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THESiS

LIBRARIES
m - A- MICHIGAN STATE UNIVERSITY
“ J ’ EAST LANSING, MICH 48824-1048

{2!674/3

This is to certify that the
thesis entitled

THE ROLE OF A SOCIAL NETWORK IN THE FUNCTIONING
OF THE GRAND HAVEN CHARTER BOAT FISHERY, LAKE
MICHIGAN ‘

presented by
KATRINA B. MUELLER

has been accepted towards fulﬁllment
of the requirements for the

Master of Science degree in Fisheries and Wildlife

 

 

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PLACE IN RETURN BOX to remove this checkout from your record.
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MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

8/01 c:/ClRC/DateDue.p65-p.15

 

THE ROLE OF A SOCIAL NETWORK IN THE FUNCTIONING OF THE GRAND
HAVEN CHARTER BOAT FISHERY, LAKE MICHIGAN

By

Katrina B. Mueller

A THESIS
Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of
MASTER OF SCIENCE
Department of Fisheries and Wildlife

2004

ABSTRACT

THE ROLE OF A SOCIAL NETWORK IN THE F UNCTIONING OF THE GRAND
HAVEN CHARTER BOAT F ISHERY, LAKE MICHIGAN

By

Katrina B. Mueller

Great Lakes charter captains targeting salmon and trout Species operate under
unpredictable and competitive environmental and socioeconomic conditions. Social
interactions that generate social capital and assist in locating and catching salmonids may
prove important in decreasing these ﬁshery-related uncertainties and thereby increase the
success of the charter industry and individual charter operations. An evaluation of the
ﬁshing-related informational exchanges between charter captains and their relationship to
ﬁshing success was thus performed in the port of Grand Haven, Lake Michigan, during
2003. This evaluation detected the presence of distinct information-sharing subgroups
within the Grand Haven ﬂeet. Although docking location played an important role in
determining the frequency at which charter captains communicated with each other, a
history of mutual support and trust, regardless of docking location, were factors that
captains considered before they exchanged ﬁshing-related information with others.
Furthermore, captains usually communicated with those who had a similar or higher
success at catching salmonids. This study has implications for both ﬁsheries
professionals and stakeholders by providing a mechanism to evaluate the ﬂow of
information within networks and how it can be utilized to enhance ﬁshery resource
management and stakeholder communication. Network analysis is thus highly valuable

in understanding stakeholder groups and in the management of ﬁsheries resources.

Dedicated to the Memories of

Captain George Bolhouse
&

Sis Schrems

iii

ACKNOWLEDGEMENTS

I would like to express my gratitude towards my major professor, Dr. William
Taylor, for giving me the opportunity to study in the Michigan State University
Department of Fisheries and Wildlife. He has opened doors to many unexpected and
appreciated opportunities and his guidance and mentoring continues to enable me to grow
on many levels as both a student and person. I very much admire his passion in regards
to and ability to generate excitement about natural resources. I am also very grateful for
all of the help provided by my committee members, Dr. Kenneth Frank, John Robertson,
and Dr. Shawn Riley. It has truly been a pleasure to interact and generate ideas with each
of you and I hope we can continue to do so in the future.

This thesis is the result of a research fellowship funded by the Great Lakes
Fishery Trust. The professional development I was afforded through this opportunity
was invaluable, and working with the GLF T staff (especially Jack Bails, Mark Coscarelli,
Julie Metty-Bennett, and Holly Madill) and Scientific Advisory Team was enjoyable and
interesting. I also owe much appreciation to the Schrems West Michigan Chapter of
Trout Unlimited, from whom I received the 2004 Cornelius M. Schrems Scholarship.

I am deeply grateful for the time and experience the Old Grin crew (Denny
Grinold and John Robertson) shared with me. All of the Grand Haven charter boat
captains and mates that participated in this study deserve special thanks for their time and
cooperation. Donna Wessander'(Charlevoix DNR) was instrumental in providing the
catch report data used in this study and always offered timely help. Also, thanks to Dr.

Dan Hayes and my lab mates Jud Kratzer, Jo Latimore, Brad Thompson, Nancy Leonard,

iv

Matt Klungle, Bryan Burroughs, and Tim Riley for contributing to the overall positive
atmosphere of the lab and providing constructive feedback and fun recreational
opportunities.

Special thanks to Ann Krause for helping me navigate SAS and KliqueFinder, and
to Rebecca Christoffel and Sonia Joseph for being especially willing to share their
graduate experiences and passion for natural resources with me. Thanks to Jill Cruth,
Terie Snyder, Julie Traver, and Mary Witchell for their administrative help and patience.

Finally, I’d like to thank my family for their love, encouragement and support.

TABLE OF CONTENTS

LIST OF TABLES .................................................................................. viii
LIST OF FIGURES .................................................................................. ix
INTRODUCTION ..................................................................................... 1
Impact of Social Interactions on F ishery—related Uncertainty and Resources ....... 2

Maine Lobster Fishery .............................................................. 3

Alaska Salmon Fishery ............................................................ 5

Goal and Objectives ......................................................................... 6

Study Area and Participants ................................................................ 7
METHODS .......................................................................................... 12
Contacting and Soliciting Participants ................................................... 12
Survey Instrument .......................................................................... 12
Survey Design ..................................................................... 13

Comparing Survey-reported Catch to MDNR Catch Records. . . . . . 1 6

Identifying Survey-reported Subgroups. . . . . . . . . . . ...................................... 16
Characterizing Survey-reported Subgroups .................................... 19

On-board Observations .................................................................... 19
Observed Communication ........................................................ 19

Observed Catch ..................................................................... 20

Identifying Observed subgroups ................................................... 21

Relating Catch, Communication, and Attributes ....................................... 22
RESULTS ............................................................................................ 23
Survey Responses .......................................................................... 23

Fleet Attributes ..................................................................... 23

Captain Attributes ................................................................. 23
Survey-reported Communication ................................................ 28
Survey-reported Catch ............................................................ 28

Subgroups Identiﬁed Using Survey Data ...................................... 3O
Characterization of Survey-based Subgroups .................................. 30
Communication within and between Survey-based Subgroups ............. 35

On-board Observations ..................................................................... 37
Observed Catch and Communication .......................................... 37

Subgroups Identiﬁed Using Observational Data .............................. 37

Relationships between Catch, Communication, and Attn'butes ..................... 40
Comparison of Observed and Reported Catch and Communication Data ......... 42
Summary of Results ........................................................... . ............ 43

vi

DISCUSSION ....................................................................................... 47

Summary of Discussion Topics .......................................................... 47
Subgroups Verses Whole Fleet Sharing of Fishing-related Information. . . . . . . . ....47
Beneﬁts of Sharing F ishing-related Information with Competing Operators... . .48

Selective Exchange of Fishing-related Information ................................... 50
The Curiousness of Sharing Not-so-helpful F ishing-related Information .......... 54
The Persistence and Strength of Stakeholder Communication Networks .......... 56
Use of Social Network Analysis for Fisheries Management ......................... 57
APPENDIX A. Replicated Letter of Intent to Potential Study Participants ................ 60
APPENDIX B. UCRIHS-approved Study Participation Consent Form. . . . . . . . . . . .62
APPENDIX C. Post-study Summary for Participating Captains ............................. 64
APPENDIX D. Replication of the 2003 Survey Instrument ................................... 67
APPENDIX E. Replication of the On-board Observation Log ............................... 73
REFERENCES ...................................................................................... 76

vii

LIST OF TABLES

Table 1. The survey variables as they are imbedded within the survey instrument used to
assess ﬂeet and captain attributes, communication, and catch ................................. 13

Table 2. Sources utilized by participating Grand Haven charter captains to obtain ﬁshing-
related information .................................................................................. 27

Table 3. The reported average monthly catch (# of salmonids) per trip in 2003 of each
participating Grand Haven charter captain exceeding the ﬂeet average monthly catch per
trip as described in the Michigan Department of Natural Resource’s catch report

database ............................................................................................... 29

Table 4. A summary of survey responses by participating Grand Haven charter captains
who were members and non-members of information-sharing subgroups in 2003.... .....32

viii

LIST OF FIGURES

Figure 1. Southwest Michigan’s Grand River and its connection to southeastern Lake
Michigan. Shown in detail are the relative locations of the six marinas used by
participating Grand Haven charter operations for docking. These marinas include Barrett
Boat Works (BBW), Holiday Inn (HI), Rycengas (RS), Grand Isle (GI), Chinook Pier
(CP), and North Shore (NS) .......................................................................... 9

Figure 2. Total annual salmonid catch of the ﬁve species (coho salmon, chinook salmon,
steelhead trout, brown trout, and lake trout) targeted by all Grand Haven charter ﬁshing-
operations from 1993-2003 ......................................................................... 10

Figure 3. Sociogram adapted from Frank 1998. This sociogram represents the process by
which teachers inﬂuenced one another through discussions. Those teachers that
communicated on a near daily basis are indicated by having thick, solid lines within the
boundary of a subgroup. Thinner lines between members of subgroups indicate that
discussions occurred less frequently .............................................................. 18

Figure 4. Percentage of participating Grand Haven charter captains docking at each
Grand Haven marina or private location in 2003: North Shore Marina, Chinook Pier,
Grand Isle Marina, Rycengas Marina, Holiday Inn Marina, Barrett Boat Works, private
trailers, and unknown ............................................................................... 24

Figure 5. The average daily catch per month (# salmonids) by captains operating out of
the port of Grand Haven in 2003. This graph compares the ﬂeet average monthly catch
per trip as calculated using the Michigan Department of Natural Resources catch report
database and the average monthly catch per trip as reported by participating Grand Haven
captains ............................................................................................... 29

Figure 6. A sociogram depicting the non-overlapping information-sharing subgroups of
the 2003 Grand Haven charter ﬁshing ﬂeet as derived from survey responses regarding
the frequency at which participating Grand Haven captains communicated with identiﬁed
captains ................................................................................................ 31

Figure 7. A sociogram depicting the docking locations of Grand Haven captains

identiﬁed through survey responses regarding the frequency at which participating Grand
Haven captains communicated with identiﬁed captains as being members of subgroup B.
Each of the six marinas represented by captains in subgroup B is boxed ................... 33

Figure 8. A sociogram depicting (through circles) the identiﬁcation numbers of

participating Grand Haven captains that reported having an average monthly catch per
trip in 2003 determined to be above the ﬂeet average monthly catch per trip ............... 36

ix

Figure 9. A sociogram depicting the non-overlapping information-sharing subgroups of
the Grand Haven charter ﬁshing ﬂeet as derived from on-board observations of ﬁshing-
related informational exchanges .................................................................. 38

Figure 10. A sociogram depicting (by adjacent black squares) the identiﬁcation numbers
of participating Grand Haven captains that were observed in 2003 to catch above the ﬂeet
average during an observation day as determined through use of the Michigan

Department of Natural Resources catch report database ....................................... 41

Figure 11. The observed number of salmonids caught per trip by Grand Haven
participating charter captains in 2003 contrasted against that’s day’s ﬂeet average as
determined through use of the Michigan Department of Natural Resources catch report
database ............................................................................................... 42

Figure 12. The sociograms derived from observed and reported communication data
depicting captains with both above-average observed and reported catches of salmonids
during 2003 .......................................................................................... 44

Figure 13. Graph depicting the tendency for participating Grand Haven captains having
observed and reported catches above the ﬂeet average in 2003 to target relatively more
individuals to give and receive ﬁshing-related information .................................... 45

Figure 14. Graph depicting the tendency for participating Grand Haven captains having
catches above the ﬂeet average in 2003 to be the target of ﬁshing-related informational
exchanges .............................................................................................. 45

Figure 15. A graph depicting the tendency of participating Grand Haven charter captains
having catches above the ﬂeet average in 2003 to also have high numbers of other
participating captains reciprocate in listing them as someone they exchange ﬁshing-
related information with ............................................................................. 46

INTRODUCTION

Communication and other such interactions between individuals form the basis of
social networks (Wasserman and Faust 1994). Networks are deﬁned as bounded
collections of actors (e.g., the individuals in an organized ﬁshery stakeholder group) and
the ties, or type of interactions, between them. Viewed through a network perspective,
ﬁshery stakeholders and their actions are interdependent, and as such, the ties between
these individuals have important implications (Wasserman and Faust 1994) for ﬁsheries.
For example, ties have the potential to provide opportunities for or constrain individual
behavior. Ties also facilitate the exchange of material or non-material resources, or
goods, such as shared ﬁshing gear and information which can be used to better one’s
circumstance.

