71-31,334 WELSH Jr., James Patrick, 1941PATTERNS OF COMPOSITIONAL VARIATION IN SOME GLACIOFLUVIAL SEDIMENTS IN THE LOWER PENINSULA OF MICHIGAN. Michigan State University, P h .D., 1971 Geology University Microfilms, A XEROXC om pany, Ann Arbor, M ichigan PATTERNS OF COMPOSITIONAL VARIATION IN SOME GLACIOFLUVIAL SEDIMENTS IN THE LOWER PENINSULA OF MICHIGAN By James P. Welsh, Jr. A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Geology- 1971 PLEASE NOTE: Some pages have indistinct print. Filmed as received. UNIVERSITY MICROFILMS. ABSTRACT PATTERNS OP COMPOSITIONAL VARIATION IN SOME GLACIOFLUVIAL SEDIMENTS IN THE LOWER PENINSULA OF MICHIGAN By James P. Welsh, Jr. The lower peninsula of Michigan presents an opportunity to study the relative process intensity and the orientation of vectored components of glaciofluvial sediments. Identification and examination of the patterns of compositional variation displayed by the volume frequency distributions in the pebble size range will provide the necessary information. Analysis of the patterns indicates that, although sedimentary structure and grain size are due to the Wisconsinan glaciations and deglaciations, a considerable amount of the material has apparently been recycled from pre-existing glacial sediments. The possibility exists that, with more detailed work, energy flux and transport cycles associated with earlier glaciations might be deduced by further examination of the pebbles in these Wisconsinan deposits. Furthermore, since the Pleistocene sediments that now mantle the lower peninsula may represent the sum total of past glaciations, the contribution from each event including the Wisconsinan, was probably much less than had been supposed. James P. Welsh, Jr. These conclusions are based on the fact that onlybasic igneous rock fragments present significant variation at the regional- level, whereas most of the other rock types show significance only at the lower levels. Apparently, acid igneous pebhles retain enough strength to be reworked b y a renewed glacial event, but the basic igneous do not persist, More careful examination of the patterns of variation of the basic igneous indicates the outwash in the morainal uplands i s more mature than in the drainage ways. This is probably due to the fact that the transport of pebbles to the morainal areas was limited in time, whereas a constant influx of fresh material was available to the deep cutting spillways, particularly from the Saginaw lobe morainal area, Significant differences for the basic igneous between upland pits closest to the Saginaw lobe moraines suggest that the moraines were probable sources of the upland material. At the pit level only three pits show significance for all rock types indicating a fine scale of variation which is approximately the distance between pits. Significance for homogeneous structural units within pits further corroborates this fine scale of variation. This is probably due to varying numbers of cycles of erosion and deposition at this local scale. ACKNOWLEDGMENTS I extend my appreciation and thanks to the following people: Dr. Robert Ehrlich, Mrs# Mary Welsh, Mrs, Mary G-annon, Mr. and Mrs, James P. Welsh, Sr., Dr, Abner Blackman, Miss Judith Welsh, Miss Linda Capps, Dr, Thomas Vogel, Dr. Harold Stone house, Dr. Hugh Bennet, Dr, Harold Winters, and the United States Navy. ii TABLE OP CONTENTS Introduction. Page 1 ....... Regional Setting............................... 2 Previous Work.».«•••••••••••.••«••••••••••••••• 5 Discussion of the Problem.....so.o.••••«•«..a*. 11 Experimental Design.................s.......... 1J+ Sampling F l a n I S Generation of D a t a ............................. 20 Analysis........................... ..........o. 2*7 Results........................................ 37 Introduction.............................. 37 Super Clusters............................ 38 Spillways versus nonspillways••••••••••• 39 Between spillways....................... 1+6 Within the major spillway. ..... 2+6 Nonspillway Super Clusters. ........ 1+7 Summary at the Super Cluster level.«.... 1+8 Introduction to remainder of Hierarchy.... 1+8 Clusters within Super C l u s t e r s . . 1+9 Pits within Clusters within Super Clusters 1+9 HSU»s within Pits within Clusters within Super Clusters•••••••»•••••••••••••••••.•• 5>0 iii Conclusions•••••••••••..... ••••••••••••••••••••••« $1 Bibliography....................... •••.•••••••••••. 514- Appendix A, Cross Reference for the hierarchy,...• 57 Appendix B, F values at each level plus the breakdowns ••••••••••.•«. . . 59 Appendix C , Original contingency tables••••••••••• 70 Appendix D, Detailed discussion at Pit level...... 90 Appendix E, Detailed discussion at HSU level...... 91+ iv LIST OP TABLES Table 1. Page Location of Pits by Township, range and section..•••.••..... ••••••.••••••••••• 21 2. Total variation for limestone category.*.. 30 3. Statistical summary for all levels of the design. ...... 4. Orthogonal breakdown at the Super Cluster level for the basic igneous category.....• 34 5. Summary for breakdown between Pits...«•••• 35 6. Summary for breakdown between HSU*s....... 36 7. Size frequency distributions, basic igneous 42 8. Skewness values for the basic igneous category at the Super Cluster level....... 1+4 Skewness values at the Fit level. 44 10. Skewness values at the HSU level 95 Bl, P values for limestone, all levels. ...... 59 B2. P values for weak sediments, all levels... 59 B3• P 60 B4. P values for acid igneous, all levels..... B5. P B6 . P values for foliated metamorphic, all levels a . . . . . . . ......... 61 B7. P values for limestone, between pits...... 62 B 8. P values for weak sediments, between pits. 62 B9. P values for quartzose, between pits...... 63 9. values values for for quartzose, all levels 60 basic igneous, all levels..««61 v LIST OP TABLES cont. BIO, F values for acid igneous* between pits.*, 63 BIX* F values for foliated metamorphic, between pits,,* ..... • 6I4. F values for weak sediments* between H S U 1 .......... 65 F values for quartzose* between HSU*s,• • •« 66 B12, B13. for acid igneous* between HSU'So, 67 Blfp* F values for basic igneous* between H S U ‘s. 68 Bl6 » F values for foliated metamorphic* between HSU 'S. . o •o............. 69 Bll|., F values Cl, Total variation* limestone.............. 72 C2 , Limestone HSU® S 73 C3« Limestone Fits•• •......... . a o .8 o a © a a o e . e ® a e o . o . 0 ® ®a e® Cl}., Limestone Clusters,..,,,.,,,,,,,...... Limestone Super Clusters,,,,,,,,,,..,,..., 74 74 70 C 6 , Total variation* weak sediments 75 C7. 76 lileak sediments HSU's,,,,,,,...... C 8 , Weak sediments Fits,,,,,,,........... 77 C9» Weak sediments Clusters,.,,,............... 77 CIO, Weak sediments* Super Clusters••*•••.*•••* 70 Cll, Total variation* Quartzose,,,,,,,,.,,..... 78 C12, Quartzose HSU's,,,,,,,,..... 79 C13* Quartzose Fits............ 80 Cll+, Quartzose Clusters,,,,,,,,,,,,,,,,.,,..... 80 Cl5, Quartzose Super Clusters,,,,,,,,,,,,,,,.., 70 Cl 6 , Total variation, Acid igneous.•• vi 81 LIST OP TABLES cont. Acid igneous, H S U 1s.•••••••••••••••••••• 82 Acid igneous, Fits 83 Acid igneous, Clusters•••••••••••«••••.• 83 Acid igneous, Super clusters•••••••••••• 71 Total variation, Basic igneous.®....... • 84 Basic igneous, HSU's.................... 85 Basic igneous, Fits..................... 86 Basic igneous, Clusters................. 86 Basic igneous, Super Clusters«•••••••••• 71 Total variation, Foliated metamorphic... 87 Foliated metamorphic, HSU's. 88 ••••••• Foliated metamorphic, Pits. ......... . 88 Foliated metamorphic, Clusters......... 89 Foliated metamorphic, Super Clusters.... 89 / vii LIST OP FIGURES Figure 1. 2. 3. Page Adapted surface feature map of the ...... study area 14- Relationship of the various levels of the hierarchy. ....... 18 Ranking of relative resistance....... 23 ij.. Reference for geographic location within the various levels of the design. ...... viii 1+0 INTRODUCTION The lower peninsula of Michigan presents an opportunity to study the relative levels of process intensity from patterns of compositional variation within glaciofluvial sediments® The area provides an excellent opportunity for the studies of this type because of the geographic location* the good preservation of surface features by continental glacial events and the variety of source terrains within and adjacent to the area. The lower peninsula provides an essentially closed system bounded on three sides by a lowland channel now occupied by the Great Lakes, The multiple glaciations have moved onto the peninsular platform from the bounding troughs and drainage during deglaciation was controlled by these marginal low areas. The Great Lakes region including Michigan contains the clearest record of deglaciation in North America (Flint* 1957)® The well preserved surface features provide qualitative evidence for determining the glacial history of the area, Geomorphological reconstructions of this record are not complete enough to shed light on the detailed nature of the process history of the region that has been impressed upon the resulting glacial sediments. In particular, the degree to which glacial sediment 1 characteristics represent a palimpsest with the record of the last glaciation-deglaciation cycle impressed over the earlier ones has never been evaluated* The object of this thesis is then to use patterns of compositional variation within the Pleistocene sediment as a means of adding to our knowledge of the nature of glaciation and deglaciation that has occurred in the lower peninsula of Michigan,, It is hoped that the results of this study will be general enough to serve as a tool for use in other glaciated regions® This research is directed toward determination of sedimentological patterns and not toward establishment or corroboration of stratigraphic concepts within Michigan or other midwestern area® REGIONAL SETTING It is generally agreed that the lower peninsula of Michigan is veneered by Wisconsin age material® (Leverett and Taylor, 1915* Hough 1958, Wayne and Zumberge, 1965, Dorr and Eschman, 1970)® Leverett described numerous surface features of glacial origin, including the major morainic systems and the Grand River spillway® Certain of these features identified by Leverett have withstood the test of time very well® Prominent among these are the drainage ways which are expressed as sand and gravel filled valleys now containing obviously underfit streams which once served as conduits for glacial melt water. 3 The most prominent of these drainage ways is the old Grand river spillway (Leverett, 1915) shown in Figure 1. The spillway apparently headed near Imlay when it served as a conduit from middle Lake Maumee to Lake Chicago approximately li4.,000 years ago (Kelley and Farrand, 1967)• As the retreat continued the spillway head changed to a location farther north near Ubly. The spillway then served as a conduit from Lake Whittlesey through Lake Saginaw and then through essentially the same channel to Lake Chicago about 12,500 years ago (Kelley and Farrand, 1967)® In addition, the lower peninsula probably contains many minor spillways* a few have been identified* At present only One used in this study is located in the southern part of Clinton county (Figure 1), The drainage ways are bounded by topographic highs (moraines). The detailed internal composition of these is not yet known. However, from limited field observations they seem to be essentially sand and gravel with subordinate amounts of till. Sediments in these features were probably not subjected to the final paroxysm of energy flux that affected sediments in the drainage ways. From field work and discussion with present day investigators it is clear that these upland areas deserve investigation and reevaluation in terms of composition, genesis and even relative age. It is beyond the scope of this thesis and hence presumptious for this k -------- Selected moraines indicating marginal positions of the Saginaw lobe Grand River Spillway Minor Spillway 40 MILES Figure 1. Adapted Surface Feature Map of the Study Area after Flint, et. al. (1959). 5 author at this time to discuss these areas in any more detailo The results of this thesis will contribute a small increment toward developing a new model® PREVIOUS WORK The general character of glaciofluvial sediments has been considered by a number of workers (Anderson 195>8> Oldale 1967)* The general objectives have been to determine when, from where, and in what manner they came® Previous workers have provided a general framework which will serve as a basis for more detailed questions concerning glaciofluvial sediments® USGS Monograph 53 (Leverett and Taylor, 1915) is a report of the investigations of the glacial history of Michigan and Indiana® The maps of glacial geology included in this report contribute the major part of the present map of surface formations of Michigan. The overall contribution of Leverett to the understanding of the general glacial geology of Michigan has not been equaled to this day. Leverett described numerous surface features of glacial origin, including the major morainic systems, the Grand River spillway associated with the drainage of glacially supplied water, identification of beach features associated with past proglacial lake levels, and further indicated the major lithologic varieties present. The precision of the surface formation map of the lower peninsula of Michigan (H.M. Martin, 1955) based on 6 Leverett is somewhat in doubt by a number of scholars (Winters, 1969), however, it is sufficiently precise for this study as it is only used for general reference. Figure 1 is an adapted surface feature map of the study area after Flint et al (1959)® An extensive compilation of the geologic knowledge concerning the Great Lakes region is provided by Hough (1958)® He is, however, mainly concerned with the evolution of the great lakes basins. In addition to the above, numerous maps that illustrate the boundaries of Wisconsin stage drift (pg® 7 ), the theoretical preglacial drainage (pg, 7 ), the principal morainic systems (pp, 8 and 9 ) and the principal stages in the evolution of the Great Lakes (inside front and rear cover) can be found in Kelley and Farrand (1967). Only one reference in the literature specifically directs itself to the problem of process intensity in glaciofluvial sediments and that is by Ehrlich and Davis (1968), Their effort was concentrated on a small-scale area adjacent to an active ice front. This study is one of the first to take into account the problem of using number frequency where volume frequency is more appropriate. They demonstrated that the