i l d o lla r v a l u e a s l i s t e d m a n y c u r r e n t l y r e c o g n i z e d j i p p r a i s a l g u id e lin e ? I n t e r t o u r p e r c e n t ( 4 % ) o t t h e a m o u n t o t lin e t lin e 3 I n t e r a n y S a l e s o r U s e T a x p a r d in a n o t h e r s t a t e ( i n c l u d i n g t a x p a i d t o l o c a l g o v e r n m e n ! u n its ) w h ic h is r e c i p r o c a l w ith M ic h ig a n L in e 4 S u b m it p ro o f (in te r th e a m o u n t o l u s e ta x d u e II Im e 3 is c o m p l e t e d , t h e t a x d u e w ill b e d i t t o r e n c o b e t w e e n l i n e 2 a n d t h e t a x s h o w n a s p a i d o n lin e 3 In a ll o t h e r c m in **■. im e 4 wiH b e t h e s a m e a s U ne ? EX EM PTIO N — T r a n s fe r s B e t w e e n R e la tiv e s : A n e x e m p t i o n I t o m u s e ta x is a l l o w e d w h e n t h e n e w o w n e r is t h e s p o u s e p r e v io u s o w n e iD o c u m e n ta tio n p n .y m y th e I m u l d e t i r f m i n . i l io n o t t f u m o t h e r . b r o t h e r , s is te r < i> iie i t t . n lia b ility is m a d e b y t h e Mic h i y a n D e p o t t m e n t o f T r e a s u i y d o c u m e n t y o u r t a x r e t u r n or p r o v e p e n a ltie s in c lu d e th e a d d e d ta x a r e e n title d t o th e e x e m p tio n c la m ie o .» n e g l i g e n c e p e n a lly , p lu s p e n a l t i e s c a n h e m i p n s f d a n l u d .n g n in in o l p r o s e c u t i o n A p e r s o n w h o v i o l a t e s .-i p i e v im o i i • ,t la » is g u ilty o t a l e l u r i y h u t* . S e< ? I P u h ln la th e r < Mild ■ ‘ 'hr* re la tio n s h ip m ay b e r e q u e s t e d b y th e D e p a rtm e n t o l T re a s u ry or ju h • - • ; fn m u :..' te n i n t e r e s t f r o m m e d a t e o f ti li n g t h i s a p p l e .m - < A d d i t a s s e s s in g -,e< . 1 nii i w it h m ie n * t o d e f i a n d *,< !< •*vad» p u n is h a b le t i >i c - u n , Y ou m ay t • rei It y o u c a n n o t s u p p o r l y m n < ' S ‘> ( H 'l 1O l ' . 'n ; s m u' u p l r 1/-"> p e r c e n t o t t h e t a x d u e m e p a y m e n t u t a l.i» • ■ ip .iit ■ u n n - n l l o r n o l h iu m - h , - - ^ ,.. ' t« - l C m /i'* Ot C-i*)# R IC H A R D H A U STIN S n r r o la r y ol SM lp W ATERCRAFT _____ C o )c I yf>* ou-ity o ' O n s r te o t r Povue' Coo* r r^ Own©' s Cckotarlp Haini -ip tp t# NA'T'A »nr) "<3&" • II H ih w v ih ) 1C R E G IS T R A T IO N M U S T B E IN P O S S E S S I O N O F O P E R A T O R W H E N E V E R THE V E S S E L IS IN U S E |C h * n 0p U P O N S A LE O F T H IS V E S S E L , P R E S E N T T H IS R E G IS T R A T IO N (A ND TITLE IF IS S U E D ) T O T H E P U R C H A S E R NOTiCC O N TH IS O A T E ( ..] 1 s o ld ° f tr a n s f e r r e d th is v e s s e l ow ner ) □ I c h a n g e d my a d d re ss I ( P r e s e n t th is r e g is tr a tio n to th e n o w Th*- leiV ***1 ItOAl ‘>»l©'y All LX 197* '©QkA«©S *11 VtAle* lo CO^XlW* m u re OelJUlOC? •nlf*m‘j l n v ' i>*' l>«tw©l©ga»itaiio'- >n IN S IH Q C T IO N S 1 I d e s t r o y e d or a b a n d o n e d th is v e s s e l I ? Ni*» Omhmw » C o'T 'pteie N a n ta a n d A dtu*xy l'4 'i 1 & ? m wu fie fill©,) r>i,I n v n p lp ir ty W «© in e d()(»i>(v*die R.x’.t w a 'tc iievcnpK jG m i i « m j t c 'v .g n o t o<*. u s e ch.* o o e num tie- ar-kil ,>pscr,|) ihvi igi4&s A ium nxi'P O lfto' TV Pf P O w tn y lL fU C l l V J • 1 :* 3 4 • 2 3 4 5 ’ G as 2 D rew* 3 E iertnc O pen CaOrfi Sar hr»© b PORIOOC N u m b e r a s s i g n e d to th is v e s s e l is p e r m a n e n t a n d s h a ll not b e tra n s f e r r e d to a n y o th e r v e s s e l V e s s e l o p e r a to r is re q u ir e d to r e n d e r a s s i s t a n c e a n d r e p o r t a n y m a rin e a c c id e n t to th e n e a r e s t p e a c e o ffic er, s t a t e p o lic e p o s t o r s h e riff o l th e c o u n ty in w hich th e a c c id e n t o c c u r s A ||( i f A n im H.’ktAi A n V)3 Ul < e n r « t a m e n d e d ri,i>ii