An individual’s ability to access resources through social relationships has been
termed social capital (e.g., Frank et al., under review; Rudd 2000). Social networks,
along with trust, reciprocity, and social norms (i.e. accepted modes of behavior) are
crucial to the development of this type of capital (Pretty and Ward 2000; Frank and
Yasumoto 1998). Trust between actors leads to cooperation and compliance with social
norms or legal regulations. Those individuals who do not comply with these norms or
exploit Shared resources through non-compliance with regulations are cooperatively
sanctioned by other individuals in the social network (e.g., Frank and Yasumoto 1998;
Acheson 1988). Thus, avoidance of environmental tragedies of the commons has been
attributed to the cooperation and compliance with regulations and norms that is mediated

by social capital (Bennett and Clerveaux 2003) and stakeholder social networks.

The analysis of social networks has great utility in assessing and understanding
the formation of ﬁshery stakeholder groups, the ﬂow of resources and communication
within these groups, and the implications of stakeholder interactions on each other and
ﬁshery resources (e.g., Bennett and Clerveaux 2003). For example, social network
analysis has been used to explain how innovations come to be diffused and adopted
within networks (e. g., Frank et al. 2004; Rogers 1995), the formation of networks among
ﬁshery stakeholder organizations (e. g., Lynch 2001), the compartmentalization of taxa in
aquatic food webs (e.g., Krause et al. 2003), and how human social networks mediate
between global economic exchange, aquatic ecosystems, and ﬁshery dynamics (e.g.,
Frank et al., under review). Nevertheless, application of social network analysis to
ﬁshery stakeholder types has been infrequent (e. g., Lynch 2001; Maiolo and Johnson

1992; McDonough et al. 1987).

Impact of Social Interactions on Fishery-Related Uncertainty and Resources
It is widely recognized that commercial ﬁshing directly impacts ﬁshery resources,

for example the historical and systematic overexploitation of native Great Lakes ﬁshes
(Eshenroder and Bumham-Curtis 1999; Brown et al. 1999) and Atlantic cod stocks
(Finlayson and McCay 1998; Kurlansky 1997). It has also been demonstrated that
commercial operators are faced with complex social environments. For instance,
commercial operators targeting the American lobster (Homarus americanus) in Maine
and salmon Species in Alaska are highly competitive and integrated into the local
community and market supply chain (Acheson 1988; Gatewood 1984). The following

case studies illustrate that, although their target Species and geographical location vastly

differ, captains operating in these two ﬁsheries exhibit similar social behavior that has

proven critical to their success and consequent impact on ﬁshery resources.

Maine Lobster F iSher

Maine commercial lobster operators target a Species that exhibits limited mobility
and generally congregates where rocky structure and kelp is readily available along the
coast. The principal ﬁshing gear used to catch lobsters is a baited trap, or pot, which is
weighted, attached to a line and buoy, and lowered into lobster habitat where it can rest
among rocks and other suitable lobster substrate (Sainsbury 1996). Although the
American lobster can be found in depths ranging from 6 - 1,200 feet, they tend to
concentrate in depths less than 180 feet. These lobsters seek deeper water during the
winter and are often found within feet of the breaking surf during the spring and early
summer. During their summer molt, Maine lobsters hide amongst rocks and are difﬁcult
to catch (Acheson 1988).

Success and proﬁtability of the lobster ﬁshery is inﬂuenced by lobster biology
(e. g., movement, molting, and reproduction), weather conditions, other ﬁsheries, markets,
and other lobster ﬁshing operations. Lobster ﬁshers reduce uncertainty related to these
factors through a variety of networks and community institutions—ties with other lobster
operators, negotiation with dealers, and the sharing of resources (Acheson 1988). The
social relations of Maine lobster ﬁshers are primarily expressed through territorial-based
“gangs,” deﬁned by local harbors (Acheson 1988). The roles of these gangs encompass
not only protection of local ﬁshing grounds from perceived intruders, but also

professional and personal support among gang members. Gang members draw on social

relationships to aggressively protect territory in which they set traps by sabotaging the
traps of perceived intruders. Sabotage consists of gang members either notching the
intruder's trap(s) as a warning or cutting the buoy line to the trap. The social structure of
the gangs is critical to sabotage as reinforcement of this behavior is considered mutually
beneﬁcial and all members of the gang are complicit in their silence of not revealing who
sabotaged the intruder's traps. To defy the gang is to risk being ostracized, a serious
social sanction as the success of a lobster operation is largely dependent upon access to
proven ﬁshing grounds and local and long-standing ﬁshery-related knowledge held by
gang members. Furthermore, because gangs rely on the social capital that results from
long-held community involvement, friendships, and kin-based relationships, being
ostracized affects one’s social standing in the community as well as their standard of
living. Gangs ultimately draw on this social capital to limit entry into the local lobster
ﬁshery which gives long-standing members of the ﬁshery a competitive advantage. This
advantage is further enhanced by sanctioning gang members who exceed or defy set
management limits or regulations (similar, albeit less organized sanctions occur on
ﬁshermen operating within the Turks and Caicos Island spiny lobster [Panulirus argus]
ﬁshery that exhibit illegal ﬁshing behavior such as poaching or using destructive ﬁshing
techniques—Bennett and Clerveaux 2003). Violators within the Maine lobster ﬁshery
are ostracized and thus made to face uncertainties related to ﬁshing and markets on their
own. AS such, commercial lobster operations in Maine have yet to experience the

massive declines in their target species indicative of overexploitation.

Alaska Salmon Fishery

The target species of commercial seining operations in Southeast Alaska are pink
salmon (Oncorhynchus gorbuscha), chum salmon (0. keta), and sockeye salmon (0.
nerka). These salmonids migrate long distances in the Paciﬁc Ocean, traveling in
relatively large schools until reaching the coastal waters of Southeast Alaska. Upon
reaching the coast, they segment into smaller groupings which each home to their natal
streams to spawn (Gatewood 1984). It is during this later phase of their life history that
commercial seiners target these population segments, netting adults as they move along
the coast in search of the mouths of their natal rivers. Given this migration pattern, it is
critically important for seiners to successfully predict the daily location of migrating
salmon during the relatively short spawning period and even Shorter legal ﬁshing season
(as few as 18 days) (Gatewood 1984).

The Southeast Alaskan salmon ﬁshery is strictly regulated (limited entry,
licensing and gear regulations, short time allotment for legal ﬁshing) and intensely
competitive (Gatewood 1984). Most of the ﬁshing vessels (350 - 400) in the Southeast
Alaskan salmon seining ﬂeet are company-owned, and these companies heighten
competition between captains by offering ﬁnancial incentives based on salmon-catching
success (Gatewood 1984). Competition is still ﬁirther enhanced by the fact that
compensation by ﬁsh processing companies is based on individual vessel catches rather
than those by the ﬂeet.

Despite these incentives that inhibit COOperation between ship captains, Gatewood
(1984) found that small groups of Alaskan commercial seine skippers exhibit cooperative

behavior just prior to legal seine periods. During this time, skippers and their crews scout

for Signs of concentrated schools of salmon (i.e. the occasional surfacing behavior
exhibited by salmon) in nearshore Alaskan waters in order to better predict the location of
these ﬁsh during the short ﬁshing season. Captains rank scouted areas for potential of
catching success based on the number of observed instances of surfacing behavior.
Sometimes the captains form small cliques, or subsets of the entire ﬂeet, with other seine
captains within which information regarding the location of salmon iS Shared (Gatewood
1984). Not all captains participate in clique cooperation and no captains cooperatively
share information in more than one clique. Cliques range in size from two to ﬁve
captains and are primarily based on close kinship relations or life-long friendships
(Gatewood 1984), of which trust is a critical component. Kinship or friendship
constitutes a form of "social collateral" Since failure in regards to honesty and secrecy
would jeOpardize prior social relationships. The validity of informational—contributions
are thus based on trust and, due to the small Size of cliques, the beneﬁts of cooperation
are equally distributed and each clique member is privy to all of the information provided
by clique-members. Information regarding the scouted areas is not Shared with non-
clique members. Due to the synergistic nature of the cooperation (i.e. captains are able to
obtain more information than they could acquire while acting independently), ﬁsh-
catching success is enhanced. The role of information Sharing in ﬁsheries thus has
important implications in the success of Alaskan commercial ﬁsheries and their

management.

Goal and Objectives

Salmonid charter ﬁsheries in the Great Lakes face a number of issues and

uncertainties akin to those faced by the Alaskan salmon seiners and Maine lobster ﬁshers.
The Species that are sought by Great Lakes salmonid charter ﬁshing operators are highly
mobile and dispersed within a large water body, making their detection difﬁcult without
cooperation. Many Great Lakes ports, such as that of Grand Haven, Lake Michigan, are
utilized and frequented by large numbers of competing charter operators, private anglers,
and tournament competitors. The goal of this study was thus to thoroughly evaluate the
degree and magnitude of ﬁshery-related information sharing occurring within the charter
boat ﬁshing ﬂeet in one Lake Michigan port in order to assess the importance of social
capital and networks on ﬁshing success in the Great Lakes charter-based salmonid
ﬁshery. The objectives of this study were to 1) describe the communication network of
the port of Grand Haven salmonid charter ﬁshing ﬂeet using social network analyses, and
2) determine the relationship between the exchange of ﬁshing-related information

between charter captains and their catch of trout and salmon Species.

Study Area and Participants

The Lake Michigan charter ﬁshing industry primarily came about in response to
the introduction of coho (0. kisutch) and chinook (0. tshawtscha) salmon from the
Paciﬁc Northwest. Salmonids from this region, along with the Great Lakes-native lake
trout, Salvelinus namaycush, were stocked in Lake Michigan beginning in the mid-19603
(Tanner and Tody 2002; Holey et al. 1995). These top predators were stocked to produce
a valuable sport ﬁshery and help control the nuisance and non-native alewife (Alosa
pseudoharengus) population that littered the beaches when abundance exceeded carrying

capacity (Madenjian et al. 2002; Tanner and Tody 2002).

Salmonids from the Paciﬁc Northwest are highly migratory during their various .
life stages in both lentic and lotic environments. After migrating as smolts from natal
streams, these salmonids track optimal temperatures and food sources and then later
return as adults to the river from which they originated to spawn. The location of
salmonids is less predictable in an open-water environment where constantly moving
temperature “breaks” (e.g., where warm river water meets cooler lake water) offer the
primary form of structure for pelagic adult ﬁshes such as chinook and steelhead, or “lake-
run” rainbow, trout (0. mykiss). The Lake Michigan salmonid charter ﬁshing ﬂeet is thus
generally faced with uncertainty related to ﬁnding and catching its target species. It has
generally been Shown that cooperation between captains targeting pelagic, mobile, or
somewhat unpredictable ﬁshes is used to decrease such uncertainties and increase ﬁshing
success (e.g., Sampson 1991; Mangel and Clark 1983).

Grand Haven, Michigan is a port located where the Grand River meets
southeastern Lake Michigan (Figure 1). This port is home to one of the largest salmon
charter ﬁshing ﬂeets on the eastern side of Lake Michigan (www.micharterboats.com),
with thirty-ﬁve ﬁshing charters operating out of Six marinas in 2003. Due to the effect of
lake circulation patterns on water temperature (e.g. Wetzel 2001), the geographical
location of Grand Haven affords relatively long ﬁshing and thus long sampling seasons
(late April through October) when compared to other Lake Michigan ports (John
Roberston, personal communication).

The Lake Michigan sport ﬁsh primarily targeted by Grand Haven charter

 

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NS RS

 

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Figure I . Southwest Michigan’s Grand River and its connection to southeastern Lake
Michigan. Shown in detail are the relative locations of the six marinas used by
participating Grand Haven charter operations for docking. These marinas include Barrett
Boat Works (BBW), Holiday Inn (HI), Rycengas (RS), Grand Isle (GI), Chinook Pier
(CP), and North Shore (NS).

operations include lake trout, chinook salmon, coho salmon, steelhead trout, and brown
trout (Salmo trutta). The Michigan charter boat industry provides an important means of
public access to the Lake Michigan pelagic ﬁshery and subsequently generates signiﬁcant
economic beneﬁts to the surrounding region. For example, from 1993-2003, Michigan
Charter Boat Association (MCBA) ﬁshing charters operating out of Grand Haven
provided over 60,000 resident and 12,000 non-resident ﬁshing licenses. These charter
operators also largely facilitated the harvest of salmonids, with just fewer than 110,000
coho salmon, chinook salmon, steelhead trout, brown trout and lake trout being taken by
charter anglers between 1993 and 2003 (Figure 2) (MDNR [Michigan Department of

Natural Resources] catch report database). Chinook salmon were the most frequently

caught and lake trout harvest exhibited the most variability over time.