variation in size (volume) frequency distribution by compositions provided a measurement of change in process intensity. Following their lead this study concentrates on an area of intermediate scale, a few orders of magnitude larger and not adjacent to an active ice front. Although in many instances we may be unable to determine the entire genetic history of a sediment, the effects of certain events tend to be progressive or additive. For instance, once particles that are either chemically or physically unstable leave their source terrain they can only suffer degradation not reconstruc­ tion, Therefore evaluation by careful sampling and careful choice of detrital species one can compare one sample with another with respect to the total amount of physical and chemical degradation the samples have endured. If we consider the degradation to be principally physical, such as result from the hydro­ dynamics of glaciofluvial events, then we might consider a sample rich in physically and chemically resistant detrital species to have undergone a greater total process intensity, all other effects being held constant by design or extracted mathematically. Thus, as used in this thesis "process intensity" is defined to mean the relative amount of degradation experienced by the detrital particles in the glaciofluvial environment. At this time we must talk in terns of relative rather than absolute process intensity. This process intensity may or may not exhibit a uniform pattern of variation. That is, the differences 8 in process intensity might reflect purely local vagaries of depositional environments. However, it is possible in Michigan, knowing the source of the melt waters and the direction to the source of the sediments, that the effects on the sediments as they are acted upon may indicate a regional pattern imposed on the local patterns. Such a pattern representing a "progressive cleaning up of the sediment" could be represented by a vector pointing away from the areas of less process intensity to areas of greater process intensity. In a study such as this xi/hich is restricted by accessibility of proper sampling sites and other considerations, it is possible only to establish the presence or absence of vectors rather than the entire field of variation. There have been a number of investigators who have addressed the general problems of vectored properties in glaciofluvial sediments (Krumbein and Lielblein, 1956, Anderson, 1958* Oldale, 1967)* These studies have considered the areal distribution of rock types without respect to a specific known source. However, based on additional information, a general source area is usually indicated prior to the study. The use of largest particles (Krumbein and Lielblein, 1956) must account for the fact that the nature of the largest particle is a function of hoxtf long and how far one looks, thus the nature of the underlying 9 population is difficult to deduce. The use of pebble counts (Anderson, 1958# Oldale, 1967) to ascertain relative proportion of lithologic types have limited usefulness due to the bias arising from the use of number frequency where volume frequency would be more appropriate (Griffiths, 1967)0 An additional area which would provide background is that which concerns stream transport of detrital particles. The work of Plumley (19i+8) on the Black Hills terrace gravel is one of the more exhaustive accounts concerning the effects of energy on sedimentary particles of various compositions during transport in natural streams. Plumley suggests that size reduction of pebble size material in streams is effected by two processes: (1) selective transport and (2) abrasion and breakage. By dividing the lithologic species into two groups (1) hard rocks (chert, quartz, quartzite) and (2) soft rocks (sandstone, limestone, metamorphics), Plumley wa3 able to assess the role of abrasion and breakage versus selective transport. He found that in a distance of 30 miles the volume of soft rocks decreased from 60$ to 10$. Plumley concludes (19i|8): (1) initial lithologic frequency distribution is directly related to the source area; (2) short distance stream transport removes most soft rock lithologies by abrasion and breakage; (3 ) loss of the soft rocks during transport is a function of rigor 10 of transport and size and composition of associated particles; (1+) decrease in mean size results from decreasing competence of the stream as the gradient decreases; (5) skewness of the size distribution decreases with distance of transport; and (6) the standard deviation or sorting shows no systematic change with distance of transport. Although this represents a major contribution to understanding the attrition of elastics, some of his conclusions should be accepted with caution. Plumley maintains that the choice of an appropriate sample was limited by the nature of the deposits and their exposures. The material being sampled was cemented in varying degrees by calcium carbonate. In addition, as a result of practical considerations the available population for samp­ ling was limited. Possibly of far more importance he was only able to obtain channel samples which, of course, would not allow assessment of variation to the degree offered by sedimentation unit sampling (Otto, 1938, Apfel, 1938, Ehrlich, 196ij.). The advantage of sedimentation unit sampling is that the variation within the unit ideally is of common origin. This is not necessarily true where the sample taken incorporates a number of units (a channel sample). In the latter case the variation can be attributed to many more unknown circumstances concerning the evolution of the sampled sediment. Thus the nature 11 of the deposit (consolidated by cementation) and the inability to assess the constituent components of variation within a channel sample are the main reasons for cautious consideration of the conclusions, Plumley*s conclusions suggest criteria for interpretation that are useful in this study. The assumption of the relative importance of abrasion relative to chemical weathering should be considered since the pebble fraction "in transport" spends the majority of time immobile according to the vagaries of the seasons and patterns of local turbulence® Notwithstanding this objection it seems reasonable that the larger particles are vulnerable to abrasion causing loss of the coarse tail of the distribution thus explaining the observed skewness variation. Both Ehrlich and Davis (1968) and Plumley (19I4.8 ) selected the scale and the place to test an analytical tool whereas this thesis will use this research approach to solve a problem. Because this considers a much larger scale than the Ehrlich and Davis (1968) study the precision of the results is lower. However, the tradeoff in precision is justified because formulation of needed models requires information at the larger scale, DISCUSSION OP THE PROBLEM There have been few unambiguous studies concerning quantitative patterns of detrital species within Pleistocene sediments. In order to minimize readily 12 apparent sources of ambiguity, it is necessary to characterize each detrital particle in terms of at least three parameters; species, volume, and aggregate volumetric proportion of that species to other species through volume classes* Sediment is a product of both source and process. The less the source material is affected by the processes of erosion, transportation or deposition the less these materials will reflect these processes. As process acts more on the source material in terms of intensity and duration the less accurately will the source be mirrored and, concomitantly, the more accurately will the processes be reflected. Most sediments bear to a lesser or a greater degree both information on source and process. Determination of the relative proportion partitioned between source and process is the purpose of this thesis. In the present instance the source terrain for most of the compositions lies beyond the area of study, particularly for contributions during the Wisconsinan xtfhich would have come mainly from north of Lake Huron (Canada). After transport from the source terrain each rock type is affected more or less according to its chemical and physical stability. Precise distinctions based on resistance to chemical and physical change are not practical except in a relative sense, mainly because most often the substance 13 being considered (especially in the pebble size range) is polyraineralic. Even in the case of a monomineralic specimen it is not often straightforward because the result of mechanical and chemical stresses may exhibit wide variations. However, we do know some general durability characteristics such as hardness and relative chemical stability in various environments (G-oldich, 1938)* This will be discussed further in the section on generation of data. Recognizing that the appearance or disappearance of more or less resistant species can give us a clue to widespread energy flux patterns it must be made clear that without the concomitant determination of volume of each clast and the aggregate volume of clasts by species the results will be ambiguous. This approach solves the problem of using number frequency (pebble counts) where volume frequency is more appropriate (Griffiths, 1967). The identified pattern will, assuming valid sampling, allow interpretation of an unique cause or a small number of causes. Detailed discussion of the sampling plan will be found below. Based on the above discussions this investigation relies on a number of assumptions. These are: (1) glaciofluvial sediments undergo change during transporta­ tion and deposition; (2) these changes are reflected as Ik patterns of compositional variation; (3) detrital species can be classified according to their relative chemical and mechanical resistance. For example if one particle each of two rock types of equal volumes, one soft and one hard, are placed in a glaciofluvial environment, after a time the weaker will be volumetrically diminished compared to the stronger. On a pebble count basis the above situation would result in both pebbles being present in equal. Thus the volume proportion of detrital particles ranked according to relative resistance is an indicator of relative process intensity. The objective thus is to identify and study the pattern of variation displayed by the volume frequency distributions for various compositions in the pebble size range. Particles in the pebble range were studied because they offer the greatest spectrum of compositional diversity and can be examined with relative ease. EXPERIMENTAL DESIGN In order to identify the pattern of variation a strategy which will allow assessment of changes due to the processes and estimation of vectored components is needed. This necessitates the use of a design which is multilevel and geometrically sensitive. Sensitivity is considered as the ability to determine with adequate precision the directional relationships of the 15 properties of the glaciofluvial sediments. The multi­ level aspect is required to obtain an estimate of the regional and local scale variability. The geometric array must be positioned so that the directions indicated by other means can be tested. For instance, observations in an established glacial spillway and observations (not in but) adjacent to the spillway yield information on direction when an appropriate geometric array is used. By using a hierarchical design, different scales of variation can be examined. This might be referred to as partitioning the array into smaller component arrays so that the contribution of local variation to regional patterns can be assessed. The results obtained from such a design can be evaluated in a way which considers local scale variation progressing to regional scale variation on the basis of the size frequency distributions by composition. SAMPLING PLAN The sampling plan must fit the design so that the desired objective can be attained. The ideal situation would be to obtain samples from an array of locations so that patterns which intersect or reside within the array could be detected efficiently. The objective of the sampling plan is to provide adequate coverage of the area of interest so that any ordered (non random) pattern can I 16 be detected. The population to be sampled is defined as glaciofluvial sediments in the size range lee to in mid-Michigan. c The available population for sampling is restricted to sand and gravel pits as a result of cost considerations. All accessible sand and gravel pits in the area were visited, approximately 100 individual pits. Of these pits over three-fourths were unavailable for sampling for the following reasons: overgrown; trespassing; (2) flooded; (1) completely (3) all walls slumped; (i|) no and (5) only available exposure unsafe due to possible caving. The remaining 22 pits were sampled in the following manner: The gross vertical and horizontal variation in the field was qualitatively evaluated and based on this estimate and personal field judgment individual samples were taken. Conscious effort was expended in assuring that each sample was truly representative of all the material from which it was taken. As is always the case due to problems encountered in the field it was not feasible to adhere to a strict probability sampling plan as is described by Krumbein and Graybill (1965). However, as will be seen in the results below departure from the ideal has not seriously jeopardized the results of this study. However, as will be seen, departure from a balanced design has injected 17 some ambiguity. In the area of interest two glacial spillways are present (based on field evidence) one major (Old Grand River Spillway) and one minor located south of and relatively parallel to the Old Grand River Spillway (Leverett and Taylor, 1915)* The spillways can be considered as locations of considerable energy flux. Compositional gradients will exist along their length if sediments introduced near their head are progressively acted on. However, this contains an implicit, probably unrealistic, assumption that a major portion of the material is contributed at the head of the system with little addition along the way. Proper sampling along these spillways should enable us to choose between these two possibilities. The direction of transport in the spillways was determined to be essentially from the east to west and the more northerly spillway to be active in more recent time (Leverett and Taylor, 1915)* The region may be characterized by defining two qualitatively different terrains, drainage ways and non-drainage ways. This constitutes the top level of the hierarchical