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2016 NICHE BREADTH AND INVASION SUCCESS Harri Pettitt-Wade University of Windsor

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NICHE BREADTH AND INVASION SUCCESS

By

Harri Pettitt-Wade

A Dissertation Submitted to the Faculty of Graduate Studies through the Great Lakes Institute for Environmental Research in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy at the University of Windsor

Windsor, Ontario, Canada

2016

© 2016 Harri Pettitt-Wade

Niche Breadth and Invasion Success

by

Harri Pettitt-Wade

APPROVED BY:

______D. A. Jackson, External Examiner University of Toronto

______T. Pitcher Department of Biological Sciences

______D. D. Heath Great Lakes Institute for Environmental Research

______C. Semeniuk Great Lakes Institute for Environmental Research

______A. T. Fisk, Advisor Great Lakes Institute for Environmental Research

18 April 2016

DECLARATION OF CO-AUTHORSHIP / PREVIOUS PUBLICATION

I. CO-AUTHORSHIP DECLARATION

I hereby declare that this dissertation includes original research reprinted from co- authored, submitted and published manuscripts. In all chapters, A T. Fisk contributed intellectually by providing consultation, and facilities and materials required for completion of the research. For Chapters 2, 3, 4 and 5, K. W. Wellband contributed to the research with sample collection, statistical guidance and manuscript consultation. For chapters 2, 3, 4 and 5, D. D. Heath contributed to the research with manuscript consultation. For Chapter 3, A. M. McLeod contributed to the research with statistical guidance and manuscript consultation. The writing of all chapters included in this dissertation, however, was completed entirely by the author, Harri Pettitt-Wade.

I am aware of the University of Windsor Senate Policy on Authorship and I certify that I have properly acknowledged the contribution of the other researchers to my dissertation, and have obtained written permission from each of the co-author(s) to include the above material(s) in my dissertation,

I certify that, with the above qualification, this dissertation, and the research to which it refers, is the product of my own work.

II. DECLARATION OF PREVIOUS PUBLICATION

This dissertation includes 2 original manuscripts that have been published or submitted for publication in peer-reviewed journals, as follows:

iii Thesis Chapter Publication title/full citation Publication status

Chapter 2 Pettitt-Wade, H., K. W. Wellband, D. D. Heath published & A. T. Fisk. 2015. Niche Plasticity in Invasive Fishes in the Great Lakes. Biol Inv 17: 2565- 2580

Chapter 3 Pettitt-Wade, H., K. W. Wellband, A. M. in review McLeod, D. D. Heath & A. T. Fisk. Ecology

I certify that I have obtained a written permission from the copyright owner(s) to include the above published material(s) in my dissertation. I certify that the above material describes work completed during my registration as graduate student at the Great

Lakes Institute for Environmental Research, University of Windsor.

I declare that, to the best of my knowledge, my thesis does not infringe upon anyone’s copyright nor violate any proprietary rights and that any ideas, techniques, quotations, or any other material from the work of other people included in my thesis, published or otherwise, are fully acknowledged in accordance with the standard referencing practices. Furthermore, to the extent that I have included copyrighted material that surpasses the bounds of fair dealing within the meaning of the Canada

Copyright Act, I certify that I have obtained a written permission from the copyright owner(s) to include such material(s) in my thesis.

I declare that this is a true copy of my thesis, including any final revisions, as approved by my thesis committee and the Graduate Studies office, and that this thesis has not been submitted for a higher degree to any other University or Institution.

iv ABSTRACT

A developing concept in ecology is that broad niches predict geographical range

size. Plasticity in resource use is often considered to be important for responding to novel

environments, and study of species that are established across different ranges provides a

model for determining the drivers of species spread and distribution. Contrasting

distributions of invasive species are often associated with species-specific feeding

ecology, but comparisons are rarely made for multiple taxa, spatial scales or between

native and invaded ranges.

Stable isotopes of carbon (δ13C) and nitrogen (δ15N) are common tracers in food web ecology and provide a quantitative measure of intra and interspecific variation in dietary niche. In this dissertation, I compare the dietary niches (variation in δ13C and

δ15N) of successful and less successful aquatic invasive species of fish and invertebrates established across broad and narrow ranges in invaded regions, fishes in native and invaded ranges, and the role of time since invasion for niche diversification in relation to habitat complexity and genetic diversity.

This dissertation demonstrates the importance of intra and inter-individual variation in resource use for successful widespread distribution of invasive fishes.

Inconsistency in this trend for oysters, tunicates and waterflea suggested dietary niche breadth is less important for invasion success in aquatic invertebrates than it is for fishes.

Moreover, dietary niche plasticity was associated with a broad body size range in fishes, but not invertebrates. Habitat complexity and environmental heterogeneity were associated with peaks in niche breadth that were exceptions to general trends of increasing niche breadth and genetic diversity with time established. Gain in niche

v breadth from native to invaded regions for populations of most successful invasive fishes, but loss of niche breadth for less successful species, further indicated the importance of intra-individual variation in resource use for widespread distribution. Loss of dietary niche breadth for less successful species implied that the invasion process could be associated with severe bottlenecks for less successful species, which could be a mechanism for limited spread. These findings highlight the potential for considerable impact from the invasion process for the ecology of the invader, and that establishment in novel environments can drive diversification in the absence of founder effects.

vi DEDICATION

For those that will inherit the Earth:

Charlie, Isla, Betsy and Tilly

vii ACKNOWLEDGEMENTS

I am foremost thankful to Aaron Fisk for taking me on as a student, investing wholly in my success and for his patience and encouragement to achieve my potential.

I am grateful for the valuable advice, critique and encouragement from my supervisory committee members Drs. Daniel D. Heath, Trevor Pitcher, Christina

Semeniuk and past member Hugh MacIsaac. I am very grateful that this research was part of the Canadian Aquatic Invasive Species Network (CAISN II). As part of CAISN, I have had the opportunity to interact with, gain advice and constructive criticism from numerous academics from around the world. In particular, Nickolas Mandrak provided advice and assistance on numerous occasions, including revision of my first data chapter following journal submission. Thanks to Lynda Corkum and Tim Johnson for sampling advice and contacts, Igor Grigorovic for Ukraine sampling advice, assistance in tracking down field assistants and in translating travel documents. I am grateful for the continuous collaboration of Kyle Wellband, who is always willing to explore the broad implications of our research. Thanks to Anne McLeod for never failing to provide honest criticism, discuss ideas at length no matter how trivial, for sharing my enthusiasm for fundamental science and continuous encouragement of my abilities. I am grateful for the support of my colleagues at GLIER and their willingness to discuss ideas, particularly Dave

Yurkowski, Nigel Hussey, Scott Colbourne, Steven Kessel and Brent Nawrocki.

Thanks to Sergey Khokodiy for being an exceptional Ukraine field assistant, lab assistant, translator and travel guide. Thanks to Yuriy Kvash, Lyonid Izergin and The

Research Institute of the Azov Sea for their incredible hospitality and assistance in

Ukraine sample collections. Thanks to Chris McKindsey for conducting sample

viii collections on the Canadian East coast, and Thomas Therriault, and the Pacific Biological

Station (Nanaimo, BC) for conducting West coast collections. Colin van Overdijk and

Samir Qureshi for assistance in Great Lakes collections. Thanks to Jake Larose, Peter

Hannikainen and the Lake Simcoe Fisheries Assessment Unit (OMNRF) for assistance in

Lake Simcoe collections, Eric Bergland and the Upper Great Lakes Management Unit

(MNR) for assistance in Thunder Bay collections. Kelly McLean for assisting in the field and discussing project ideas in the early stages. Jessica O’Neil, Matthew Renaud, Andrea

Lespeance, Jason Barsotta, Erin Donnelly, Kylie Dean, Amy Tanner, Brittany Charron,

Stephanie Isaac, Jake Nix, Erin Mailloux, Jordan Mailloux, Erin Donnelly, Tanya

Fendler, Amanda Peters, Brent Nawrocki, Katelynn Johnson and particularly Anna

Hussey for laboratory and field assistance. I am grateful to Katerina Stojanovic for assisting in the lab and field, but most of all, encouraging me to pursue my ambitions.

Above all, I am indebted to my parents Ann Pettitt and Barry Wade for their life- long support in all matters; you are forever my inspiration. I would not have made it through this journey without the support of my family and friends whom I have neglected for far too long in the UK, and my new friends across the water, of which I am fortunate enough to say there are far too many to mention.

This research was part funded by NSERC Canadian Aquatic Invasive Species

Network (CAISN II), and the Ontario Trillium Award scholarship. Research was conducted with approval from the University of Windsor Animal Care Committee,

OMNR Licences to collection fish for Scientific Purposes and Sample Importation

Permits.

ix TABLE OF CONTENTS

DECLARATION OF CO-AUTHORSHIP / PREVIOUS PUBLICATION ...... iii

ABSTRACT ...... v

DEDICATION ...... vii

ACKNOWLEDGEMENTS ...... viii

LIST OF TABLES ...... xiii

LIST OF FIGURES ...... xv

CHAPTER 1 - GENERAL INTRODUCTION ...... 1 ECOLOGICAL NICHE ...... 2 NICHE PLASTICITY ...... 3 ISOTOPIC NICHE ...... 4 INVASIVE SPECIES ...... 5 THE PONTO-CASPIAN ...... 6 OBJECTIVES AND CHAPTER OVERVIEW ...... 7 Study systems and sampling protocol ...... 7 Analysis of isotopic niche ...... 8 Chapter 2 Approach and predictions ...... 8 Chapter 3 Approach and predictions ...... 12 Chapter 4 Approach and predictions ...... 14 Chapter 5 Approach and predictions ...... 16 REFERENCES ...... 20