Grand Haven Salmonid Catch by Year (1993-2003)

 

 

: 75 1 ﬂ ''''' Coho ,
l g I Salmon
'5 3% T +Chinook ;
if Salmon }
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Year

Figure 2. Total annual salmonid catch of the ﬁve species (coho salmon, chinook salmon,
steelhead trout, brown trout, and lake trout) targeted by all Grand Haven charter ﬁshing
operations from 1993-2003.

Non-govemmental organizations (NGOS), such as the MCBA, are comprised of
stakeholders with a common interest(s). For example, the MCBA is a state-level NGO
dedicated to establishing and maintaining a professional charter industry that promotes
safe and quality charter excursions for resident and non-resident anglers
(www.micharterboats.com). Members of the MCBA and its local chapters meet annually
to discuss ﬁshery-related issues, and operators from the same port have the opportunity to
interact and/or cooperate during the late spring, summer and fall. The qualities of the
MCBA and its local chapters (such as that in Grand Haven) make this stakeholder group
an ideal candidate for the evaluation of an information-Sharing and social network as it is
related to ﬁsh-catching success. Thus, individuals targeted for participation in the study

were licensed captains that were members of the MCBA and the primary operators (as

10

some licensed captains acted as ﬁrst mates) of charter operations in the port of Grand

Haven, Michigan.

11

METHODS

Contacting and Soliciting Participants

The names and contact information of all 2003 Grand Haven charter captains who
were also members of the MCBA were obtained from the MCBA webpage
(www.micharterboats.com). After the study was approved by Michigan State
University’s Institutional Review Board, The University Committee on Research
Involving Human Subjects in the spring of 2003, these captains were mailed a one-page
letter of intent (Appendix A). This letter described the study’s goal and objectives and
explained the captain’s potential role as a participant. Each captain was then contacted
personally via telephone in May of 2003 with the intention of formally requesting his or
her participation in the study and describing the study goal, objectives, survey length
(approximately one-half hour to complete), and on-board observation methodologies. All
participating captains willingly signed the UCRIHS-approved consent form (Appendix
B) prior to their participation in the study. Following analysis of survey responses and
observational data, participants were mailed a summary of the study results (Appendix

C).

Survey Instrument

The survey was personally provided to Grand Haven captains during the 2003
ﬁshing season (May-September). Captains were asked to return the survey in person or
via mail. To describe the communication network of the Grand Haven charter ﬁshing

ﬂeet and then relate the ﬁshing-related transfer of information to ﬁsh-catching success of

12

its captains, it was necessary to develop a survey instrument that would describe 1) ﬂeet

and captain attributes, 2) relative ﬁsh-catching success of Grand Haven charter captains,

and 3) exchange of ﬁshing-related information between captains. In order to develop this

survey, a review of related literature (e.g. Hilbom and Ledbetter 1985) and discussions

with representatives of the charter industry were initiated to evaluate the social and

biological dynamics related to the Great Lakes salmonid charter ﬁshery. From these

information sources, a list of survey variables was constructed (Table 1) which was used

in the development of the survey instrument (Appendix D).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Survey Variables Survey Question #
Vessel size 4
Age of captain 8
Years of experience 9, 10
Occupational 11, 12,13
Fishing Motivation 14
Kin/industry ties 15,16
Education 17
Competitiveness 1 8,19
Level of involvement 22, 23
Knowledge seeking 20, 21, 27, 33
Innovativeness 24, 25, 26, 28, 30
Feelings towards management 40, 41, 43
% return customers 44
Communication
Modes 29, 29b
Perceived value 31, 32
Quality 35, 37, 38, 39, 42
Frequency 32, 33, 45
Fish catching success 34

 

Table 1. The survey variables as they are imbedded within the survey instrument used to
assess ﬂeet and captain attributes, communication, and catch.

Survey Design

The survey was designed to ﬁrst elucidate responses dealing with ﬂeet (i.e. vessel

length and docking location) and captain attributes and then to ascertain how these

13

 

captains communicated with other Grand Haven captains and assess their the relative
success at catching salmonids. Redundancy of certain variables throughout the survey
occurred in order to best capture the effect of complex variables (Fowler 1998).

The survey instrument asked captains to provide their age and the highest level of
education they had completed. Captains were also asked to describe any additional
occupations they currently held and income received in addition to charter ﬁshing to
determine if full time/part time status had any effect on the amount of ﬁshing-related
information Shared between captains. They were also asked to describe their motivation
(e.g., social) for charter ﬁshing and their level of competitiveness (deﬁned as
participation in tournaments).

Acheson (1988) found that lobster ﬁshers that possessed kin ties with other ﬁshers
had more access to ﬁshing-related help. Thus, Grand Haven captains were asked to
describe their kin ties within the charter ﬂeet. A point system was created to rank the
weight of inﬂuence that kin ties had on access to ﬁshing-related information. Each
captain received a kin tie value of 2.0 for each mate to whom they were related and a kin
tie value of 3.0 for each captain with whom they had familial relations. Relations with
other captains were given a higher value Since it was assumed that captains were more
invested and permanent within the industry than mates and could thus provide a higher
quality and quantity of ﬁshing-related information that could potentially inﬂuence the
catch. For example, a captain who had a spouse as a mate and a brother as a captain
would receive a kin tie value of 5.0, whereas a captain with kin ties with two other
captains would receive a value of 6.0.'

The survey also assessed captain’s interest in being actively involved in shaping

l4

the ﬁshery. Research (e.g., Gigliotti and Peyton 1993) has correlated membership in
special interest organizations with an individual’s desire to be politically inﬂuential. AS
such, captains were asked to describe their membership and involvement in NGOS.
Additionally, captains were asked whether they kept a personal ﬁshing log (in which
information in excess to that required by the MDNR was recorded). This was a measure
of each captain’s desire to actively acquire information which would improve their
success. Additionally, attendance of trade ﬁshing shows (where ﬁshing products are
displayed and sold) was attributed to information-seeking afﬁnity.

Innovation is described as an important aspect of the “Skipper effect.” The
skipper effect is a captain’s ability to inﬂuence his or her own ﬁshing success and can be
used to illustrate a one’s propensity to take risks and try new techniques (Durrenberger
and Palsson 1986). In this study, measures of innovativeness included use of Nextel
phones, utilizing the intemet, and having business-related websites.

Captains were also asked to describe their opinions regarding management, i.e.
perceived quality of communication with ﬁsheries managers and effectiveness of
different branches of governing bodies (i.e. local, state or federal).

Since I intended to evaluate the relationship between individual attributes,
communication networks, and catch, captains were also asked to provide their average
catch per trip for each month (May-August) for 2002 and 2003 and describe the mode
(e.g., cell phone or radio), frequency, perceived value, and quality of communication with
other identiﬁed Grand Haven captains. As another measure of success as a charter
ﬁshing operation, participating captains were asked to estimate the percentage of their

customers that returned from year to year (% return customers). It was thought that ﬁsh-

15

ﬁnding ability and the quality of experience provided by the charter captains and mate
would inﬂuence the amount of customers that returned and chartered the operations

multiple times.

Comparing Survey-reported Catch to MDNR Catch Records

Following administration of the survey instrument, I personally contacted MDNR
biologists and staff at the Charlevoix Fisheries Research Station in Michigan in regards to
accessing the 2003 salmonid charter ﬁshing catch report database. The data provided by
the MDNR was anonymous and included information regarding ﬂeet catch per
trip/day/month. Using this data, I calculated the ﬂeet’s average daily catch per month.
These values were then compared to the average monthly catch per day as reported by
participating captains in the survey. This comparison allowed the classiﬁcation of
captains as catching above or below the ﬂeet average (above-average was deﬁned as

being at greater than one-tenth above the ﬂeet average).

Identiﬁdng Survey-reported Subgroups

Based on how frequently surveyed captains reported exchanging ﬁshing-related
information with other members of the Grand Haven ﬂeet, Frank’s “KliqueFinder”
algorithm (Frank 1995) was used to analyze and identify information-Sharing subgroups
within the ﬂeet. KliqueFinder iteratively reassigns actors to subgroups by maximizing a
single (or set of) parameter(s) that measure the extent to which interactions (in this study,
the frequency of ﬁshing-related informational exchanges) occur within a subgroup.

Thus, the process accounts for the unique qualities of the network as deﬁned by the

16

researcher (Frank 1995).

In this study, KliqueFinder identiﬁed cohesive inforrnation-sharing subgroups
within the Grand Haven charter ﬁshing ﬂeet when ties between captains were relatively
more frequent when compared to those within the entire social network. KliqueFinder
addressed the validity of the placement of captains within subgroups by maximizing the
odds that there was a tie based on ﬁshing-related communication between two captains
(as opposed to an absence) that was associated with membership in a common subgroup
(e. g. Frank and Yasumoto 1998). Captains who did not exchange ﬁshing-related
information or who did so with only one other captain were not assigned to a subgroup.
Aﬂer assigning captains to information-sharing subgroups within the Grand Haven ﬂeet,
KliqueFinder produced a graphical representation of ﬂeet in the form of a crystallized
sociogram. “Crystallized” refers to the fact that the subgroups are deﬁned by high
concentrations of ties and then integrated among the sparse ties.

Sociograms provide a visual representation of the relative frequency or strength of
ties within and between individuals holding membership in cohesive subgroups (e.g.,
Frank and Yasumoto 1998). Frequency or strength of interactions (e. g., exchanging
ﬁshing-related information) between actors (e.g., charter captains) is portrayed by the
distance between both individuals and subgroups. For example, captains or subgroups of
captains that exchange more information would appear in closer proximity while those
who communicate less frequently would be farther apart (Figure 3). The more frequently
actors interact, the more they have the potential to inﬂuence one another (Wasserman and

Faust 1994).

17

 

Figure 3. Sociogram adapted from Frank 1998. This sociogram represents the process by
which teachers inﬂuenced one another through discussions. Those teachers that
communicated on a near daily basis are indicated by having thick, solid lines within the

boundary of a subgroup. Thinner lines between members of subgroups indicate that
discussions occurred less frequently.

18

Characterizing Survey-reported Subgroups

The ﬂeet and captain attributes, communication, and catch data from the survey
were analyzed using descriptive statistics (e.g., the mean, mode and range of captain’s
ages and experience). The results of these descriptive statistics were then used to
characterize each survey-reported information-sharing subgroup identiﬁed within the

ﬂeet by its member’s attributes.

On-board Observations

Catch and ﬁshing-related communication of Grand Haven charter captains was
observed and recorded while on-board Grand Haven charter boats. This was done in
conjunction with administration of the survey instrument during the 2003 ﬁshing season
(May-September). I maximized direct interactions with the charter ﬁshing crews (i.e.
through the on-board observations).in order to establish enough rapport to ideally
persuade all Grand Haven charter captains to participate in the study, as a census or near-
census is preferred for this type of social network analysis (e.g., Frank 1996; Aldeman
2003). For this purpose, I acquired a MCBA mate’s card, which allowed me to act as a
surplus crewmember. AS such, I was able to carry out on-board observations related to

ﬁshing-related communication and ﬁsh-catching success.

Observed Communication
The communication behavior of Grand Haven captains was observed and
recorded in a ﬁshing log (Appendix E) while on-board charter boats and during chartered

ﬁshing trips. Data collected regarding on-board ﬁshing-related informational exchanges

19

included mode of communication (radio, cell phone, Nextel phone, and walkie-talkie),
communicators (identity as later coded as a randomized number), and exchanged ﬁshing-
related information (dialogue). Fishing-related information exchanged between captains
included description of lures being used, gear set-up (e.g., Spinner on a lead core), depth
of set-ups, vessel speed, species caught, and etcetera.

Exchanges consisted of direct ﬁshing-related transfer of information regarding
lures, gear set-up, depth, location, temperature, water temperature, and boat speed. Each
transfer was uni-(one-way transfer of information), bi-(exchange between two captains)
or multidirectional (exchange between three or more captains). For example, one captain
might ask another captain or private angler a set of ﬁshing-related questions to which the
other captain would respond (unidirectional). This would be considered a single “unit” of
information provided to the information-seeker since it was bounded by a beginning and
end (the end being when the information-seeking captain had received all of the
information he requested). Each captain received one point for each unit of information
transferred to others. During any given charter trip, such exchanges occurred multiple
times between pairs of captains, resulting in multiple points for each ﬁshing-related
information provider. Cumulative points of exchange between captains were used to
determine subgroup membership based on frequency of observed ﬁshing-related

informational exchanges.
Observed Catch

Number of salmonids caught was also observed for each captain during each

chartered ﬁshing trip. The catch from each trip was then compared to the daily ﬂeet

20

average calculated using the MDNR catch report database. This daily ﬂeet average of
catch per trip was computed in a Similar manner as the survey—reported daily catch per
month averages by dividing the total number of captains ﬁshing on an observation day by
the total number of salmonids caught that day (from the MDNR catch report database).
This calculation gave the average catch per trip per day for the entire Grand Haven
charter ﬁshing ﬂeet. This ﬂeet average was then compared to the observed catch of
individual captains on each observation day to determine if the captain caught below or
above the average for that day. An observed catch value was determined for each captain
by calculating the difference between the average ﬂeet catch and that captain’s catch on a
given observation day. That captain’s best observed catch (in relation to that of the ﬂeet)
was used when statistically relating catch to other variables (below). These values thus
ranged from negative to positive values (i.e. negative values for catches below the ﬂeet
average) and were non-categorical. For example, if a captain was observed on three
occasions and caught a number of salmonids below the average number of salmonids
caught by the charter ﬁshing ﬂeet each time, his best catch in relation to the ﬂeet was

used, even if it was a negative value.