design (Figure 2). This top level compares drainage ways with non-drainage ways. In order to assess the variability within each terrain we must examine the variation at the super clusters level. Next we can assess TERRAINS SPILLWAY NON SPILLWAY SUPER CLUSTER SUPER CLUSTER CLUSTER CLUSTER PIT PIT HSU HSU SAMPLE SAMPLE Figure 2. Relationship Of The Various Levels Of The Hierarchy 19 the variation between super clusters within each terrain. Continuing down the hierarchical ladder we are able to assess the variation within the super clusters or the between cluster variation. Each step allows estimation of the variation at a smaller, geographic scale thus reducing the generality of the results obtained. Further reduction provides an estimate of the within cluster or between pit variation. Next in the hierarchical arrangement we can look at the within pit or between homogeneous structural unit (HSU) variation. Finally we are, at the most local (smallest) scale in this investigation, looking at the within HSU or between sample variation. Further breakdown at each level of this design is possible if a statistically significant result is obtained. This technique, an orthogonal breakdown, provides a method for identifying where in the level the significant differences reside. Application of this technique will be found at the super cluster level for the basic igneous category discussed in the results. Each sampled unit here defined as a field observed ’’homogeneous structural unit" (HSU) Otto (1938) s Apfel (1938) and Ehrlich (1981}.), consisted of two samples in standard volume (lOOOcc) containers level filled with pebbles in the size range lcc to i}5cc. The two samples were taken only from within the boundaries of the HSU. 20 These two samples permit estimation of the within HSU variation. In each sand and gravel pit one or more HSU's might be sampled thus allowing estimation of between HSU variation and within pit variation. The variation between pits which are not very far apart provides an estimate of between pit variation and a within cluster variation. The variation between clusters and a within super clusters can also be estimated. In addition the variation between super clusters can be assessed which provides an estimate of the between super cluster within terrain variation. Further the between terrain variation can be ascertained completing the hierarchical design. The location of the pits by township, range and quarter section is given in Table 1. The relationship of the various levels in the hierarchy is illustrated in Figure 2. A cross reference by number is provided in Appendix A. GENERATION OF DATA Pebbles between lcc and l±% cc were evaluated. The size is considered on an individual "grain" or particle basis as the water displacement volume of the particle. The composition is identified on an individual particle basis and assigned to a rock type. Each sample was washed and each particle identified and allocated to a compositional category, then, each 21 Table 1 - Location Of Pits By Township, Range And Section Pit Number 1 2 3 b 5 6 7 8 9 10 11 12 13 lb 15 16 17 18 19 20 21 22 Township T T T T T T T T T T T T T T T T T T T T T T 7 N 5N 5N 5N 5N 5N 5N 7 N 8 N 8 N 8 N 8 N 8 N 7 N 7 N 8 N 8 N 5N b N 9 N 7 N 2 S Range Section R R R R R R R R R R R R R R R R R R R R R R SE, SE 9 S^g, NE, 16 SE, NW, 8 NE, SW, 6 NW, SW, 17 NW, 7 SE, NE, SE, 12 SE, SE, 11 SE, NW, 22 NW, 31 CNL, Sis, 31 NE, NW, 36 NW, SE, 25 CNL, 31 SE, NE, 31 SW, NE. 7 SW, 11 NE, NE, NE, 19 CNL, NW, 35 NW, SW, 15 Eis, 32 CWL, 12 5 W b W zi W b w 3 2 3 1 1 W W w W w 1w 1w 2 W 2 W 3 w 3 w 3 w Ij. w 5 w 2 W 11 E 12 W 2 E 22 identified particle was placed in a graduated cylinder and its volume measured by water displacement to plus or minus lcc. This data was generated for all particles in each sample for all samples. It is assumed that rock types broadly similar in composition and texture have similar resistance to communition. This assumption allows grouping of similar rock types into general compositional categories. These categories can be ranked as having low, intermediate or high resistance to mechanical and chemical breakdown. Figure 3 shows such a ranking for the compositions identified in this study. Based on the ranking and the above assumption, the rock types can be combined and placed in six general categories® These categories are: (1) limestone, (2) acid igneous, (3) basic igneous, (Ij.) foliated metamorphic, (5) weak sediments and (6) quartzose. LIMESTONE The limestone category consists of limestone and dolomite. Three slightly different varieties of limestone were encountered. Correlation of any of the limestone pebbles to the parent formation is not attempted, however, some suggestions are offered. Examples containing fossils such as chain and honeycomb corals may have been derived from the Manistique Dolomite which crops out in an arc across the southern part of the upper peninsula. MECHANICAL RESISTANCE Low Intermediate High Quartz Quartzite Chert Sandstone Quartz conglomerate Granite gneiss Granite Rhyolite Granodiorite Dolomite Greywacke Shale Siltstone Coal Limestone Gabbro Diorite Basalt Quartz-biotite schist Quartz-biotite, muscovite schist Figure 3. Ranking Of Relative Resistance 2k Examples that suggest the Traverse Limestone are based on the occurrence of pebbles containing the colonial coral Hexagonaria, often called "Petoskey" stone. The Traverse Limestone forms a wide belt below the drift in the northern part of the lower peninsula. Some samples contained pebbles of a cherty limestone breccias these are probably from the Mackinaw City, St, Ignace and Mackinac Island region* however, positive correlation is not made. It is a reasonable assumption that most of the limestone is not far traveled as ample local source is available. ACID IGNEOUS The acid igneous category consists of granite, granodiorite, rhyolite and granite gneiss. Although all of these are not igneous they will be considered together as they are similar enough in their properties for this study. Rhyolite occurred in very few samples (59 and 60, HSU 3 0)| the source is probably from north of Lake Huron. Granodiorite and granite are present in a number of different varieties. Some of the granite probably derived from the upper peninsula of Michigan, the rest from Canada. Neither granite nor other igneous and metamorphic rock types occur in the lower peninsula as bedrock. 25 BASIC IGNEOUS The basic igneous category consists of gabbro, diorite and basalt. Diorite has not been found as bedrock in Michigan, thus, its source is probably Canada. Gabbro and basalt both are found in outcrop in the upper peninsula and are most likely derived from there and Canada. FOLIATED METAMORPHIC The foliated metamorphic category consists of a quartz-biotite gneiss and quartz-biotite-muscovite schist. Both compositions are considered to be from the upper peninsula and Canada. Schist is the most common meta­ morphic rock type in the western half of the upper peninsula and is also common on the north shore of Lake Huron• WEAK SEDIMENTS The weak sediments category is made up of shale, sandstone, coal, siltstone, quartz conglomerate and greywacke. No attempt was made to ascertain which formation a particular sedimentary rock fragment came from, however, in some instances, a general suggestion is offered. The important thing is that all of the above are probably locally derived with the exception of the greywacke which may have come from a few areas in the western part of the upper peninsula. In the lower peninsula. It does not occur 26 It is possible that a few samples contain representatives of the Jacobsville sandstone which occurs in the upper peninsula as a distinctly red sandstone and was identified in very small amounts in a few samples. The only other possible specific sandstone identification may be from a few samples which contained a mottled variety ranging in color from brown to yellow to red and purple which fits the description of the Ionia sandstone. This is most definitely a local derivative as it occurs in outcrops along the Grand River valley and in the vicinity of Ionia and Grand Ledge. The coal and shale which are very sparse are probably from more northern subcrops of the Goal Measure shales of the Saginaw Sandstone which are exposed in the vicinity of Grand Ledge, Jackson, Corunna and Williamston. The quartz conglomerate may be from the Marshall sandstone (Huron County), however, a positive correlation is not made. QUARTZOSE The quartzose category consists of quartz, chert and quartzite. The quartz may be from the pegmatites or quartz veins of the upper peninsula, however, a definite correlation is not made. Possible source of the chert is from the chert beds which underlie the Bayport Limestone in Arenac County. Quartzite is a common rock in the iron ranges area of the upper peninsula and probably the specimens found in the study area are derived from there. 27 Each of the above categories is considered as a composition for analysis. The data is then reduced on a compositional basis for each sample. The resultant data is in the form of size frequency distributions by composition. The reduction makes use of five cubic centimeter classes. Particles larger than lj.5>cc were purposely excluded in the samples. The data in this form was submitted for analysis. This censored distribution is suitable because with overall reduction in size when particles get so small that they fall out the larger particles will fall into the range of the distribution. ANALYSIS The object of the analysis and of this thesis is to identify the pattern of variation displayed by the size frequency distribution for various compositions throughout the study area and also to determine if these patterns of variation can be used to better understand the general process of glaciofluvial accumulation. The appropriate statistical analysis to achieve the objective must provide for comparison of the size frequency distributions for each compositional category at the local and regional levels and estimation of the variation at those levels. 28 The analysis must be compatable with the sampling plan and the nature of the data. The sampling plan is a nested or hierarchical type and the data is essentially enumeration. In addition the large amount of data requires an economical means of analysis. This type of data in the hierarchical arrangement is most suitably portrayed and analyzed in contingency tables® Contingency tables provide a convenient way of displaying data which considers a number of criteria which have been divided into classes. The statistical objective is to determine if two or more properties are manifested independently. Thus a statistical test which tests independence for enumeration data is appropriate. The G-test (Sokal and Rohlf, 1969), is chosen because it uses enumerative data arranged in contingency tables. The G— statistic provides a closer approximation to the chi-square distribution than the traditional chisquare statistic. The G-test is computationally simpler for tests of independence. (Sokal and Rohlf, 1969). The statistical analysis answers the following questions. Does a pattern of variation exist and, if so, at which level or levels does it reside? Figure 2 illustrates the hierarchical arrangement. The lowest level is the individual sample, the next higher level is the HSU; then the pit; cluster complete the arrangement. cluster and super 29 The components of variation arising at each level are shown by the familiar analysis of variance table. Source of Variation Super Clusters (SC) Components of Variation S + H + P + C + SC Clusters (C) S + H + P + C Pit (P) S + H + P HSU (H) S + H Samples (S) S Using the G-test it is possible to compute a G-statistic which is an estimate of the total variation. G-statistics are computed for each level of the design obtaining an estimate of the variation at each level and identifying where in the design significant difference resides. One definite advantage with this form of analysis is that if there is significance at a lower level it does not require significance at successively higher levels. The G-statistic is computed by the following relationship: G = 2 [(^f In f for the cell frequencies) (STf In f for the row and column totals) + (n In n)J Where G is the statistic, f is the individual cell frequency, In is the natural logarithm and n is the grand total. The G-statistic which estimates the total variation is based on the size frequency distribution for all samples for one composition at a time. Table 2 is an 30 TABLE 2. TOTAL VARIATION FOR LIMESTONE CATEGORY V o I k * o O] 1 - 5 6 - J O JJ ■ " ’ ~ Si" ' 5 8 9 5 ..... 46 65 - - - - "14 0 58 130 42 ioa 1 4 5 4 1 --89" 105 58 197 19 115 56 14 0 ---- “ 1 5 8 84" 62 122 - - - - - - 194 50 77 125 ----- 127 . 123' 76 161 - - - - - - 241' “ ' 6 9 40 6 - - - - - ...1 6fl9 o - 1 5 1 6 - 2 0 2 J - 2 5 2 6 - 3 0 31-35* 3 6 - 4 0 4 J - 4 5 n 0 U 0 54 60 25 0 0 0 25 60 30 40 0 45 "72 0 5 20 0 0 45 0 0 45 57 0 0 6 25 0 (1 1 5 " " 44 n 0 0 15 0 0 0 Cl • "ff 0 60 . 40 0 0 0 0 0 ' 0 0 0 0 g 35 0 0 12 0 0 0 0 p 39 2(1 0jj— 30 V ' 0 0 0 12 20 n 60 0 0 0 66 0 'rr " 0 0 0 12 0 0 0 35 30 0 0 0 15 <5 0 0 43 ' 0 25 0 0 0 15 20 0 0 • 0 “ 0— ' 39 ^ 0 "o' 0. o' " 2 5 " 0 0 0 0 25 © 0 - 25 • ‘ 2 9 "' ' 66 45 0 " - 33"*-- ~ o 40 35 56 63 97 0 0 0 20 ~~ l6(J '"S' 49 0 0 0 0 40 0 0 0 0 27 25 0 60 193 4(1 "0 - - - - - - 1 4 4 .... 0 3 0" ” 6 ... -45 — ' '20' 0 p 0 0 0 177 30 117 0Q 20 - - - - - - 1 0 4 ■ - 4 5 '" 3 0 " " 4 0 '“ 0". . 0 "~3Q" 0 0 98 0 . 0 0 6D D 71 fio 0 . . . . . 9 4 . . 8 8 ' 4 5 ' 20' 0 ' -6“ "n 0 0 49 0 c 0 0 25 176 D - - - l i r .. 36' u 0 0 25 0 20 0 0 30 0 1 6 9 .... 6 2 .. 2 7 0 0 - - - - - - 231 0 . - "O' ' •0 • 0 0 0 0 0 0 0 0 • 175 0 0 42 f1 i2 7 _ ~ fi­ 0 0 46 " "'55 ' ' 5 C 0 .. . . 7 3 ll 0 0 0 20 1 3 1 .... 58 2j . .. 3 0 0 0 - "' 3 0 ' ' ' — a— — n - - - - - - 3 0 3. G " 24 "58' n 55 0 0 0 2 1 - 225~ 5 .325 78 • 5 4 ' 42 - 4 1 - - - - - - 90 ■. 0 •' - - 33— — 0— 0 0 70 0 83 15 25 116 0 60 11 40 0 - ' 0" ' C " .. . . 1 1 5 114 " 114 "50 40 54 0 0 72 0 ...... 0fi_ 60 91 0 - - - - - - 13 3 ' T 0 100 “ 54 — ' 40 ' ' " 2 5 “ 0 54 0 2 5Q 0 0 152 50 20 c — ■•20 2 - 8 6 ~ 2 J " ” 2 0 fl'"'""".O' — 0— 0 35 27 38 0 104 0 73 0 - - .- - l 3 9 ' 3 3 " 2 7 — D ‘ V 20 — 2 5 " .. '0" 0 P 29 171 45 23 0 0 Dn-. . _ tf- - - - - - - 173 “ 10 2 " — 0 ~~'0 0 '2tf 0 0 0 0 136 0 0 0 0 19 0 ~ " O' - - - - - I l l - 54- ■ 1 2 ' 4 0 " . . 0 Tl " ■ 0 n 15 59 25 0 60 0 ..... 00 70 ■ 0 7 6 " 30 - --- 132 fl - 25 “ ” " 0 "■ p 0 143 37 0" — 3 5()- - _ _ 0— 0. 38 42 0-— 0 ' " - - - - - 1 0 6 ■ -7i - 2 7 4 6 .. 4 7" r. 0 57 c ■ .114 15 0 n 0 ------ 1 37 44 n .. 