CHAPTER 2 - NICHE PLASTICITY IN INVASIVE FISHES IN THE GREAT LAKES ...... 27 INTRODUCTION ...... 28 METHODS ...... 30 Study sites and sample collections ...... 30 Stable isotope analysis ...... 31 Statistical analyses ...... 32 Isotopic niche ...... 33 Niche plasticity ...... 35 RESULTS ...... 35 Baseline bivalves ...... 36 Round Goby and Tubenose Goby ...... 36 Trophic position and isotopic niche overlap ...... 37 Isotopic niche breadth ...... 38 Isotopic niche plasticity ...... 39 DISCUSSION ...... 41 REFERENCES ...... 48

x CHAPTER 3 - NICHE BREADTH CHANGES WITH TIME ESTABLISHED, HABITAT COMPLEXITY AND GENETIC DIVERSITY FOR A WIDESPREAD INVASIVE FISH ...... 59 INTRODUCTION ...... 60 METHODS ...... 63 Sample collection ...... 63 Population specific parameters ...... 64 Site-specific habitat parameters ...... 65 Stable isotope analysis ...... 66 Isotopic niche ...... 67 General Linear Models ...... 67 Regressions with year established ...... 68 RESULTS ...... 69 Population specific parameters ...... 69 Site-specific habitat parameters ...... 70 Variation in isotopic niche explained ...... 70 Regressions with year established ...... 72 DISCUSSION ...... 72 REFERENCES ...... 81 SUPPLEMENTAL MATERIAL ...... 96

CHAPTER 4 - CONTRASTING NICHES OF INVASIVE FISHES IN NATIVE AND INVADED REGIONS ...... 105 INTRODUCTION ...... 106 METHODS ...... 109 Study species and regions ...... 109 Stable isotope analysis ...... 110 Statistical analysis ...... 111 Niche metrics and ellipses ...... 112 Baseline community ...... 112 Niche plasticity ...... 113 RESULTS ...... 113 Baseline community ...... 113 Invasive fishes ...... 113 Within region species comparisons ...... 115 Comparisons across all regions ...... 116 DISCUSSION ...... 116 Niches in the invaded region ...... 117 Niches in the native region ...... 119 Contrasting niches in native and invaded regions ...... 120 Habitat suitability and invasion success ...... 122 Conclusions ...... 124 REFERENCES ...... 126 SUPPLEMENTAL MATERIAL ...... 142

CHAPTER 5 - DIFFERENT NICHES IN SUCCESSFUL AND LESS SUCCESSFUL AQUATIC INVASIVE INVERTEBRATES ...... 145

xi INTRODUCTION ...... 146 METHODS ...... 149 Study sites and sample collections ...... 149 Stable isotope analysis ...... 150 Baseline corrections ...... 151 Isotopic niches ...... 152 Statistical analysis ...... 153 RESULTS ...... 153 Invasive tunicates ...... 154 Invasive Cladoceran waterflea ...... 155 Invasive oysters ...... 156 DISCUSSION ...... 156 Invasive tunicates ...... 157 Invasive Cladoceran waterflea ...... 159 Invasive oysters ...... 160 The potential role of invasion history ...... 161 Conclusions ...... 162 REFERENCES ...... 164 SUPPLEMENTAL MATERIAL ...... 176

CHAPTER 6 - GENERAL DISCUSSION ...... 178 MAJOR FINDINGS ...... 180 Contributions to niche theory ...... 181 Habitat niches and invasion success ...... 182 Ecosystem engineers vs ecosystem stability ...... 183 Future distributions ...... 185 FUTURE DIRECTIONS ...... 186 Expanding on niche metrics ...... 187 CLOSING REMARKS ...... 188 REFERENCES ...... 189

Appendix A – REPRINT PERMISSIONS ...... 193

VITA AUCTORIS ...... 196

xii LIST OF TABLES

CHAPTER 2

Table 2.1 Length, weight and stable isotope data (mean ± S.E.), population metrics, SIBER ellipses and ellipse overlap between Round Goby and Tubenose Goby collected at mouth (Mitchell’s Bay) and outflow (Sand Point) of Lake St. Clair and in western Lake Superior (Thunder Bay and Duluth) ...... 53

CHAPTER 3

Table 3.1 Population specific demographic and isotopic niche data for invasive Round Goby (muscle tissue) in the Great Lakes from water bodies with different times since first recorded sighting (Year Est.)...... 85

Table 3.2 Population specific demographic and isotopic niche data for invasive Round Goby (liver tissue) in the Great Lakes from water bodies with different times since first recorded sighting (Year Est.)...... 87

Table 3.3 Shell length (SL) and isotopic niche of baseline primary consumer dreissenids (whole tissue) corresponding to site collections of Round Goby in the Great Lakes...... 88

Table 3.4 Environmental and habitat characteristics of each site corresponding to Round Goby collection in the Great Lakes...... 89

Table 3S.1. Genetic diversity for Round Goby populations and genetic divergence from longest established population in Lake St Clair based on microsatellite data from Wellband and Heath (unpublished)...... 96

Table 3S.2. Statistics output for a General Linear Model Test of Between-Subject Effects on the isotopic niche of Round Goby (muscle tissue) in the littoral Great Lakes basin. .. 97

Table 3S.3. Statistics output for a General Linear Model Test of Between-Subject Effects on the isotopic niche of Round Goby (liver tissue) in the littoral Great Lakes basin...... 99

Table 3S.4. Results from backward variable selection using Akaike Information Criterion (AIC) for each niche metric (Muscle tissue) ...... 101

Table 3S.5. Results from backward variable selection using Akaike Information Criterion (AIC) for each niche metric (Liver Tissue)...... 102

CHAPTER 4

Table 4.1. Stable isotope data of macro-invertebrate baseline community in the Native North West Black Sea and invaded Great Lakes regions ...... 131

Table 4.2. Biometric and stable isotope data for goby fishes (muscle tissue) collected

xiii from the native North West Black Sea and invaded Great Lakes regions...... 132

Table 4.3 Biometric and stable isotope data for goby fishes (liver tissue) collected from the native North West Black Sea and invaded Great Lakes regions ...... 134

Table 4.4 Tissue specific differences (from muscle to liver) in isotopic niche of goby fishes from the native North West Black Sea and invaded Great Lakes regions ...... 136

Table 4S.1 Biometrics and stable isotope data (mean ± S.E.) for macro-invertebrate species collected from the NW Black Sea region and Great Lakes basin...... 142

CHAPTER 5

Table 5.1 Stable isotope data and isotopic niche of successful (Botryllus schlosseri, Golden Star) and less successful (Botrylloides violatious, Violet) invasive tunicates in the North East Atlantic (Nova Scotia) ...... 168

Table 5.2 Stable isotope data and isotopic niche of successful (Bythotrephes longimanus, Spiny) and less successful (Cercopagis pengoi, Fish-hook) Cladoceran waterflea in the Great Lakes region ...... 169

Table 5.3 Body size and isotopic niche of successful (Crassostrea gigas, Pacific oyster) and less successful (Crassostrea virginica, Eastern oyster) invasive oysters in the North East Pacific (Vancouver region) ...... 170

Table 5S.1 Shell length (SL) and stable isotope data (δ13C and δ15N) of bivalve primary consumers used as baseline for spatial and temporal comparison of invasive Cladoceran waterflea in the Great Lakes region and oysters in the North Each Pacific ...... 176

xiv LIST OF FIGURES

CHAPTER 2

Figure 2.1 Collection sites for Round Goby and Tubenose Goby in Lake St. Clair (a) Mitchell’s Bay (September 2011) and (b) Sand Point (October 2012) and western Lake Superior (August 2012), Duluth and Thunder Bay...... 55

13 15 Figure 2.2 Bi-plot of δ C and δ N with Standard Ellipse Areas (SEAC) of bulk muscle and lipid-extracted liver from Lake St Clair (Mitchell’s Bay and Sand Point) and western Lake Superior Round Goby and Tubenose Goby. For same size Round Goby (open circles, solid gray ellipses) and Tubenose Goby (solid gray circles, black ellipses), Round Goby larger than all other fishes (standard Length, p < 0.05 T-Test; open triangle, dashed gray ellipses) and Tubenose Goby significantly smaller than all other fishes (black star and black dashed ellipses). Stable isotope data (Mean ± S.D.) are shown for bivalves from Duluth (black square) and Thunder Bay (black diamond), western Lake Superior. Note different range on the x and y-axis for western Lake Superior. See Table 2.1 for niche metrics, total ellipse areas and ellipse overlap data...... 56

Figure 2.3 Density box-plots of Bayesian estimates of Standard Ellipse Area (SEAB) for bulk muscle and lipid extracted liver tissue for size-matched Round Goby and Tubenose Goby and larger Round Goby (> 6cm) that were significantly larger than all other fishes (T-test, p < 0.05). Note different y-axis maximum for western Lake Superior. Black circles are mode total area (‰2) and grey boxes represent 50%, 75% and 95% credible 5 abc intervals produced from 10 Bayesian iterations of SEA (SEAB). Different lower case letters denote significant difference in SEAB between groups within each location for muscle and liver independently. * Probability of difference between muscle and liver SEAB within each population, higher number denotes higher probability * 0.6-0.69, ** 0.7-0.79, *** 0.8-0.89, **** 0.9-1...... 57

Figure 2.4 (a) Mean difference ± S.E. between bulk muscle and lipid extracted liver δ13C and δ15N in Round Goby and Tubenose Goby in Mitchell’s Bay, Sand Point (both Lake St. Clair) and western Lake Superior. * Significant difference between muscle and liver δ13C or δ15N within each population (paired T-tests) * p < 0.05, ** < 0.01, *** < 0.001. abcd Different lower case letters denote significantly different calculated mean difference of liver and muscle between each group (p < 0.05, ANOVA or independent T-test). (b) Standard Ellipses Areas (SEAC) of bulk muscle and lipid extracted liver (arrows point from muscle to liver) δ13C and δ15N in Round Goby (gray) and Tubenose Goby (black)...... 58

