THE IMPLICATIONS OF LAKE HISTORY FOR CONSERVATION BIOLOGY
Kristine Alexia Ciruna
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Zoology, University of Toronto
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ABSTRACT
Ciruna, Kristine Alexia. 1999. The implications of lake history for conservation biology. Ph.D. dissertation. Department of Zoology, University of Toronto, Toronto, Ontario.
The historical formation of aquatic ecosystems and the regional environmental processes acting at the watershed level are important components in the conservation of aquatic ecosystems which are often'neglected. This thesis integrates the fields of cornmunity and landscape ecology. conservation biology, multivariate statistics and geographical information processing in an attempt to examine the ecology of fish communities within 550 inland lakes in the Great Lakes - St. Lawrence basin of Ontario with respect to their local and regional environment and historical lake formation. These lakes have been grouped into six geographic regions: Wellington, Bruce Peninsula,
Lacloche, Sudbury, Wawa, and Algoma.
Two new constructs have been created which describe lakes based on their historical formation: "relict" and "solus". A relict lake is defined as a lake that was once part of a large waterbody presumably sharing a common species pool that has since receded to form a number of smaller lakes. A solus lake is defined as a lake formed in isolation which was never a part of a larger water system or species pool.
Differences in fish community structure, environment, and species - environment relationships were examined between proximally paired relict and solus lake regions using a suite of rnultivariate statistics. The results of this study conclude that relict and solus lakes have significantly different local and regional environments, fish comrnunity structure, and species - environment retationships. Striking similarities were also found Abstract
between relict and solus lakes and landbridge and oceanic islands, respectively,
regarding historical formation, extinction and colonization potential, and comrnunity
structure. The results strongly suggest that solus lakes and their surrounding
watersheds represent ecologically distinct aquatic systems within Ontario containing
unique environments and fish species assemblages. Recommendations are made for
the inclusion of solus lake regions as provincial "Areas of Natural and Scientific Interest".
Therefore the recognition of lakes as historical constructs which 1 term relict and solus
provides insight into conservation planning for fish biodiversity. Acknowledaements
ACKNOWLEDGEMENTS
I am very grateful to have had the opportunity to doing my graduate studies at the Department of Zoology, University of Toronto. This institution has provided me with an academic program that helped stimulate my intellectual growth and a scientific community which encouraged me to develop new ideas.
First and foremost I would like to thank Professor Harold H. Harvey, my supen/isor, for his ünending encouragement and guidance in the development of the ideas and concepts contained in this thesis. It is an honour to have been mentored by such an outstanding scientist.
1 would also like to thank Professors Ann Zimmerman, Jyri Paloheimo, and Ed Crossman for their helpful discussions pertaining to the species and environment analyses used in this thesis, their ongoing support and their great sense of humour.
I thank the following individuals for providing sorne of the data and tools used in this thesis: Professor Larry Band, Department of Geography, University of Toronto; Professor Terry Carleton, Faculty of Forestry. University of Toronto: Mr. George Gale, Ontario Ministry of Natural Resources; and Mr. Erling Holm, Centre for Biodiversity and Conservation, Royal Ontario Museum.
I am grateful to al1 those at U of T who directly or indirectly have given me the benefit of their experience. Especially, I want to thank al1 of my rnany friends in the Dept. of Zoology for al1 of the great times and memories. 1 am very fortunate to have such great friends!
Most of all, I want to thank rny parents lrene and John and my brother Brian who supported me throughout my academic career. 1 could not have done it without your help.
Kristine A. Ciruna Table of Contents
p.
TABLE OF CONTENTS
Page
ABSTRACT ...... ii ACKNOWLEDGMENTS ...... iv LIST OF TABLES ...... xii LISTOFFIGURES ...... xvii
CHAPTER 1 THESIS INTRODUCTION ...... 1-1
I. OVERVIEW OF FRESHWATER ECOSYSTEM CONSERVATION IN CANADA ...... A . Water Resources ...... B . Canadian Freshwater Fishes in Peril...... C . Dichotomy of Consewation...... D. Causes for Decline of Freshwater Fishes ...... E. Needed Research and Consewation Management...... II. THIS STUDY: A STEP IN THE RlGHT DIRECTION...... A . Objectives ...... 1. Chapter Two ...... 2 . C hapter Three ...... 3 . Chapter Four ...... 4 . Chapter Five ...... 5 . Chapter Six ......
CHAPTER 2 RELICT AND SOLUS LAKES ...... 2-1
1. INTRODUCTION...... 2-1 A . Definition of Relict and Solus Lakes...... 2-1 II. Relict and Solus Lakes Throughout the World ...... 2-2 III. Glacial Solus Lakes Within the Great Lakes - St. Lawrence Basin...... 24 IV. Glacial Relict Lakes Within the Great Lakes - St. Lawrence Basin ...... 2-6 V . Evidence for the Formation of Glacial Relict and Glacial Solus Lakes..... 2-7 Table of Contents
Page V . Evidence for the Formation of Glacial Relict and Glacial Solus Lakes ..... 2-7 VI . CONCLUSIONS...... 2-8
CHAPTER 3 AN EXAMINATION OF ENVIRONMENTAL DIFFERENCES IN RELICT AND SOLUS LAKES WITHIN THE GREAT LAKES . . ST . LAWRENCE BASIN ...... 3-1
INTRODUCTION...... 3-1 A Objectives of This Chapter ...... 3-2 1. Defining Environmental Variables ...... 3-2 a) Ecological Boundaries...... 3-2 b) Local and Regional Environmental Variables ...... 3-2 c) Relationships Between Local and Regional Environmental Variables ...... 34 MATERIALS AND METHODS ...... 3-6 A Study Lakes ...... 3-6 I . Databases...... 3-6 B Study Variables ...... 3-8 1. Local Environmental Variables ...... 3-9 2 . Regional Environmental Variables ...... 3-12 C Statistical Methods ...... 3-15 1. Normality. Linearity and Transformation of Environmental Variables ...... 3-15 2. Wilcoxon-Mann-Whitney Test ...... 3-15 3 . Canonical Correlation Analysis ...... 3-15 4 . Pearson Product-Moment Correlations...... 3-17 5 . Principal Component Analysis ...... 3-17 6 . Discriminant Analysis ...... 3-18 RESULTS ...... 3-20 A Preliminary Data Analysis ...... 3-20 B Merging of Datasets...... 3-21 C Relationships Between Environmental Variables ...... 3-21 1. Group Comparisons of Environmental Variables ...... 3-21 2. Individual Comparisons of Environmental Variables...... 3-25 Table of Contents
Page D Lake Environmental Composition...... 3-27 1. All Relict and Solus Lakes Combined...... 3-27 a) Environmental Differences...... 3-27 b) Statistical Significance of Environmental Differences...... 3-32 2 . Comparisons of Proximally Paired Relict and Solus Lake Regions 3-34 a) Wawa and Algoma Lakes ...... 3-35 i. Environmental Differences...... 3-35 ii. Statistical Significance of Environmental Differences ...... 3-38 b) LaCloche and Sudbury Lakes ...... 3-39 i . Environmental Differences...... 3-39 ii . Statistical Significance of Environmental Differences...... 3-43 c) Bruce Peninsula and Wellington Lakes ...... 3-44 i. Environmental Differences...... 3-44 ii. Statistical Significance of Environmental Differences...... 3-48 IV DISCUSSION ...... 3-50 A Environmental Differences Behveen Relict and Solus Lakes ...... 3-50 1. Regional Environmental Differences...... 3-50 2 . Local Environmental Differences...... 3-51 V CONCLUSIONS ...... 3-53
CHAPTER 4 RELICT AND SOLUS UKES AS LANDBRIDGE AND OCEANIC ISLANDS: AN EXTENSION OF THE THEORY OF ISLAND BIOGEOGRAPHY...... 4-1
INTRODUCTION...... 4-1 A Theory of Island Biogeography ...... 4-1 1. Colonization and Extinction Rates ...... 4-1 2 . Island Size and Distance from Mainland...... 4-2 3 . Species Carrying Capacity ...... 4-4 4 . Landbridge and Oceanic Islands ...... 4-4 6 Lakes as Islands ...... 4-6 1. Relict Lakes...... 4-6 2. Sotus Lakes ...... 4-7
3 . Historical Formation of the Great Lakes O St. Lawrence Basin...... 4-7 fable of Contents
Page 4 . Origin of Fish Species in the Great Lakes .St . Lawrence Basin..... 4-8 5 . Dispersal Ability ...... 4-8 a) Preferred Temperature ...... 4-9 b) Swimming Ability ...... 4-10 c) Trophic Level ...... 4-10 C Objectives of This Chapter...... 4-11 II MATERIALS AND METHODS ...... 4-12 A Study Lakes and Databases...... 4-12 B Fish Sampling Procedure...... 4-12 C Statistical Methods...... 4-14 1. Mante1 Test and the Phi Coefficient of Similarity ...... 4-14 2 . Chi-Square Statistics...... 4-15 3 . Species Richness...... 4-16 4 . Correspondence Analysis ...... 4-16 5 . Discriminant Analysis ...... 4-17 6 . Dispersal Ability Index ...... 4-17 Ill RESULTS...... 4-19 A Merging of Datasets ...... 4-19 B Species Frequency of Occurrence...... 4-21 1. All Relict and Solus Lakes Cornbined...... 4-21 2. Cornparisons of Proximally Paired Relict and Solus Lake Regions. 4-24 a) Wawa and Algoma Lakes ...... 4-25 b) LaCloche and Sudbury Lakes ...... 4-28 c) Bruce Peninsula and Wellington Lakes ...... 4-31 C Species Richness...... 4-34 D Fish Species Composition in Lakes ...... 4-39 E Statistical Significance of Differences in Species Composition...... 4-50 F Index of Dispersal Ability ...... 4-52 IV DISCUSSION...... 4-55 A Species Richness...... 4-55 1. Latitudinal Gradients ...... 4-56
B Variation in Community Structure...... , ...... 4-58 C Lake Age ...... 4-59 Table of Contents
Page D Dispersal Ability ...... 4-59 E Genetic Variation...... 4-60 F Effects of Human Intervention of Fish Distribution...... 4-61 1. Canais ...... 4-61 2. Diversions...... 4-62 V CONCLUSIONS ...... 4-63
CHAPTER 5 SPEClES .ENVIRONMENT RELATIONSHIPS IN RELICT AND SOLUS LAKES......
I INTRODUCTION...... A Fish Species .Environment Studies in North American Lakes ...... B Species Niche...... C Objectives of This Chapter...... II MATERIALS AND METHODS...... A Study Lakes. Variables and Databases ...... B Statistical Methods...... 1. Canonical Correspondence Analysis ...... a) Partitioning of Species Variation ...... b) Biplots of Species - Environment Relationship...... 2 . Discriminant Analysis ...... 3 . Weighted Averaging and Calibration...... III RESULTS ...... A Community .Environment Relationships ...... 1. All Relict and Solus Lakes Combined...... a) Partitioning of Fish Species Variation ...... b) Species Composition .Environment Relationship ...... c) Statistical Significance of Species .Environment Relationships...... 2. Cornparisons of Proximally Paired Relict and Solus Lake Regions a) Partitioning of Fish Species Variation ...... b) Species Composition .Environment Relationship...... c) Statistical Significance of Species .Environment Relationship...... Table of Contents
Page B Species Specific .Environment Relationships...... 5-40 1. Environmental Gradients...... 5-40 2 . Species Optimum and Tolerance ...... 541 a) Species Comparisons in Proximal Relict and Solus Lake Regions. 541 i. Wawa and Algoma Lakes...... 5-42 ii . LaCloche and Sudbury Lakes...... 5-51 iii . Bruce Peninsula and Wellington Lakes ...... 5-60 b) White Sucker and Yellow Perch Cornparisons...... 5-69 IV DISCUSSION...... 5-78 A Partitioning of Species Variation...... 5-78 1. Species Variation Explained by Environmental Variables ...... 5-78 2 . Undetermined Species Variation ...... 5-78 6 Species Composition - Environment Relationship...... 5-79 C Regional Environmental Variables ...... 5-80 V CONCLUSIONS ...... 5-81
CHAPTER 6 CONCLUSIONS AND RECOMMENDATIONS...... 6-1
I RELlCT AND SOLUS LAKE THEORY ...... A . Environmental Characteristics of Relict and Solus Lakes ...... 6. Species Richness in Relict and Solus Lakes ...... C . Species Composition in Relict and Solus Lakes ...... D . Species - Environment Relationships in Relict and Solus Lakes...... E. Comparison of Relict and Solus Lakes with Landbridge and Oceanic Islands...... III IMPLICATIONS / RECOMMENDATIONS...... A . Fisheries Conservation in Ontario: A Proposed Management Plan for Unique Assemblages in Algoma . Sudbury . and Wellington Solus Lake Regions...... Table of Contents
Page
APPENDIX A Lake Formations Throughout the World and Their Classification as Either Relict or Solus ...... Al
. . APPENDIX 6 Schematic Summary of the Formation of the Great Lakes...... Bi
APPENDIX C Location and Quatemary Geology of Bruce Peninsula, Wellington, Lacloche, Sudbury, Wawa and Algoma Regions ... Ci
APPENDIX D Results of Canonical Correlation Analyses Correlating Regional Environmental Variables with Lake Morphology and Water Chemistry...... Dl
APPENDIX E Principal Component Analyses of Combined Relict and Solus Lakes and Proximally Paired Relict and Solus Lake Regions Using Local, Lake Morphology, Water Chemistry and Regional Environmental Variables...... El APPENDIX F Discriminant Analyses for Each of the Six Study Regions Using the Fint Two Principal Components of Principal Component Analyses of Combined Local and Regional, Local, Regional, Lake Morphology, and Water Chemistry Environmental Variables...... FI
APPENDIX G Reconstruction of the Glacial Lake Phases of Lakes Agassiz, Superior, Michigan, Erie, Ontario, Barlow-Ojibway, and the Champlain Sea With lnflow and Oufflow Connections...... Gl
APPENDIX H Environmental Gradients for Surface Area, Volume, Maximum Depth, Total Shoreline Perimeter, Specific Conductivity, Surrounding Lake Net Primary Productivity, and Surrounding Lake Forest Cover Within Each of the Six Study Regions...... Hl List of Tables
LIST OF TABLES
Page
Table 1.1. A summary of the main stresson effecting freshwater fish and their habitats (modified from Maitland 1995)...... 1 -3
Table 2.1. A summary of lake formations throughout the world and their classification as either relict or solus ...... 2-3
Table 3.1. Summary of local and regional environmental variables examined in this study ...... 3-8
Table 3.2. Surnmary of transfomed environmental variables. A perfectly normal distribution has a skewness and kurtosis value of O and a normality value of 1 ...... 3-20
Table 3.3. Summary of Wilcoxon-Mann-Whitney test results between 198 lakes present within both Harvey (1997) and OMNR (1997) datasets ...... 3-21
Table 3.4. Summary of canonical correlation analyses between local and regional, lake morphology and regional, and water chemistry and regional environmental variables...... 3-22
Table 3.5. Corretations, standardized canonical coefficients, canonical correlations, percents of variance, and redundancies between local and regional variables and their corresponding canonical variates.. . 3-24
Table 3.6. Significant Pearson Product-Moment correlations of al1 environmental variables using a sequential Bonferroni correction. R-square and probability values are states for each relationship.. ... 3-26
Table 3.7. Correlations of local and regional environmental variables with the first two principal components of a principal component analysis of al1 relict and solus lakes...... 3-28
Table 3.8. Summary of discriminant analyses of relict and solus lakes using the first two principal components of principal component analyses of combined local and regional environmental variables, local environmental variables, regional environmental variables, lake morphology variables and water chemistry variables...... 3-33
Table 3.9. Percent of environmental information sumrnarized in the significant eigenvahes of each principal component analysis across each of the proximally paired regions. The number of significant eigenvalues for each principal component analysis using the Broken Stick model (Frontier 1976) is indicated in brackets ...... 3-34 List of Tables
Page Table 3.1 O. Correlations of local and regional environrnental variables with the first two principal cornponents of a principal cornponent analysis of Wawa and Algorna lakes...... 3-35
Table 3.1 1. Sumrnary of discriminant analyses of Wawa (relict) and Algoma Algoma (solus) lakes using the first two principal cornponents of principal cornponent analyses of wmbined local and regional environmental variables, local environmental variables, regional environmental variables, lake morphology variables and water chemistry variables...... 3-39
Table 3 .12. Correlations of local and regional environmental variables with the first two principal components of a principal cornponent analysis of LaCloche and Sudbury lakes ...... 3-40
Table 3.1 3. Summary of discriminant analyses of LaCloche (relict) and Sudbury (solus) lakes using the first two principal components of principal component analyses of combined local and regional environmental variables, local environrnental variables, regional environmental variables, lake morphology variables and water chernistry variables ...... 3-44
Table 3.14. Correlations of local and regional environmental variables with the first two principal components of a principal component analysis of Bruce Peninsula and Wellington lakes...... 3-45
Table 3.1 5. Summary of discriminant analyses of Bruce Peninsula (relict) and Wellington (solus) lakes using the first two principal components of principal cornponent analyses of combined local and regional environmental variables, local environrnental variables, regional environmental variables, lake morphology variables and water chemistry variables...... 3-49
Table 4.1. Fish species examined in this study ...... 4-1 3
Table 4.2. Summary of indices used in the dispersal abiiity index...... 4-1 8
Table 4.3. Summary of Mantel test between 198 lakes present within both Harvey (1997) and OMNR (1997) species datasets...... 4-1 9
Table 4.4. Summary of frequency of occurrence of species in the Harvey (1997) and OMNR (1997) datasets. Bold X2 values indicate a significant difference in the species frequency of occurrence between the two datasets ...... 4-20
Table 4.5. Surnmary of frequency of occurrence of species in relict and solus lakes. Bold X2 values indicate a significant difference in a species frequency of occurrence between relict and solus lakes ...... 4-22 List of Tables
Page Table 4.6 Summary of frequency of occurrence of species in Wawa (relict) and Algoma (solus) lakes. Bold X2 values indicate a significant difference in a species frequency of occurrence between relict and sol us la kes ...... 4-25
Table 4.7 Summary of frequency of occurrence of species in LaCloche (relict) and Sudbury (solus) lakes. Bold X2 values indicate a significant difference in a species frequency of occurrence between relict and solus lakes...... 4-28
Table 4.8 Sumrnary of frequency of occurrence of species in Bruce Peninsula (relict) and Wellington (solus) lakes. Bold X2 values indicate a significant difference in a species frequency of occurrence between relict and solus lakes ...... 4-31
Table 4.9 Comparison of species-area curves between relict and solus lakes.. 4-34
Table 4.1 0 Summary of native fish species located within each study region (Mandrak and Crossrnan 1992). "Xnrepresents the presence of a species in a region. Bold species indicate species examined within this study ......
Table 4.1 1 Summary of correspondence analyses of relict and solus lakes, Bruce Peninsula and Wellington lakes, LaCloche and Sudbury lakes, and Wawa and Algoma lakes ......
Table 4.1 2 Summary of discriminant analyses of al1 relict and solus lakes, Bruce Peninsula (relict) and Wellington (solus) la kes, LaCloche (relict) and Sudbury (solus) lakes, and Wawa (relict) and Algoma (solus) lakes using the first two components of correspondence analyses of lakes in relation to their species composition......
Table 4.1 3 Summary of discriminant analyses of al1 six regions using the first two components of a correspondence analysis of lakes in relation - to their species composition......
Table 4.14 Summary of species scores on the Dispersal Ability Index......
Table 4.15 A comparison of relict and solus lakes with landbridge and oceanic islands......
Table 5.1. Fish species variation partitioning for both relict and solus lakes using combined local and regional environmental variables......
Table 5.2. Summary of fish species codes used for each of the biplots in this study ...... List of Tables
Page Table 5.3 Summary of discriminant analysis of relict and solus lakes species - environment relationship using lake scores on the first two components of a canonical correspondence analysis of combined local and regional environmental variables with spatial variation partialled out ...... 5-20
Table 5.4. Sumrnary of discriminant analysis of species - environment relationships for each of the six study regions using lake scores on the fin two components of a canonical correspondence analysis of combined local and regional environmental variables with spatial variation partialled out...... 5-22
Table 5.5. Fish species variation partitioning of each of the six study regions using combined local and regional environmental variables...... 5-24
Table 5.6. Summary of canonical correspondence analyses of local and regional environrnental variables with spatial variation partialled out for each of the six study regions ...... 5-28 Table 5.7. Surnmary of discriminant analysis of the species - environment relationship for each of the paired proximal relict and solus lake regions using lake scores on the first two components of canonical correspondence analyses of combined local and regional environmental variables with spatial variation partialled out...... 5-36
Table 5.8. Summary of standard deviation of environmental gradients for each of the fourteen environmental gradients examined for each study region...... 5-40
Table 5.9. Surnmary of comparison of observed optima and tolerances of seven environmental variables for common species found in both Wawa and Algoma regions. "Yes" indicates a significant difference in observed optimum and tolerance for a species between regions. The bracketed region indicates for which region the observed optimum and tolerance is larger. 'Non indicates no significant difference in observed optimum or tolerance between regions for a species ...... 5-43
Table 5.1 0. Summary of comparison of observed optima and tolerances of seven environmental variables for common species found in both LaCloche and Sudbury regions. "Yesn indicates a significant difference in observed optimum and tolerance for a species between regions. The bracketed region indicates for which region the observed optimum tolerance is larger. "No" indicates no significant difference in observed optimum or tolerance between regions for a species ...... 5-52 List of Tables
Page Table 5.1 1. Summary of comparison of observed optima and tolerances of seven environmental variables for common species found in both Bruce Peninsula and Wellington regions. "Yesn indicates a significant differences in observed optimum and tolerance for a species between regions. The bracketed region indicates for which region the observed optimum and tolerance is larger. "No" indicates not significant difference in optimum or tolerance between regions for a species...... 5-61
Table 5.12 Summary of observed optima and tolerances for the white sucker and yellow perch between proximal regions for seven environmental variables. "Yesn indicates a significant difference in obsewed optimum and tolerance for a species between regions. The bracketed region indicates for which region the observed optimum and tolerance is larger. "Non indicates no significant difference in observed optimum or tolerance between regions for a species...... 5-70
Table 6.1. A comparison of relict and solus lakes with landbridge and oceanic islands ...... 6-6 List of Figures
LIST OF FIGURES
Page
Figure 2.1. Summary of relict and solus lakes formation...... Figure 2.2 Maximum extent of proglacial lakes in Ontario (modified from Teller 7 989)......
Figure 3.1. Spatial relationship between local and regional environmental variables with reference to the ecological boundary of the species or community under study......
Figure 3.2. Location of study regional within the Great Lakes - St. Lawrence basin of Ontario. Algoma, Sudbury and Wellington regions contain solus lakes. Wawa, LaCloche and Bruce Peninsula regions contain relict lakes (map modified from Teller 1989)......
Figure 3.3. Venn diagram summarizing the retationship examined between sets of environmental variables using canonical correlation analysis......
Figure 3.4. Principal components analysis of relict and solus lakes using local and regional environmental variables......
Figure 3.5. Principal component analysis of lakes in the six study regions using local and regional environmental variables......
Figure 3.6. Principal cornponents analysis of Algoma and Wawa lakes using local and regional environmental variables ......
Figure 3.7. Principal components analysis of LaCloche and Sudbury lakes using local and regional environmental variables......
Figure 3.8. Principal components analysis of Bruce Peninsula and Wellington lakes using local and regional environmental variables......
Figure 4.1. Hypothetical changes in colonization and extinction rates for close and distance islands from mainland and small and large islands indicating species carrying capacity 'K" for each condition (Ka = distant and small islands. Kb = distance and large islands, Kc = close and small islands. and Kd = close and large islands)......
Figure 4.2. Comparison of landbridge an oceanic island formation......
Figure 4.3. Species-area plots for Wawa and Algoma regions. Wawa lakes (Y=4.6W-I8.00. R2 = 0.20. P = 0.003). Algoma lakes (y=3.41x- 7.69, R2=0.20. P = 0.00002)...... List of Fiaures
Page Figure 4.4. Species-area plots for LaCloche and Sudbury regions. LaCloche lakes (Y=3.41X-10.94, R2 = 0.27, P = 0.0004). Sudbury lakes (yz2.05X-2.65. R2=0.13, P = 0.00001 )...... 4-35
Figure 4.5. Species-area plots for Bruce Peninsula and Wellington regions. Bruce Peninsula lakes (y=4.73X-15.5, R2 =0.31, P = 0.00001). Wellington lakes (y=1.17X+0.97, R2= 0.003, P = 0.1)...... 4-36
Figure 4.6. The association of relict and solus lakes based on a correspondence analysis of fish species composition...... 442
Figure 4.7. The association of the six regions based on a correspondence analysis of fish species composition...... 4-43
Figure 4.8. The association of Wawa (relict) and Algoma (solus) lakes based on a correspondence analysis of fish species composition...... 4-44
Figure 4.9. The association of Wawa (relict) and Algoma (solus) lakes based on a correspondence analysis of fish species composition. Ellipses represent a grouping of species related to a set of surrounding Wawa or Algoma lakes. Species are listed in order of placement from left to right on the CA Axis 1...... 4-45
Figure 4.1O. The association of LaCloche (relict) and Sudbury (solus) lakes based on a correspondence analysis of fish species composition... 4-46
Figure 4.1 1. The association of LaCloche (relict) and Sudbury (solus) lakes based on a correspondence analysis of fish species composition. Ellipses represent a grouping of species related to a set of surrounding LaCloche or Sudbury lakes. Species are listed in order of placement from left to right on the CA Axis 1...... 4-47
Figure 4.1 2. The association of Bruce Peninsula (relict) and Wellington (solus) lakes based on a correspondence analysis of fish species composition ...... 4-48
Figure 4.1 3. The association of Bruce Peninsula (relict) and Wellington (solus) lakes based on a correspondence analysis of fish species composition. Ellipses represent a grouping of species related to a set of surrounding Bruce Peninsula or Wellington lakes. Species are listed in order of placement from left to right on the CA Axis 1.. 4-49
Figure 5.1. Variation partitioning of fish species variation according to combined local and regional environmental variables for relict and solus lakes...... ,., ...... 5-1 3 List of Ficiures
Page Figure 5.2. Canonical conespondence analysis ordination biplot of fish species (points), and local and regional environmental variables (vecton) for relict lakes with spatial variation partialled out. Vectors point in the direction of maximal change of a given environmental variable. Environmental variables with long vectors are more strongly correlated with the axes than are those with shorter vectors, and accordingly, are more strongly related to the species pattern in the biplot. Species can be projected relative to the vectors such that the ordering of species along the axis of a vector is approximately the ranked, weighted mean value of the species relative to the environmental vector...... 5-1 7
Figure 5.3.Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environmental variables (vectors) for solus lakes with spatial variation partialled out. Vectors point in the direction of maximal change of a given environmental variable. Environmental variables with long vectors are more strongly correlated with the axes than are those with shorter vectors, and accordingly, are more strongly related to the species pattern in the biplot. Species can be projected relative to the vectors such that the ordering of species along the axis of a vector is approximately the ranked, weighted mean value of the species relative to the environmental vector...... 5-1 8
Figure 5.4. Canonical correspondence analysis of relict and solus lakes using local and regional environmental variables with spatial variation partialled out...... 5-21
Figure 5.5. Canonical correspondence analysis of lakes in the six study regions using local and regional environmental variables with spatial variation partiatled out...... 5-23
Figure 5.6. Variation partitioning of fish species variation according to combined local and regional environrnental variables for each of the six study regions ...... 5-26
Figure 5.7. Canonical correspondence analysis ordination bipIot of fish species (points), and local and regional environmental variables (vectors) for Wawa (relict) lakes with spatial variation partialled out ...... 5-29
Figure 5.8. Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environmental variables (vectors) for AIgoma (solus) lakes with spatial variation partialled out...... 5-30
Figure 5.9. Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environrnental variables (vectors) for LaCloche (relict) lakes with spatial variation partialled out...... 5-3 1 List of Fiaures
Page Figure 5.1 0. Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environmental variables (vecton) for Sudbury (solus) lakes with spatial variation parüalled out...... 5-32
Figure 5.1 1. Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environmental variables (vectors) for Bruce Peninsula (relict) lakes with spatial variation partialled out.. ... 5-33
Figure 5.1 2. Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environmental vanables (vecton) for Wellington (solus) lakes with spatial variation partialled out...... 5-34 figure 5. t 3. Canonical correspondence analysis of Wawa (relict) and Algoma (solus) lakes using local and regional environmental variables with spatial variation partialled out...... 4-37
Figure 5.14. Canonical correspondence analysis of Lacloche (relict) and Sudbury (solus) lakes using local and regional environmental variables with spatial variation partialled out...... 5-38
Figure 5.1 5. Canonical correspondence analysis of Bruce Peninsula (relict) and Wellington (solus) lakes using local and regional environmental variables with spatial variation partialled out...... 5-39
Figure 5.1 6. Surnmary of common species' optima and tolerances for surface area in both Wawa and Algoma lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-44
Figure 5.17. Summary of cornmon species' optima and tolerances for volume in both Wawa and Algoma lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-45
Figure 5.18. Summary of common species' optima and tolerances for maximum depth in both Wawa and Algoma lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-46
Figure 5.19. Summary of common species' optima and tolerances for total shoreline perimeter in both Wawa and Algoma lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 547
Figure 5.20. Summary of cornmon species' optima and tolerances for specific conductivity in both Wawa and Algoma iakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-48 List of Fiaures
Page Figure 5.27. Summary of common species' optima and tolerances for net primary productivity in both Wawa and Algoma lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-49
Figure 5.22. Summary of common species' optima and tolerances for surrounding lake forest cover in both Wawa and Algoma lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region......
Figure 5.23. Summary of common species' optima and tolerances for surface area in both LaCloche and Sudbury lakes. The number in the brackets before the species narne indicates the number of lakes where the species occurred for that region......
Figure 5.24. Summary of common species' optima and tolerances for volume in both LaCloche and Sudbury lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region ......
Figure 5.25. Summary of common species' optima and tolerances for maximum depth in both LaCloche and Sudbury lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region ......
Figure 5.26. Surnmary of cornmon species' optima and tolerances for total shoreline perimeter in both LaCloche and Sudbury lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region ......
Figure 5.27. Summary of common species' optima and tolerances for specific conductivity in both LaCloche and Sudbury lakes. The number in the brackets before the species narne indicates the number of lakes where the species occurred for that region......
Figure 5.28. Summary of cornmon species' optima and tolerances for net primary productivity in both LaCloche and Sudbury lakes. The number in the brackets before the species narne indicates the number of lakes where the species occurred for that region......
Figure 5.29. Summary of comrnon species' optima and tolerances for surrounding lake forest cover in both LaCloche and Sudbury lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region......
Figure 5.30. Summary of cornrnon species' optima and tolerances for surface area in both Bruce Peninsula and Wellington lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... List of Figures
Page Figure 5.31. Summary of common species' optima and tolerances for volume in both Bruce Peninsula and Wellington lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-63
Figure 5.32. Summary of cornmon species' optima and tolerances for maximum depth in both Bruce Peninsula and Wellington lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-64
Figure 5.33. Sumrnary of common species' optima and tolerances for total shoreline perimeter in both Bruce Peninsula and Wellington lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-6 5
Figure 5.34. Summary of common species' optima and tolerances for specific conductivity in both Bruce Peninsula and Wellington lakes. The nurnber in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-66
Figure 5.35. Surnmary of common species' optima and tolerances for net primary productivity in both Bruce Peninsula and Wellington lakes. The number in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-67
Figure 5.36 Summary of cornmon species' optima and tolerances for surrounding lake forest cover in both Bruce Peninsula and Wellington lakes. The nurnber in the brackets before the species name indicates the number of lakes where the species occurred for that region...... 5-68
Figure 5.37. Summary of white sucker and yellow perch optima and tolerances for surface area within each of the six study regions ...... 5-71
Figure 5.38. Summary of white sucker and yellow perch optima and tolerances for volume within each of the six study regions...... 5-72
Figure 5.39. Summary of white sucker and yellow perch optima and toleranœs for maximum depth within each of the six study regions ...... 5-73
Figure 5.40. Summary of white sucker and yellow perch optima and tolerances for total shoreline perimeter within each of the six study regions.. ... 5-74
Figure 5.41. Summary of white sucker and yellow perch optima and tolerances for specific conductivity within each of the six study regions...... 5-75
Figure 5.42. Summary of white sucker and yellow perch optima and tolerances For net prirnaw productivity within each of the six studv reaions ..... 5-76 List of Fiaures
Page Figure 5.43. Summary of white sucker and yellow perch optima and tolerances for surrounding lake forest cover within each of the six study regions ...... 5-77 Thesis Introduction
Thesis Introduction
1. OVERVIEW OF FRESH WA TER ECOSYSTEM CONSERVATION IN CANADA
A. WATER RESOURCES
As the hurnan population continues to grow, there is a parallel increase in the conflict between the human consumptive use of the Earth's freshwater resources and the maintenance of healthy aquatic ecosysterns and biodiversity. Only 2.5% of the Earth's water is freshwater (Engelman and LeRoy 1993). Most of the freshwater is locked in polar ice caps, stored in underground aquifen (many with recharge cycles measured in millennia), or part of soi1 moisture, permafrost and swamp water. Amazingly, only 0.01 % of the Earth's water is available as freshwater riven and lakes (Engelman and LeRoy 1993). Despite the fact that these freshwater habitats comprise less than one-hundredth of a percent of the Earth's water, rivets, lakes and wetlands have exceptional concentrations of biodivenity. Almost 25% of global vertebrate biodivenity is concentrated within these freshwater habitats (Stiassny 1996). In many respects, freshwater habitats are like islands of water surrounded and isolated by land, and like other insular ecosystems they are extremely vulnerable to ecological perturbation.
B. CANADIAN FRESHWATER FISHES IN PERIL
There are 177 native freshwater fish species in Canada. Currently, 66 of these species are listed by the Cornmittee on the Status of Endangered Wild Flora and Fauna in Canada as being either endangered, threatened or vulnerable (World Wildlife Fund Canada 1998). This indicates that an astonishing 37% of al1 freshwater fish species in Canada are in peril. The trend in this listing indicates that membership in each of these species-at-risk categories will continue to escalate into the next millennium. Rewvery prospects of these listed species is bleak considering that 60 of these 66 species do not have recovery plans due to a lack of information regarding their habitat and environmental requirements. Thesis Introduction
Other aquatic taxa exhibit the same and even higher rates of endangement. The following are North American examples because no such information exists for Canada alone. Master (1990) reported that 36% of the crayfishes and 55% of the mussels in North America are extinct or imperiled. The vast nurnber of fish, crayfish and mussel species at risk of extinction indicates that temperate freshwater ecosystems are becorning severely degraded (Karr and Dudley 1981; Karr et al. 1985; Hughes and Noss 1992; Williams and Neves 1992). Without shifts in management toward watershed and ecosystern planning, Moyle and Williams (1990) stated that North American waters may lose as much or more of their aquatic biodiversity, including fishes, than tropical systems.
C. DICHOTOMY OF CONSERVATION
Fishes and other aquatic fauna are disproportionately imperiled in relation to terrestrial fauna. The Nature Conservancy estirnates that only 7% of North Amencan mammals and birds have become extinct or are currentiy imperiled (Master 1990). Clearly, fish and other aquatic fauna are disproportionately imperiled by a factor. as high as four times the extinction rate of terrestrial fauna. The aquatic environment is in more desperate need of conservation and management than terrestrial systems and yet little is being done. Why does this dichotomy exist?
There seems to be a social bias against small, cold, and wet species. Fish and other aquatic fauna live in the water which also makes them difficult to see and therefore appreciate (Hughes and Noss 1992) as opposed to the visible terrestrial "charismatic megafauna"such as large mammals and birds. The current public perception is to conserve what they can see and to be generally indifferent to the widespread plight of fishes and other aquatic organisms.
Even when attention is focused on freshwater fish conservation, the effort is directed primarily at game species and less regard is had for other species or the community as a whole. This occurs in spite of the fact that non-game fish comprise the overwhelming bulk of fish species in any natural waterbody (Warren and Burr 1994). These non-game fishes, which constitute 89% of North American fish species. are perceived as mere 'minnows" with a primary value as bait or food for game fishes (Sheldon 1988; Master 1990). Thesis lntroduction
O. CAUSES FOR DECLINE OF FRESHWA TER FISHES
The causes of imperilment and extinction of fishes in freshwater ecosystems have been extensively studied by many researchers (e.g., Miller et al. 1989; Williams et a%1 989; Lubchenco et al. 1991; Cairns and Lackey 1992; AHan and Flecker 1993; Maitland 1995). The major causes responsible for their decline are: 1) physical habitat loss, degradation or alteration, 2) chemical pollution or alteration, 3) overexploitation, and 4) introduction of non-indigenous species (Table 1.1 ).
Table 1.l. A surnmary of the main stressors effecting freshwater fish and their habitats (rnodified from Maitland 1995).
Stressors Effect Infilling, drainage and channelization Loss of habitat, shelter and food supply Water abstraction Loss of habitat, and spawning grounds, - transfer of species Fluctuating water levels (reservoirs) Loss of habitat, spawning and food supply Land use (farming and forestry) Eutrophication, acidification, sedimentation Industrial development (including roads) Sedimentation, obstructions, transfer of species River obstructions (dams) Blocking of migration routes, sedimentation / of spawning beds Warm water discharge gradients Deoxygenation, temperature Industrial and domestic effluents Pollution, poisoning, blocking of migration II 1 routes Acid deposition Acidification, release of toxic metals Fish farming Eutrophication, introductions, diseases, genetic changes Angling and fishery management Elimination by piscicides, diseases, / introductions Commercial fishing Overfishing, genetic changes Introduction of exotic species Elimination of native species, diseases, parasites Global warming Northward movement of southern species Thesis Introduction
E. NEEDED RESEARCH AND CONSERVAT/ON MANAGEMENT
There is a strong need for the development of more conservation management plans that focus on the conservation of entire freshwater ecosystems at the watershed level rather than on the recovery of single endangered species. A single species approach to conservation management is appropriate only when the species at risk has a large critical habitat area which is necessary for its survival. For example, in the Greater Yellowstone ecosystem, the grizzly bear (Ursus homBilis) is the focus of much conservation planning. Maintaining a habitat of sufkient quality and size to support a viable grizzly bear population also supports the protection of most other species found within this habitat and associated ecosystem (e.g., Knight and Eberhardt 1985; Mattson and Reid 1991; Mattson and Craighead 1994). In essence, the grizzly bear serves as a large "umbrella" species for the protection of its associated ecosystem's species and environment. However this key species management approach is not viable for freshwater ecosystems because the environment for aquatic species is deterrnined primarily by the physico-chemical characteristics of the surrounding watershed which is not part of the aquatic species' habitat. The physical, chemical and biotic properties of a lake are directly influenced by changes throughout its entire watershed. Water continuously moves through the watershed and influences the nurnerous life cycles and physical processes of the aquatic species. An action or change in one location within a watershed has potential implications for many other natural features and processes that are linked by the interactive movement of surface and ground water. Therefore, to protect and manage only the freshwater habitat of an aquatic species would not ensure the protection of its aquatic environment from habitat degradation and perturbation from its surrounding waters hed. From a freshwater conservation standpoint, a single species approach to recovery of imperiled species is not viable. Instead, a watershed level management program is required for successful conservation work.