0""- — 0 G 54 6 ■" 2 5 '“ ... 0 0 0 30 0 0 0 0 0 71 0 TST"" 0 2 21 25 12 18 51 - - - - ,.-1 58 22 15 " 0 0 101 15 25 90 0 39 0 108' — 6 4 “ “ ■ 1 5 '" 4 0 30 0 2.05 61 6 ------ 204 " 1 1 9 15' 0 20 1 75 2 f) 0 65 145 ----- 143 2 7 *" n - " 4 / 158" " t r -• 9 4 2 2 : 9 6 1 3 f o r 't o t a i " " s (:Y 0 0 0 0 0 0 0 0 p n 0 0 0 p — p" 0 "C 0 0 ' 0 0 ■ Q 0 0 0 0 * 31 example of the contingency table which contains the total variation. Thus there is a total G for each composition. Next the two samples in each HSU are combined and a new G-statistic is computed. This estimate contains the variation due to the HSU and the individual samples. This procedure is repeated at each successive level of the design. Then the separate G values for each level for one composition may be subtracted from the next higher level resulting in an estimate of the variation due to that level. The resulting values are the estimates of the variation arising at each individual level. These values are divided by the appropriate degrees of freedom and the resulting value treated as the variance for the individual level. Levels which show significant differences can be broken down into comparisons within that level. This allows identifica­ tion of the significant set or sets for that level. Breakdown at the super cluster level provides an example. The comparisons are determined apriori. The comparisons are for the relationship of the spillways and the non spillways, in addition the north versus south and the east versus west directions. These comparisons test the regional scale variation. Variance ratios are obtained by collapsing from the lowest level to successively higher levels and comparing the result to the F distribution. This-is possible by the 32 following relationship: G 1 /df 1 G = P dfl, df2 2 / df 2 Where G^ and G£ are the G statistics for the appropriate levels and df^ and df 2 are the respective degrees of freedom and P is the variance ratio for reference to an F-table• This is the same procedure as with individual degrees of freedom in analysis of variance. The relationship between the chi square and P distributions which allows for the above manipulation is explained in most general statistics texts (li, 1966). The results of the analysis are given in Tables 3, i|, 5 and 6. Appendices B and G contain the P values at each level plus the breakdowns and the original contingency tables respectively. 33 Table 3. Statistical Summary for All Levels of the Design sc- sc- HSU sc- sc- sc- Super Cluster Cluster ■sc- S i g n i f i c a n t (<*= .0 5 ) at the 0 .0 5 lev el \t 4\ Basic Igneous Foliated Metamorphic sc- Quartzose Pit Weak Sediments Acid Igneous Level Limestone Compositional Category 34 Table i|. Orthogonal Breakdown At The Super Cluster Level For The Basic Igneous Category Source Degrees of Freedom G/ F df 36 16.71 2 .78* Spillway versus Non-spillway 6 15*73 2.619-: Major spillway versus Minor spillway 6 34*76 5.77-* 4*192 O .696 ns 2.80* Super Clusters East plus central versus West within major spillway super clusters 6 East versus central within major spillway super clusters 6 16.86 North versus South non-spillway super clusters 6 5*78 East versus West non-spillway super clusters 6 23.38 Clusters * S ig n ifican t 66 at 0 .0 5 ns non significant lev el 6.01 (c* = . 0 5 ) 0.962 ns 3.87* 35 Table 5» Summary for Breakdown Between Pits & *■ is- Pit 6 versus Pit 7 Pit 12 versus Pit 13 Pit ll\. versus Pit 15 w 4\ it- iC- iSS ig n ifican t (<*■= . 0 5 ) i* at 0 .0 5 lev el Basic Igneous Acid Igneous it- Quartzose Pits Weak Sediments Limestone Source Foliated Metamorphic Compositional Category 36 Table 6 . Summary of Breakdown Between HSU's HSU's * HSU 13 versus HSU I k -I!- A ■5J- HSU 15 versus HSU16 ■JI* *- -:!• HSU 22 versus HSU 23 versus HSU 2 k HSU 25 versus HSU 26 Foliated Metamorphic -:s- HSU 5 versus HSU 6 HSU 1? versus HSU 18 Basic Igneous Acid Igneous Quartzose Weak Sediments Source Limestone i I Compo sitiona 1 Category «n. * *55* * Significance at the .05 level (c<= .05) % RESULTS INTRODUCTION The results of the statistical analyses answer the questions: Does a nonrandom pattern of variation exist and at which levels does it reside? Examination of the basic descriptive statistics for the levels which are significantly different provides more detailed information on the patterns of variation. Reference to the relative resistance of each species (Figure 3) provides a basis for interpretation of the process intensity. If a comparison yields a nonsignificant result, then the size frequency distributions are not distinguishably different. It indicates that the geologic history of the materials for each case has produced the statistically indistinguishable size frequency distributions but it does not necessarily indicate that the geologic history in each case was the same. Significant differences cannot arise from compositional differences arising entirely from grain size effects. That is, spasmodic changes in water velocity at a single time and space favoring different sectors of the size frequency distribution will yield different total volumes of a detrital species. However, the proportional volumes between size classes from sample 37 38 to sample should be similar. The analytic method chosen is only sensitive to disproportional differences. The results of the analysis indicate that a pattern of significant variation is present. SUPER CLUSTERS Significance at the super cluster level identifies a pattern of regional scale variation. Only the basic igneous category of all the compositional categories is significant at the super cluster level. Reference to Figure 3 indicates that the basic igneous, acid igneous and quartzose categories are all considered to have high mechanical resistance. Of these three nonlocally derived categories the basic igneous are the least chemically resistant. In addition to the above considerations this investigator found in the field that the acid igneous compositions have maintained considerable integrity over an estimated period in excess of 1000 years, whereas the basic igneous compositions are falling apart due to weathering. This strongly suggests that the basic igneous compositions could not have survived for very long. Thus it appears that the acid igneous compositions are the result of past accumulations mixed with renewed influx, whereas the basic igneous compositions indicate only the latest episode. The implications of this result cast the glacial sediment in quite a different light than'heretofore 39 mentioned* Many have argued in the past whether a given volume of sediment was a product of a particular stage, as resolved above* The last processes which moved the sediment may well have been due to the Wisconsinan stage* However, the material itself may have been progressively brought into the area by preceding glaciations. Thus, although land forms and the sedimentary structures and the patterns of grain size variation may be properly attributed to the Wisconsinan stage, a great proportion of the component clasts might well be Illinoian or Kansan in terms of the glacier that delivered them to the lower peninsula* Situations such as this have long been observed in purely fluvial systems where transport of the coarse fraction is quite slow and the major source of contribution is from the banks, SPILLWAYS VERSUS NON SPILLWAYS Super clusters 1, 2 and 3 within the old Grand River spillway and super cluster dj. within a smaller parallel spillway are compared with the non spillway locations, super clusters 5, 6 and 7 (Figure if.)« Results are significant from analysis of the basic igneous category* This result is not unexpected, as it reflects the shift in the size frequency distribution of the basic igneous toward the small 3izes in the spillways (Table 7A)• Inspection of the descriptive statistics associated with these distributions provide another means of verifying the results from the contingency tables* Uo U Kills 10 Clusters I 1 L_ 18 Kilos Figure 1*. REFERENCE FOR GEOGRAPHIC LOCATION WITHIN THE VARIOUS LEVELS OF THE DESIGN I _ * ----1— I Id Miles ii. hh B.B. VI* 252( van H StJ'a i 1-- 1 — 18 Miles it Figure lj.# Continued Table 7. SIZE FREQUENCY DISTRIBUTION, BASIC IGNEOUS Volume Class ID 1-5 6-10 11-15 501 1081 582 194 502 232 157 81 16-■20 20 40 21-25 75 25 26-30 60 0 31-35 0 0 36-40 40 0 21-25 75 0 26-30 60 0 31-35 0 0 36-40 0 40 21-25 75 0 26-30 60 0 31-35 0 0 36-40 0 0 21-25 0 75 26-30 0 60 31-35 0 0 36-40 0 0 21-25 0 25 26-30 0 0 31-35 0 0 36-40 0 0 21-25 25 0 26-30 0 0 31-35 0 0 36-40 0 0 G « 125.8772 for Total Set 7A Volume Class ID 1-5 6-10 11-15 503 722 412 182 504 359 170 12 16-•20 20 0 G » 278.1476 for Total Set 7B Volume Class ID 1-5 6-10 11-15 505 680 399 182 517 42 13 0 16-•20 20 0 G » 33-5404 for Total Set 7C Volume Class ID 1-5 6-10 11-15 516 47 26 27 506 633 373 155 16-■20 20 0 G= 134.9434 for Total Set 7D Volume Class ID 1-5 6-10 11-15 518 42 44 54 504 104 83 27 16- 20 0 40 G =46.2939 for Total Set 7E Volume Class ID 1-5 6-10 11-15 514 86 30 54 515 104 83 0 16- 20 40 0 G- 187.0463 for Total Set 7F 43 Of the descriptive statistics, only the skewness is relevant because the mean is very sensitive to local hydrodynamics and because the standard deviation is proportional to the skewness, it is redundant. The skewness statistic, as discussed above in regard to the loss of the tail, provides for the most straight forward interpretation. Inspection of Table 8 shows the difference in skewness between the spillways and non spillways. The skewness values are four to six times greater, with the exception of the east end of the major spillway, for the spillways than the non spillways. This is contrary to that expected from the Plumley (191+8) conclusions• Assuming Plumley*s (1948) argument is correct, we must suspect the upland sediment to be more mature. In view of the greater energy flux down the spillways, this result would at first glance seem paradoxical. However, once the basic igneous clasts were delivered to the uplands, the source of additional basic igneous pebbles was terminated. Then the material of the region was acted on by a complex of erosional and deposition processes due to the stablishment and evolution of the consequent drainage. At that time, as now, streams migrate across their floodplains eroding and depositing in an almost random fashion. Thus the'net down valley 10* Table 8 . Skewness Values for the Basic Igneous Category at the Super Cluster Level Non-spillways Spillways Skewness Super Cluster Super Cluster Skewness Major 1 0.38 5 0.23 2 1.55 6 0.32 3 1.2? 7 0.22 4 2.91 Minor Table 9 . Skewness Values at the Pit Level Pits Compositional Category Limestone 6 7 12 13 14 15 1.50 1.99 2.1^7 0.7 2 0.53 1.39 0.12 1 .0 0 -0.59 Weak Sediments 1.48 Quartzose -0.13 —Oeij-1 1.36 - 0.36 - 0.22 -1.09 Acid Igneous -0.89 0.71 0 .88 0.0 24 -0.39 0 .6 3 - 0.2 8 -1.91 Foliated Metamorphic k$ transport of the coarse fraction is almost nil. Kuenen (19^ 0 ) estimates that in an alluvial plain it takes one million years for the average sand grain to move one mile. In contrast to the upland, where the contribution of basic igneous material ceased, the spillways could have remained open, thus continually receiving additional basic igneous material. Rather than the evolution of a drainage pattern, we have a fixed course drainage east to west with the head situated in glacial lakes, which being relatively still water would contribute little coarse sediment. Thus, in the drainage way, the water was contributed by the lakes and the material from the bed and sides of the drainage way. The above suggests that much material resulted from major erosion in the materials through which the drainage way first passed. The rest of the material was derived from along its course. Examination of Table 8 indicates that the most mature sediment in the spillway exists at the head. This is consonant with the theory that lake waters act most vigorously on the materials at the beginning portion of a developing channel. Further down the spillway course the features (considered to be peripheral moraines of the Saginaw lobe) have provided a continual source of additional material. U6 It is in this way that the very low skewness values at the head and the very high skewness values in the central portion are explained. Another lower skewness value at the mouth where the width of the spillway has decreased from greater than a mile in the central area to less than a mile is probably due to the concentration of fluvial energy by decreased channel size. BETWEEN SPILLWAYS Breakdown of the "between spillway super clusters" compares the major spillway (super clusters 1, 2 and 3) with the minor spillway (super cluster ij.) (Figure !).)