Identiﬁzing Observed Subgroups

The use of KliqueFinder to identify information-sharing subgroups and depict
them in a crystallized sociogram was repeated, this time using the observational data (i.e.
the number of ﬁshing-related information units transferred) related to observed ﬁshing-
related communication between Grand Haven captains and private ﬁshermen during

2003. This second analysis was done in order to validate the survey responses related to

21

who communicated with whom and the frequency at which communication occurred.

Relating Catch, Communication, and Attributes

A chi-squared test, in addition to a correlation test, was used in showing how
strongly pairs of survey and observed variables were related (Rao 1998; Kitchens 1998).
In order to ﬁnd the direction of the correlation between the survey-reported and observed
variables, the SAS correlation procedure was used to compute the correlation coefﬁcient
(r) and probability (p) values (Younger 1998). A conﬁdence interval of a = 0.05 was
used. The data used for this test was all non-categorical data collected either through
observations or survey responses, such as experience (number of years), catch (number of

salmonids), and the reported exchange of ﬁshing-related information (frequency).

22

RESULTS

Survey Responses

Twenty-nine of thirty-three (87.9%) primary Grand Haven charter captains
completed the survey. Survey results are divided into four categories. These include
ﬂeet and captain attributes, ﬁshing-related communication, and reported catch. From
this information, the communication network was identiﬁed, described and ﬁnally related

to success at catching salmonids.

Fleet Attributes

Although all study participants operate from the port of Grand Haven, these
captains clocked at least Six marinas within the port, and were thus not all geographically
adjacent. Figure 4 Shows the percentage of participating charter operations at each
docking location within the port of Grand Haven in 2003. The marina at which the
majority of participating captains docked was Chinook Pier (48%), followed by Grand
Isle Marina (14%). The average length of 2003 charter vessels was 32.5 feet and ranged

from 22 to 37 feet.

Captain Attributes
All participating captains were male (100%) and primarily Caucasian (94%). The
average age of captains was 53.5 years, and ranged from 33 to 80 years. Participating

captains had gained the majority of their charter ﬁshing experience operating as captains

23

Docking Location of Grand Haven Charters
i 3% 3% 7%

7% 7% i Rycengas ’7' 1
i I North Shore

E Holiday Inn
Grand Isle

Chinook Pier

I Barrett Boat Works
I Trailer l
1 El Unknown '

 

10%

14%

 

 

Figure 4. Percentage of participating Grand Haven charter captains docking at each
Grand Haven marina or private location in 2003: North Shore Marina, Chinook Pier,
Grand Isle Marina, Rycengas Marina, Holiday Inn Marina, Barrett Boat Works, private
trailers, and unknown.

in Grand Haven for an average length of 16.4 years (range = 35 years, median and mode
= 20 years). The cumulative charter ﬁshing experience (i.e. including locations other
than Grand Haven) was only slightly higher (17.9 years, on average). This illustrates the
fact that captains had generally been in the same ﬁshery and social system for the
majority of their charter ﬁshing careers.

Reported income, in excess of proﬁt derived from chartered ﬁshing trips, came
from a wide variety of sources including the automotive industry (e.g., General Motors),
sales, law enforcement, social security, pension, retirement, investments, various
companies, engineering, taxidermy and mortgage broking. No captain relied solely on
income generated by the charter ﬁshery for their livelihood.

Approximately 57% of participating captains characterized their primary

24

motivation to ﬁsh as the personal satisfaction they acquired during charter ﬁshing-related
activities, while the motivation of 29% of participants was based primarily on their
enjoyment related to being outdoors. The remainder of participants reported being
motivated by the social satisfaction they gained during the charter ﬁshing season or by a
combination of the above factors.

Kin tie values ranged from zero to seven, with an average of 2.5. Thus, on
average, Grand Haven charter captains had familial relations with at least one other
Grand Haven mate. Only two captains reported having connections with people holding
professional ﬁshery-related positions (e.g., in academia or management).

Approximately 25% of 2003 Grand Haven captains had obtained high school
degrees as their highest level of schooling, one-quarter completed four or more years of
college education, and the remainder had completed one to three years of college courses.

Grand Haven captains participated in an average of 1.4 tournaments in 2003.
Thirteen captains did not participate in any tournaments during 2003, while the highest
number of tournaments that any one captain competed in was Six. Many captains
competed in the same tournaments, especially the Grand Haven and Tri-city tournament,
the latter including the Lake Michigan ports of (South Haven, Grand Haven, and
Holland).

Grand Haven charter captains belonged to an average of two NGOS, one of which
was the MCBA (requirement of being a participant). Participating captains also
commonly held membership with one or more of the following NGOs: the Grand Haven
chapter of the MCBA (GHCBA), the Michigan United Conservation Clubs (MUCC), the

National Association of Charter Boat Operators (NACO), the National Riﬂe Association

25

(NRA), the Michigan Steelhead and Salmon Fisherrnen’s Association (MSSF A, known
commonly as “Steelheaders”), and the Michigan Anglers Association. Eleven
participants reported holding leadership positions (i.e. secretaries, presidents, treasurers,
board members, chairs, and advisors) in the MCBA, GHCBA, local pier associations (i.e.
Chinook Pier), the NRA, Steelheaders, LMTF, NACO, MDNR Lake Michigan Advisory
Council and the Great Lakes Fishery Commission (GLF C).

As related to knowledge-seeking activities, eleven participants kept detailed logs
related to ﬁshing equipment success and lake/weather conditions (in excess of that
required by the MDNR). Twenty-one participants reported attending trade-ﬁshing
shows, primarily to examine new products and talk with other charter boat operators
about the value of these new products. Captains also reported attending trade-ﬁshing
shows to see what other charter operators and anglers were buying. The diversity of
ﬁshing-related information sources sought by Grand Haven charter ﬁshing captains
included membership meetings and magazines, other ﬁshermen, agency personnel, web-
pages, agency meetings, etc., and these sources are detailed in Table 2.

Just over two-thirds of participants exhibited innovativeness by owning a Nextel
phone. On average, captains have owned a Nextel for three years, with ownership
ranging from 2 to 8.5 years. Forty-ﬁve percent of 2003 Grand Haven charter captains
had a website advertising their charter ﬁshing business. Approximately 80% of
participants reportedly utilize the Internet (email, searching for ﬁshing-related
information) and 46% expressed willingness to enter their MDNR-required catch reports
online.

Based on survey responses, only ten (34%) participating charter captains felt

26

 

 

 

 

 

 

 

 

 

 

 

 

 

Source of Number of Priority of Use Detail
Information Captains on avg.
Utilizing Source (1 as highest
priority)
Membership 1 5 2.5 MCBA
Meetings GHCBA
MSSFA
Membership 19 1 .8 MCBA
Magazines GHCBA
MUCC
Great Lakes Angler
Great Lakes Fisherman
MSSFA
Michigan Out of Doors
Saltwater Sportsman
Rod Maker Magazine
Word-of-mouth 23 1.9 Charter captains
(Grand Haven) Private anglers
Word-of-mouth 13 2.3 Charter captains
(elsewhere) Private anglers
Agency Personnel 9 4.0 MDNR
Sea Grant
Web-pages 6 4. 1 MDNR
weather.com
Lake MI webcam
MSU Coastwatch
Not-speciﬁed
Agency Meetings 7 5.5 Sea Grant
Other Sources 3 1 Trial and error
MSU Sea Grant
Newspaper articles
Michigan Out of Doors
Practical Sportsman

 

 

Table 2. Sources utilized by participating Grand Haven charter captains to obtain ﬁshing-
related information.

conﬁdent that ﬁshery management agencies such as the MDNR effectively
communicated with natural resource stakeholders. Expectedly, the majority of Grand
Haven captains also felt that they preferred local to distant (e. g. federal) management of

their target resource.

27

On average, 62.9% of Grand Haven charter captain’s customers were returns, i.e.
they returned multiple times in a given season or year to year. However, given that some
captains were in their ﬁrst year of operation, percent return customers within the charter

ﬁshing ﬂeet ranged from zero to one-hundred.

Survey-Reported Communication

On a scale of 1-10, with 10 being the highest ranking, participating captains felt
that the importance of exchanging ﬁshing-related information with other ﬁshermen on
their success ranked, on average, a 6.7, with a median and mode of 7 and 8, respectively.
On average, participating captains identiﬁed 4.6 captains with whom they reported
exchanging ﬁshing-related information. Four captains reported not exchanging
information with anyone, whilst one captain identiﬁed 15 captains that he communicated
with (median and mode = 4, range = 15). Captain responses were compared to see if the
captains identiﬁed by participants as being someone they communicate with listed them
in turn. On average, captains held only 2.3 ties in common with those they identiﬁed
communicating with (verses the 4.6 identiﬁed), illustrating that not all captains identiﬁed
by other participating captains identiﬁed those captains as someone they communicated

with (median = 2, mode = 1, range = 0 to 7).

Survey-reported Catch
In response to the survey question soliciting the average monthly catch per trip,
approximately half (48%) of participants were willing or able to provide the requested

information. Reported monthly catch per trip was compared with the monthly ﬂeet

28

average per trip as documented in the MDNR catch report database (Figure 5). Nine
captains (ID numbers 149, 360, 591, 692, 754, 225, 820, 847, and 975) reported catching,
on average, more salmonids per trip in 2003 than the Grand Haven ﬂeet average catch.

The catches of these captains are illustrated in Table 3.

2003 Average Catch per Unit Effort

p—A
N

: —<>— Survey- ii

 

 

' a, M .

7 Ta 10 ay reported 1
1 ° catch ! .
l E 2 l?
i gt) 4 + Fleet I l
a 1 Catch ll
! t3 2 * * l.
0 ~~~» l

 

Figure 5. The average daily catch per month (# salmonids) by captains operating out of
the port of Grand Haven in 2003. This graph compares the ﬂeet average monthly catch
per trip as calculated using the Michigan Department of Natural Resources catch report
database and the average monthly catch per trip as reported by participating Grand Haven
captains.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

May June July August 2003 Total
Captain ID Fleet Average 9. 7 6.3 5.3 7.4 7.2
149 13.0 6.5 10.0 11.0, 10.1
360 14.0 10.0 5.0 7.0 9.0
591 8.0 7.0 8.0 11.0 8.5
692 15.0 4.0 5.0 10.0 8.5
754 10.0 8.0 10.0 12.0 10.0
225 13.3 4.1 5.3 8.9 7.9
820 11.2 6.0 6.8 N/A 8.0
847 9.6 9.6 4.5 N/A 7.9
975 16.0 9.0 5.0 N/A 10.0

 

Table 3. The reported average monthly catch (# of salmonids) per trip in 2003 of each

participating Grand Haven charter captain exceeding the ﬂeet average monthly catch per

trip as described in the Michigan Department of Natural Resource’s catch report

database.

29

 

Subgroups Identified Using Survey Data

Using the KliqueFinder algorithm, two non-overlapping cohesive subgroups were
identiﬁed from the data regarding the frequency at which captains reported exchanging
ﬁshing-related information with others in the ﬂeet (Figure 6). With the exception of the
random number representing Grand Haven private ﬁshermen in general, each number in
the sociogram indicates a Grand Haven charter captain; lines indicate the frequency of
ﬁshing-related communication between captains. Seventeen charter captains
communicated frequently enough with each other to form a non-overlapping cohesive
subgroup (A), while eleven charter captains and the private boat category (one
identiﬁcation number) formed subgroup B. Six Grand Haven charter captains were not
assigned to a subgroup based on lack of reported exchanges of ﬁshing-related

information with other Grand Haven captains.