The initial step in the irnplementation of a watershed level freshwater conservation management plan is to more fully understand the fish communities and their environments and the critical species - environrnent relationships that affect their extinction or survival. Most of the research that has been conducted to date on fish comrnunities in Canada has focused on environmental variables that operate at both a local spatial scale and a recent temporal smle (e.g., Hinch 1991). Much of the work has Thesis Introduction
neglected historical context and regional environmental characteristics to help define community structure. Research needs to be focused on the following three areas: 1) historical context. 2) community structure, and 3) regional dynamics at the watershed level.
Il. THIS SWDY :A STEP IN THE RIGHT DIRECTION
This thesis examines fish community structure and local and regional environments of inland lakes within the Great Lakes - St. Lawrence basin in Ontario. A total of 550 lakes are examined within 6 geographic regions; Wellington. Bruce Peninsula. Lacloche. Sudbury. Wawa and Algoma. This is a biogeographic study which integrates: 1) community and landscape ecology, 2) conservation biology, 3) multivariate statistics, and 4) geographical information processing. This thesis is an attempt to examine the ecology of fish communities in lakes with respect to their local and regional environmerit and historical lake formation. It is a first step in understanding these communities as a function of their environments and should provide a basis for the identification of critical relationships that could help to minimize further imperilment of freshwater ecosysterns in Canada.
A. OBJECTIVES
The objectives of this thesis in the remaining chapters are as follows:
CHAPTER 7WO: To categorize lakes into two new types of classifications based on their historical formation: relict and solus. To identify the historical development of these two lake types and show how differences in lake formation can affect both fish community structure and local and regional environments.
CHAPTER THREE: To examine differences in the local and regional environments of relict and solus lakes. This thesis focuses on the importance of watershed characteristics in defining Thesis Introduction fish cornmunity structure as well as the traditional examination of within-lake environmental characteristics.
CHAPTER FOUR: To examine differences in species richness and cornmunity structure based on relict and solus lake formation.
CHAPTER FIVE: To examine differences in the community structure - environment relationship between relict and solus lakes. To examine differences in the ecological niches of species in relict and solus lakes. Differences in both local and regional environmental characteristics are examined.
CHAPTER SIX: To establish recornmendations for the conservation of solus lake regions. Cha~ter2 Relict and Solus Lakes
Relict and solus lakes
INTRODUCTION
Current studies on the ecology of freshwater systems, especially lakes, neglect to examine the historical formation of the system. More specifically, there has been no study to date which examines how the historical formation of a lake is related to its subsequent environment and species assemblage structure. This area of historical context in freshwater ecology needs urgent attention, since, as this thesis will show, historical formation plays a critical role in understanding the relationships between fish species and their lacustrine environment.
A. DEFINITION OF RELICTAND SOLUS LAKES
The purpose of this chapter is to introduce a new concept in the way lakes are defined based on their historical formation. Two new terrns, "relict" and "solus" are defined in this thesis in an attempt to describe the differences in colonizatian and extinction processes affecting species composition in these two types of lakes. A "relict" lake ("relict" meaning "remaining" in Greek), is defined as a lake that was once part of a large waterbody which has since receded to form smaller lakes (Figure 2.1). Species in relict lakes are derived primarily from the common species pool of the large ancestral waterbody. A 'solus" lake ("solus" meaning "isolated" in Greek), on the other hand, is defined as a lake formed in isolation which was never a part of a larger water systern (Figure 2.1). Solus lakes, by definition, never shared a common species pool with other lakes. This categorization of lakes as either "relict* or 'solusn is analogous to 'oceanicn and 'landbridge" islands in the Theory of Island Biogeography (MacArthur and Wilson 1967), if one regards lakes as "aquatic islands" within a "terrestrial sea". Chapter 2 Relict and Solus Lakes
- Time
RELICT LAKES
- Time
SOLUS LAKES
Figure 2.1. Cornparison of relict and solus lake formation.
II. RELICT AND SOLUS LAKES THROUGHOUT THE WORLD
The definitions presented here for relict and solus lakes should be suitable for describing any lake formation throughout the world. Lakes formed from movements of the Earth's crust, volcanic activity. meteorites. landslides, local solution, fluviatile action and glacial activity can be discussed within the context of relict and solus lakes. Appendix A provides a detailed review for the formation of many lakes throughout the world. An overview of the key formation processes and their relationship to the solus and relict lake classification is sumrnarized in Table 2.1. Chapter 2 Relict and Solus Lakes
Table 2.1 Summary of lake formations throughout the world and their classification as either relict or solus.
Examples Reference
II A. Movements of the ~akesTanganyika, Edward, and Cohen et al. 1993 Mobuto Sese Seko, Western Klerkx et al. 1998 African Rift Lake Victoria, Central plateau of Johnson et al. 1996 Westem Afncan Rift I so'us Lake Baikal. USSR Artyushkov et al. 1990 Solus
1. Calderas Crater Lake, Oregon, US Allen 1984 1 Solus Wolcott 1964 Lake Tazawko, Honsyu, Japan Hutchinson 1957 Solus The Pulvemarr, Eifel District of Lorenz 1974 Gemany I solus Lac d'lssarles, Auvergne District Scrope 1858: Solus of France Hutchinson 1957 Delebecque and Ritter 1892: Hutchinson 1957 Lakes at base of Mount Willis 1936: Solus Ruwenzori, Central Africa Hutchinson 1957 Burgis and Morris 1987 Laguna Negra Campo del Ciele, Nagera 1926: Solus Gran Chaco of Argentina Hutchinson 1957 Ungava Lake, Ungava, Quebec Meen 1950,1952: Solus Hutchinson 1957 II D. Landslides Hebgen Lake, Montana, US Winter and Woo 1990 Solus Lake Cresent, Washington, US Brown et al. 1960 Solus 1 E. Local Solution Deep lake, northwestem Puri and Vernon 1960 Florida, US r soius 1. Plunge-pool lakes Lakes Falls and Castle, Wolcott 1965 Relict Washington, US 11 2. Levee lakes Lakes Pontchartrain and St. Smith 1996 1 Relict Catherine, Mississippi Delta, US 3. Oxbow lakes Lake St. Joseph, Louisiana, US Cooper& and McHenry Relict 11 4. Floodplain lakes Lakes within Amazon River floodplain, Brazil G. Glacial Activity 1. Lakes held by ice or Demmevatn, Hardanger, Strom 1938a: Solus .by moraine in contact with Gemany Hutchinson 1957 Chanter 2 Relict and Solus Lakes
Great Lakes, Canada I US Hough 1958 Relict Dyke and Prest 1987a 2. Glaciated rock basins a) Ice-scour lakes Lakes in western Scotland Wemitty et al. 1994 RelicV Solus b) Cirque lakes La kes Iceberg, Hidden, Dyson 1948a, b Solus Avalanche, Gunsigbt and Eilen Wilson. Montana. US c) Glint lakes Lochs Rannoch, Ericht, Ossian, Maitland 1994 Solus Treig, Rannoch Moor, Scotland 3. Drift basins a) Kettle lakes Lakes on Central plains of North Christiansen 1979 Solus Amenca b) Thermokarst lakes Lakes in interior of eastem Wallace 1948: Solus Alaska Hutchinson 1957
III. GLACIAL SOLUS LAKES WITHIN THE GREAT MUES - ST. LAWRENCE BASlN
The last glacial recession began approximately 18,000 years ago creating a series of proglacial (ice front) lake formations throughout the upper half of North America. The Great Lakes - St. Lawrence basin began to emerge from the glacial ice approximately 14,000 years ago and developed into its present-day form approximately 7,000 years ago (e.g., Barrett 1992). During this period, there were several episodes of proglacial (ice front) lake formations within the region which covered most of the Great Lakes - St. Lawrence basin. Figures B1 to 89 in Appendix B depict the sequential formation of the present Great Lakes and surmunding area from 14.000 years ago to present. These figures illustrate how proglacial lakes were developing and receding, and drainage routes were connected and disconnected throughout this period.
Several areas within the Great Lakes - St. Lawrence basin were never covered by proglacial lakes (Figure 2.2). Most of these regions are located on the divide between the Hudson Bay I Great Lakes - St. Lawrence drainages. These regions contain inland lakes that were never part of proglacial waterbodies from the last glacial recession beginning 18.000 years ago. to present. These lakes. which are analogous to oceanic islands (MacArthur and Wilson 1967), are defined as glacial solus lakes in this thesis. Chaoter 2 Relid and Solus Lakes
They were fomed within areas of land never inundated by a lager body of water. Based on the bedrock structure of the Precambrian Shield, many of the glacial solus lakes in this region are thought to have been fomed by glacial ice-scour. Pre-existing fractures and shatter belts formed by glaciers dunng the pre-Pleistocene era were excavated by the most recent glaciers as they retreated, forming basins which were filled with glacial meltwater. Glacial solus lakes also rnay have been formed in other ways. For example, it is thought that some glacial solus lakes in the St Lawrence Lowlands were fomed by the deposition of blocks of ice washed out with drift material from the glaciers as they retreated. These blocks of ice often took several hundred years to melt completely, and resulted in the formation of keffle lakes (Florin and Wright, 1969). tastly, some glacial sotus lakes may have been fomed from the upwelling of groundwater spnngs, forming seepage lakes.
Figure 2.2. Maximum extent of proglacial lakes in Ontario (modified fmm Teller 1989). Cha~ter2 Relict and Solus Lakes
Without a connection to a larger body of water, glacial solus lakes are essentially aquaüc islands in isolation. For this reason, glacial solus lakes are expected to be species-poor and to show a greater variation in their fish community structure in cornparison to lakes that were derived from large proglacial waterbodies and share a common species pool with other bodies of water.
Colonization of purely aquatic species such as fish into glacial solus lakes may have been achieved in several ways. Glacial solus lakes containing oufflows may have been colonized by species swimming upstream from connected relict lakes. Catastrophic flooding is another possible mechanism of species colonization, depositing fish from relict lakes into glacial solus lakes. The extent of colonization would depend on the degree of flooding. which in turn would depend on the relative elevation of glacial solus lakes. ln glacial solus lakes without an inflow and oufflow, colonization of fish may be accomplished by rare events such as birds dropping their fish prey into these isolated lakes. or by tornadoes lifting fish from one lake and releasing them into a glacial solus lake. However, a more viable, common colonization method is the process of stocking glacial solus lakes with game and bait fish.
IV. GLACIAL RELICT LAKES WITHIN THE GREAT LAKES -ST. LAWRENCE BASlN
Lakes that were once a part of a larger body of water during the last glacial recession are defined in this thesis as "glacial relict" lakes. These lakes are analogous to landbridge islands (MacArthur and Wilson 1967). Most of the inland lakes within the Great Lakes - St. Lawrence basin fall into this category. Proglacial bodies of water formed at the edges of melting glaciers, and receded to form smaller glacial relict lakes. These glacial relict lakes were most likely formed in existing fractures and shatter belts in the Precambrian Shield and may have been further excavated by glacial ice-scour to yield basins which filled with proglacial water. Glacial relict lakes in the St. Lawrence Lowlands, such as on the Bruce Peninsula, in part were formed in depressions via the solution of limestone by water.
Connected to the same large ancestral waterbody, glacial relict lakes are expected to share a similar species composition, since they are derived from a common ancestral species pool. Chapter 2 Relict and Solus Lakes
Because glacial relict lakes differ from glacial solus lakes in the way they were foned, it is hypothesized that the physical environment and species composition of glacial solus lakes would be different from those of glacial relict lakes in adjacent areas.
V. EVIDENCE FOR THE FORMATION OF GLACIAL RELICl AND GLACIAL SOLUS LA KES
Both geomorphological and biological findings provide evidence that glacial relict and glacial solus lakes have distinct, and different origins. Old proglacial lake shores, river deltas, and proglacial lake bottom deposits, dated by ~arbon'~techniques, show where proglacial lakes formed and how they migrated in the wake of the ice front (Barrett 1992). These physiographic remains of proglacial waterbodies delineate the fomation of glacial relict lakes. Glacial solus lakes are found in areas where these physiographic remains of proglacial lakes do not exist.
It is well established that Mysis relicta, Senecella calanoides, Limnocalanus macrurus, and Pontoporeia afinis are large cnistaceans occurnng primarily in glacial relict lakes (Dadswell 1974). The intricate relationship between the present relict crustacean distributions and the last glacial succession of proglacial lakes that followed the ice front retreating to the north has been examined by Ricker (1959) and Dadswell (1974). Mysis relicta is a prime example of a glacial relict species. and both the evolutionary and zoogeographical history of this species have been extensively studied (e.g., Loven 1862; Sarnter 1905; Jagerskiold 1912; Hogbom 1917; Ekman 1922; Thienemann 1925,1950; Segerstrale 1957. 1962, 1976, 1982; Holrnquist 1959, 1966; Ricker 1959; Muller 1964; Kuderskii 1971; Dadswell 1974; Roff et al. 1981; Bousfield 1989; Vainola and Varvio 1989). Chapter 2 Relict and Solus takes
VI. CONCLUSIONS
Two new terms are created which describe lakes based on their formation; relict and solus. These constructs of relict and solus lakes are applicable to any lake formation throughout the world. A relict lake is defined as a lake that was once part of a large waterbody which has since receded to fom smaller lakes. Species in relict lakes are obtained prirnarily from the common species pool of the large ancestral waterbody. A solus lake, on the other hand, is defined as a lake formed in isolation and one which was never initially a part of a larger water system. Solus lakes are not expected to share a common species pool with other lakes. Therefore, it would be expected that: relict and solus lakes share different environments, solus lakes are species-poor and have a more variable community structure than relict lakes, species composition in solus lakes is driven primarily by colonization, relict lakes, derived from the same large ancestral waterbody, share a similar species composition and community structure, species composition in relict lakes is driven primarily by extinction, and relict and solus lakes differ in their species-environment relationships.
The objective of this thesis is to investigate these expectations and to detemine if they are correct using environmental and species incidence data from a set of glacial relict and glacial solus lakes in the Great Lakes - St. Lawrence basin.
Since the lakes addressed in this study were al1 derived from the last glacial recession, they are properly defined as glacial relict and glacial solus lakes. This is intended to differentiate them from relict or solus lakes formed from other geophysical events. However, since these distinctions are not relevant in this study, glacial relict and glacial solus lakes will be referred to hereafter. for use of discussion, simply as relict and solus lakes. Cha~ter3 Environmental Differences
An examination of environmental differences in relict and solus lakes within 3 the Great Lakes St. Lawrence basin
1. INTRODUCTION
One of the greatest challenges ecologists face is understanding what components of the environment are critical to the suwival of a species in its ecosystem. An ecosystem has such a complex environmental structure that it is virtually impossible to study every aspect of it. Instead, ecologists are forced to select specific components of the environment, i.e., environmental variables, which they think are most important in relation to the species or community under study. Traditionally. these variables have been identified as local environmental variables. Historically. ecologists have focused their studies on a small spatial scale, and explored the environmental characteristics within a discrete site. For example, the local environmental characteristics of a lake or forest stand, would be identified and correlated with the local faunal community. With the emergence of powerful computers and geographical information systems within the past decade, ecologists are now able to explore ecological patterns and processes on a larger spatial scale. Today it is possible to study the spatial ecology of species and communities with ranges spanning anywhere from an ecoregion to the entire globe.
This ability to examine environmental processes at large spatial scales has led to an emerging view in ecology that community structure is constrained not only by local environmental factors (e.g., water chemistry and lake morphology in relation to a lacustrine fish community). but also by larger scale, regional environrnental factors (e.g., climate and historical biogeography) (Ricklefs 1987; Roughgarden 1989; Menge and Olson 1990; Ricklefs and Schluter 1993). However, there is a lack of consistency in the literature as to what constitutes a local venus a regional environrnental variable. It seems that most ecologists arbitrarily define local and regional variables based on the spatial magnitude of these variables rather than in relation to the species or community under study. Chapter 3 Environmental Differences
A. OBJECTIVES OF THIS CHAPTER
The purpose of this chapter is to develop a rnethod for specifically defining local and regional environmental variables with reference to a species or community under study. This methodology should not only lead to better reproduction of field studies but should also help to detenine which environmental variables are most relevant to the existence of the species or community being exarnined. The second and third objectives of this chapter are: To examine local and regional environmental variables affecting lacustrine fish communities within selected lakes in the Great Lakes - St. Lawrence basin, and To detennine if differences in local and regional environments exist between relict and solus lakes.
7. DEFlNlNG ENVIRONMENTAL VARIABLES a) ECOLOGICAL BOUNDARlES
In order to chose the most appropriate spatial scale for an ecological study, it is first necessary to define the ecological boundary of the species or community being examined. The ecological boundary is defined here as the actual spatial lirnit in which the species or community under study exists at the present ecological tirne. For example, the ecological boundary of an entire lacustrine fish community is the entire lake that the community occupies. lnflow and oufflow tributaries are not considered to be part of the ecological boundary of this community. This is not to be confused with the geographical spatial limits of the environment containing the species or community being studied. The ecological boundary also does not take into consideration historical processes such a post-glacial dispersion and speciation which operate in evolutionary time. b) LOCAL AND REGlONAL ENVIRONMENTAL VARIABLES
Two types of environmental variables can be defined with reference to the ecological boundary of the species or community under study: local and regional. For the purpose of this investigation, local environmental variables are defined as those homogeneous Chapter 3 Environmental Differences factors which act only within the ecoldgical boundary of the species or mrnmunity under examination (Figure 3.1). Lake area and pH are examples of such local environmental variables with reference to an entire lacustrine fish cornmunity. One value at a snapshot in tirne, represents these local environmental variables for the ecological boundary. Local environmental variables are proposed to form the strongest environmental relationship with the species or community. Numerous studies, for example, have concluded that lake area and pH are strongly related to the diversity of lacustrine fish communities (e.g., Barbour and Brown 1974; Bendell and McNicol 1987; Eadie and Keast 1984; Harvey 1975,1978,1981 ; Hinch et al. 1991; Johnson et al. 1977; Matuszek and Beggs 1988; Minns 1989; Rago and Wiener 1986; Rahel1986; Rahel and Magnuson 1983; Somers and Harvey 1984; Tonn and Magnuson 1982).
Ecological Boundary
Figure 3.1. Spatial relationship between local and regional environmental variables with reference to the ecological boundary of the species or community under study. Chapter 3 Environmental Differences
Regional environmental variables are defined as factors that adon a larger spatial scale than the ecological boundary defined previously. They cornpletely encompass the ecological boundary as well as the local environmental variables defined for the species or community under study (Figure 3.1 ). Mean annual precipitation and annual number of degree days are examples of such regional environmental variables with reference to an entire lacustrine fish community. Regional environmental variables may also be directly related to the creation and maintenance of environmental variables encompassed within their existing spatial boundary including local environmental variables. Regional environmental variables, like local environmental vanables, are homogeneous within the ecological boundary and can be represented by a single value at any point in its space. However. regional environmental variables are often more difficult to interpret and quantify than local environmental variables because of their broad spatial scope. c) RELA TIONSH/PS BETWEEN LOCAL AND REGIONAL ENVIRONMENTAL VARIABLES
Every species or community has a different ecological boundary and therefore different sets of pertinent local and regional environmental variables. Even within a fairly well defined ecosystem such as a lake, different communities within a lake are defined by unique ecological boundaries and therefore contain different sets of local and regional environmental variables. For example. the ecological boundary of an entire lacustrine fish community is the entire lake. Local environmental variables for the lacustrine fish community such as lake pH and volume are homogeneous and encompass the whole lake. However, if the macrophyte community within the lake is chosen to be examined, its habitat occupies a smaller and different ecological boundary than that of the lacustrine fish community. The macrophyte community does not utilize the whole lake, only the littoral zone. Therefore, local, whole lake environmental variables for the fish community become regional variables for the macrophyte community because its ecological boundary occupies only a portion of the fish community habitat.
In order to study the ecology of lacustrine fish comrnunities. it is first necessary to understand the environment within which these fish comrnunities exist. In this thesis, the ecological boundary of a lacustrine fish community is defined as the entire lake within which the fish community exists since the fish cornmunity uses the entire lake as habitat. Cha~ter3 Environmental Differences
Environmental variables examined within this study are therefore defined with reference to this ecological boundary. Local environmental variables exarnined in this study include: lake surface area, volume, maximum depth, total shoreline perimeter, pH, specific conductivity and Secchi depth. Regional environmental variables examined in this study include: annual number of degree days, mean annual precipitation, contouring cornplexity. parent material, and sunounding lake net primary productivity. forest cover and soi1 drainage. Chapter 3 Environmental Differences
II. MATERIALS AND METHODS
A. STUDY LAKES
A total of 550 lakes divided among six regions within the Great Lakes - St. Lawrence basin of Ontario are examined in this study. Each of the six study regions represents an area composed of one or more watersheds as defined by Cox (1978) (Table Cl in Appendix C). For discussion and analysis purposes, each region has been classified as containing either relict or solus lakes based on the definitions presented in Chapter 2 sections II1. and IV., respectively . These reg ions are paired such that regions containing relict and solus lakes that are in close proximity to one another are matched as a pair. Therefore, Wawa and Algoma regions are matched as a pair, as are LaCloche and Sudbury regions, and Bruce Peninsula and Wellington regions (Figure 3.2).
1. DATABASES
The study lakes were selected from two databases compiled separately by Dr. Harold H. Harvey, Department of Zoology, University of Toronto (1997) and the Ontario Ministry of Natural Resources (OMNR) (1997). Lake data for the Bruce Peninsula, LaCloche and Wawa regions were obtained from the database compiled by Harvey (1997). Lake data in the Wellington, Sudbury and Algoma regions were obtained from the database compiled by OMNR (1997). Each database contains the following information for each lake: name, latitude, longitude, elevation, sampling date, species incidence data, and environmental data including, surface area, volume, maximum depth, total shoreline perimeter, Secchi depth, pH, and specific conductivity. Species data for 114 of the lakes compiled by OMNR were further supplemented from resources at the Royal Ontario Museum.
Watershed characteristics of areas surrounding each lake were obtained from Canadian Landsat Image maps (scale 1:500,000) obtained from Band (1997) using the Geographical Resource Analysis Support System (GRASS). GRASS is a public-domain raster GIS modelling product of the US. Army Corps of Engineers' Construction Engineering Research Laboratory. GRASS was used to create a IOOrn buffer surrounding each lake and to determine the average value of each lake for each of the Cha~ter3 Environmental Differences following regional environmental variables (map coverages): annual number of degree days. mean annual precipitation, sunounding lake net primary productivity. contouring complexity, surrounding lake forest cover. parent material. and surrounding lake soi1 drainage.
Figure 3.2. Location of study regions within the Great Lakes - St. Lawrence basin of Ontario. Algoma. Sudbury and Wellington regions contain solus lakes. Wawa, LaCloche and Bruce Peninsula regions contain relict lakes (rnap modified from Teller 1989). Chanter 3 Environmental Differences
B. STUDY VARIABLES
Fourteen environmental variables were examined to establish water chemistry, lake morphology, and surrounding lake environmental characteristics for lakes within each of the six study regions. The classification and definition of each of these environmental variables is summarized in Table 3.1.
Table 3.1. Summary of local and regional environmental variables examined in this study .
Total volume lntegral of the areas of each stratum at successive depths from the surface of the lake to the point of maximum depth. It is estimated by the following equation: V = h/3[A1 + A2 / AlA2] where h is the vertical depth of the stratum, A1 is the area of the upper surface, and A2 is the area of the lower surface. 1 Maximum depth ' Greatest depth of the lake. Shoreline Total length of the shoreline including islands. perimeter PH Logarithm of the concentration of free hydrogen ions in the water measured in the summer at the surface of the lake. Specific Inverse of the resistance of lake water to electrical flow at a conductivity temperature of 25 OC.
Secchi depth Measure of water transparency calculated at the depth of the lake l where a weighted white and black disk, 20 cm in diameter, reappears upon raising it after it has been lowered into the water beyond visibility.
1 Regional Definition - Environmental Factors Annual number of Total number of degrees per day per year that the air temperature above a lake is greater than or equal to 5 OC as interpolated from isoclines from existing weather stations using the inverse distance sq uared interpolator.
Mean annual Mean precipitation for a year as interpolated from isoclines from precipitation existing weather stations using the inverse distance squared . interpolator. Cha~ter3 Environmental Differences
Net primary Total carbon production minus transpiration expressed as the productivity number of grams of carbon per metreZ produœd par year for areas of vegetation surrounding the lake. Obtained from National Oceanic and Atmospheric Administration data predicted using an Advanced Very High Resolution Radiometer.
Contouring Rugosity of the surrounding landscape of the lake calculated as complexity the standard deviation of elevation from a digital elevation model.
Forest cover Density of the vegetation surrounding the lake calculated from Landsat frequency bands 3,4, 5 using an index of vegetation.
Parental material Parental material or bedrock material of the lake basin obtained from a digitized geology rnap of Ontario.
Soil drainage Porosity of the soit surrounding the lake obtained from a digitized soils map of Ontario.
1. LOCAL ENVIRONMENTAL VARIABLES
Lake morphology and water chemistry variables are categorized as local environmental variables. These variables are homogeneous and act only within a lake, the ecological boundary of the lacustrine fish community. Numerous studies have focused on the relationship between these local factors and fish species composition within Ontario lakes (e.g., Johnson et al. 1977; Harvey 1978, 1981; Eadie and Keast 1984; Somers and Harvey 1984; Bendell and McNichol1987; Matuszek and Beggs 1988; Minns 1989; Hinch et al. 1991).
Lake morphometry is a function of the geologic origin of the lake, subsequent water movements which have modified the basin since the lake's origin, and the degree of sediment loading from the lake's watershed. Once the lake basin is formed, physical, chernical and biological factors interact to produce an ecosystem within the lake. This ecosystern persists despite the continual movement of the water that is characteristic of al1 aquatic ecosystems. The following lake morphology factors are selected for this study: surface area, volume, total shoreline perimeter, and maximum depth. Cha~ter3 Environmental Differences
A standard protocol described by Dodge et al. (1978) in the OMNR lake survey was used for each lake to measure local environmental variables. The following is a summary of why each of these lake morphology variables is chosen for this study.
Surface area is predictive of species richness (e.g., Barbour and Brown 1974; Browne 1981). and highly correlated with habitat diversity (e.g., Barbour and Brown 1974; Eadie and Keast 1984; Minns 1989). Both species richness and the diversity of fish species assemblages have been shown to increase with lake area. Barbour and Brown (1974), Harvey (1978,1981 ), Browne (1981 ), Rahel(1982). Tonn and Magnuson (1982) and othen have shown a positive, significant correlation between species richness and lake area. Barbour and Brown (1974), and Eadie and Keast (1984) and others have shown that increasing lake area encompasses an increasing number of habitats. The larger a lake, the greater the local variation in water quality and hydrology such as inflow or oufflow areas, sheltered coves, and eutrophicated sites. As well, the erosive effects of waves and wind Vary greatly due to bays and other fomis of shoreline undulation.
Volume is representative of the three dimensional aspect of the aquatic environment available to fish species. Since fish utilize the three dimensional aspect of their environment, lake volume is expected to be more representative of fish habitat than lake surface area. Hawey (1978) and (1981) has shown that species richness increases with lake volume.
Maximum depth is predictive of lake thermal stratification which may be one of the most important factors in detenining species divenity in lakes. Salmonids such as lake trout, and lake whitefish require cold temperatures found in hypolimnetic water. These species are unable to survive in shallow lakes which do not stratify thermally (e.g., Harvey and Coombs 1971 ), thereby precluding the existence of these hypolimnetic species (e.g ., Magnuson et al. 1977). Winter oxygen levels also Vary depending on lake depth. In shallow lakes, depleted oxygen levels in the winter may lead to winter fish kills (Casselman and Harvey 1975; Tonn and Magnuson 1982; Robinson and Tonn 1989).
Shoreline perimeter is the interface between the terrestrial and aquatic environment. i-e., an ecotone. which is a region of elevated biodiversity (Krebs 1978). It is also a measure of the littoral zone and harboun most of the smaller fish species as well as Cha~ter3 Environmental Differences
acting as a nursery for the young-of-the-year. The importance of the littoral zone to lake ecosystem function has been emphasized in the literature i.e., Lodge et al. (1988) and Frost et al. (1 988).
Lake water chemistry has important effects on the species composition of the lake. Water chemistry within each lake is extremely varied. and reflects the lake's origin. subsequent modifying events of water movements within the basin since the lake's origin, and the degree of chemical loading from the lake's watershed through surface runoff and sedimentation. lnorganic nutrients within a lake provide the chemical compounds on which the entire food chain is based. Bottom-up control in food chahs emphasizes the importance of nutrient and light availability for primary producers and the subsequent energy and nutrient flow through a series of trophic levels (e.g.. Elton 1927; Lindeman 1942; Carpenter et al. 1985; McQueen et al. 1986; McQueen et al. 1989). The nutrients that are important in lakes are those which are often in short supply and which limit growth of plants and animals. The major components of these nutrients include: CO,. O,, NH,, NO,, PO,, SiO,, SO,,and Fe (Wetzel 1983). Important minor nutrients that may occasionally be in short supply include: rnanganese, cobalt, molybdenum, copper and zinc (Wetzel 1983). Three water chemistry variables are examined in this study: pH, specific conductivity, and Secchi depth.
The water chemistry sarnpling protocol used in this study is summarized in Ontario Ministry of the Environment (1981). The following is a summary of why each of the water chemistry factors is chosen for this study.
Lake pH is correlated with species richness by limiting the distribution of certain species of fish (e.g. cyprinids) in acid-stressed systems (e.g., Harvey 1975. 1980, 1982; Rahel 1982.1986; Rahel and Magnuson 1983; Rask 1984a. 1984b; Somers and Hanrey 1984; Schindler et al. 1985; Rago and Weiner 1986). Therefore. large circurnneutral lakes usually contain the most species and the rarest species. Most lakes frequently experience changes in pH between 6.5 and 7.5 with no negative effects on the lake's Rora and fauna. However. when the pH of a lake falls below 6 over the long tenn. there Chapter 3 Environmental Differences is a noticeable decrease in the abundance of many species. A long-terrn pH level of 5 in a lake will kilt most species of organisms found in circumneutral lakes.
Specific conductivity provides a measure of total ionic concentration and has been correlated with fish biomass and productivity (Rawson, 1960). The specific conductivity of lake water is proportional to the concentration of its dissolved major elements: Ca, Mg, Na, K, H, Fe, NH,, HCO,, SO,, CI and F. These major elements determine which species can survive in a lake depending of the tolerance of fish species to the individuai major elernents (Wetzel 1983). In open lakes, the chernical composition of the water is determined prirnarily by the composition of influents from its watershed and the atrnosphere. In Ontario, high conductivity lakes usually have lirnestone/dolomite basins. Water salinity in closed basins is increased by evaporation and inputs of dissolved ions from runoff and rnodified by precipitation of salts (Hutchinson 1957). Specific conductivity is a good overall parameter for general nutrient status in the study areas on the Shield composed mostly of granites and gneisses without local calcareous influences. Due to this composition of bedrock on the Shield, specific conductivity has a high correlation with summer pH, major cations and also with total nitrogen and phosphorous. Specific conductivity also has a very high correlation with algal productivity (llmavirta 1983).
Secchi depth is a measure of the phototrophic zone of the lake which is inversely related to the lake's productivity (algal biomass). In general, oligotrophic lakes tend to be clear and eutrophic lakes tend to be turbid (Nicholls and Dillon 1978; McQueen et al. 1990).
2, REGIONAL ENVIRONMENTAL VARIABLES
Watenhed characteristics of the areas surrounding each lake are expressed as regional environmental variables. These variables act over a larger spatial scale than the ecological boundary of the lacustrine fish community. These regional environmental variables, like local environmental variables. completely encompass the ecological boundary and are hornogeneous throughout the ecological space of the lacustrine fish community. Regional environmental factors affect the structure and function of the watershed and thus the takes within the watershed. Watershed characteristics are Chapter 3 Environmental Differences important determinants of lake structure, mostly due to their role in nutrient cycles. The size, slope, geological composition, and climate of the lake's watershed basin influences the identity and quantity of minerals suspended or dissolved in the lake or deposited in its sediments. The size of the lake's drainage area in relation to the surface area of the lake is also important. Higher productivity in lakes is often associated with large drainage areas (e.g ., Wohl et al. 1995). Seven waters hed characteristic variables are examined in this study: annual number of degree days, mean annual precipitation, net primary productivity, contouring complexity, surrounding lake forest cover, parent material, and surrounding lake soi1 drainage.
The following is a summary of why each of the surrounding lake variables is chosen for this study.
Mean annual precipitation influences the water tevel and sedirnent and nutrient transport in lakes. The main source of nitrogen in a watershed is rainfall and the main source of phosphorous is soi1 erosion.
Annual number of degree days is a measure of solar radiation which is responsible for establishing thermal stratification in lakes. Solar radiation also regulates the rates of chemical reactions and biological processes within a lake. An increase in heat during the summer increases the metabolism of fish and other poikilotherms. The rate of recycling organic and mineral components in lakes also increases with temperature. In general, chemical reactions and biological activities such as respiration double for each rise in temperature of 10 OC (see Johnson et al. 1977).
Surrounding lake net primary productivity is a predictor of the detritus loading of a lake from its surrounding watershed. Chapter 3 Environmental Differences
Contour complexity is a measure of the drainage area of the lake. The higher the contour complexity of the land surrounding the lake, the smaller the lake's drainage area. In general, lakes with large drainage areas collect more nutrients from their drainage basins than lakes with small drainage areas. The ratio of lake surface area to the drainage area is a major factor influencing the lake's trophic state (Wetzel 1983).
Surrounding lake forest cover is an indirect measure of the degree of soi1 erosion that enters a lake as surface runoff and may also heavily influence the arnount of coarse woody debris cover within a lake. The greater the density of forest cover surrounding a lake, the smaller the amount of soi1 erosion entering a lake as surface runoff. Particles of eroded sediment cause turbidity in lakes. This is usually undesirable as sediments may kill fish or impair their respiration by clogging their gills, smother fish spawning gravel. and bury submerged plants. Soil erosion may also alter the water chemistry of a lake. For example, phosphorous and iron are abundant in lakes with high rates of surface runoff since they are generally transported as salts adsorbed to soi1 particles (Home and Goldrnan 1994).
Parent material is chosen because the amount and type of trace elements and silica in a lake are controlled by the weathering of parent rock. The gradua1 weathering and decay of the parent rock releases material directly to the runoff water. The soR waters of lakes in resistant, old rocks. such as granite or metarnorphosed grits resemble rainwater in their chernical composition. Sedimentary rocks dissolve more easily to produce lakes with hard water.
Surrounding lake soi1 drainage is directly related to the amount of surface runoff and groundwater a lake receives. In general, lakes with drainage areas consisting of porous soils receive more water recharge as groundwater than lakes with drainage areas consisting of fine soils. Porous soils enable water to infiltrate the ground after a precipitation event and recharge the water table. Fine soils such as clay do not permit easy penetration, thereby increasing surface runoff into a lake. Cha~ter3 Environmental Oifferences
C. STA TISTICAL METHODS
i. NORMALITV, LlNEARITY AND TRANSFORMATION OF ENVIRONMENTAL VARIABLES
All local and regional environmental variables are checked for normality. linearity and outliers. The Kolmogorov-Smirnov goodness-of-fit test (Kolmogorov 1933; Smirnov 1939). is used to test al1 variables for normality using the SAS procedure UNIVARIATE (SAS Institute 1995). Variables are transformed if necessary to approximate normal distributions and linearize bivariate relationships. The resultant transformed environmental variables are individually plotted against one another in a casernent plot using NT-SYS (Rohlf 1992). Residual analyses are performed to examine the uniformity of the variance in the regressions.
2. WILCOXON-MANN-WHITNEY TEST
Two local environmental data sets are used in this study; the Harvey (1997) lake dataset and the Ontario Ministry of Natural Resources (1997) lake dataset. It is necessary to test for similarity between the two datasets before questions relating to environmental variation across ail of the study regions and between study regions can be examined. The Wilcoxon-Mann-Whitney test (Wilcoxon 1945; Mann and Whitney 1947), is a non- pararnetric rank test used to test a two-tailed nuIl hypothesis that there is no difference between two samples. Wilcoxon-Mann-Whitney tests are used to test for similarity between the two data sets by examining environmental rneasurements taken from the same Iake sampled from the two separate datasets. A total of one hundred and ninety- eight lakes are present in both the Ontario Ministry of Natural Resources (1997) and Harvey (1997) data sets. The following lake measurements are tested: surface area, specific conductivity. elevation. maximum depth, total shoreline perimeter and pH.
3. CANONICAL CORRELATION ANAL YSIS
Canoniml correlation analysis (CCorrA) (Jongman et al. 1993, is used in this study to determine if relationships exist between local and regional environrnental variables. CCorrA is a multivariate statistic which rneasures how groups of variables are correlated Chapter 3 Environmental Differences with each other in multivariate space. The structure of correlations between tocal and regional environmental variables, across al1 of the lakes in this study, is examined by constructing two groups of linear compounds, terrned canonical variates. Canonical variates are groups of ordination axes derived from one set of variables such as the local environmental variables. This set is then rotated, under certain constraints, to correlate maximally with a group of ordination axes derived from a second set of variables such as regional environmental variables. lntraset and interset correlations are derived by correlating each canonical variate with either the original variables of the same set (intraset correlation), or the variables of the opposite set (interset). lntraset or interset correlations, when squared, indicate the proportion of variance expressed by the corresponding canonical variate. Redundancy, the amount of variation the canonical variates from one set of variables extract from the other set of variables, is also calculated by taking the average of the intenet correlations on a single canonical variate. CCorrA is used to examine the relationships between the following sets of environmental variables: local versus regional, lake morphology (a subset of the local environmental variable group) versus regional, and water chemistry (a subset of the local environmental variable group) versus regional. These relationships are visually defined in Figure 3.3. Chapter 3 Environmental Differences
LOCAL ENVIRONMENTAL VARIABLES REGIONAL ENVIRONMENTAL VARIABLES m precipitation \ surface area degree days shoreline perimeter A maximum depth contouring complexity parent material
net primary productivity Water Chemistry O forest cover PH specific conductivihr soi1 drainage \\ - Secchi i
Figure 3.3. Venn diagrarn summarizing the relationships examined between sets of environmental variables using CCorrA.
4. PEARSON-PRODUCT MOMENT CORRELA TIONS
The strength of the relationships among the environmental variables is assessed using a Pearson Product Moment correlation matrix (Pearson 1920) across the suite of local and regional environmental variables. The significance level for the probability of cornmitting a Type I error due to multiple cornparison is adjusted using a sequential Bonferroni correction.
5. PRlNClPAL COMPONENT ANAL YSlS
Principal component analysis (PCA) (Hotelling 1933). is used in this study to detenine if relict and solus lakes differ in their environmental characteristics. PCA is a rnultivariate statistic which reduces the original environmental variable data set to several independent vectors defining lake associations according to the greatest cumulative Cha~ter3 Environmental Differences
variation. PCA is performed on correlation matrices composed of both relict and solus lakes to identify how the pooled effect of environmental variables surnrnarizes inter-Iake patterns. PCA is performed on the following five sets of environmental data to detemine which sets of environmental variables best discriminate differences between glacial relict and glacial solus lakes: combined local and regional, local, regional, lake morphology, and water chernistry.
These PCAs are repeated to examine pairwise comparisons for the following pairs of proximal relict and solus regions: Wawa and Algoma, LaCloche and Sudbury, and Bruce Peninsula and Wellington (Figure 3.2).
PCA has been criticized for frequently distorting relationships in the resulting ordination (de Leuw 1987). Distortion is created when the data do not meet the assumption of linearity (Heiser 1987) or the data set contains data with too rnany zero values (Legendre and Legendre 1983). The number of dimensions considered interpretable for each PCA is determined using the Broken Stick Model (Frontier 1976).