CHAPTER 3

Figure 3.1 Map of sampling sites for invasive Round Goby (Neogobius melanostomus) and dreissenid mussels from the Great Lakes basin collected 2011-2013. See Table 3.1 for year of first recorded sighting of Round Goby in each water body...... 90

xv Figure 3.2 Variation in isotopic niche of invasive Round Goby (a) muscle and (b) liver explained by time of establishment in each water body (Year Est., USGS.org), population specific demographics and site-specific habitat characteristics. Sum of Squares (III) of each variable from General Linear Models Test of Between-subject-effects was used to determine % variation explained. Niche variation is represented by δ13C and δ15N standard error (S.E.), ranges (CR, NR), Bayesian Standard Ellipse Area (SEAB) and 5 standard deviation of SEAB (S.D., from 10 Bayesian iterations). See Table 3S.2 and Table 3S.3 for output summary, Table 3S.4 and Table 3S.5 for most parsimonious model using AIC. SexD= proportional sex diversity, Condition (Kn) = Fulton’s condition factor, Genetic diversity = allelic richness by heterozygosity interaction (Table 3S.1), Year&Month = year and month sampled interaction, Wave Height = mean significant wave height, Water Temp = mean surface water temperature, Substrate = substrate diversity index, Macro&Detr = macrophyte and detritus density interaction, Dreiss 13 15 δ Cb/δ Nb = bootstrapped S.E. and 95% confidence interval range interactions for both δ13C and δ15N of baseline dreissenid mussels at each site/year. Unexplained = variation unexplained by the model...... 91

Figure 3.3 Linear regressions for Round Goby muscle tissue covariate adjusted mean ± 13 S.E. SEAB (a) and δ C S.E. (b) with time of first recorded sighting in the Great lakes. Only isotopic niche metrics that had a significant trend with year of first sighting are shown. Regressions exclude Georgian Bay as a significant outlier (> 3 S.D. of the mean). Estimated means for each water body were produced from 2011-2013 data using GLMs with the covariates total length (TL) and baseline dreissenid mussel S.E.b by 95% CIRb interactions for both δ13C and δ15N. ‘Cov & A Adj’ indicates the trend with time of first sighting and isotopic niche metric following adjustment of the ‘Covariate Adj’ linear regression by the linear regression for allelic richness (A) and time of first sighting. Table 3S.1 for genetic data, Table 3.1 for all other population specific data...... 93

Figure 3.4 Linear regressions for Round Goby liver tissue covariate adjusted mean ± S.E. 13 SEAB (a), δ C S.E. (b) and CR (c) with time of first recorded sighting in the Great lakes. Notice the different maximum on y-axis than in Figure 3. Only isotopic niche metrics that had a significant trend with year of first sighting are shown. Regressions exclude Georgian Bay as a significant outlier (> 2 S.D. of the mean). Estimated means for each water body were produced from 2011-2013 data using GLMs with the covariates total b b length (TL), sexD and baseline dreissenid mussel S.E. by 95% CIR interactions for both δ13C and δ15N.‘Cov & A Adj’ indicates the trend with time of first sighting and isotopic niche metric following adjustment of the ‘Covariate Adj’ linear regression by the linear regression for allelic richness (A) and time of first sighting. Table 3S.1 for genetic data, Table 3.1 for all other population specific data...... 94

Figure 3S.1 Regressions of nitrogen ranges, carbon ranges and SEAB for muscle and liver tissues by Total Length (mm) for Round Goby populations in the Great Lakes Basin. Nitrogen range (top panel), carbon range (middle panel) and SEAB (bottom panel) were calculated for bulk muscle (left panels, a-c) and lipid extracted liver (right panels, d- f) of Round Goby populations collected in 2011, 2012 and 2013 across the Great Lakes Basin. Each symbol represents a site/year of collection. Populations that were prominent outliers in one of the regressions are represented in all the figures using the same symbols

xvi (e.g. black square = Collingwood 2013). Collingwood 2013 and Nanticoke 2013 were not used in regression calculations. Regressions for nitrogen range and carbon range were linear, regressions for SEAB were parabolic...... 103

Figure 3S.2 Variation in sites based on a PCA of environmental and habitat parameters (water temperature, wave height, substrate diversity, Macrophyte density, detritus density, dreissenid baseline δ13C S.Eb. and 95 % CIRb, δ15N S.Eb and 95% CIRn) for (a) muscle tissue sites and (b) liver tissue sites. In both cases, PC 1 summarized 64 % of the data, while PC 2 summarized 24 %. PCAs for muscle and liver were conducted on similar data, with exception for two additional sites for muscle tissue (Sand Point, Lake St Clair in 2011, and South Bay Mouth, Lake Huron in 2012)...... 104

CHAPTER 4

Figure 4.1 Map of sampling sites for goby fishes and macro-invertebrates in the Black Sea drainage (native, Aug 2013) and Great Lakes basin (invasive, June – Oct 2011-2013). Black dots indicate sampling sites. Black star indicates location of first sighting of goby fishes in the Great Lakes (St Clair River, Jude et al. 1992) and sampling site in the Black Sea region which is the estimated location from which invasive goby fishes were predominantly sourced (Stepien et al. 2005). Base map sources: WW F, USGS, Esri, EPA, NOAA...... 137

Figure 4.2 Bi-plot of isotopic niches (ellipses of δ13C and δ15N) for (a) muscle tissue and (b) liver tissue in goby fishes from their native NW Black Sea and invasive Great Lakes regions. Letters denote waterbody/site: A. Dnieper, B. Dniester, C. Danube, D. Sea of Azov. a. Sand Point (Lake St Clair), b. Mitchells Bay (L St Clair), c. Duluth (Lake Superior), d. Thunder Bay (Lake Superior), e. Lake Erie EB, f. Georgian Bay, g. Trent River...... 138

Figure 4.3 Density plots of Bayesian Standard Ellipse Area (SEAB ± 95, 75 and 50 % credible intervals) for goby bulk muscle, lipid extracted liver and baseline invertebrate lipid extracted whole tissue from (a) the North West Black Sea region and (b) Great Lakes basin. Dotted lines denote different water body/region. Letters on the x-axis denote different species: Round Goby (R), Monkey Goby (M), Tubenose Goby (T) and Racer Goby (RA) or, for baseline, different specific sampling locations (See Fig 4.1 for sampling sites)...... 140

Figure 4.4 Mean ± S.E. SEAC, CR and NR from native and invaded region goby fish (a) muscle and (b) liver tissue following baseline corrections. Base used were filter feeders or in one case Gammaridae (for Native Azov Tubenose region only). See Table 4.1 for baseline niche metrics and stable isotope data. See Table 4.2 (muscle) and Table 4.3 (liver) for fish population data including number of fish populations of each species, number of individuals used for each population and significant differences between groups...... 141

CHAPTER 5

Figure 5.1 Map of sites where invasive (a) oysters, (b) Cladoceran waterflea and (c)

xvii tunicates were collected Aug-Nov 2011-2012. See text for sample collection methods and Table 5.1, 5.2 and 5.3 for species and year of collection for each site. Service layer credits for ArcGIS basemap: Esri, DeLome, GEBCO, NOAA, NGDC...... 171

Figure 5.2 Isotopic niche bi-plots (a) and Bayesian density plots (b) of successful invasive violet tunicate (Botryllus schlosseri, sold lines and dark gray boxes) and less successful golden star tunicate (Botrylloides violatious, dashed lines and white boxes). Standard Ellipse Areas (SEAC in bi-plot, SEAB in density plot) were calculated using δ13C and δ15N bivariate data. See Table 5.1 for data and sites corresponding to the figure (first two letters of each site and year of collection are given in the figure). * Indicates significant differences in isotopic niche (SEAB) between successful and less successful invasive species at each site/year * p < 0.05, ** p < 0.01, *** p < 0.001 (i.e. > 95% 105 Bayesian iterations of SEAC)...... 172

Figure 5.3 Isotopic niche bi-plot (a) and Bayesian density plots (b) of successful invasive spiny waterflea (Bythotrephes longimanus) and less successful fishhook waterflea (Cercopagis pengoi). Standard Ellipse Areas (SEAC in bi-plot, SEAB in density plot) were calculated using baseline corrected δ13C and δ15N. See Table 5.2 for data and site names corresponding to the figure (first two letters of each site provided in the figure). Ratio above each density plot indicates total comparisons for which isotopic niche (SEAB) of most successful species was significantly broader (∧) or smaller (∨) than the 5 less successful species (p < 0.05 or > 95% of 10 Bayesian iterations of SEAC)...... 173

Figure 5.4 Isotopic niche bi-plots (a) and Bayesian density plots (b) of invasive oysters: successful Pacific oyster (Crassostrea gigas) and less successful Eastern oyster (Crassostrea virginica). Bayesian Standard Ellipse Areas (SEAB) were calculated using baseline corrected δ13C and δ15N. See Table 5.3 for data and site names corresponding to the figure legends (first two letters of each site presented in figure). * Indicates significant differences in isotopic niche (SEAB) between successful and less successful invasive species * p < 0.05, ** p < 0.01, *** p < 0.001 (i.e. > 95% 105 Bayesian iterations of SEAC)...... 174

Figure 5.5 Total significant differences in isotopic niche between successful and less- successful aquatic invasive species of tunicate, Cladoceran waterflea, oysters and goby fishes. Data presented are % number of comparisons with higher Bayesian standard 5 ellipse area (SEAB, p < 0.05 or > 95% of 10 simulations). SEAB represents core variation (40%) in δ13C and δ15N bivariate population data (baseline corrected for comparisons that involved temporal and spatial comparisons). Total number of comparisons in parenthesis. Comparisons for the less successful oyster species were restricted to one population. Data for comparisons of goby fishes was from Pettitt-Wade et al. (2015). Fish comparisons included two different size groups for the most successful invader. Pooling of data across size groups increased % broader isotopic niche in the most successful invader and reduced % comparisons that were not significantly different...... 175

xviii CHAPTER 1

GENERAL INTRODUCTION

1 The combination of multiple stressors including rapid climate change, habitat fragmentation, over exploitation, spread of disease and invasive species, is currently causing an overall decline in biodiversity (Barnosky et al. 2011). With persistent decline in biodiversity, the destabilization of natural cycles becomes increasingly likely

(Barnosky et al. 2011, Parmesan 2006), which could ultimately catalyze the next mass extinction event (Barnosky et al. 2011, Jablonski 2004). Study of the factors that influence species spread and distribution is essential for understanding how species will respond to these impacts and to avoid further loss of biodiversity. Species distribution is heavily influenced by resource use and species-environment interaction, study of which can provide important insights on the drivers of diversification.