« The significant result indicates a difference between the major and minor spillways. There appears to be a definite shift in the size frequency distribution of the basic igneous toward the smaller sizes in the major spillway (Table 7B). The higher skewness value for the minor spillway (2.91) is suggestive of the probable short life of this feature as a drainage way compared to the longer occupation of active channeled energy flux in the major spillway. WITHIN THE MAJOR SPILLWAY The next two comparisons in the breakdown examine the within major spillway variation. The first compares the central and eastern super clusters (1 and 2) with the hi eastern (super cluster 1, Table ?D) (Figure if). The first comparison does not yield a significant result. This indicates a certain degree of homogeneity and uniformity within the drainage way. This conclusion could be tempered by the other comparison. The second comparison does yield a significant result. This might have been expected; although the skewness values are apparently quite different (1.55 versus O .38 respectively), the two locations have much in common. Both are situated at or near a lake water source. Thus, they might well be expected to reflect similar characteristics as their environmental conditions were probably very much alike. The difference which the skewness value is emphasizing is a function of the position in the spillway and availability of additional basic igneous material from the banks and bed of the spillway. However, because this result relies on such a small sample, it should be treated circumspectly. If the pattern of differences are truly regional differences, this again could be interpreted as the intense reworking at the head where the supply of additional material is limi ted. WON-SPILLWAY SUPER CLUSTERS The breakdown of the non-spillway super clusters first considers the north south comparison. This comparison (super cluster 6 plus 7 versus 5* Table 7E) 48 (Figure i f . ) , does n o t yield a significant result. This demonstrates that over an area this size the complex events yield a uniform result. came from the north. The material ultimately Thus, the absence of a north-south direction clearly indicates the homogeneity. However, the comparison of the east (super cluster 7 ) versus west (super cluster 6 ) non spillway super cluster (Table 7F) (Figure I4.), provides a significant result. The western super cluster (6 ) is proximal to a major morainal feature, thus emphasizing the differences due to a slightly different source. It appears that the differences between spillways and within the uplands arise from a perturbing source within the lower peninsula. This is apparently the Saginaw lobe moraine. SUMMARY AT THE SUPER CLUSTER LEVEL Therefore, examination of the patterns at the super cluster level for the basic igneous category suggests that the differences between spillways and uplands (non spillways) is apparently due to local character in the uplands and constantly renewed source in the spillways. This also points up the importance of morainal material as a source. INTRODUCTION TO REMAINDER OF HIERARCHY As mentioned earlier, only the basic igneous category showed significance at the super cluster level. k9 In general, at the lower levels, many categories show significance, excepting the basic igneous category. The reasons for this were discussed above. Thus, significant patterns of the other rock types must be interpreted in light of patterns impressed by the latest energy cycle upon materials that have experienced earlier episodes. At the pit level (Table 5) rock types, except the basic igneous show significance. At the next level, the HSU level (Table 6), significant differences for the basic igneous reappears. CLUSTERS WITHIN SUPER CLUSTERS Variation between clusters, within super clusters, is a measure only of the variation between clusters within each super cluster. Only two super clusters contain more than one cluster. Both of these reside in the central portion of the study area (Figure i|). They both contain only spillway locations, no upland locations. The comparisons show nonsignificance, indicating process homogeneity at this scale. Because there were not enough clusters available in the upland regions, comparisons were not possible. PITS WITHIN CLUSTERS WITHIN SUPER CLUSTERS Variation between pits, within clusters within super clusters, assesses only the variation between pits within a cluster. All the clusters containing more than one pit are located in the central portion of the study 50 area. Again, as with the higher level (clusters within super clusters), we are limited by the unavail­ ability of sufficient sampling sites to the spillway locations• Of the comparisons made, only three showed significant results. We take this to indicate we are just moving to a scale where quirks of local history are becoming apparent. That is, differences which are sporadic at this level become more apparent at the next lower level. The variation at the pit level is local and there­ fore it is felt that a detailed discussion at this point does not serve a useful purpose. Detailed discussion at this level is contained in Appendix D. H S U ’S WITHIN PITS WITHIN CLUSTERS WITHIN SUPER CLUSTERS The HSU's represent the lowest scale of variation investigated and analysed in this study. The results a-PPly only between H S U ’s within a pit within a cluster within a super cluster and, thus, are relevant to the pattern of local scale variation only. Interpretation relies, in part, on the "law of superposition". Of the six HSU comparisons showing significant results, one is located in the minor spillway, four are located in the central portion of the major spillway and one is located in the upland area south of the two $1 spillways. Because the variation at the HSU level is also at a local scale a detailed discussion at this point does not serve a useful purpose and therefore has been deferred to Appendix E* CONCLUSIONS Patterns of compositional variation do exist in the area studied* The method of analysis assures that these differences are not due to grain size and are also greater in magnitude than differences expected from chance variation* Analysis of the patterns indicate, in general, that the record contained in the glaciofluvial sediments is not unlike a palimpsest in that, although the physiography, sedimentary structure and grain size are due to the Wisconsinan glaciations and deglaciations, a considerable amount of the material has apparently been recycled from pre-existing glacial sediments* The possibility exists that, with more detailed work, energy flux and transport cycles associated with earlier glaciations might be deduced by further examination of the pebbles in these Wisconsinan deposits* Furthermore, since the Pleistocene sediments that now mantle the lower peninsula may represent the sum total of past glaciations, it may be that the sediment contribution of each, including the Wisconsinan, was much- less than was 52 heretofore supposed. These conclusions are based on the fact that onlybasic igneous rock fragments present significant variation at the regional level, whereas most of the other rock types show significance only at the lower levels. Mechanisms proposed to explain this concerns the comparatively like mechanical resistance of the basic and acid igneous rocks to their disparate chemical resistance. Whereas the acid igneous retain enough strength to be reworked by a renewed glacial event, the basic igneous do not last. More careful examination of the patterns of variation of the basic igneous indicates the outwash in the morainal uplands is more mature than in the drainage ways. This is probably due to the fact that the transport of pebbles to the morainal areas was limited in time, whereas a constant influx of fresh material was available to the deep cutting spillways, particularly from the Saginaw lobe morainal area. The Saginaw moraine prominent in the discussion of the provenance of the spillway material also are probable sources of upland material, as evidenced by the significance for upland pits closest to the moraines, From analysis at the pit level, all rock types exhibit significant difference in only three pits. This indicates that a fine scale of variation exists which is approximately the distance between pits.- Existence of 53 significant variation of HStPs within pits further corroborates this fine scale of variation, probably due to local energy flux involving varying numbers of cycles of erosion and deposition, or at least varied energy fluxes during a single episode. The conclusions of this thesis should offer encouragement to those who would like to supplement knowledge based on stratigraphy and geomorphology with sedimentological data in order to more clearly understand the nature of continental glaciation. This study demonstrates that valid use of the pebble fraction can yield satisfying results without resort to great operational complexity or extremes in data reduction and analysis. BIBLIOGRAPHY BIBLIOGRAPHY Anderson, R.G., 1955, "Pebble Lithology of the Marseilles Till Sheet in Northeast Illinois", Jour, Geology, V, 63, pp. 228-210. Apfel, E. To, 1938, "Phase Sampling of Sediments", Jour, Sediment, Petrol®, V. 8, pp, 67-68, Dorr, J,A«, and Eschman, D,P., 1970, Geology of Michigan, University of Michigan Press, Ann Arbor, Mich, l+76p. Ehrlich, R«, 1961+, "The Role of the Homogeneous Unit in Sampling Plans for Sediments", Jour® Sediment, Petrol,, V, 31}., pp, i+37 —i+39® Ehrlich, R , , and Davies, D,K,, 1968, "Sedimentological Indices of Transport Direction, Distance and Process Intensity in Glacio-Pluvial Sediments", Jour. Sediment• Petrol., V3 8 , pp, 1166-1170. Flint, R,P., 1957® Glacial and Pleistocene Geology, John Wiley and Sons, New York, 553p® Flint, RePo, 1959s "Glacial Map of the United States East of the Rocky Mountains", U.S, Geological Survey, Goldich, S » S ,, 1938s "A Study in Rock Weathering", Jour, Geology, V. 1+8, pp,17-58. Griffiths, J,C•, 1967, Scientific Method in the Analysis of Sediments, McGraw-Hill, New" Y o r k 5 " ^ 8 p , Hough, J,L,, 1958, Geology of the Great Lakes. of Illinois Press, Urbana, i'll,, 313P« University Kelly, R.W., and Parrand, W.R., 1967, The Glacial Lakes Around Michigan, Michigan Geological Survey, feull• k» 2l+P. Krumbein, W.C., and Lielblein, J,, 1956, "Geological Application of Extreme Value Methods to Interpre­ tation of Cobbles and Boulders in Gravel Deposits", American Geophys. Union Trans,, V. 37, PP® 313-319. Krumbein, W.C., and Graybill, P.A., 1965, An Introduction to Statistical Models in Geology. McGraw-Hill, New York, i+75p« 5U 55 Kuenen, Ph.H., 1950, Marine Geology. New York, 568p. John Wiley and Sons, Leverett, F.B., and Taylor, P., 1915, The Pleistocene of Indiana and Michigan and the History of the Great Lakes. U.S. Geological Survey, Monograph £5. Li, J.C.R., 1964, Statistical Inference I . Edwards Brothers Inc., Ann Arbor, Michigan, 658p. Martin, H.M., 1955 k "Map of the Surface Formations of the Southern Peninsula of Michigan” , Publication 49, Michigan Geological Survey. Oldale, R.N., 1987, "Pleistocene Stratigraphy of Cape Cod, Massachusetts, (Abs.)” , Geol. Soc, America NE Section Program, p.47« Otto, G.H., 1938, "The Sedimentation Unit and Its Use in Field Sampling” , Jour. Geol., V. 46, pp. 569-582. Plumley, W.J., 1948, "Black Hills Terrace Gravels: A Study in Sediment Transport” , Jour. Geol., V. 56, pp. 526-577. Sokal, R.R., and Rohlf, P.J., 1969, Biometry, The Pr inti pie and Practice of S t a M s t i csiri Biological Research. W.H. Freeman and Company, 776p. Wayne, W.J., and Zumberge, J.H., 1965, "Pleistocene Geology of Indiana and Michigan”, in The Quaternary of the United States. Princeton University Press, Princeton, N.J., pp. 63 -8 4 ® Winters, H., 1969, Personal Communication, Michigan State University. APPENDICES APPENDICES Appendix A, Cross Reference for the hierarchy Appendix B, P values at each level plus the breakdowns Appendix C, Original contingency tables Appendix D, Detailed discussion at Pit level Appendix E, Detailed discussion at HSU level 5.6 APPENDIX A, CROSS REFERENCE FOR THE HIERARCHY APPENDIX A Cross Reference for the Hierarchy SUPER Cluster SAMPLE PIT HSU 1 1 1 1 + 2 2 2 2 3 +k 3 3 3 5 + 6 k 7 + 8 5 9 + 10 6 11 + 12 USTER 4 4 5 5 7 13 + 14 6 6 8 15 + 16 7 9 17 + 18 7 8 10 19 + 20 8 9 11 21 + 22 10 12 23 + 24 11 13 25 + 26 14 27 + 28 15 29 + 30 16 31 + 32 17 33 + 34 18 35 + 36 14 19 37 + 38 15 20 39 + 40 16 21 41 + 42 9 12 10 13 11 12 57 58 APPENDIX A (continued) SUPER CLUSTER 2 6 7 CLUSTER 13 1U 15 PIT 17 18 19 HSU SAMPLE 22 1+3 23 1|,5 + I 4.6 2U U7 25 1|.9 + 26 51 + 52 27 53 + 51+ 28 55 29 57 + 58 + U8 50 58 1 16 20 30 59 + 60 3 17 21 31 61 + 62 5 18 22 32 63 + 61+ APPENDIX B, F VALUES AT EACH LEVEL PLUS THE BREAKDOWNS Table Bl. F Values for Limestone, All Levels "Corrected” Source df G G df G/df P dfl df2 Super Clusters 48 1066.70 1066.7C 48 22922 0.597 48 88 Clusters 136 4181.07 3114.37 88 37.2C 1.424 88 32 Pits 168 5018.59 837.52 32 26, IS 1.7 2« 32 80 HSU 248 6242,95 1224.36 80 15.3 80 256 Samples 50lj 9422.96 3180.01 256 1.25 12.42 ^Significant at 0.05 level (cx= 0 ,05) Table B2. P Values for Weak Sediments, All Levels “Corrected” Source df G G df G/df P dfl df2 Super Clusters 36 556.09 556.09 36 11.58 1.06S 36 66 Clusters 102 1507.50 951.41 66 10.81 1.21f 66 24 Pits 126 1791.97 284.47 24 8.89 1.637* 24 60 HSU 186 2226.56 434.59 60 5.43 2 .784 * 60 192 Samples 378 2725.85 499.29 192 * Significant at 0.05 level ( « = 0.05) 59 1.948 60 Table B3. P Values for Quartzose, All Levels "Corrected” Source df Super Clusters 42 566,86 566,86 42 11.80 0.734 42 77 Clusters 119 1982.49 1415.63 77 16.09 0.869 77 28 Pits 147 2574.02 591.53 28 18,5 1.929 * 28 70 HSU 217 3340.58 766,56 70 9.6 4913.50 1572.92 224 Samples 44l G G df G/df P 1.56* dfl df2 70 224 6.15 ■fr Significant at 0,05 level ( - = 0,05) Table B4> F Values for Acid Igneous, All Levels, "Corrected” Source df G Super Clusters 42 954.16 954.16 Clusters 119 Pits 147 HSU Samples G df G/df p 42 19.87 0.805 42 77 3120.98 2166.82 77 24o62 1.148 77 28 3806.19 685.21 28 21.45 2.127 * 28 70 217 4615.06 808087 70 10.1 1.73 * 70 224 441 6110.61 1495.55 224 * Significant at 0,05 level (-<= 0.05) 5.845 dfl df2 61 Table B5« P Values for Basig Igneou3p All Levels ’’Corrected" Source df Super Clusters 36 G 802.39 G df G/df 802.39 36 16.71 P dfl df2 2 .78 « 36 66 Clusters 102 1325.35 522.96 66 6.01 1.443 66 24 Pits 126 1458.58 133.23 24 4.16 0.825 24 60 HSU 186 1862.8? 404.29 60 5.05 2.88-fc 60 192 Samples 378 2478.82 615.95 192 2.41 «• Significant at 0.05 level (<*= 0.05) Table B6. P Value for Foliated Metamorphic, All Levels "Corrected" Source df G G G/df df p dfl df2 Super Clusters 24 198.66 198.66 24 4.138 0.967 24 36 Clusters 60 506.43 307.77 36 4.27 0.77' 36 8 Pits 68 586.91 80.84 8 5.5 2.8-* 8 24 HSU 92 685.37 94®48 24 1.965 5.044 24 44 136 719.67 34.30 44 0.39 Samples •* Significant at 0.05 level ( « = 0.05) 62 Table B7. F Values for Limestone, Between Pits "Corrected” Source df F dfl df 2 G/df Between Pits Within Clusters 32 26*19 1*72* 32 80 Cluster 6 Pit 6 , 7 8 10*19 0*6661 8 80 Cluster 9 Pit 10, 11 8 0 .2*396 8 80 Cluster 10 Pit 12, 13 8 2*2.02 2.72*70* 8 80 Cluster 11 Pit li*, 15 8 2*5.72* 2.9899* 8 80 H S U ’s 80 6*721}. 15®3 ■fr Significant at 0®05 level (« = 0 *0 5 ) Table B 8 . Source F Values for Weak Sediments, Between Pits .. . ... — "Corrected" df F dfl G/df Pits 22* df 2 8*89 1.637* 22* 60 Cluster 6 Pit 6 , 7 6 3° 582* 0.6602* 6 60 Cluster 9 Pit 10, 11 6 2*336 0.2*305 6 60 Cluster 10 Pit 12, 13 6 19.2*32 3.5789* ■ 6 60 Cluster 11 Pit 12*, 15 6 10.205 1.8797 6 60 HSU* s 60 5.2*3 # Significant at 0*05 level ( ~ = 0,05) 63 Table B9* F Values for Quartzose, Between Pits "Corrected" Source df F dfl df 2 G/df Pits 28 18.5 1.929* 28 70 Cluster 6 Pit 6 , 7 7 14*9143 1*5536 7 70 Cluster 9 Pit 10, 11 7 15.148 1*5779 7 70 Cluster 10 Pit 12, 13 7 29.968 3.1218* 7 70 Cluster 11 Pit 14, 15 7 13.910 1*449 7 70 dfl df 2 70 HSU's 9*6 * Significant at 0.05 level (c<= o ao5) Table BIO. F Values for Acid Igneous, Between Pit 3 "Corrected" Source df F G/df Pits 28 21.45 2.127* 28 70 Cluster 6 Pit 6, 7 7 30.827 3 .0522 :> 7 70 Cluster 9 Pit 10, 11 7 20,622 2.0419 7 70 Cluster 10 Pit 12, 13 7 12.568 1.2445 7 70 Cluster 11 Pit 14, 15 7 21.633 2.1419*: ^ 7 70 HSU's 70 10 01 * Significant at 0*05 level (<*.= o*05) 61+ Table Bll. P Values for Foliated Metamorphic, Between Pits "Corrected11 Source P df dfl df2 G/df 2.8% 8 21+ 2.562 0.61+75 i+ 21+ k 8.787 1+.1+727% 1+ 21+ 21+ 1.965 Pits 8 Cluster 9 Pit 10. 