Characterization of Survey-based Subgroups

The attributes of subgroup and non-subgroup members are summarized in Table
4. In general, each subgroup was comprised of captains from four or more marinas.
However there was a dominant presence (>40%) of captains from one marina in each
subgroup. For instance, charter captains operate out of six marinas in subgroup B. Over
42% of these captains are docked in one marina (Figure 7). Furthermore, captains from
the same marina tended to communicate more frequently with each other than with
captains from other marinas within this subgroup.

When compared to subgroup B, individuals in subgroup A have, on average, less

years experience as charter captains in Grand Haven or elsewhere. Subgroup B is also

30

 

 

Figure 6. A sociogram depicting the non-overlapping information-sharing subgroups of
the 2003 Grand Haven charter ﬁshing ﬂeet as derived from survey responses regarding

the frequency at which participating Grand Haven captains communicated with identiﬁed
captains.

31

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Subgroup Subgroup Subgroup
Fleet and Captain Attributes A B non-
members
n 15 10 4
(# of participating captains)
Docking location 64 44.4 50
(highest % of captains in same marina) (n-l)
Vessel size 33.1 32.6 29
(avg. length in ft.)
Age 46.4 62.8 56.5
4mg. years) (n- 1) (n-ZL
Experience as Grand Haven captain 14.9 21.2 10.0
(avg. years)
Kin ties 2.3 3.0 1.5
(avg. value: mates=2, captains=3)
Education 2.2 l .9 2.0
(avg: 1=HS, 2=some college, 3=college graduate) (n-2)
Competition
(% that compete in tournaments) 80 22 25
(avg. # tournaments for % that compete) 2.9 1 l
' 01- 1)
Industry involvement 27 60 25
(% captains with leadership positions)
Information seeking 47 33 25
(% of captains that keep a ﬁshing log)
Innovativeness 80 63 25
(% captains that own a Nextel phone) (n-2)
Communication (frequency) 73 50 0
(% captains that communicate more than 10
times/day with other captain)
% return customers 62.9 52 74.5
(n-l)
Communication 7.2 7.4 3.0
(perceived importance on ﬁsh catching success) (n-l)
(1-10, 10 as most important)
Observed catch 27 33 0
(% captains with above avg. catch) (n-2) (n- 1) (n-l)
Communication 5.6 5. 1 0
(avg. # captain reported Sharing information with) (n-1) (n-2)
(avg. # that reported sharing information w/ 5.0 3.8 0.5
captain) (n- 1)
(avg. # of shared ties based on exchange of 2.5 3.1 0
ﬁshing-related info)

 

 

Table 4. A summary of survey responses by participating Grand Haven charter captains
who were members and non-members of information-Sharing subgroups in 2003.

32

 

 

 

 

 

 

Figure 7. A sociogram depicting the docking locations of Grand Haven captains
identiﬁed through survey responses regarding the frequency at which participating Grand
Haven captains communicated with identiﬁed captains as being members of subgroup B.
Each of the six marinas represented by captains in subgroup B is boxed.
generally comprised of older captains. Although 57% of participating captains identiﬁed
the factor that most motivated them to ﬁsh as the personal satisfaction they obtained from
being a charter captain, more charter captains in subgroup A were more motivated by the
social interactions provided by ﬁshing than those in subgroup B, who were generally
more motivated by spending time on the water (i.e. outdoor enjoyment).

No patterns between kin ties and the structure of the social network of the Grand
Haven ﬁshing ﬂeet were evident. Although many participating captains were in some
way related to their mates (e.g., grandchildren, children, parents, Spouses), only two pairs
of captains that were members of the same information-sharing subgroup were related.

Thus, family ties in the Grand Haven charter ﬁshing ﬂeet did not exhibit as signiﬁcant an

effect on subgroup membership or ﬁsh-catching success as seen in other ﬁsheries.

33

Members of subgroup A, on average, had more years of formal schooling than captains in
subgroup B. The most frequently held level of education of captains in subgroup A was
1-3 years of college, followed by four or more years of college (one third). Half of the
captains in subgroup B had received a high school diploma as the highest level of
schooling completed, over a third completed four or more years of college, and
approximately 12% completed 31-3 years of college.

Participation in tournaments, as a measure of competitiveness, was highly varied
between the two subgroups, with members of subgroup A exhibiting the most
competitive behavior. Only 22% of captains in subgroup B reported competing in
tournaments in 2003, while 80% of the charter captains in subgroup A participated in at
least one tournament a year, with those captains competing in an average of 2.9
tournaments.

Members of subgroup B were generally more involved in leadership roles within
ﬁshery-related organizations. Sixty percent of the individuals in subgroup B have held
positions of leadership in various organizations or agencies, whereas only one quarter of
respondents in subgroup A held such positions.

Nearly half of the captains in subgroup A collected data in excess of that required
by the MDNR in a ﬁshing log while only a third of captains in subgroup B collected such
information. Additionally, captains in subgroup A were found to be more innovative
than those in subgroup B. For example, captains in subgroup A had, on average, owned a
Nextel phone for over 3.5 years, while captains in subgroup B owned a Nextel for just
over 2.5 years. No difference was noted in the availability of a business website between

subgroups. However, all captains that were not members of a subgroup did not have a

34

website, and all but one non—member owned a Nextel phone.

On average, captains in subgroup A had more customer returns than those
captains in subgroup B (62.9% vs. 52%). The percent of customers returning to those
captains not in a subgroup exceeded that of both subgroup B and A members at 74.5%.

Captains that reported having above-average catches of salmonids tended to hold
relatively “central” positions within the Grand Haven social network, i.e. they identiﬁed
and were identiﬁed more oﬁen as someone with whom ﬁshing-related information was

exchanged than those captains with below-average catch (Figure 8).

Communication within and between Survey-based Subgroups

Charter captains in subgroup A tended to communicate more frequently with each
other than captains in subgroup B; only 50% of those in group B reported exchanging
information (any mode) with other captains more than ten times a day, while 75% of
those in subgroup A report this level of exchange per day. No captains who were not part
of a subgroup reported exchanging ﬁshing-related information more than ten times a day.

In general, those who reported exchanging ﬁshing-related information more than
ten times a day also felt that communication Signiﬁcantly improved their ﬁsh-catching
success. On a scale of l to 10, with 10 being the highest ranking of perceived
importance, Grand Haven charter captains from both subgroups ranked the importance of
ﬁshing-related communication on the success of their charter business as being slightly
over seven (subgroup A=7.2, subgroup B=7.4). Captains who were not included in an
information-Sharing subgroup ranked the importance of ﬁshing-related communication

on the success of their charter operation an average of only 2.3.

35

  

Above Average
0 Reported Catch

 

Figure 8. A sociogram depicting (through circles) the identiﬁcation numbers of
participating Grand Haven captains that reported having an average monthly catch per
trip in 2003 determined to be above the ﬂeet average monthly catch per trip.

36

Subgroup A has the greatest proportion (60%) of captains that reported or were
reported as giving sometimes less than reliable information. These included 692, 754,
748, 975, 912, 125, 133, 820, and 591. In Subgroup B, only two captains (847, 149) and
private anglers in general (363) reportedly gave slightly unreliable information (30%).
Interestingly, all respondents strongly agreed that they considered any exchanges of

ﬁshing-related information with those not in their subgroup reliable.

On-board Observations

Observed Catch and Communication

Communication between captains and catches of salmonids were observed and
recorded during forty-one charter-ﬁshing trips from May 18, 2003 through September 6,
2003. Throughout the entire ﬁshing season, and while I was on their boat during a
chartered ﬁshing trip, captains being observed received a total of 138 units of ﬁshing-
related information. In turn, these captains gave 132 units of information to other vessels

while I was on their boat. I also observed the catching of 280 salmonids during this time.

Subgroups Identiﬁed Using Observational Data

KliqueFinder depicted the existence of four subgroups from the on-board
observational data as opposed to the two, as identiﬁed when using communication data
from the survey (Figure 9). During on-board observations, three charter captains who
were described with the survey data as not participating in the exchange of ﬁshing-related

information with others were indeed observed to communicate with more than one person

37

 

O
S
.M‘;."..
gill on
q

:::::e%:;s: if
a. ........‘O

 

 

 

Figure 9. A sociogram depicting the non-overlapping information-sharing subgroups of
the Grand Haven charter ﬁshing ﬂeet as derived from on-board observations of ﬁshing-
related informational exchanges.

38

 

and were therefore included in the sociogram based on observed ﬁshing-related
communication. Additionally, it was noted that four charter captains included in one of
the two subgroups based on survey-reported frequency of ﬁshing-related communication
were not actually observed to communicate with one or more captain or private vessel
and were hence excluded in the depiction of the network based on observed ties.

Although there were four subgroups based on observed ties rather than the two as
reported by survey responses, there were Similarities between the two KliqueFinder
sociogram outputs. For instance, all but two of the captains that comprised the subgroup
B based on survey-reported ties were also in the same subgroup that was based on on-
board observations (subgroups B, observed). Survey-reported subgroup A captains that
were observed to be in different subgroups (A, C, and D, observed) still maintained
communication with the same captains that they had reported communicating with in the
survey—the observed frequency was just less and likely a product of observation hours.

Due to the close proximity of subgroups C and D in the sociogram derived from
observations, it was evident that these two subgroups exchanged relatively more ﬁshing-
related information with each other than the other two subgroups (A and B). This indeed
reﬂects the fact that these captains from observed subgroups C and D reported
communicating frequently enough with each other that they were initially included in the
same subgroup (A) based on survey responses related to ﬁshing-related informational
exchanges. Subgroups A and B exchanged relatively less information with each other
than with subgroups C or D, which was also reﬂected in the survey data.

Six Grand Haven captains (360, 847, 754, 225, 896 and 975) were observed to be

more successful in locating and catching salmonids than other captains during the

39

summer of 2003 (Figure 10). These captains caught above the ﬂeet average on days
when they were observed. Figure 1 1 contrasts the observed catch against the average

ﬂeet catch.

Relationships between Catch, Communication and Attributes

A chi-squared test determined that geographic (docking) location of charter
operations was signiﬁcantly related to captain membership in subgroups. However,
geographic location was not the only determinant that participants use when choosing
with whom to exchange ﬁshing-related information. Communication occurred between
those captains that had a history of mutual support, who acknowledged support when it
was given, who acted in the best interest of others, and who were likely to reciprocate.

The SAS correlation determined that the following variables were signiﬁcant at or
= 0.05. Observed catch was signiﬁcantly and positively correlated with the number of
NGOS in which a captain was a member (p = 0.0337; r = 0.44422) and number of
reciprocal ties held by captains Q) = 0.0144; r = 0.52540). Vessel length was
signiﬁcantly and positively correlated with experience in Grand Haven (p = 0.0002; r =
0.63711) and elsewhere (p = 0.0007; r = 0.59303), in addition to the number of kin ties
held (p = 0.0188; r = 0.43357). Age was signiﬁcantly and positively correlated with
experience in Grand Haven (p = 0.0058; r = 0.52596) and elsewhere (p = 0.0026; r =
0.56637), but negatively correlated with education (p = 0.0438; r = -0.41495) and
competitiveness (p = 0.0348; r = -0.42377). Experience in Grand Haven was
signiﬁcantly and positively correlated (as was experience elsewhere) with kin ties (p =

0.0102; r = 0.46951) and the amount of times a captain was listed by other captains as

40

I Above Average
Observed Catch

    

   
     
      
   
  

..‘ 40......

;;:.:,. .3}: a

320 5133418 ,. . .

      
    
   
  

  

   

    
  

D \ I "‘“~-- vvv9?5.2!.\“.. .
.22: t..:......:............ ...........,.;i754 :-;:.ig75
, , 33' ° :’ {'3' .

Figure 10: A sociogram depicting (through adjacent black squares) the identiﬁcation
numbers of participating Grand Haven captains that were observed in 2003 to catch

above the ﬂeet average during an observation day as determined through use of the
Michigan Department of Natural Resources catch report database.

41

_e __L z- a L- a- - 1

Catch: Fleet Average vs. Individual Observed

 

 

 

 

 

 

 

 

l

: i5

iE 40

l O

l E , ‘3 c- h h f f Pi- A

i 5’ 30 U o ‘ 0 Fleet

Z 3 20 o- -. ., ,- , _ W - Average

i g e

’5 a 02.... $ . l 0 Observed .

5:. 10 5,5“ 15.3.. 313:. . a, a :1 1-- catch l

:g 0 00600 ring 337 .00 0 Di 1

T U ! i

i 13-May 2-Jun 22-Jun 12-Jul l—Aug 21-Aug 10-Sep 30-Sep :
Individual Observations

 

 

 

Figure 11. The observed number of salmonids caught per trip by Grand Haven
participating charter captains in 2003 contrasted against that’s day’s ﬂeet average as
determined through use of the Michigan Department of Natural Resources catch report
database.

someone they communicated with (p = 0.0214; r = 0.43275). Competitiveness was
signiﬁcantly and positively correlated with the amount of times a captain was listed by
other captains as someone they communicated with (p = 0.0450; r = 0.38882).
Membership in NGOS was signiﬁcantly and positively correlated with the amount of
times a captain was listed by other captains as someone they communicated with (p =
0.0073; r = 0.50412) and also with reciprocal ties (p = 0.0200; r = 0.46239).