oi »r»* iiypiir.ji.iv InooilO O j t tx j i'0 SlU San* POAN i O iH f P(rw©< 6 N o Pen*©* r v a iu -e C om m ercial L<«0>y O lbw C om m ercial F 'e ^ n i 6 C o rn m t-c .a 1 A P P E N D IX B 1994 M IC H IG A N R E C R E A T I O N A L B O A T IN G S U R V E Y Q U E S T IO N N A IR I 1994 MICHIGAN RECREATIONAL BOATING SURVEY 1 H o w m a n y b o a t s d o y o u o w n th a t w e re r e g is te r e d in M ic h ig a n in 1 9 9 4 ? ___________________ IF Y O U O W N M O R E T H A N O N E B O A T T H A T IS R E G IS T E R E D IN M IC H IG A N , P L E A S E A N S W E R T H I S S U R V E Y O N L Y F O R T H E B O A T I D E N T IF IE D IN T H E A D D R E S S L A B E L O N YOUR ENVELOPE 2. W a s y o u r b o a t u s e d f o r re c r e a tio n in M ic h ig a n in 19 9 4 ? O YES IF Y O U R r* )A T W A S IN A C T IV E IN 1994, P IX A SF. S K IP T O Q t T .S IIO N 24 £ A N D F O I J jO W T H F . IN S T R U C T IO N S FOR R E T U R N IN G T H IS SUR VI Y D E S C R IP T IV E IN FO R M A TIO N ABOUT YOUR BO A T Y T y p c o fb o a t (ch eck o ne) : P P □ In b o a r d I n b o a r d /o u tb o a r d O u tb o a r d 4. B o a t le n g th ( f e e t ) __________ _ _ □ □ □ S a il, u n p o w c rc d S a il, w ith p o w er P o n to o n Q C a n o e o r R ow D P e rs o n a l w a tc rc r a f l (e g Jet sk i) □ O th e r , p le a s e s p e c i f y ___________ __ 5 H o w lo n g h a v e y o u o w n e d th i s b o a(7 m o n th s y e a rs 6 . W h e r e d id y o u u s u a lly k e e p th i s b o a t d u r in g th e 1994 b o a tin g s e a s o n 9 a . C o u n ty w h e r e th e b o a t w a s k e p i _____________________________ b. T y p e o f fa c ility ( c h e c k o n e ) c. D u r in g t h e 1 9 9 4 b o a tin g s e a s o n , w h e r e w as y o u r b o a t k e p t ' □ p e r m a n e n t re s id e n c e □ c o t ta g e o r s e c o n d h o m e P p u b li c m a r in a □ r e n t e d s p a c e in a c o m m e r c ia l m a r in a □ o w n e d s p a c e in m a r in a o r d o c k a m in iu n i P y a c h t f b o a t c lu b P O t h e r (p le a s e s p e c i f y ) __________________ □ O n la n d □ In a d r y s ta c k fa c ility □ In th e w a te r (w et s lip , m o o r in g or d o c k s id c ) □ A tta c h e d to o r o n a la r g e r b a i t □ O th e r ( p le a s e s p e c i f y ) ________ d W a s th i s lo c a tio n ( c h e c k o n e): P P □ P A w a te rf r o n t s ite w ith a c c e s s to th e G re a t L a k e s & c o n n e c tin g w a te rs A n in la n d la k e w a te rf r o n t site (n o G r e a t L a k e s a c c e s s) A n v e r o r s tr e a m w a te rfro n t s ite ( n o G r e a t L a k e s a c c e s s) A n o n - w a te rf ro n t s ite 7 In 1 9 9 5 d o y o u in t e n d to ( c h e c k o n e ) P C o n tin u e lo u se th is b o at □ S ell o r d is p o s e o f th is b o at 0 ^ S k ip to Q u e s tio n w K 7 a. W ill th i s b o a t b e re g is te r e d in M ic h ig a n in I9 9 5 9 □ YES O NO 7 b D u r in g t h e 1995 b o a tin g s e a s o n , w ill y o u k ee p th is b o at in th e s a m e c o u n ty a s in 19 9 4 9 □ YES □ N O T SURE □ NO O W h a t c o u n ty in 19957 7 c In 1 9 9 5 , w ill y o u k e e p (h is b o a t m th e s a m e k in d o f f a c ility a s in 1994 (see c a te g o r ie s in q u e s tio n o h ) ’* □ 7d YES □ N O T SURE □ NO ^ W h a t ty p e o f la c iliiy tn 1 9 9 5 9 ___ W ill y o u !u i\e d n e c l a c c e s s lo G r e a t I^akes w aters fro m tin s fa c ility in I9 9 5 9 D YES D NO 154 U SE O F Y O U R BOAT IN M IC H IG A N W A TERS IN 1994 8. P le a s e e s ti m a t e to t h e b e s t o f y o u r r e c o lle c tio n th e to ta l n u m b e r o f d a y s th is b o a t w a s u s e d m M ic h ig a n u a i c r s in 1 9 9 4 , w h e th e r b y y o u o r s o m e o n e e l s e C o u n t e a c h d a y o r p a r t o f a d a y th a t th e b o a t w as u n d e rw a y a s o n e d a y o f b o a tin g . R e p o r t d a y s o f u s e o n ly fo r th e b o a t y o u d e s c rib e d a b o v e . ________________________T O T A L D A Y S T H I S B O A T W A S U S E D IN M I C H I G A N D U R I N G 1994 9 N o w p le a s e d iv i d e th i s u s e b e tw e e n G R E A T L A K E S a n d IN L A N D b o a tin g u s in g th e d e f in itio n s at th e r ig h t Y o u r e s ti m a t e s o f G R E A T L A K E S a n d IN L A N D b o a tin g u s e s h o u ld s u m to th e to ta l y o u e n te re d in q u e s tio n 8 G R E A T L A K E S B O A T I N G D A Y S = a n y d a y s th a t th e b o a t w a s u n d e rw a y o n th e G r e a t L a k e s a n d c o n n e c tin g w a te rw a y s {takes Huron. Sujx-nor. /{nr, M ic h ig a n , a n d S t C la ir , th e S t M a ry 's . S t.( 'la i r a n d / V m u / H ie c r), in c lu d in g la k e s a n d r iv e r s th a t p ro v id e a c c e s s to th e G re a t L a k e s I N L A N D B O A T I N G D A Y S = a n y d a y s th e b o a t w as u n d e r w a y o n ly o n in la n d la k e s a n d s tre a m s th a t d o n o t p r o v id e d ire c t a c c e s s to th e G re a t L i k e s 10. I n t h e ta b le b e lo w n a m e th e M ic h i g a n c o u n tie s (se e th e e n c lo s e d m a p ) in w h ic h th i s b o m w a s u se d in 199 4 . b e g i n n in g w ith th e lo c a tio n u s e d m o s t fre q u e n tly . In C o lu m n B . e s tim a te th e to ta l n u m b e r o f d a y s th e b o a t w as u n d e r w a y in e a c h o f th e s e c o u n tie s . In c o lu m n C , e n te r th e n u m b e r o f th e s e d a y s th a t th e b o at w a s u s e d o n th e G r e a t L a k e s o r c o n n e c tin g w a te rs in th i s c o u n ty ( a s d e f in e d a b o v e ) C o lu m n B B O A T IN G U S E BY COUNTY EX A M PLE C o u n ty u s e d m o s t o fte n M I C H IG A N C O U N T Y ( s e c m a p fo r c o u n ty n a m e s ) D a y s b o a t u a s u s e d in th is c o u n ty in 1 9 9 4 . all u a i c r s C f f a V -T u / 1 C o lu m n C' D ay s b o at u a s u s e d in th is c o u n ty . G re a t L a k e s w a te rs 6- C o u n ty u s e d 2 n d m o s t o fte n C o u n ty u s e d 3 r d m o s t o fte n A ll o th e r c o u n tie s A L L O T H E R C O U N T IE S N o te: I f y o u b o a te d in m o re th a n o n e c o u n ty on the sam e day, a ssig n th a t d a y to the c o u n ty used fo r the m ost tim e I f you b o a te d in m o re th a n th ree c o u n tie s in 1994, r e c o r d the d ays the b o a t w as u sed in a ll o th e r counties in fhe fin a l row See e n c lo se d m a p f o r c o u n ty nam es. 11. E s tim a te th e p e r c e n ta g e o f u s e o f th i s b o a t in 1994 th a t in v o lv e d e a c h o f th e f o llo w in g a c tiv itie s (T h e four p ctccn U ag cs s h o u ld a d d to 100% E n t e r z e ro if y o u d id n ot u s e th i s b o a t fo r a g iv e n a c tiv ity ) P le a s u r e b o a t in g % F is h in g fro m % boat W a te r s k iin g O th e r ( e g s c u b a , h u n ti n g fr o m b o a t. TO TA L SHOULD EQUAL % ) _ % 100% 155 12 T r a n s p o r t in g & L a u n c h in g . In 1994. h o w m a n y lim e s w a s th is b o a t tra n s p o rte d fro m y o u r h o m e o r o th e r lo c a tio n to o n e o r m o re la u n c h in g s ite s o r m a n n a s in M ic h ig a n ? (E n te r 0 if n o n e ) T r a n s p o r t in g to la u n c h at s ite s w ith a c cess to th e G r e a t L a k e s in M ic h ig a n _ _ 13. 14. T r a n s p o r t in g to la u n c h at site s o n In la n d L a k e s o r r iv e r s in M ic h ig a n In 1 9 9 4 , d id y o u e v e r k e e p th is b o a t o v e rn ig h t at a M ic h ig a n m a r in a , y ac h t c h ib o r d o c k a m im u m fo r a s h o rt p e r io d (1*30 n ig h ts ) , fo r e x a m p le w h ile o n a n o v e rn ig h t tr ip ? D o n ot in c lu d e th e fa c ility w h e r e y o u n o r m a lly k ee p y o u r b a it □ YUS ^ a NO N u m b e r o f n ig h ts in a te m p o ra ry m a r in a s p a c e in 1 9 9 4 ? _____________ O A n n u a l E x p e n s e s fo r th is b o a t. E s tim a te th e a m o u n