11 1+ Cluster 10 Pit 12, 13 H S U ’s •^Significant at 0.05 Level = 0.05) 65 Table B12. P Values for Weak Sediments, Between H S U ’s "Corrected" Source df P dfl df2. G/df HSU's 60 543 2.781** 60 192 6 2 a099 1.0783 6 192 Pit HSU 3 3, b 5,6 6 12.107 6.2157* 6 192 li 13, 11+ 6 5.621}. 2.8879* 6 192 12 15, 16 6 6.399 3.2858* 6 192 13 17, 18 6 13*315 6 .8358 * 6 192 17 22, 2 3 , 21+ 12 2.907 14928 12 192 18 25, 26 6 6.71 3 ol497* 6 192 19 27, 28, 29 12 1.1212 12 192 b Samples 192 .5758 1.948 *• Significant at 0.05 level ( ~ = 0.05) 66 Table B13* P Values for Quartzose, Between HSU*3 df Source "Corrected" G/df HSU's Pit 70 9*6 dfl df2 1*56* 70 224 P HSU 3 3, 4 7 1*02 0*1661 7 224 4 5, 6 7 5*782 0*9404 7 224 11 13, 14 7 11*042 1*7957 7 224 12 15, 16 7 7*423 1*2072 7 224 17, 18 7 13,693 2*2268- «■ 7 224 14 11*189 1*8195: {• 14 224 7 14,098 2,2926- * 7 224 14 10.189 1*6569 14 224 12 17 22, 2 3 , 24 18 25, 26 19 27, 28, 29 Samples 224 6*15 * Significant at 0*05 level (~=0*05) 67 Table Bl4. F Values for Acid Igneous, Between HSU*s df Source "Corrected" p dfl df2 70 224 G/df HSU ’s 70 10 .1 1.73* 3 3, 4 7 11.113 1.9011 7 224 4 5, 6 7 8.950 1.5315 7 224 23 ,433 4.0092* 7 224 2 . 0692* 7 224 7 12 15# 16 7 12.093 13 17, 18 7 8.046 1.3768 7 224 17 22, 2 3 , 2i| lit 6.146 1.0517 14 224 18 25, 26 7 12.970 2.2192* 7 224 19 27, 28, 29 111 6.104 1.0445 14 224 Samples 224 5.845 H n -d" HSU HI Pit A * Significant at 0.05 level ( « = 0.05) 68 Table B15. F Value3 for Baaic Igneous, Between H S U «3 ’’Corrected" Source df P df2 dfl G/df HSU*s Pit 60 5*5 2.88* 60 19 2 HSU 3 3, 4 6 0.059 0.0246 6 192 4 5® 6 4.90 2 a 0334* 6 192 11 13® lb 6 4*533 1.8811 6 192 12 15® 16 6 2.330 0.9672 6 192 13 1 7 ® 18 6 12.776 5.3014* 6 192 17 22, 12 4*880 2.0044* 12 192 18 25® 26 6 13*373 5.5494* 6 192 19 27® 28® 29 12 l«45l 0.6023 12 192 Samples 192 2.41 6 2 3 , 21}. Significant at (c*= 0.05) .0.05 level 69 Table Bl6. P Values for Foliated Metamorphic, Between HSU's Source df "Corrected” G/df HSU's Pit 2k 1.965 P dfl 5 «Ol*-::- 2U df2 lik *TT HSU b 5, 6 5 1*.739 12.1530-: ^ 5 kb 12 15, 16 5 2.782 7.131+24 i- 5 1*1* 13 17, 18 5 1.698 1+.35504 ^ 5 kk 17 22 , 23 , 21* 9 1.51*1* 3.96004 : 9 Ui* Samples 0.39 # Significant at 0.05 level ( « = 0,05) APPENDIX C, ORIGINAL CONTINGENCY TABLES Note: All zero columns are not used in the computation of the degrees of freedom. ‘ ! Limestone Super Clusters Table Cj> ID 116 -100 117 . . . 140 118 - 114 115 1 5 6 - 1 0 1 1 - 1 5 '! 6 - : : o ' 206 123 3fl 40 . 4299 2009 1157 900 409 180 45 20 2412 1349 4 2 5 - 31.5 239 333 93 20 99 445 238 137 812 395 53 19* G = 1066,7094 GSTAT/ DEGREES 26-30 31-3o 25 423 0 175 47 50 97 3 C- / : 0 Al -' i . ' i 30 0 " 0 0 24 Q- .. 2 0 6 . .... 4 0 - . 4 5 _____ 0 0 o 0 - 9 0 ---- 70 . . . . . 0 — .80 -------0 1 0 0 0 0 35 . . 0 0 - ..... 0 o 0 0 FOR TOTAL' SET - 22,2231 OF FREE DOM Table CIO Weak sediments, Super Clusters Vol.iiTi C.l.’.r;s ID 216 .-220 217 .. 24 0 218 .214 215 G * }"? 6 -10 20 31 “5 . - 2 6 0 . 1 3 8 .. 1 8 16 41 »i) 64 60 191 - n 18 57 0. - • 25 .0 35 23 d 556, 0906 FOR -6 75 -0 2? »0 50 0 »0 60 "0 20 0 20 0 Table Clj? 316 -320 317 - 340 318 - 314 315 G r 566,860-! -0 "0 °0 -0 . 30 0 -0 “0 •>0 0 c . -0 "0 • > 0 - -V 0 “0 ”0 - 0 .... " 0 -0 -0 .... 0 . - 0 0 0 11,5852 Quartzoso Super Clusters VoTu i C: Cl ? ■? G ~ 10 3 1- ■}:> 1( 3 -: : o 2 j 55 62 377 581 46 20 312 - 1 1 8 29 32 52 40 99 83 -0 57. - 3 5 TOTAL SET GS T AT / DE G r KES OF FREEDOM ID 3 6 - 6 0 41 - 1 1 - 1 . ) 1.0- '.0 2 J - / ■> 7: 6- 30 3 1 - 3 5 66 I4d 15 81 22 53 84 26-30 31-35 36-60 61-35 -0 •’0 «0 "0 "0 94 .. 90 . . 7 0 0 - -42 _ _ "0 “0 "0 "0 -0 50 . 60 — *• 0 - . - 0 - — . n 0 ----«c 25 "0 «Q “0 -0 25 30 - 0 --. i o .. F» 0 25 •0 ■«0 -0 20 195 -0 • 84 40 20 40 FOR TOTAL SET GSTAT/ DEGREES OF FREEDOM 11,8096 70 71 Table C20 Volurra C l a m J-.5 6 - 10 31 • 1 5 i G - : : o 2 1 - 2 5 1D ' 4i 6 <20 <17 44 0 . <18 <16 < 15 • Acid igneous, Super Clusters G * <7 26 27 .716 <90 20 5 <2 13 - 5 3 4 < .._- 1 7 4 .. 9 ?. , 67 76 27 ■1 1 3 . 71 57 96 85 0 954,1666 ................ 2 6 - 3 0 3.1-11 3 36 - 7, 0 • 0 -0 20 169 90 153 « ci • - 0 *0 5 7 . 75 . 2 0 7 0 30 20 0 • 30 0 0 0 0 POK TOTAL SET -0 70 -0 35 35 35 35 *>0 '0 1 6 0 ___ i 0 ... •i o *0 -0 0- --0 «0 *, 0 - -• * 0 - <*0 ^0 ---------------- SSUT/nEGRKES or FREEDOM - 19,8785 I ‘ I » Table C2£ Volin;, Basic igneous, Super Clusters C 1..’::; in )-? G- i o n ■•!i> U ; - : : o 2 J 516 47 • 2 6 2 7' 20 520 633 373 1 5 5 . .0 517 42 13 *0 54 0 . . - 3 5 9 170 1 ? ....... 0 516 42 44 27 -0 514 86 30 ■54. . 40 515 1 04 63 -5 ••0 - . G = 802,3952 GSTAT/DEGREES Of POP TOTAL FREEDOM 26-30 3 j - 3 3 3 6 - 6 0 /, ] T*0 •■0 -0 -0 ’ -0 60 75 .-o . -0 >•0 "0 ”0 -■ 0- ------0 ...... 0 - . . - 4 0...... - 0 - 0 »0 "0 - 0 .. : - 0 ..... ■25 ... - 0 - 0 -0 -0 "0 . ___ _ ”0 *0 ”0 to t0 “0 -0 . _________ __. , ........ _________________ -------- SET 16,7166 72 T a b le Cl T o ta l v a r ia tio n , V o lliV i* iu\ 101 102 103 104 105 106 107 108 109 110 11 1 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 1.26 1 29 130 131 132 133 134 135 136 137 13 B 139 140 14 1 142 143 144 145 14 6 147 148 149 150 151 15 2 153 154 155 156 157 156 159 160 161 162 163 164 1-5 C L '.l •• (>■. 1 0 11 - 1 5 54 58 81 95 46 30 65 72 14 0 58 45 130 15 100 42 146 41 15 69 105 60 50 1 97 5 115 19 12 140 56 39 84 158 12 62 122 0 1 94 50 12 125 77 30 127 123 43 76 161 15 69 39 241 4a 166 n 39 0 29 97 63 56 49 160 0 193 60 27 144 58 45 117 177 3,1 45 1 04 30 60 93 71 94 88 45 49 176 0 36 ii 111 ' 169 82 27 2 31 42 .0 42 175 12 73 46 87 3 r, .82 1 31 '101 ' 51 24 125 55 70 90 54 42 11.6 83 15 114 11.4 115 72 91. 54 133 100 54 58 54 152 86 202 23 10 4 7 3 • 2? 139 30 27 29 45 171 1.73 102 0 136 79 0 54 111 12 70 . 59 15 76 132 36 143 38 4? 71 106 27 11 4 57 15 137 44 84 221 82 152 98 108 205 204 145 143 lim e s to n e 71 51 101 39 84 61 119 175 158 45 1? 15 15 15 3,0 15 66 ,2 7 3*2' 21-25 1 7f,-3!> :iH - 3 5 3 6 - /;() 0 25 0 0 0 fco 25 6 0 - - - 0 —. o -------o 40 45 0 0 0 0 20 57 0 0 ...... ...0 - - 0 .......45 0 25 'o 0 0 40 0 —... o ...... 0 0 - 0 0 0 . .0 0 0 40 0 0 - o . ... 0 .. . 0 _ _ o 0 35 0 0 0 0 0 0 •3 0 - - 0 — 0 - - - 0 20 0 0 20 0 0 0 0 -- 0 — o 6Q 60 0 0 0 0 0 0 0 0 —- 0 0 .... o - -35 la 0 0 0 0 25 0 0 0 0 ------ • o 0 20 0 0 25 0 0 0 25 0 - 0 0 ........ 0 0 45 33 0 66 25 0 0 40 ... :. o 20 0 - 35 0 0 0 0 0 40 0 ..... 0 40 ■ 25 .. o ... 0. . 0 0 0 30 0 20 0 0 - . 0 0 . .. . 0 20 0 0 30 0 0 40 o ... 60 0 0 ......... 0 . 0 0 0 0 0 211 0 o 0 .... 0 - 0 — 0 - 25 0 0 25 0 0 20 o ... o 0 0 . 3 0 ... 0 0 0 • 0 0 0 0 o ... . 0 .... . . o ____ 0 0 0 0 0 0 5 8 . 50 0 - 0 . .. . o 0 .... 0 -- . 0 20 0 0 30 0 50 0 o .... 0 ... - 0 . . . . 0 20 - 25 25 33 0 0 0 40 2 5 . 60 ... 70 . - 0 .... o 0 0 0 0 50. 0 40 0 ... . 4 0 — 0 0 . . . 0 -61) 0 0 25 0 40 0 0 .. - 0 . . . . 0 25 0 20 0 0 0 0 0 20 35 38 0 0 . o ..... 0 0 0 25 0 0 20 23 0 - . 0 . ■ 0 .... 0 0 0 0 0 0 0 20 0 . . . . - .0 ....... 0 0 .0 0 0 0 0 0 0 40 0 0 25 0 0 60 0 0 25 0 0 0 35 37 0 ... o 0 . ... 0 0 0 47 0 0 40 n 0 0 0 . 0 0 0 25 0 0 0 0 0 18 (1 0 40 0 20 20 0 G a 9 0 2 2 , 9 6 1 3 FOR TOTAL SET 0 25 0 25 0 0 0 0 47 0 0 0 0 o 0 30 ... 0 0 0 0 0 . 0 0 0 0 0 0 • . 0 0 0 0 0 0 0 0 0 :0 . ..... -. . . . n 0 0 0 0 0 o 0 73 Table C2 ID 1.01 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 12 7 128 129 130 131 132 Limestone H S U ’s V o l i n a Cl.'1.: -' :i i - : j 5 3 6 - ' 'i0 7il 1.-5 (>••10 3 1 -1.5 1 0 •• 7.r’ 25- 75 2 6 - 3 0 0 0 60 176 104 84 50 0 100 0 ... 90 c 0 270 123 77 0 117 0 lo 0 0 63 25 246 40 30 0 - 0 .-. lo 163 286 63 0 . 0 40 35 30 0 0 255 75 51 0 20 0 •. - 0 0 60 280 146 0 00 1? 3 5 • .0 0 0 319 ' 127 4? 0 18 jog .0 0 25 0 288 54 20 -• 0 0 0 50 0 407 0 117 3? 0 186 06 25 63 85 0 - 6 0 - 40 .... 45 0 0 0 25 353 109 0 27 80 0 - - 0 ... 0 30 175 0 321 75 40 0 30 0 0 105 12 3 0 10 0 175 0 0 0 45 25 --0 137 27 0 20 0 0 0 25 30 280 118 27 20 . -0 0 0 ... 0 0 406 84 12 0 0 0 128 0 0 117 50 78 20 4 0 - 0 •0 226 106 25 30 78 10? 103 0 2 06 57 50 0 137 40 60 0 206 ■ 40 ... 0 186 1 6 B 10 0 50 0 0 0 0 0 285 158 50 109 60 . o .... o 366 159 58 0 0 .... 3 5 53 0 89 0 0 48 •U 310 72 20 _ 0 0 3 09 0 (! o . 20 161 s 0 0 124 27 25 0 1 70 0 100 .35 25 275 114 37 0 0 0 7? 0 0 47 42 0 0 220 126 40 358 25 115 0 _. 0 .. ... 0 .. .. o 12 9 0 0 234 ’ 152 0 0 27 25 18 0 206 4 0 - 25 33 123 30 ... 0 - 0 ... 0 0 4 09 180 0 0 45 0 20 0 0 . - 0 .. 0 288 47 . ... 0 333 93 20 G = 6242,9583 FOR TOTAL SET — . . . ------------- ------- .------- 7h Table C3 L im e sto n e Voll:':''.! C \ 11.) C- jo l-'j 176 270 532 535 319 208 407 136 35 3 321 445 606 430 206 206 205 1005 4 45 012 206 409 280 ....." t o i : 102 103 104 10? 106 107 10B 109 110 111 112 113 114 115 116 117 118 119 120 121 122 n - 104 123 246 221 127 199 117 63 109 175 242 202 234 13 7 106 150 39 9 238 395 123 180 333 G * 5 0 1 0 ,! 5942 ’ 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 110 V o J.u 1-0 to 84 117 90 63 42 59 39 85 27 75 173 39 219 57 169 105 12? 99 193 3fl 45 93 50 0 25 0 0 25 50 25 25 0 25 25 75 50 50 50 48 50 97 25 0 47 100 77 80 100 18 20 0 86 80 40 120 20 156 40 100 60 98 137 58 40 20 20 3i~35 36-60 h 1- 60 0 0 0 . . . . 0 .. 0 _ . 0 — - ? 0 0 0 0 0 0 _. _0. . -90 .. 3 5 ... 35 0 0 0 0 • 0 . 0 -_ c 0 0 • 0 . .0 .. 45 68 .40 0 O 0 0 G 30 0 . . 0 . 0 0 0 30 0 0 ... 0 - - 0 30 0 0 30 0 1 0 3 ... 0 --■ - 0 60 0 0 40 0 0 . - 0 .. . 0 ... ......0 35 0 0 0 3 5 ..... 0 • .0 0 0 0 0 0 0 30 . 0 -;.... 0 0 0 0 0 o .... 0 0. 0 __ .. _ - -w Limestone Clusters Ol.i: (,- ] 0 176 270 53 2 535 319 695 186 353 766 1116 412 285 1005 445 812 206 4 09 268 •» t ■»<■-20 21- 75 2 6 - 3 0 ] J : t. FD R TOTAL SET Table Cij. Tl), P its ) ! - ] !> ) '; - : : o 104 123 24 6 2?1 127 316 63 1.0 9 417 436 3?3 158 3 99 23a 395 123 1 ;>0 333 64 117 90 63 4? 97 85 27 248 258 225 108 122 99 198 30 45 93 100 77 BO 100 18 20 86 80 160 176 140 60 98 137 58 40 20 20 : 26-30 31-35 36-60 60 50 0 0 0 0 " o - . 0 ..... 9 0 ' 1) n 25 0 0 . . . . . 00 90 Cl 35 n 0 0 . . . 3. 5Q . . . 0 ...... 0 0 .... " 0 ' 75 0 25 0 68 45 «o 0 25 0 0 0 25 60 0 0 0 6 " 1 0 0 ' 60 0 0 " too 103 60 40 . . 0 0 50 0 0 0 48 0 35 0 0 . . . 0 ... 50 ' 0 ' 35 0 97 0 .... 0 00 '. . . . . . 0 . 25 30 ' " 0— 0 0 ... 0B 0 0 47 " 0 ■ 0 “ .....O ' " G s 4 3 .0 1 ,07 44 F O R T O T A L S E T ! i i t C3 -p ! i' I S3 <7 * <7 • 0 s •H •o O ^ 03 <7 i vc: «r> id I i ! i ! O O O O OO o O O O O O O O O O O O O O OO O OOO O O O O O O O O O G O O G G O G O O O O O O C 70 O G O O o o o o o o o o o o O O Q . Q O O I in O O • O O O i I t * O O O O O ! O O ! O ! O O i O O O I O I O C 3 : 0 0 ; G G ! O O ; Q O O I O O ■ O 1 O O ■ O O O 1 O O i O i O O : O O ! O O O O O : O O O i O O i O G O : OOOOOOOOOOOOOOOOOGOOOOOOOOOOOCa OOOOOCDOO^ OGQOOOOOOOOOCDO o o o o o o o o o o v : CJ 0 •H -P a? •H o o o o o o o o o o o o o o o o o C M o o t r v o o o o o o i n o o o o o o i r . o o o o o o o o o o o o o i r \ © o i r . o o CM CM CM CM CM CM cs o o o o o o o o o o A3S % d { • ‘ ! O 1*^ o o o o -o < 0 0 0 0 0 0 CVJ ■«—4 r—*' o O o o o o o o o o o o ' . o « o i c u v a - o o i c - o ' c - ' c o i o i c v rv o o < o < o t r \ o » o * o * o . o o o o o o - o - o tS H 0 cm o o o o o o c o o o < ri . ja o 1 o ;o o o o o * 0 0 * 0 *o o - o + o w o * o - o ri «0.i 0 r- i < o i o t o < c > o > o * 0 - 0 tn v o .O ‘o * o ‘o i r*» H d -P • IVlOi ^o o o o o o o o o o c j o a o o a o Q o o o o o c o a o c c a o o o o o o o o o o a o o o o o o o o Q c o o o o CM CM CM CM CM v7* i > o o c o o o r ^ ' O o o o ^ o r*< o o o c o o o r o o o o o a . ' s . o o -rH «H «"» » "i 0 0 0 0 p o o ' O O c o c m o o p n .o T -f t-H «-< r - i • T < o o » 4 r H K ) i f \ i C ' O O s r ' V C O c c c . c o ® c c : c D W J ‘ M n v . ' N r < r o N C ' r o o v * r ^ ,Q, ' H W ^ i ' r ’r o r ' 0 * c \ i i A f ^ A W c o i s« a c 5 r v ^ o - ' ’C f N ' O i r n i r . vO o 0) H cj H r l H W H H t- 1 r-< r-i v-1 r - i <*i r l W r l CM CM . H £ ^ J r t ^ l ^ ^ ' £ ^ ^ C O I > Q H ^ J ^ O T l ^ s 5 ^ a 3 ( ^ O r < ( M f O V ( i ^ 0 ^ 3 5 ^ ^ 0 W ( ^ J ^ 5 ' l r l A ' C ^ O ( ^ O t 1 ( \ l ( O C l A ' O ^ C ^ O v O H ( ^ i y ) r u ' ^ ' 0 ^ c a C ^ ^ r { ^ 0 ,O C O O O Q O Q O O O r t r i r l r i H r H r l H n H W W C U ^ W W W C M C ' J N I C t O n f O n ^ f O f O l O t O ^ t r ^ W v r N - C ’ W L n i A ^ ^ u ' i n i r , U*1i r NLTl *C' 0' C' 00 CU CM CM CM CM CM <\ J CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CVJ CM C M C M C M C M C M f O C M C M CM C M C M C M C M C M C M C M C M C M C M C M C U C M C M C M C M C M C M C M C M C M f M it a 76 Table C? Weak Yolrivn c:i Jl) 1-5 6 - .30 213 214 215 216 21 7 216 219 1 10 24 28 15 31 37 20 26 8 20 16 20 14 26 23 12 10 25 220 7 201 202 203 204 205 206 207 2nb 209 21 0 211 212 221 8 222 47 223 224 225 226 227 226 229 230 231 232 11 12 10 15 6 6 7 ’ 31 41 IB 1 1-15 1C 44 »n n 0 ■-a 36 ' -6 6 -d 0 45 10 -a 12 -a r(l -d 0 is 0 ■ n 6 d -0 - n 8 -a 0 0 33 13 rt 0 -0 7 15 0 6 -0 -n 8 a 13 -a 10 - d -0 -a 7 15 0 a 0 a *0 -a 13 ~d 22 -A 20 -a 16 -0 17 - a G a 2226.5625 se d im e n ta 20 21 - 2 5 H0 «b "0 "0. 20 w0 - 0 "0 0 20 0 “0 »0 0 0 - 0 40 0 • •• 0 tl O T0 "0 0 °0 20 0 • -0 -0 -0 -0 -0 ■ -0 FOR 'TOTAL H S U 's 26-30 3 i -3. 5 3 5 - 'id 4 1 - *s 0 »0 no pO *0 "0 . «*0 «0 -“ 0 "0 «0 *0 a Q • 0 »>o . **0 -0 22 »o "0 25 -0 -0 "0 "0 -0 "0 . 29 27 0 ..-0 cO - 0 *0 r0 . 25 - 0 ~0 30 0 "0 -0 "0 ... k0 »0 -0 -0 • 0 25 30 25 rO . *0 "0 - 0 ■. . «0 -0 -0 a 0 . .-o -0 »0 . . . o - * 0 . .. SET •* 0 f'O -0 »0 -0 «0 ”0 *0 *»0 °0 p0 -o • "0 ”0 -0 •>0 ”0 ”0 •*0 • i 0 •>0 -Cl . - 0 -0 -0 -0 -0 -0 . f«0 - 0 -0 "0 r0 - 0 -0 - 0 - 0 -0 -0 - 0 - ■>0 0 0 0 - 0 -0 - .p 0 -0 "0 -0 rO r 0 . . *! 0 - 0 "0 - 0 35 -o . 0 - 0 . .■ "0 »0 «0 »0 >0 - 0 . *Q ... . sO -0 «0 -0 -0 ■ eO . rO -0 "0 -0 ff Q -0 -.0 *u0 -0 p O - 0 *0 ... . - 0 hr 0 «0 - 0 - 0 . n 0 -— 0 . 77 « T a b le in , 201 202 203 20 'I 205 206 207 208 209 210 211 212 213 21 <1 215 216 217 218 219 220 221 222 C8 W eak s e d i m e n t s P i t s VoJvr.v'. Cl -ii 1-5 C-■10 1) - ] 5 K -:]o j- ' ■ 4 4 -6 -0 10 *0 -ft “0 52 42 ft 0 46 10 45 20 37 12 - 0 “0 Ft 0 20. -0 -0 0 15 26 0 6 0 20 0 20 8 ft 0 16 - 0 -ft "0 34 8 ft 0 49 33 15 0 7 22 15 ' 40 25 -ft ■»0 -0 7 8 ft 0 0 13 -ft -0 70 17 15 0 25 0 ft ■ 20 35 23 ft 0 20 31 - f t •0 41 -0 16 "0 17. 18 ••ft • 0 G = 1791 , 9775 TOYAl. FOP Table C9 -0 •0 0 0 -0 -0 22 -0 25 -0 25 0 25 - 0 0 “0 0 50 . . . 0 "0 -0 38-60 61- »0 "0 -0 ” 0 o ....... «0 . . no 0 0 0 0 _. o._ . 0 ........ - - 0 0 -0 F>0 -0 -0 •?0 • <50 -0 - "0 »o . —0 "0 ■>0 "0 -0 "0 "0 »0 -0 "0 "0 . -0 -o "0 -0 0 0 0 0 27 . . . 0 o. o .... 0 0 0 0 "0 *0 -0 - 0 — IB 0 35 30 " 0 - u0 " 0 - - . . - " 0 . .. - o 0 0 0 0 0 . o — .. 0 30 0 0 0 0 - 0 ■ -0 - 0 ....... .