6. DISCRIMINANT ANAL YSIS
To test for significant differences in the environment between relict and solus lakes. a discriminant analysis (Legendre and Legendre 1983). is performed on lake scores from each of the first two axes of al1 PCAs. Discriminant analysis, also termed discriminant function analysis, canonical vafiate analysis and canonical discriminant analysis, is a multivariate statistic which is used to maxirnally contrast two groups of variables in order to examine whether significant differences exist between the two groups of va riables. The resultant discriminant function, also terrned the mnonical variate or canonical axis, is the maximum difference behrveen the two groups. Discriminant analyses are performed to test for significant differences in the environment between: relict and solus lakes, and Chabter 3 Environmental Differences
each of the paired regions: Wawa and Algoma, LaCloche and Sudbury, and Bruce Peninsula and Wellington. The sets of environmental variables examined for each cornparison include: . local, regional, combined local and regional, lake morphology, and water chernistry. Chapter 3 Environmental Differences
III. RESULTS
A. PRELIMINARY DATA ANALYSE
All local and regional environmental variables were checked for normality. linearity and outliers. Variables were transformed as necessary to approximately normalize distributions and linearke bivariate relationships. These transformations are surnmarized in Table 3.2. The results of the residual analyses indicate that there are no significantly skewed variances arnongst the environmental variables.
Table 3.2. Summary of transformed environmental variables. A perfectly normal distribution has a skewness and kurtosis value of O and a norrnality value
Environmental Skewness Kurtosis Normality Variable P>O.OS log surface area 0.1 1 0.46 0.99 log volume 0.06 -0.04 0.98 square root 0.36 0.00 0.96 maximum depth log total shoreline 0.36 0.54 0.98 perimeter pH -0.50 0.29 0.97 !og specific 0.25 -0.84 0.94 cond uctivitv square root secchi 0.36 0.92 0.98 depth log degree days 0.06 -0.98 0.91 square net -0.34 -0.09 0.97 primary productivity negative inverse 0.21 -1 -26 0.9 1 mean annual precipitation square root 0.14 0.79 0.96 contour complexity surrounding lake -3.56 14.83 0.62 forest over parent material -0.78 -1 34 0.59 surrounding take 0.25 0.33 O -78 soi1 drainacte Chapter 3 Environmental Differences
B. MERGING OF DA TASETS
The Wilcoxon-Mann-Whitney test is used to detemine if signifiant differences exist between the Harvey (1997) and OMNR (1997) datasets using one hundred and ninety- eight lakes present within both datasets. No significant differences are found between the two data sets for the following environmental measurements examined: surface area, elevation, maximum depth, total shoreline perimeter. pH and specific conductivity (P>0.05). Therefore, the two environmental data sets are considered to be similar and are merged for statistical analysis (Table 3.3).
Table 3.3. Summary of Wilcoxon-Mann-Whitney test results between 198 lakes present within both Harvey (1997) and OMNR (1 997) datasets.
Perirneter Sum of Negative Ranks -4279 -5775 -1 197 -1296.5 -1 626.5 -4879.5
Sum of Positive Ranks 4236 5400 694 1259.5 1493.5 5560.5 1 1 Cases lncluded 130 149 61 71 95
I Missing Cases 25 5 72 86 3 1
1 Two Tailed P-Value for 0.961 1 0.7231 0.071 4 0.91 79 0.7467 0.4977 Normal Amroximation
C. RELA TIONSHIPS BEWEEN ENVIRONMENTAL VARIABLES
1. GROUP COMPARISONS OF ENVIRONMENTAL VARIABLES
Canonical correlation analysis is used to test for relationships between the following sets of environmental variables:
9 local versus regional, lake morphology (a subset of local) versus regional. and r water chemistry (a subset of local) venus regional. Cha~ter3 Environmental Differences
Summary Results from the CCorrA indicate that there is a very strong first canonical variate correlation between local and regional environmental variables (0.73) which accounts for 63% of the total variance (Table 3.4). The percent redundancy for local and regional environmental variables is 7 8% and 13% respectively. These results indicqte a strong relationship between local and regional lake variabtes. Local envitonmental variables are divided into lake morphology and water chemistry variables and canonically correlated with regional environmental variables. Water chemistry variables are found to be more highly correlated with regional environmental variables than the lake morphology variables (Table 3.4). In each CCorrA, regional environmental variables are found to summarize more local environmental variation (percent redundancy) than local environmental variables are able to summarize regional environmental variation.
Table 3.4. Summary of canonical correlation analyses between local and regional, lake morphology and regional, and water chemistry and regional environmental variables.
Correlation Percent of 63% 35% 51% Variance Percent Redundancy for 18% 1 13% 21% 18% 32% / 12% Each Set of Environmental Factors
All of the canonical correlations between the local and regional sets of environmental variables are significant (P<=0.05) using Wilk's Lambda test of significance (Jongman et al. 1995). A summary of the results of the first four pairs of canonical variates is presented in Table 3.5. The first canonical correlation was 0.73 (63% of the variance); Chapter 3 Environmental Differences the second was 0.55 (24% of the variance); the third was 0.32 (6% of the variance); and the fourth was 0.25 (4% of the variance). Total percent of variance and total redundancy indicate that the first and second pair of canonical variates are moderately related, but the third and fourth pair are only minimally related. Interpretation of the third and fourth pair is therefore marginal. Chapter 3 Environmental Differences
Table 3.5. Correlations, standardized canonical coefficients, canonical wrrelations, percents of variance, and redundancies between local and regional variables and their corresponding canonical variates.
Variate Variate Conelatio Coefficient Correküo Cwfficknt Cornl.th Coelncknt Correlatio Coefficient n n n n Local Set
Area 0.18 -0.08 0.74 -0.08 -0.4 -1.09 0.14 0.71 Volume 0.39 0.03 0.85 0.71 -0.1 -0.1 0.07 -0.8 Maximum 0.59 0.25 0.52 0.13 0.43 1.1 0.2 -0.19 Depth Shoreline 0.22 -0.11 0.74 0.43 -0.3 0.26 0.06 -0.4 Perimeter PH -0.86 -0.41 0.21 0.43 0.31 0.6 -0.06 -0.43 Conductivity -0.9 -0.52 -0.11 0.01 0.16 -0.07 0.3 0.86 - -- Secchi Depth -0.52 0.13 0.12 -0.1 0.25 -0.03 0.73 0.95 Percent of 0.34 0.3 1 0.09 0.1 0 Total: Variance 0.84 Redundancy 0.18 0 .O9 0.01 0.01 Total= 0.29
Regional Set Degree Days 4.31 -0.53 -0.9 -0.49 -0.18 0.64 -0.1 1 -0.88 Precipitation -0.01 -0.19 -0.68 -0.44 0.38 0.38 -0.16 0.44 Net Primary 0.4 0.44 -0.61 0.1 1 -0.13 -0.76 -0.08 0.25 Productivity Contour 0.51 0.2 -0.35 -0.1 0.4 0.34 0.14 0.12 Complexity Forest Cover 0.46 0.18 -0.27 -0.12 0.45 0.42 -0.23 -0.19 Parent -0.63 0.24 0.14 0.05 -0.03 -0.66 4.6 -1.44 Material Soil Drainage -0.86 -0.76 0.25 0.16 0.1 0.59 -0.1 1.23 Percent of 0.24 0.29 0.1 1 0.07 Total= Variance 0.71 Redundancy 0.13 0.09 0.01 0.00 Total= 0.23
Canonica t 0.7 3 0.55 0.32 0.25 Correlation
Correlations of the first and second canonical variates are listed in column one and three, respectively, of Table 3.5. Variables with a correlation greater than or equal to the absolute value of 0.3 are considered to be highly correlated and are thus indicated in Chapter 3 Environmental Differences bold. Variables in the local and regional data sets that correlate highly with the first canonical variates indicate that large, acidic, turbid lakes with low conductivity also tend to be located in forested, productive, relatively cool hilly areas with pool soi1 drainage. Correlations of the second pair of canonical variates indicate that large lakes also tend to be located in Rat, productive and relatively cool and dry areas.
A detailed summary of the results of the canonical correlation analyses between lake morphology and regional and water chemistry and regional environmental variables are shown in Tables Dl and D2 in ~ppendixD.
2. INDIVIDUAL COMPARISONS OF ENVIRONMENTAL VARIABLES
The strength of the relationships between the environmental variables is assessed by calculating a Pearson-Product Moment correlation maûix across the suite of local and regional environmental variables. The resulting significant Pearson Product-Moment correlations after a sequential Bonferroni Correction are summarized in Table 3.6. Correlation values greater than or equal to the absolute value of 0.5 indicate a very strong relationship between environmental variables. The results indicate that there are three clusters of highly inter-correlated environmental variables. Lake morphology variables: surface area. volume, total shoreline perimeter, and maximum depth are al1 highly inter-correlated. This is not surprising considering they are al1 measures of lake site. Specific conductivity, pH, and soi1 drainage are also highly inter-correlated with each other. These variables are related by the degree of chemical loading within a Iake. Lastly, mean annual precipitation, number of annual degree days and surrounding lake net primary productivity are highly inter-correlated with each other. These variables are al1 masures of climate. Overall. a strong relationship is found between local, regional, and local-regional variables (Table 3.6). Ninety-five percent of the local environmental variable correlations are significant (Pc=0.0001). Eighty-one percent of the regional environmental variable correlations are significant (P<=0.0001). Seventy-one percent of local-regional environmental variable correlations are significant (Pc=0.0006). Annual number of degree days and mean annual precipitation are most highly conelated with lake morphology. Contouring cornpiexity, parent material, and surrounding lake forest cover, net primary productivity, and soi1 drainage are most highly correlated with water chemistry (Table 3.6). Surface area
Volume
Maximum depth
Shoreline perimeter
Specific conductivity
Secchi depth
Degree days
Precipitation
Net primary productivity
Contour complexity
Forest cover
Parent material Chapter 3 Environmental Differences
D. LAKE ENVIRONMENTAL COMPOSITlON
Principal cornponent analysis (PCA) (Hotelling 1933). is performed to identify how sets of environmental variables summarize inter-lake patterns for relict and soius lakes. Four sets of lake data are exarnined in this study: All relict and solus lakes combined, and Pairs of relict and solus regions: Wawa and Algorna, LaCloche and Sudbury, and Bruce Peninsula and Wellington. The following five sets of environrnental variables are exarnined for each set of lakes: cornbined local and regional, local, regional, lake morphology, and water chemistry.
7. ALL RELICT AND SOLUS LAKES COMBINED
a) ENVlRONMENTAL DIFFERENCES
Summary Only the first eigenvalue is significant for each of the PCAs using the Broken-Stick model (Frontier 1976) except for the PCA of combined local and regional variables where the first two eigenvalues are significant. The percent of environmental information summarized in the significant eigenvalues for each PCA are: 1) 50% for combined local and regional environmental variables, 2) 52% for local environrnental variables, 3) 30% for regionai environmental variables, 4) 70% for lake morphology variables, and 5) 65% for water chemistry variables.
Details The PCA of combined local and regional environmental variables extracts two significant factors incorporating a total of 50% of the data variation. The first component accounts for 32% of the variance (Table 3.7). The high correlation of the first principal component Cha~ter3 Environmental Differences with lake morphology and water chemistry variables suggests an overall lake site and water chemistry gradient. The second component explains 18% of the data variation. This cornponent loads positively on surrounding lake net prirnary productivity, mean annuat precipitation. surrounding lake forest cover and contour complexity. It loads negatively on surface area and total shoreline perimeter. . .
Table 3.7. Correlations of local and regional variables with the first No principal components of a principal component analysis of al1 relict and solus lakes.
IvmGtaiÏ[Principal Component 1 Variable 1 Number
Surface Area 0.27 -0.32 Volume 0.32 -0.18 Maximum 0.36 -0.05 Depth Total Shoreline 0.28 -0.30 Perimeter H -0.30 -0.22 1 çpecific -0.35 -0.10 11 Conductivitv 1 1
Annual Number 1 -0.26 1 0.27 of Degree Days Mean Annual -0.13 0.38 Precipitation Net Primary 0.03 0.44 Productivity Contour 0.1 5 0.30 Complexity Surrounding 0.12 0.31 Forest Cover Parent Material -0.28 -0.1 8 Surrounding -0.30 -0.28 Soil rai nage Percent of 0.32 0.1 8 Total Variation 1 Cumulative 0.32 0.50 Percentaae Cha~ter3 Environmental Differences
The separation of lakes by the PCA illustrate the distinct grouping of relict and solus lakes (Figure 3.4). Relict lakes tend to be either small, deep lakes with a high pH and conductivity or large shallow, acid lakes with a low conductivity. Solus lakes tend to be either small, shallow, acid iakes or large, deep lakes with a high pH and conductivity (Figure 3.4). A strong regional pattern in lake environmental charactefistics is also evident for each of the six study regions (Figure 3.5).
A summary of the PCA results for local, regional, lake morphology and water chemistry variables are found in Appendix E. Tables El to E4 in Appendix E list those variables which load highly (>=/0.3/) on each of the significant eigenvalues for each PCA. Figures El to E4 in Appendix E surnmarize the relict and solus lakes in relation to the first two principal components of each PCA.
Chapter 3 Environmental Differences
6) STA TSTICAL SlGNlFlCANCE OF ENVRONMENTAL DIFFERENCES
Discriminant analyses are perfomed to assess prediction of mernbership in relict and solus lakes using the first two principal components of PCAs perfomed on the following sets of environmental variables: combined local and regional, local lake morphology, water chemistry, and regional.
Summary The results of the discriminant analyses (Table 3.8), indicate that relict and solus lakes have significantly different environments in terms of the following sets of environmental variables examined: combined local and regional (P < 0.000001), local (P < 0.000001), water chemistry (P c 0.000001), and reg ional (P < 0.000001 ). Lake morphology is the only set of environmental variables for which relict and solus lakes do not differ significantly (P c 0.60). This indicates that relict and solus lakes have a sirnilar morphology. Group centroids for relict and solus lakes for lake scores on PCAs of each of these sets of environmental variables are represented in Figures 3.4 and El to E4 in Appendix E. There is a significant separation between relict and solus lakes with regards to water chemistry. Solus lakes are significantly more basic, have a lower specific conductivity and are more turbid than relict lakes. There is also a signif cant separation in relict and solus lakes with respect to their regional environmental variables. Solus lakes have a significantly lower surrounding lake forest cover and net primary productivity, a lower contour complexity and higher surrounding lake soi1 drainage properties than relict lakes. Chapter 3 Environmental Differences
Table 3.8. Summary of discriminant analyses of relict and solus lakes using the first two principal components of principal component analyses of combined local and regional environmental variables, local environmental variables, regional environmental variables, lake morphology variables, and water chemistry variables.
Combined Lake Water Local Regional Local and Morphology Chemistry Environmental Environmental II Regional Variables Variables Variables Varia Mes Environmental Variables U Eigenvalue 0.1 1 .O019
Canonical correlation Wilks lambda
Degrees of freedom Significance level Relict Solus
Classification results: % Predicted w relict lakes % Predicted solus lakes
Discriminant analyses are also performed to assess prediction of membership in each of the six study regions. All of the discriminant analyses are highly significant (P < 0.000001) for each of the sets of environmental variables examined: combined local and regional, local, lake rnorphology, water chemistry, and regional. Tables FI to F5 in Appendix F summarize the results of these discriminant analyses. Chapter 3 Environmental Differences œ
2. COMPARISONS OF PROXIMALLY PAIRED REUCT AND SOLUS LAKE REGIONS
PCAs are perfoned to examine pairwise cornparisons for the following pain of proximal relict and solus lake regions: Wawa and Algorna, LaCloche and Sudbury. and Bruce Peninsula and Wellington. Cornparisons of the PCAs of paired regions indicate Mat LaCloche and Sudbury regions have the greatest amount of their local and regional environmental information summarized in significant eigenvalues (58%) followed by Bruce Peninsula and Wellington regions (54%), and Wawa and Algoma regions (46%) (Table 5.9). For al1 of the sets of environmental variables examined using PCA, Wawa and Algorna regions have the least arnount of their environmental information summarized in significant eigenvalues of al1 three paired regions except for the PCA using regional environmental variables.
Table 3.9. Percent of environmental information surnmarized in the significant eigenvalues for each principal component analysis across each of the proximally paired regions. The number of significant eigenvalues for each principal component analysis using the Broken Stick model (Frontier 1976) is indicated in brackets.
Environmental Wawa and Algoma LaCloche and Bruce Peninsula Variables Used in Regions Sudbury Regions and Wellington Each PCA Regions Local and Regional 46% 58% 54% (3 (3)
Local
Lake Morphology 1 58% 1 59% 1 65%
1 1 Water Chemistry 1 1 46% 42%
Reg ional 1 77% 68% 35% Cha~ter3 Environmental Differences
a) WAWA AND ALGOMA LAKES
i. ENVIRONMENTAL DIFFERENCES
The principal component analysis of combined local and regional environmental variables extracts one significant factor incorporating a total of 46% of the data variation. Regional environmental variables correlate highly on the fint principal component. This principal component loads positively on parent material and surrounding lake soi1 drainage, and negatively on mean annual precipitation, surrounding lake net primary productivity and surrounding lake forest cover suggesting a strong productivity gradient (Table 3.10).
Table 3.10. Correlations of local and regional vanables with the fint two principal components of a principal component analysis of Wawa and Algoma la kes.
1 Environmental 1 Principal Component 1 Variable -~umber
Surface Area 0.12 0.58 Volume 0.1 1 0.23 Maximum Depth -0.1 1 0.46 Total Shoreline 0.08 0.59 Perimeter pH 0.19 -0.06 Specific Conductivity 0.05 -0.1 O Secchi Depth -0.21 -0.04 Annual Number of 0.26 -0.13 Degree Days Mean Annual -0.37 0.02 Precipitation Net Primary Productivity -0.34 0.09-- Contour Complexity -0.27 -0.05 Surrounding Forest -0.33 0.01 Cover Parent Material 0.34 -0.02
Surrounding- Soi1 0.34 -0.02 Drainage - Percent of Total 0.46 0.1 5 Variation Cumulative 0.46 0.62 Percentaae Cha~ter3 Environmental Differences
The separation of lakes by the PCA illustrates a very distinct grouping of Wawa (relict) and Algoma (solus) lakes (Figure 3.6). Wawa lakes tend to be located in areas with high productivity and fine soils. Algoma lakes tend to be located in unproductive areas with coarse soils.
A summary of the PCA results for local, regional, lake morphology and water chemistry variables are found in Appendix E. Tables E5 to E8 in Appendix E list those variables which Joad highly (>=/0.3/)on each of the significant eigenvalues for each PCA. Figures E5 to E8 in Appendix E sumrnarize the Wawa and Algoma lakes in relation to the first two principal components of each PCA.
Chapter 3 Environmental Differences
Il. STA TISTICAL SIGNIFICANCE OF ENVIRONMENTAL OlffERENCES
The results of the discriminant analyses (Table 3.1 1). indicate that Wawa (relict) and Algoma (solus) lakes have significantly different environments in ternis of the following sets of environmental variables examined: cornbined local and regional (P < 0.000001), local (P < 0.000001), water chemistry (P < 0.000001), and regional (P < 0.000001 ). The lake morphology set is the only set of environmental variables for which Wawa and Algoma lakes are not significantly different (P c 0.06). This indicates that Wawa and Algoma lakes share a similar lake morphology. Group centroids for Wawa and Algoma lakes for lake scores on PCAs of each of these sets of environmental factors are represented in Figures 3.6 and E5 to E8 in Appendix E. Overall, there is a significant difference in both local and regional environmental variables between Algoma and Wawa lakes. Algoma lakes are significantly larger and are more basic with a lower specific conductivity and are more turbid than Wawa lakes. Algoma lakes also have a lower mean annual precipitation. a lower surrounding forest cover and net primary productivity and a higher soi1 drainage than Wawa lakes. Cha~ter3 Environmental Differences
Table 3.1 1. Summary of discriminant analyses of Wawa (relict) and Algoma (solus) lakes using the first two principal components of principal component analyses of cornbined local and regional environmental variables, local environmental variables, regional environmental variables, Iake morphology variables, and water chemistry variables.
Environmental Variables Eigenvalue 4.70 0.04 0.31
Canonical 0.91 0.20 O .49 correlation 1 Wilks lambda ' 0.18 0.96 0.76
Degrees of 1 2 freedom Significance 0.000001 level Relict Solus Relict Solus Relict Solus lakes Lakes Lakes Lakes Classification results: t Oh Predicted 98.00 2.00 56.00 44.00 60.00 40.00 relict lakes + III % Predicted 2.20 97.80
6) LaCLOCHE AND SUDBURY LAKES
i. ENVIRONMENTAL DIFFERENCES
The principal component analysis of combined local and regional environmental variables extracts three significant factors incorporating a total of 58% of the data variation. The first component (Table 3.12) accounts for 28% of the variance. This component loads positively on the annual number of degree days and negatively on pH. parent material and surrounding lake soi1 drainage. The second component explains 16% of the data variation. The high correlations of the second principal component with lake morphology variables suggest an overall size gradient (Table 3.12). The third Cha~ter3 Environmentai Differences
cornponent accounts for 15% of the variance. The high correlations of the third principal component with mean annual precipitation, surrounding lake net primary production and surrounding lake forest cover suggest an overall productivity gradient.
Table 3.12. Correlations of local and regional variables with the first Iwo.principal cornponents of a principal component analysis of LaCloche and Sudbury lakes.
Perimeter 1 DH -0.31 0.02 0.26 Specific -0.07 -0.09 0.1 7 Conductivity Secchi Depth 0.21 0.29 0.06 Annual Number O .43 0.1 0 -0.14 of Degree Days Mean Annual -0.00 0.06 0.53 Precipitation Net Primary O -29 -0.03 0.39 Productivity Contour 0.28 0.08 0.29 Complexity Surrounding 0.09 -0.02 0.48 Forest Cover Parent Material -0.37 -0.09 0.03 Surrounding -0.36 -0.06 0.01 Soil Drainage
The separation of lakes by the PCA illustrate a very distinct grouping of LaCloche (relict) and Sudbury (solus) lakes (Figure 3.7). LaCloche lakes tend to be more acid and located in warmer areas with coarser soils than Sudbury lakes. Lakes in both LaCloche and Sudbury regions varied greatly in size. Chapter 3 Environmental Differences
A summary of the PCA results for local. regional. lake morphology and water chemistry variables are found in Appendix E. Tables E9 to El2 in Appendix E Iist those variables which load highly (>=/0.3/)on each of the significant eigenvalues for each PCA. Figures E9 to El2 in Appendix E summarize the Lacloche and Sudbury lakes in relation to the first two principal components of each PCA. Cha~ter3 Environmental Differences
LaCloche Lakes Centroid m 1 .
Sudbury Lakes Centroid
PRINCIPAL COMPONENT 1
LaCloche (Relict) Lakes
Sudbury (Solus) Lakes
Figure 3.7. Principal component analysis of LaCloche and Sudbury lakes using local and regional environmental variables. Chapter 3 Environmental Differences
ii. STA TISTICAL SIGNlFICANCE OF ENVIRONMENTAL DIFFERENCES
The results of the discriminant analyses (Table 3.13), indicate that LaCloche (relict) and Sudbury (solus) lakes have significantly different environments in tens of the following sets of environmental variables examined: cornbined local and regional (P < 0.000001), local (P < 0.000001),
Q water chemistry (P < 0.000001 ), and regional (P < 0.000001). The lake rnorphology set is the only set of environmental variables for which LaCloche and Sudbury lakes are not significantly different (P c 0.1 3). This indicates that LaCloche and Sudbury lakes share a similar lake rnorphology. Group centroids for LaCloche and Sudbury lakes for lake scores of PCAs of each of these sets of environmental variables are represented in Figures 3.7 arid E9 to €12 in Appendix E. These results indicate that there is a significant difference in local and regional environmental variables between LaCloche and Sudbury lakes. Sudbury lakes are significantly larger, more basic and turbid and have a lower conductivity than LaCloche lakes. Sudbury lakes also have a lower surrounding lake forest cover and net primary productivity, and a higher surrounding lake soi1 drainage than LaCloche lakes. Chanter 3 Environmental Differences
Table 3.1 3. Summary of discriminant analyses of LaCloche (relict) and Sudbury (solus) lakes using the fint two principal components of principal component analyses of cornbined local and regional environmental variables, local environmental variables, regional environmental variables, lake morphology variables, and water chemistry variables.
c) BRUCE PENINSULA AND WELLINGTON LAKES i. ENVIRONMENTAL DIFFERENCES
The principal component analysis of cornbined local and regional environmental variables extracts three significant factors incorporating a total of 54% of the data variation. The first component (Table 3.14) accounts for 23% of the variance. The high correlations of the fint principal component with lake rnorphology suggest an overall size gradient. The second component explains 19% of the data variation. This component loads positively on surrounding lake net pnmary productivity and mean annual precipitation (Table 3.14). The third component explains 12% of the data variation. This Cha~ter3 Environmental Differences component loads positively on maximum depth, Secchi depth and contour complexity and negatively on surrounding lake net primary productivity.
Table 3.1 4. Correlations of local and regional variables with the first two principal components of a principal component analysis of Bruce Peninsula and Wellington lakes.
Environmental Principal Component Number Variable 1 7 2 3 Surface Area 0.5 1 -0.05 -0.1O Volume 0.45 0.02 0.1 1 Maximum Depth 0.1 8 0.13 0.55 Total Shoreline 0.48 -0.04 -0.08 Perimeter -- pH O .O7 0.16 0.03 Specific -0.14 0.18 0.20 Conductivity Secchi Depth 0.23 0.22 0.43 Annual Number -0.28 -0.O4 0.1 O of Deqree Days Mean Annual 0.01 0.56 -0.O5 Precipitation Net Primary -0.O 1 0.40 -0.40 Productivity Contour -0.18 -0.01 0.46 Complexity Surrounding -0.24 0.29 0.16 Forest Cover Parent Material 0.0 0.0 0.0 Surrounding Soil 0.16 0.02 O. 12 Drainage Percent of Total 0.23 0.1 9 0.12 Variation Cumulative 0.23 0.42 0.54 Percentaae
The separation of lakes by the PCA illustrate the distinct grouping of Bruce Peninsula (relict) and Wellington (solus) lakes (Figure 3.8). Bruce Peninsula lakes tend to be larger in size than Wellington lakes. 50th Bruce Peninsula and Wellington regions have a wide range of lakes in areas of high and low mean annual precipitation and surrounding lake net primary productivity. Chapter 3 Environmental Differences
A summaiy of the PCA results for local. regional, lake rnorphology and water chemistry variables are found in Appendix E. Tables El3 to El6 in Appendix E list those variables which load highly (>=/0.3/)on each of the significant eigenvalues for each PCA. Figures El3 to El6 in Appendix E summarize the Bruce Peninsula and Wellington lakes in relation to the first two principal components of each PCA.
Cha~ter3 Environmental Differences ii. STA TISTICAL SIGNIFEANCE OF ENVIRONMENTAL DlFFERENCES
The results of the discriminant analyses (Table 3.15), indicate that Bruce Peninsula (relict) and Wellington (solus) lakes have significantly different environments in terms of the following sets of environmenta1 variables examined: combined local and regional (P < 0.000001), local (P < 0.000001 ), lake morphology (P < 0.000001), and regional (P < 0.000001). Water chemistry is the only set of environmental variables for which Bruce Peninsula and Wellington lakes are not significantly different (P c 0.10). This indicates that Bruce Peninsula and Wellington regions are the only set of proxirnally paired relict and solus regions that share a similar lake water chemistry. Group centroids for Bruce Peninsula and Wellington regions for lake scores of PCAs of each of these sets of environmental variables are represented in Figures 3.8 and El3 to El6 in Appendix E. Overall. Wellington lakes are significantly smaller and have a higher mean annual precipitation and surrounding lake net primary productivity than Bruce Peninsula lakes. Cha~ter3 Environmental Differences
Table 3.1 5. Sumrnary of discriminant analyses of Bruce Peninsula (relict) and Wellington (solus) lakes using the first two principal components of principal component analyses of combined local and regional environmental variables, local environmental variables, regional environmental variables, lake morphology variables. and water chemistry variables.
Environmental Variables Eigenvalue 1.O75 0.54 0.03 O .42 1.58
rn I Canonical 1 0.72 1 0.59 1 0.18 1 0.54 1 O .78 correlation Wilks lambda O .48 0.65 0.97 0.7 1 0.39
Degrees of freedorn Significance level Relict 1 Solus Relict Solus Lakes Lakes Classification results: i- O/O Predicted 53.57 46.43 80.36 19.64 =F relict lakes III % Predicted solus lakes Cha~ter3 Environmental Differences
IV. DISCUSSION
A. ENVtRONMENfAL DIFFERENCES BEWEEN RELlCT AND SOLUS UKES
Proximal pair-wise comparisons were used to examine envimnmental differences between relict and solus lake regions (see Figure 3.2 in Materials and Methods section). Such comparisons are much more robust than an overall examination of relict and solus lakes because they accentuate the possibility that the closer the lakes are to one another, the more similar they should be in terms of their environmental characteristics. It was found that relict and solus lake regions have extremely different local and regional environments. The magnitude of these differences are surprising based on the close proximity of these lakes to one another.
The general physiography of the Great Lakes - St. Lawrence basin is found to dictate overall trends in lake environment. The basin is divided into two physiographic regions based on bedrock geology; the Canadian Shield and the Great Lakes - St. Lawrence Lowlands. The Canadian Shield is composed of Precambrian granites, gneisses and metavolcanic and metasedimentary rocks. Algoma, Wawa, LaCloche and Sudbury study regions are located on the Shield. The Great Lakes - St. Lawrence Lowlands are composed of primarily Paleozoic sedimentary rocks (Barrett 1992). Bruce Peninsula and Wellington study regions are located within these Lowlands. Based on these physiographic differences. local and regional environmental differences between relict and solus lakes will be discussed separately for study regions located on the Canadian Shield, and study regions located within the Great Lakes - St. Lawrence Lowlands.
1. REGIONAL ENVIRONMENTAL DIFFERENCES
Relict lakes and their surrounding watersheds are located on glaciolacustrine deposits. Glaciolacustrine deposits are sediments that have been carried by glacier meltwater and subsequently deposited in proglacial lakes. These proglacial lakes may have either been in direct contact with the glaciers (ice-contract lakes). or they may have been fed by glacier rneltwater streams (non-contact or distal glacier-fed lakes) (Smith and Ashley 1985). Both types of glacier-fed lakes were affected by the characteristics of glacier meltwater. including: strong seasonal and weather dependent discharge. and high Chapter 3 Environmental Differences sedirnent loads (Smith and Ashley 1985). The most common types of glaciolacustrine sediments deposited within glacier-fed basins are rhythmites. Each rhythrnite consists of a couplet composed of a sand-silt base overlain with a silt-clay layer. These deposits are cornposed of fine material which creates low soil drainage properties within the watersheds. These deposits are also extremely rich in nutrients and minerals. Most of the agriculture developed in Ontario occurs on glaciofluvial and glaciolacustnne deposits because of their rich nutrient content (Acton 1989). For these reasons, it is expected that relict lake regions be more productive than solus lake regions based on these differences in surficial geology.
The results of this study corroborate with the prediction that relict lakes are located within more productive regions than solus lakes. Relict lake regions are found to have a significantly higher surrounding lake forest cover and net primary productivity because of their fertile soi1 as well as low drainage properties associated with the presence of fine material in the soil. Solus lakes were never covered by proglacial water bodies and therefore lack any form of glaciolacustrine deposits. As a result, solus lakes are situated in nutrient poor, coarse soils which have high soi1 drainage properties. Their surrounding watersheds therefore have a significantly lower forest cover and net primary productivity than those of relict lake regions.
2. Local Environmental Differences
Local environments of relict and solus lakes on the Canadian Shield are found to be sig nificantly different in terms of lake water chernistry. Solus lakes, in this physiographic region, are found to have a higher pH, and lower specific conductivity than relict lakes. This suggests that these solus lakes may have a higher arnount of organic compounds such as humic and fulvic acids than relict lakes (Zimmerman et al. 1983). Bruce Peninsula and Wellington lakes on the Great Lakes - St. Lawrence Lowlands are chemically very similar. This suggests that physiographic properties such as underlying bedrock are driving processes determining water chemistry within these regions.
Solus and relict lakes on the Canadian Shield are found to share sirnilar lake morphology characteristics This similarity is probably related to the common geological conditions from which they were formed. Wawa, Algoma, LaCloche and Sudbury regions are al1 Chaoter 3 Environmental Differences
located on the Precambrian Shield. The majority of the lakes within these regions were formed from the excavation of existing fractures and shatter belts in the bedrock by glacial scour. Lakes within the Bruce Peninsula (relict) and Wellington (solus) regions are located on sedimentary rock in the Great Lakes - Si. Lawrence Lowlands. These regions are found to have significantly different lake morphologies. This is-notsurprising since most of the Bruce Peninsula lakes were foned by the solution of their underlying limestone bedrock. Wellington lakes on the other hand are predominately kettle lakes formed from the deposition of blocks of ice from the last glacial recession which melted to form isolated basins. Chapter 3 Environmental Differences
V. CONCLUSIONS
This study is unique in that it examined differences in the local and regional lake environment based on historical lake formation. The conclusions frorn this study are as follows:
A new method using the concept of an ecological boundary was derived to specifically define local and regional environmental variables with reference to a species or community under study. This methodology was helpful in detenining which environrnental variables were most relevant to the existence of the fish communities examined within this study,
Regional environmental variables summarize more local environmental variation than local environmental variables summarize regional environmental variation. This proposes that local environmental variables rnay be derived from regional environmental processes which supports the definition of local and regional environmental variables in relation to the ecological boundary of the species or community under study,
Relict and solus lakes have significantly different local and regional environments,
3 Relict lake regions have a significantly higher surrounding lake forest cover, surrounding lake net primary productivity, and lower soi1 drainage properties than solus lake regions,
= On the Shield, relict lakes have a significantly lower pH and a higher specific conductivity than solus lakes. Relict and solus lakes share a similar water chemistry on the Lowlands,
a On the Shield, relict and solus lakes share a similar lake morphology. On the Lowlands, relict and solus lakes have significantly different lake morphologies.
The environrnental characteristics of a lake are strongly related to its historical formation. Chapter 4 S~eciesComposition Differences
Relict and solus lakes 4 as landbridge and oceanic islands: An extension of the Theory of lsland Biogeography.
1. INTRODUCTION
The purpose of this chapter is to propose an expansion of the current Theory of lsland Biogeography (MacArthur and Wilson 1967) to include lakes. Two new lake classifications are described based on historical formation; relict and solus lakes. 1 will suggest that these lake types share similar characteristics with landbridge and oceanic islands respectively. Differences in species composition beniveen relict and solus lakes are examined and discussed within the scope of the Theory of lsland Biogeography.
A. THEORY OF ISLAND BIOGEOGRAPHY
The Theory of lsland Biogeography (MacArthur and Wilson 1967), is amenable to testing and as such is one of the most intensively researched theories in ecology of this century. MacArthur and Wilson proposed this theory from two key observations: 1) the farther an island is from the maintand the more depauperate its fauna, and 2) larger islands have a more diverse fauna than smaller islands. These observations imply that species composition depends on habitat size (heterogeneity). and the species' colonization ability and extinction potential.
7. COLONIZATIONAND EXTINCTION RATES
The Theory proposes that as a new island becomes inhabited over time, the number of species on an island increases asymptotically until it reaches some sort of species carrying capacity. Since a population colonizes an island by establishing individuals on an island. the colonization and extinction rates for species should detennine the island's carrying capacity. Once a species colonizes an island and becomes established, the Chapter 4 Species Composition Differences potential pool of species with high potential to colonize that island decreases by one. Therefore, the rate of colonization is expected to decrease with an increasing number of species in the community on an island over time. However, species cannot become extinct until they are established, so the number of species becoming extinct should increase with the number of species colonizing an island over time. When the number of species on an island becomes very high, cornpetition, cornpetitive displacement and predation may drive a species to extinction even though that species persisted on the island prior to the arrivai of its predator or competitor. The species carrying capacity of the island is the predicted point where colonization and extinction rates of an island are equal.
2. ISLAND SIZE AND DISTANCE FROM MAINLAND
The size of an island and its distance from mainland influence these rates of colonization and extinction. The Theory of Island Biogeography predicts that islands farther from mainland have a lower colonization rate than islands nearer to rnainland because their colonizen must travel farther to get there. The closer an island is to the mainland, the more likely it is to have access to al1 rnainland individuals. The farther an island is from mainland, the more likely it is to have only access to highly vagile, migratory species (Figure 4.1 ). Cha~ter4 Species Composition Differences
Colonization -close island Extinction -srnaIl island
Extinction -large island
K, Kt, Kc Kd
Number of Species
Figure 4.1. Hypothetical changes in colonization and extinction rates for close and distant istands from mainland and small and large islands indicating species carrying capacity "K" for each condition (Ka = distant and small islands, K, = close and srnall islands, K, = distant and large islands, and K, = close and large islands).
Island size also has an influence on the number of species present. Large islands generally have a larger fauna than do small islands, even if they are the same distance from mainland. Larger islands usually have a more diverse selection of habitats to be occupied. This habitat heterogeneity offers more opportunities for different species to coexist once they become established. This positive relationship of island size and species diversity is usually presented as a species-area curve, which illustrates that species richness increases with an increase in habitat area. Colonization rates are predicted not to differ with island size, whereas extinction rates are predicted to differ. A smaller island is expected to have a much higher extinction rate than a larger island, Chapter 4 Species Composition Differences because there are fewer available habitats to occupy. This indicates that a large island has a higher species carrying capacity than a smaller island (Figure 4.1).
3. SPECIES CARRYING CAPACITY
The final question posed by the Theory of Island Biogeography is whether the species carrying capacity on an island is stable. Species appear to colonize islands continually. causing other species to go extinct. These dynamic processes are predicted to cause a turnover in the species present on an island. However, over time, the carrying capacity of an island rnight actually increase. As more coionists appear on an island, specialist species rnay replace generalist species. Specialist species use a smaller niche breadth than generalist species and therefore do not cornpete with as many other species for resources as generalist species. Also, some species of specialists may not be able to colonize unless other species are first established on an island. Several specialist species rnay replace one generalist species, which would act to increase the carrying capacity of the island. Over evolutionary time, species on an island may also evolve to becorne specialists. A few species may adaptively radiate into many niches and evolve into a variety of different species. Therefore. evolution could also result in an increase in the carrying capacity of an island.
4. LANDBRIDGE A ND OCEANIC lSLANDS
The last Ice Age occurred approxirnately 15.000 yean ago during the Pleistocene era. Three thousand years later, as the Earth experienced a global warming, the glaciers began to recede. scarring the landscape and creating ouf present day geophysical features. These historical geologic and climatic processes of the last glacial recession created two distinct island formations as defined by MacArthur and Wilson (1967). Islands are classified as either "landbridge" or "oceanic" depending on how they were forrned. Landbridge islands are land masses which were once connected to species-rich areas such as rnainland. During the glacial episodes of the Pleistocene, much of the water presently in the oceans was bound up in glacial ice. Reduced sea levels and the exposure of land masses which are undemater today, led to a terrestrial wnnection between mainland and "landbridge" islands. This connection made migration possible and the landbridge islands shared a common species pool with the mainland. All Chapter 4 Species Composition Differences
mainland species had an equal opportunity of colonizing these landbridge islands. During the last glacial recession starting approximately 15,000 yean ago, as the sea level rose. these landbridge islands becarne disconnected frorn mainland areas (Figure 4.2). Once disconnected, landbridge istands are hypothesized to suffer a net loss of species due to local extinction and faunal relaxation (Patterson and Atrnar 1986; Patterson 1987; Patterson 1990; Wright and Reeves 1992). Therefore, species composition on landbridge islands is thought to be driven prirnarily by extinction. Although colonization rates may not balance rates of extinction on landbridge islands, they may be high enough, especially for highly mobile species to significantly influence species distribution.