ECOLOGICAL NICHE

A rapidly developing theory in ecology is that geographical range size can be predicted by niche breadth (Slatyer et al. 2013). The term ‘Ecological niche’ is often used to describe how species respond to diversification in resources, environmental conditions and the associated species interactions (Grinnel 1924, Hutchinson 1978). Niche concepts are particularly useful for predicting species range expansion and adaptation to climate change (Atkins and Travis 2010), habitat suitability (Hirzel and Le Lay 2008), dietary niche and trophic structure (Jackson et al. 2011, Layman et al. 2007, Quevedo et al. 2009) and the distribution of invasive species (Broennimann et al. 2007, Peterson 2003, Guisan et al. 2014). Hutchinson (1978) portrayed the physical world, or biotype, as a map with points depicted by geographical space and an n-number of environmental variables at a given time. The same environmental variables depict a species niche space and niche axes, which can be plotted against the biotype map of space and time (Colwell and

2 Rangel 2009, Hutchinson 1978). The above description refers to what Hutchinson termed the ‘fundamental niche’; which occurs without the presence of such negating factors as competition and predation. A ‘realized niche’ is the niche of a species when it is subject to negating factors, such as competition and predation (Colwell and Rangel 2009,

Hutchinson 1978), which is generally the case in nature.

The ultimate goal in the study of ecological niches should be to develop a comprehensive database of dynamic multi-dimensional niches for different functional groups in space and time (Winemiller et al. 2015). This lofty goal has limited feasibility in studies of natural systems, particularly when spatial and temporal variation is incorporated. Focus on individual niche axes, such as diet, can provide an extensive and realistic understanding of ‘dietary niche’ for a specific set of organisms. One can then determine the relative influence of, for example, population demographics, or the abiotic environment, to bring the single niche axis analysis closer to a multi-dimensional niche.

Ecological niche metrics are dynamic in space and time (Pearman et al. 2008) and understanding the factors that drive variation in niches provides for wider applicability of the findings and potential implications.

NICHE PLASTICITY

The modern conception of an individuals niche allows that circumstantial changes can occur, termed ‘niche shifts’ (Pearman et al. 2008). A change in relative experience can result in different biotic and abiotic adaptive responses due to a stretch of tolerance levels (Atkins and Travis 2010, Holt 2009). An organism’s ability to respond to the environment is heavily influenced by their phenotypic traits, and a niche breadth analysis can highlight traits that are beneficial in a given situation. As a measure of phenotype, a

3 shift in relative niche can indicate the phenotypic potential for adaptation or plasticity:

such as the introduction of a highly competitive non-native species and the subsequent

loss of a dietary item (Broennimann et al. 2007, Ingram et al. 2012).

Diet-derived phenotypic plasticity can occur over a relatively short period of time;

such as decadal changes in the beak shape of Galapagos finches (Grant and Grant, 2002),

sunfish morphology Lepomis humilis (Hegrenes 2001) and common carp Cyprinus carpio

invasive in the Great Lakes (Rahman 2010). Furthermore, trophic and habitat niches can

indicate generalist or specialist behaviour, species interactions and food web inter-

connectivity (Quevedo et al. 2009). Shifts in trophic and habitat niches are closely

associated with behavioural flexibility (Sol et al. 2002). But the study of natural systems

often entails an array of complexities, which poses a particular challenge in the aquatic

realm due to the difficulty of observing interactions directly.

ISOTOPIC NICHE

A method of determining niche breadth that incorporates both trophic and habitat

niches is through the use of stable isotopes of carbon and nitrogen (Newsome et al.

2007). Stable isotopes are presented in delta (δ) notation, which depicts the ratio of heavy

to light isotope relative to standard reference materials. Nitrogen14 – Nitrogen15 (δ15N) indicates trophic position and Carbon13 – Carbon14 (δ13C) indicates the habitat of

resources consumed, such as littoral or pelagic resources (Post 2002). These metrics are

particularly useful when examined in combination with, for example, a bi-plot of δ13C on the x-axis and δ15N on the y-axis. This method can be used to determine generalist and

specialist feeding strategies, trophic interaction and resource competition (Post 2002).

The spread and extent of data points on the bi-plot can be used to depict population and

4 community metrics for an analysis of trophic and habitat niche breadth (Jackson et al.

2011, Layman et al. 2007, Quevedo et al. 2009). Use of stable isotopes to study ecological niche has shown considerable potential in studies of species interaction

(Karlson et al. 2007; Meckstroth et al. 2007, Newsome, et al., 2007) and fitness for survival (Darimont et al. 2007, Ingram et al. 2012). Furthermore, different tissues assimilate stable isotopes at different rates and can therefore indicate different time periods of diet history (Bearhop et al. 2004, Newsome et al. 2007).

INVASIVE SPECIES

Niche breadth analysis has shown particular promise in the study of invasive species (Broennimann et al. 2007, Meckstroth et al. 2007, Peterson 2003, Vázquez 2006).

Invasive species are species that cause harm to ecosystems and/or economy and are most often associated with anthropogenic introduction. Dietary niche breadth is often suggested to have important implications for successful establishment (Bergstrom and

Mensinger 2009, Polacik et al. 2009, Reid and Orlova 2002), but evidence for the importance of niche breadth for post-established spread is currently inconclusive (Hayes and Barry 2008). There is also a disproportionate focus on terrestrial primary producers in the invasion literature (Lowry et al. 2012), and a particular need for studies on aquatic systems that incorporate multiple scales and species.

The anthropogenic spread of invasive species continues to occur on a scale that is unprecedented in the geological record, and in a long list of multiple stressors is always considered a top priority (Ricciardi 2007). Invasive species are often suggested to have traits that promote survival in challenging environments (Rahel and Olden 2008, Reid and Orlova 2002), and species ranges are shifting at increasing rates due to rapidly

5 changing climates and habitat fragmentation (Atkins and Travis 2010, Parmesan 2006). It is, therefore, apparent that study of what drives post-established spread of invasive species is not only informative for predicting potential impact, but also for understanding general mechanisms of species spread and distribution. Moreover, it is necessary to determine the factors that determine the current distribution of species to provide a metric for comparison of distributions in the future.

THE PONTO-CASPIAN

A significant portion of this dissertation involves comparisons of invasive species that originate in the Ponto-Caspian. Successful establishment of invasive species in the comparatively (geologically) young Laurentian Great Lakes (hereafter Great Lakes) and

Baltic Sea is partly due to the current similarity in conditions to the Ponto-Caspian where many of the species originated, predominantly via the ballast of transoceanic ships

(Kornis et al. 2012, Reid and Orlova 2002). The prevalence of invasive species from the

Ponto-Caspian is suggested to be a factor of high phenotypic and genetic diversity from a complex geological history (Reid and Orlova 2002). Repeated geological separation and reforming of water bodies in the region has led to multiple speciation events (Brown and

Stepien 2008, Reid and Orlova 2002), and the formation of one of the most diverse fish taxa: the Gobiddae, >2000 species in >200 genera (Miller 1986) with a broad and globally expanding geographical distribution (Kornis et al. 2012). Interestingly, a broad geographical distribution is also the only common trait found in species that survive mass extinction (Jablonski 2004). The only commonality in species that avoid extinction in general includes a list of traits that gobiids have also acquired: diverse genera, pelagic juvenile dispersal and a benthic burrowing lifestyle (Jablonski 2004). Given the current,

6 and projected continuation, of a global decline in biodiversity (Barnosky 2011), research on species that share traits with those that survive extinction could prove particularly useful for determining future patterns in diversity.

OBJECTIVES AND CHAPTER OVERVIEW

Aquatic invasive species are the focus of this research, with success defined by the speed, distance and abundance of post-established spread. The overriding objective of this dissertation was to investigate for variation in the relative isotopic niches of successful and less successful aquatic invasive species. Variation in isotopic niche within and among individuals, populations, and across spatial and temporal scales, was used as a measure of potential for phenotypic plasticity in relation to trophic and habitat niche.

Variation in trophic and habitat niche was predicted to be a key determinant of success, but to hold greater importance for fishes than more sessile organisms due to the likelihood of mobile organisms encountering a broader variety of prey.

The first research chapter of this dissertation focuses on niche differences between sympatric gobies in invaded Great Lakes (Chapter 2), the combined and interactive effects of establishment time, genetic diversity, environmental heterogeneity and demographics on isotopic niche (Chapter 3), niche variation between populations of goby fishes in their native and invaded ranges (Chapter 4), and niche variation between pairs of successful and less successful aquatic invasive invertebrates (Chapter 5).

Study systems and sampling protocol The isotopic niche of goby fishes was investigated for variability across the invaded distribution in littoral regions of Great Lakes (Chapter 2 and 3) and in native

Ukraine (Chapter 4). Invasive invertebrates (Chapter 5) were compared from their

7 invaded distributions in the Great Lakes (waterflea), North Western Atlantic coast

(tunicates) and North East Pacific coast (oysters). Fish were obtained using seine nets,

rod and line, and minnow traps. Cladoceran water fleas were collected using plankton

nets (750um or 250um mesh). Oysters and tunicates were obtained by benthic trawl.

Primary consumers were collected by hand, using grabs or benthic trawl to use as a

reference for spatial and temporal comparisons of stable isotope data.

Analysis of isotopic niche Stable isotope data was compared among individuals, populations and species to

determine the relative importance of trophic niche (δ15N) and habitat niche (δ13C) for post-established spread in aquatic invasive species. Isotopic ratio mass spectrometry

(IRMS) was used to determine δ13C and δ15N. Spatial and temporal comparisons of stable isotope data should be conducted in association with data on primary consumers as a baseline (Post 2002). Baseline organisms used in this dissertation are primarily dreissenid mussels (Zebra/quagga mussels; Dreissena polymorpha/bugensis) in the Great Lakes and

Ukraine, and blue mussels (Mytilus sp.) in Nova Scotia and BC. Muscle and liver tissue

δ13C and δ15N of goby fishes was compared to infer changes in diet through time (i.e. diet plasticity). Bayesian ellipses of bivariate δ13C and δ15N data were used to compare

population isotopic niche breadth in relation to variability in δ13C and δ15N individually

(Jackson et al. 2011).