t o f m o n e y s p e n t in 1994 to o p e r a te a n d m a in ta in th is b o a t R e p o rt e x p e n s e s o n ly fo r th e b o at th a t y o u h av e d e s c rib e d ab o v e . D O N O T in c lu d e s p e n d in g fo r c o n s u m a b le ite m s u s e d o n b o a tin g trip s o r tr a n s p o r ta tio n to a n d fro m b o a tin g a r e a s (fo r e x a m p le , a u to fu e l, fo o d , b a it a n d lu r e s ) B o a t e q u ip m e n t (e g., motors, trailer, anchors, sails, fishing wateraki, safety A electronic equipment, ) S S e a s o n a l s lip re n ta l o r d r y s t a c k s to r a g e S R e p a ir & M a in t e n a n c e (e g , to hull, motor, trailer, mast, sails, galley, d e c k shaft. prop, docks......) $ P u t in a n d h a u l ou t f e e s S B oat In su ran ce $ O ff-s e a s o n sto r a g e % _______ 15. H o w m u c h m o n e y w a s s p e n t o n fu e l fo r t h is b o a t in 1994? 16. A rc th e r e fix e d o r p o rta b le to ile t fa c ilitie s o n th is b a i l ? a. H E A D /IN S T A L L E D T O IL E T ( f ix e d o n th e b o a t) H o w o f ic n is th e h e a d u s e d o n th e b a i t ? M o st T rip s □ c. $_ DYES □ NO ^ S k ip to Q u e s tio n 17 W h a t k in d ? ( c h e c k e a c h ty p e th a t you h a v e a n d c o m p le te q u e s tio n s b e lo w th a t c o lu m n ) □ b. ________ Som e T rip s □ R a re ly D N ot U se d n □ b P O R T A B L E T O IL E T (re m o v a b le fro m b o a t) H o w o fic n is a p o rta b le to ile t u s e d o n th e b o a t? M o st T rip s □ H o w m a n y tim e s d id th is b o a t u se a p u m p o u t f a c ility in M ic h ig a n in 1994? R arc h □ □ N ot U sed □ c W h e re d o you u s u a lly em p ty u m i p o r ta b le toilet*' □ □ □ □ □ tim e s u s e d a p u m p o u t Som e Tups A t a d u m p s ta tio n In a p u b lic r c s tio o m A t a h o m e o i c o tta g e In th e w ate r O th er d H ow o fte n h a v e you e n c o u n te re d p ro b le m s in f in d in g o r u s in g p u m p o u t fa c ilitie s or d u m p s ta tio n s o n y o u r b o a tin g tr ip s in M ic h ig a n ' (C h ec k o n e ) □ M O S T O F T H E T IM E O S O M E T IM E S □ HARDLY EVER □ NEVER 156 IN FO RM A TIO N ABOUT YOU AND YOUR FAM ILY This information is requested lo p r o v i d e a profile of registered boat owners and lo identify boating patterns for different subgroups of boaters 17 Please give the county, stale or province, and 7.ipcodc of your permanent residence C o u n ty S ta te o r P ro v in c e Z jp c o d c 18. A g e o f th e b o a t o w n e r _ _ _ _ _ _ _ y e a rs 19 H o w m a n y p e o p le , in c lu d in g y o u rs e lf, r e s id e in y o u r h o u s e h o ld ? ___________ A d u lts C h ild r e n u n d e r 18 y e a rs o f ag e 20. W h a t w a s y o u r a n n u a l h o u s e h o ld in c o m e in 1994 ? (c h e c k o n e ca teg o ry b e lo w ) □ U n d e r $ 2 0 ,0 0 0 □ S 6 0 .0 0 0 -S 9 9 .9 9 9 □ $ 2 0 ,0 0 0 - $ 3 9 ,9 9 9 O $ 4 0 ,0 0 0 - 5 5 9 ,9 9 9 21 . D o you c u r r e n tly o w n a s e a s o n a l h o m e , c o n d o m in iu m o r c o tta g e in M ic h ig a n ? D YES ^ □ NO In w h a t M ic h ig a n c o u n ty is it l o c a t e d ? ______________ c o u n ty 22. D o y o u in t e n d to re g is te r a n y w a te rc r a f t in 1995 th a t y o u d id n o t o w n o r r e g is te r in M ic h ig a n d u r i n g th e 1994 b o a tin g s e a s o n ? □ NO □ N OT SURE □ YES *=> W h a t size b o a t(s )? feel 23. W e a r c p la n n in g to ask a s a m p le o f b o a t o w n e rs to re p o r t th e ir o p in io n s a b o u t w a te r q u a l ity is s u e s a n d b o a tin g fa c ilitie s in M ic h ig a n W o u ld you b e w illin g to c o m p le te a n o t h e r sh o rt m a ile d surv ey a b o u t th e s e to p ic s ’' □ YES D NO 24. T H A N K Y O U V E R Y M U C H F O R Y O U R H E L P W IT H T H I S S U R V E Y T O R E T U R N Y O U R C O M P L E T E D S U R V E Y . F O L D A N D T A P E O R S T A P L E IT S O T H