LANDBRIDGE ISLANDS
C Time
OCEANIC ISLANDS
Figure 4.2. Comparison of IandbrÏdge and oceanic island formation. Cha~ter4 S~eciesCom~osition Differences
Oceanic islands according to the Theory of Island Biogeography (MacArthur and Wilson 1967), have never been connected to the mainland. They are most comrnonly formed from the upwelling of volcanoes from the ocean floor (Figure 4.2). Oceanic islands, because of their isolation from species source pools are often species-poor. Oceanic islands are not only more isolated than landbridge islands but they are also generally much older. Therefore higher rates of endemism rnay tend to exist within oceanic islands. Characteristically, oceanic islands support only highly vagile species and presumably never shared a common ancestral species pool with the mainland. Therefore, species composition within oceanic islands have developed primarily through colonization and subsequent speciation (Patterson and Atmar 1986; Patterson 1987; Pattenon 1990; Wright and Reeves 1992). Extinction rates generally do not exceed rates of colonization except where human activity and catastrophic events have had a strong impact (e.g., Harris et al. 1987; Olson and James 1982).
B. LAKESASISLANDS
Several researchen have investigated the notion of lakes as aquatic islands within a terrestrial sea (e.g., Barbour and Brown 1974; Browne 1981; Magnuson 1988 ). Their research has concluded that lakes are small, relatively isolated environments in which species richness should be determined by extinction and colonization events in a manner analogous to terrestrial islands. The purpose of this study is to take this analogy of "lakes and islands" one step further and separate inland lakes within the Great Lakes - St. Lawrence basin into two categories based on their formation which are similar to landbridge and oceanic islands. These ON0 new categories of lakes are named here "relict" and "solusn lakes.
7. RELICT LAKES
"Relictn lakes are defined as lakes that were once a part of a large proglacial waterbody during the last glacial recession which has since receded to form smaller independent lakes. These lakes are analogous to landbridge islands (MacArthur and Wilson 1967). Relict lakes. derived from a common ancestral proglacial waterbody. are expected to have similar species compositions, since these relict lakes share a cornmon ancestral Chapter 4 Species Composition Differences
species pool. The species pool of the ancestral proglacial waterbody was in tum derived from the dispersa1 of fish species fom their glacial refugia into these lakes during the last glacial recession.
2. SOLUS LAKES
"Solus" lakes are defined as lakes which were formed within areas of land never inundated by a larger body of water. Without a navigable connection to a larger body of water, solus lakes are essentially aquatic islands in isolation. For this reason, solus lakes are expected to contain a unique species structure, since they have never shared a common species pool with other bodies of water. These lakes are expected to be species-poor in cornparison to lakes that were once part of large proglacial waterbodies, and to show greater variation in fish comrnunity structure.
3. HISTORICAL FORMA TION OF LAKES WITHIN THE GREAT LAKES - ST. LAWRENCE BASIN
The historical formation of lakes within the Great Lakes - St. Lawrence basin has been reconstructed by many researchers using both geologic and climatic evidence (see Barrett 1992; Fulton 1989). Appendix G is a summary of the formation of the Great Lakes - St. Lawrence basin during the last glacial recession based on numerous resources: Radforth 1944; Hough 1958; MacKay 1963; Hubbs and Lagler 1964; Prest 1970; Flint 1971 ; Pfiieger 1971; Hocutt et ai. 1978; Bailey and Smith 1981; Teller et al. 1983; Eschmann and Karrow 1985; Farrand and Drexler 1985; Karrow and Calkin 1985; Kaszycki 1985; Underhill 1986; Dyke and Prest 1987a; Dredge and Cowan 1989; Fulton 1989; Karrow and Occhietti 1989; Mandrak 1994. Appendix G is the most complete summary of its kind to date. Table G1 in Appendix G is a detailed summary of the different stages invoived in the formation of each of the major glacial lakes contributing to the formation of the Great Lakes - St. Lawrence basin: Lake Agassiz, Lake Superior. Lake Michigan. Lake Huron, Lake Erie. Lake Ontario, Lake Barlow-Ojibway, and the Champlain Sea. Tables G2 to G9 in Appendix G sumrnarize the inflows and oufflows for each of these glacial lakes throughout their development and illustrate the dispersal corridors for fishes from within the Atiantic. Mississippi and Missouri refugia into the Great Lakes - St. Lawrence basin. The implications of these corridors in establishing Cha~ter4 S~eciesComoosition Differences
species composition patterns within inland lakes in the Great Lakes - St. Lawrence will be examined further in the discussion section.
4. ORIGIN OF F/SH SPECIES IN THE GREAT LAKES - ST. LAWRENCE BASIN
The Laurentide Ice Sheet covered ail of Ontario at the last Wisconsinan glacial maximum approximately 18,000 years ago. Ontario was devoid of life at this time. Much of the flora and fauna present in Ontario today descended from pioneer species that colonized the area after the last glacial recesslon starting 15,000 years ago. It has been hypothesized that the native fish species currently present in the Great Lakes - St. Lawrence basin have corne from the descendants of four major Wisconsinan refugia: the Atlantic Coastal refugium, the Mississippi refugium, the Missouri refugium, and the Beringian refugium (Bailey and Smith 1981; Crossman and McAllister 1986). The Atlantic Coastal refugium existed along the coastal plain east of the Appalachians. The Mississippi refugium, located south of the Laurentide Ice sheet, was the largest Wisconsinan refugium. It was also the most significant refugium with respect to the number of species it contained and the geographic area it recolonized (Lindsey and McPhail 1986; Crossman and McAllister 1986). The Mississippi refugium was separated from the Missouri refugium by the Des Moines and James lobes of the Laurentide ice sheet (Dyke and Prest 1987a). The Beringian refugium was located within Alaska, Yukon, and the Northwest Territories as part of the Bering Strait. Mandrak and Crossman (1992b) summarized the refugial origins and dispersal routes of Ontario freshwater fishes within the Atlantic, Mississippi and Missouri refugia.
5. DISPERSAL ABILITY
A fish's ability to colonize the Great Lakes - St. Lawrence basin from corridors connecting its glacial refugium during the last glacial recession and its subsequent colonization into eitherlor relict or solus lakes is dependent upon nurnerous life history characteristics of the fish species such as temperature preference, swimming ability, and trophic level. These characteristics play a crucial role in determining the timing of migration of a species into the pristine waters of rivers and lakes in newly deglaciated areas in cornparison to other species. Historical factors such as invasion order (priority effects) and invasion rate (e.g., Robinson and Dickerson 1987; Robinson and Edgemon Chanter 4 Species Composition Differences
1988) may also influence a species' dispersal ability and therefore the resultant species composition of a lake. For example, if early colonists are able to pre-empt the lake habitat and prevent later invasion by other species, then the order of arriva1 of species will be important in determining the species composition of the lake. Good dispersers may have a greater ability to create regular patterns in species distribution by re- colonizing and revening any local extinctions. However, poorer dispeners may be present in only the largest and richest lakes where extinction rates are lower than in smaller lakes.
a) PREFERRED TEMPERATURE
Most fishes are both ectotherms and poikilotherms. The term ectothermy indicates that a fish's body temperature is controlled by its external water temperature. Poikilothermy refers to the inability of a fish to intemally regulate its metabolism. Therefore, at any given temperature, a fish's body temperature will be close to the temperature of its surrounding water medium. A fish's metabolic rate and other related physical and chernical processes such as rate of enzyme activity, mobility of gases, diffusion and osmosis, are therefore dependent upon its surrounding water temperature (e.g., Fry 1971; Hokanson 1977; Hochachka and Somero 1984; Cossins and Bowler 1987). Within the temperate zone, three thermal guilds of fishes have been defined based on a fish's metabolic rate and temperature tolerance; temperate eurytherms (warmwater fishes 25-32 OC), mesotherms (coolwater fishes, 10-25 OC), and stenotherms (coldwater fishes, 5-10 OC) (Magnuson et al. 1977).
Temperate fishes need to be able to persist under cold winter conditions. Even though temperate warmwater fishes appear to have adapted to warrn water, they in fact endure the largest temperature range of aIl the thermal guilds. Temperate coolwater fishes may have the best ability to deal witfi cold to moderately wanwater, but they have a much narrower temperature range. Temperate coldwater fishes are best adapted to cold temperatures such as those found in the hypolimnion of a large, deep lake. A fish species*ability to tolerate fluctuations in its environment especially temperature is a key factor in a species' ability to colonize an area after glaciation. Fish species with coldwater preferences are expected to have recolonized Ontario inland lakes and rivers long before species with wamwater preferences because proglacial waters especially Chapter 4 Species Composition Differences
near the glacier were exceptionally cold. A warrnwater fish's ability to successfully recolonize Ontario's inland lakes was probably further impeded by isostatic rebound. lsostatic rebound in many areas of Ontario eliminated immigration routes from lowland into many highland areas, such as the Haliburton Highlands (Kaszycki 1985). Some late arriving warmwater species such as centrarchids, were unable to colonize highland areas due to this steep increase in elevation.
The swimming ability of a fish is usually defined as two modes: sustained swimming and burst swimming. Sustained swimming involves a wide range of swimming activities and speeds that can be maintained for an indefinite period of time (in operational terms for longer than 200 minutes and does not involve fatigue). Metabolism is aerobic and the activities done using this type of swimming include foraging. station holding. schooling, cruising at preferred speeds in negatively buoyant fish, and steady swimming at low speeds including migration (Hoar and Randal 1978). Burst swimming involves rapid movements of short duration and high speed, maintained for less than 15 seconds. Energy is made available largely through anaerobic processes. Burst activity can be subdivided into an acceleration period and a sprint when swimming speed is high but steady (Hoar and Randal 1978).
A great deal of work has been done on the swimming speeds of fish in relation to body length. Two general relationships have been found. The first is that the bunt speed that a fish can reach is approximately 10 times its own length per second (Blaxter 1969; Beamish 1978). The second is that the sustained speed is approximately 3 times a fish's own length per second (Blaxter 1969; Beamish 1978). These relationships indicate that large fish in general are capable of faster and longer migrations than srnaller fish. Based on this relationship, large fish species are expected to have been the first to colonize the Great Lakes - St. Lawrence basin during the last glacial recession.
C) TROPHIC LEVEL
Fish species can be classified into trophic groups based on feeding habits (Karr et al. 1986; Berkman and Rabeni 1987). Omnivores are those species with a broad spectrum Chapter 4 Species Composition Differences
diet but feeding mostly on detritus. Omnivores are near the base of the trophic structure and are often the most tolerant of habitat degradation and ecosystern dysfunction. Other trophic levels, in order of sensitivity to degradation, beginning with the least sensitive include: planktivores, insectivores, benthic insectivores (e.g., benthic feeders), and insectivores/piscivores at the top of the trophic structure (Karr and Dudley 1981). It can be expected that in the least disturbed systems a higher proportion of species present would be in benthic insectivore and piscivore groups than in heavily degraded sites. As degradation intensifies, those species at the top of the trophic structure, Le., the insectivorelpiscivores, would disappear fint, followed in sequence by benthic insectivores, general insectivores, planktivores and omnivores. In the case of dispersal from refugia it may be advantageous to be an omnivore from the standpoint of migrating through a highly disturbed system.
C. OBJECTIVES OF THIS CHAPTER
Based on the historical formation of relict and solus lakes within the Great Lakes - St. Lawrence basin, it is expected that the fish species composition would be very different in these two types of lakes. The purpose of this chapter is to determine if such differences exist, and to develop possible explanations for the observed differences based on lake derivation and species dispersa1 ability. Cha~ter4 Soecies Comoosition Differences
II. MATERIALS AND METHODS
A. STUDYLAKESAND DATABASES
A total of 550 lakes divided amongst six regions within the Great Lakes - St. Lawrence basin of Ontario were examined in this study. Each region is classified as containing either relict or solus lakes based on historical lake formation. These regions are paired such that regions containing relict and solus lakes that are in close proximity to one another are matched as a pair. Therefore, Wawa and Algoma regions are matched as a pair, as are LaCloche and Sudbury regions, and Bruce Peninsula and Wellington regions. Please refer to chapter 3 pages 3-10 and 3-1 1 for a complete summary of the lakes and the databases used within this study. Figure 3.2 found on page 3-12 in chapter 3 illustrates the location of the study regions.
B. F/SH SAMPLING PROCEDURE
A standard protocol described by Dodge et al. (1978) in the Ontario Ministry of Natural Resources Lake Survey was used for sarnpling fish in each of the study lakes. All survey data used in this study were obtained using multiple sampling gear including gillnets, coarse and fine mesh trapnets, baited traps, and seine nets. Sampling gear was placed in a broad range of habitats to rnaximize the number of fish species captured from the littoral, profundal and pelagic zones. lncreased effort was used in littoral habitats since these areas are used by numerous species of smaller fish. Species not captured after extensive sarnpling are assumed to be absent or extrernely rare and therefore of little ecological signifimnce to the system. Lakes with no fish are excluded from the study. lntroduced species such as goldfish, carp, splake. alewife. Arctic grayling. rainbow trout. brown trout and rainbow smelt are also excluded from the study. Overall. sixty-one fish species were examined in this study (Table 4.1 ). Cha~ter4 S~eciesCom~osition Differences
Table 4.1. Fish species examined in this study.
Amiidae bowfin Amia calva Salmonidae: brook trout Salvelinus fontinalis Salmoninae lake trout Salvelinus namaycush lake whitefish Coregonus clupeafotmis
cisco Coregonus artedi round whitefish Prosopium cylindraceum Esocidae northern pike Esox lucius muskellunge Esox masquinongy Umbridae central mudminnow Urnbra limi Catostomidae longnose sucker Catostomus catostomus white sucker Catostomus commersoni shorthead redhorse Moxostoma rnacrolepidotum Cyprinidae northern redbelly dace Phoxinus eos finescale dace Phoxinus neogaeus lake chub Couesius plumbeus brassy minnow Hybognathus hankinsoni hornyhead chub Nocomis biguttatus river chub Nocomis micropogon qolden shiner Notemigonus crysoleucas emerald shiner Notropis atherinoides cornmon shiner Luxilus cornutus blackchin shiner Notropis heterodon blacknose shiner Notropis heterolepis spottail shiner Notropis hudsonius rosyface shiner Notropis rubellus mimic shiner Notropis volucellus bluntnose minnow Pimephales notafus fathead minnow Pimephales promelas l blacknose dace 1 ~hinichthvs,-atratulus
II llonanose- dace 1~hinichthvs a cataractae 11 lcreek chub 1 Semotilus atromaculatus
pearl dace Margariscus margarita lctaluridae yellow bullhead A meiurus na talis brown bullhead A meiurus nebulosus channel catfish lctalurus puncta tus tadpole madtorn Noturus gyrinus Fun ulidae banded killifish Fundulus diaphanus Ilburbot Lota Iota brook stickleback Culaea inconstans Chapter 4 Species Composition Differences
threespine stickleback Gasterosteus aculeatus ninespine stickleback Pungitius pungitius Percopsidae trout-perch Percopsis orniscomaycus Centrarchidae rock bass Ambloplites mpestris - green sunfish Lepomis cyanellus purnpkinseed Lepomis gibbosus blue~ill Lenomis macrochirus longear sunfish Lepomis megalotis smallmouth bass Microp terus dolotnieu 1 1 Ilargemouth bass 1~icropterus salmoides 11
Fish species incidence data are used instead of abundance data because most fish are very difficult to sample in such a way that the relative frequencies of species in a sarnple are representative of their true numbers within the community (e.g., Shapiro 1975; Verner 1983). Each species' probability of capture differs arnong sarnpling gear. lake habitat. and.time of year and day. This sampling problem makes an accurate estimation of equitability difficult (He and Lodge 1990). These sampling problems result when fish species cover many size classes and are located in very different habitats.
C. STA TlST/CAL METHODS
1. MANTEL TEST AND THE PHI COEFFICIENT OF SIMILARITY
Two fish species data sets are used in this study; Harvey (1997) dataset and Ontario Ministry of Natural Resources (1997) dataset. It is necessary to test for differences between the two datasets before questions relating to species diversity across al1 of the Cha~ter4 Soecies Composition Differences
regions and between regions can be examined. A Mantel test (Mantel 1967). is performed on one hundred and ninetysight lakes found to be present in both the Ontario Ministry of Natural Reso~rces(1 997) and Harvey (1997) data sets. The Phi coefficient of similarity (Legendre and Legendre 1983). is used in the Mantel test to test for significant differences in species richness between the hnro datasets. The Harvey (1997) dataset is then randomly rearranged and the Phi coefficient of sirnilarity recalculated between the two datasets. The randomization procedure is performed 10,000 times to generate a nuIl distribution for the Phi coefficient of similarity given a random arrangement of the Harvey (1997) species matrix. This distribution is similar to other statistical distributions. but does not require assurnpüons about the properties of the data. The nul1 hypothesis assumes that the Harvey (1997) and the OMNR (1997) data sets are not more closely associated than expected by chance alone.
The Phi coefficient of similarity is also used to test for differences in species richness for lakes sampled in both the Harvey (1997) and OMNR (1997) datasets. Phi similarity coefficient values comparing species incidence data between datasets for each of the 198 lakes found within both datasets are plotted as a frequency distribution with values ranging from -1 to 1. A mean Phi value of O indicates that the Harvey (1997) and OMNR (1997) species datasets are identical. A Phi value less than two standard deviations from O indicates that there is no significant difference between the two datasets at the 5% level.
2. CHI-SQUARE STA TISTICS
A Chi-Square test is a goodness-of-fit statistic used to determine whether observed frequencies are significantly different from expected frequencies. A Chi-Square test is performed to examine differences in sampling effort between the Harvey (7 997) and OMNR (1997) datasets for each species using species incidence data for each of the 198 lakes found within both datasets. Chi-Square analyses are also performed for each species to determine if there is a significant difference in the frequency of occurrence of each species within relict and solus lakes. The analysis is repeated to examine painvise comparisons for the following pain of proximal relict and solus lake regions: Wawa and Algoma. LaCloche and Sudbury. and Bruce Peninsula and Wellington. Cha~ter4 S~eciesCom~osition Differences
Species richness across each of the six regions is examined at two spatial scales; a) the number of species per region and b) the average number of species per Iake within each region. The number of species per region is tabulated using Mandrak and Crossman's (1992a) distribution range maps of freshwater fish species within Ontario. The distribution range of each species found in Ontario is plotted based on various sampling expeditions from the 1950s until the early 1990s. Mandrak and Crossman (1992a) is the rnost complete summary to date of fish species distributions within Ontario.
It has been established that fish species richness is strongly correlated with lake area (e.g., Barbour and Brown 1974; Eadie and Keast 1984; Harvey 1978,1981: Minns 1989). In order to examine if differences exist in the number of fish species per lake between relict and solus lakes, it is necessary to control for this species-area relationship. Species-area curves are calculated for each of the six study regions. A modified t-test (Zar 1984), is used to test for significant differences in species-aiea regression lines between pair-wise proximal relict and solus lake regions.
4. CORRESPONDENCE ANAL YSIS
Correspondence analysis (CA) (Hirchfeld 1935), is a multivariate technique that is an extension of weighted averaging used in Whittaker's (1967) direct gradient analysis. CA more accurately represents the spatial arrangement of sites and species than does principal CO-ordinatesanalysis. However, the relative advantage of this method is influenced by the length of the gradient under examination. CA maintains the relative distances between samples and is not affected greatly by numerous zero values. However, CA is influenced by rare species in species-poor sites (Gauch 1982). In this study, CA is used to convert fish species incidence data of a combined relict and solus lake data set into continuous variables to measure the relationship between lakes based on their species composition.
This analysis is repeated to examine pairwise cornparisons for the following pairs of proximal relict and solus lake regions: Wawa and Algoma, LaCloche and Sudbury, and Bruce Peninsuia and Wellington. Chaoter 4 Soecies Comoosition Differences
5. DISCRlMlNANT ANAL YSIS
To test for significant differences in fish species composition between relict and solus lakes, a discriminant analysis (Legendre and Legendre 1983), is perfonned on lake scores from each of the first two axes of the correspondence analyses. Discriminant analysis, also termed discriminant function analysis, canonical variate analysis and canonical discriminant analysis, is a rnultivariate statistic which is used to rnaximally contrast two groups of variables. The resultant discriminant function, also temed the canonical variate or canonical axis. is the maximum difference between the two groups. Discriminant analyses are perfomed to test for significant differences in species composition between relict and solus lakes, and each of the paired proximal regions: Wawa and Algoma, LaCloche and Sudbury, and Bruce Peninsula and Wellington.
6. DISPERSAL ABILITY INDU(
An index of dispersa1 ability is created to predict the order of fish species re-colonizing the Great Lakes - St. Lawrence basin. The index is based on the following categories: temperature preference. swimming ability and trophic level. Al1 three categories are given equal weight. Each category is split into three levels (Table 4.2). The level contributing the most to dispersal ability is given a rank of 1. Sirnilarly, the tevel contributing the least to dispersal ability is given a rank of 3. Each species within this study is placed at a level within each of the categories and given the appropriate rank. The ranks over al1 three categories are totaled for each species providing an indication of colonization ability for that species during the last glacial recession. A species with an overall rank of 3 or 4 indicates that it was probably one of the fint species able to successfully recolonize the Great Lakes - St. Lawrence basin. A species with an overall rank from 5 to 7 indicates an average colonizaüon ability into the area. Finally a species with an overall rank of 8 or 9 indicates that it was most probably one of the last species to successfully colonize the area. Cha~ter4 S~eciesCom~osition Differences
Table 4.2. Surnrnary of indices used in the dispersal ability index.
11 Rank Temperature 1 Swimming Ability Preference 1 Coldwater Fast Omnivore I Coolwater Average Insectivore1 Piscivore
3 Warmwater Slow Insectivo rel Piscivore Cha~ter4 S~eciesCom~osition Differences
III. RESULTS
A Mantel test using the Phi coefficient of similarity is used to test for significant differences in species richness between one hundred and ninety eight takes present in both the Harvey (1997) and OMNR (1997) datasets. The original Phi similarity coefficient calculated for the Harvey (1997) and OMNR (1997) data sets is more extreme than that found in less than 5% of the randomized matrices (P=0.0001). Therefore, the nuIl hypothesis is rejected at the 5% level indicating that both datasets are sirnilar (Table 4.3). Therefore, the two species datasets are considered to be equivalent and are merged for statistical analyses.
Table 4.3. Summary of Mantel test between 198 lakes present within both Harvey (1997) and OM NR (1997) species datasets.
Tests for association:
A frequency distribution is also calculated using Phi similarity coefficient values comparing species incidence data between each of the 198 lakes found within both datasets. Phi similarity coeficient values range from -1 to 1. A mean Phi value of O indicates that the Harvey (1997) and OMNR (1997) species datasets are identical. The results indicate that the mean of the Phi similarity coefficients is less than two standard deviations from O. Therefore the results agree with the Mantel test that there is no significant difference between the two datasets at the 5% level.
A Chi-Square analysis is performed to test for differences in sampling effort between the Harvey (1997) and OMNR (1997) datasets for each species using species incidence data for each of the 198 lakes found within both datasets. Fourteen of the fifty-three Chabter 4 S~eciesCom~osition Differences
species examined are found to be significantly different in their frequency of occurrence between datasets (Table 4.4). Each of these species has a higher frequency of occurrence in the Harvey (1997) dataset. The majority of these fourteen species are small, non-game, littoral zone fish. The results indicate there is a greater sampling effort in the Harvey (1997) dataset for small non-game fishes.
Table 4.4. Summary of frequency of occurrence of species in the Harvey (1997) and OMNR (1997) datasets. Bold X2 values indicate a significant difference in the species frequency of occurrence between the two datasets.
- - w - Species Richness
L. Famiiy Species Nams Harvey (1997) OMNR (1997) X2 Value Dataset Dataset Critical Value = 3.84 Amiidae Bowfin 5 4 0.1 1 Salmonidae 8rook trout 40 36 0 .26 Lake trout 23 27 0.37 Lake whitefish 13 12 0.04 Cisco 25 30 0.53 Esocidae Northern pike 79 47 1 1.92 Muskellunge 3 2 O .20 Umbridae Central mudminnow 66 34 13.70 Catostornidae Longnosesucker 8 4 1.38 white sucker 147 107 17.57 11 [Shorthead redhorse 1 O 1 1 1 1.O0 11 Cyprinidae Northern redbelly dace 75 40 15.01 Finescale dace 55 15 27.77 Lake chub 35 14 10.27 Brassy minnow 2 4 0.68 River chub 1 1 0.00 Golden shiner 79 44 14.45 Emerald shiner 1 1 0.00 II ICommon shiner 1 59 1 43 1 3.38 11 Blackchin shiner 25 16 2.20 Blacknose shiner 64 31 15.08 Spottail shiner 8 2 3.69 Mimic shiner 15 12 0.36 Bluntnose minnow 87 50 15.28 Fathead minnow 1 53 25 12.52 Blacknose dace 5 1 Longnosedace 11 4 3.40 Chanter 4 S~eciesComnosition Differences
Family Species Name Hanrey (t997) OMNR (1997) Xi Value Dataset Dataset Critical Value = 3.84 Creek chub 48 33 3.49 1 Fallfish 2 O 2.01 Pearl dace 37 24 3.27 lctaluridae Yellow bullhead 5 5 0.00 Brown bulltiead 81 63 3.54 II l~adpolemadtom 1 14 1 11 1 0.38 11 Funguiidae Banded killifish 1 14 14 0.00 Gadidae Burbot 22 14 1.96 Gasterosteidae Brook stickleback 71 28 24.90 Ninespine stickleback 6 5 0.09 Percopsidae Trout perch 7 4 0.84 I lt~entrkhidae l~ockbass 1 96 1 77 1 3.70 11
Bluegill 12 10 0.1 9 SrnaIlmouth bass 83 72 1.28 Largemouth bass 40 27 3 ,O4 Black crappie 1 1 0.00 Percidae Yellow perch 187 157 19.92 Walleye 23 19 0.43 Rainbow darter 5 1 2.71 Iowa darter t27 61 44.1 1 Least darter 1 6 5 0.09 Johnny darter 37 24 3.27 Logperch 15 7 3 .O8 Cottidae Mottted sculpin 13 5 3.72 Slimy sculpin 11 5 2.34
B. SPECIES FREQUENCY OF OCCURRENCE
7. ALL RELICT AND SOLUS LAKES COMBINED
A Chi-Square statistic is calculated for each species to test for significstnt differences in the frequency of occurrence between relict and solus lakes. Forty-five of the sixty-one species examined are found to be significantly different in their frequency of occurrence between relict and solus lakes (Table 4.5); the remaining nine species are found to have a similar frequency of occurrence. White sucker (Catostomus commersonfl is ubiquitous throughout both relict and solus lakes. It occurs in approximately 67% of al1 lakes within this study . Brook trout (Salvelinus fontinalis), finescale dace (Phoxinus neogaeus). lake Chapter 4 Species Composition Differences
chub (Couesius piumbeus), and blacknose shiner (Notropis hetemlepis) occur in approximately 22% of al1 relict and solus lakes in this study. Rare species in both relict and solus lakes include round whitefish (Prosopium cyiindraceum), brassy minnow (Hybognathus hankinsonr'),hornyhead chu6 (Nocomis biguttatus), river chub (Nocomis micropogon), ninespine stickieback (Pungitius pungitius), bluegill (Lepomis macrochirus), mottled sculpin (Cottus bairdi) and slimy sculpin (Cottus cognatus). The number of species which occur with a greater frequency in relict lakes is equal to the number of species which occur with a greater frequency in solus lakes; 23 and 24 species res pectively . The s horthead redhorse (Moxostoma macrolepidotum),th reespine stickleback ( Gasterosteus acuieatus) and sauger (Stizostedion canadense) are al1 cornmon species in solus lakes but are not found in a single relict lake (Table 4.5).
Table 4.5. Summary of frequency of occurrence of species in relict and solus lakes. Bold X2 values indicate a signifiant difference in a species frequency of occurrence behveen relict and solus lakes.
Species Richness ccurrence
Species Total Relict Solus Relict Solus X2 Vat ue lFami'y INarne Lakes Lakes Lakes Lakes Critical Value =
Salmoninae brook trou? 128 45 83 22.28 21 .If 0.10
lake trout 145 27 . 118 'l3.37 30.10 20.23 Coregoninae lake whitefish 147 12 135 5.94 34.44 58.1 3 cisco 173 31 142 15.35 36.22 28.1 5 round 9 1 8 0.50 2.04 2.1 3 Chapter 4 Species Composition Differences Chapter 4 Species Composition Differences
Species Species Richness Frequency of Occurrence
Family Species Total Relict Solus Relict Solus X2 Value Name Lakes Lakes Lakes Lakes Critical Value = .3.84 threespine 43 O 43 0.00 10.97 23.89 stickleback ninespine 24 7 17 3.47 4.34 0.26 stickleback Percopsidae trout perch 39 5 34 2.48 8.67 8.35 Centrarchidae rock bass 96 72 24 35.64 6.12 85.74 qreen sunfish 24 O 24 0.00 6.12 12.89 pumpkinseed 149 124 25 61.39 6.38 214.65 bluegill 41 13 28 6.44 7.14 0.10 longear 9 O 9 0.00 2.30 4.71 sunfish smallmouth 96 67 29 33.17 7.40 65.34 bass largemouth 85 45 40 22.28 10.20 15.85 bass black crappie 23 2 21 0.99 5.36 6.83 Percidae yellow perch 350 150 200 74.26 51 -02 29.74 sauger 197 O 197 0.00 50.26 151.89 walleye 121 18 103 8.91 26.28 24.78
rainbow darter 107 4 103 . 1.98 26.28 53.28 Iowa darter 179 91 88 45.05 22.45 32.34 least darter 93 6 87 2.97 22.1 9 37.31 Johnny darter 35 22 13 10.89 3.32 13.79 logperch 38 11 27 5.45 6.89 0.46 Cottidae rnottled 16 2 14 0.99 3.57 3.39 sculpin slimv sculoin 26 10 16 4.95 4.08 0.24
2. COMPARISONS OF PROXIMALLY PAIRED RELICTAND SOLUS LAKE REGIONS
Chi-square statistics are calculated for each species to examine pair-wise cornparisons between the following proximal regions: Wawa and Algoma, LaCloche and Sudbury, and Bruce Peninsula and Wellington. Cha~ter4 S~eciesComposition Differences a) WAWAANDALGOMA LAKES
A Chi-Square statistic is calculated for each species to test for significant differences in its frequency of occurrence between Wawa (relict) and Algoma (solus) lakes. Wawa and Algoma are the rnost northem regions in this study. Nineteen species of the collective sixty-one species examined in this study are not found in either of these regions: bowfitn (Amia calva), round whitefish (Prosopium cylindraceum), central mudminnow ( Umbra limi), brassy minnow (Hybognathus hankinsont] , hornyhead chub (Nocomis biguttatus), river chub (Nocomis rnicropogon), bluntnose minnow (Pimephales notatus), al1 ictalurid species, and ail centrarchid species except for one rock bass (Ambloplites rupestns) found in Roller lake in the Wawa region (most likely introduced). Twenty-three of the forty-two species examined are significantly different in their frequency of occurrence between Wawa and Algoma lakes (Table 4.6). The number of species which occur with a greater frequency in Wawa lakes was less than the number of species which occur with a greater frequency in Algoma lakes; 7 and 16 species respectively (Table 4.6). Muskellunge (Esox masquinongy), shorthead redhorse (Moxostoma macrolepidotum), rosyface shiner (Notropis rubellus), threespine stickleback (Gasterosteus aculeatus), sauger (Stizostedion canadense), rainbow darter (Etheostoma caeruleum), least darter (Etheostoma microperca). and mottled sculpin (Cottus baird11are al1 common species in Algoma lakes but are not found in any Wawa lakes.
Table 4.6. Summary of frequency of occurrence of species in Wawa (relict) and Algoma (solus) lakes. Bold XZ values indicate a significant difference in a species frequency of occurrence between relict and solus lakes.
/ Spesies Rishness / Frequencyspecies of 1 Occurrence Total 1 Relict 1 Solus Relict 1 Solus X2 Value Chapter 4 Species Composition Differences
Species Species Richness Frequency of Occurrence Family Species Total Relict Solus Relict Solus X2 Value Name Lakes Lakes Lakes takes Critical Value = 3.84 cisco 57 3 54 6 59.34 .38.12 round O whitefish Esocidae northern pike 78 8 70 16 76.92 48.46 muskellunge 70 O 70 O 76.92 76.38 Urnbridae central 0. 1 rnudrninnow Catostomidae longnose 13 7 6 14 6.59 2.12 sucker white sucker 114 36 78 72 85.71 3.92 shorthead 76 O 76 O 83.52 90.58 redhorse Cyprinidae northern 36 21 15 42 16.48 11.05 redbelly dace finescale dace 43 20 23 40 25.27 3.30 lake chub 51 31 20 62 21.98 22.39 brassy O minnow hornyhead O chub ~iverchub O I golden shiner 2 2 O 4 O 3.69 eme rald 1 O 1 O 1.10 0.55 shiner cornmon 1O 8 2 16 2.20 9.33 shiner blackchin 1 O 1 O 1.10 0.55 Chaater 4 Saecies Corn~ositionDifferences Chapter 4 Species Composition Differences
b) LaCLOCHE AND SUDBURY LAKES
A Chi-Square statistic is calculated for each species to test for significant differences in its frequency of occurrence between LaCloche (relict) and Sudbury (solus) lakes. Seven species of the collective sixty-one species examined in this study are not found in either of these regions: bowfin (Amia calva), brassy minnow (Hybognathus hankinsoni), yellow bullhead (Ameiurus natalis), channel catfish (Ictalurus punctatus), tadpole madtom (Noturus gyrinus), longear sunfish (Lepomis megalotis), and black crappie (Pomoxis nigromaculatus). Thirty-six of the fifty-four species examined are significantly different in their frequency of occurrence between LaCloche and Sudbury lakes (Table 4.7). The number of species which occur with a greater frequency in LaCloche lakes was half the number of species which occur with a greater frequency in Sudbury lakes; 12 and 24 species respectively. It is interesting to note that shorthead redhorse (Moxostoma macrolepidotum), finescale dace (Phoxinus neogaeus), blackchin shiner (Notropis heterodon), spottail shiner (Notropis hudsonius), blacknose dace (Rhinichthys atratulus), fallfis h (Semotilus corporalis), threespine stickleback ( Gasterosteus aculeatus), sauger (Stizostedion canadense), and least darter (Etheostoma microperca) are al1 common in Sudbury lakes but are not found in a single LaCloche lake. Conversely, brown bullhead (Ameiurus nebulosus), pumpkinseed (Lepomis gibbosus) and bluegill (Lepomis macrochirus) are common species in LaCloche lakes but are not found in any Sudbury lakes (Table 4.7).
Table 4.7. Surnrnary of frequency of occurrence of species in LaCloche (relict) and Sudbury (solus) lakes. Bold X2 values indicate a significant difference in a species frequency of occurrence between relict and solus lakes.
S pecies Species Richness Fraquency of Occurrence Family Species Total Relict Solus Relict Solus X2 Value Name Lakes Lakes Cakes Lakes Critical Value =
bowfin . Salmonidae: brook trout Salmoninae Cha~ter4 S~eciesCorn~osition Differences
Species Richness FrequencySpecies of 1 occurrence 'amily Species Total Relict Solus Relict Solus X2 Value Nam /I)Lakes Lakes Lakes Lakes Critical Value = 3.84 cisco 86 22 64 50.00 37.65 - . 2.22 round 9 1 8 2.27 4.71 0.51 whitefish Esocidae northern pike 98 19 79 43.18 46.47 0.15 muskellunge 76 1 75 2.27 44.12 26.72 Urnbridae central 3 3 O 6.82 0.00 11.76 mudrninnow Catostomidae longnose 29 O 29 0.00 17.06 8.68 sucker white sucker 153 24 129 54.55 75.88 7.81 shorthead 122 O 122 0.00 71.76 73.45 redhorse Cyprinidae northern 53 5 48 11-36 28.24 5.34 redbelly dace finescale dace 53 O 53 0.00 31.18 18.23 lake chut, 32 1 31 2.27 18.24 7.00 1 brassy IO1 1 minnow hornyhead 1 O 1
river chub 1 O 1 0.00 0.59 0.26
golden shiner 19 . 13 6 29.55 3.53 29.24 emerald 4 O 4 0.00 2.35 1 .O6 shiner cornmon 56 5 51 11.36 30.00 6.28 shiner blackchin 49 O 49 0.00 28.82 16.45 shiner blacknose 35 2 33 4.55 19.41 5.65 shiner spottail shiner 31 O 31 0.00 18.24 9.38 rosyface 1 O 1 0.00 0.59 0.26 shiner mimic shiner 1 1 O 2.27 0.00 3.88 bluntnose 19 13 6 29.55 3.53 29.24 minnow fa thead 30 1 29 2.27 17.06 6.34 minnow blacknose 28 O 28 0.00 16.47 8.34 dace longnose dace 5 O 5 0.00 2.94 1.33 creek chub 33 4 29 9.09 17.06 1.70 , fallfis h -29 O 29 0.00 17.06 . 8.68 Chapter 4 Species Composition Differences Chapter 4 Species Composition Differences
c) BRUCE PEN/NSULA AND WELLINGTON LAKES
A Chi-Square statistic is calculated for each species to test for significant differences in its frequency of occurrence between Bruce Peninsula (relict) and Wellington (solus) lakes. Three species of the collective sixty-one species examined in this study are not found in either of these regions: round whitefish (Prosopium cylindraceum), ninespine stic kleback (Pungitius pungitius), and trout perch (Percopsis omiscomaycus). Thirty -n ine of the fifty-eight species exarnined are significantly different in their frequency of occurrence between Bruce Peninsula and Wellington lakes (Table 4.8). Twenty-two species occur with a greater frequency in Bruce Peninsula lakes than in Wellington lakes. Seventeen species occur with a greater frequency in Wellington lakes than in Bruce Peninsula lakes. Muskellunge (Esox masquinongy), longnose sucker (Catostomus catostomus), shorthead redhorse (Moxostoma rnacro/epidoturn), lake chub (Couesius plumbeus), blacknose dace (Rhinichthys atratulus), fallfish (Semotilus corporalis), channel catfish (Ictalurus punctatus). threespine stickleback (Gasterosteus aculeatus), green sunfish (Lepomis cyanellus), bluegill (Lepomis macrochirus). longear sunfish (Lepomis megalotis), and sauger (Stizostedion canadense) are al1 common species in Wellington lakes but are not found in any Bruce Peninsula lakes. Conversely, the mimic shiner (Notropis volucel/us) is a common species in Bruce Peninsula lakes but is not found in any Wellington lakes (Table 4.8).
Table 4.8. Summary of frequency of occurrence of species in Bruce Peninsula (relict) and Wellington (solus) lakes. Bold X2 values indicate a significant difference in a species frequency of occurrence between relict and solus lakes.
1 Species Richneas 1 Fiequencyspecies of 1 Chapter 4 Species Composition Differences ChaDtef 4 S~eciesCorn~osition Differences Cha~ter4 Soecies Com~ositionOifferences
C. SPECIES RICHNESS
Speciesarea curves are calculated for each of the six study regions to detemine if differences exist in the number of species per lake (alpha richness), between proximally paired relict and solus lakes while controlling for lake sire. The results indicate that lakes in the Bruce Peninsula region have a significantly greater number of species per lake than lakes in the Wellington region. LaCloche and Sudbury regions, and Wawa and Algorna regions share a similar number of species per lake area (Table 4.9). Figures 4.3 to 4.5 represent the species-area curves for each of the pairs of proximal regions.