Innovativeness (years of Nextel ownership), the number of ties identiﬁed by captains, and

% return customers were not signiﬁcantly correlated to any variables.

Comparison of Observed and Reported Catch and Communication
On-board observations veriﬁed that ﬁve of ten captains that reported catching
above the ﬂeet average did indeed catch, on average, more salmonids than others within

the Grand Haven ﬂeet (Figure 12). Captains with both above-average observed and

42

reported catch generally reported having more ties than other participating captains with
below-average catch (Figure 13). Additionally, captains with both observed and reported
above-average catch were in the top ten as being listed most frequently by other captains
as someone they communicated with about ﬁshing-related information (Figure 14). The
same was true for reciprocated ties, i.e. seven above-average captain (observed or
reported) were in the top ten as having listed a captain that also listed them (Figure 15).
Five captains with above-average observed and reported catch were within the top ten as

listing the most ties with other Grand Haven captain.

Summary of Results

This study identiﬁed a distinct network through which ﬁshing-related information
ﬂowed between members of the Grand Haven charter ﬁshing ﬂeet during 2003.
Subgroups of concentrated ties based on ﬁshing-related informational exchanges within
the ﬂeet had unique captain attributes, such as level of experience, competitiveness,
involvement as leaders, and perceptions regarding ﬁshery management. Captains with
above-average ﬁsh-catching success generally had more access to information (i.e. more
ties) and held a relatively central position within the communication network. Captains
were generally able to depict their position within this communication network and recall
ties with other captains, especially if the other captains exhibited Similar or higher ﬁsh-

ﬁnding and -catching ability.

43

      

   

 

~ '1' . _
, . .,-.ui' -
‘1
«J

I'ﬂfll coco...

 

'.

1. 0 Above Average
' Observed &
Reported Catch

;s:=.

:;¢‘

 

Figure 12. The sociograms derived from observed and reported communication data
depicting captains with both above-average observed and reported catches of salmonids
during 2003.

44

 

 

 

 

 

 

 

l - .___- ___, - .____._ EMA- -_.___._ A“
‘ Reported Number of Ties & Relative Catch Success
1 If“ __ .__._
i B 16 [E i 0 Ties Identiﬁed I
l 3:3 14 l by Captains in l

5 12 C I W W 1 Rank Order
I ._. 10 .

. e93
, E—i .
l E 6 O ’13]. ’ ’ ° ’ * Above-average :
E g 4 ., ,,, o o o o oww , - Observed &

O O O O

l g 2 f- -2.-. f _ l3 Reported 4L
‘ Z 0 e e e e T , ; {L‘CatCh J ,
l ________

0 10 20 30 I

Figure 13. Graph depicting the tendency for participating Grand Haven captains having
observed and reported catches above the ﬂeet average in 2003 to target relatively more
individuals to give and receive ﬁshing-related information.

1 Captains

 

 

 

 

 

 

 

 

 

 

 

l— _ m-“ _ _._._.__.____._ -
‘ Captains Identifed by Others as Communicators
l & Their Relative Catch Success
| ﬁ__ _. ____ , l
. 14 . - ~ . . 0th 1
.5 El “S
.3 g 12 -- ,_ —~ - Identifying
‘8 Ca tain in
0 O 10 P
<6 3 [2] Rank Order
U) 8 i L ,,__
“.e.’ a «:1
i E: 3;, 6 __, ’E. ’ ' ‘ 1 Above
; 8.8 4 00908 Average
1 B E 00 ‘ Observed &
, — ee . ~ ‘
I g 3 2 000000 Reported
I Z 0 rr . . ‘- ,-____§3_at£h_-_-‘
O 10 20 3O
1 Captains

 

Figure 14. Graph depicting the tendency for participating Grand Haven captains having
catches above the ﬂeet average in 2003 to be the target of ﬁshing-related informational
exchanges.

45

Reciprocated Communication & Relative Catch Success

 

 

 

'52 8 -. I : Reciprjated .
I 8 7 E Ties in Rank I
§ 6 I Order
a. s a I
.._ I i
O 0 0|: : :l I
g 4 , , . D Above I
‘8 3 1 Average I I
g 2 "° . E Observed& :1
I g 1 .90... 7 7 I Reported I]
Z O #666: l 1|L_(_:_3I_C.h__ II
0 10 20 30 i
Captains i

Figure 15. A graph depicting the tendency of participating Grand Haven charter captains
having catches above the ﬂeet average in 2003 to also have high numbers of other
participating captains reciprocate in listing them as someone they exchange ﬁshing-
related information with.

46

 

DISCUSSION

Summary of Discussion Topics

Grand Haven charter captains belong to information-sharing subgroups which
appear to be related to ﬁsh-catching success. The formation of subgroups within ﬁsheries
is not unique to Grand Haven as Acheson (1988) and Gatewood (1984, 1987) reported
similar phenomena for Maine lobster ﬁshermen and Alaskan salmon seiners. In all cases,
these subgroups formed in response to ﬁshery-related uncertainty. The formation of
subgroups inherently results in unequal sharing of information and other resources
throughout ﬁshing ﬂeets that beneﬁts some while not others. The beneﬁts and social
capital that Grand Haven charter captains acquire through the Sharing of ﬁshing-related
information appear to outweigh the consequences related to helping competitors. Grand
Haven charter captains selectively choose whom to exchange ﬁshing related information
with and the quality of the information transmitted. Social network analysis was useful
in determining the communication network of the Grand Haven charter ﬁshing ﬂeet and
provides a methodology for assisting ﬁshery managers in understanding stakeholder

groups for more efﬁcient management in the future.

Subgroup Verses Whole Fleet Sharing of Fishing-related Information

A basic premise for subgroup formation within a ﬁshery is to minimize
competition for a resource while maximizing beneﬁts for those within the subgroup. For
instance, if captains were to exchange ﬁshing-related information with everyone, their

ﬁsh-catching success would likely be decreased Since too large of a cooperative group

47

would result in diminished catch of salmonids for all (e.g., Hoetzel’s 1993 study
regarding optimal group sizes of killer whales [Orcinus orca] foraging for migratory
salmonids). In Grand Haven, the formation of information-sharing subgroups appeared
to be attributed to the tendency of captains to share ﬁshing-related information with those
whom they 1) have a social history (e.g., graduating from the same Coast Guard captain
licensing class), 2) perceive to provide quality information that increased their likelihood
of catching ﬁsh 3), share docking facilities, and 4) have desirable personal character traits
(e.g., expressing gratitude for or reciprocating past help). Captains minimize their

interactions with those that do not meet these criteria.

Beneﬁts of Sharing Fishing-related Information with Competing Operators

Grand Haven charter captains who exchange success—enhancing information with
other charter captains received several important beneﬁts that likely outweighed the
disadvantages related to helping competitors ﬁnd and catch salmonids. For example,
Grand Haven captains having difﬁculty ﬁnding salmonids would often call another
Grand Haven captain, volunteer ﬁshing-related information, and then either ask a direct
question (e.g., “Where are you ﬁshing?”) or wait for a reciprocated sharing of
information in response to the volunteered information. Captains who participated in the
exchange of ﬁshing-related information often increased their immediate (e.g., current
conditions) and long-term (e.g., techniques) breadth of knowledge, thus also increasing
their likelihood of ﬁnding and catching highly mobile and somewhat unpredictable
salmonids. Thus, Grand Haven captains who were classiﬁed as having salmonid catches

above the ﬂeet average were generally found to exchange more ﬁshing-related

48

 

information with other captains than those captains with below average catches. Captains
were aware of and ranked highly the importance of ﬁshing-related communication on
their ﬁsh-catching success. The existence of information-sharing subgroups within other
types of ﬁshing ﬂeets, such as those formed by Alaskan salmon seiners, lend beneﬁts
such as increased ﬁsh-catching success or, at worst, diffusion of the responsibility placed
on the captain by the crew in the event of an unsuccessﬁrl ﬁshing attempt (e.g., Gatewood
1984). In communicating with others, skippers of Alaskan seining vessels were
perceived by their crew as actively trying to maximize catch and thus protecting their
welfare. As such, the crew did not blame the captain in theevent of poor catches, as they
perceived that the skipper had done all possible to maximize their ﬁsh-catching success.
Sharing ﬁshing-related information and helping in other ways (e.g., giving
another captain a lure with proven ﬁsh-catching ability) also enabled Grand Haven
captains to acquire a key social currency, social capital. The beneﬁts of acquiring and
maintaining social capital included the ability of Grand Haven captains to access ﬁshing-
related information through those captains who had previously received their help or, for
example, who had generally acted in the best interest of other captains. Social capital
also assisted in providing new opportunities to the cooperating captains, such as customer
referrals. Through their survey responses, charter captains exhibited a predisposition to
target other captains with ﬁshing-related information with whom social capital had been
acquired in the past, e.g., they shared a history of mutual support and reciprocation. A
Similar phenomenon, deferred gratiﬁcation, has been described in other ﬁsheries (e. g.
small-scale ﬁshermen in Puerto Rico) as an adaptive characteristic in Situations where

uncertainty is high (Poggie 1978).

49

Within the Grand Haven charter ﬁshing ﬂeet, social capital appeared to be
acquired through both success at catching ﬁsh and previous positive social relations. For
example, the directionality of voluntarily offered ﬁshing-related information was often
aimed at captains with equal or greater ﬁsh-catching success. Thus captains with lesser
catches could use positive social interactions with others to bolster their social capital that
could then be used to access ﬂeet resources, such as ﬁshing knowledge. Captains with
high catches were likely already at an advantage since their catching success gave them

more access to ﬂeet resources and the respect of others.

Selective Exchange of Fishing-related Information

Selective exchange of ﬁshing-related information in Grand Haven was not largely
driven by kinship ties. This is contrary to what has been noted in other ﬁshing networks,
such as that of the Maine lobster (e.g., Acheson 1988) and southeast Alaskan salmon
seining ﬁsheries (Gatewood 1984), in which ancestry and kinship allow for access to
many resources, including ﬁshing grounds, capital (social and monetary), and ﬁshing-
related information. However, past employment as a mate in Grand Haven appeared to
insure some social beneﬁts within the ﬂeet. For example, a captain who mated as a crew
member for two successful and socially-integrated Grand Haven captains in the past was
a member, albeit at the periphery, of a subgroup despite hisrelatively isolated docking
location and inexperience. Additionally, a docking neighbor of this captain was also part
of the larger subgroup again at the periphery as, he too, was at the same isolated marina,

relatively inexperienced, and had not previously acted as a mate for others in that

subgroup. Ties through secondary employment were also somewhat indicative of

50

subgroup composition, since people who worked together outside of ﬁshing developed
stronger friendship ties or had more interactions outside of charter ﬁshing. Loyalty to
licensed cohorts appeared to also have an effect on subgroup membership. For example,
although one captain was somewhat on the fringe of being included in a Grand Haven
information-sharing subgroup for past socially unacceptable behavior, he enjoys the
beneﬁts of subgroup membership due to his long-lasting friendship with another highly
integrated (i.e. who has many information-sharing ties with others) captain.

In Grand Haven, the most obvious reason why captains communicated with
selected captains was geographical convenience. Being docked in the same marina was
shown to be statistically related to the likelihood of captains exchanging ﬁshing-related
information. This is likely a function of the case at which such interactions could occur
when not ﬁshing. However, this was not the only determinant regarding who exchanged
ﬁshing-related information with whom. For example, four captains in subgroup A were
docked adjacently in the same marina and frequently Shared ﬁshing-related information.
However, in response to the survey question regarding communication choices (#32, “I
choose to communicate with other charter ﬁshermen while charter ﬁshing when it is. . .),
none of these adj acently-docked captains agreed that they based their communication
decisions purely on convenience (i.e. docking adjacently) and only one agreed that he
“chose to communicate with others when it was easy” (i.e. with neighbors). Grand
Haven captains thus chose whom to approach for and share ﬁshing-related information,
regardless of docking location and convenience. Reasons for this selectivity included the
catch and individual attributes of captains. In the Grand Haven ﬁshery, captains sought

to communicate with those captains having equal or higher catch and who reciprocated

51

over time. To do otherwise would be counterproductive. The directionality in the
communication between captains is also evident in other ﬁshing ﬂeets. Maine lobster
ﬁshermen have been described as tending not to divulge secrets unless the resource
(information, social capital etc.) obtained during the exchange is worth at least as much
as what they are giving (Acheson 1988). In addition, highly successﬁrl lobster ﬁshermen
have relatively more abundant and diverse access to resources, as many ﬁshermen want
to talk to them. Additionally, highly successful lobster ﬁshermen were found to often
initiate and maintain ties with other successful ﬁshermen distant from their local network,
thereby gaining access to new innovations and thus higher catching abilities (e.g.,
Granovetter 1973; Rogers 1995). This was also observed in Grand Haven as some
captains maintained ties, albeit less frequent, with others not in their subgroup.