E R E T U R N A D D R E S S S H O W S M A I L I T F R O M A N Y U .S . P O S T A L B O X . NO PO STA G E NECESSARY IF M A ILED IN TH E U N IT E D S T A T E S B U S IN E S S REPLY M AIL FIR ST C L A SS MAIL PERM IT NO 941 E A ST LANSING. Ml P O S T A G E WILL BE PAID BY A D D R E SSE E DEPARTMENT OF PARK, RECREATION AN D TOURISM R E S O U R C E S MICHIGAN STATE UNIVERSITY 131 NATURAL R E S O U R C E S BUILDING EAST LANSING Ml 4 8 8 2 4 -9 9 0 2 M u l l . . ! . I . M . . I I . I . I I 1.1.1..II A PPE N D IX C IN D IC E S O F B O A T I N G O P P O R T U N IT IE S 157 A p p e n d ix C. Indices o f B oating O pportunities. B O A T IN G C O U N T Y G M “ LM h O P P O R T U N IT IE S IN D IC E S SH C R S '1 <16' A lcona A lgci A llegan I6'-20’ G L C >21' CP' -,-R.e >16' 101 NA 5.6 0 5 1.304 654 292 946 27 0 84 32 5 JO NA 1.858 1.1 18 265 157 422 120 0 29 67 1.1.12 2.12 NA 2.7 .10 5.885 2.365 1 .2 6 7 3.632 24 1 31 22 9 37 8 c NA 1.810 2.875 964 427 1. 391 61 0 89 A ntrim 17 7 NA 4.695 2 .6 2 6 1 .2 4 9 677 1.926 27 0 97 36 5 A renac 727 NA 2.41.1 1.009 1.849 404 2.253 47 0 32 27 8 Baraga 16 3 NA 1 .1 4 2 61 1 1 97 92 289 70 0 48 46 1 Barry NA 0.47 2.291 4 .7 9 2 2.003 940 2.943 NA NA 9 0 2.1 4 8 NA .127 4.834 2.836 2.135 4.971 36 0 30 19 (I 47 5 A lp en a Bay B enzie 588 NA 3.145 2.069 847 304 1.151 25 2 81 Berrien 2 .7 8 0 NA 4.448 7.573 3.133 2,013 5.146 14 1. 33 B randt NA 0 38 2.583 3,473 1.628 703 2.33 1 NA NA 66 69 4 2 C alhoun NA 0 15 6.738 2.414 922 3.3 3 6 NA NA Cass NA 0 58 3.149 4.6 3 2 2,091 1.046 3.1 3 7 NA NA 7 7 1.450 NA 3.87.1 2.1 13 1.037 842 1.879 102 7 25 74 8 C heboygan 729 NA 4,831 2.742 1.057 812 1.869 35 3.75 73 9 C h ip p ew a 441 NA 4.7 8 7 2.837 1 .1 0 8 433 1.541 456 3 73 207 9 C lare NA 0 17 8.285 2.5 4 2 910 450 1.360 NA NA 7 2 C linton NA 0.00 46 3.5 1 6 1. 4 8 5 596 2.081 NA NA 0 3 Craw ford NA 0 .04 3.912 1.047 1. 2 3 3 216 1.449 NA NA 57 8 D elta 224 NA 2.412 3.131 992 2 81 1 .2 7 3 1 99 1 19 104 3 D ick in so n NA 149 76 1.689 2.2 6 7 733 200 baton NA 0.00 147 4.8 1 8 2.0 8 0 C harlevoix 10 856 933 NA NA 63 2 ,9 3 6 NA NA 0 4 32 6 H inm et 567 NA 4.382 2,505 1.141 789 1 .9 3 0 75 3 12 G enesee NA 0 .09 789 16.510 8.379 4.936 13.315 NA NA 12 t i l a d w in NA 0 14 5.4 9 2 2.188 1.340 685 2.025 NA NA 7 8 41 NA 2.530 1 .7 6 3 486 152 638 30 0 26 84 9 G ran d Traverse 284 NA 3.296 6.238 3.007 2 .0 0 8 5,015 56 2 05 58.9 G ratiot NA 0.01 1 06 2 .0 6 9 829 279 1 .1 0 8 NA NA 0 3 I li l l s d a l c NA 0 .09 1 .8 1 4 2 ,5 1 8 1,289 520 1.8 0 9 NA NA 2 7 1lo u g h to n 157 NA 2.417 1,900 702 361 1,063 51 115 44.3 NA 5.100 1.361 977 687 1.664 93 2.03 46 8 346 9.472 4 .1 3 2 2,051 6.1 8 3 NA NA 0 4 390 3.044 1 .1 3 5 405 1.540 NA NA 1 7 2,960 1.3 9 1 583 1.974 36 1 96 27 3 G o g ebic I luron 1.035 0 00 0.02 Ingham NA Ionia NA Iosco 1.015 NA 6.643 Iron NA 1 . 8 5 9 71 2.584 1,871 380 115 495 NA NA 47 4 Isabella NA 0 01 933 2,424 1 .0 1 4 421 1 ,4 3 5 NA NA 0 3 Jackson NA 0.53 1 ,8 4 4 8.325 3,765 2 ,2 6 2 6.0 2 7 NA NA 88 K alam azoo NA 0.4 0 614 10.493 4.578 2.531 7,1 0 9 NA NA 7 0 K alk a sk a NA 0 12 3.466 1 .5 1 3 477 32 1 798 NA NA 14 5 Kent NA 0 .36 1.361 2 3 .473 10.609 5.793 16.402 NA NA NA 1 .2 8 4 203 80 32 112 424 1 19 13 5 6 45 8 K eweenaw 86 3 6 (> la k e NA 0 .07 7 .4 6 1 1 .0 2 5 798 103 901 NA NA Lapeer NA 0 09 743 3 ,3 8 6 1,656 900 2,556 NA NA 12 Leelanau 790 NA 4,172 2,508 1,192 702 1 ,8 9 4 151 6 43 60 9 Lenawee NA 0.12 2,177 4,548 2 ,2 8 9 1,106 3,395 NA NA 4 4 L ivingston NA 0.7 0 1 , 64 3 6,693 4 ,1 9 9 2,940 7,139 NA NA Luce NA NA 1,112 986 1 84 77 261 31 - 9.7 77 1 457 NA 4 ,0 3 9 1 ,8 0 2 597 352 949 298 7 15 M acom b 11,580 NA 527 18,525 12,104 13,514 25,618 27 12 4 6 2 7 M anistee 922 NA 3.196 2.152 806 348 1,154 25 3.17 38 5 M ackinac 1 32 1 M arquette 166 NA 4.079 4 .8 2 6 1 ,5 8 5 506 2.091 79 0 31 54 4 M ason 560 NA 3,045 2.508 845 427 1,272 28 3 09 68 7 158 A p p e n d ix C (cont'd). B O A T IN G O P P O R T U N IT IE S IN D IC E S COUNTY GMa LMh SEE <16' RS*' 16'-20' >21' 1.102 G IT CP' T IC >16’ M ecosta NA 0 35 3.273 2 .6 0 1 537 1.639 NA NA 9 9 M enom inee 21ft NA 1 .7 2 7 1.701 540 208 748 41 0 79 20 1 Midland NA 0.02 417 4.867 2.412 1.142 3.554 NA NA (1 5 M issaukee NA 0.08 2 . 