Table 4.9. Cornparison of species-area curves between relict and solus lakes.
Wawa Algoma Lacloche Sudbury
R Square 0.20 0.20 0.27 0.13 # Obs. 50 91 44 168 Significance 0.003 0.00002 0.0004 0.00001 Level Y - intercept 18.00 -7.69 -1 0.94 -2.65 Slope 4.62 3.41 3.41 2.05 T statistic 1.12 1.38 Degrees of 137 208 freedom T critical 1.66 1.65 (1 tailed) Significance No No Pc0.05 Cha~ter4 S~eciesCorn~osition Differences
Wawa (Relict) Lakes
O Algoma (Solus)Lakes
O
Log Lake Surface Area
Figure 4.3. Species-Area plots for Wawa and Algorna regions. Wawa lakes (y = 4.62~-18.00, R2 = 0.20,P = 0.003).Algoma lakes (y = 3.41x -7.69,RZ = 0.20, P = 0.00002).
1 Lacloche (Relict) Lakes 1 0 Sudbury (Solus) Lakes
Log Lake Surface Area
Figure 4.4. Species-Area plots for LaCloche and Sudbury regions. LaCloche iakes (y = 3.41 x - 10.94, Rz = 0.27, P = 0.0004). Sudbury lakes (y = 2.05~-2.65, Rz = 0.13, P = 0.00001). Chapter 4 Species Composition Differences
Bruce Peninsula (Relid) Lakes O Wellington (Salus) Lakes
O
Log Lake Surface Area
Figure 4.5. Species-Area plots for Bruce Peninsula and Wellington regions. Bruce Peninsula lakes (y = 4.73~-1 5.5. R2 = 0.31, P = 0.00001). Wellington lakes (y = 1.17~+ 0.97. R2 = 0.03, P = 0.1 ).
In order the examine native fish species richness across regions (beta richness), Mandrak and Crossman's (1992a) distribution maps were used to identify the number of fish species located in each of the six study regions. A total of 86 native fishes are found within the six study regions. Combined relict regions have a greater species richness (81 species) than combined solus study regions (70 species). Comparisons between proximally paired relict and solus lake regions indicate that al1 relict lake regions are more speciose than their proximal solus lake regions (Table 4.10). Chapter 4 Species Composition Differences
Table 4.10. Summary of native fish species located within each study region (Mandrak and Crossman 1992a). "X" represents the presence of a species in a region. Bold species indicate species examined within this study. Cha~ter4 S~eciesCom~osition Differences Chapter 4 Species Composition Differences
Johnny darter X X X X X X logperch X X X X X spoonhead X X X X X sculpin deepwater sculpin X X mottled sculpin X X X X X
, slimy sculpin X X X X X SPECIES 81 70 80 57 52 34 RICHNESS:
D. FISH SPECIES COMPOSITION IN LAKES
Correspondence analysis (CA) is performed to test for differences in species composition between relict and solus lakes. CAS are conducted on fish species incidence data for al1 relict and solus lakes combined and for the following proximally paired relict and solus lake regions: Wawa and Algoma, LaCloche and Sudbury, and
O Bruce Peninsula and Wellington.
A graphic representation of the results of each of the 4 CAS is represented in Figures 4.6 to 4.1 3. The ordering of species and lakes along the first axis of each CA is the result of the maximum possible correlation between species and lake scores (Pielou 1984). The second axis also maximally correlates species and lake scores with the constraint that this axis is orthogonal to axis 1. A lake is positioned at the centroid of the coordinates from a corresponding plot of species that are found within that lake. Lakes containing rare species are positioned farther away from the graph's origin. Similarly. lakes that contain common species are positioned near the graph's orîgin. Overall. lakes are positioned on the graph in relation to the sirnilarity of their species composition with other lakes. Therefore, lakes positioned at opposite ends of the graph contain distinctly different species compositions than lakes positioned on the graph in close proximity to Cha~ter4 S~eciesComposition Differences one another. The same holds true for the position of species in relation to lakes. Species found in few lakes are positioned farther way from the graph's ongin than species common in many lakes. Species are positioned on the graph in relation to the lakes where they are found. Therefore, species positioned at opposite ends of the graph are not found within the same lake.
Eigenvalues associated with each axis represent the correlation coefficient between species scores and lake scores (Pielou 1984). Therefore, an eigenvalue of one represents a high degree of correspondence between species and sites, and an eigenvalue close to zero represents very little correspondence. The first two eigenvalues for each of the CAS are represented in Table 4.1 1. The first two axes of the combined relict and solus lakes summarizes 67% of the species-lake variation. In regard to the proximally paired relict and solus lake regions, the first two axes of the LaCloche- Sudbury CA summarizes the most species-lake variation (71%) followed by Wawa- Algoma (64%), and Bruce Peninsula-Wellington (58%) (Table 4.1 1).
Table 4.1 1. Sumrnary of CAS of relict and solus lakes, Bruce Peninsula and Wellington takes, LaCloche and Sudbury lakes, and Wawa and Algoma lakes .
Axis 1 Eigenvaiue (% Variation :mmarized) Axis 2 1 Eigenvalue % Variation 1 Summarized) Total % Variation Summarized
Relict and solus lakes fondistinct groups in each CA of al1 relict and solus lakes combined. Wawa and Algoma lakes, LaCloche and Sudbury lakes. and Bruce Peninsula and Wellington lakes (Figures 4.6 to 4.1 3). In the CA graph of al1 relict and solus lakes cornbined, solus lakes are more diffuse across both axes than relict lakes (Figure 4.6). Chapter 4 Species Composition Differences
Relict lakes are tightly grouped within the positive quadrant. The results therefore indicate the solus lakes contain a more diverse species composition with less cornmon species than relict lakes. When the lakes are separated into the six study regions. there is a strong similarity in species composition between Sudbury, Algoma and Wawa lakes (Figure 4.7). Wellington and LaCloche lakes have only a weak similarity in species composition with the other regions.
All CAS of proximally paired relict and solus lake regions indicate that solus lakes contain a more variable community structure than relict lakes. Solus lakes and their associated species are located farther from the origin in a more diffuse grouping than relict lakes and their species assemblages. Figures 4.6,4.8. 4.1 0, and 4.12 illustrate this relationship between species and groups of relict and solus lakes.
Cha~ter4 Soecies Com~ositionDifferences
burbot Iowa darter white sucker logperch slimy sculpin 7 ...... 10 .,a..... -.. .. . ninespine stickleback blackchin shiner .--8 -- 4 . - . 9 lake trou1 4 . longnose sucker lake chub .- ".. common shiner finescale dace + 6 -. pearl dace t 4 + brook trout 'h " + norîhern redbelly dace *O 4 longnose dace brook stickleback ,.a...... 43,...... a .:* CV .- '...... fathead minnow .,."D 4.. 4 r 4 "'.-+q~.=i4 *-- . - * . ... FI.. j +oi B 0 a %a .:a ,...... : . 5 0 .a..--* 30 *.- ai ...... V?..--.-.* 15 20-.. % i I a a r rn mjm -2 .- m ....m 0 m m m,... 'a a 0. M: a -' a Johnny darter sauger blackchin shiner ' '.- muskellunge spotlail shiner lake trout / ...... o. I emerald shiner least darter lake chub ...... g...... 8. 'i' watleye shorthead redhorse -8 silver shiner rainbow darter trout-perch finescale dace / lake whitefish yellow perch -6 pearl dace cisco mottled sculpin 1 northern redbelty dace ' lhreespine stickleback /;"'""I northern pike blacknose shiner CA MIS 1 rosyface shiner creek chub Wawa (Relict) Lakes brook slickleback Algoma (Solus) blacknose dace 1 Lakes 1 fallfish
Figure 4.9. The association of Wawa (relict) and Algoma (solus) lakes based on a correspondence analysis of fish species composition. Ellipses represent a grouping of species relaied to a set of surrounding Wawa and Algoma lakes. Species are lisled in order of placement from lefî to right on the CA AXlS 1. Chapter 4 Species Composition Differences
LaCloche (Relict) Lakes
Sudbury (Solus) Lakes
Figure 4.10. The association of LaCloche (relict) and Sudbury (solus) lakes based on a correspondence analysis of fish species composition. Cha~ter4 S~eciesCorn~osition Differences
walleye btuntnose rninnow lake lrout rainbw darter ninespine stickleback creek chub iiorîhern pike Iowa darter river chub niuskellunge white sucker fallfish lake whilefish least darler brook trou ClSc0 logperch longnose dace burbot shysculpin pari dace sauger shorthead redhorse brook stickleback mottled sculpin green sunfish nort hem redbelly dace blacknose shiner emera\d shiner lake chub spottail shiner cornmon shiner blacknose dace O** ~&A-~erch blackchin shiner finescale dace +++ rosyface shiner longnose sucker fathead minnow a O .,...... threespine stickleback +OB@ 4 j ...... '. ...*..:.-..*..*.- '5' ' ...... '.. m a ...:0.' N ...... a. .. I ..*- n rn =..-Ta ./ + *.:' O 0 m 0 a œ A m 1 m - . v 1 - 8 1. I 9 t 1 *'== -= I - a 0- I - 8 0 -20 -15 -1O "ts:: . L.. 20 atam @MI rn i 8. m... m. .a I mimic shiner 1golden shiner ..... i i 8 $,... I brown bullhead yellow perch . 8 ..... b m I . ..S. . *.. . .. bluegill Johnny darler ...... 8 banded killifish pumpkinseed rock bass srnallrnouth bass largemoulh bass
1 Sudbury (Solus) Lakes 1
Figure 4.1 7. The associalion of LaCloche (relicl) and Sudbury (solus) lakes based on a correspondence analysls of fish species composition. Ellipses represent a grouping of species related to a sel of surrounding LaCloche and Sudbury lakes. Species are lisled in order of placement from left to Rght on the CA AXlS 1.
2 I OLIL. 8 8= 3 $ E Io gEzz=2c.5~A $ese Q 2 c O uS,ccn3a3= o JSf 4 sr% F $ r r .-g$?=sa oq~è-2 g203 ~~galR5 2 Qacn ci-2 'P g* c $r cozrnc c='E mo c%mo 0, ae $8 ~~cndz c~r=rncm('Ja,$~~~p.~ f3~6~axa on2 E 8, p 1 GEX" g-gf gg 0Ef2aL2,0=;~ z sim vac Y> Cha~ter4 Snecies Corn~ositionDifferences
E. STA TISTICAL SIGNIFICANCE OF DIFFERENCES IN SPECIES COMPOSIITON
Discriminant analyses are perfomed to assess prediction of membership in relict and solus lakes using the fint two components of CAs performed on lakes in relation to their fish species composition. The same procedure is repeated on pair-wise comparisons between the following proximal regions: Wawa and Algoma, LaCloche and Sudbury, and Bruce Peninsula and Wellington.
The results of the discriminant analyses indicate that relict and solus lakes have significant differences in species composition (Table 4.12) for al1 of the relict and solus lakes examined and for each of the proximally paired relict and solus lake regions examined: al1 relict and solus lakes combined (P < 0.000001), Wawa and Algoma (P < 0.000001 ), LaCloche and Sudbury (P c 0.000001), and Bruce Peninsula and Wellington (P c 0.000001 ). Cha~ter4 S~eciesCom~osition Differences
Table 4.12. Summary of discriminant analyses of al1 relict and solus lakes, Bruce Peninsula (relict) and Wellington (solus) lakes, LaCloche (relict) and Sudbury (solus) lakes. and Wawa (relict) and Algoma (solus) lakes using the first two components of correspondence analyses of lakes in relation to fish species composition.
A discriminant analysis is also performed to assess prediction of membership in each of the six study regions. The results of the discriminant analysis indicate a highly significant difference (P < 0.000001 ) in species composition between each of the six regions (Table 4.1 3). Algoma and Wawa had the strongest group placement of al1 regions with 77% of their lakes correctly predicted followed by LaCloche (61%), Wellington (35%). Bruce Peninsula (32%),and Sudbury (12%). Table 4.1 3. Surnmary of discriminant analyses of al1 six regions using the first two components of a correspondence analysis of lakes in relation to fish species composition.
11 Discriminant 1 Eigenvalue ( Relative 1 Canonical II
Actuall Bruce LaCloche Wawa Wellington Sudbury Algoma Predicted Peninsula Percentage Bruce 32.14 42.86 14.29 10.71 0.00 0.00 Peninsula LaCloche 15.91 61.36 2.27 15.91 0.00 4.55 1 Wawa 2.33 0.00 76.74 0.00 13.95 6.98 1 Wellington 18.18 19.32 15.91 35.23 6.82 4.55 . Sudbury 2.35 0.59 37.65 0.59 11.76 47.06
F. lNDEX OF DISPERSAL ABILlTY
Three important characteristics necessary for a species to successfulIy recolonize the Great Lakes -St. Lawrence basin after the last glacial recession are; temperature preference, swimming ability, and trophic Ievel. It is assumed that the first species able to successfully re-colonize this region are those that are coldwater species with a strong swimming ability and a generalized diet (low Dispersa1 Ability lndex score). Conversely, it is assumed that wamwater, piscivorous, slow swimming species (high Dispersal Ability lndex score), were probably the last to recolonize the area. The results of the Dispersa1 Ability lndex suggest that the channel caffish (lctalums punctatus) (Dispersal Ability lndex score of 4), was probably the first species to successfully recolonize the Great Lakes - St. Lawrence basin (Table 4.14). It is followed closely by bowfin (Amia calva), Chaoter 4 Species Composition Differences
salrnonids, catostomids, burbot (Lota Iota) and other ictalurids. The species predicted to colonize the area last are the centrarchids, gasterosteids and several shiner species (Dispersal Ability Index score of 8) (Table 4.14).
Table 4.14. Sumrnary of species scores on the Dispersal Ability Index.
Thermal Sustained 1 Trophic Guild Swimrning Level Speed 1=fast 1=omnivore 2=average 2=planktivorei 3=slow insectivore/ low = 8 to 9 benthivore 3=insectivorel II piscivore
channel catfish bowfin brook trout lake trout lake whitefish cisco round whitefish longnose sucker white sucker shorthead redhorse -. IlbFwTbulihëad
jnorthern pike 'muskellunqe central mudminnow hornvhead chub hiver chub golden shiner common shiner lonqnose dace yellow bullhead yellow perch i sauger walleve Ihohnnv darter p ---p. llslirny sculpin I
Ilnorthem redbellv dace I Chapter 4 Species Composition Differences
Thermal Sustained Dispersal Guild Swimming Ability Speed 1 1=fast 1=omnivore high = 3 to4 2=average 2=planktivorer average=5 to 7 3=slow insectivore1 low = 8 to 9 benthivore 3=insectivore/ piscivore ake chub wassy minnow ~lacknoseshiner osyface shiner nimic shiner ~luntnoseminnow athead minnow dacknose dace reek chub iearl dace rout-perch lmallmouth bass wgemouth bass ainbow darter 2wa darter zast darter ~gperch nescale dace lmerald shiner lackchin shiner pottail shiner rook stickleback , irees ine stickleback Kë&zaq
lack crao~ie Chapter 4 Species Composition Differences
IV. DISCUSSION
Parallels are drawn between relict and solus lakes and landbridge and oœanic islands using the analogy of "lakes as aquatic islands within a terrestrial sea". The focus of this discussion will be to establish how well patterns in species richness, variation in community structure, extinction and colonization processes, and age of relict and solus lakes match those of landbridge and oceanic islands.
A. SPECIES RICHNESS
It is predicted that relict lakes should contain more species than solus lakes. Relict lakes are formed from a large ancestral waterbody with a large species pool. Every species within the ancestral waterbody is assumed to have had an equal opportunity of colonizing each relict lake thereby forming relict lakes supersaturated with species. It is hypothesized that over time the species composition in these relict lakes is being driven primarily by extinction. Solus lakes, conversely, formed as isolated bodies of water. They never shared a common species pool with other bodies of water. Solus lakes formed on areas of land that were never inundated by a large proglacial water body (Figure 2.2 in Chapter 2). These areas of land are also generally located at a higher elevation than proximal areas of land that were once submerged under the weight of proglacial water bodies. Solus lakes. therefore, are generally located at a higher elevation than proximal relict lakes. Colonization into these isolated solus lakes would therefore be expected to occur through either upstream colonization of fish frorn lower elevation relict lakes into the oufflow of solus lakes or through catastrophic flooding events. For these reasons, solus lakes are expected to be species-poor in relation to relict lakes.
An examination of regional species richness between proximal relict and solus lake regions corroborates this prediction. Across al1 proximally paired relict and solus lake regions. regiooal species richness is deterrnined to be higher for relict lakes than solus lakes using Mandrak and Crossman (1992a); the most complete fish species distribution guide for Ontario to date. As well, an examination of species-area curves for each of the study regions indicates that there is a trend for relict lakes to contain a greater nurnber of species per area (lake size) than solus lakes. Therefore. the differences in species Cha~ter4 Species Composition Differences
richness between relict and solus lakes based on extinction and colonization processes are very similar to the species richness patterns and extinction and colonization processes within landbridge and oceanic islands respectively.
7. LA TITUDINAL GRADIENTS
Latitudinal gradients in species diversity have been recognized for over a century (Wallace 1878). Since Wallace, the cause of these gradients has received much attention. A number of theories have arisen about the factors that regulate species divenity. Recent hypotheses include biotic interactions involving competition, species packing, coevolution, and resource partitioning (e.g., Diamond 1986). However, the most widely accepted hypothesis of latitudinal gradients of species divenity is a parallel change in climate. or specificaily temperature (Hutchins 1947; Darlington 1951; Fisher 1960; Sanders 1968; MacArthur 1972; Ricklefs 1979; Rannie 1986). This relationship behveen temperature and latitude is especially important in determining species diversity patterns in fishes because of their ectothermic 1 poikilothermic nature. Such regional fish diversity patterns in relation to temperature have been examined by Barbour and Brown (1974) and Emery (1978).
No distinct iatitudinal species richness gradient is found amongst the six study regions based on regional species richness. However, when lakes are categorized based on their historical derivation, a decrease in species richness with increasing latitude is observed for both relict and solus lakes. Bruce Peninsula, the most southern reiict region, has a total regional species richness of 80 followed by LaCioche (52) and Wawa (35). Wellington, the most southern solus region, has a total regional species richness of 57 followed by Sudbury (34) and Algoma (29),which is located the farthest north. This pattern of decreasing species richness with increasing latitude is most likely revealed because significant differences in environment between relict and solus lakes are removed when the lakes are grouped by historicai derivation (refer to Chapter 3).
The distribution of a fish species is highly related to a decrease in temperature with increasing latitude in the Northern hemisphere. Proximal pair-wise cornparisons of relict and solus lakes are therefore performed to take into consideration these changes in climatic factors with latitude in relation to a species distribution range. For example in Chapter 4 Species Composition Differences comparing Wawa, and Algoma, the two most northem regions within the study, it is not surprising that green sunfish (Lepomis cyanellus) and longear sunfish (Lepomis megalotis) are not present in either of these regions, due to the notthem limit of their distibution range extending only into southern OntaBo (Mandrak and Crossman lW2a). It is noteworthy that there are many species of fish that are common in Algoma lakes but are not present in any Wawa lakes. These species include: muskellunge (Esox masquinongy), shorthead redhone (Moxostoma macrolepidotum), rosyface shiner (Notropis rubellus). threes pine stickleback (Gasterosteus aculeatus). sauger (Stizostedion canadense), rainbow darter (Etheostoma caeruleum), least darter (Etheostoma microperca) and mottled sculpin (Cottus baidi). The location of Algoma north of Wawa negates any factors related to species range limits in restricting the presence of these species in Wawa lakes. There are also no foreseeable barriers to dispersa1 such as waterfalls, dams etc., that would effect the structunng of the fish communities in this way (e.g.. Magnuson 1976). A similar distribution pattern of species found commonly in a solus lake region but absent from lakes in an adjacent relict region is also found for LaCloche and Sudbury and Bruce Peninsula and Wellington regions. There is no significant difference in sampling effort rneasured between relict and solus lakes. Differential sampling effort is not a possible factor contributhg to differences in species composition between relict and solus lakes. Biotic interactions such as cornpetition and predation have been observed in some lakes to strongly structure fish cornmunities (e.g., Werner and Hall 1988). However, the regional exclusion of these species from over 100 lakes does not make a biotic interaction argument plausible. It is most probable that differential environments between proximal relict and solus regions account for this selectivity in species occupancy . The relationship between the environment and species composition in relict and solus lakes will be discussed in Chapter 5.
One of the most interesting findings in this study is that threespine stickleback (Gasterosteus aculeatus), shorthead redhorse (Moxostoma macrolepidotum), and sauger (Stizostedion canadense) are ubiquitous throughout al1 three solus lake regions but are absent from al1 relict lakes within the study even though these lakes are within the species' ranges (Mandrak and Crossman 1992a). What is driving this distribution pattern? These are very different species with very different life histories. Perhaps these species prefer solus lakes due to their environmental tolerances or niche Chapter 4 Species Composition Differences
preference. Chapter 3 concluded that solus lakes are more basic, have a lower conductivity and a lower surrounding lake forest cover and net prirnary productivity than relict lakes. Perhaps these species are only able to exist within this range of the environrnent. These species-environment relationships will be examined in Chapter 5. Colonization and historical dispersa1 and biogeography are not likely be to facton driving this selectivity because these species are expected to have moved through relict lakes before moving into solus lakes. Therefore, these species are expected to be found in relict lakes. However, resource competition and predation may play a role in their isolation from relict lakes. Another hypothesis for this species pattern may be a priority effect (Robinson and Dickenon 1987; Robinson and Edgeman 1988). The niche space for these species may already have been occupied by competitors for these resources who colonized the relict lakes before these species and therefore pre-empted the niche space. These species therefore had to migrate further to find a lake with its appropriate niche without an existing competitor in its place. Examples of niche competitors within this study for the shorthead redhorse (Moxostoma macrolepidotum) are the white sucker ( Catostomus commersoni) and the Iongnose sucker (Catostomus catostomus). Niche competitors within this study for the threespine stickleback (Gasterosteus aculeatus) are the brook stickleback (Culaea inconstans) and the ninespine stickleback (Pungitius pungitius). A niche cornpetitor within this study for sauger (Stizostedion canadense) is the walleye (Stizostedion vitreum).
B. VARIA TlON lN COMMUNlTY STRUCTURE
It is expected that relict lakes, derived from the same ancestral species pool, share a similar community structure. Conversely, solus lakes, which are formed in isolation, have never shared a common species pool with another water body. Solus lakes are also generally located at a higher elevation than areas of land once inundated with proglacial waterbodies which later formed relict lakes. Colonization is therefore the prirnary process driving species composition in solus lakes. Solus lakes with outflows are most likely to have been colonized by the upstream movement of fish from relict lakes or by catastrophic flooding. However, historical factors such as invasion order and invasion rate were most likely important facton in detemining species composition in these lakes (Robinson and Tonn 1989). If early wlonists were able to pre-empt the habitat and prevent later invasion, then both the random order of arriva1 and the number Chapter 4 Species Composition Differences
of colonizations of a species were important in ensuring that each colonizing species was established somewhere in the system. Over tirne, a variety of species may have been the first to colonize different solus lakes thereby negating this priority effect on a regional basis. For these reasons. solus lakes are expected to show a wider variation in community structure compared to proximal relict lake regions.
The results of this study corroborate with the prediction that isolated lakes have a greater variation in their fish communities than lakes which evolved from a common species pool. Correspondence analyses performed on proximal relict and solus regions indicate that solus lakes are in fact more highly varied in their species composition than relict lakes. Therefore, variation in community structure based on extinction and colonization processes in relict and solus lakes are very similar to landbridge and oceanic islands respectively.
C. LAKEAGE
Oceanic islands are typically older than landbridge islands. However, this does not hold true for relict and solus lakes. As the glaciers retreated northward, relict and solus lakes at the same approximate latitude are expected to have formed at the same time (Figure B1 to 89 in Appendix B). Proximal relict and solus lake regions examined within this study are therefore approximately the same age. Therefore. there are no isolating factors with respect to the age of the lake infiuencing differences in community structure between relict and solus lakes. However. differences in colonization potential between relict and solus lakes rnay act as an isolating mechanism.
D. DISPERSAL ABILITY
The species divenity of the region is largely dependent on the length of time the region has been open for colonization. The last maximum glaciation of North America occurred approximately 18,000 years ago at which time the Laurentide Ice sheet covered most of Canada and the northern United States. These areas were devoid of life at this moment in history. All flora and fauna present today in these areas had to have corne from descendants that colonized after the last glacial recession starting approximately 15,000 years ago. A fish species' swimming ability as well as its tolerance to fiuctuations in the Chapter 4 Species Composition Differences environment, especially temperature and food resources, are key factors in a species' ability to recolonize the Great Lakes - St. Lawrence basin after glaciation. The Dispersal Ability Index predicts that salmonids, catostomids and ictalurids were probably the first species to successfully recolonize the proglacial lakes in the area. As the temperature increased and the hydrology stabilized, cyprinids are predicted to have moved back into the area followed lastly by centrarchids. Over time it is expected that a vast number of individuals from each species colonized the proglacial lakes in the Great Lakes - St. Lawrence basin. These proglacial lakes receded to form relict lakes with established cornmunity structure containing both poor and strong dispersers. If solus lakes are as isolated as oceanic islands, then it is expected that solus lakes contain only species with the strongest dispersal ability such as salmonids, catostomids, and ictalurids. The results of this study do not cornply with this prediction. Solus lakes contain a wide variety of species with varied dispersal abilities.
E. GENETIC VARIA TION
Previous research has concluded that the last (Wisconsinan) glaciation has decreased fish genetic diversity through population bottleneck effects. Populations of northern ternperate fishes were confined in separate glacial refugia where they evolved independently for thousands of years, resulting in the development of genetically distinct intraspecific groups (Bernatchez 1995; McAllister et al. 1986). As the glaciers retreated, huge proglacial lake and river connections were created that provided opportunities for the dispersal and mixture of these previously isolated fish populations (Bernatchez and Dodson 1991). Mitochondrial DNA (mtDNA), has been widely used as a genetic marker in population studies because of its higher mutation rate relative to nuclear DNA. generally materna1 inheritance, and Jack of sexual recombination (Brown 1985). The ability of mtDNA to retain a history of past isolation, despite the mixing of previously isolated populations, is well demonstrated in a variety of fish species (Bemingharn and Avise 1986; Avise et al. 1987; Billington and Hebert 1991; Avise 1992). Among northem fishes. mtDNA analyses of walleye (Billington et al. 1992). lake trout (Grewe and Hebert 1988; Wilson and Hebert 1998); lake whitefish (Bernatchez and Dodson 1991; Bodaly et al. 1992; Foote et al. 1992), cisco (Bernatchez and Dodson 1990), white sucker (Lafontaine and Dodson 1997). and rainbow smelt (Bematchez 1995). have al1 revealed the presence of genetic differences in populations related to the genetic divergence of Chapter 4 Species Composition Differences these populations occupying different glacial refugia at various times during the Pleistocene.
Solus takes were formed in isolation from other waterbodies. They were also generally formed at a higher elevation than glacial relict lakes. For these reasons, solus lakes are expected to be colonized by fewer individuals of a species than relict lakes. It is also plausible that founder effects may be prominent in solus lakes due to their isolation. Based on these founder effects, fish populations in solus lakes are expected to have a lower genetic diversity or be more genetically isolated cornpared to related populations in relict lakes. Studies of mtDNA of northern fishes have clearly illustrated the impact of glaciation on intraspecific genetic structure in glacial refugia. These protocols should be used on select species found in proximal relict and solus lakes to detenine the degree of isolation between these populations.
F. EFFECTS OF HUMAN INTERVENTION ON FISH DISTRIBUTION
One very important problem in examining fish biogeography is the effect of human intervention on species distributions. When fishes are dispersed by human activities, natural dispersal barrien are overcome and the resulting community in a lake may be quite different form the community that would have existed otherwise. Human intervention is fish distribution is prominent at both the regional and local levels.
Canals, diversions, dams and other human-intervened habitat changes act to restrict fish species ranges and even eliminate species over parts of their natural range. The following are examples of canals and diversions within the Great Lakes - St. Lawrence basin which may have significant impacts on natural fish species distributions (MacKay 1963).
7. Canals r Opening of the Welland canal in 1829 and subsequent diversions and dams have provided access for the dispersal of sea larnprey and alewife, both exotic species, from Lake Ontario into the upper Great Lakes. Pnor to the opening of the Welland canal, Niagara Falls was a natural barrier to their dispersal. Cha~ter4 S~eciesCom~osition Differences
Chicago drainage canal made access from the Mississippi watershed to the Great Lakes possible.
Erie-Barge Canal in New York connects the Hudson River drainage to Lake Erie and Ontario which enabled exotic species such as the white perch to enter Lake Erie and Ontario.
Diversions
Longlac diversion and control dam was designed to Roat pulpwood into Lake Superior through Long Lake and the Aguasavon River. Starting in 1941 this dam has been used for hydroelectric power.
Lake St. Joseph diversion and control dam was opened in 1957 and redirects water from Lake St. Joseph to Lac Seul via the Root River.
The effects of human intervention on fish community structure is also predominant at the local level of inland lakes. Many cottages are located along most of the larger inland lakes creating beach fronts and docks which destroy the littoral zone and thus disrupt species habitat. Many of the lakes have year-round fishing which creates extemal stressors on the lakes as in over-fishing and species introductions (sport fish and bait fish). Many lakes also have stocking programs for sport fish such as lake trout. brook trout and bass. There are numerous unauthorked introductions of sport fishes into these lakes as well as no widespread records discriminating between native and introduced populations. All of these interventions may negatively impact the natural distribution patterns of native fish species. C hapter 4 Species Composition Differences
V. CONCLUSIONS
The conclusions from this study are as foliows:
0 Relict and solus lakes have significant differences in their fish species composition. Solus lakes have a more depauperate species composition and a more diverse comrnunity structure than relict lakes. These results suggest the presence of a founder effect in solus lakes,
O Fish community structure is strongly related to the historical formation of a lake, r A Dispersal Ability Index (DAI) was derived to predict the order of fish species re- colonizing the Great Lakes - St. Lawrence basin. This method is based only on species attributes and is applicable to an examination of any fish species within the temperate zone. The DAI is based on the temperature preference, swimming ability, and trophic level of fish species, and r Relict and solus lakes are found to share al1 of the characteristics of landbridge and oceanic islands respectively except for the notions that landbridge islands are generally younger than oceanic islands, and oceanic islands support only highly vagile species.
These striking similarities between relict and solus lakes and landbridge and oceanic islands regarding historical formation. extinction and colonization potential. and resultant fish community structure warrant the expansion of the current Theory of Island Biogeography to include relict and solus lakes. Table 4.15 is a summary of the Cndings of this chapter for relict and solus lakes and how well they match those characteristics of landbridge and oceanic islands. Cha~ter4 Soecies Corn~ositionDifferences
Table 4.1 5. A cornparison of relict and solus lakes wiîh landbridge and oceanic islands. Characteristics of Agree Characteristics of Relict Lakes Landbridge Islands
species from common ancestral species from common ancestral water body species pool J mainland species pool
higher species richness than higher species richness than solus lakes oceanic islands
species composition driven species composition driven primarily through extinction 4 primarily through extinction
colonizatton rates may not colonization rates may not balance rates of extinction but balance rates of extinction but they may be high enough J they may be high enough especially for highly mobile especially for highly mobile species to significantly influence species to significantly influence species distribution species distribution
approximately the same age as younger than oceanic islands Il solus lakes lx/ Characteristics of Characteristics of Solus Lakes Oceanic Islands
never shared an comrnon never shared an ancestral species pool with an ancestral common species pool with water body mainland
species poor relative to proximal species poor relict lakes
- species composition driven a species composition driven primarily through colonization J primarily throug h colonization
supports a widely range of support only highly vagile species / species approximately the same age as older than landbridge islands II relict lakes Chapter 5 Species - Environment
Species = environment relationships in relict and solus lakes
1. INTRODUCTION
Community ecology includes both the search for patterns in species composition and the processes that drive these patterns. Processes that drive patterns in species composition operate over numerous temporal and spatial scales. Time is most commonly divided into evolutionary and ecological time. Historical processes, such as the last glacial recession and the dispersal of fish species into inland lakes within the Great Lakes - St. Lawrence basin as discussed in Chapter 4, are part of evolutionary time. Current processes involving biotic factors such as species interactions (i.e., competition, predation, and parasitisrn), and abiotic factors such as local and regional environmental variables operate in ecological time. It is important in examining the factors that drive species composition, to consider the processes as operating over different temporal scales. It is equally important to examine these processes as operating over different spatial scales. All of the processes described above function over a range of spatial scales and change with time. DifFerent processes therefore may become more prominent than others depending on the spatial scale of the study. Trying to determine what factors are important in defining community structure also depends on how the ecological boundary of the community is defined (refer to Chapter 3).
The broader the spatial scale of the study. the more prevalent abiotic factors and geologic history become in defining community structure (e-g., MacArthur 1972; Ricklefs 1987). Biotic variables. on the other hand, become generalized to the frequency of occurrence level (Le., presencd absence) at larger scale studies because the feasibility of collecting biotic detail decreases with increasing spatial scale. Abiotic factors cannot be controlled sufficiently in large scale studies as they could in single community-single site studies where the smaller spatial scale of the study eliminates most of the abiotic variance, and biotic interactions such as competition and predation become prevaient. Cha~ter5 S~ecies- Environment
A. FISH SPECIES - ENVIRONMENT STUDIES IN NORTH AMERtCAN LAKES
A summary of fish species - environrnent studies conducted in North American lakes is found in sections B1 and 82 of the Materials and Methods section in Chapter 3. This summary highlights the species - environrnent relationships that have already been established and widely accepted as well as those relationships that need further refinement. Most of the studies of fish species - environment relationships in North American lakes have focused on local environmental variables especially lake surface area, volume maximum depth, and pH. Relatively Meresearch has been conducted on the effects of regional environmental variables such as climate and geology on Csh species composition in lakes. Temperature is the only regional variable that has been studied in much detail. This study will use both local and regional environmental variables in an attempt to better understand the relationships behveen lacustrine fish species and their surrounding environments.
B. SPEClES NICHE
The methods used in this study to examine species -environment relationships are derived from the concept of the ecological niche (Hutchinson 1957). Each species is most suited to a particular value (its optimum) of an environmental gradient and cannot survive when the value is either too low or too high (e.g., Fry 1947). Each species' occurrence is therefore confined to a limited range. its niche. The fundamental niche of a species is determined solely by physiological processes and cannot be observed in reality (Putnam 1994). What can be observed is the realized niche of a species which is a limited proportion of conditions and resources within a species' fundamental niche that allows a species to maintain a viable population even in the presence of cornpetitors and predators. These interactions between species in a cornmunity change along environmental gradients according to unirnodal functions.
Hutchinson (1 957) and (1959) extended the niche concept to n-dimensions. Each species therefore occurs in a characteristic, limited range of a multi-dimensional habitat space. and within this range, each species tends to be most abundant around a specific environmental optimum (Green 1971 ). Chapter 5 Species - Environment
C. OBJECTIVES OF THIS CHAPTER
The purpose of this chapter is to examine why there are differences in cornmunity structure between relict and solus lakes within the Great Lakes - St. Lawrence basin. Chapter 4 examined the historical dispersa1 of fish species into these regi0.n~from the start of last glacial recession to the present time. It was concluded that these different lake types have significantly different species compositions which may have resulted from differences in colonkation potential between the two lake forms. Chapter 3 examined the local and regional environrnents of relict and solus lakes and wncluded that these lakes have significantly different local and regional environments. Therefore, an objective of this chapter is to determine if differences in relict and solus take environments can account for differences in species composition between relict and solus lakes. This should help extend our understanding of the relative contributions of local and regional processes to the cornmunity structure of relict and solus lakes.
Chapter 4 also provided evidence of a founder effect in solus lakes due to their isolation. If there is a prominent founder effect within these lakes. it would be expected that the species within solus lakes would have different niches than the same species found in adjacent relict lakes. The final objective of this study is to examine differences in a species' observed optimum and tolerance to environmental gradients in relict and solus lakes. Chapter 5 Species - Environment
II. MATERIALS AND METHODS
A. STUDY LAKES, VARIABLES AND DATABASES
A total of 550 lakes divided amongst six regions within the Great Lakes - St. Lawrence basin of Ontario are exarnined in this study. Each region is classified as containing either relict or solus lakes based on historical lake formation. These regions are paired such that regions containing relict and solus lakes that are in close proximity to one another are matched as a pair. Therefore, Wawa and Algoma regions are matched as a pair. as are LaCloche and Sudbury regions, plus Bruce Peninsula and Wellington regions. Refer to Chapter 3 pages 3-1 0 and 3-1 1 and Chapter 4 pages 4-1 3 to 4-1 5 for a complete summary of the lakes and the species incidence and environment variable databases used within this study.
B. STA TISTlCAL METHODS
1. CANONICAL CORRESPONDENCE ANA LYSIS
Gradient analyses are multivariate statistical methods designed to analyze sets of species occurrence and environmental variables over numerous sites. The ecological niche (Hutchinson 1957). provides a conceptual basis for gradient analysis. Each species in a gradient analysis is treated as a distinct biological unit with a unique niche or set of ecological requirements that are reflected in its distribution (Whittaker 1956, 1967).
Canonical correspondence analysis (CCA) (ter Braak 1986). is a fom of direct gradient analysis which uses a combination of ordination and multiple regression techniques to examine the effect of a particular set of environmental variables on species composition. Alt CCAs in this study are performed using version 2.1 of the program CANOCO (ter Braak 1987). The statistical mode1 underlying CCA is that a species* frequency of occurrence is a unimodal function of position along environmental gradients; a species' niche. CCA summarizes the maximum amount of species variation in a community while simultaneously forcing this species matrix to correlate with axes based on linear composites of environmental data. Therefore. relationships between species are summarized in such a way that the community relationships and the gradients in the Chaoter 5 S~ecies- Environment environmental variables are maximally conelated. The resulting ordination diagram expresses not only a pattern of variation in species composition, but also the relationship between the species and each of the environmental variables (ter Braak 1986).
CCA builds on the rnethod of weighted averaging of indicator species proposed by Ellenberg (1948: Jongrnan et al. 1995) and Whittaker (1956 and 1967). CCA extends weighted averaging to the sirnultaneous analysis of many species and many environmental variables. CCA also builds in the ordination method of correspondence analysis (Hill 1973, 1974) through regression (ter Braak and Verdenschot 1995).