In Grand Haven, exclusion of those charter captains that did not contribute to the
increased success or social capital of other captains was gradually being accomplished
through a variety of means. For example, the adoption and utilization of Nextel and
cellular telephones in the transferring of ﬁshing-related information has become a more
popular means of communication than ship-to-ship radios, the latter of which allows
everyone to tune in and eavesdrop. Unlike the radio, Nextel and cell phones offer a much
more direct and selective means for charter captains to target individuals with or for
ﬁshing-related information based on their historical success or individual attributes.

Selective communication thus not only leads to the formation of information-
sharing subgroups within speciﬁc ﬁshery groups, but also acts to further separate
differing ﬁshing groups (i.e. charter ﬁshing ﬂeet vs. private anglers). For example,

Grand Haven charter captains described that reporting helpful ﬁshing-related

52

information, such as the location of a high density of salmonids, to someone over the
radio often resulted in many private vessels or inexperienced charter captains
congregating around the reported area, creating maneuvering problems, tangling ﬁshing
gear, and ultimately resulting in decreased ﬁsh-catching success for experienced charter
captains and their customers. AS many private ﬁshermen clock less angler hours than
more business-oriented charter captains, these ﬁshermen often try to compensate for their
lack of experience and knowledge regarding the ﬁshery by trying to emulate the tactics of
more experienced captain without considering the possible negative impacts and
hindrance that their ﬁshing behavior causes to the experienced ﬂeet captains.

Similarly, interactions between recreational/part time and full-time commercial
Maine lobster ﬁshermen mirror those between Grand Haven private ﬁshermen and
charter ﬁshing operations (Acheson 1988). Part-time lobster ﬁshermen tend to learn
obtrusively from highly successful, full-time ﬁshermen due to a lack of understanding of
the lobster ﬁshery and existing social norms that would guide them in learning
unobtrusively.

Both part-time lobster ﬁshermen and private ﬁshing boats in Grand Haven are
generally unable to reciprocate or build social capital due to infrequent ﬁshing and thus
inexperienced. They are oftentimes perceived as impinging on rights established through
following social norms and are considered at best a nuisance. This is accentuated by the
fact that private ﬁshermen do not depend on ﬁshing as a source of income, and thus have

less to lose if they are the recipient of sanctions as a result of inconsiderate behavior.

53

The Curiousness of Sharing Not-so-helpful Fishing—related Information

Those that Share membership in subgroups are already afforded access to
resources and protection from potentially detrimental outside forces, such as competing
users or uncertainty (e.g., Frank and Yasumoto 1998; Frank et al., under review).
Interestingly, the ﬁshing-related information reportedly Shared between a number of
Grand Haven charter captains in the same subgroups (based on survey) data was reported
as somewhat untimely or unreliable. This is contrary to Gatewood’s (1987) description
of salmon seining cliques in Alaska, where individuals in a clique within the larger
network generally exchanged trustworthy and reliable information. Even more
interesting is that information ﬂow between Grand Haven subgroups was reported as
reliable and timely. Exchanges of unreliable information within subgroups, yet not
between, is worthy of note and begs addressing.

The reason for these differences in information quality was likely related to
delegation of social capital and enforceable trust within and between subgroups as seen in
Frank and Yasumoto’s (1998) study of the French ﬁnancial elite. Frank and Yasumoto
(1998) Showed that hostile actions, such as a corporate takeover among the French
ﬁnancial elite, seldom occurred within subgroups. However, it was observed that
members of the French ﬁnancial elite sought to engender new obligations and access new
information and resources by helping those outside their subgroups (Frank and Yasumoto
1998). They further hypothesized that actors would be less likely to enforce each other’S
trust and more likely to engage in reciprocation and supportive actions if they were not
members of the same subgroup. It was reasoned that members of the French ﬁnancial

elite supported others outside their subgroups because they already had social capital

54

 

within their subgroups via enforceable trust — the dense social ties within subgroups
increased the likelihood that anyone who betrayed the trust of a subgroup member would
be sanctioned, socially and otherwise, by the group as a whole.

As with the French Financial elite, it is likely that Grand Haven captains had
developed enough social capital with those in their subgroup and could thus afford, at
times, to withhold or minimize the quality of the information exchanged. Since subgroup
non-members are generally not afforded all of the beneﬁts of members, it a captain’s best
interest to exhibit socially acceptable behavior and provide a higher quality of ﬁshing-
related information to those not in their subgroup. So perhaps, as Frank and Yasumoto
(1998) describe, actors that share membership in the same subgroup are conﬁdent they
will receive subgroup beneﬁts (e.g., customer referrals within the charter industry) and
are therefore motivated to push the limit of providing sub-par information while still
maintaining social capital.

Additionally, it must be understood that charter ﬁshing is a highly visible,
potentially lucrative, and ego-driven endeavor which provides an underlying context for
social behavior while ﬁshing. For instance, captains, crewmembers, customers, and
private anglers are publicly made aware of other captain’s catches via display at public
ﬁlleting stations. Charter ﬁshing is thus a high proﬁle Sport, not only affecting the
angling customers but also captain and crew. AS such, it would not be inconsistent
human behavior for charter captains to sometimes stray from being completely accurate
or thorough in what information they choose to distribute during a ﬁshing excursion.
Described as not timely or exaggerated by Grand Haven captains, exchange of low

quality information has been attributed to information management in competitive

55

 

endeavors such as ﬁshing (e.g., Anderson 1973).

Also interesting is that a number of Grand Haven captains stated that they could
tell the difference between exaggerated or untimely information and reliable information.
Primarily this was a function of the experience and judgment of the captain receiving the
information with the ﬁshing conditions of the day and previous experience with the
information-giver. Even with the awareness that the information passed between
subgroup members could be marginal, they still exchanged ﬁshing-related information as
some information could be helpﬁrl in increasing their ﬁsh-catching success.

Communication behavior was least reliable between competitive Grand Haven
captains with exaggerations being ampliﬁed in subgroups in which captains ﬁshed
tournaments. This coincides with Anderson’s (1973) study which described
exaggerations as being reputation-based and competitive. It should be noted that
informational exchanges between “exaggerators” were oﬁen playful in nature and could
be considered a good representation of maritime ﬁshing traditions (e.g., Anderson 1973).
The exchange of “chatter” and “real” information is a function of the ﬁshing
circumstance. When Grand Haven captains and other types of ﬁshermen are having
moderate or high success at ﬁnding and catching ﬁsh, they are more likely to banter;
when ﬁnding and catching ﬁsh is difﬁcult, the quality of information improves and
atmosphere of exchange becomes more serious. Furthermore, communication between
Grand Haven captains was more reliable when captains were faced with safety and well-

being issues (i.e. mechanical problems while ﬁshing).

The Persistence and Strength of Stakeholder Communication Networks

56

As it has been Shown in this study and in others (e.g., Gatewood 1984), anglers
targeting species with unpredictable behavior tend to form subgroups of information-
sharers. Gatewood (1984) found that the formation of information-sharing cliques prior
to salmon seine periods are somewhat ephemeral. This is likely due to the year-to-year
changes in the ﬁshery and how important skippers feel information-sharing is to their
success and respectability by their crews. Likewise, Grand Haven charter captains tended
to elicit ﬁshing-related information more frequently and at levels of higher detail during
periods of time when they were having difﬁculty locating and catching salmonids. Thus,
ﬁsheries that are in a state of unpredictability or poor shape will have networks that
facilitate communication and interactions of a higher quality and quantity than those that

are stable.

Use of Social Network Analysis for Fisheries Management

Social network methodologies provide ﬁsheries managers with useful tools that
enhance their understanding of stakeholder groups and the inﬂuence of their interactions
on Shaping behaviors towards natural resources. Use of these tools allows for ﬁsheries
professionals to evaluate the distribution of resources (e.g., knowledge, social capital,
innovations) within networks and thereby enable them to more effectively communicate
with stakeholder groups (e.g., Maiolo and Johnson 1992; Acheson 2001). For example,
Acheson (2001, 1975) reported that managers could better predict reactions of lobster
ﬁshermen to management schemes once they understood the importance informal norms
which were generated through the strong interactions between stakeholders operating

within the Maine lobster ﬁshery. Failure to do so can result in negative consequences for

57

ﬁshery resources (Hilbom 1985). In the Maine lobster ﬁshery, managers were able to use
social network knowledge formalize already-existing social institutions into the
management structure, thereby creating a more acceptable and effective management
regime for this lobster ﬁshery (Acheson 1975). In a case study, Acheson (1975) argued
that potential opposition to ﬁsheries regulations would be minimized if such regulations
were congruent with existing social network norms and institutions. He reported that
limited entry as a management intervention was the most effective protocol for declining
lobster catch as it was consistent with what the local ﬁshing community determined
socially acceptable. This limited entry management approach essentially formalized the
way in which lobster ﬁshermen operate (Acheson 1975, 1980). Thus, insight into social
network processes of stakeholder groups will likely result in development and
establishment of better decisions which garner stakeholder support and the needed
sustained behavioral modiﬁcations which assist sustainability of the target ﬁshery.

Social network methodologies also provide a means to evaluate the ﬂow of
resources within a stakeholder network. Furthermore, these methods enable managers to
better anticipate how resources diffuse through networks and subsequently the best ways
in which track the adoption of new innovations and success of management programs.
(e.g., Rogers 1995; Decker and Krueger 1999; Frank et al. 2004).

Understanding social network dynamics is becoming increasingly important as
ﬁsheries become more globalized in nature. In most ﬁsheries, external inﬂuences from
non-locally derived stakeholders as well as those who are local but do not directly engage
in ﬁshing are dominating the management landscape. As local ﬁsheries experience

globalization, the utilization of social networks will become increasingly important to

58

stakeholders and management agencies. For example, providing opportunities for
socially central stakeholders to serve on community advisory committees might, in part,
ameliorate problems that arise when management becomes increasingly distant (Maiolo
and Johnson 1992). In Grand Haven, a number of charter captains serve on advisory
committees for Great Lakes agencies, i.e. the MDNR and GLF C. Furthermore, given the
time, person power, and ﬁnancial limitations of many natural resource agencies,
approaching central and inﬂuential network members that have many ties within the
network has the potential to decrease the resources required to implement new
innovations or policies that are acceptable to the stakeholder community as these central
actors are better able to communicate effectively and diffuse information through the
network efﬁciently due to their earned social capital (e.g., Frank et al. 2002). It is
important to note that the central actors have the trust or respect of the majority of other
stakeholders within the group and thus can be viewed as inﬂuential voices for all
stakeholders within the community.

The reactions of ﬁshermen to ﬁshery-related uncertainty are better understood and
predicted with increased insight into the social fabric of ﬁshing communities and their
ﬁshery resources (Acheson 2001; Mangel and Clark 1983; Sampson 1991). This study
described the importance of interactions among Lake Michigan salmonid carter captains
on their target ﬁshery resource. The selective exchange of ﬁshing-related information
and use of social capital within the Grand Haven ﬂeet enabled charter captains to increase
their likelihood of locating and catching salmonids. In this way, captains have the ability

to inﬂuence their current and future access to ﬂeet and ﬁshery resources.

59

 

APPENDIX A

60

 

APPENDIX A

Replicated Letter of Intent to Potential Study Participants

Date
Address
Dear [Name of Grand Haven MCBA charter captain]:

I am a graduate student in the Department of Fisheries and Wildlife at Michigan State
University. My research focus is on the manner in which and the degree that
communication inﬂuences catch success in the charter industry. Ultimately I believe this
will help ﬁsheries managers gain a better understanding of social dynamics within the
charter industry, which will enable managers to work more constructively with charter
ﬁshing captains. I have received a MCBA mate’s license, and would like very much the
opportunity to serve as a second mate on your charter for 2 days this summer at your
convenience. This mate’s license will enable me to board your boat as a non-customer.