Chapter 2 Approach and predictions Main objective: Determine variability in isotopic niche between populations and species

of successful invasive Round Goby (Neogobius melanostomus) and less successful

Tubenose Goby (Proterorhinus semilunaris) in invaded Great Lakes

Hypotheses:

8 H1: Greater niche breadth and plasticity in Round Goby compared to Tubenose

Goby

H2: Differences are accentuated when comparing adult (large) Round Goby to adult

Tubenose Goby

H2: Overlap in isotopic niche is predicted to be associated with a restricted niche in

similar size individuals of Round Goby and Tubenose Goby

Data chapter 2 involved pair-wise comparisons of the isotopic niche of successful

Round Goby and less successful Tubenose Goby to test whether more successful invasive species incorporate a broader niche. Comparisons were made between populations of the two species and within the same species, although due to the limited range of Tubenose

Goby, the majority of intra-specific comparisons were restricted to the Round Goby.

Neogobius and Proterorhinus are suggested to have diverged 5.2 ± 1 million years ago, likely during isolation of the Paratethys basin (now Black Sea) from the Mediterranean

Tethys Sea (Dillon and Stepien 2001). In the Great Lakes, Round Goby and Tubenose

Goby were first sited in the early 1990’s in the St Clair River (Dillon and Stepien 2001,

Kornis et al. 2012). Like many invasive species, it is generally accepted that they were transported via ballast water from Europe following invasion through European waterways from the Black and Caspian seas (Brown and Stepien 2009). Round Goby have established in a far greater number of locations and attained much higher abundance than seems to be the case for Tubenose Goby in the Great Lakes, and throughout

European waterways (Dillon and Stepien 2001, Naseka et al. 2005). I aim to investigate the importance of trophic and habitat niche for the more successful post-established

9 spread of Round Goby compared to Tubenose Goby, and as crucial factors for survival of species in novel environments.

There are limited published studies on the Tubenose Goby in the Great Lakes

(Dillon and Stepien 2001, French and Jude 2001, Jude et al. 1995, Leslie et al. 2002,

Neilson and Stepien 2009), in comparison to the considerably more successful Round

Goby (See Kornis et al. 2012 for review of Round Goby literature since Great Lakes invasion). Round Goby success is partly attributed to being aggressively territorial as adults, diurnal feeding, and populations grow rapidly and form dense aggregations

(Kornis et al. 2012). Round Goby also adopt pelagic dispersal as juveniles but otherwise have a benthic lifestyle, live in nests and burrows, and are from a highly diverse genus

(Kornis et al. 2012). These latter traits are common in species that survive extinction in the geological record, as is a broad geographic range with species that survive mass extinction (Jablonski 2004).

Prey home range and habitat are crucial aspects that can influence trophic and habitat niches of the predator. In the Great Lakes, Round Goby exhibit an ontogenetic shift towards dreissenids driven by gape size (Ray and Corkum 2001). Although, using stable isotope analysis (δ13C and δ15N), Brush et al. (2012) suggested gut contents analysis has led to the overestimation of dreissenids and that other dietary items hold higher importance; particularly chironomids, amphipods and cladocerans. Brush et al.

(2012) studied Round Goby from < 2m of water, and some evidence suggests dreissenids are fed on the most in 5-7m of water where they are most abundant (French and Jude,

2001). In tributaries of Lake Erie, where dreissenids are not present, Round Gobies seem to remain as generalist invertivores with a small preference for midges (Krakowiak and

10 Pennuto 2008). Although rather than preferred, dreissenids have been suggested to be

dominant in the diet of Round Goby due to lower encounter rates with other prey

(Diggins et al. 2002, Raby et al. 2010). Such an opportunist could utilize a more narrow

spatial range if easy to catch prey are abundant across a narrow range, and all other prey

are too difficult to catch (Diggins et al. 2002, MacArthur and Pianka 1966). It has

therefore been suggested that adult Round Goby are opportunistic-specialists for

dreissenids within a generalist population (Raby et al. 2010). These ontogenetic shifts

indicate the importance of body size for the niche breadth of this invasive fish, and an

important parameter to consider in comparison of Round Goby and Tubenose Goby.

In the Great Lakes, Tubenose Goby are suggested to have a similar diet to Round

Goby but without the molluscs because they lack the appropriate gape morphology

(French and Jude 2001). French and Jude (2001) also found that Tubenose Goby favor

habitats with macrophytes over anything else, which could drive differences in δ13C (i.e. variation in diet-derived habitat) compared to Round Goby. Due to their specific habitat preferences and unique morphology with smaller gape size (Pinchuk et al. 2004); a smaller niche is predicted for Tubenose Goby compared to Round Goby where they occur in sympatry. Fewer differences are predicted for trophic and habitat niches in similar size fish. Evidence of niche overlap is expected to reduce as Round Goby exceed the size of Tubenose Goby and switch to more prey outside the gape size of Tubenose

Goby. Overall, higher intra-population variability in relative niche is predicted for more successful Round Goby compared to less successful Tubenose Goby.

11 Chapter 3 Approach and predictions Main objective: Determine if there is an association between isotopic niche breadth and time since first recorded sighting of Round Goby in the invaded Great lakes, in relation to population specific demography, environmental heterogeneity and genetic diversity.

H1: Broader niches are predicted for longer established goby populations than

populations in more recently established locations

H2: Decreasing genetic diversity with distance from longest established locations is

predicted to correlate with decreasing niche breadth

H3: Variation around any trends between time established and niche breadth is

predicted to associate with population specific demographics, environmental

heterogeneity, habitat complexity and genetic diversity

H4: Liver tissue (short term integration of diet) is predicted to represent more

variation in association with the environmental, habitat and demographic

covariates than muscle tissue (long term integration of diet)

Time is a crucial resource for species that are introduced or spread to novel environments. More time provides more opportunity for an adaptive or plastic response to the environment and resources available. Successful invasive species spread rapidly across broad geographic distances and provide a model for understanding the interaction between population specific characteristics and environmental complexity through time

(Guisan et al. 2014). In Chapter 3, I investigate the relationship between time since first recorded sighting of the invasive Round Goby and their isotopic niche breadth in invaded littoral areas of the Great Lakes. ‘Optimal foraging theory’ implies that through time, species are able to develop a foraging strategy that is closer to optimum (Pyke 1984).

This could mean specialization for specific prey items (restricted niche), or branching out

12 to feed on novel prey (broad niche). The latter is more likely to occur in the absence of favoured prey choices. Round Goby occurs in high densities (Johnson et al. 2005), is a ferocious competitor for prey (Bergstrom and Mensinger 2009, Karlson et al. 2007) and establishment of Round Goby is often associated with a change in the macro-invertebrate prey community (Barton et al. 2005, Krakowiak and Pennuto 2008, Kuhns and Berg

1999). Conversely, longer time in invaded regions would also be associated with increased adaptive response of native competitors and predators. Round Goby is considered to be fully integrated into many Great Lakes food webs, and provides an important prey resource for many species with important implications for ecosystem wide energy dynamics (Rush et al. 2012) and the abundance of toxins in higher trophic levels

(Hebert et al. 2014).

Broad scale patterns in resource use could be distorted by spatial and temporal variation in environmental complexity or facilitated transport events. These processes are particularly important to consider when interested in the importance of time spent in invaded regions because they indicate the conditions that could limit or promote spread and diversification. Furthermore, environmental complexity is directly associated with resource use and species abundance and diversity (Sakai et al. 2001). For Round Goby specifically, substrate, turbidity and flow are important for prey availability (i.e. dietary niche) and the demographic structure of Round Goby populations (Cooper et al. 2009,

Ray and Corkum 2001). Round Goby are tolerant of extremely low hypoxic conditions, but have a limited thermal optimum (Charlebois et al. 1997) that could influence relative body condition and prey consumption.

13 Populations of the invasive Round Goby have been found to have reduced genetic diversity and relatedness at progressive distances from the location of first recorded sighting (Bronnenhuber et al. 2011, Wellband and Heath unpublished). This is an important consideration since time of first recorded sighting has a close association with distance from initial introduction, although broken up by jump dispersal events

(Bronnenhuber et al. 2011, Kornis et al. 2012). Moreover, genetic diversity can have important implications for population structure and phenotypic variability within a population (Sakai et al. 2001). The association between ecological and genetic characteristics of populations of invasive species across invaded distributions relative to their interaction with environmental complexity can provide important insights on the evolutionary relevance of this dissertation. It is important to note that this is not an examination of genotype-phenotype interaction, but rather, this chapter investigates the role of population genetic diversity and environmental complexity in shaping population niche breadth through time. It was hypothesised that niches are broader in longer established populations than more recently established. This general trend is predicted despite temporal and spatial variation in environmental complexity. These parameters are hypothesised to have a greater influence on short-term diet history (inferred from stable isotopes in liver tissues) than long-term (muscle tissue), in association with seasonal variations in prey diversity and reproduction.

Chapter 4 Approach and predictions Main objective: Determine variability in isotopic niche within and among populations of goby fishes in native Ukraine compared to invasive populations in the Great Lakes.

14 H1: Most successful Round Goby have the broadest isotopic niche compared to less

successful invasive gobies in native Ukraine

H2: Greater differences in isotopic niche with less overlap between fishes is

predicted for populations of goby in their native region compared to the

invaded region

H3: Populations of invasive fishes have broader isotopic niches in the native region

than in invaded Great Lakes

The Ponto-Caspian is the native region of the successful Great Lakes invaders:

Round Goby and Tubenose Goby (Brown and Stepien 2009). In Europe, several other

Ponto-Caspian Gobiidae have successfully established, but to date have not been discovered in the Great Lakes (Borza et al. 2009, Polacik et al. 2009, Simonovic 2001).

This study further investigates the relationship between niche breadth and widespread establishment, with a comparison of relative niche width of Gobiidae in the native

Ukraine and invaded Great Lakes. Focus remained on comparison of Round Goby and

Tubenose Goby. Native region comparisons also involved Monkey Goby (Neogobius fluviatilis) and Racer Goby (Babka gymnotrachelus) that have not invaded the Great

Lakes, but are invasive throughout Europe. Body size and stable isotopes were used to determine relative isotopic niche of different populations and species. Collections concentrated on locations suggested to be the primary source of invasion of Gobiidae in the Great Lakes (Brown and Stepien 2009).