CCA forms a linear combination of environmental variables that maximally separates the niches of the species based on field data of biological communities and environmental features (ter Braak 1987). The species centroid (niche) is therefore the weighted average of the environmental gradient values of the sites at which the species occurs. The species centroid is an estimate of the species optimum for its n-dimensional niche space (see Hutchinson 1957), if the response curve of the species is symrnetric. The first synthetic gradient derived from CCA is terrned the first ordination axis. The maximum amount of species' niche separation (how much variation in the species data is explained by the combination of environmental variables for the axis), is given by the eigenvalue of the ordination axis. Su bsequent ordination axes are also linear combinations of the environmental variables that maxirnally separate the species niches, but subject to the constraint that they are uncorrelated (Le., orthogonal), with the axis or axes extracted previously. In principle, as many ordination axes can be extracted as there are environmental variables. However, because the niche separation (eigenvalue), decreases with increasing axis number, it is often sufficient to examine only the first few axes (ter Braak and Verdenschot 1995). a) PARTITION/NG OF SPECIES VARIA TION
Species composition and environmental variables may share a common spatial structure. In this situation, the spatial structure will cause gradient analyses such as CCA to overestimate the arnount of species variation explained by the environmental variables due to spatial autocorrelation. In order to reveal species-specific habitat preferences, it is first necessary to remove this underlying spatial structure from the Chapter 5 Species - Environment
biological and environmental data. and then model the residual species-environment relationships (Borcard et al. 1992; Legendre 1993). Recent developments in gradient analysis have focused on methods for partitioning variation in species composition among sites into two or more components. Borcard et al. (1992) derived a rnethod of partitioning the variation of species composition by its relative correlation with sets of environmental variables by using eigenvalues of constrained and partial ordinations from CCA. This partitioning approach is used in this study to examine fish species- environment relationships after removing the underlying spatial structure including lake longitude, latitude and elevation variation. Borcard et al. (1992) uses four CCA analyses to partition species variance: 1) CCA of the species matrix. constrained by the environrnental matrix, 2) CCA of the species matrix, constrained by the matrix of spatial coordinates, 3) like (l), after removing the effect of the spatial matrix. 4) like (2), after removing the effect of the environmental variables. Eigenvalues from these 4 steps are used to calculate the overall amount of explained variation (step (1) + step (4), or step (2) + step (3)),the relative percentages of variance explained at each step, and to partition the total species variance into four components: nonspatial environmental variation = step (3), spatially structured environmental variation = step (1 ) - step (3),or step (2) - step (4), spatial species variation not shared by the environmental variation = step (4); unexplained variation = 100 - (step (1) + step (4)).
This partitioning of species variation has been used to more accurately infer species - specific habitat preferences independent of underlying spatial patterns in both species and environmental data (e.g.. Hill 1991; Vetaas 1993). However, CCA cannot be used to quantify spatial autocorrelation. lnstead, partial Mantel tests can be used to quantify and control for spatial autocorrelation in ordination analyses of species-specific habitat preferences (e.g., Sanderson et al. 1995). b) BIPLOTS OF SPECIES - ENVIRONMENT RELAT/ONSHIP
An ordination biplot is a graphic representation of the species - environment relationship. For each ordination biplot, species are plotted as points. Species that have a broad niche for the environmental variables examined in this study produce CO-ordinatesclose Chapter 5 Species - Environment to the origin. These species are able to exist in a wide range of environments and are thus fairly common. Conversely, species that have a narrow niche for the environmental variables examined in this study are found to be located far from the origin. These species are able to exist only in very specialized habitats. Environmental variables are represented as vectors. The length of an arrow indicates the importance of the environmental variable in summarizing species variation. The direction indicates how well the environmental variable is correlated with the various ordination axes. The angle between arrows indicates the correlation between environmental variables. Each environmental vector determines a direction or axis in the diagram, obtained by extending the arrow in both directions. Frorn each species point, a line can be drawn perpendicular to this environmental axis. Its location along the environmental axis indicates the species' optimum niche for that particular environmental gradient in comparison to the other species (ter Braak 1994).
CCA is performed using a set of combined local and regional environmental variables with spatial variation partialled out to detemine the effect of these environmental variables on species composition in relict and solus lakes. For this analysis, the variation in fish species composition is correlated with the following three sets of variables: environment and spatial, pure environment, and pure spatial. Any species variation that cannot be accounted for from these sets of variables is categorized as "undeterminedn.
These procedures are repeated to examine pair-wise cornparisons for the following proximally paired relict and solus lake regions: Wawa and Algoma, LaCloche and Sudbury. and Bruce Peninsula and Wellington. Cha~ter5 S~ecies- Environment
2. DISCRIMINANT A NAL YSIS
CCA ordinates each lake within the study according to its fish species composition and environment. Therefore, to test for significant differences in the species - environment relationship between relict and solus lakes, a discriminant analysis (Legendre and Legendre 1983) is performed on lake scores from the fint two axes of CCAs of all relict and solus lakes combined and each pair of proximal relict and solus lake regions. Discr~minantanalysis, also termed discriminant function analysis, canonical variate analysis and canonical discriminant analysis. is a multivariate statistic which is used to maximally contrast two groups of variables to examine if significant differences exist between the two groups of variables. The resultant discriminant function, also tened the canonical variate or canonicétl axis, is the maximum difference between the two groups.
3. WEIGHTED A VERAGING AND CALIBRATION
CCA uses weighted averaging methods to calculate a species' observed optimum and tolerance for each environmental variable in relation to the whole suite of environrnental variables examined in a study. It therefore does not provide a specific observed optimum and tolerance value for each species along each environmental gradient examined. Instead, version 2.1 of the program WACALJB (Line and Birks 1990) is used to examine species specific observed optima and tolerances for each environmental gradient.
As stated previously, weighted averaging is based on the ecological niche concept (Whittaker 1967) which States that each species has a unimodal response (Gaussian curve) to an environmental gradient and an observed optimum for a specific environmental variable and an associated observed range of tolerance (niche breadth). The value of a species' observed optimum for a specific environrnental variable is therefore obtained by taking the weighted average of values for the environmental variable over those sites where the species is present. The species' observed tolerance is calculated as the standard deviation of the species response to the environrnental gradient. Cha~ter5 S~ecies- Environment ter Braak and Looman (1986) compared the performance of the methods of weighted averaging and of Gaussian logit regression to estimate the observed optimum of a Gaussian curve from species incidence data. Through simulation and practical examples, they showed that the weighted average is about as efficient as the regression method for estimating the obsewed optimum when a species is rare and has a narrow ecological amplitude. and when the distribution of the environmental variables among the sites is reasonably hornogeneous over the whole range of occurrence of the species along the environmental variable.
One problem with weighted averaging is gradient length. If the environmental gradient length under consideration is short (2 standard deviations or less), species are generally behaving rnonotonically along the gradient, and linear regression and calibration methods are therefore appropriate. If the environmental gradient length is long (2 standard deviations or more), several species will have their observed optima located within the gradient, and a unimodal based method of regression and calibration such as weighted averaging is appropriate (ter Braak and Prentice 1988).
Therefore, the following environmental gradient measures are calculated for each of the environmental variables for each of the six study regions: minimum value, maximum value, median, mean, and standard deviation.
If the standard deviation of an environmental gradient is greater than or equal to two standard deviations, it can be used appropriately in weighted averaging and calibration analysis. High (maximum value), low (minimum value) and close (mean) plots are used to compare the same environmental gradient within each pair-wise proximal relict and solus lake region. This will ensure that the environmental ranges overlap so that species' observed optimum and tolerance comparisons between proximal regions are possible. Chapter 5 Species - Environment
The weighted averaging and calibration technique is used to estimate ecological observed optima and tolerances of fish species in relation to environmental gradients within each of the six study regions. Individual species' observed optima and tolerances along each environmental gradient are computed by weighted averaging using Version 2.1 of the program WACALIB (Line and Birks 1990). Chapter 5 Species - Environment
III. RESULTS
7. ALL RELICT AND SOLUS LAKES COMBINED a) PARTITIONlNG OF FIS# SPECIES VARIA TION
CCA variation partitioning of the fish species data rnatrix for both relict and solus lakes is perfomed using combined local and regional environmental variables. Fish species variation for both relict and solus lakes is wrrelated with the following three components: nonspatial environmental variation, spatial species variation not shared by environrnental variation, and spatially structured environrnental variation. Any species variation that cannot be accounted for from these sets of variables is categorized as "undetermined".
Combined local and regional environmental variables explain approximately 88% of the variation in the species matrix in relict lakes and 55% in solus lakes (Table 5.1 ). Roughly half of this variation for both relict and solus lakes can be explained by the spatial location (latitude longitude, and elevation) of the lakes. This indicates that fish community structure and environmental variables have a fairly similar spatial structuring in both relict and solus lakes. The other half of the explained fish species variation from environrnental variables in both relict and solus lakes involves a pure species composition - environment relationship without an underlying spatial pattern (Table 5.1 ). This partitioning of species variation into pure environment, environment and spatial, pure spatial and undetermined cornponents is summarized in Figure 5.1. Chapter 5 Species - Environment
Table 5.1. Fish species variation partitioning for both relict and solus lakes using combined local and regional environmental variables.
Solus Cakes
eigenvalues (total inertia) =
2) CCA of species matrix, constrained by the extended matrix of spatial coordinates: surn of al1 ,703 canonical eigenvalues =
3) Like (1), after removing the effect of the spatial matrix: surn of al1 eigenvalues = .398
4) Like (2),after removing the effect of the environmental variables: surn of al1 canonical 126 eigenvalues =
The surn of al1 eigenvalues in a CA of the species matrix = 1.256
The percentage of the total variation of the species 1) 71.42 matrix accounted for by each step of the analysis 2) 55.97 = total inertia * 100 1 CA eigenvalue sum 3) 31.69 4) 10.03 The overall amount of explained variation represented as the percentage of the total variation of the species 87.66 matrix = (2) + (3) = (1) + (4) = Percentage of non-spatial environmental variation = (3) = 31.69
Percentage of spatialiy structured environmental variation 45.94 = (2)- (4)~(1) - 3)=
Percentage of spatial species variation not shared by environmental variables 10.03 7.51
Percentage of unexplained variation 12.34 = 100 - ((2)+ (3)) = IO0 - ((1) + (4)) = -- Cl Undetemined a Spatial Environment & Spatial Environment
Relict Solus Lakes Lakes
Figure 5.1. Variation partitioning of fish species variation according to combined local and regional environmental variables for relict and solus lakes.
Approximately 10% of the explained species variation in reiict lakes and 8% in solus lakes is spatial variation that is not related to the environmental variables examined in this study (Figure 5.1). This spatial variance in both relict and solus lakes may be acting as a descriptor of unmeasured underlying processes driven by other environmental variables or biotic factors. However, this small amount of species variation accounted for by spatial location alone in both relict and solus lakes suggests that no important spatial- structuring processes have been missed.
The amount of undetermined species variation is almost four times greater in solus lakes (45%) than relict lakes (12%) (Figure 5.1). Although the underlying processes cannot be identified from the available data, the analyses suggest Viat these unidentified processes Cha~ter5 S~ecies- Environment
are to sorne degree independent of the measured environmental variables, and their relationship with fish cornrnunity structure cannot be totally predicted by lake spatial coordinates. This undetermined fish species variation is the result of effects of unrneasured (biotic or abiotic) variables, or spatial structure. Therefore, environmental and spatial variables surnmarize more fish species variation in relict lakes thansolus lakes. The species composition found in solus lakes has a larger percentage of variance that cannot be explained by the lake's environment and spatial location than the species composition in relict lakes. bJ SPEClES COMPOSITION - ENVIRONMENT RELA TlONSW
CCA is performed using combined local and regional environmental variables with spatial variation partialled out for both relict and solus lakes. The results of these CCAs are plotted as ordination biplots in Figures 5.2 and 5.3 respectively (Table 5.2 is a sumrnary of the species codes for al1 CCA biplots presented in this study). Eigenvalues of the first two axes are 0.74 and 0.10 for relict lakes and 0.1 9 and 0.09 for solus lakes. The sum of al1 canonical (i.e., constrained) eigenvalues is 0.40 for relict lakes and 0.36 for solus lakes. The ordination biplots for relict and solus lakes therefore represent 60% ( = 1OO* (O. 14+0.10) 10.40) and 78% (=100*(0.19+0.09)/0.36) of the variance in the fish species data respectively. Cha~ter5 Species - Environment
Table 5.2. Summary of fish species codes used for each of the biplots in this study.
------brook trout C lake trout D 1 ll~ikiwhitefish I F Il
..- .- .- - - brown bullhead Al channel catfish AJ iitad~olemadtom 1 AK II banded killifish AL burbot AM brook stickleback A0 threespine stickleback 1 AP ninespine stickleback AQ trout-perch AR rock bass AT green sunfish AU pumpkinseed AV bluegill AW Chapter 5 Species - Environment
llCommon Name ( Species Code Il
longear sunfish smallrnouth bass AY Ikaroernouth bass 1 A2 II
Y -' sauger walleve BD rainbow darter BE Iowa darter BF least darter BG (I~ohnnvdarter 1 BH II logperch BI mottled scubin BJ Hsiimv scul~in I BK 1 Chapter 5 Species - Environment
Area Z Shoreline \ NPP Max Depth
Secchi
1 Forest Wover ,, Parent Material \ Conductivity Soil Drainage
CCA Anis 1 Figure 5.2. Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environmental variables (veclors) for relict lakes with spatial variation partialled OUI.Vectors point in the direction of maximal change of a given environmental variable. Environmental variables wilh long vectors are more slrongly correlated with the axes than are those with shorter vectors, and accordirigly are more strongly related to the species pattern in the biplot. Species can be projeded relative to the vectors such that the ordering of species along the axis of a vector is approximately the ranked, weighted mean value of the species relative to the environmental vector.
Chapter 5 Species - Environment
The species-environment correlation coefficients are higher for relict lakes (~0.93for axis 1 and r = 0.76 for axis 2) than for solus lakes (r=0.67 for axis 1 and r=0.60 for axis 2). This indicates that environmental variance surnmarizes more variation in community composition in relict lakes than in solus lakes.
Fish species found in relict lakes are located very close to the ongin (Figure 5.2). Proximity to the origin indicates that these species have a similar broad niche for the environmental variables examined in this study. Environmental variables which account for most of the variation in fish species composition in relict lakes ranked in order from most to least are: surrounding lake soi1 drainage, surrounding lake net primary productivity, Secchi depth, volume. maximum depth, pH, surface area, total shoreline perimeter, surrounding lake forest cover, specific wnductivity, mean annual precipitation, parent material, contouring complexity, and annual number of degree days.
Fish species found in solus lakes are located far from the origin (Figure 5.3). Distance from the origin indicates that these species have an overall narrower niche for the environmental variables examined in this study. Environmental variables which account for most of the variation in fish species composition ranked in order from most to least are: surface area, surrounding lake net primary productivity, surrounding lake forest cover, mean annual precipitation, contouring complexity, Secchi depth, parent material, surrounding lake soi1 drainage, specific conductivity, pH, volume, total shoreline perimeter, maximum depth, and annual number of degree days.
C) STATISTlCAL SlGNlFlCANCE OF SPECIES - ENVIRONMENT RELATlONSHIPS
CCA ordinates each lake within the study according to its fish species composition and environment. Therefore, to test for significant differences in the species composition - environment relationship between relict and solus lakes, a discriminant analysis (Legendre and Legendre 1983), is performed on lake scores from the first two axes of a CCA using local and regional environmental variables with spatial variation partialled out.
The results of the discriminant analysis indicate that relict and solus lakes have a significantly difierent species composition - environment relationship in tems of combined local and regional environmental variables with the spatial variation rernoved Cha~ter5 S~ecies- Environment
(P~0.000001)(Table 5.3). Figures 5.4 summarizes the difference in the species - environment relationship between relict and solus lakes in relation to their lake scores on the first two axes of the CCA. 72% and 66% of the relict and solus lakes respectively, are correctiy classified.
Table 5.3. Summary of a discriminant analysis of relict and solus lakes species - environment relationship using lake scores on the first two components of a canonical correspondence analysis of cornbined local and regional environmental variables with spatial variation partialled out.
Combined Local and Regional Environmental Variables
Eigenvalue 0.15
Canonical correlation 0.36 11 Wifks lambda I 0.87
11 Significance level 0.000001 L I Relict takes Solus Lakes Classification results: % Predicted relict lakes 71.79 33.81
% Predicted solus lakes 28.21 66.19
Chapter 5 Species - Environment
A discriminant analysis is also perfomed to assess membenhip prediction in each of the six study regions. The results of the discriminant analysis indicate a signifiant difference (P < 0.0001) in species-environment relationship between each of the six ragions (Table 5.4). Figure 5.5 summadzes the differences in the species - environment relationship between the six study regions in relation to their lake scores on the first two axes of the CCA. Bruce Peninsula has the strongest group placement of al1 regions with 86% of its lakes correctly predicted followed by Wawa (81 %). Algoma (66%). LaCloche (50%). Wellington (46%) and Sudbury (16%) (Table 5.4).
Table 5.4. Summary of discriminant analysis of species - environment relationships for each of the six study regions using lake scores on the first two components of a canonical correspondence analysis of combined local and regional environmental variables with spatial variation partialled out.
- 1 Discriminant 1 Eigenvalue 1 Relative 1 Canonical II
(1 Functions Wilks 1 X2- DF
Actuali Bruce LaCloche Wawa Wellington Sudbury Algoma Predicted Peninsula Percentage Bruce 85.71 0 .O0 0.00 1.79 8.93 3.57 Peninsula LaCloche 2.27 50.00 0.00 20.45 15.91 11.36
Wawa 0.00 1 1.63 81.40 0.00 6.98 0.00 1 1 Wellington 9.09 7.95 9.09 46.59 14.77 12.50
Sudbury 24.71 2.35 21 -18 2.35 16.47 32.94
Algoma 0.00 10.99 14.29 3.30 5.49 65.93 Chapter 5 Species - Environment b
4 Peninsula Lakes
i Lacloche Lakes Wawa Lakes -60-80 1 Wellington Lakes CCA AXlS 1 VI 4, Sudbury Lakes
Algoma Lakes Figure 5.5. Canonical correspondence analysis of lakes in the six study regions using local and regional environmental variables with spatial variation partialled out. Cha~ter5 S~ecies- Environment
2. COMPARISONS OF PROXIMALLY PAIRED RELICTAND SOLUS LAKE REGIONS
CCAs are perfomed to examine pairwise comparisons for the following proximal regions: Wawa and Algoma, LaCloche and Sudbury, and BNC~Peninsula and Wellington. a) PARTITlONING OF FISH SPECIES VARIAT10N
Relict lake regions are found to summarize more species variation from local and regional environmental variables than solus lake regions. Cornbined local and regional environmental variables explain approximately 84%, 57%, and 77% of the variation in the species variation in Wawa, LaCloche and Bruce Peninsula lakes, respectively, and 41 %, 48%, and 52% in Algoma, Sudbury, and Wellington solus lake regions, respectively (Table 5.5). Approximately half of the species variation in al1 relict and solus lake regions can be surnmarized by the spatial location (latitude, longitude and elevation) of the lakes. This indicates that fish cornmunity structure and environmental variables have a fairly similar spatial structuring in both relict and solus lakes. The other half of the explained species variation from environmental variables in both relict and solus lake regions involve a pure species composition - environment relationship without an underlying spatial pattern. The partitioning of species variation into pure environment, environment and spatial, pure spatial and undetermined components is summarized in Figure 5.6.
Table 5.5. Fish species variation partitioning for each of the six study regions using combined local and regional environmental variables.
Function 1 nigoma Bruce Wellington Lakes Lakes P@tlitlih 1 Lâke~ 1) CCA of the species matrix, constrained by the environmental matrix: sum of al1 canonical eigenvalues- (total inertia)
2) CCA of species matrix, constrained by the extended matrix of spatial coordinates: sum of all canonical eigenvalues = Cha~ter5 Species - Environment -- wawa ~lgoma Lacloche Sudbury Bruce La kes Lakes Lakes îakes Peninsula Lakes
3) Like (1), after removing the effect of the spatial matrix: sum of al1 eigenvalues =
the effect of the environmental variables: sum of ail canonical eigenvalues =
a CA of the species matrix =
The percentage of the total variation of the species rnatrix accounted for by each step of the analysis = total inertia ' 1O0 / CA eigenvalue surn
explained variation represented as the percentage of the total variation of the species matrix (3)=(1)+(4)= Percentage of non-spatial environmental variation
structured environmental variation
environmental variables = (4) =
Percentage of unexplained variation Chapter 5 Species - Environment
O Undetermined flSpatial Environment & Spatial mEnvironment
Figure 5.6. Variation partitioning of fish species varîation according to combined local and regional environmental variables for each of the six study regions.
Approximately 12%, 12%. and 13% of the explained species vanation in Wawa. LaCloche and Bruce Peninsula relict lakes respectively, and 3%. 9%. 11% in Algoma. Sudbury, and Wellington solus lakes respectively is spatial variation that is not related to the environmental variables examined in this study (Figure 5.6). This spatial variance in Chapter 5 Species - Environment both relict and solus lake regions may be acting as a descriptor of unrneasured underlying processes driven by other environmental or biotic variables. However, this small amount of species variation accounted for by spatial location along in each of the six study regions suggests that no important spatial-structuring processes have been missed. . .
The amount of undetermined species variation is significantly greater in solus lake regions than in relict lake regions except between Lacloche and Sudbury lakes (Figure 5.6). Although the underlying processes cannot be identified from the available data, the analyses suggest that these unidentified processes are to some degree independent of the measured environmental variables, and their relationship with fish community structure cannot be totally predicted by lake location. This undetermined fish species variation is the result of effects of unmeasured biotic andfor abiotic variables. b) SPECIES COMPOSITÏON - ENVIRONMENT RELATIONSHIP
CCA is performed using combined local and regional environmental variables with spatial variation partialled out for each pair of proximal relict and solus lake regions. The results of the CCAs indicate that relict lake environments consistently surnmarize more variation in species composition than solus lake environments for each pair of proximal relict and solus lake regions (Table 5.6). Moreover, there is a very strong trend in differences in species' niche between relict and solus lakes. The majority of species found in relict lakes are located near the biplot origin (Figures 5.7. 5.9, and 5.1 1). Proximity to. the origin indicates that these species have an overall fairly broad niche for the environmental variables examined in this study. The majority of species found in solus lakes on the other hand, are evenly dispersed from the origin (Figure 5.8, 5.1 0, and 5.12). This indicates that these species have a narrower niche for the local and regional environmental variables examined in this stud y. Cha~ter5 S~ecies- Environment
Table 5.6. Summary of canonical correspondence analyses of local and regional environmental variables with spatial variation partialled out for each of the six study regions.
Wawa Lacloche Sudbury Bruce Wellingtofl Lakes Lakes Lakes Peninsula ' Lakes Lakes Axis 1 Eigenvalue .22
Axis 2 Eigenvalue
Sum of al1 canonical eigenvalues Sum of al1 eigenvalues in CA of species matrix % species variation summarized in biplot Species- environment correlation coefficient for axis
Species- environment .7 1 .74 -62 correlation coefficient for axis 2 Environmental 1. volume 1. area 1. Secchi 1. area 1. maximum 1. area variables ranked 2. Secchi 2. shoreline depth 2. depth 2. maximum from high to low in depth 3. maximum 2. maximum contouring 2. volume depth 3. pH depth depth complexity 3. Secchi 3. order of strength of 4. NPP 4. 3. volume 3. NPP depth conductivity relationship with 5. soi1 contouring 4. 4. maximum 4. soi1 4. soif species drainage complexity contounng depth drainage drainage 6. parent 5. parent complexity 5. forest 5. area 5. shoreline material material 5. pH =ver 6. shoreline 6. pH 7. area 6. soi1 6. 6. shoreline 7. 7. degree 8. maximum drainage conductivity 7. Secchi conductivity da ys depth 7. NPP 7. forest depth 8. 8. Secchi 9. shoreline 8. pH cover 8. soi1 wntouflng depth 10. degree 9. 8. shoreline drainage complexity 9. volume days wnductivity 9. area 9. pH 9. pH 10. forest 11. forest 10. volume 10. NPP 10. parent 10. forest wver wver 11. degree 11. degree material cover 11. contour 12. days da ys 11. 11. NPP complexity contouring 12. forest conductivity complexity cover 12. volume 13. conductivity Chapter 5 Species - Environment
f Area Volume
Shoreline
'O 1O0 Con tour Complexity
CV Soil Drainage & 8 Parent Material AB W Degree Days BD G (186,5) 1 - 9 wA " 1 1 a \: i -100 4 -50 - NPP 'N O 10 'AG
Secchi
Figure 5.7. Canonical conespondence analysis ordination biplot of fish species (points), and local and regional environmental variables (vectors) for Wawa (relict) lakes with spatial variation parlialled out. \ pH Cha~ier5 S~ecies- Environment
Conductivity + AF
Secchi H volume BK Parent Material & -50 Soil Drainage AE0 \ Contour Shoreline ~omplexity100 Max Depth
CCA Axis 1
Figure 5.8. Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environmental variables (vectors) for Algoma (solus) lakes with spatial variation partialled out.
Ctiapter 5 Species - Environment
' Soil Drainage
Secchi Degree Days
Forest /Cover Max Depth Af P
CCA Axis 1 Figure 5.12. Canonical correspondence analysis ordination biplot of fish species (points), and local and regional environmental variables (vectors) for Wellington (solus) lakes wi th spatial variation partialled out.
Conductivity Chapter 5 Species - Environment
Environmental variables are ranked according to the amount of species variation they summarize on the first and second axes of the CCA biplot for each study region (Figures 5.7 to 5.12). The results indicate that local environmental variables are usually the top three environmental variables summanzing the species variation in each of the six regions. Surface area surnmarizes the most species variation of al1 environmental variables examined for solus lakes and is ranked lower for relict lakes. Maximum depth also ranks consistently high for the amount of species variation it summarizes in solus lakes but ranks more variably for relict lakes. Volume and Secchi depth are ranked higher in terms of the species variation they summarize for relict lakes than solus lakes. Surrounding lake forest cover ranks consistently low for relict lakes and has a variable ranking in terms of the species variation it summarizes in solus lakes. The remaining variables lack any discemible pattern within relict and solus lakes in terms of ability to summarize species variation.
C) STA TISTICAL SiGNlFlCANCE OF SPECIES - ENVIRONMENT RELA TlONSHlP
The results of the discriminant analyses of pmxirnally paired relict and solus lake regions indicate that Wawa and Algoma lakes and LaCloche and Sudbury lakes have significantly different species - environment relationships in ternis of combined local and regional environmental variables (P<0.006 and P<0.001 respectively) (Table 5.7). Lakes in the Bruce Peninsula and Wellington regions however are not significantly different in terms of their species composition - environment relationship (Pc0.79). Figures 5.1 3 to 5.1 5 summarize the differences in the species - environment relationship between each of the proximally paired relict and solus lake regions in relation to their lake scores on the first two axes of their CCAs. Table 5.7. Summary of discriminant analysis of the species - environment relationship for each of the paired proximal relict and solus lake regions using lake scores on the fint two wmponents of a canonical correspondence analysis of combined local and regional environmental variables with spatial variation partialled out.
1) Metric ( Wawa and 1 LaCloche and 1 Bruce Peninsula Algoma Lakes Sudbury Lakes and Wellington I I Lakes Eigenvalue 0.08 0.07 0.003
Wilks lambda 0.92 0.94 1.O0
Degrees of freedom 2 2 2 II Significance level I 0.006 I 0.007 I 0.79 Relict Solus Relict Solus Relict Solus Lakes Lakes Lakes Lakes Lakes Lakes Classification results: % Predicted relict lakes 65.12 34.88 56.82 43.18 57.14 42.86
% Predicted solus lakes 32.97 67.03 37.06 62.94 50.00 50.00
Chapter 5 Soecies - Environment
Bruce Peninsula Wellington Lakes Centroid 8 Lakes Centpid
Bruce Peninsula (Relict) Lakes
B Wellington (Solus) Lakes CCA AXlS 1
Figure 5.15. Canonical correspondence analysis of Bruce Peninsula (relict) and Wellington (solus) . lakes using local and regional environmental variables with spatial variation partialled out. Chapter 5 Species - Environment
B. SPECIES SPECIF/C - ENVIRONMENT RELA TIONSHIPS
1. ENVIRONMENTAL GRADIENTS
Length of the environmental gradient for each environmental variable examined in this study is calculated for al1 relict and solus lakes and each of the six study regions. The results indicate that only seven of the 14 environmental variables have suffcient gradients greater than or equal to two standard deviations to use the weighted averaging calibration technique to predict a species' observed tolerance and optimum for each of the environmental variables; surface area, volume, maximum depth, total shoreline perimeter, specific conductivity, surrounding lake net prirnary productivity and surrounding lake forest cover (Table 5.8).
Table 5.8. Summary of standard deviation of environmental gradients for each of the fourteen environmental gradients examined for each study region.
Environmental Variable Lakes Lakes Lakes Lakes Lakes Lakes Peninsula Lakes La kes Surface Area 3.23 3.41 2.16 4.44 4.24 4.90 3.40 4.95
5.97 10.36 4.05 6.72 7.70 5.78 4.82 4.81
3.28 54.58 2.55 1.33 2.64 107.95 1.09 0.58
2.43 18.14 1.76 2.77 3.30 11.04 2.23 2.85 IYPerimeter m Specific Conductivity (umhoslcm @ 25 OC) Annual Numbei ,of Degree Days Net Primary Productivity (g/rnz of carbonlyear) Contouring Complexity (watershed area gradient) High. low and close plots using the maximum value, minimum value and mean of each of the seven acceptable environmental variables are plotted for each pair of proximal regions (Tables Hl to H7 in Appendix H). The results indicate that ail seven environmental gradients overlap within each region. Therefore, it is possible to examine a species' observed optima and tolerances knowing that each species has the same general environmental range within both relict and solus lakes.
2. SPECIES OPTIMUM AND TOLERANCE
Obsenred environmental optimum and tolerance for each of the seven acceptable environmental variables examined in this study are calculated for each species within solus and relict lakes and each of the six study regions using weighted averaging and calibration. These results are divided into WO sections: species cornparisons in proximal relict and solus lake regions, and white sucker and yellow perch cornparisons across al1 six study regions. a) SPECIES COMPARISONS IN PROXIMAL RELICT AND SOLUS LAKE REGIONS
It is not possible to compare every species between proximal relict and solus regions because a given species may not be found in both regions, or it rnay not be found in enough lakes to generate a good estirnate of its observed optimum and tolerance within that region. Therefore, only species found in 10% or more of the lakes within each Chaoter 5 S~ecies- Environment
region are used to examine differences in species' obsewed optima and tolerances between relict and solus lakes. i. WAWA AND ALGOMA LAKES
White sucker (Catostomus commerson~],finescale dace (Phoxinus neogaeus), lake chub (Couesius plumbeus), pearl dace (Margadcus margarita), brook stickleback (Culaea inconstans), yellow perch (Perca flavescens) and lowa darter (Etheostoma exile) are the only species occurring in more than'i 0% of the lakes within both Wawa and Algoma regions. Figures 5.16 to 5.22 summarize these species' observed optima and tolerances for each of the seven environmental gradients examined. Significant differences in observed optimum and tolerance values are found for all eight species for lake volume and surrounding lake net primary productivity between Wawa and Algoma lakes. All eight species have a significantly higher observed optimum for maximum depth in Algoma lakes and a significantly higher observed optimum for surrounding lake net primary productivity in Wawa lakes (Table 5.9). All eight species, except lowa darter, have a significantly higher observed optimum for surrounding lake forest cover in Wawa lakes than in Algoma lakes. AH eight species except for brook stickleback have a significantly higher observed optimum for specific conductivity in Algoma lakes than in Wawa lakes. White sucker, lake chub, pearl dace, yellow perch and lowa darter have a significantly higher observed optimum for surface area in Algoma lakes than in Wawa lakes, whereas northern redbelly dace and brook stickleback have a significantly higher obsewed optimum for surface area in Wawa lakes. Cha~ter5 S~ecies- Environment
Table 5.9. Summary of a wmparison of observed optima and tolerances of seven environmental variables for common species round in bath Wawa and Algoma regions. 'Yes" indimtes a significant difference in observed optimum and tolerance for a species between regions. The bracketed region indicates for which region the observed optimum and tolerance is larger. 'No" indicates no significant difference in obsewed optimum or tolerance between regions for a species.
redbelly (Wawa) (Algorna) (Wawa) (Algoma) (Wawa) (Wawa) dace Finescale no Yes no no YeS YeS Yes dace (Algoma) (Atgoma) (Wawa) (Wawa) Lake chub Yes YeS no no Y= Yes Y=
Pearl dace Yes Yes no no Ye* Yes YeS (Alqoma) (Algoma) (Algoma) (Wawa) (Wawa) Brook Yes y= no no no YeS YeS stickleback (Wawa) (Algoma) (Wawa) (Wawa) Yellow Yes Yes no Yes Yes Yes Yes ~erch (Algoma) (Algoma) (Algoma) (Algoma) (Wawa) (Wawa) Surface Area ( ma )
(36) White sucker Wawa (78) White sucker Algoma
(19) Northem redbelly dace Wawa (15) Northern redbelly dace Algorna
(20) Finescale dace Wawa (23) Finescale dace Algoma
(31 ) Lake chub Wawa (20) Lake chub
(21) Pearl dace Wawa (18) Pearl dace Algoma
(22) Brook stickleback Wawa (15) Brook stickieback Algoma
(1 8) Yeilow perch Wawa (65) Yell0~perch Atgoma
(17) lowa darter Wawa (29) lowa darter Aigoma Volume (m a )
(36) White sucker Wawa (78) White sucker Algoma
(19) Norttiern redbelly dace Wawa (15) Northem redbelly dace
(20) Finescale dace Wawa (23) Finescale dace Algorna
(31 ) Lake chub Wawa (20) Lake chub Algoma
Wawa
( 18) Pearl dace Algoma
(22) Bmok stickleback Wawa (15) Bmk stickleback Algoma
(18) Yellow penh Wawa (65) Yellow penh Algma
(1 7) Iowa darter Wawa (29) Iowa darter Aigoma
Cha~ter5 S~ecies- Environment
Figure 5.19. Summary of cornmon species' observed optima and tolerances for total shoreline perimeter in both Wawa and Algoma Lakes. The number in the bracket before the species name indicates the number of lakes where the species occurred for that region.
Chapter 5 Species - Environment
Species
Figure 5.22. Summary of common species' observed optima and tolerances for surrounding lake forest cover in both Wawa and Atgorna Lakes. The number in the bracket before the species name indicates the number of lakes where the species occurred for that region. Cha~ter5 Species - Environment
ii. LACLOCHE AND SUDBURY LAKES
Cisco (Coregonus aited~],northern pike (Esox lucius), white sucker (Catostomus cornmerson& yellow perch (Perca navescens) and lowa darter (Etheostoma exile) occur in more than 10% of the lakes within both LaCloche and Sudbury regions. Figures 5.23 to 5.29 sumrnarize these species' observed optima and tolerances for each of the seven environmental gradients. All five species have a significantly higher observed optimum for surface area in Sudbury lakes than in LaCloche lakes (Table 5.1 0). As well. al1 five species have a significantly higher observed optimum for surrounding lake net primary productivity in LaCloche lakes than in Sudbury lakes. Cisco. northem pike and white sucker have a significantly higher observed optimum for total shoreline perimeter in Sudbury lakes than in LaCloche lakes. Cisco and northern pike have a significantly higher observed optimum for volume in LaCloche than Sudbury lakes whereas yellow perch and lowa darter have a significantly higher observed optimum for volume in Sudbury lakes. Only northern pike has a significantly higher observed optimum for maximum depth in Sudbury lakes than in LaCloche lakes. No difference is found in observed species' optima for specific conductivity or surrounding lake forest cover in LaCloche and Sudbury lakes. Chapter 5 Species - Environment
Table 5.10. Summary of a cornparison of observed optima and tolerances of seven environmental variables for cornmon species found in both LaCloche and Sudbury regions. 'Yes" indicates a significant differenœ in observed optimum and tolerance for a species between regions. The bracketed region iiidicates for which region the observed optimum and tolerance is larger. 'Non indicates no significant difference in observed optimum or tolerance between regions for a species.
Species CCisco II Northern
(Sudbury) 1 (Sudbury) (Lacloche) Y= yes no no no YeS no (Sudbury) (Sudbury) (Lacloche) Yes Yes no no no YeS no darter (Sudbury) (Sudbury) (Lacloche) Cha~ter5 Species - Environment
S pecies
Figure 5.23. Summary of common species' observed optima and tolerances for surface area in both LaCloche and Sudbury lakes. The nurnber in the bracket before the species name indicates the number of lakes where the species occurred for that region. Volume (rn )
(15) Cisco Lacloche (65) Cisco Sudbury
(18) Northem pike LaCloche (80) Northem pike Sudbury
(23) White sucker Lacloche f (129) White sucker a Sudbury
(36) Yellow perch LaCloche (73) Yellow perch Sudbury
(14) lowa darter LaClocfie (50) lowa darter Sudbury Chapter 5 Species - Environment
Species
Figure 5.25. Summary of mmmon species' observed optima and tolerances for maximum depth in both LaCloche and Sudbury lakes. The number in the bracket before the species name indicates the number of lakes where the species occuned for that region. Chapter 5 Species - Environment
Species
Figure 5.26. Summary of wmmon species' observed optima and tolerances for total shoreline perimeter in both Lacloche and Sudbury lakes. The number in the bracket before the species name indicates the number of lakes where the species occurred for that region. Specific Conductivity (umhos I cm @ 25 O C )
4 h) W P m O O O O O O
(15) Cism LaCloche
(65) Cism Sudbury
(18) NorViem pike LaCloche
(80) Northem pike Sudbury
(23) White sucker f Lacloche O E- (129) White sucker Sudbury
(36) Yeltow perch LaCloche
(73) Yellow perch Sud bu ry
(14) lowa daiter Lacloche
(50) Iowa darter Sudbury Net Prirnary Productivity (g 1 m2 of carbon 1 year)
(15) Cisco LaCloche
(65)Cisco Sudbury
(18) Northem pike LaCloche
(80) Northem pike Sudbury
(23) White sucker LaCloche =cn- - (129) White sucker ip UI Sudbury
(36) Yellow perch LaCloche
(73) Yellow perd Sudbury
(14) Iowa darter LaCloche
(50) Iowa darter Sudbury Chapler 5 Species - Environment
- Specles
Figure 5.29. Summary of cornmon species' observed optima and tolerances for surrounding lake forest cover in both Lacloche and Sudbury lakes. The number in the bracket before the species name indicates the number of lakes where the species occurred for that region. Chapter 5 Species - Environment iii. BRUCE PENINSULA AND WELLINGTON LAKES
Northem pike (Esox lucius), white sucker (Catostomus cornmerson& golden shiner (Notemigonus crysoleucas), fathead rninnow (Pimephales promelas), brown bullhead (Ameiuws nebulosus), pumpkinseed (Lepomis gibbosus), smallmouth bass (Micropterus dolomieu), largernouth bass (Micropterus salmoides), and yellow perch (Perca flavescens) occur in more than 10% of the lakes within both Bruce Peninsula and Wellington regions. Figures 5.30 to 5.36 summarke the observed optima and tolerances of these species for each of the seven environmental gradients. All nine species have a significantly higher observed optima for surface area and total shoreline perimeter in Bruce Peninsula lakes than Wellington lakes (Table 5.1 1). As well, eight of those species (excluding fathead minnow), have a higher observed optima for volume in Bruce Peninsula lakes than do those species in Wellington lakes. Ail nine species, except for brown bullhead, have a significantly higher observed optimum for specific conductivity in Wellington lakes than in Bruce Peninsula lakes. Northern pike and largemouth bass have a significantly higher observed optimum for surrounding lake forest cover in Wellington lakes than in Bruce Peninsula lakes. Fathead minnow has a significantly higher observed maximum depth optimum in Wellington lakes than in Bruce Peninsula lakes. Lastly, brown bullhead has a significantly higher observed optimum for surrounding lake net primary productivity in Bruce Peninsula lakes than in Wellington lakes. Cha~ter5 S~ecies- Environment
Table 5.1 1. Summary of a cornparison of optima and tolerances of seven environmental variables for wmmon species found in both Bruce Peninsula and Wellington regions. "Yesn indicates a significant difference in optimum and tolerance for a species between regions. The bracketed region indicates for which region the optimum and tolerance is larger. 'No" indicates no significant difference in optimum or tolerance between regions for a species. (27) Northem pike Bruce Peninsula ( 13) Northem piks Wellington
(27) White sucker Bruce Peninsula (23) Waesucker Wellington
(25) Golden shiner Bruce Peninsula 11 3) Golden shiner Wellington
(17) Fathead minnow Bruce Peninsula (13) Fathead minnow Wellington
(18) Brown bullhead Bruce Peninsula (17) Brown bullhead f Wellington
(37) Purnpkinseed Bruce Peninsula (25) Pumpkinseed Wellington
(281 Smallmouth bass Bruce Peninsula (21 Smallmouth bass Wellington
(21) Largemouth bass Bniœ Peninsula (32) Largemouth bass Wellington
(50) Yellow perch Bruce Peninsula (31) Yellow perch Wellington Volume (m 3 )
(27)Northem pike Bruce Peninsuia (13) Northem pike Wellington
(27)White sucker Bruce Peninsula (23) White sucker Wellington
(25) Golden shiner BNC~Peninsula (13) Golden shiner Wellington
(17) Fathead minnow Bruce Peninsula (13) Fathead minnow Wellington
(18) Brown bullhead v, Bruce Peninsula E (17) Brown bullhead O Wellington
(37) Pumpkinseed Bruce Peninsula (25) Pumpkinseed Wellington
(28) Smallmouth bass Bruce Peninsula (21 ) Smallmouth bass Wellington
(21) Largemouth bass Bruce Peninsula (32) Largemwlh bass Wellington
(50) Yellow perch Bruce Peninsula
(31) Yellow perch Wellington elnsu!ued =rua sseq wnowews (81) Tatif Shomline Petrimeter (m)
(27) Northem pike Smce Peninsula (13) Northem pike Wellington
(27) White sucker Btuce Peninsula (23) White sucker Wellington
(25) Golden shiner Bruce Peninsula (131 Golden shiner Wellington
(17) Fathead minnaw Bruce Peninsula (13) Fathead rninnow Wellington
(18) Brown bullhead Bruce Peninsula H (17) Bmwn bdihead g Wellington
(37) Pumpkinseed Bruce Peninsula (25) Pumpkinseed Wellington
(28) Smallmwth bass Bruce Peninsula (21) SmallmouUi bass Wellington
(21) Largemouth bass Bruce Peninsula (32) Largemouth bass Wellington
(50) Yellow perch Bruce Peninsula (3 t ) Yellw parch Wellington (27) Norüiem pike Bruce Peninsula (13) Northern pike Wellington
(27) White sucker Bruce Peninsula (23) White sucker Wellington
(25) Gotden shiner Bwce Peninsula (13) Golden shiner Wellington
(17) Fathead minnow Bruce Peninsula (1 3) Fauiead minnow Wellington
(18) Brown bullhead w Bruce Peninsula (17) Bmbullhead s Wellington
(37) Pumpkinseed Bruce Peninsula (25) Pumpkinseed Wellington
(28) Smallmouth bass Bruce Peninsula (21) Smallmouth bass Wellington
(21 ) Largemouth bass Bruce Peninsula (32) brgemwth bass Wellington
(50)Yellw Penh Bruce Peninsula (3 1 ) Yellow perch Wellington Cha~ter5 S~ecies- Environment
Spec ies
Figure 5.35. Summary of common species' obseived optima and tolerances for net prirnary productivity in both Bruce Peninsula and Wellington lakes. The number in the bracket before the species name indicates the number of lakes where the species occurred for that region.