I plan to collect observational data, such as catch, and general information on
communication and use of cell phones, 2 way radios, etc., and will help outwith any
chores (not limited to ﬁsh cleaning, customer service, and line-rigging). I am also asking
charter captains and mates operating from Grand Haven to answer questions regarding
communication patterns with other captains as part of my graduate research. Signing a
consent form and answering the survey questions indicates your consent as a participant
in this study in so far as your responses will be analyzed. I will keep all data collected as
conﬁdential. Preserving conﬁdentiality, I will share the generalized results with
participants by 2004. Participation in this study is voluntary.

I plan on contacting you in person to make two appointments: 1) to serve as a second
mate and make observations as mentioned above, and 2) to serve as a second mate, make
observations, and provide the survey (this Should take approximately 25-30 minutes at
the end of the charter trip after the customers have leﬁ).

Thank you for your time. I look forward to talking to you in the near future. If you have
further questions, please feel free to contact me: 703-927-2087 or muelll 12@msu.edu

Sincerely,

Katrina B. Mueller
Graduate Research Assistant

61

APPENDIX B

62

APPENDIX B

UCRIHS-approved study participation consent form

The Effects of Communication and Social Capital on the Catch Success of Charter
Boat Operators in Grand Haven, Michigan

I am asking charter captains and mates in your port, Grand Haven, to answer the
following questions as part of my graduate research in the Fisheries and Wildlife
Department at Michigan State University. My research focus is on understanding aspects
of social dynamics of ﬁshery stakeholders, namely the manner in which and the degree
that communication inﬂuence catch success in the charter industry. Ultimately I believe
this will help ﬁsheries managers, including myself, work more constructively with
charter boat captains by better understanding communication and social dynamics.

1 plan to collect the following data as part of this research project:

1. Field notes based on observations on charter boats and at the dock.
2. The estimated 30-minute interview that is on the following pages.

Participation is voluntary. You may choose not to participate at all, or you may reﬁrse to
answer certain questions or discontinue the interview at any time. I will keep all data
collected as conﬁdential. Preserving conﬁdentiality, results will be available in 2004.

Although no trade secrets will be revealed and I will protect your conﬁdentiality by using
conﬁdential identiﬁcation numbers for individual charter boat captains in all publications,
you or others may be able to discern some of the identities based on reported attributes of
participants. There is also the possibility of unforeseeable risks. You may withdraw your
consent and discontinue participation in the study at any time during the interview.

If you have any questions or comments, please contact my advisor (Bill Taylor, 517-353-
0647, taylorw@msu.edu) or myself (517-353-6697, mueller112@msu.edu). If you have
questions or concerns regarding your rights as a study participant, or are dissatisﬁed at
any time with any aspect of this study, you may contact—anonymously, if you wish,
Ashir Kumar, M.D., Chair of the University Committee on Research Involving Human
Subjects (UCHRIS) by phone: 517-355-2180, fax: 517-432-4503, email: ucrihs@msu.edu,
or mail: 202 Olds Hall, East Lansing, MI 48824. I appreciate your taking time to
participate.

Katrina Mueller, Master’s candidate

I voluntarily agree to participate in this study date

 

63

 

APPENDIX C

64

 

APPENDIX C

Post-study Summary for Participating Captains

THE ROLE OF A SOCIAL NETWORK IN THE FUNCTIONING OF THE GRAND
HAVEN CHARTER BOAT FISHERY, LAKE MICHIGAN

By Katrina B. Mueller

Project Summary

Evaluation of ﬁshing-related communication between charter captains and ﬁshing
success was performed in cooperation with the charter boat industry in the Grand Haven,
Michigan Harbor during the 2003 ﬁshing season. I used direct observation while on
board charter captain’s boats during charter trips and a survey instrument to ascertain the
dimensions and dynamics of information-sharing subgroups within the charter ﬂeet.
Additionally these identiﬁed subgroups were examined as to their relationship to relative
ﬁshing success as determined by catch.

Key Findings

0 The Grand Haven charter ﬁshing ﬂeet is comprised of four information Sharing
subgroups that differ in regards to ﬁshing success, individual attributes, and
frequency of ﬁshing-related communication

0 Although marina location plays an important role in determining the frequency of and
ease at which charter captains communicate with other captains, communication
reportedly occurs between captains with some history of mutual support and trust,
regardless of docking location.

0 The number of captains with whom a captain communicates is positively related to
ﬁshing success

0 Charter captains with above-average catch (reported and/or observed) generally have
access to informational exchanges with more captains

o In general, access to ﬁshing-related information increases the likelihood of ﬁnding
and catching salmonids for captains within each subgroup.

65

The Grand Haven Information Sharing Network

The diagram (ﬂipside) represents the observed ﬂow of information between Grand Haven
charter captains. Random numbers represent each captain. The distance between
captains represents the frequency at which they exchange information; the Shorter the
line, the more frequent the communication. Similarly, the closer the subgroup, the more
frequent the communication between its members. In Grand Haven, I found that more
ﬁshing-related communication occurs between subgroups D and C than between the
other subgroups and little communication occurs between subgroups A and B. Members
of subgroup A are, on average, the least experienced and have the lowest reported and
observed catch. Charter captains from subgroups A and B are also most geographically
isolated from each other.

 

Information-sharing
Subgroups

Between Subgroup
Communication

Within Subgroup
C ommuni cati on

 

 

 

 

 

66

 

APPENDIX D

67

APPENDIX D

Replication of the 2003 survey instrument

Name:

Boat Name:

Position:

Boat Type/Length:

Species:

Handicap Accessible (Yes/no):

Phone/email:

Date of birth:

Years as a charter captain/mate:

0. Years as a charter ﬁsherman in Grand Haven, MI:

”ioWSP‘SAPP’NI"

11. If applicable, please list your occupation(s) before becoming a charter captain in
Grand Haven (Company/agency name, total years worked, and job title/position).

12. Do you have a source of secondary income during the ﬁshing season? If yes, list
company name/type and % of total yearly income

13. During the off-season, what is your source of primary income (if applicable)?
Company name/type and % of total yearly income:

14. Rank the following as they are most important to you, 1 being most important: Being
a charter ﬁsherman gives me

[ ] personal satisfaction

[ ] social satisfaction

[ ] time to enjoy being outdoors

[ ] money

[ ] Others? Please list

15. Do you have any family members that work as charter captains or mates (yes/no)? If
yes, please list your relationship to them and where they operate

16. Do you have any friends or family members that work in a ﬁeld related to ﬁsheries
(aquaculture, ﬁsheries management, non-proﬁt organizations, goods/sales, tourism
etc) (yes/no)? If yes, please list relationship to them and their ﬁeld.

17. What is the highest level of schooling completed (circle)? 11 years or less, high
school equivalency test, 1-3 years of college, or 4 or more years of college.

68

 

18. If you participate in ﬁshing tournaments, please list by name, location, and
approximate date.

19. I participate in tournaments (yes/no). If yes, rank in order of importance, 1 being the
most important

[ ] To learn about other people’s ﬁshing techniques

[ ] To see how new gear is being used

[ ] for competition

[ ] To socialize

[ ] To talk to ﬁshermen from other ports

[ ] Other, please explain

20. Do you go to trade/ﬁshing shows? Yes/no. If yes, rank in order of importance, 1
being the most important

[ ] Look at new products

[ ] Talk to charter ﬁshermen about new products

[ ] See what other charter ﬁshermen are buying

[ ] To see what other ﬁshermen are buying

[ ] Other, please explain

21. Where do you ﬁnd ﬁshery-related information about regulations, ﬁshery issues, etc.?
Rank all that apply with 1 being the method you use most.

] Membership magazines (please list here)>

] Membership meetings (please list organizations)>

] Word of mouth from other charters in Grand Haven

] Word of mouth from outside this port

] From agency personnel:

] From governmental web pages:

] From attending management agency meetings (please list)>

] Other (please explain)>

F—ﬁr—ﬁPaﬁl—‘qFF—HFHHF-I

22. Are you a member of any non-proﬁt natural resource-related organizations? Yes/no.
If yes, please list:

23. Do you serve on any committees or boards natural resource-related agencies or
organizations (i.e. MCBA, NGOS, etc.) Yes/no. If yes, please list:

69

24.- 27. Check the box that applies

 

Strongly Agree Disagree Strongly
agree disagree

 

I use the latest ﬁshing gear

 

Other charter captains or mates ask me
what gear I am using

 

I am one of the ﬁrst people to try
something new

 

1 seek out current information dealing
with the state of the ﬁshery

 

 

 

 

 

 

 

28. I use the intemet at least [X once a day] [once a week] [once a month] [never]

29. While ﬁshing, I use a cell phone/Nextel (circle) for ﬁshing related conversation at
least [once a day] [2-5 times a day] [5-10 times a day] [more than 10 times] [never]

29b. Radio use per day (see choices in 29)?
30. How long have you owned a Nextel (if applicable)?

31. Rank the following, 1 being the most important in regards to locating ﬁsh while
on a charter .

[ ] cell phone/Nextel

[ ] 2-way radio

[ ] ﬁsh ﬁnder

[ ] observation of other charter boats

[ ] other, please explain: (i.e. experience etc.)

32. On a scale of 1-10 (10 being most important), how important do you think
informational exchanges are to the catch success of you charter? . To
other charters?

33. Do you keep personal logs of your catch and effort in addition to that required by
state? If yes, what data do you collect and how long have you been collecting it?

34. If possible, please ﬁll in the following table.

 

May June July Agust September

 

Total average catch per day in
Grand Haven (2002)

 

Total average catch per day in
Grand Haven (2003)

 

 

 

 

 

 

 

 

70

32. I choose to communicate with other charter ﬁshermen while charter ﬁshing
(SD=strongly disagree, D=disagree, A=Agree, SA=strongly agree)

DA SA

DJ

With whom I have a history of mutual support
Who acknowledge my support

Who act in the best interest of other ﬁshermen
When it is convenient for me to do so

Who are likely to reciprocate

When others expect me to do so

When doing so will directly beneﬁt me

When it is easy for me to do so

When doing so will indirectly beneﬁt me

----~m
NNNNNNNNNU
wwwwwwww
AAAAAAAAA

36. To describe how you feel you ﬁt into the charter ﬁshing culture, mark 1 (strongly
agree); 2(agree); 3(disagree); or 4 (strongly disagree)

[ ] I am relatively solitary and don’t interact much with other charter ﬁshermen at my
dock, marina, or in Grand Haven itself

[ ] I am of average position in the ﬂeet meaning that a lot of other charter ﬁshermen
have a similar frequency of interactions and informational exchanges

[ ] I am central to the network, meaning I have more interactions and informational
exchanges relative to other charter captains

[ ] I interact and communicate with people outside the port than within the port

37. How do you choose whom you give your cell phone number to (ﬁshing-related)?

38. How does ﬁshing related information given out while ﬁshing differ than
communication after-hours?

39. Describe the timing of ﬁshing related communication, i.e. is it given out in a
timely manner or hours aﬂer the fact?

40. Do you think management agencies such as the DNR effectively communicate
with natural resource stakeholders? Please explain:

41. Describe how you feel about local verses distant management of natural
resources, i.e. state/local management agencies verses federal agencies

71

42.

F'r'r'a‘qo ran 999‘s»

A
U)

44.

45.

Rank the importance of information as it iS given to you
number of ﬁsh caught
lure used

Rig
Side of boat that rig/gear is on
Depth of lure/rig
Longitude
Latitude
Depth that other boat is in
Water temperature
Speed of boat
Etc., please list

 

 

 

 

 

 

 

 

 

. Would you be willing to enter your catch report into a computer yourself if a

more thorough report was sent to you in a more timely fashion by the DNR?

Approximately what percentage of your customers return year to year or
multiple times in one year?

With whom do you communicate about ﬁshing-related information in Grand
Haven (ﬁll out table below)?

Name Amount Info Exchange Info is reliable
(please list captains and/or 1=multiple Xs/day 1=I give info 1=SA

mates) 2=lX/day 2=they give info 2=A
3=1X/week 3=we exchange 3=D
4=lX/month info 4=SD

 

72

,, WW L, ,Li, j

 

APPENDIX E

73

APPENDIX E

Replication of On-board Observation Log

Date:

Boat name:

Captain:

1St mate:

Number of customers:

Time of departure:

Weather at time of departure:
Additional comments:

Time Species Location

 

74

Communication/interactions

Observation #:
Time:

Type (communication with or observation of another boat):
Mode: ’
Actors:
Dialogue:

Observation #:
Time:

Type (communication with or observation of another boat):
Mode:
Actors:
Dialogue:

Observation #:
Time:

Type (communication with or observation of another boat):
Mode:
Actors:
Dialogue:

Observation #2
Time:

Type (communication with or observation of another boat):
Mode:
Actors:
Dialogue:

Observation #1
Time:

Type (communication with or observation of another boat):
Mode:
Actors:
Dialogue:

75

 

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