Comparison of the phenotype in native and invaded habitats provides a means for determining the influence of phenotypic potential for plasticity on ability to tolerate novel environments. Phenotypic diversity is thought to play a pivotal role in invasion success.

15 Ponto-Caspian species are suggested to have developed traits that favour invasion success from the continual geological separation and reforming of water bodies, driving species diversity (Reid and Orlova 2002). High genetic diversity is apparent for Round Goby in the native Ponto-Caspian and at many invaded locations (Brown and Stepien 2009), indicating the likelihood of high phenotypic diversity. Since the invasion of goby in the

1990’s, several laws have passed to reduce introductions to the Great Lakes via ballast water exchange (Holeck et al. 2004). Reduced transport of propagules to the Great Lakes would create a barrier to gene flow between invaded and native region populations, which could have supplemented niche diversification.

I hypothesize the success of Round Goby is facilitated by a variable trophic and habitat niche among populations, which provides high potential for plasticity and adaptation. Reid and Orlova (2002) also suggest diet, and associated habitat selection, is an important parameter adding to the success of aquatic invaders from the Ponto-Caspian, but point out there are conflicting findings in the literature. Polacik et al. (2009) suggested success of Round Goby in the Danube is facilitated by use of broad food resources. The relative niche of goby in native Ponto-Caspian is hypothesized to be larger than in the invaded Great Lakes. This is partly due to an expected reduction from native to invaded regions in the diversity of phenotypes that associated with feeding ecology.

Similar size native Round Goby and Tubenose Goby are also predicted to have less overlapping niches than similar size non-native goby populations.

Chapter 5 Approach and predictions Main objective: Determine variability in isotopic niche within and among populations of successful and less successful aquatic invasive species pairs of colonial tunicate,

Cladoceran waterflea and oyster.

16 H1: A broader isotopic niche is predicted for the more successful invasive species

of each pair

H2: Less variation in isotopic niche is predicted within sessile suspension feeders

(tunciates and oysters) than mobile active foragers (waterflea and goby).

The focus of Chapter 5 is to test the generality of the hypothesis that more successful aquatic invasive species incorporate a broader trophic and habitat niche.

Isotopic niches from δ13C and δ15N were compared and contrasted for multiple populations of successful and less successful matched pairs of invasive invertebrates.

Successful and less successful (respectively) matched pairs of invasive invertebrates in this dissertation are violet tunicate and golden star tunicate (Botrylloides violaceus /

Botryllus schlosseri, respectively) in the North West Atlantic; Pacific oyster and Eastern oyster (Crassostrea gigas / Crassostrea virginica) in the North East Pacific; spiny waterflea and fishhook waterflea (Bythotrephes longimanus / Cercopagis pengoi) in the

Laurentian Great Lakes basin. Interestingly, the geological record demonstrates it is predominantly invertebrates that survive extinction with the aforementioned common traits to goby fishes (Jablonski 2004).

Studies on the trophic and habitat niche of invasive invertebrates are relatively rare, particularly for sessile suspension feeders (Hayes and Barry 2008). Invertebrates are rarely the focus of studies that measure isotopic niche, or use carbon and nitrogen stable isotopes as a tool in general (although see Haines and Montague 1979 and Montague et al. 1981), but are often involved as baseline organisms for temporal or spatial comparisons (Post 2002), or as dietary components to fish (e.g. Spurgeon et al. 2014).

Stable isotope analysis of oysters is more common than the other species pairs in our

17 study, mainly due to their popularity in aquaculture (e.g. Marín Leal et al. 2008; Piola et

al. 2006), and because of their recognized role in nutrient cycles and ecosystem

functioning (Montague et al 1981, Peterson 1999, Peterson and Fry 1987). Studies

involving stable isotope analysis of tunicates or waterflea are most often part of a

community wide food web assessment (Dauby et al. 1998, Sierszen et al. 2014), and

stable isotope analysis of tunicates is particularly rare (but see Duineveld et al. 2007).

Both species of tunicate in this dissertation have invaded both East and West

coasts of Canada (Lejeusne et al. 2011). Golden star tunicates were most likely

introduced via hull fouling to west and east coasts of North America from the Pacific and

Mediterranean regions, respectively (Lejeusne et al. 2011). North American violet

tunicate populations all came from one or more founding introductions from Japan, most

likely predominantly transported unintentionally in the aquaculture trade (Bock et al.

2011, Lejeusne et al. 2011). Despite these differences in invasion histories both species

lay dormant for a period proceeding invasion before rapidly spreading throughout east

and west coasts of North America (Lejeusne et al. 2011). Most likely due to the smaller

number of founding introduction events, the violet tunicate is reported to have a lower

genetic diversity than golden star tunicate (Lejeusne et al. 2011). This could lead to lower

phenotypic diversity, narrower trophic and habitat niche, and less variability between

populations than for genetically diverse golden star tunicate.

Using δ13C and δ15N, Marín Leal et al. (2007) determined the food sources of cultivated Pacific oyster (C. gigas) in two contrasting trophic environments in Normandy

(France). Isotope composition of oyster flesh was shown to vary depending on the source of organic matter, time of year and type of ecosystem and results led to a general

18 consensus that Pacific oyster is an opportunistic suspension feeder (Marín Leal et al.

2007, Riera and Richard 1996). Studies on Eastern oyster are rare in comparison to the

Pacific oyster, although there is particular interest in the role of Eastern oyster in the

spread of disease (Kennedy 1996). In experiments testing the effect of reduced ambient

food concentrations in dense aggregations of shellfish on condition index, significant

effects on growth and condition index were observed in the Easter oyster in reduction

from as little as 27% from relatively high ambient food concentrations (Rheault and Rice

1996).

Comparative studies of the spiny waterflea and fishhook waterflea are also

uncommon. The two species are closely related, but fishhook waterflea is much smaller

than spiny waterflea (Rivier 1998). Analysis of δ13C and δ15N indicated a considerable shift in the trophic level of herring in a Baltic Sea bay following invasion by the spiny waterflea, suggesting significant alteration had occurred to food web structure due to competition for food resources with spiny waterflea (Gorokhova et al. 2005). The spiny waterflea is also a highly effective predator with ability to consume a considerable range of prey sizes (Foster and Sprules 2010, Schulz and Yurista 1999, Witt and Caceres 2004).

Laboratory studies indicate spiny water flea will consume fishhook waterflea, but field studies are yet to support this finding and it is expected that natural encounter rates between these species are rare (Witt and Caceres 2004). Stable isotope analysis of these species could also help determine their trophic role in the food web and potential predator prey interactions that are currently predominantly inferred from temporal changes in native prey species (Benoít et al. 2002, Laxson et al. 2003).

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26 CHAPTER 2

NICHE PLASTICITY IN INVASIVE FISHES IN THE GREAT LAKES

27 INTRODUCTION

Invasive species are one of the leading causes of extinction in the world and second only to habitat destruction for North American fishes (Clavero and García-

Berthou 2005, Jelks et al. 2008). Habitat destruction often facilitates further successful establishment of invasive species (Marchetti and Moyle 2001, Marvier et al. 2004;

Ricciardi 2001, Shea and Chesson 2002) and invasive species themselves are often ecosystem engineers that dramatically alter habitats from their pre-invasion state (Jude and DeBoe 1996, Karlson et al. 2007). Extensive establishment in invasive species is often associated with flexible habitat use facilitated by a broad diet and environmental tolerance (Marvier et al. 2004, Shea and Chesson 2002); thus, higher temperatures from global warming during the last century and increasing fragmentation from habitat destruction could provide a catalyst for further biological invasions (Harka and Bíró

2007).

Some invasive species are more widely established than others, despite retaining apparent similarities and a certain degree of relatedness. Study of the traits of widespread and rarely established invasive species can provide insights on the drivers of geographic spread and establishment success (Van Kleunen et al. 2010). High genetic and phenotypic diversity are often suggested to be important in the survival of populations following introduction events (Reid and Orlova 2002, Stepien et al. 2005); and variability in phenotype can provide scope for phenotypic plasticity, acclimation or adaptation (Holt

2009). Analysis of ecological niche is regularly used as a method for studying variation in phenotype and resource use (Moyle and Marchetti 2006, Peterson and Vieglais 2001).

28 A broad ecological niche driven by flexible diet and habitat use is often considered to be

important for successful colonization, establishment, and spread of invasive species

(Peterson and Vieglais 2001). The use of carbon (δ13C) and nitrogen (δ15N) stable

isotopes is common in studies of diet history, trophic ecology, and food web dynamics of

fishes (Brush et al. 2012, Post et al. 2007, Vander Zanden et al. 1997) and stable isotopes

are increasingly used to depict dietary niche and diet-driven habitat niche (e.g. Guzzo et

al. 2013, Jackson et al. 2012). This technique proves particularly useful for comparing the

breadth of resources assimilated by different populations where they overlap in

distribution. Due to the different assimilation rates of tissue, and thus stable isotope, the

comparative analysis of multiple tissues can provide an indication of seasonal changes in

diet, diet plasticity, and generalist and specialist feeding strategies (Bearhop et al. 2004).

Therefore, we investigated dietary driven differences in ecological niche of two invasive

fish species using δ13C and δ15N.

The Gobiidae are one of the largest fish families with over 2500 species in over

200 genera and include the widely established Round Goby (Neogobius melanostomus) and narrowly established Tubenose Goby (Proterorhinus semilunaris) that are both invasive in the Laurentian Great Lakes (Miller 2004). Round Goby and Tubenose Goby were first discovered in the St Clair River in 1990 and were probably established in Lake

St Clair by this time (Jude et al. 1992). Round Goby has since established in high densities throughout much of the Great Lakes (Kornis et al. 2012), whereas, Tubenose

Goby has remained restricted to Lake St Clair, Lake Erie and western Lake Superior

(Vanderploeg et al. 2002, see USGS 2014 for detection data). The co-occurrence of these two gobiids provides an excellent opportunity to determine the traits that are most

29 prevalent in species that survive novel environments. Furthermore, comparison of these

two species where they overlap in distribution can help us understand the factors that

enable two similar species to share the same habitat space.