Chapter 5 Species - Environment
b) WHITE SUCKER AND YELLOW PERCH COMPARISONS
White sucker (Catostomus commersoni) and yellow perch (Perca flavescens) are the only species that are commonly found throughout al1 six study regions. These species are therefore used to examine differences in a species' observed environmental optimum and tolerance throughout al1 of the study regions. Figure 5.37 to 5.43 summarize the differences in observed environmental optimum and tolerance for the white sucker and yellow perch in al1 six study regions for each of the seven environmental variables. White sucker and yeltow perch are found to share similar trends in observed optima and tolerances throughout the regions. The observed optimum for volume for both the white sucker and yellow perch is found to be significantly higher in the Shield regions than in the Lowland regions. No latitudinal gradients in observed optima are found for either the white sucker or yellow perch for any of the seven environmental gradients examined between the regions. However, both the white sucker and yellow perch's observed optima for surface area, volume and maximum depth increase with latitude in relict regions. The white sucker's observed optimum for volume increases with latitude in solus regions. Observed optima for both white sucker and yellow perch Vary widely between regions for surface area, volume, maximum depth, pH, and specific conductivity. Overall, there are relict and solus lake differences in both the white sucker and yellow perch's observed optima for surface area, volume and total shoreline perimeter in the Shield and Lowlands.
Cornparisons of observed environmental optima and tolerances for white sucker and yellow perch for each of the seven environmental variables are examined in proximally paired relict and solus lake regions. The results indicate that both white sucker and yellow perch have significantly different observed optima and tolerances for environmental variables between proximal relict and solus lake regions (Table 5.12). Cha~ter5 S~ecies- Environment
Table 5.12. Summary of a cornparison of observed optima and tolerances for the white sucker and yellow perch between proximal regions for seven environmental variables. "Yes" indicates a significant difference in observed optimum and tolerance between regions and the bracketed regions indicates for which region the observed optimum and tolerance is targer. White sucker results are listed on top followed by yellow perch results if different.
Ënviknmental Wawa and Algoma LaCloche and Bruce Peninsuia Variable Sudbury and Wellington Surface area (m2) yes (Wawa) yes (Sudbury) yes (Bruce Peninsula) Volume (m3) yes (Algoma) no yes (Bruce yes (Sudbury) Peninsula) Maximum depth (m) no no no
Total shoreline yes (Algoma) yes (Sudbury) no perimeter (m) S pecific conductivity (urnhoslcm@ 25OC) yes (Alqorna) no yes (Wellington) Net primary productivity (glm2of yes (Wawa) yes (Lacloche) no
L carbon/vear) Surrounding lake forest cover (density no no no aradient) Chapter 5 Species - Eiivironment
Relict Solus Relict Solus White Sucker Yellow Perch
Figure 5.37. Summary of white sucker and yellow perch's observed optima and tolerances for surface area within each of the six study regions.
Cha~ter5 S~ecies- Environment
Reiict Solus Relict Solus White Sucker Yellow Perch
Figure 5.39. Summary of white sucker and yellow perch's observed optima and tolerances for maximum depth within each of the six study regions. Ctiapter 5 Species - Environment
Relict Sotus Relict Sotus White Sucker Yellow Perch
Figure 5.40. Summary of white sucker and yellow perch's observed optima and tolerances for total shoreline perimeler within each of the six study regions. Chapter 5 Species - Environment
Relict Solus Relict Solus White Sucker Yellow Perch
Figure 5.41. Summary of white sucker and yellow perch's observed optima and tolerances for specific conductivity within each of the six study regions. Chapter 5 Species - Environment
IJ Ii Relict Solus Relict Solus White Sucker Yellow Perch
Figure 5.42. Summary of white sucker and yellow perch's observed optima and tolerances for net primary productivity within each of the six study regions.
Cha~ter5 S~ecies- Environment
IV. DISCUSSION
A. PARllTIONING OF SPECIES VARIA TlON
1. SPECIES VARIATION EXPLAINED BY ENVIRONlkIENTAL VARIABLES lt is expected that relict lakes share a more similar environment than solus lakes since they originated from a cornmon ancestral waterbody. It is also expected that species in these relict lakes, which were derived from the sarne ancestral species pool, have a higher association with their environment than lakes formed in isolation with random species colonization driving cornmunity structure. For these reasons, it is expected that the environment in relict lakes should explain more species variation than the environment in solus lakes. The results of this study support these predictions. The local and regional environment in relict lakes is found to explain more species variation than solus lakes across al1 proximal relict and solus lake region cornparisons.
2. UNDETERMINED SPECIES VARIA TlON
Solus lakes. across al1 proximal cornparisons, consistently have a much higher amount of undetermined species variation. This indicates that there are unidentified processes driving species composition which are not examined in this study. These processes are to some degree independent of measured environmental variables, and their relationship with fish community structure cannot be totally predicted by lake location. These unexplainect processes must also be affecting solus lakes to a greater extent than relict lakes. This would therefore exclude such factors as anthropogenic stresses, stochastic events such as epizootics. and I or sampling error. It is most probable that this undetermined variation in species composition is attributable to the process of species colonization into solus lakes.
Solus lakes. which are forrned in isolation, have never shared a common species pool with another water body. Solus lakes are also generally located on areas of land that are higher in elevation than areas of land that were inundated with proglacial waterbodies which later formed relict lakes. Colonization is therefore the primary process driving species composition in solus lakes. Solus lakes with outflows are most likely to have Chapter 5 Species - Environment been colonized by the upstream rnovernent of fish from relict lakes or by catastrophic flooding .
B. SPECIES COMPOSITION - ENVIRONMENT RELATIONSHIP
Solus lakes were formed in isolation from other waterbodies. They were also formed at a higher elevation than relict lakes. For these reasons, solus lakes are predicted to be colonized by fewer individuals of a species than relict lakes. It is therefore plausible that founder effects may be prominent in'solus lakes based on their isolation. If founder effects exist within solus lakes, fish populations in solus takes are expected to have a lower genetic diversity or be more genetically isolated cornpared to related populations in relict lakes. The reduced gene pool in solus lakes should reduce the number of genotypes in the population. This reduction in genotype should produce a population with a sornewhat different ecological niche Man from the original population from where it originated. It is also predicted that populations of the same species within different solus lakes have evolved somewhat different niches based on the isolation of solus lakes from other bodies of water. This is the basis of evolutionary change.
The results of this study very strongly concur with the above predictions. Species present in solus lake regions across al1 proximal relict and solus lake region comparisons consistently have narrower niches for the environmental variables examined in this study than species in relict lake regions. Species in relict regions are found to have a fairly similar broad niche for the environmental variables examined. This strongly supports the notion that species in relict lakes shared a common ancestral waterbody and have retained the environmental characteristics and species genetic diversity from that waterbody. Constant environments should be typified by strongly interactive species limited by stable resources.
The results of an examination of species specific observed optima and tolerances across a range of environmental gradients in both relict and solus lake regions also concur with the prediction of a founder effect in solus lakes. Signifiant differences are found in observed species' optima and tolerances between proximal refict and solus lakes. Especially strong relict and solus lake differences are found in white sucker (Catostomus commersonr) and yellow perch (Perca flavescens) observed optima and tolerances Chapter 5 Species - Environment
across the six study regions. Observed species' tolerance to environmental gradients in solus lakes is found to be generally greater than in relict lakes. This further agrees with the founder effect hypothesis since species should develop specialized niches and broader tolerances in individually isolated solus lakes on a regional basis than species in relict lakes which were derived from the same ancestral species pool. All of the environmental gradients were checked for overlap. Therefore these striking differences in an observed species' optima and tolerances for environmental gradients benNeen relict and solus lakes cannot be attributed to non-overlapping environmental gradients.
C. REGIONAL ENVIRONMENTAL VARIABLES
Temperature is the only regional environmental variable that has received any significant attention regarding species - environment relationships in lakes in North Arnerica (e-g., Hokanson 1977; Legendre and Legendre 1984; Mandrak 1994; lnskip and Magnuson 1986; McAllister et al. 1986; Rahel 1986; Meisner et al. 1987). Seven regional environmental variables (annual number of degree days, mean annual precipitation, surrounding lake net primary productivity, surrounding lake forest cover, surrounding lake soi1 drainage, parent material, and contouring complexity) are examined in this study in relation to their ability to explain fish species composition in lakes. These regional environmental variables are found to be strong predictors of fish species composition, especially in combined relict and combined solus lakes. This is logical considering that in a large scale study encompassing al1 six regions, regional processes should become more predominant in terrns of their variation. However, their ability to explain species variation is also found at the regional level within each of the six study regions. Regional environmental variables are shown to rank no lower than fourth of fourteen environmental variables in terms of their ability to explain species variation within a region. This is a very surprising result since traditionally only local environmental variables, specifically lake morphology and water chemistry, have been used to predict fish species composition (e.g., Beamish and Harvey 1972, Harvey 1978; Rahel 1982; Matuszek and Beggs 1988; Minns 1989). CONCLUSIONS
The results of this study indicate that: Proximal relict and solus lake regions have significantly different species composition -environment relationships. This conclusion reinforces sirnilar results produced in Chapters 3 and 4. Chapter 3 concluded that relict and solus lakes have significantly different local and regional environments. Chapter 4 concluded that relict and solus lakes have significantly different species composition and structure. It is not surprising given these conclusions, and from the differences in the formation of relict and solus lakes, that these lakes have significant differences in species composition - environment relationships,
Species found in solus lake regions have a narrower niche than those found in relict lake regions, which reinforces the founder effect in solus lakes,
Relict lake environments summarize more species variation than solus lake environments,
There is more undetermined species variation in solus lakes which spatial location and local and regional environmental variables cannot account for than in relict lakes. This undetermined species variation is most probably attributable to colonization processes in solus lakes,
Common species have very different observed optima and tolerances for the same environmental gradient in relict and solus lakes,
Regional environmental variables are found to play a prominent role in explaining fish species variation in lakes and should be examined more widely,
A new statistical method is defined for testing for significant differences in species - environment relationships among different lakes using lake site scores of a CCA of environmental variables with spatial variation partialled out. Overall Conclusions
6 Conclusions and Recommendations
i. RELICTAND SOLUS LAKE THEORY
Two new terms have been created in this thesis which describe lakes based on their formation; "solusnand "relict" lakes. These constructs of relict and solus lakes should be applicable to lake formation throughout the world. A relict lake ("relict" meaning "remaining" in Greek). is defined as a lake that was once part of a large waterbody which has since receded to forrn smaller independent lakes. A solus lake ("solus" meaning "isolated" in Greek), is defined as a lake formed in isolation and one which was never initially a part of a larger water system. These lakes never shared a common species pool with other bodies of water.
Several researchers have investigated the notion of lakes as aquatic islands within a terrestrial sea (e-g.. Barbour and Brown 1974; Magnuson 1976; Browne 1981; Magnuson 1988). Their research has concluded that lakes are small, relatively isolated environments in which species richness should be determined by extinction and colonization events in a rnanner analogous to terrestrial islands. This thesis has taken this analogy of "lakes as islandsnone step further and compared community structure and environmental characteristics of relict and solus inland lakes within the Great Lakes - St. Lawrence basin directly with landbridge and oceanic islands, respectively.
A. ENVIRONMENTAL CHARACTERISTICS OF RELICT AND SOLUS LAKES
Based on their formation history, it is expected that relict and solus lakes should have different regional and water chernistry characteristics. Relict lakes and their surrounding watersheds are located on glaciolacustrine deposits, whereas solus lakes and their surrounding watersheds are not. Glaciolacustrine deposits are sedirnents that have been camed by glacier meltwater and subsequently deposited in proglacial lakes. These deposits are composed of fine material which creates low soi1 drainage properties within Overall Conclusions the watersheds. These deposits are also rich in nutrients and minerals. For these reasons, relict lake regions would be expected to have higher productivity and lower soi1 drainage properties associated with the presence of fine, nutrient rich soi1 as compared to solus lakes.
The results of this study show that the environmental characteristics of a lake are strongly related to its historical formation. Relict and solus lakes have significantly different local and regional environments. Relict lake regions have a significantly higher lake-surrounding forest cover, surrounding forest net primary productivity. and lower soi1 drainage properties than solus lake regions. On the Precambrian Shield, relict lakes have a significantly lower pH and a higher specific conductivity than solus lakes. 60th lake types share a similar lake morphology. This similarity in lake morphology is probably related to the common geological conditions frorn which they were formed. The majority of the lakes within these regions were formed from the excavation of existing fractures and shatter belts in the bedrock by glacial scour. On the Lowlands, relict and solus lakes share a similar water chemistry but have significantly different lake morphologies. This suggests that physiographic properties such as underlying bedrock are driving processes determining water chemistry within these regions. It is not surprising that Bruce Peninsula and Wellington lakes have different lake morphologies because Bruce Peninsula lakes were mostly formed by the solution of their underlying limestone bedrock. Wellington takes on the other hand are predorninately kettle lakes formed from the deposition of blocks of ice form the last glacial recession which rnelted to form isolated basins.
B. SPECIES RICHNESS IN RELICT AND SOLUS LAKES tt would be expected that relict lakes should contain more species than solus lakes. Relict lakes are formed from a large ancestral waterbody with a large species pool. Every species within the ancestral waterbody is assumed to have had an equal opportunity of colonizing each relict lake thereby foming relict lakes supersaturated with species. It is hypothesized that over time the species composition in these relict lakes is being driven prirnarily by extinction. Solus lakes, conversely, formed as isolated bodies of water. They never shared a common species pool with other bodies of water. Therefore. colonization is expected to be the prirnary process driving species Overall Conclusions
composition in solus lakes. Solus lakes are generally located at a higher elevation than proximal relict lakes. Naturaf colonization into these isolated solus lakes would therefore be expected to occur through either upstream colonization of fish from lower elevation relict lakes into the oufflow of solus Iakes or through catastrophic flooding events. For these reasons, solus lakes are predicted to be both species-poor and colonized by fewer individuals of a species in relation to relict lakes.
The results of this study show that fish species composition within a lake is strongly related to the historical formation of a lake. Across al1 proximally paired relict and solus lake regions, regional species richness was determined to be higher for relict lakes than solus lakes based on fish species distribution data by Mandrak and Crossrnan (1992a); the most complete fish species distribution guide for Ontario to date. As well, an examination of species-area curves for each of the study regions indicates that there is a trend for relict lakes to contain a greater number of species per unit area (lake size) than solus lakes. Therefore, the differences in species richness between relict and solus lakes based on extinction and colonization processes are very similar to the species richness patterns and extinction and colonization processes found within landbridge and oceanic islands respectively.
C. SPECIES COMPOSITION IN RELICT AND SOLUS LAKES
Historical factors such as invasion order and invasion rate (Robinson and Dickerson 1987; Robinson and Edgemon 1988) are also expected to be important factors in determining-speciescomposition in solus lakes. If early colonists were able to pre-empt the habitat and prevent later invasion, then both the random order of species arriva1 and the number of colonizations were important in ensuring that each colonizing species was established somewhere in the system. Over time, a variety of species may have been the first to colonize different solus lakes thereby negating this priority effect on a regional basis. For these reasons, solus lakes are expected to show a wider variation in community structure compared to proximal relict lake regions.
The results of this study corroborate the prediction that isolated lakes have a greater variation in their fish communities than lakes which evolved from a common species pool. Correspondence analyses perfomed on proximal relict and solus regions indimte Overall Conclusions that solus lakes are in fact more highly varied in their species composition than relict lakes.
O. SPECIES - ENVIRONMENT RELATIONSHIPS IN RELICT AND SOLUS LAKES
It is possible that founder effects may be prominent in solus Iakes based on their isolated formation. Fish populations in solus lakes would therefore be expected to have a lower genetic diversity or be more genetically isolated compared to related populations in relict lakes. The reduced gene pool in solus lakes should reduce the number of genotypes in the population. This reduction in genotype should produce a population with a somewhat different ecological niche than that of the original population from which it originated. It is also expected that populations of the same species within different solus lakes would have evolved somewhat different specialized niches based on the isolation of solus lakes from other bodies of water.
The results of this study very strongly corroborate with the above predictions. Relict and solus lake regions were found to have significantly different species composition - environment relationships. Species present in solus lake regions across al1 proximally paired relict and solus lake regions consistently had a narrower niche for the environmental variables examined in this study than species in relict lake regions. Species in relict regions were found to have a broad niche for the environmental variables examined. This strongly supports the notion that species in relict lakes shared a common ancestral waterbody and have retained the environmental characteristics and species genetic diversity from that waterbody. Relict lake environrnents were found to summarize more species variation than solus lake environments which reinforces the notion that relict lakes evolved from a common ancestral waterbody. Constant environments should be typified by strongly interactive species limited by stable resources .
The results of an examination of species specific observed optima and tolerances across a range of environmental gradients in both relict and solus lake regions also corroborated the prediction of the founder effect in solus lakes. Significant differences were found in species' obsewed optima and tolerances for similar environmental gradients in proximal relict and solus lakes. Especially strong relict and solus lake Overall Conclusions
differences were found in white sucker (Catostomus commersonr) and yellow perch's (Perca flavescens) observed environmental optima and tolerances across the six study regions. Observed species' tolerances to environmental gradients in solus lakes were found to be generally greater than those in relict lakes. This further supports the founder effect hypothesis slnce species should develop specialized niches and broader observed tolerances in individually isolated solus lakes on a regional basis than species in relict lakes which were derived from the sarne ancestral species pool.
Regional environmental variables examined in this study were found to be strong predictors of fish species composition, especially in cornbined relict and combined solus lakes. This is logical considering that in a large scale study encompassing al1 six regions, regional processes should become more predominant in ternis of their variation. However, their ability to explain species variation was also found at the regional level within each of the six study regions. Regional environmental variables were shown to rank no lower than fourth of fourteen environmental variables in terms of their ability to explain species variation within a region. This was a very surprising result since traditionally only local environmental variables, specifically lake morphology and water chemistry have been used to predict fish species composition. Therefore, regional environmental variables should be examined more widely for the contribution they may make in explaining fish species variation in lakes.
E. COMPARISON OF RELICTAND SOLUS LAKES WITH LANDBRIDGE AND OCEANIC ISLANDS
Striking similarities were found between relict and solus lakes and landbridge and oceanic islands, respectively, regarding historical formation, extinction and coionization potential, and fish community structure as summarized in Table 6.1. Overall Conclusions
Table 6.1 A comparison of relict and solus lakes with landbridge and oœanic islands.
species from common ancestral species from common ancestral water body species pool J mainland species pool higher species richness than higher species richness than solus lakes J oceanic islands species composition driven species composition driven primarily through extinction J primarily through extinction colonization rates rnay not colonization rates may not balance rates of extinction but balance rates of extinction but they may be high enough J they may be high enough especially for highly mobile especially for highly mobile species to significantly influence species to significantly influence s~eciesdistribution s~eciesdistribution - -- II O approxim$ely the 1 younger than oceanic islands sOIUS lakes X l C haracteristics of Characteristics of H Solus Lakes I l Oceanic Islands never shared a cornrnon species never shared an ancestral pool with an ancestral water J common species pool with body mainland isolated isolated O species poor relative to proximal 1 species poor 11 relict lakes species composition driven species composition driven primarily through colonization J primarily through colonization supports a wide range of species support only highly vagile species X a approximately the same age as older than landbridge islands relict iakes X 1 populations may have a different may have higher rates of genetic structure than in relict endemism than landbridge islands
This thesis represents an innovative way of examining fish species composition - environmenbl interactions for inland lakes based on historical lake formation. It has been demonstrated that historical lake formation is responsible for significant differences in fish community structure. environment and species - environment relationships Overall Conclusions
between relict and solus lakes. This relict and solus lake theory may be useful in other ecological studies to help explain fish communities in lake systems in other parts of the world.
II, IMPLICATIONS / RECOMMENDA TIONS
A. FISHERIES CONSERVATION IN ONTARIO: A PROPOSED MANAGEMENT PLAN FOR UNIQUE ASSEMBLAGES IN ALGOMA, SUDBURY AND WELLINGTON SOLUS LAKE REGIONS
The land area within which solus lakes exist, encornpasses less than five percent of the total land area of Ontario. The results of this study strongly indicate that solus lakes and their surrounding watenheds represent an ecologically distinct aquatic system within Ontario containing unique environrnents and fish species assemblages. Natural geographically and potentially genetically isolated fish populations in solus lakes, are of particular interest. as they have the greatest potential for adaptive genetic change since they represent populations that are reproductively isolated from other conspecific populations units from cornmon relict lakes. These solus lake fish populations represent evolutionarily significant units (Waples 1991) which are important components in the evolutionary legacy of their species. The combined rarity of these solus lakes with the uniqueness of their fish species assemblages and environments present a strong case for the conservation of Algoma, Sudbury. and Wellington regions as Areas of Natural and Scientific lnterest within Ontario.
The designation of a region as an Area of Natural and Scientfic lnterest (ANSI) by the Ontario Ministry of Natural Resources is based on the earth science and life science features of the region. The principle of earth science features is to protect regions which illustrate Ontario's geological and geomorphological history. Life science representation is concerned with the protection of areas which characterize distinctive environments containing relatively undisturbed or unique local biological communities.
These regions should be considered for a watershed management plan to aid in the protection of these areas as ANSls. The scale of management plan at the watershed Overall Conclusions level is appropriate for a number of reasons. Lakes are but a small part of the total watershed system. The physical, chemical, and biotic properües of a fake are directly influenced by changes throughout its watershed. Water continuously moves through the watershed and influences nurnerous life cycles and physical processes throughout its cycle. An action or change in one location within a watenhed has potential implications for many other natural features and processes that are linked by the interactive movement of surface and ground water. Also. water movement does not stop at political boundaries so that watershed and subwatersheds may encompass al1 or part of several municipalities.
A management plan should be devised to manage the water, landlwater interactions, aquatic life and aquatic resources within these solus lake watersheds in order to protect the health of these unique ecosystems as land use changes. The plan should therefore provide an image of how the watersheds should look and function and what areas are appropriate for protection and rehabilitation.
The province's steady economic, urban and industrial growth over the past decades has brought with it a wide range of water quality and quantity concerns, demands and conflicts, which are more complex than ever before. The watershed approach to ecosystem conservation and management should be based on the recognition that ecosystems have limits to stresses which can be accommodated before the ecosystems are irreversibly degraded or destroyed. Furthermore, this approach should require that ecological goals be treated equally with and be considered at the same time as economic and social goals.
The primary goal of the watershed management plan should be to designate Algorna, Sudbury and Wellington solus lake regions within Ontario as Areas of Natural and Scientific lnterest (ANSI) based on the unique ecology of their systems. This necessitates the preservation of these areas through the initiation of secundary goals of protecting and restoring fish habitat within these three recommended ANSls. Ali land use and natural resource management activities within these recommended ANSls should therefore maintain the watenhed systems in as naturally functional and as undisturbed a state as possible. These regions should specifically restrict species introductions. Overall Conclusions
In conjunction with these ecosystem level goals there should be two genetic conservation goals for solus lake populations: 1) maintenance of viable populations in the short term (extinction avoidance), and 2) maintenance of the ability of the biota to continue adaptive genetic change. References
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Lake Formations Throughout the World and Their Classification as Either Relict or Solus I. RELICT AND SOLUS LAKES THROUGHOUT THE WORLD
A. LAKES FORMED FROM MOVEMENTS OF THE EARfH'S CRUST
Movements such as unwarping or faulting of the earth's crust have created basins known as tectonic basins. These basins may contain solus lakes. These solus lakes formed as single lakes occupying crustal rifts. These lakes were neither a part of a larger waterbody nor shared a cornmon species pool with any other lake. The great lakes of eastem Africa are probably the rnost spectacular example of solus lakes formed from major rnovernents in the earth's crust. The faults which run north - south through Africa are a series of splits in the earth's crust which in places have filled with water foning some of the world's largest and deepest solus lakes (Burgis and Morris 1987). The Eastern Rift extends as far north as Israel, where it contains Lake Tiberias and the Dead Sea. In Ethiopia, parts of the Rift are occupied by Lakes Zwai, Abiata, Chamo and several other Ethiopian Rift Lakes.
To the west lies another split in the African continent, the Western Rift. The Western Rift contains three large tectonic solus lakes; Lakes Tanganyika, Edward and Mobuto Sese Seko. Lake Tanganyika is the second deepest lake in the world, and is the third oldest lake, preceded only by Lake Baikal and the Caspian Sea which were both forrned in the pre-Pliocene (Cohen et al. 1993; Klerkx et al. 1998).
At the junction of the Eastern and Western rifts, the northern end of Lake Malawi lies in a separate Rift. lt is also a very deep lake. Although younger than Lake Tanganyika, it has been isolated from the other water bodies long enough to develop a very diverse fish fauna in which the majonty of the species are endemic (Martens et al. 1994; Ring and Betzler 1995).
Lake Victoria, one of the largest lakes in the world, lies on the central plateau of the Western Rift in Africa. It is a huge, relatively shallow solus lake lying in a saucer-shaped basin. It was forrned when the western edge of the Eastern Rift and the eastem edge of the Westem Rift were gradually pushed upwards as the Rift formed. The land between the Rifts bent to form the basin in which the lake now lies (Rach 1992). Lake Victoria is 750.000 yean old but was probably completely desiccated 12,400 years ago (Johnson Appendix A
et al. 1996). It is known for its enormous fish diversity of endemic cichlid populations (e.g., Dont 1990; Ribbink 1993; Lowe 1994).
Lake Baikal, USSR, is both the deepest and oldest lake in the world. It is also an example of a solus tectonic lake. Lake Baikal is a long and relatively narrow lake 674 m in length. with a maximum depth of 1741m (Hutchinson 1957). Its southem basin is believed to have originated in the Paleocene or the late Cretaceous. However, most of the movements that produced the lake basin as it now exists, occurred during the Pliocene (Artyushkov et al. 1990).
B. LAKES FORMED FROM VOLCANIC ACTIVITY
Various kinds of lake basins such as calderas and maars are formed from volcanic activity. These lakes are all considered examples of solus lakes because they are completely isolated from al1 other waterbodies. Volcanic lakes are found in Iceland, the Eifel district of Gennany, the Auvergne district of France. the Roman Campagna and the Phlegrean Fields in Italy, most of lndonesia northward through the Phillipines into Japan, parts of central Africa, New Zealand and parts of Australia, the northwestern United States. and much of Central America and the Andes (Hutchinson 1957).
7. CALDERAS
Caldera lake basins are located at the top of a volcano. They are formed by the collapse of the volcanic peak from the discharging of magma and other material from its core from an explosive eruption (Lanon 1989). Crater Lake in Oregon, United States is an example of a solus lake in a caldera basin. It is the second deepest lake (608.4m) in North America next to Great Slave Lake in Canada (Allen 1984). The basin of this lake was forrned by the collapse of the central part of a high volcanic peak, now called Mount Mazarna. after an enonous eruption about 6.500 years ago (Allen 1984). Crater Lake has an approxirnately circular form and is surrounded by a rirn that rises about 600m above its water level (Wolcott 1964).
Other caldera solus lakes surrounded by high rims are found in Japan. Lake Tazawko, in Honsyu. has an area 25.64 km2 and a depth of 425m. It is sumunded by a rim which spans the lake approximately 250m above its water's surface (Hutchinson 1957). Lake Masyukois, in southwestern Hokkaido, has an area of 19.77 km2 , and a maximum depth of 21 1.5m. It has a nearly vertical rim king almost 300m above the level of the lake (Hutchinson 1957).
2. MAARS
A considerable number of solus iake basins are formed by volcanic explosions below the earth's surface which produce low crater rims at the surface of the volcano. These low crater rims are built on fragments of rock with little or no volcanic material. If these embryonic volcanoes do not evolve further they often fiIl with water and become small deep solus lakes. There are a number of excellent examples of such lakes in the Eifel district of Germany. where they are locally termed maars (Lorenz 1974). In general, maar lakes are characteristically small in surface area and very deep. The deepest maar lake in Germany is the Pulvermaar which is 74m deep but has a surface area of only 0.35 km2. The maan of the Eifel district of Germany orîginated during the last stages of the Pleistocene glaciation (Lorenz 1974).
In France, several exarnples of these maar lakes are found in the Auvergne District. Of these. the Lac d'lssarles is the deepest (108.6m) and has a surface area of only 0.92km2 (Scrope 1858: Hutchinson 1957; Delebecque and Ritter 1892: Hutchinson 1957) again demonstrating the srnall, deep characteristics of this type of lake.
Several maar lakes occur around the base of Mount Ruwenzori in central Africa (Willis 1936: Hutchinson 1957). There are more than eighty small solus maar lakes there of various depths. ln some of these maar lakes, the rims have been eroded so that their volcanic origins are less obvious. However, they are thought to have been formed during a period of intense volcanic activity approximately 8,000 to 10.000 yean ago (Burgis and Morris 1987).
C. LAKES FORMED FROM METEOR IMPACTS
The rarest formation of a lake basin is through the impact of a meteorite forming a crater on the earth's surface. Only five crater lakes are known to exist; Kaalijarv on the Island Appendix A
of Osel (Saaremaa) in the Baltic (Spencer 1933: Hutchinson 1957). Laguna Negra Campo del Ciele in the Gran Chaco of Argentina (Nagera 1926: Hutchinson 1957). Lake Bosumhnri in Ghana (Turner et al. 1996), Lonar Lake in western lndia (Mishra 1987), and Ungava Lake in Ungava, Quebec (Meen 1950,1952: Hutchinson 1957). Ungava Lake occupies the largest and most well-established terrestrial meteonte crater in the world. The diameter of the top of the crater wail is approxirnately 3350m. The crater has depth of about 41 0m. Ungava lake, occupying the crater, has a maximum depth of 251 m. It is thought to have been fomed in the late Pleistocene (Meen 1950, 1952; Hutchinson 1957).
D. LAKES FORMED BY LANOSLIES
Landslides of rockfalls or mudfiows may fil1 the floors of valleys. In doing so, landslides may temporarily dam streams, forming mostly transient lakes behind the landslide dam. Such lakes are able to penist if the dam is high enough so that water cannot discharge over it, and if these lakes develop an effluent that does not follow the original valley. Sufficiently large slides are most likely to occur in mountain valleys, where streams erode relatively soft rock that is overlaid by more resistant material. The rock may become undercut, and the resultant lakes are relict lakes. Several lakes have been produced by rockslides originating in this way in the Warner Range of northeastern California. Examples of these relict lakes include Clear Lake, Blue Lake, Pit Lake, and Lost Lake (Russell 1927: Hutchinson 1957). This area is one of the few locations in the world where a lake district is characterized by this type of relict lake basin. Hebgen Lake, Montana, west of Yellowstone National Park, is another example of a landslide- dammed lake that has persisted for many years (Winter and Woo 1990). Lake Cresent in Olympic National Park in Clallam County, Washington State is also an example of a landslide lake (Brown et al. 1960).
Several good examples of rockslide dams are also found in Europe. Castiglioni (1984) notes several exarnples from the eastern Alps; arnong them the Lago di Alleghe in the Agordo Valley. Lake Belluno, is noteworthy as being forrned relatively recently, and the much older Lago di Molveno, Trentino, for its considerable depth of 118m. Apoendix A
E. SOLUTION LAKES
The solution of soluble rock by percolating water may produce cavities. In limestone districts, lake basins are often formed from the local solution of limestone from precipitation containing carbon dioxide. These solution lakes are examples of solus lakes. Since the most prominent formation of such basins occun in the Karst region just inland from the Dalmatian Coast of the Adriatic, the production of solution basins is frequently terrned a karstic phenomenon (Hutchinson 1957). The most prominent groups of solution basins in North America occur in the state of Florida (Puri and Vernon 1960).
A large number of solution lakes occur in the calcareous parts of the Alps. These basins differ frorn those in the Florida region in that they have had a considerable amount of glacial restructuring. The deepest of the solution lakes of the Alps is the Lunenee in the Rhatikon, with a maximum depth of 102 m (Castiglioni 1984).
F. LAKES DUE TO FLUVlATILEACTION
1. PLUNGE-POOL LAKES
A waterfall has the corrosive power to excavate a basin below the fall. If the river is diverted, the rock basin left at the base of the fall may contain a lake. These plunge-pool lakes are exarnples of relict lakes. The most impressive of such plunge-pool lakes are lakes which were formed from the former course of the Columbia River that now forms the Grand Coulee in the state of Washington. This gorge was formed at a tirne when the Columbia River was blocked by ice during last glacial maximum in the region. The most prominent plunge pools, Falls Lake and Castle Lake lie at the bottorn of dry escarpments that were formerly large waterfalls at the head of the Lower Coulee (Wolcott 1965).
2. LEVEE LAKES
Where a tributary reaches its sink. which may be an ocean or a large lake. the sediment of the tributary is abruptly deposited due to the sudden decrease in current velocity. This sediment deposition forms a bar. Water tends to flow around the bar, increasing its ends in the fom of a U with its open end directed towards the large lake or sea. A series of such U-shaped banks are deposited, each corresponding to the mouth of one tributary. The flow around these new bars will cause the deposition of sediment which may ctose the previously open ends of the first series of banks. Each bank will therefore be converted into a basin as the new set of bars develop towards the large lake or sea. These lake basins are an example of relict lakes. On the Mississippi Delta, Lake Pontchartrain is an example of a lake held between the levee of an outgrown tributary, Bayou Sauvage, and the higher land north of the floodplain of the Mississippi. Other smaller lakes such as Lake St. Catherine in the same region, are entirely enclosed by levee walls of small tributaries (Smith 1996).
3. OXBO W LAKES
Several types of floodplain lakes are formed in the lower parts of large river valleys, especially those in which the main stream runs in a wide flood plain. There, lakes are formed from local erosion and deposition that occurs in such flood plains. They are al1 examples of relict lakes. Oxbow lakes are usually formed from a river rneandering in an easily eroded flood plain. The river meanders may develop into loops which may be cut off or isolated from the river by silting. The enclosed loop over time fills in to forrn an oxbow lake. Oxbow lakes are an example of relict lakes. They are extremely common in the floodplain of the lower Mississippi and its tributaries. Hundr9ds of examples exist in Arkansas, Mississippi, and Louisiana, the largest being Lake St. Joseph (Cooper and McHenry 1989; Smith 1996). Numerous examples also occur along the Darling and Murray river in Australia where oxbow lakes are termed billabongs (David and Browne 1950).
4. FLOODPLAIN LAKES
Floodplain lakes are another form of fluviatile lakes. These relict lakas are fomed from hollows in the floodplain of a river which are filled by the river when it overfiows its banks during times of flooding. The Amazon River's floodplain covers 60.000 km2and contains thousands of relict lakes of considerable variety (Burgis and Morris 1987). These floodplain relict lakes Vary seasonally not only in area but also in depth. In the dry season they are mostly shallow lakes which are well mixed by the wind, but in the rainy Appendix A season they can become sufficiently deep to stratify themally. During a flood in the rainy season, fish and other aquatic animals gain access to these relict lakes, which they may othe~lisebe denied access to during the dry season. Therefore, these relict lakes are typified by their wide range of seasonal variation which depends on the size of a flood in any one year and the position of the relict lakes relative to the river (Butgis and Morris t 987).
G. LAKES FORMED FROM GLACIAL ACTIVIN
The majority of lakes in the North Temperate Zone, including lakes in North America, the English and Scottish Lake Districts, and the alpine lakes of Europe especially in Finland. were forrned by the gouging and scraping action of glaciers during the last Pleistocene glacial recession. This glacial activity has produced the greatest number and diversity of lakes in the world (Winter and Woo 1990).
Lakes of glaciat origin can be divided into four categories (Hutchinson 1957): lakes held by ice or by moraine in contact with ice such as proglacial lakes, lakes formed from glacial rock basins such as ice-scour lakes, cirque lakes and glint lakes,
0 lakes formed from morainic and outwash dams, and lakes forrned from drift basins such as kettle lakes.