4 13 1 .1 0 3 648 165 813 NA NA 5 8 5 .9 6 1 NA 292 4.354 2,988 2.214 5.202 57 0.97 5 8 22 6 11 2 M on ioc M ontcalm NA 0.27 2.871 4.103 1 .3 7 4 545 1.919 NA NA M ontm orency NA 0.37 4.8 7 3 1 .4 3 0 283 24 1 524 NA NA 2.212 2.499 NA 1.1 7 0 7.871 3.392 5.604 27 2 69 21 7 N ewaygo NA 0.4(1 5.057 3 .6 3 9 1 .5 2 8 643 2.171 NA NA 48 0 ( la k la n d NA 2 52 2.556 32.873 2 3.082 16.647 3 9 .7 2 9 NA NA 13 8 Oceana 177 NA 3.504 1.659 555 279 834 27 1 05 28 1 Ogemaw NA 0 .17 5.678 1,838 856 325 1.181 NA NA 39 1 42 NA 1.222 872 2.36 65 301 56 (I 0 9 58 8 O sceola NA 0.04 3.328 1.565 547 124 671 NA NA 5 0 ( Lscoda NA 0.04 4.520 737 94 8 31 NA NA 50 4 O tsego NA 0.2(1 3. 7 1 1 1 ,77 1 562 32.3 885 NA NA 31 8 Ottawa 4.3 3 4 NA 1 .7 2 8 10.728 4.9 9 6 3.688 8.684 25 4 53 11 8 I’r c s q u e Isle 252 NA 3.044 1.716 535 337 872 69 2 33 39 6 R oscom m on NA 1(16 10.580 2.945 1 .6 2 7 1.217 2.8 4 4 NA NA 48 3 67 NA 202 8.907 4.510 2.425 6.935 - 5.915 NA 1.921 5.952 3.450 3.472 6.922 164 0.02 8 52 11 8 S ai n t J o s e p h NA 0 46 1.481 4 .9 7 7 2,054 740 2.794 NA NA 7 0 Sanilac 268 NA 3 .4 7 9 1 ,1 0 4 607 342 949 41 2 19 15 9 86 2 Muskegon Ontonagon Saginaw S ai n t C la ir 868 112 Schoolcraft 39 NA 1 ,7 8 2 1,368 322 434 46 0.37 Shiawassee NA 0.01 I 17 3.495 1,461 577 2 .0 3 8 NA NA T uscola 263 NA 743 2,362 1.269 712 1.981 V a n U ure n W ashtenaw W a y lie W exford 1.054 NA NA 0 .39 0.02 0 1 13 4 4,661 1 ,8 1 3 965 2,7 7 8 13 3.35 85 935 7,573 4 ,2 9 8 2,357 6,6 5 5 NA NA 9 3 3,51 1 7.613 NA 1 .0 2 3 31,478 21,172 15.709 36.881 75 4.04 7 3 NA 0.09 2,166 2,347 1.339 376 1 .7 1 5 NA NA 13 3 a CIM indica tor : n u m b e r o f m a r i n a s p a c e s in t h e c o u n t y b I .M index : s t o r a g e o p p o r t u n i t y i n d e x for b o a t s k e p t at m a r i n a s in in la n d c o u n t i e s c SI I i n d ic a t o r n u m b e r o f s e c o n d h o m e s in t h e c o u n t y , d R S i n d ic a t o r n u m b e r o f r e g is te r e d b o a t s in t h e c o u n t y e Cil. i n d ic a t o r m i l e s o f G r e a t L a k e s s h o r e l i n e s in t h e c o u n t y f C IJ i n d e x c r u i s i n g o p p o r t u n i t y in d e x g 20 (I 3 I R i n d e x b o a t i n g o p p o r t u n i t y i n d e x for b o a t s k ep t at n o n w a t e r f r o n t h o m e s . A P P E N D IX D N U M B E R O F B O A T D A Y S G E N E R A T E D B Y B O A T S IN D I F F E R E N T S T O R A G I S E G M E N T S IN D I F F E R E N T C O U N T IE S 159 A p p e n d i x D. N u m b e r o f B o a t D a y s G e n e r a t e d b y B o a t s in D i f f e r e n t S t o r a g e S e g m e n t s in D i f f e r e n t C o u n t i e s . B O A T S T O R A G L SI ( A 1 I N I TO I'A I N o n w a tc r f r o n t COUNTY o r STORAGL Second H om e M a r in a W a te r f r o n t H o m e 1 I o n ic .S o u th e a s t M acom b 3 0 0 .( 1 7 7 15.8 1 5 21 7. 6 X 7 M o n ro e 134 .4 (0 8.703 4 2 .7 7 9 17 5 . 8 9 7 3 8.547 709 .4 7 5 2 4 4 .5 5 7 S t C la ir 133.277 5 7 .047 59.725 52.048 3 2 2 .0 9 7 W as ne 107.278 30.099 3 0 4.482 270.190 X 0 8 .0 5( i 1 1 1 xoo 4.298 13.414 5 9.388 188.909 3 3.874 07.031 4.0 4 7 18.028 98.426 142.980 125.440 C e n tra l h a st H as 1 III roil 3.488 2.055 20.871 S a n il a c 13.950 4 5 .7 2 0 2.703 12.642 T u s c o la 13.090 9.705 5.725 20.803 75.021 55.984 128.720 S a g in a w N o rth e a s t A lc o n a 3.0 0 0 9 7.325 17.044 1 1.345 A lp e n a 0.904 31.429 3 0.907 22.077 91.317 A ren ac 21.035 21.095 4 1 .8 9 9 27.830 15.208 100.578 83.885 3 4.653 23.348 103.581 30.200 11 5 . 