The aim of this study was to compare the relative diet plasticity and niche of

Round Goby and Tubenose Goby using stable isotopes. Liver and muscle of each species

and population of gobies were analyzed for δ13C and δ15N to quantify 'isotopic niche breadth'. The different assimilation rates of isotopes in tissues (liver, muscle) were utilized to represent change in diet over time and thus plasticity in trophic niche

(variation in δ15N) and diet-driven habitat niche (variation in δ13C). We hypothesized that the more successful (widely established) Round Goby would have a broader isotopic niche and greater niche plasticity than the less successful (narrowly established)

Tubenose Goby. Analysis of phenotypic traits is integral to a better understanding of the factors that drive greater establishment success in invasive species. Study of niche breadth and niche plasticity can help determine which species are more likely to persist, as on-going climate change and habitat destruction lead to novel environments and continue to threaten the stability of ecosystems and the maintenance of biodiversity.

METHODS

Study sites and sample collections Samples of Round Goby, Tubenose Goby, and bivalves were collected from the littoral edges of Lake St. Clair and western Lake Superior (W. Lake Superior; Fig 2.1).

Mitchell’s Bay is at the edge of a river delta in Lake St Clair and Sand Point is at the head of the Detroit River. In Thunder Bay, Tubenose Goby was collected from Mission Marsh near the mouth of the Kaministiquia River, and Round Goby was collected from within

30 the Duluth Harbor basin at the head of the St. Louis River. Gobies were collected using a

bag seine net (Model SEM-03: 15.2m long, 1.2m tall with 1.2 x 1.2 x 1.2m cod end and

6.4mm mesh. Franklin Net and Twine, Wheatley, ON), angling, and minnow traps (42cm

torpedo with 53cm openings). Fishes were euthanized, bagged individually, placed on

ice, and returned to the laboratory where measurements were taken before freezing to -

40°C (wet weight ± 0.1g; total length and standard length minimum ± 0.1mm using

150mm calipers). Whole fishes were later thawed, and skinless and boneless dorsal

muscle and liver tissue were removed and re-frozen before freeze-drying. Fishes were

sexed by external urogenital papilla (Miller 2004). Many individuals were too small to

accurately sex and were deemed immature; papilla is generally visible at > ~15mm in

Tubenose Goby (Leslie et al. 2002) and > ~20mm in Round Goby (Leslie and Timmins

2004).

Primary consumers are considered to be the most appropriate baseline for spatial

and temporal comparison of δ13C and δ15N (Guzzo et al. 2013, Post 2002). Bivalves were collected from each site (10 - 30 per location, Zebra Mussel/Dreissena polymorpha from

Lake St Clair and Duluth; unionids from W. Lake Superior, not identified to species level), kept on ice, then frozen to -40°C in the laboratory. Bivalves were later thawed, weighed (tissue wet weight ± 0.1g), measured (shell length and shell width ± 0.1mm), tissue and shell separated, frozen to -80°C, and freeze-dried. Similar-size individual bivalves were matched for comparison between locations and whole individual tissue samples were run for stable isotope analysis.

Stable isotope analysis All dried tissue samples were ground to homogenous sample using mortar and pestle and scissors. Fish liver and bivalve whole body tissues were lipid extracted

31 (Solvent Distillation Method: 2x agitation of tissue in 2:1 chloroform/methanol solution

for 24h, solvent decanted, sample air dried; modification of method outlined by Bligh and

Dyer 1959). Muscle tissues were not lipid extracted due to low lipid content based on

C:N ratio < 3.5 in gobies (Post et al. 2007). Samples were weighed into 5mm x 9mm tin

cups (400-700µg per sample; ± 1µg). Samples and standards were then run for δ13C and

δ15N, C% and N%, using a Delta V IRMS (Thermo Electron Corporation, Waltham,

Massachusetts, USA) equipped with an elemental analyzer (Costech, Santa Clarita,

California, USA). The abundances of carbon and nitrogen isotopes in each sample were expressed in delta notation relative to standard materials, using the following equation:

δR (‰) = (Rsample/Rstandard – 1) x 1000

where R is the ratio 15N/14N or 13C/12C. Standard reference materials were Pee Dee

Belemnite (PDB) carbonate for CO2, and atmospheric nitrogen for N2. NIST standard

8414 and an internal fish muscle standard (Nile Tilapia, Oreochromis niloticus) were

analyzed every 12th sample. To assess repeatability every 10th sample was run in triplicate. Precision of analysis based on the standard deviation of the two reference standards ranged from 0.07 ‰ to 0.08 ‰ for δ13C and 0.12 ‰ to 0.13 ‰ for δ15N (NIST

8414 and Nile Tilapia muscle standards, respectively; n = 247). Accuracy based on the

difference between our NIST standard data and certified data for NIST standards ranged

from 0.03 ‰ to 0.14 ‰ for δ13C (NIST 8542, 8573) and 0.05 ‰ to 0.31 ‰ for δ15N

(NIST 8573, 8548, 8547).

Statistical analyses As Round Goby grow to a larger size than Tubenose Goby and a size-related ontogenetic dietary shift is often reported to occur in Round Goby (Kornis et al. 2012), multiple groups were formed for statistical comparison based on size class in relation to

32 the size range of Tubenose Goby. Significantly different groups were determined using

box-whisker plots of standard length and wet weight and Student T-tests. An additional

group was formed for a small subset of Tubenose Goby that were within the size range of

young-of-year (YOY) Tubenose Goby in the Great Lakes (Leslie et al. 2002) and

significantly smaller than all other fishes in this study (Thunder Bay only, Student T-test,

p < 0.05). In summary, the following groups were formed: i. Round Goby matched in

size with Tubenose Goby; ii. Tubenose Goby matched in size with Round Goby; iii.

Round Goby significantly larger than all other fishes; and, iv. Tubenose Goby

significantly smaller than all other fishes. Standard length (or shell length), δ13C and δ15N

of each size group from each location were found to not differ significantly from a

normal distribution (Kolmogorov-Smirnov) or homoscedastic variance (Levene’s).

Standard length, δ13C, δ15N and sex of each population in each location were compared independently for liver, muscle tissue and whole bivalve tissue using MANOVA followed by post-hoc least significant difference (LSD) pairwise comparisons for each variable. Cohen’s power analysis was used to determine the influence of sample size, which gives a value ranging from 0 (strong effect) to 1 (no effect). For power < 0.8, samples were bootstrapped (n = 2000) and the comparison repeated. Statistical analyses were conducted in SPSS v.22 or R v.3.1.0. Significance threshold of p < 0.05 was used for all statistical analyses.

Isotopic niche To compare niche breadth of the two goby species at the different locations, ellipses of δ13C and δ15N bi-plots were constructed using a multivariate Bayesian package in R (Stable Isotope Bayesian Ellipses in R – SIBER; Jackson et al. 2011). Measures of variability in mean δ13C and δ15N of all samples at each location were used as a proxy for

33 the limits to niche breadth for the goby populations. In the SIBER package, these metrics

are based on five community metrics originally developed by Layman et al. (2007) that

represent key aspects of trophic structure. Standard Ellipse Area’s (SEA’s) are used as a

measure of mean isotope variability. The SEA of bivariate data is calculated from the

variability in x and y of the stable isotope bi-plot. The SEA represents approximately 40

% of the spread of data, thus, with sufficient sample sizes (> 30), is expected to represent

the core niche and be insensitive to sample size (Cummings et al. 2012, Jackson et al.

2012). Use of the transformed version, SEAC, accounts for loss of a second degree of freedom when using bivariate data and provides for an unbiased correction of SEA for sample sizes < 30:

SEAC = SEA x (n-1)/(n-2)

SEAC was then used to determine the degree of overlap in isotopic niche breadth between

populations. The probability of one population having a smaller isotopic niche than

another population was calculated from credible intervals produced from multiple

Bayesian iterations of SEA (105 posterior draws; see Jackson et al. (2011) for details).

The Bayesian estimate of SEA (SEAB) is analogous to a bootstrapping procedure, in that it

also provides a robust adjustment for differences in sample size. Probability values

(hereafter labeled as P) of isotopic niche size differences ranged from zero to one; zero

meaning no difference. Probability of overlap or niche size difference > 0.6 was

considered to be significant, which is the same criteria used in the Schoener’s diet index

(Wallace 1981) and also used by Guzzo et al. (2013) in the comparison of native Yellow

Perch (Perca flavescens) and invasive White Perch (Morone americana) δ13C and δ15N

SEA’s. In the present study, we used the total area of ellipses for bivalves at each location

34 to represent variability in isotopic niche at the base of the food web and a measure of

variation in isotopic niche available to the gobies at each location. As primary consumers,

the isotope signature of bivalve tissues is more responsive than fishes to source-driven

changes in isotope signature through time. Thus, variation in baseline isotope signature

(or baseline isotope niche breadth) indicates the degree of temporal and spatial variation

in secondary and tertiary consumers that is due to source-driven changes in isotope

concentrations, as opposed to shifts in diet.

Niche plasticity It is well established that muscle tissue represents a longer integration of stable

isotope assimilation than liver tissue (Post et al. 2007). We used the difference in δ13C and δ15N from muscle to liver tissue to quantify the degree to which the isotopic niche in an individual changed. We compared the difference in isotopic niche (SEAB) between

muscle and liver and the probability of overlap in isotopic niche (SEAC) between muscle and liver as a measure of isotopic niche plasticity in a population. In addition, we compared liver and muscle for δ13C and then for δ15N in each individual using paired

Student T-tests and compared the calculated difference between liver and muscle for each population using independent T-tests.

RESULTS

A total of 190 Round Goby and 102 Tubenose Goby were collected where they overlap in distribution from two sites at the littoral edges of Lake St. Clair (Mitchell’s

Bay, Sep 2011 and Sand Point, Oct 2012) and W. Lake Superior (Thunder Bay and

Duluth Aug 2012, Table 2.1, Fig. 2.1). The two species were not available from the same

35 location in W. Lake Superior, although they were present in both locations the previous

year (Schloesser et al. 2011).