7. UKES HELD BY /CE OR BY MORAINE IN CONTACT WITH /CE
On glaciated mountains, a stream may be dammed by the edge of a glacier forming an isolated lake. This damming of a strearn occurs when the glacier of a main valley extends far enough down to dam a tnbutary stream, or altematively, when a lateral glacier dams the main stream (Hutchinson 1957). These dams are usually not permanent, since they are constantly being eroded by water spilling over the top of the glacial ice or discharging through crevasses across the ice dam. Such ice-dammed lakes, typically located on glaciated mountains, are examples of glacial solus lakes. Strom (1938: Hutchinson 1957) lists four glacial solus lakes held by ice-dams in Noway. The best known is Demmevatn in Hardanger, Nowuay. When a glacial ice sheet is receding. the newly uncovered land will not immediately rebound to its pre-glacial elevation. The newly uncovered valleys may form basins dammed by the retreating ice sheet. Basins form when the original relief is very gentle, and when the pre-glacial drainage is directed towards the region still covered by ice. These lakes are examples of large proglacial lakes which recede to form smaller glacial relict lakes. Many examples of these glacial relict lakes are known in North America. The rnost prominent examples are the developmental stages of the Great Lakes (e.g., Hough 1958; Dyke and Prest l987a).
2. GLACIA TED ROCK BASINS
a) /CE-SCOUR LAKES
Glacial rock basins are formed when pre-existing fractures and shatter belts on hard bedrock are excavated by glaciers as they retreat, forming basins which are filled with glacial meltwater. These ice-scour lakes may be considered glacial relict or glacial solus lakes depending on whether they were formed from a large proglacial waterbody or in isolation. Prominent European examples of ice-scour basins are found in Finland (Seppala 1980). b) CIRQUE LAKES
The heads of glaciated valleys are often molded into amphitheatre-like basins, termed cirques, by glacial ice action. True cirque lakes are generally small and shallow, though a few deep cirques have been found. Cirque lakes occur in practically every glaciated mountain range. They are examples of isolated glacial solus lakes. Numerous examples of cirque lakes are found in the Cordilleran chains of North America. Lakes Iceberg, Hidden. Avalanche, Gunsight and Ellen Wilson are prominent examples found in Glacier National Park. Montana, US (Dyson 1948a. b).
Other examples of cirque lakes also exist in the glaciated parts of Tasmania (David and Browne 1950). Numerous examples of cirque lakes also occur in the glaciated mountains of New Zealand such as Lake Browne (Soons and Selby 1982). C) GLINT LAKES
In glaciated regions, there is a tendency for ice to accumulate in valleys with small outlets. Large rock basins may develop at the outlet filled with glacial ice. Lakes fomed from the melting of glacial ice in these areas are referred to as glint lakes ("glint" meaning 'boundaryn in Nowegian). These lakes are an example of glacial solus lakes. A number of striking examples of glacial solus glint lakes are identified in Scotland such as Loch Rannoch, Loch Ericht, Loch Ossian, and Loch Treig, which radiate from the ice cauldron that occupied Rannoch Moor (Maitland 1994).
3- DRIFT BASINS
a) KETTLE LAKES
The most characteristic type of lake in many areas covered by continental ice during the last Pleistocene glaciation is the kettle lake. Such lakes were formed by the deposition of blocks of ice washed out with glacial drift material from the glaciers as they retreated. As the masses of ice melted, basins were left which were often referred to as kettle lakes. These lakes are an example of glacial solus lakes.
Numerous freshwater ponds on the Midwestern plains, termed prairie potholes, are examples of solus kettle lakes on the central plains of North Arnerica (Christiansen 1979). Many kettle lakes also occur in the Winegar Moraine which represents the last advance of glacial ice in the central United States (Zumberge 1952: Hutchinson 1957).
In Europe, kettle lakes are rnost prominent in lreland (Mitchell 1951). A number of kettle lakes also exist in Switzerland, particularly in the fluvioglacial deposits of Canton Zurich. Numerous kettle lakes also occur in Sweden and Finland, including a number of lakes occupying kettles in eskers (Embelton 1984). b) THERMOKARST LAKES
In regions of perennially frozen ground, lakes are frequentiy fomed by local thawing. Such lakes are analogous to kettle lakes, with one exceptional feature: the position of a Appendix A kettle take is detemined by the presence of a discrete mass of buried ice. whereas the position of a local thaw lake is detenined by extraneous events causing local melting. The term thermokarst has been used to describe this type of solus lake formation. Examples of thermokarst solus lakes are found in the interior of eastem Alaska (Wallace 1948: Hutchinson 1957). The permafrost in this region is unstable; once soi1 in this area thaws, it will not refom a perennially frozen layer. Once formation of a therrnokarst lake begins, the embryo lake progressively increases in area. Aooendix B
APPENDIX B
Schematic Surnrnary of the Formation of the Great Lakes ro Co-* >
Figure 84. Schematic map of the Great Lakes -St. Lawrence Basin 11,000 years ago (Modified from Dyke and Prest 1987b). Figure 65. Schematic map of the Great Lakes -St. Lawrence Basin 10,000 years ago (Modified from Dyke and Prest 1987b).
Appendix B
Figure 87. Schematic map of the Great Lakes -3.Lawrence Basin 8,000years ago (Modified from Dyke and Prest 1987b). Appendix B
Figure B8. Schematic map of the Great Lakes -St. Lawrence Basin 7.000 years ago (Modified from Dyke and Prest l987b). Appendix B
Figure 69. Schematic map of the Great Lakes -St. Lawrence Basin 5,000 years ago (Modified from Dyke and Prest 1987b). Location and Bedrock Geology of Bruce Peninsula, Wellington, Lacloche, Sudbury, Wawa, and Algoma Regions. Table Cl. Summary of study regions (bedrock geology is summarized from Barrett 1992).
Location of Regions Bedrock Geology Region Watersheds Latitude Longitude Number Era Description Cox (1978) Boundary Boundary of Lakes Wawa 280 4755 - 4827 8415 - 50 Net3 to Metasedimentary 8458 Mesoarchean and metavolcanic rock -massive to foliated granodiorite to granite -foliated to gneissic tonalite to granodiorite
Lacloche 8100 - Proterotoic Paleo - Metasedimentary 8208 proterozoic and metavolcanic rock -Cobalt group - congtomerate wacke, arkose, quam arenite. argilite Phanerozoic Paleozoic Sedimentary rock (Ordoviaan) -limestone, dolostone. shale,
Bruce 8058 - Phanerozoic Paleozoic Peninsula 81 40 (UPPer -timestone, Silurian) dolostone. shale, sandstone, gypsum Salt Phanerozoic Paleozoic Sedimentary rock ( MiddleILower -sandstone, shale, Silurian) dotostone, siltstone Algorna 8455 - Neo to Metasedimentary 8559 Mesoarchean and metavo~canic rock -massive ta foliated granodiorite to granite -foliated to gneissic tonalite to qranodiorite Sudbury Proterozoic Paleo - Metasedimentary proterozoic and metavdcanic rock -Cobalt group - cunglornerate wacke. arkose, quartz arenite. argilite -- Neo to Metasedimentary Mesoarchean and metavolcanic rock massive to foliated granodiorite to qranite 1 Location of Regions Beârock Geology Latitude Lon~itude Number Boundary Boundary of Lakes 4255 - 4425 8009 - 88 Phanerozoic Paleozoic Sedimentary rock 81 10 (UPP~~ -sandstone. Devonian) dolostone. Iimestone Phanerozoic Paleozoic Sedimentary rock 7--1imestone. Devonian) dolostone. shale Phanerozoic Paleoroic Sedimentary rock (UPW -limestone, Silurian) dolostone, shale, sandstone, Results of Canonical Correlation Analyses Correlating Regional Environmental Variables with Lake Morphology and Water Chemistry Table Dl. Correlations, standardized canonical coefficients, canonical correlations, percents of variance, and redundancies between lake morphology and regional variables and their corresponding canonical variates.
First Canonical Variate Second Canonical Variate Correlation 1 Coefficient Comlation [ Coefficient Morphology Set I 1
Maximum Depth II IShoreline Perimeter 0.66 0 .29 4.5 -0.08 1 Percent of Variance 0.59 0.20 Total = 0.8( 0.21 0.04 Total = 0.2:
Re~ionaiSet Degree Days -0.89 -0.59 0.24 0.5 Precipitation -0.5 -0.47 0.59 0.32 Net Primary -0.2 0.3 0.47 -0.31 ~roductivit~ Contour Com~lexitv 0.1 3 0.1 1 0.72 0.39 L I I Forest Cover 0.16 0.07 0.68 0.43 Parent Material -0.37 0.03 -0.46 -0.42 Isoil Drainage -0.4 -0.25 -0.54 -0.05 Percent of Variance O .23 0.26 Total = 0.50 1 Redundancy 1 0.08 1 0.05 1 Total = 0.13 Table 02. Correlations, standardized canonical coefficients, canonical correlations, percents of variance, and redundancies between water chemistry and regional variables and their corresponding canonical variates.
Regional Set Degree Days 0.3 0.6 1 0.86 1.21 -0.11 -0.51 Precipitation 0.03 O. 18 0.17 -0.56 -0.01 0.49 Net Primary -0.41 -0.48 0.46 0.13 -0.09 -0.04 Productivity Contour Complexity -0.48 -0.17 0.07 0.02 0.3 0.25 Forest Cover 4.43 -0.15 O. 1 0.01 -0.01 O. 02 Parent Material 0.63 -0.28 -0.26 -0.23 -0.6 -1-59 Soil Drainage 0.87 0.79 -0.27 -0.11 -0.09 1.36 Percent of Variance 0.23 0.22 0.06 Total = 0.52 Redundancy 0.1 2 0.02 0.00 Total = 0.14 Table D3. Correlations, standardized canonical coefficients, canonical correlations, percents of variance, and redundancies between lake rnorphology and water chernistry variables and their corresponding canonical variates.
Correlation Coefficient Correlation Coefficient Correlation Coefficient Lake Morphology Set
Area 0.38 -0.3 0.8 -1.39 -0.15 2.06 Volume 0.68 0.31 -0.61 -0.48 -0.19 -0.29 Maximum 0.97 0.91 -0.03 0.59 0.04 0.52 Depth Shoreline 0.44 O. 04 0.6 0.65 4.5 -2.49 Perimeter Percent of 0.44 0.34 0.08 Total = 0.84 Variance Redundancy 0.1 8 0.02 0.00 Total = 0.21
Set
PH 9.59 -0.08 -0.43 -1.24 0.68 0.61 Conductivity 9.71 -0.43 0.35 1.25 0.61 0.42
Variance Redundancy 0.22 0.01 0.01 Total = 0.24
II Cananical 1 0.64 1 1 0.27 1 1 0.1 8 1 1 Appendix E
Principal Component Analyses of Cornbined Relict and Solus Lakes and Proximally Paired Relict and Solus Lake Regions Using Local, Lake Morphology. Water Chernistry and Regional Environmental Variables. Appendix E
Table El. Correlations of local environmental variables with the first two principal components of a principal component analysis of al1 relict and solus la kes.
Environrnental Principal Component ILaibls i Number II Surface Area 1 0.40 1 0.49 11 Volume 0.40 1 0.10 11 0.42 , - -- Maximum Depth II 11 Total Shoreline 1 0.41 1 0.45 (1 II Perimeter I I II
II Conductivitv 1 1 If Secchi Depth 0.31 Percent of Total 0.52 0.1 9 1 Variation Cumulative 0.52 0.71 - Percentage
Table E2. Correlations of lake morphology variables with the fint two principal components of a principal component analysis of al1 relict and solus la kes.
Il Environrnental 1 Principal Component 11 II Variable 1 Nurnber 1 i 2 Surface Area 0.54 -0.45 Volume 0.46 0.51 Maximum Depth 0.46 0.56 Total Shoreline 0.54 -0.46 Perimeter Percent of Total 0.70 0.17 1 Variation Cumulative 0.70 0.87 1 1 Percentaae 1 I II Table E3. Correlations of water chemistry variables with the first two principal cornponents of a principal component analysis of al1 relict and solus lakes.
0.62 Specific 0.63 0.32 Conductivity Secchi Depth -0.47 0.88 Percent of Total 0.65 O .24 Variation Cumulative 0.65 0.89 11 Percentage 1 Il1
Table E4. Correlations of regional environmental variables with the fint ho principal components of a principal component analysis of al1 relict and solus lakes.
Environmental Principal Component Variable Number
Annual Number of Degree Days Mean Annual -0.1 3 0.56 Precipitation Net Prirnary -0.30 0.50 Productivit Contour -0.4 1
Surrounding -0.35 Forest Cover Parent Material 0.47 0.24 Surrounding Soil 0.54 0.1 3 II Drainaae 1 Table E5. Correlations of local environmental variables with the first two principal components of a principal component analysis of Wawa and Algoma la kes.
II Environmental 1 Principal Component II Variable Number I 4 I 9 II
Percentaae I II
Table E6. Correlations of iake morphology variables with the first two principal components of a principal component analysis of Wawa and Algoma la kes.
Environmental Principal Component Variable Number
Surface Area -0.23 Volume Maximum De th 0.42 0.1 3 Total Shoreline -0.27 Perimeter Percent of Total 0.58 0.23 Variation Cumulative 0.58 0.81 il Percentaae I II Table E7. Correlations of water chernistry variables with the fint two principal components of a principal component analysis of Wawa and Algoma lakes.
Environmental Principal Component Variable Number 1 2 -0.40 0.86 Specific 0.60 0.50 / ~onductivit~ Secchi Depth 0.69 O .O5 Percent of Total 0.41 0.33 Variation Cumulative 0.41 0.74 11 Percentage I I 1
Table E8. Correlations of regional environmental factors with the first two principal cornponents of a principal component analysis of Wawa and Algoma la kes .
11 Precipitation II 1) Net Primary 1 -0.36 1 0.06 If
Contour -0.29 O -46 Complexity Surrounding -0-36 0.04
Forest Cover-- - Parent Material 0.37 Surrounding Soil 0.37 ' 0.37 1 II Drainaae 1 II Table €9. Correlations of local environmental variables with the first two principal components of a principal cornponent analysis of LaCloche and Sudbury la kes.
Environmental Principal Component II Variable Number II Surface Area Volume -0.10 0.47 -0.19 Total Shoreline 0.55 -0.08 Perimeter / DH 0.16 0.55 11 Specific 1 -0.02 1 0.53 11
Secchi Depth 0.17 -0.58 Percent of Total 0.35 0.20 II Variation I I II Cumulative 0.35 0.56 Percentage L
Table El 0. Correlations of lake morphology variables with the first two principal components of a principal component analysis of LaCloche and Sudbury la kes.
Environmentai Principal Component n Variable Number Surface Area -0.31 Volume 0.45 O .22 Total Shoreline -0.35 Perimeter Percent of Total 0.59 0.21 Variation Cumulative 0.59 0.81 il Percentaae I I Il Table El1. Correlations of water chemistry variables with the first two principal components of a principal cornponent analysis of LaCloche and Sudbury la kes.
II Specific 1 0.60 1 0.48 11 ~onductivit~ Secchi Deoth -0.49 0.85 Percent of Total Variation Cumulative
Table El 2. Correlations of regional environmental variables with the first two principal components of a principal cornponent analysis of LaCloche and Sudbury lakes.
1 2 Annual Number of 1 .O0 -0.12 Degree Days Mean Annual -0.12 1 .O0 Precipitation Net Primary 0.44 0.45 Productivity Contour 0.40 0.31 Corn lexit Surrounding Forest Cover Parent Material -0.62 Surrounding Soi1 -0.57 Table El3. Correlations of local environmental variables with the first two principal components of a principal cornponent analysis of Bnice Peninsula and Wellington lakes.
Environmental Principal Component Variable Number
Surface Area -0.29 Volume 0.29 0.57 Total Shoreline 0.51 -0.27 Perirneter pH 0.04 0.08 Specific -0.15 0.43 Conductivity Secchi Depth 0.29 0.57 Percent of Total 0.40 0.21 Variation Cumulative 0.40 0.61 Percentage
Table €14. Correlations of lake morphology variables with the first two principal components of a principal cornponent analysis of Bruce Peninsula and Wellington lakes.
Environmental Principal Component Variable Number
1 I 1 Surface Area 0.58 -0.28
.------Maximum Depth O .25 Total Shoreline 0.57 ' -0.27 1 Perimeter Percent of Total 0.65 0.24 Variation Cumulative 0.65 0.89 Appendix E
Table El5. Correlations of water chernistry variables with the fint two principal components of a principal component analysis of Bruce Peninsula and Wellington lakes.
IEniironmenta~ 1 Principal Component 11 1 Variable 1 Number 11 1 2 0.69 -0.14 Specific 0.69 -0.15 Conductivity Secchi Depth 0.21 0.98 Percent of 1otal 0.42 0.33 Variation Cumulative 0.42 0.75
, Percentage ,
Table €16. Correlations of regional environmental variables with the first two principal components of a principal component analysis of Bruce Peninsula and Wellington lakes.
Environmental Principal Component Variable Number
Degree Days Mean Annual 0.58 0.02
Net Primary -0.05 Productivi Contour -0.09 Complexity Surrounding 0.29 0.55 I[ Forest ~over 1 1 11 Parent Material 0.0 I- Surrounding Soil -0.01 2 -0.24 Appendix E
4
Solus Lakes Centroid
Relict Lakes Centroid
PRINCIPAL COMPONENT 1 Relict takes l
Figure El. Principal component analysis of relict and solus lakes using local environmental variables.
.-cn V) -)r Cuc (TI
- (TI .-Q O zt
4 4 +
m Algorna Lakes Centroid B *4 1' . 8 'Ir
. , 'km rn 8. :: 1 1 1 1 L 'mm - ' I av 1 -4 -3 4 -2. 4 3 4 5 6 -b 8 4 8 m m8 '4 4 8. iD m m . -1" I na rn m m 8 + m -2" . 8 Wawa (Relict) Lakes a Algoma (Solus) Lakes
-3 " m
-4 - PRINCIPAL COMPONENT 1
Figure E5. Principal component analysis of Wawa and Algoma lakes using local environmental variables.
a
Sudbury Lakes Centroid . LaCloche Lakes Centroid I /
LaCloche (Relict) Lakes PRINCIPAL COMPONENT 1 Sudbury (Solus) Lakes
Figure El1. Principal component analysis of LaCloche and Sudbury lakes using water chernistry environmental variables.
Wellington Lakes Centroid 8 1 Bruce Peninsula Lakes Centroid
4 Bruce Peninsula (Relict) Lakes
Wellington (Solus) Lakes
PRINCIPAL COMPONENT 1
Figure El5. Principal component analysis of Bruce Peninsula and Wellington lakes using water chemistry environmental variables,
Appendix F
Discriminant Analyses for Each of the Six Study Regions Using the Fint Two Principal Components of Principal Component Analyses of Combined Local and Regional, Local, Regional, Lake Morphology and Water Chemistry Environmental Variables Table FI. Summary of a discriminant analysis for each of the six study regions using the first two principal components of a principal component analysis of combined local and regional environmental variables.
11 Discriminant 1 Eigenvalue 1 Relative 1 Canonical II
1 Actuall Bruce LaCloche Wawa Wellington Sudbury Algoma : Predicted Peninsula Percentage Bruce 66.07 0.00 0 .O0 21.43 3.57 8.93 Peninsula LaCloche O .O0 61 -36 27.27 2.27 9.09 0.00 Wawa O .O0 32 .O0 40.00 0.00 28.00 0.00 1 Wellington 5.68 0.00 0.00 94.32 0.00 0.00 1 Sudbury 0.59 21 -76 16.47 O .O0 42.94 18.24 / Appendix F
Table F2. Sumrnary of a discriminant analysis for each of the six study regions using the first two principal components of a principal component analysis of local environmental variables.
11 Discriminant 1 Eigenvalue 1 Relative 1 Canonical 1
Actuall Bruce LaCloche Wawa Wellington Sudbury Algoma Predicted Peninsula Percentage Bruce 57.1 4 0.00 0.00 32.14 O .O0 10.71 Peninsula LaCtoche 0 .O0 68.18 18.1 8 0.00 13.64 0.00
Wawa 0.00 20.00 32.00 0.00 30.00 18.00
Wellington 21.59 0.00 1.14 72.73 0.00 4.55 L 1 I Sudbury 0.00 20.00 24.12 0.00 37.65 18.24
Algoma 2.20 1-10 13.19 3.30 8-79 71.43 Table F3. Summary of a discriminant analysis for each of the six study regions using the first two principal cornponents of a principal component analysis of lake morphology variables.
Actuall Bruce 1 lacloche / Wawa 1 Wellington / Sudbury / Algoma Predicted Percentage Bruce 60.71 5.36 1.79 21.43 7.14 3.57 Peninsula LaCloche 13.64 2.27 25.00 20.45 34.09 4.55
Wawa 12.00 12.00 46.00 8.00 22.00 O .O0
Wellington 17.05 0.00 5.68 75.00 1.14 1.14
Sudbury 7.65 6.47 30.00 4.12 43.53 8.24
Algoma 10.99 5.49 24.18 4.40 41.76 13.t9 Appendix F
Table f4. Summary of a discriminant analysis for each of the six study regions using the first two principal cornponents of a principal component analysis of water chernistry variables.
Peninsula LaCfoche 0.00 68.1 8 6.82 0.00 25.00
1 1 Wawa 4.00 14.00 44.00 0.00 18.00 20.00
Wellington 40.91 0.00 0.00 53.41 2-27 3.41
Sudbury 0.00 15.88 17.65 0.00 62.35 4.12 Table F5. Surnmary of a discriminant analysis for each of the six study regions using the first two principal components of a principal component analysis of regional environmental variables.
(1 Discriminant 1 EigenvaIue 1 Relative % 1 Canonical 11
Actuall Bruce 1 LaCloche 1 Wawa Wellington 1 Sudbury 1 Algoma II Predicted 1 eni insu la 1 Percentage Bruce 73.21 0.00 0.00 25.00 0.00 1.79 Peninsula LaCloche 0.00 79.55 0.00 0.00 20.45 0.00 1 ~awa 0.00 0.00 98.00 0.00 0.00 2.00 1 Wellington i 3.41 1.14 0.00 95.45 0.00 O .OO Sudbury 5 -29 34.12 4.71 0.00 52.35 3.53
Algoma 0 .O0 0.00 3.30 0.00 1.10 95.60 Reconstruction of the Glacial Lake Phases of Lakes Agassiz. Su perior. Michigan. Erie, Ontario. Barlow-Ojibway, and the Champlain Sea With lnflow and Outflow Connections
Based on Numerous Resources: Radforth 1944; Hough 1958; MacKay 1963; Hubbs and Lagler 1964; Prest 1970; Pflieger 1971 ; Hocutt et al. 1978; Bailey and Smith 1981; Teller et al. 1983; Eschrnann and Karrow 1985; Farrand and Drexler 1985; Karrow and Calkin 1985; Kaszycki 1985; Underhill1986; Dyke and Prest 1987a; Dredge and Cowan 1989; Karrow and Occhietti 1989; Mandrak 1994. Appendix G
Table G1. Glacial phases of the Great Lakes.
Lake Lake Lake Lake iake Lake Lake Champlain Agassiz Erie Ontario Barlow- Sea Ojibway
iâkûs Winnipeg wlnnipegosii Manitoba
Hudson St. Lmrencc Rtvef Bay
Ene
Houghton- Nipissing Staniey- Tyreil Ntpissing Sea Ojibway Ojhvay- Post- Minong- Ojibway- Lampsilis Houghtan Anglies Nipigon Barlow- Mino* Staniey- 'erniscaming Hough R#'& larlow-Aylen -W Ba: Korah Eany Moorehead Minnnn Phase C Champlain Sea I Aigonqiun Cass [Calumet)
Avon Vermont iariy Phase -Newberry Giacial ice Damville ; Glacial lce Albany Maumee Glaciaî lce dke Ctucag Glaàai Ice Table G2. Glacial lake phases of present day Lake Agassiz.
lnflow oumow
proglacial ~ississippiRiver to Mississippi basin
proglacial Mississippi River to Mississippi basin
proglacial Minnesota River to Mississippi basin
proglacial and from the Sheyenne, Minnesota River to Mississippi Assiniboine and Souris-Pembina basin Warren River to the Minnesota River to the Mississippi basin
Lockhart proglacial and from the Sheyenne, Warren River to the Minnesota (1 1250-1 0800) Assiniboine and Souris-Pembina River to the Mississippi basin Rivers 1 Moorehead proglacial and from the Sheyenne Nipigon outlet to Superior basin River to Michigan basin to Straits of Mackinac to Huron basin Nipigon outlet to Superior basin to St. Croix outlet to Bruce- Portage to Mississippi basin Kasinabowie-Seine River to Dog River to Lake Nipigon to Superior basin to St. Mary's Strait to Huron basin to Fossmill - Petawawa outlet to Ojibway basin to Mink Lake to the Ottawa River basin to Champlain Sea to Proto -Gulf of St. Lawrence to Atlantic Ocean
II Emerso proglacial Warren River to Minnesota River to Mississippi basin Agassiz basin Nipigon outlet to Superior basin to St. Mary's Strait to Huron basin to the Ottawa River basin to St. Lawrence River to the Atlantic Ocean
Agassiz basin Barlow-Ojibway to Ottawa River basin to St. Lawrence River to the Atlantic Ocean Agassiz basin Nelson River to Hudson Bay Table G3. Glacial lake phases of present day Lake Superior.
.- - .- .. - Lake Phase lnflow outflow (Years Before Present) Duluth A -Western Basin proglacial St. Croix outlet to Bruce- (1 1500-1 1250) Portage to Mississippi
Duluth B -Western Basin proglacial St. Croix outlet to Bruce (11250-1 0750) Portage to Mississippi basin
Phase C Agassiz basin to Nipigon to Michigan basin to (10750-1 0400) Straits of Mackinac to Huron basin St. Croix outlet to Bruce Portage to Mississippi basin
Early Minong Agassiz basin to Nipigon St. Croix outlet to Bruce- (10400-1 0000) Portage to Mississippi basin St. Mary's Strait to Huron basin to Fossrnill - Petawawa outlet to Barlow-Ojibway basin to Mink Lake to Ottawa River basin to Champlain Sea to proto-Gulf of St. Lawrence to Atlantic Ocean
Minong -Eastern Basin / proglacial St. Croix outlet to Brule- Duluth -Western Basin Portage to Mississippi (10000-9650) basin St. Mary's Strait to Huron basin to Ottawa River basin to proto-Gulf of St. Lawrence to the Atlantic Ocean
Post Duluth Agassiz basin to Nipigon Au Train -Whitefish - (9650-9500) Green Bay outlet to Michigan basin to Straits of Mackinac to Huron basin to Ottawa River basin to proto-Gulf of St. Lawrence to the Atlantic Ocean
Minong Agassiz basin to Nipigon St. Mary's Strait to Huron (9500-9050) basin to Ottawa River basin to proto-Gulf of St. Lawrence to the Atlantic Ocean lnflow
Agassiz basin to Nipigon St. Mary's Strait to Huron Superior basin basin to Ottawa River basin to St. Lawrence River to the Atlantic Ocean
Houghton -Nipissing Superior basin St. Mary's Strait to Huron (8000-7000) basin to Ottawa River Il basin to St. Lawrence River to the Atlantic Ocean
Superior basin St. Mary's Strait to Huron basin to Mattawa outlet to St. Lawrence River to the Atlantic Ocean St. Mary's Strait to Huron basin to St. Clair-Detroit River to Erie basin to Niagara River to Ontario basin to St. Lawrence River to the Atlantic Ocean
Superior basin St. Mary's Strait to Huron basin to St. Clair-Detroit River to Erie basin to Niagara River to Ontario basin to St. Lawrence River to the Atlantic Ocean
11 Present Day Lake Superior Superior basin St. Mary's Strait to Huron lasin to St. Clair-Detroit River :O Erie basin to Niagara River :O Ontario basin to St. ,awrence River to the Atlantic 3cean Appendix G
Table G4. Glacial lake phases of present day Lake Michigan.
Lake Phase I lnflow oumow (Years Before Present) Lake Chicago (Glenwood 1) proglacial Chicago outlet to Des proglacial to Grand River Plaines / Illinois River to Mississippi basin lndian River to Huron basin to Fort Wayne outlet to Wabash River and Ohio River to Mississippi basin
Low Phase proglacial to Green Bay Indian River to Huron (13500-1 31 00) basin to Fort Wayne outlet to Wabash River and Ohio River to Mississippi basin Straits of Mackinac to Huron basin to Ubly Channel to Mississippi basin
Lake Chicago (Glenwood II) proglacial to Huron basin Straits of Mackinac to (13100-12100) 1 10 lndian River to Grand Huron basin to Ubly River Channel to Mississippi basin Chicago Outlet to Des Plains 1 Illinois River to Mississippi basin
Algonquin (Low Phase) proglacial to Green Bay lndian River to Huron basin to Kirkfield outlet to Ontario basin to Champlain/tludson River to Atlantic Coast basin 8 Straits of Mackinac to Huron basin to St. Clair - Detroit River to Erie basin to Buffalo outlet to Niagara River to Ontario basin to St. Lawrence River to Champlain Sea to Atlantic Ocean
Algonquin (Calumet Phase) proglacial to Green Bay Bonnechere River to (1 1650-11 150) proglacial Atlantic Coast basin lndian and Barron Rivers to Atlantic Coast basin Petawawa River to Atlantic Coast basin
Post Algonquin proglacial to Upper indian River to Huron (11150-10100) Peninsula basin to Pori Huron outlet proglacial to St. Clair - Detroit River to Erie basin to Buffalo 7 Lake Phase lnflow outflow (Years Before Present) Ontario basin to St. Lawrence River to Atlantic Ocean Straits of Mackinac to Huron basin to St. Clair - Detroit River to0Erie basin to Buffalo outlet to Niagara River to Ontario basin to St. Lawrence River to Atlantic Ocean Straits of Mackinac to Huron basin to Fossmill - Petawawa outlet to 8arlow-Ojibway basin to the Mattawa outlet to the Ottawa River to the Champlain Sea to proto- Gulf of St. Lawrence to the Atlantic Ocean
Chippewa proglacial Straits of Mackinac to (1 O1 00-7000) progfacial to Upper Huron basin to North Bay Peninsula outlet to Ottawa River Michigan basin basin to St. Lawrence River to Atlantic Ocean
Nipissing Michigan basin Straits of Mackinac to (7000-3500) Huron basin to North Bay outlet to Ottawa River basin to St. Lawrence River to Atlantic Ocean Straits of Mackinac to Huron basin to Port Huron outlet to St. Clair - Detroit River to Erie basin to Buffalo outlet to Niagara River to Ontario basin to St. Lawrence River to Atlantic Ocean
Atgoma Michigan basin Chicago outlet to Illinois (3500-2500) River to Mississippi basin
Present Day Lake Michigan Michigan basin 8 Straits of Mackinac to (2500-0) Huron basin to Port Huron outiet to St. Clair -Detroit River to Erie basin to Buffalo outlet to Niagara River to Ontario basin to St- Lawrence River to the Atlantic Ocean Table G5. Glacial lake phases of present day Lake Huron. lnflow I outflow proglacial Fort Wayne outfet to Wabash River and Ohio River to Mississippi basin lmlay Channel outlet to Saginaw Bay basin to Grand River to Michigan basin
Arkona proglacial lmlay Channel outlet to (13500-1 3000) Saginaw Bay basin to Grand River to Michigan basin
Whittlesey proglacial lmlay Channel outlet to Saginaw-Saginaw Basin Saginaw Bay basin to (13000-1 2800) Grand River to Michigan basin Ubly Channel to Mississippi basin
Warren proglacial lmlay Channel outlet to (12800-i 2600) Saginaw Bay basin to Grand River to Michigan basin Ubly Channel to Mississippi basin
Grassmere proglacial Mohawk - Hudson River to (12600-1 2400) Atlantic Coast basin
Lundy proglacial lndian River to Michigan (12400- 12250) basin to Chicago outlet to Des Plaines / Illinois River to Mississippi basin
Michigan basin to lndian Port Huron outlet to St. River Clair - Detroit River to Erie basin to Buffalo outlet to Niagara River to Ontario basin to Champlain1 Hudson River to Atlantic Coast basin
Algonquin (Kirkfield) Michigan basin to Straits Kirkfield (Fenelon Falls) (12000-1 1750) of Mackinac outlet to Ontario basin to Champlain1 Hudson River to Atlantic Coast basin
Algonquin , Bonnechere River to (1 1750-11000) Lake phasep- outflow (Years Before Present) lndian and Barron Rivers to Atlantic Coast basin Petawawa River to Atlantic Coast basin
Post Algonquin Superior basin to St. Port Huron outlet to St. 1l000-1 O 100) 1 Mary8sÇtrait , Clair- Detroit River to Erie ! basin to Buffalo outlet to Niagara River to Ontario basin to Champlain Sea to the Atlantic Ocean Fossrnill - Petawawa outlel to Bartow-Ojibway basin ta Mattawa outlet to Ottawa River basin to Champlain sea to proto- Gulf of St. Lawrence to Atlantic Ocean
Stanley-Hough Superior basin to St. North Bay outlet to Ottawa (10 100-8850) Mary's Strait River basin to Proto Gulf of St. Lawrence to Atlantic Ocean
Stanley-Nipissing Michigan basin to Straits North Bay outlet to Ottawa (8850-7000) to Mackinac 1 River basin to St. Superior basin to St. Lawrence River to Atlantic Mary's Strait Ocean
Nipissing Superior basin to St. North Bay to Ottawa River (7000-3500) Mary's Strait basin to St. Lawrence River tp Atlantic Ocean Port Huron outlet to St. Clair - Detroit River to Erie basin to Buffalo outlet to Niagara River to Ontario basin to St. Lawrence River to Atlantic Ocean
Michigan basin to Straits 1 Port Huron outlet to St. of Mackinac Clair - Detroit River to Erie Superior basin to St. basin to Buffalo outlet to Mary's River Niagara River to Ontario basin to St. Lawrence River to Atlantic Ocean
Present Day Lake Huron Michigan basin to Straits Port Huron outIet to St. (2500-0) of Mackinac Clair - Detroit River to Erie Superior basin to St. basin to Buffalo outlet to Mary's River Niagara River to Ontario basin to St. Lawrence River to Atlantic Ocean Appendix G
Table G6. Glacial lake phases of present day Lake Erie.
Lake Phase lnflow outflow (Years Before Present) Maumee proglacial Fort Wayne outlet to (1 4250-13750) Wabash River and Ohio River to Mississippi basin lmlay Channel outlet to Saginaw Bay basin to Grand River to Michigan basin Fort Wayne outlet to Wabash River and Ohio River to Mississippi basin
Arkona proglacial Grand River to Michigan (1 3750-13600) basin
Ypsilanti proglacial Mohawk River to Atlantic (13600-1 3000) Coast Basin Buffalo outlet to Niagara River to Ontario basin to Susquehanna River to Atlantic Coast basin Mohawk River to Atlantic Coast basin
Whittlesey proglacial lmlay Channel to Saginaw (13000-1 2800) Bay to Grand River to Michigan basin Ubly Channel to Mississippi basin
Warren proglacial lmlay Channel to Saginaw (1 2800-12600) Bay to Grand River to Grand River to Michigan basin Ubly Channel to Mississippi basin
Grassmere proglacial Mohawk - Hudson River to (12600-1 2400) Atlantic Coast basin
Lundy proglacial lndian River to Michigan (1 2400-12250) basin to Chicago outiet to Des Plaines / Illinois River to Mississippi basin
Early Algonquin Huron basin to St. Clair - Buffalo outlet to Niagara (1 2250-12000) Detroit river River to Ontario basin to Champlain/ Hudson River to Atlantic Coast basin Lake Phase lnflow outflow (Years Before Present) Early Erie Erie basin Buffalo outlet to Niagara (12000-1 1800) River to Ontario basin to Champlain1 Hudson river to Atlantic Coast basin
Present Day Lake Erie Huron basin to St. Clair - Buffalo outlet ta Niagara (11800-0) Detroit River River to Ontario basin to Erie basin St. Lawrence River to Huron basin to St. Clair- Atlantic Ocean Table G7. Glacial lake phases of present day Lake Ontario.
Belmont-Fillmore proglacial Susquehanna River to (13600-1 3400) Atlantic Coast basin Allegheny to Mississippi basin
Nunda proglacial Susquehanna River to (13400-1 320) Atlantic Coast basin
Dansville progtacial Susquehanna River to (13200-1 3000) Atlantic Coast basin
Newberry proglacial Susquehanna River to (13000-1 2700) Atlantic Coast basin
Hal1 proglacial Niagara River to Erie (12700-1 2600) basin
Avon proglacial Mohawk - Hudson River to (12600-1 2400) Atlactic Coast basin
Iroquois progtacial Mohawk - Hudson River to Erie basin to Niagara Atlantic Coast basin River ChamplainIHudson River Huron basin to Kirkfield to Atlantic Coast basin outlet Champlain Sea to Atlantic Erie basin to Niagara Ocean River Early Ontario Erie basin from Niagara Champlain Sea to Atlantic j' (11500-8500) River Ocean l Present Day Lake Ontario Erie basin from Niagara St. Lawrence River to Il (8500-0) River Atlantic Ocean Appendix G
Table G8. Glacial lake phases of present day Lake Barlow-Ojibway.
- II Lake Phase 1 inflow Outlfow (Years Before Present) / S heguiandah Huron basin to Nipissing Mink Lake to Ottawa River River Basin to Champlain Sea to prote -Gulf of St. Lawrence to Attantic Ocean
Mattawa River to Ottawa River basin to proto- Gulf of St. Lawrence to Atlantic Ocean Aylen outiet to Ottawa River basin to proto -Gulf of St. Lawrence to Atlantic Ocean
Barlow-Temiscaming Huron basin to Nipissing Temiscarning outlet to (9500-8850) River Ottawa River basin to proto- Gulf of St. Lawrence to Atlantic Ocean
Ojibway-Angliers Agassiz basin Angliers outlet to Ottawa (8850-8350) River basin to proto -Gulf of St. Lawrence to Atlantic Ocean
Ojibway-Kinojevis Agassiz basin Kinojevis outlet to Ottawa (8350-8000) River basin to St. Lawrence River to Atlantic Ocean
L Tyrell Sea Hudson Bay basin Hudson Bay (8000-7600) Present Day Hudson Bay Hudson Bay basin (7600-0) * Table G9. Glacial lake phases of present day Champlain Sea. Lake Phase -- Outtfow (Years Before Present) Albany proglacial Hudson River to Atlantic (1 3750-13 150) Coast basin
Vermont proglacial Hudson River to Atlantic (1 31 50-1 2000) Ontario basin Coast basin
Champlain Sea Ontario basin proto -Gulf of St. (1 2000-9500) Hudson River Lawrence to Atlantic Barlow -0jibway basin to Ocean Ottawa River Ontario basin to St. Lawrence River Lampsilis Barlow -0jibway basin to proto -Gulf of St. (9500-7500) Ottawa River Lawrence to Atlantic Ontario basin to St. Ocean Lawrence River St. Lawrence River to Atlantic Ocean
Present Day St. Lawrence Ontario basin to St. St. Lawrence River to River Lawrence River Atlantic Ocean (7500-0) Environmental Gradients for Surface Area, Volume, Maximum Depth, Total Shoreline Perimeter, Specific Conductivity. Surrounding Lake Net Piimary Productivity, and Sunaunding Lake Forest Cover Within Each of the Six Study Regions
Regions
Figure H2. High (maximum value), low (minimum value, and close (mean) plots for volume gradient across ali six studv reaions. Number in brackets indicate the number of lakes oer reaion.
Regions
Figure H5. High (maximum value), low (minimum value. and close (mean) plots for specific conductivity gradient across al1 six studv reciions. Number in brackets indicate the number of lakes Der reaion.
Regions
Figure H7. High (maximum value), low (minimum value. and close (mean) plots for surrounding lake forest wver gradient auoss al1 six study regions. Number in brackets indicate the number of lakes per region.