*0 »0 -0 "0 -0 ■F-0 , r 0 . ... “ 0 » 0 & 0 " .'5 1- 3 5 20 4. - - GT Weak sediments Clusters V o I utci Cl in 201 202 203 204 205 206 207 208 209 210 211 212 233 214 215 216 217 238 ) (>■ i 10 52 46 37 46 fl 20 50 71 32 ■10 11- -].'j 44 - 0 42 10 12 • 0 0 0 0 <••0 8 70 25 23 31 41 13 3.7 0 35 20 16 13 17 8 -0 -0 0 45 »0 15 0 0 0 30 0 •* 0 15 0 0 "0 -0 -0 C - ::n 7 1 - 7 5 r.vj-j'.i "0 '... 0 0 20 "0 0 20 0 0 40 0 -0 0 20 0 ••0 1-:;5 3 8 - 6 0 6 ) - - 0 "0 -0 <*0 • 0 ' ffi ■ 5 - 0 ■ i-0 ■ *0 «F0 0 . _ 00 ..„ 0 0 0 - 0 0 '"O' " 0 — 1* 0 -0 *0 1* 0 . ..." 0n 0 O ' ' 0 22 "0 -0 *•0 «o • - 0 "0 25 “ fl fi 0 "0 25 ->0 " (i "0 - 0 25 27 0 ' ~ 0 D ' SO 0 0 35 O " fl • »0 " 0 ■« 0 -0 n 0 f) ft 0 0 30 0 0 50 0 0 0 0 0 *0 -n %0 ' ■ -6 -(I -0 -n ••0 •» 0 G = 1 5 0 7 , 5 0 9 9 fOF? T O T A L P G T -0 -n -0 «0 1*0 *0 -0 -0 78 T a b le C ll T o ta l v a ria tio n , Q u a rtso so Vol ' i Tr: Cl . -::-;: ID 301 302 303 304 305 306 307 30 ft 309 3 10 311 312 313 314 315 316 317 316 319 320 321 322 323 324 325 326 327 326 329 33 0 331 332 333 334 335 336 337 336 339 340 341 342 343 344 345 346 34 7 346 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 1-5 6 - 10 ] 1 •-3.5 9 . 31 23 14 15 43 . 1ft 29 14 23 22 13 17 23 15 2 20 21 11 9 3 16 25 19 6 12 17 9 16 ' 29 64 44 ’ 3 7 11 9 2 2 7 1 15 21 31 29 41 52 13 17 5 11 29 7 5 16 21 27 6 22 25 30 29 17 16 11 -m :>i - ">r. 2 6 - 3 0 :>,1- : r , .'56-60 t i ­ 0 0 0 .......6 0 ll 0 0 6 o - — 0 0 ... .... 0 6 0 0 0 0 21 0 0 6 0 0 o- - — 0 0 - . 3 0 - .... I) .... 0 6 12 0 0 26 0 0 15 0 40 o 6 24 0 0 0 .... o - ... 0 0 • •0 0 8 15 0 0 0 19 16 0 0 - . , . o .. ... 0 _ . . o 3 0 0 0 0 U 0 0 0 o - - ..... 0 - .. . . . 0 - — 0 0 a 0 0 0 0 25 0 0 0 0 d 0 - . 0. - ... 0 - — . o 0 0 20 6 0 0 0 0 0 0 0 6 0- . . o 0 .. ' 0 -._ 0 12 0 3 0 0 0 0 0 15' 0 .0 ... 0 .. 0 10 18 0 ...... 0 . . . 0 6 0 0 0 0 0 0 0 0 . 3 0 .. . . 0 .. 0 - . . . 0 10 25 0 6 0 0 20 0 0 0 1) 6 14 22 0 - .... 0 . - ■ 0 .. .4 2 n 0 0 0 0 37 30 0 0 20 23 0 - .... o . . .. o - 0 0 15 0 0 0 15 0 0 20 0 0 - 0 0 -.... 0 22 0 0 0 3 0 0 18 c 0 0 0 0 30 o 0 0 ■. 0 . 12 0 0 35 0 10 15 20 0 0 0 o _ .35 11 17 o - .... 0 0 6 0 0 0 10 0 13 0 0 . 0 ■ 31 0 - 0 0 - .... 0 6 ■ 0 0 6 0 0 0 d 0 0 .... 0 . 0 0 .. 0 .... o .... 0 0 a 0 16 0 0 0 0 0 p 0 . 0 . . .. o 0 15 0 ■ 0 ... o .... 0 0 0 22 0 20 0 3 0 ... . 0 .0 20 0 . 0 4 0 - 25 0 0 0 7 0 30 6 20 14 0 - ... 0 . . 0 -... 0 0 0 a 0 0 0 0 0 0 15 0 0 35 0 0 .... 0 .. _ 0 .. 0 - ... 0 - 0 0 0 0 0 12 0 0 25 .. 0 0 ..... 0 .... ... 0 __. 0 d 0 0 0 7 23 0 0 0 0 0 . 0 ... .. o 7 . a 0 - 0 . 0 0 6 0 n 0 0 0 0 .... 0 12 27 0 .... 0 0 . ..... 0 20 0 ft 0 30 0 a 0 0 0 ._ .... 0 -...... 0 20 15 25 0 .. 20 0 23 0 0 26 23 0 0 . 0 .. 0 0 0 25 . .0 20 a 0 17 0 15 30 0 0 0 n . .. 0 .....0 0 1? 0 0 0 0 0 0 0 33 40 ' 0 0 1 6 ' 12 0 0 . 0 . 0 0 . 0 0 16 3 0 0 0 0 0 0 15 25 27 0 0 0 0 ia 0 . . 0. ... 9 .... ....o. 0 .0 . 9 o • 18 15 0 0 0 0 0 22 24 20 - .0 .. o . . . .0 . . . . . . _ o - . . . . . o. 0 40 42 0 0 0 0 0 14 ii 0 0 . . . 0 ... . . . 0 ■_ . . 0 0 . 0 6 0 0 0 0 15 ' 0 17 2? 0 0 . . 0 - - . . 0 _. . o . . . . 0 0 15 25 0 0 d 40 0 G = 4913,507ft FOR TOTAL SET 79 Table C12 ID . 301 302 303 304 305 306 307 30 S 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 Quartsose HSU's V o l u v c Clni-r: n - ].:> i c 1-5 6 4 C ........6 37 27 58 32 47 27 37 -0 35 0 40 12 17 10 41 10 34 20 60 19 44 42 30 IB 26 11) 45 41 14 108 16 10 20 20 4 21 8 8 36 25 14. 60 93 16 28 30 23 16 36 17 16 21 40 31 3o 30 55 62 46 20 29 32 G 3 3 3 10 , 5£3‘J.2 FOR -0 12 39 15 -9 0 -fi 15 6 6 15 15 12 15 15 - 0 15 0 0 30 12 23 27 15 25 27 42 27 15 66 15 22 - 2 5 26 - 7. 5 :i i - :j 5 3 6 - 4 0 4 1 «0 "0 0 0 o0 40 1 6 • *0 »0 »0 25 20 «• 0 -0 -0 10 25 0 22 0 0 20 -0 -0 18 »0 37 0 -0 -0 •“ 0 . - 0 “0 -0 47 60 0 20 «0 -0 cO -0 n0 "0 20 **0 25 20 25 20 0 0 *■0 40 25 0 *•0 "0 "0 20 "0 -0 25 40 TOT.AL SET «t 0 ”0 1*0 • = 0 -0 "0 p o . .. p 0 =0 -0 " 0 • • *0 • ”0 *r 0 i 0 ■ "0 -0 -0 0 - 0 -0 -0 r. 0 »0 »0 -0 . «o . 70 -0 -0 . „0 - - 0 "0 “0 «0 »0 <-0 -0 ^0 . *0 . -0 -0 -HO - -0 »n “0 . *0 . . - o . .lO «0 . ■« 0 . . - >0 -0 —0 . »: 0 . - 0 «0 ••0 *0 . . . . »0 *0 -0 - . * o .. - " 0 - - *0 30 . . “0 ...... * o . -0 - " 0 ... '-Q 30 ... 0 30 •- 0 ►o - 0 •■0 - ~0 « o “0 30 "0 "0 . « ■0 -0 30 - 0 30 *■0 -o *0 -o «'U "0 bQ oQ “0 no •>0 •’ O “0 "*0 "0 42 -0 -0 ”0 ”0 -0 *0 **0 •*0 ••0 »0 B0 10 "0 »0 "0 "i 0 "0 "0 *>0 “0 ”0 -0 80 I T a b le 10 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 31 6 317 316 319 320 321 322 C13 Q u a rtz o se V o l . u w . Cl.-1.: .': } -•;> (>- 10 ] ) -3 6 40 37 27 105 59 0 72 40 12 17 10 41 ‘ 10 34 20 60 19 44 42 44 . 40 55 153 36 30 4 • 21 6 8 36 25 183 60 40 52 99 83 62 55 46 20 29 32 G -/:() Al*0 *0 "0 ■0 <*6 -0 •0 - .*0 . . - c — ,.*o 0 .30 1? 0 0 0 54 56 0 0 0 • 0 .. - o 25 "C . -0 6 20 »0 *0 *•0 -0 *0 ■0 -d "0 15 "0 ••o . - 0 • . - 0 18 -0 . 30 -0 25 0 0 0 42 0 . 0 • 22 0 0 »0 "0 20 30 -0 15 0 »>o . «o •0 -0 *0 15 -0 70 "0 27 0 - 0 55 0 -0 *0 -0 15 -o «0 *0 »• 0 "0 47 -0 -0 15 60 30 ~Q -0 -0 0 0 20 -0 -0 -0 -0 -0 30 -0 . -0 . -0 f0 -o . ” 0 12 "0 «0 «o 25 30 65 40 "0 0 . *0 . o . 30 53 2 5 20 -0 84 «0 ■ -0 ■ -0 25 40 -0 - 0 .. .-*0 -0 65 -0 20 -0 - 0 «0 -0 -0 15 -0 »0 25 - 0 . "0 *0 22 40 FOR TOTAL SET Quartzose Clusters Voliin-,: Cl.'!:." i « s (>■■JO n - .1 > * r-r> 40 37 105 72 40 50 20 19 68 183 12 36 18 3 52 99 55 46 29 P its 6 27 59 0 12 20 34 60 82 91 29 25 60 40 B3 62 20 32 .0 12 54 0 *0 15 0 15 42 30 30 12 65 53 84 66 15 22 !- 7 2C.-50 .'5 i ■L>5 3r,-/;c> A h »0 ”0 *0 30 0 0 56 0 n ■'ii " 20 ' " 2 5 -0 '•n »0 30 18 25 n 0 2? 0 30 20 n 0 55 47 •~ 0 60 30 20 0 ' -0 -n -0 30 25 40 2 5 ‘ ' 30 20 25 -0 40 -0 20 " «n *• 0 -0 "0 ' -n 40 ' 25 G t 1.552 , *t9 1 S F O R T O T A L S E T «6 »0 0 B0 *0 "’ "fl ‘ 0 "0 70 -0 »0 »0 «0 *0 *0 "0 «0 -0 eQ B0 0 &0 nQ n0 O' 60 *0 ■0 *0 60 "0 Q «0 0 *0 c0 b >0 42 r.0 ■0 «0 *0 »0 *0 ■ -0 *0 e0 *0* *0 -0 -0 i>o "0 81 T a b le ID 401 402 403 404 405. 406 40? 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 4?8 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 440 449 450 451 452 453 454 455 456 457 458 4 59 460 461 462 463 464 g C l6 - T o ta l v a ria tio n , Volrr.vi Cl a i'.': 1-o 10 n - ■15 -6 ' J2 15 0 26 36 '2 ? 16 12 0 24 16 12 15 0 27 29 21 o' 17 10 3ft 0 1 0 25 24 0 22 18 d 14 35 h 24 6 d 30 0 0 22 13 ri 16 8 6 17 18 0 26 6 d 33 0 15 6 3 a 3 0 d 17 22 0 25 10 d • 18 50 0 37 0 tj 13 7 d 19 6 27 17 10 15 0 20 fi 51 15 22 ' 40 0 a . 24 56 15 53 0 ri 6 8 14 7 0 0 66 12 ■fi 18 11 d 14 15 0 6 8 fi • 17 15 31 26 9 0 9 0 d 23 10 a 46 27 23 59 6 ■ 27 28 6 27 35 14 0 24 30 15. 15 22 a 36 24 27 24 23 15 27 17 ■ 15 27 6 a 16 ■ 8 a 13 20 a 24 0 a 26 13 d 13 23 d 13 12 ri 8 21 13 . 26 16 l? 30 t> 6 12 7 0 30 6 a 37 70 27 * 6 iin ,6 i6 9 ro;> 20 2 1 - 2 5 0 0 25 0 25 0 0 0 17 0 0 0 0 0 0 0 0 0 0 20 0 0 25 C 0 0 0 0 25 '0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 . ... 0 0 0 0 - -• 0 47 20 0 -- 0 30 0 18 0 0 0 o. 0 ... 0 0 0 0 0 0 0 0 0 0 0 .... 0 0 0 -25 0 0 0 0 ... 0 47 17 0 . 0 40 0 0 0 0 0 25 20 0 0 0 0 : 0 0 0 0 0 0 0 0 0 0 0 0 0 ------- 0 0 0 0 _______ 0 0 20 0 0 0 0 0 0 20 0 total set A c id ig n e o u 3 1 - 3 5 36- /IO A ). 0 0 0 0 0 - -0 80 . . o 0 0 0 0 ... 30 ...... 0 . . . . . 0 ------ o -------0 0 0 0 . 0 •..... 0 _ — 0 -----0 . 35 0 0 •0 0 ... 0 ..... 0 o -----0 0 0 0 . - 0 .... 0 . .. 1) -...... 0 0 0 0 0 0 0 - . 0 ..... 0 0 0 0 '3 0 - 30 ... .. 0 .... o ..... 0 -----0 60 0 0 0 .... o ...... - 5 7 . ... 0 ~ . 0 0 0 0 0 .... 0 ... o ------- 0 ---------0 0 40 0 0 ..... 0 ... 4 0 -------o 0 0 0 0 0 ______ 0 ....... 0 ------ 0 -------0 0 30 0 .... 0 ......0 ... 0 0— 35 0 30 0 0 . . .0 0 .... o 0 0 0 0 . o- . . . o o .....0 0 0 0 0 .. o ..... . 0 ..... 0 _______ 0 ---------■ 0 0 0 0 .... 0 . 0 ...... 0 ------ o . . . . 0 0 0 0 0 ..... 0 . .. 0 ...... 0 --------, 0 0 0 0 . 0 .. . 0 . .. . 0 ____0 _________ 0 0 0 0 30 .... 36 0 ...... 0 -----0 0 0 0 0 ~ 0. .... o — - 0 ________ 0 0 0 0 .... 0 . . . 0 ..... 0 o ------0 0 0 0 . o . .. 0 .... 0 .— 0 ------0 0 0 0 .... 0 -_ - 0 .. .. 0 ...... - 0 ..... 0 0 0 0 . o .... 0 - o - — -0 - ... 0 0 30 0 0 ... 0 - o - 0 -------0 0 0 0 . a ... 35. ... ... o . 0 ____ 0 0 0 0 35 0 . 0 0 . 0 0 0 0 0 0 0 0 .. 0 - . ... 0 •- .. o ------- o . .. . 0 0 0 0 ...... 0 . _______ 0 . .... o _______ 0 - ... 0 0 - 0 0 ....... 0 . . . . . 0 .... o. . .... o 0 0 0 0 0 fi 0 . . . 0 ...... 35 30 0 0 - 82 Table C17 Acid igneous, H S U ’s V o ] UV'.r ID 401 402 403 404 405 406 4 07 406 409 410 411 412 413 414 415 416 417 416 419 420 421 422 423 424 425 426 4 27. 428 429 430 431 432 J-5 G- 10 ] ] • ■ V j 48 41 28 40 44 21 18 10 47 42 59 • 20 13 52 34 25 59 6 6 6 42 • 32 50 55 32 i5 37 10 62 5l 109 24 15 6 23 66 23 20 26 41 10 32 5.0 5 33 63 20 45 46 59 48 54 23 36 21 50 13 25 ' 36 47 26 4? 13 67 76 16- 27 12 27 3B fi 6 0 0 15 0 -ri o 27 15 15 15 14 - 0 0 30 - 0 50 27 15 42 15 0 - 0 -0 27 -0 27 '*() 21 - 2 -> 2 6 - 3 0 25 o 0 25 - 30 0 «"0 -0 17 0 .. . . . . 0 • . o -0 -0 20 •5 U 25 0 60 0 0 117 25 0 -0 -0 20 0 0 0 -0 -0 - 0 30 0 0 30 0 0 47 “0 20 56 - 0 -0 -0 -0 -0 “0 -o "0 f o -0 "0 0 30 0 25 -0 0 - 0 "0 -0 47 17 »0 -0 “0 40 25 “0 20 30 0 0 0 0 0 0 0 0 «F 0 . -0 "0 -0 -0 -0 R 0 -u 20 *0 -0 - 0 . o. 30 20 G r. 4 6 1 5 , 0 6 88 FOR. TOTAL SL'f 3 ?,(>■ 40 61- 0 80 . * ■0 ■■ "0 • - 0 -0 ... 3 5 . e 0 ■ ■0 -0 - R0 -0 -0 • 0 -0 "0 -0 "0 0 80 -0 -0 *■0 - 0 35 "0 •*o . - 0 R0 -0 .. O0 ■ - 0 -0 -0 -0 -0 35 ••o ~ 0 . rO “0 -0 . -0 -0 - 0 -0 - 0 ... - 0 •*0 -0 ... 3 5 -0 • 35 -0 ...»0 p0 -0 -0 _ . IX 0 -0 . -0 -0 . . . 35 . . ... R0 - ofl ®0 «0 «0 «o •>0 ”0 *0 '0 n0 -0 *0 -0 c0 "O O0 -0 ”0 *0 "0 *0 "0 1o T0 -0 •<0 -0 -0 10 R0 "0 HO 83 Table Cl8 Acid igneous, Pits Vo)»vC! Cl nr-s 3-5 (>- JO ] ] - ] 5 1 0 - 2 0 21- 25 2 6 - 5 0 3 1 - 3 5 3 6-.60 A J ■ ID 48 28 31 62 13 34 6 6 32 50 26 76 92 20 41 10 99 71 B5 26 13 76 .........41 40 62 106 52 25 59 6 42 55 69 171 38 23 26 32 213 113 96 47 42 67 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 G = 3506,1958 Table C19 27 12 65 6 fi 6 15 0 -n 0 42 36 14 0 30 - 0 92 57 n 27 -fi 27 FOR 0 0 17 20 0 0 20 0 -0 0 20 56 -0 0 0 -0 77 0 0 20 «0 20 . 25 25 0 25 0 . 25 -0 0 “0 0 47 m0 F0 0 25 . *i c 72 0 c “0 -0 0 0 30 0 • -0 60 117 -0 0 °0 30 30 -0 -0 - 30 *0 *0 -0 30 0 ►0 ”0 30 0 f0 35 »0 *■0 •0 -0 . 0 -0 -0 35 T>0 w0 35 »0 -0 •>0 . 35 35 -0 -0 35 . 00 r-0 -0 -0 - 0 pQ -0 80 -0 -0 -0 -0 - 0 - 0 -0 pQ -0 -0 -0 ■>0 -0 "Q -0 _p 0 ■»o v .- ^ 0 «0 "0 "0 «0 "0 -0 «0 . *i0 «0 . _. " 0 -0 .. .. n 0 m0 ... " 0 •>0 -0 *>0 - - 10 TOTAL SET Acid igneous, Clusters Yo)iiv:: Cl. ■JD 41 40 62 10 6 52 84 6 42 124 209 49 32 213 tl 3 96 47 4? 401 402 4 03 404 405 4 06 407 408 409 410 411 412 413 414 415 416 417 416 G 10 J 1••15 1C -20 }-> 67 = ~ 27 12 65 0 0 15 48 28 31 62 13 40 6 32 73 167 n -0 4? 44 30 -0 92 57 61 10 9o 71 85 26 13 76 3120,903 6 0 27 -0 27 TOR l 25 25 0 '0 n 17 20 0 ■ 20 0 ' »0 20 ' 56 0 -0 77 ■ 0 0 20 -0 20 TOTAL 26-:;o 3 i.- ‘i.5 36- 60 61 25 n 25 n o fi 47 »n 25 V 0 72 C n “ II -n 0 SET 0 30 0 ' -n 6 35 ■6 60 “0 1 1 7 ■ *0 0 0 «0 ' -0 ' 60 35 ■ '“ O'" - 0 30 35 »n ' “ 0 «n -0 3 ft ' 3 5 (I 35 -0 ' "0 -0 -0 ' 30 35 80 *0 *0 A0 " t?Q “0 80 • o0 -0 -0 «0 A0 *0 t/0 *0 *0 o0 «0 O *0 p0 p «0 “0 "0 «o w0 ** 0 »o rO o0 *0 p0 “0 •0 »0 ■0 84 Table C21 Total variation, Ba3ic igneous Volin':'. OWit'S 11) 1-5 (>■- 1 0 n ~ J 5 10 - 2 0 71--25 2 6 - 3 0 3.1 -.'15 3 6 - / ( 0 A 501 ' ' ~ 4 5 ’ 30 502 19 . 503 17 504 24 505 506 30 507 23 28 506 38 5o 9 510 32 16 511 13 512 20 513 9 514 515 ' 21 35 516 517 22 12 510 519 30 33 520 12 521 7 52 2 12 523 524 ' 22 22 525 526 19 16 527 19 520 529 22 ’ 23 530 10 531 53 2 17 533 12 534 34 2 535 536 12 , 537 20 9 536 . 539 8 0 54U 541 1 7 542 35 543 34 544 38 545 546 28 20 547 34 546 36 549 6 550 23 551 19 552 17 553 55 4 12 24 56 5 556 26 13 557 556 ’ " 12 559 ' 21 26 560 561 30 562 12 29 563 564 13 0 60 46 0 0 30 0 0 .... 0 - - 0 .....0 ----- 0 6 0 6 0 ■ 0 0 0 0 0 6 0 0 36 - 0 ........ 0 ...... -0 0 0 ... o 12 0 0 15 0 0 0 0 6 p.... _ . — 13 o .... 0 : 0 IS .. 0 0 0 - 0 0 6 0 0 0 0 0 ..; - o ...... o ... 25 o : 0 0 6 16 0 0 0 0 ' 40 n 0 . 0 .... o - .. . 23 0 0 .... 0 - . 0 6 0 0 0 0 0 0 6 0 0 n .....— --------0 0 • :. 0 0 0 0 0 0 6 0 ' 0 0 0 0 o . ------------------- 0 6 0 0 0 0 0 0 6 0 0 12 0 0 (I 0 o ................................ 14 • Q 0 0 0 ■ 6 0 0 0 0 0 0 n 0 0 ---------------------0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 o ---------------0 0 0 36 14 0 0 0 0 0 .0 0 0 0 0 0 .... o - - 0 ------------------------16 0 0 15 0 0 52 0 0 0 0 0 0 o .... 0 . . 0 — 13 - 0 n 0 (1 0 0 22 25 0 30 0 0 o -------------------------0 ... 0 / 0 .- o 0 0 0 0 20 0 15 0 0 0 0 . ■ • 0 • - - o .. . 20 o 0 0 - 0 0 0 0 0 0 0 1? 0 o . ... . - . . 6 . 0 .. o ■ ... 0 ... 0 . 0 0 n 0 0 0 0 0 6 0 0 - 0 .... 0 - • - ................... ---■ 33 0 . 0 • 0 0 0 19 0 0 0 0 27 0 8 0 3.5 o ...... 0 ... 0 ------ 0 0 . 0 10 0 0 0 0 0 0 0 . - . .... . 24 0 : o . - 25 .... o ..... 0 .... o 0 0 0 0 0 6 0 0 0 -...... 0 - - 0 -------------------------3.2 ' 0 ■ 0 . . o 1? 0 14 0 0 0 0 0 6 0 0- -■ 0 . o ....... 0 ... 0 -— 0 ■ 0 0 0 0 0 0 0 0 6 0 0 0 0 0 6 0 ..... o ... 0 10 0 0 0 n 0 0 0 16 • 6 0 25 . 0 • 0 0 0 6 0 0 0 12 0 0 0 ...... 0 ... o 0-.. 32 n. 0 . 0 0 0 6 0 ri 0 0 0 0 ...... 0 0 ----20 6 0 . .. 0 0 0 6 0 0 15 0 0 0 0 ..... o 7 39 o ...... 0 20 0 0 7 0 0 20 0 0 • 0 10 o ... 0 .... 0 ----- o _ 25 0 0 0 6 0 0 0 0 0 0 -------26 0 ... 0 ... 0 . . . . 0 ... 0 o ■ 0 . 0 0 0 0 0 0 0 0 13 0 0 0 Q 0 d 0 0. ... o .... fl 23 0 . 0 ' f) 1 0 13 1 ’0 o; •’ ■ ' 0‘" ■ o 1 r 0 II 1 0 ’ i! D 6 15 • 0 ~ - -0 . ... 0 ... .. 0 ... ■ o ... . 0 —■18 0 0 12 20 0 0 0 6 0 -- 0 n 0 ii . 0 .... 0 ............7 0‘ o' O' 0 0 0 - o1 30 0 ... o' . o ______________________ 27 O' O’ •o 14 n 0 0 '0 o' 0 O' ■ G. s 24 7 6 , 8 26 0 F OR TOTAL SET fl 1 I II ...... ll 1 II (• '1 ;l 8£ Table C22 Basic igneous, HSU's Volur,?:*. Clat'-a 5 :i 6 -/iO 4 1 1-5 C - J O ] 1- 1 5 J 0-20 21 - .?:> 2 6 - 3 0 3 «0 75 ♦>0 «0 501 0 52 30 0 60 « 0 - "O ..... •<0 36 36 -0 502 D0 1? “0 w0 n0 54 *0 *0 503 20 «0 *0 -b *0 -••>0 33 -*•0 .... «J 0 *0 - O0 "0 504 51 0 ”0 505 41 40 0 0 70 ri 0 r0 ■D 506 29 «• 0 ."0 -0 «0 "0 -0 “ 0 • •’ O 507 29 "0 12 -0 "0 “0 “0 -0 -0 ... -0 56 508 20 "0 12 * o - - «"0 *r 0 509 34 -0 "0 -0 -0 -o ”n -0 -0 - -0 . .. "0 63 14 510 36 *• 0 “0 *■0 -0 1.9 -0 511 16 15 "0 -0 -0 »0 *0 34 512 25 «■0 «0 - "0 "0 *• 0 "0 -0 513 25 "0 29 -0 -0 30 41 0 •• 0 ‘0 35 514 40 “0 "0 •*0 "0 15 -0 515 «0 ">0 45 6 -0 12 >0 .-o ”0 . r 0 - -0 516 27 13 -0 "0 -0 -0 <■0 4? 517 46 "0 27 *•0 ”0 -0 ~0 14 "0 *0 518 34 -0 -0 0 25 0 *0 IQ 29 -0 51 9 12 -0 12 -0 "0 »n 520. 8 14 -0 "0 . -0 . -0 ... . -0 -fi "0 0 “0 ■*0 521 -0 - 0 "0 ~b -0 fj -0 69 522 25 ~c - '0 0 29 -0 . o "0 523 66 • 30 1? - 0 n -ft 12 -ft 14 15 -ft 45 1? 42 12 . -ft -6 12 54 -ft 27 -ft 27 10 - 2 0 b 0 -D 0 -0 -0 -0 -0 -0 -0 0 -0 0 "0 -0 -0 0 40 -0 20 -0 -0 V 21-25 0 »0 -0 0 -0 -0 -0 -0 -0 -0 25 -0 25 -0 -0 “0 25 25 -0 -0 -0 - »C 20-20 3.1.