3 4 9 3 7 .0 2 9 2 5 .0 2 0 20 7.003 7.499 5 2 .850 18.839 13.354 92.548 A n tr im 7.440 80.079 3 7 .2 7 7 23.826 148.023 B e n z ie 53.042 25,792 17.205 121.355 C lu ir lc s 'o ix 24.710 00.930 00,059 33.032 2 0 .5 8 0 1 8 0 .0 2 1 Pnnnel 23.833 74.741 3 6 .2 9 9 2 3 .125 157.998 2 19.239 C heboygan Io s c o P r e s q u e Is le N o rth w e s t G r a n d T ra v e rse 1 1.938 50.218 92,603 58.480 1 e c la n a u 3 3 .2 0 7 7 1.159 3 6.093 22 .9 8 9 163.448 M a n is te e 3 8 .7 5 0 54.512 26 .2 9 0 1 7. 7 1 1 137.208 M ason ■>3 5 3 9 5 1.930 2 9 .7 9 6 20 .328 125.001 22.000 198.059 C e n tra l W est 29 .1 3 9 94.241 <) c e a n a 3 ,7 2 0 07.881 4,440 17.388 93.430 O tta w a 91 .2 4 0 3 3 ,475 4 5 .2 8 8 135.905 305 .9 1 4 M usk eg o n 5 2.013 S o u th w e s t A lle g a n 20.358 2 2 ,603 57.713 5 2 ,555 153.289 B e r r ie n 5 0 .1 5 0 3 0 ,925 7 8 .473 09 .3 7 7 2 3 4.932 V an B u ren 18.955 2 9,147 44,908 41 .2 0 0 134.330 S o u th I n la n d B a rrs 9.354 5 1 .290 3 5 .085 38.925 135.253 B ran c h 7.495 57.827 2 7,534 28.800 121.050 C a lh o u n 3.048 224 4 4 .7 9 2 52.343 100.400 1 1 .4 4 5 70,498 36,492 3 8 ,4 9 5 150.931 5 5.313 C ass C li n to n 57 1,030 25,900 2 8 ,3 2 7 B a to n 00 3,291 3 6 ,0 6 9 3 9 .0 6 7 78.488 17.664 143.750 143.565 300.691 G enesee G r a ti o t H ill s d a le In g h a m 1 ,7 1 3 200 1.721 31 2,373 14,519 16.322 33 .4 2 0 40,61 1 2 0 ,9 7 9 2 1 ,235 7 8 .0 2 9 84 540 158.750 53.464 58.499 7,746 72.943 Io n ia 408 8.73 1 2 0 ,5 8 0 I s a b e lla 208 20.888 17.814 23 .745 19.530 Jackson 10.500 41.283 07.361 70 ,345 189.555 K a la m a z o o 8.007 13,746 81.972 87.213 190.938 K ent 7.173 30 ,4 6 9 187,246 196.582 421,471 L apeer 1.832 16.634 28,420 2 8.923 75.809 L enaw ee 2,322 48,738 38 ,2 9 0 3 8 ,735 128.085 13,909 3 6 ,783 69,646 6 3.386 183.724 427 9,3 3 6 40,454 4 1 .2 1 6 9 1.433 5,268 49.891 6 4 ,275 26,345 3 1 .5 3 9 127.420 57,223 3 7 3 ,9 1 2 3 2 5.217 8 0 6.243 L i v in g s to n M id la n d M o n tc a lm O a k la n d 160 Appendix D (cont'd). M O A T S T O R A C jT S I . G M I M TOTAI Nonwaterfront CO UNTY O f STORAGE St J o s e p h Second Hom e M anna 9.120 W at er f r on t H o m e 1l o m c 3 3 .1 5 6 2.619 35.768 3 9 .645 25.541 2 8.066 5 6 .338 7.038 20.932 70.412 6 7. 4 8 . 3 166.465 2.410 9 1 .7 1 6 3 0 .9 0 6 2 5.244 150.277 561 4 3 .3 0 7 2 1 .7 1 9 13.515 79.101 (iladw in 1.958 60.797 3 6 .3 2 0 2 4 .7 2 5 123.801 Kalkaska 1.689 38.369 18.495 14.985 73.538 923 82.595 11 . 4 1 6 1 10.597 26.698 HP Shiaw assee W ashtenaw 112 1 17 . 6 9 5 N orth Inland C la re Crawford 1ake M ecosta 4.893 36.233 15 . 6 6 4 34.399 M issaukee 1.146 2 6 .712 15.512 M ontm orency 5.094 53.94 5 5 5 . 106 14.933 11.735 13.356 8 7 .327 New aygo 5.465 55.982 46.474 3 6 .924 144.845 ( )p em a« 2.373 6 2,857 24.317 108.193 <)sceola 497 3 6.842 1 6.754 18.946 14.959 ( )scoda 587 5 0 ,037 13.970 9.906 74.501 O tsego 2.824 41,081 2 0 ,9 4 7 17.368 82,221 14.666 117,123 5 1 .252 3 3 .6 9 5 216 .7 3 5 1 .2 9 5 2 3.978 3 2.958 24.919 8 3.150 1 08.632 R oscom m on W exford 69.051 S o u th U p p e r P e n insu la Delia D ick in son Iron 5.664 0 0 59.922 2 5.855 1 7 ,1 91 4 1.960 18.748 12.502 73.21 1 6 4.195 13.828 8.9X7 87.010 140.102 1 1 .5 5 5 1 00.342 17.263 10.942 M enom inee 5.461 4 2.904 14.709 9.613 72.688 Schoolcraft 986 44.271 10.648 6.920 62.825 1 ,8 4 4 10.019 12,917 7,939 12.235 4.351 3 1 .347 Baraga 7 .0 6 1 2.6 1 7 2 7 .636 C hippew a 2 7 .1 0 7 33.279 3 4 ,0 7 8 12.967 107.431 liogcb ic 2 .5 2 0 17,588 19.228 6.748 4 6 .085 1lo u g h t o n 9,650 16.803 2 2 .9 4 0 8.811 58,205 Keweenaw' 5.286 8.926 2 .4 4 9 935 17.596 7 ,7 3 1 10.137 3.381 2 1.249 113.224 M ackinac N o rth U p p e r P e n insu la A lg e r l. u c e 0 Marquette 10,204 28,357 54,779 19,885 Ontonagon 2 ,5 8 2 8,495 9.4 2 7 3.278 23.782 1 .8 4 5 ,6 2 9 3,3 6 0 ,8 1 2 3 .6 2 5 ,3 7 5 3,457,550 1 2 ,289,366 S ta te T o ta l A P P E N D IX E N U M B E R O P B O A T D A Y S IN S T O R A G E R E G IO N S A N D D E S T IN A T IO N R H G IO N S BY B O A T S IN D IF F E R E N T S T O R A G E S E G M E N T S Appendix E. N um ber o f Boating Days in Storage Regions and Destination Regions By Boats in Different Storage Segments. Boat Days (000's) Total STORAGE REGIONS DESTINATION South Central North North Central South Inland Inland UP UP REGIONS East East East West W est West South North South North S o u th e a st 1.791.0 12.5 2.2 2.8 3.8 2.0 0.3 0.2 0.5 1.891.1 M anna 745.4 8.9 2.2 2.8 3. 8 1.8 - - 02 0 5 765 6 Sec o n d hom e 112 9 - - - - - - - - - 112 9 W a te rfro n t H o m e 624.7 - - - - - - - - - 624 7 S o n w a te r fr o n l H o m e 308.0 3.6 00 - 0.1 0.2 7 5.8 0.3 - - 388 0 23.4 463.0 1.3 1.1 1.1 2.5 55.4 1.8 0.0 0.1 549.8 14 1 160.0 09 0 5 0.7 03 - - 00 01 1767 - - 129.5 C e n tr a l E ast M a r in a 75.8 S ec o n d hom e - 129.5 - - - - - - W a te rfro n t H o m e - 46 .8 - - - *> -> - - 5 5.4 S o n w a te r fr o n l H o m e N o r th e a st M a r in a S ec o n d hom e W a te rfro n t H o m e S o n w a te r fr o n l H o m e N o r th w e s t M a r in a 9.2 126.8 04 06 0.5 17.6 31J 776.3 3.8 4.9 1.9 47.8 82 2 15 1.5 07 - - - 6.5 81 - - 422 7 - - - - - 46 8 18 0.0 - 196 8 8.0 0.3 0.7 892.6 - 01 0.2 100 7 - 4 2 2. 7 - 166 3 - - - - - - 166 3 11 0 2 3 .2 1050 23 3.4 12 4 7 .8 80 02 0.5 202 8 29.4 17.0 3.9 1.230.9 12.1 8.5 62.8 15.4 0.7 0.8 1,381.6 18.7 9.5 3.0 215.4 4.4 2.0 - - 0 3 0 5 25 3 8 5 08 3 S ec o n d hom e - - - 508 3 - - - - - - W a te rfro n t H o m e - - - 3172 - - - - - - 3 17 2 107 7.5 10 1900 7.6 65 62 8 15 4 0 5 0.3 30 2 2 12.0 3.6 0.7 2.7 514.6 6.2 34.2 6.5 0.1 0.1 580.8 5.4 2.7 07 18 1284 15 - - 01 01 140 7 S e c o n d hom e - - - - 124.0 - - - - - 124 0 W a te rfro n t H o m e - - - ■ 78 9 - - - - - 78 9 66 0. 9 0 0 0 9 183 4 4 7 34 .2 65 - - 23 7 2 6.8 2.5 0.5 0.8 12.2 465.4 51.8 0.3 0.1 0.1 540.4 3.9 2.0 0.5 06 6.3 81 9 - - 01 0.1 95 5 S e c o n d hom e - - - • - 88 7 - - - - 88 7 W a te rfro n t H o m e - - - • - 181 2 - - - - 1812 29 0 5 0 0 (I 2 5 8 113 6 S o n w a te r fr o n l H o m e C e n tr a l W e st M a r in a S o n w a te r fr o n l H o m e Southw est M anna S o n w a te r fr o n l H o m e 51 8 0 ; ■ 175 1 Appendix E (cont'd). B o a t D a y s (0 0 0 's) T otal S T O R A G E R E G IO N S D E S T IN A T IO N So u th C e n tra l N o rth N o rth C e n tra l S outh Inland In lan d UP R E G IO N S E ast E ast E ast W e st W e st W est S o u th N o rth S o u th 114.1 I n l a n d S o u th Marina Second home Waterfront Home Xomvaterfront Home I n l a n d N o r th M anna Second home Waterfront Home Sonwaterfronl Home U P So u th Marina Second home 11aterfronl Home Sonwaterfronl Home U P N o r th M anna S ec o n d hom e H'aterfronl Home Sonwaterfronl Home TOTAL Marina S eco n d hom e Waterfront Home Sonwaterfronl Home - 12.2 - 114.1 122 43.3 30.6 - - 0.1 0.9 - - - 09 133 12.8 0 1 13.3 - 28.2 - 3.0 5.7 - 3.0 5.7 12.8 - N o rth . - - - 28.2 3.3 00 - 3,580.0 152 1 657 4 1.542 4 1.228 1 5.6 5.6 108.5 108.5 1.483.6 464 821.6 394 6 221.1 0.3 03 0.1 0.1 1,693.6 46 4 821 6 394 6 431 0 - - 0.0 - 3.408.0 152 1 657 4 1.542.4 1.056.1 - 3.3 UP - - 43 3 30.6 15.2 8.4 1.4 2.2 9.7 1.0 23.9 6.0 538.5 5.1 611.4 62 3.1 0.8 10 1.4 07 - - It) - - - - - - - - - - - - - - - - 9.0 5.3 06 1.2 83 03 239 60 22 7 353.6 101.1 61 2 37 5 353 6 101 1 1192 32.8 7.2 0.9 3.2 13.4 1.2 30.4 35.8 4.2 439.1) 4.9 25 06 0.8 11 05 - 02 66 0 76 6 - - - - - - - - - - - - - 142 0 172 .3 58.6 142 0 172 3 177 1 - - 3.4 - - - 280 4.8 0.2 2.4 12.3 07 304 35.8 40 2.085.4 588.3 790.3 1.254.2 598.0 522.6 3.898.6 1.561.0 544.5 446.6 805.1 112 9 624 7 542 7 19 6.8 90 9 422.7 166 3 1104 224.4 508 3 317.2 204.2 147 6 124.0 78.9 247 5 89 5 88.7 181 2 163.2 152.1 657 4 1.542 4 1.546 7 464 23 7 353 6 1011 662 69 2 142 0 172.3 63.0 129.5 46 8 215.3 - - 821.6 394 6 298 4 568.1 12.289.4 1.845 6 3 .3 6 0 8 3.625 4 3.457.6 LIST O F R E F E R E N C E S L IS T O F R E F E R E N C E S Afifi. 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