-35 3! Wi O . 4 1 - 60 ... » o *0 -.-0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 •*Q -0 -0 -o . -0 «o . . '0 -O’ *0 -0 *0 E0 ■0 - ■ 0 -0 "0 -0 0 „ . 40 - - *0 . -0 -o -0 -0 • -0 -0 -0 "0 -0 -0 -0 -0 -0 -0 "0 -0 -0 -0 -0 -0 “0 ”0 “ 0 - -o -0 -0 -0 -0 . -0 "0 ■ -0 -0 -0 -0 . -0 - "0 -0 "0 -0 -0 . -0 -0 -0 -0 *0 -0 -o . -0 -0 *0 -0 -0 . . - 0 -• • *’ 0 . o o o o o o o o o o o o o o c a o o o o o o o ID FOR TOTAL SE= T Basic igneous, Clusters Vo] r.vcf C l a p s ):> (,-I0 31-■15 1.0 - '• f ! 21-25 26-20 31-2.5 3r.-/|() A 1 - ' 5 75 36 105 99 29 90 63 19 110 132 37 8 189 66 104 47 42 42 ' "52 36 61 41 12 20 36 16 94 80 26 '0 69 30 «3 26 13 44 3 0 "" 0 ■-O' 12 -0 "0 0 -0 1? 14 15 45 54 12 -0 12 0Q - 0 -'0 ••0 0 0 -0 -0 0 ' 40 -0 ►0 20 -0 "0 -0 27 0 0 54 27 0 . 0' «n 60 ■**0 - 0 " - 0 -0 »0 »0 ' «0 -0 ’ *0 ' ' - n " -0 -n - 0 - 0 -n 25 25 -0 -ft «n -n ' -0 25 -n - n ■ ‘ 25 -ft - n -0 -n " -ft -n » 0 ■ »n G = 1 3 2 5 , 3 5 3 4 F O R T O TAL SET 0 - 6 -0 -0 *• 0 "0 -0 "0 "0 «0 -O' -0 "O ' -0 • -0 A0 60 (i0 40 *0 00 *0 • *■0 a0 *■0 ®0 « 0 ....... ' 150 n0 ■0 »0 » 0 ... "0 <•0 «0 p0 *0 *0 -0 " *<0 «0 "0 «0 *0 •0 "0 vQ -0 I>0 ■ *0 " ... *0 87 Table C26 Total variation, Foliated metaraorpbic Vo)u"':: Cla?r. 3D 601 604 605 606 6 0 ‘/ 609 610 611 612 613 614 61 ? 619 620 623 624 625 626 629 631 632 633 635 641 644 646 64 7 64 9 650 65 U 659 661 662 663 66 4 G = 1-5 6 --]0 1 3 - 3 1) 1 6 - 2 0 2 ft 3 5 3 3 0 0 0 0 0 0 1 0 3 0 0 8 2 0 1 10 3 0 5 . 0 0 12 0 6 1 0 0 0 2 0 3 0 5 8 2 0 5 0 3 0 0 1 5 0 5 0 9 0 15 0 5 0 3 ' 0 4 0 1 0 2 0 6 7 •5 23 0 ' 10 7 1 9 , i6722 ft 0 ft 12 15 d 6 ft 6 6 0 fl ft 0 ft ft ft II 0 ft ft 0 ii 15 ft ft ft fl ft ri 0 0 ft FOfi 23- 25 2 f>--3 0 0 0 0 - 0 0 0 0 • 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 20 0 0 0 0 . 0 0 o . 24 0 0 0 0 0 0 0 - 0 o ..... 0 ■ n .... 0 - o ....... 0 a . - 0 0 0 0 0 0 •0 0 0 0 0 0 ..... 0 0 • o 0 0 0 0 0 0 0 - o ..... TOTAL 5LT 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .0 0 OfWiO A 0 0 0 ... 0 0 ..... 0 0 0 0 0 . 0 ----- . o ---------------------------- 0 0 0 - -0 0 0 . .. 0 0 . ---------------.------- — 0 • 0 0 .... 0 --------------------------n 0 0 ...... 0 ...... 0 .... - o ..... 0 0 0 0 ... o ------ o ----------------------------0 0 0 0 --------------------------. . . . 0 ..... 0 0 0 0 . . . . 0 ■- 0 ..... o ------------- ------------- 0 0 0 ... 0 ... 0 - - 0 ------------- -------------— 0 0 0 o . ... .... 0 -.-.0 0 0 0 .... 0 .. . 0 - . 0 __________________ 0 0 0 .... 0 ... .. 0 .... 0 — ... 0 0 0 0 .... ............. —------- — ...... 0 . . . . o 0 0 0 .... 0 ------ o ........ o __________________ 0 0 G _. . 0 ........ 0 ...... 0 ----- 0 0 0 ..... 0 o ......... o ___ _______________ 0 0 0 o _________________ ..._. 0 ----- 0 0 0 , 0 88 Table 027 Foliated metaroorphic, HSU’s Vol uv: ' . Cl.:'--:'. ID 601 602 603 604 60 5 606 607 609 610 612 613 615 610 617 610 621 622 623 624 625 6 29 63 0 631 6 32 G c ]-j (,- 2 3 8 3 4 2 4 5 0 1 5 5 7 3 1 5 5 9 15 0 4 1 ' 8 5 *0 -.0 6 *• 0 0 27 “0 -0 0 -ri ri -6 (i -f) ri 0 0 ri 15 0 -0 0 ri -0 - ri 26-30 :u-:s5 36-40 .41- »0 *0 ■ 0 '■' ■ « o ' .... “ Q" ■-0 *0 "Q .. •’ 0 * 0 - - "0 *0 »0 ■0 *• 0 "0 ■0 0 ... o . ...- o 0 ... u 0 - o -0 "0 '0 -0 "0 *0 • «i0 "0 '0 "0 "0 "0 • -0 - 0 -0 -0 ■0 0 0 Q 0 0 -0 •*0 -0 "0 “0 -0 -0 *0 ' 0 •>0 *0 20 -0 -0 "0 "0 "0 -O' -0 - o . no 24 •>0 0 -0 ^o -0 *■0 -0 ~0 . 0 . 0 0 0 0 0 0 0 0 0 0 20 0 . o .. . 0 0 0 0 0 0 0 0 0 0 0 . 0 0 . 0 0 0 0 0 0 0 0 0 - 0 r. o ... r o . f-0 ... * 0 ”0 0 0 0 0 0 0 . 0 0 . . 0 . ... 0 0 0 -0 “0 "0 - 0 - 0 «■0 "0 . 50 ■?0 . 'o «■0 «0 TOG TOTAL SET Cl 0- Hi 2 3 11 6 4 5 0 1 5 1? 4 5 29 8 619 4 62 0 621 622 8 5 G = -0 21-25 Foliated metamorphic, Pits Vo) ir, -J1) 11- 3 .*> 1 6 - 2 0 10 1 ] I■■35 1G-. 20 2.1-•• r‘ '•0 -0 -0 0 10 0 10 0 0 8 0 «- 0 0 ■•0 *■0 0 7 -0 38 -ri -ri -ri -0 ” • »o n0 «0 » (1 -0 0 *>o *•0 .•0 ••0 0 -o 20 0 0 20 "0 -0 0 24 -0 ”0 -0 15 -o »o -0 - ri -ri ri -0 "0 0 -0 -0 “0 -0 0 *•0 -0 -0 27 -ri ri ••ri fi ■ ri ri ri 5 6 6 t 9 114 r o n T O T A L S E T 26-20 - -0 -0 "0 ...o ■’0 ■ 0 ’0 "0 0 "0 -0 " 0 "0 ■<•■0 ”0 .. 0 - 0 -0 31 -35 2 ) 41- «0 r<0 «0 -0 i;0 -0 0 n [\ s0 «0 -0 0 . "0 ■ -0 -0-. «o 0 0 t-0 • -"0 w0 *• 0 - ®0 M O' "0 «0 -0 "0 -o ... 0 0 *»0 - 0 *<0 '0 -0 «>0 «o «0 «0 *0 . 0 "O '’ O o. *0 -0 °0 -o "0 ■»o 0 -0 ^■0 89 Table C29 Foliated metamorphic, Clusters Clovo: Volin'"! 6 - JO 3D 3-5 6 01" 682 683 684 6 8b 686 607 689 610 612 613 614 615 61.6 617 618 ....... 2 G 11 6 4 5 8 1 16 5 0 a " 0 0 •> 0 •5 0 0 29 8 4 1 8 7 D 3a 5 s « 0 -0 -0 27 .0 0 « c 0 0 -0 15 -0 •» 0 0 -0 "0 * 0 » 0 8 10 0 18 3 FOR 506,4301 Table C30 11) 1-5 616 620 617 64 0 618 614 615 G -- 2 1 - ?:> 2 6 - 3 0 » 0 " ' -0 " « 0 - 0 -0 c " 0 2020 » 0 -0 « 0 " 0 ' 0 -0 « 0 total - 8 -0 -8 - (j - fl 8 *0 -8 24 *11 »f l *- 0 - 0 0 vf l •0 get i 53 0 -29 5 . 8 *> n •" o -n fl . . . ' -e « o - 0 « 0 n6 G- ” •0 n -n "\-0 #0 *0 B0 6 U <•0 0 c Q ' *0 . -0 0 ...... -0 p 0 " 0 " 0 p0 *• 0 "0 « 0 Ml -n " 0 -n - 0 -8 - 0 -8 nf l - n “ “ r> 0 - n - 0 0 p6 " 0 ' *0 « 0 cQ *0 - 0 0 »0 v0 ....... ................... - 0 0 PO p0 - ... — 26-30 31-35 3 l6-::0 4 « 10 - 2 0 3 1-3 5 OF TOR TOTAL SET FREEDOM 4,l3b8 0 .-0 -0 f 0 -0 “ 0 - .. - 0 ----- •’■0 -------"0 -0 "0 - -0~ - 0 --- - 0 -0 -0 -0 0 0 - 0 -- - - 0 — APPENDIX D, DETAILED DISCUSSION AT PIT LEVEL I APPENDIX D Between Pit 12 and Pit 13 The limestone and weak sediments categories both show significant differences between pit 13 and pit 12 (cluster 10)« Both of these compositional categories are probably from within the lower peninsula and are not very durable,, traveled® Thus, they are very likely not far They probably do not lie very far from their subcrop, thereby strengthening the idea of mixing rather than long distance transport for individual clasts. The difference in skewness values (Table 9) shows that both categories indicate a more mature state in the pit 13 position (Figure 1|). This is in agreement with their relative positions on opposite sides of a subcrop contact which provides for the contribution of additional material to the more southerly pit 12 position. The foliated metamorphic compositions are even le3S durable than the above discussed compositional categories and, as they are not of local derivation, they are indicators of the later or last episode of energy flux to effect these positions. As might have been expected, the skewness values (Table 9) for the more southerly pit 12 position indicate greater maturity for the foliated metamorphic material® This emphasizes the reason for the differences shown by the previous 9.0 91 two categories: 1) the addition of new material of probably local source and 2) the mixing and remixing which would have surely decreased the amount of less durable material if an additional influx was not available, in this case the foliated metamorphic compositions* Field observations tend to support this conclusion of very poor relative durability of the foliated metamorphic compositions, as the individual clasts were in almost every instance in an advanced state of deterioration. The quartzose category provides the only other compositional category for which significant differences were found for the pit 12 and pit 13 comparison. The skewness values (Table 9) for the quartzose category show the pit 13 position having greater maturity. This is the same result as for the limestone and weak sediments and, in this case, is most likely not due to the additional incorporation of quartzose material between pit 13 and pit 12® The tremendous durability of the quartzose compositions, relative to the limestone and weak sediments, suggest long time preservation in this environment rather than addition from a nearby subcrop. Between Pit 1J+ and Pit If? Pit 11+ is northwest of pit 15 and both are located in the central portion of the major spillway (super cluster 2, cluster 11, Figure 4). The limestone 92 and acid igneous categories are the only compositional categories which show significance# This provides a comparison of a local, not very durable derivative and a non local, very durable compositional category# The skewness values (Table 9) for both categories suggest the pit Ilf position having greater maturity# It should be noted here that the skewness values for the more durable acid igneous compositions are negative, whereas they are positive for the less durable limestone compositions# This does not say that this negative versus positive skewness could serve as an additional measure of durability# However, as can be observed for the compositions showing significant differences between pits 12 and 13, there does seem to be a relationship to the relative durability# The negative skewness indicates the drawing out of the left tail® In this case, the smaller size by volume clasts are fewer volumetrically* Thus, lithologic species which are not durable would decrease in size when destructively acted upon, thereby increasing the volume of smaller size clasts# Conversely, the more durable species would provide a lesser volume of smaller size clasts under similar destructive circumstances# In both cases, the skewness values suggest that influx of additional material, resulting in mixing of older with newer material, is responsible for the indicated pattern# 93 Between Pit 6 and Pit 7 The acid igneous category is the only significant compositional category for this comparison. Pit 6 and pit 7 are in cluster 6, which is the easternmost cluster in the minor spillway (Figure if.)* north and east of Pit 7« Pit 6 is slightly The skewness values (Table 9) show a change from negative skewness to positive skewness going from pit 6 to pit 7 or in the direction of the considered flow for this minor spillway. This increase in volume of smaller size cla3ts of acid igneous material suggests attrition with little addition of newer material. However, it is felt that, due to the small proportion of acid igneous materials in these samples and the lack of significant results for any of the other compositions, this result 3hould not be relied upon too heavily. APPENDIX E, DETAILED DISCUSSION AT HSU LEVEL APPENDIX E Between HSU 5 and HSU 6 HSU 5 and HSU 6 are located in pit Ij., which is the most western pit in the minor spillway (Figure 4)« is the stratigraphically lower unit (older). HSU 6 The 3kewness values (Table 10) indicate an increase in the volume of larger size material from HSU 6 time (older) to HSU 5> time for two (weak sediments and foliated metamorphic categories) of the three compositional categories showing significant differences* The proportion of basic igneous material in HSU 6 precluded the computation of a valid skewness value* This result points to the vagaries of local scale transport and* in the case of foliated metamorphic compositions, hints at the effect of local scale process intensity on these nondurable lithologic species. Between HSU 13 and HSU li|. HSU 13 and HSU llj. are located in pit 11, which is in the eastern part of the central portion of the major spillway (Figure !{.). HSU 13 is the older unit. The weak sediments (local and nondurable) and acid igneous (non­ local and durable) are the compositional categories showing significant results. As in the above comparison, the skewness values (Table 10) indicate an increase in the volume of large size material from older (HSU 13) to younger (HSU ll|.) for both categories. 9k It should be pointed out Table 10. Skewness Values at the HSU Level HSU Compositional Category5 Weak Sediments -0.91 1.23 13 1.0 -0.13 0.30 Quartzose Acid Igneous 1.02 Basic Igneous 1.01 Foliated Metamorphic 6 ll* 15 16 -0.61 0.73 17 18 -0.93 -0.99 -0.26 0.50 2 .41* -0.22 -0.83 22 23 21* 0.18 1.75 25 26 -1,38 -0.53 0.82 0.88 0.01 -0.51* 0.58 1.06 -0.02 -0.27 0.28 1.58 0.06 -1.1*3 0.53 0.21* 0.53 1.09 0.3l 0.35 1.21* 0.77 0.07 -0.1*9 1.23 1.31 0.76 -0.11 0.27 -2.32 -1.77 0.61* -0.75 -4.58 -0.55 96 that this is not actually an increase from one HSU to the next. It is merely a shift in the size frequency di stributions« Between HSU 15 and HSU 16 HSU 15 and HSU 16 (pit 12) are located in the eastern part of the central portion of the major spillway^ slightly west and north of H S U ’s 13 and 11+ (Figure 1+), HSU 16 is the older unite These composi­ tional categories provided significant results. Of these* it was not possible to compute valid skewness values for both H S U ’s for the foliated metamorphic and weak sediments categories® The skewness values for the acid igneous category (Table 10) indicate greater maturity for the younger (HSU 15), This may be a reflection of the mixing and remixing with each successive pulsation of glaciofluvial energy. Between HSU 17 and Hr ' 18 HSU 17 and HSU 18 (pit 1 3 ’’ e located to the north and east of the previous HSu*s compared (Figure !+)• HSU 17 is the older unit. significant differences. Four compositions show It was not possible to compute a valid skexmess value for both HSU's for the foliated metamorphic category. The skewness values (Table 10) for the remaining three compositional categories, weak sediments, quartzose and basic igneous indicate greater 97 maturity for HSU 17 (older) for all three categories. Considering the difference in durability and the local and nonlocal derivation for these compositional categories, it is apparent that at this local level a balance of the effects of depositional and transport process intensity is obtained. Between H S U 8s 22, 23 and 21+ H S U 8s 22, 23 and 2ij. (pit 17) are located in the northwestern part of the central portion of the major spillway (Figure Ij.)® HSU 22 is the oldest unit and HSU 21|. is the youngest unit® The quartzose, basic igneous and foliated metamorphic categories yield significant results. It was not possible to compute a validskewness value for the foliated metamorphic category for two of the three HSU*s. The skewness values (Table 10) for the remaining two categories indicate an overall increase in maturity from the oldest to youngest. The similar results with the disparity here in relative durability is again evidence of the addition of newer material (the presence of the very weak basic igneous) and reworking. Between HSU 2£ and HSU 26 HSU 25 and HSU 26 (pit 18) are located southwest of the minor spillway in an upland area (Figure 1;), HSU 26 is the older unit. The weak sediments, quartzose, 98 acid igneous and basic igneous categories show significance. The skewness values (Table 10) for all four categories indicate greater maturity for the older unit (HSU 26). Again, the disparity in source and durability demonstrate by similar results the continued addition and reworking of the glaciofluvial sediments.