Baseline bivalves The baseline bivalves from the two locations in Lake St. Clair had significantly

different δ13C and δ15N; with a total difference of 1.4 ‰ lower δ13C and 1 ‰ higher δ15N in bivalves from Sand Point, at the head of Detroit River, than Mitchell’s Bay (ANOVA,

13 15 F1, 55 = 57.3 & 79.8 for δ C and δ N respectively, p < 0.01, see Table 2.1 for sample

sizes and stable isotope means ± S.E.). Although the total Standard Ellipse Area (SEAC) was larger in bivalves from Mitchell’s Bay (Table 2.1), the Bayesian inference from multiple iterations of Standard Ellipse Areas (SEAB) were not significantly different

(probability (P) Sand Point 2012 Bivalve SEAB < Mitchell’s Bay 2011 Bivalve SEAB =

0.56, which is lower than the predefined significance of P > 0.6). W. Lake Superior,

Duluth Harbor bivalves were much higher in δ15N (10 ‰) and significantly lower in δ13C

(2 ‰, ANOVA, F1, 19 = 148.7, p < 0.01) than Thunder Bay bivalves. Therefore, niche

overlap between Round Goby and Tubenose Goby was not a comparable metric for W.

Lake Superior. However, SEAB was not significantly different between the two baseline

populations (P = 0.59), which suggests the isotopic niche breadth available to the fishes

was similar and the ellipse sizes of the fish populations could be compared.

Round Goby and Tubenose Goby Once separated by size group, tissue and location, our samples of gobies for

which ellipses were drawn ranged from 20 – 38 individuals, with exception for one group

of 13 (Table 2.1). Reliability in ellipse estimations reduces considerably with sample

sizes < 10 (Jackson et al. 2011), therefore, we suggest caution in the interpretation of

ellipses for YOY (young-of-year) Tubenose Goby from Thunder Bay (n = 8) despite the

36 inherent sample size correction provided by SEAC and SEAB. All other comparisons involving W. Lake Superior Round Goby and Tubenose Goby that matched in size and

YOY Tubenose Goby were bootstrapped due to the high effect from differences in sample size identified by Cohen’s power analysis. All other power values were > 0.8.

The sex composition for each size class at each site was

(Male/female/immature/unsexed: Mitchell’s Bay: RG 8/4/0/20, larger RG 4/23/0/7, TG

5/1/0/23. Sand Point: RG 3/2/0/33, larger RG 25/9/0/2, TG 17/9/0/3. W. Lake Superior:

RG 9/6/5/7, larger RG 14/6/0/3, TG 21/1/0/1, YOY TG 8/4/8/1). The only comparison for which sex had a significant effect was for δ15N in Mitchell’s Bay Round Goby (ANOVA

15 where F tested the effect of sex on δ N in muscle tissue: F3, 57 = 5.2, p = 0.003). In

Mitchell’s Bay, male Round Goby had higher δ15N (12.5 ± 0.5 ‰ p < 0.05) than

immature (11.8 ± 0.4 ‰), unsexed (11.9 ± 0.4 ‰) and female Round Goby (12 ± 0.4 ‰).

However, note the high proportion of ‘unsexed’ fishes in Mitchell’s Bay and Sand Point.

Trophic position and isotopic niche overlap Across all sites and size classes, Round Goby had a higher trophic position

(higher δ15N) than Tubenose Goby, with exception for the grouping of Round Goby at

Sand Point that were significantly larger than all other fishes (larger Round Goby, Table

2.1, lower case letter denotes significance). Round Goby and Tubenose Goby that were within the same size range (size-matched) also had significantly different δ13C in all cases except Mitchell’s Bay muscle tissue, and larger Round Goby had significantly different

δ13C than Tubenose Goby in Mitchell’s Bay muscle tissue and Sand Point liver (no liver was available for size-matched Round Goby from Sand Point, Table 2.1). The differences in W. Lake Superior seemed to be partially due to baseline differences in δ13C and δ15N

between the two sampling locations (See Baseline Bivalves, Table 2.1, Fig. 2.1), so one

37 should avoid drawing conclusions on the lack of niche overlap between the two species.

However, baseline isotopic niche breadth was similar (see Baseline Bivalves section),

which suggests a similar range in isotopic niche breadth was available to the fishes.

The ellipse, or isotopic niche, of size-matched Round Goby and Tubenose Goby

at each location were distinct with no significant overlap, which was predominantly due

to the higher δ15N in Round Goby (Fig. 2.2, see Table 2.1 for % overlap). In Sand Point a

high percentage of Tubenose Goby ellipses (83.6 % and 21.4 % muscle and liver

respectively) were covered by larger Round Goby ellipses. There was also significant

overlap between the two size groups of Round Goby in Mitchell’s Bay and W. Lake

Superior but not Sand Point (Fig. 2.2, Table 2.1).

Isotopic niche breadth Across all size classes, in 11 of 15 comparisons, we found significantly broader

isotopic niche to occur in the widely established Round Goby, compared to the narrowly

established Tubenose Goby (Table 2.1, Fig. 2.3). Exceptions were size-matched Round

Goby from Sand Point and larger Round Goby from Mitchell’s Bay, both of which had

significantly smaller isotopic niche than Tubenose Goby when comparing muscle tissue

(P = 0.79 and 0.85, respectively). Again, when comparing muscle tissue, size-matched

Round Goby and Tubenose Goby isotopic niche were also not significantly different in

Mitchell’s Bay and neither was the isotopic niche of larger Round Goby and YOY

Tubenose Goby (P < 0.6 in both cases).

Overall, differences in isotopic niche were driven by variation in both δ15N (NR)

and δ13C (CR). But in Lake St Clair, broader isotopic niche in Round Goby was predominantly driven by higher nitrogen range (NR), whereas in W. Lake Superior there was a larger difference in the carbon range (CR) of gobies than NR (Table 2.1). In W.

38 Lake Superior, size-matched Round Goby had a significantly broader isotopic niche than

larger Round Goby (P = 0.90 and 0.78, muscle and liver, respectively, Fig 2.3), as did

YOY Tubenose Goby compared to size-matched Tubenose Goby (P = 0.93 in muscle,

liver sample size too small for reliable comparison). In Mitchell’s Bay, size-matched

Round Goby also had a significantly broader isotopic niche than larger Round Goby for

muscle tissue (P = 0.94), but for all other intra-specific comparisons larger Round Goby

had a broader isotopic niche (Fig. 2.3).

Isotopic niche plasticity Across all size groups, the difference between liver and muscle tissue, or niche

plasticity, was more pronounced for Round Goby than for Tubenose Goby. See Figure

2.3 for significant differences (*) between muscle and liver SEAB. See Figure 2.4 for significant differences in δ15N and δ13C between tissues of individuals (*), and comparison of mean difference between tissues for different species and size groups of gobies (letters denote significantly different groups within each site). There was a higher probability of muscle SEAB being broader than liver SEAB in 3/5 comparisons between

Round Goby and Tubenose Goby (Fig. 2.3). One exception was larger Round Goby in

W. Lake Superior that had similar probability of isotopic niche breadth (SEAB) being different between tissues as Tubenose Goby (sample size for YOY Tubenose Goby liver was too low for this comparison). In W. Lake Superior, overlap between muscle and liver isotopic niches was also higher for Round Goby (28.3 – 75.3 %) than Tubenose Goby

(14.5 – 17.8 %). The second exception was the only case in which Tubenose Goby had a greater probability of difference in SEAB between tissues than Round Goby (Lake St

Clair, Fig. 2.3).

39 There were three comparisons for which mean difference in δ15N, or niche

plasticity, was greater between tissues for Round Goby than for Tubenose Goby (Fig.

2.4a). In contrast, there was only one comparison in which Tubenose Goby had

significantly greater mean difference in δ15N than Round Goby and this was for YOY

Tubenose Goby in comparison to larger Round Goby in W. Lake Superior (note sample

size of YOY Tubenose Goby liver, Table 2.1, Fig. 2.4a). Mean difference in δ15N between

tissues was also greater for size-matched Round Goby than Tubenose Goby from W.

Lake Superior (0.3 ± 0.2 ‰ more difference, Fig. 2.4a, right panel). But comparison of

bootstrapped samples did not yield a significant difference (note sample size differences,

Table 2.1).

There was a significant difference in the δ15N between muscle and liver of individuals within every group, with exception for larger Round Goby from W. Lake

Superior (Fig. 2.4a). Including larger Round Goby from W. Lake Superior, δ13C was

significantly different between tissues of individuals for 5/9 groups (3 Tubenose Goby, 2

Round Goby). Sand Point gobies had particularly variable δ13C between tissues, and this was the only case in which Tubenose Goby had significantly higher variation in δ13C between tissues than Round Goby (0.49 ± 0.2 ‰ greater difference, Fig. 2.4, Table 2.1).

Variable δ13C (habitat niche) in Sand Point seemed to be the driving force for the only

case of greater difference in SEAB between tissues of Tubenose Goby than Round Goby

(Fig. 2.4b). Otherwise δ15N (trophic niche) was the dominant metric driving variation in isotopic niche plasticity.

40 DISCUSSION

Broad trophic and habitat niche are often considered to be facilitators of successful establishment of aquatic invasive species (Marvier et al. 2004, Shea and

Chesson 2002), our findings indicate that this is the case for Round Goby, at least, in comparison to Tubenose Goby. A number of studies have suggested broad diet and habitat use facilitated the establishment and spread of Round Goby in North America

(Brush et al. 2012, Diggins et al. 2002, Raby et al. 2010). Our study and a study by Vašek et al. (2014) on gobies in the Danube basin using stomach contents, are the first to demonstrate broader niche and higher plasticity in Round Goby than Tubenose Goby where they occur in the same habitat. In our study, we used stable isotope analysis of multiple tissues to investigate niche plasticity. Bearhop et al. (2004) warned of the effects of differences in physiology that can result in different fractionation levels when comparing tissue types to infer temporal changes in diet from stable isotope data.

Although Round Goby and Tubenose Goby grow to different maximum body sizes, the two species are commonly found within the same size range, are closely related, share similar environments (Miller 2004), and have similar field metabolic rates (O’Neil et al.

2013). Thus, metabolic turnover of nutrients and stable isotopes in tissues is expected to be similar between the two species.

We also found higher trophic niche plasticity in Round Goby than Tubenose

Goby based on variation in isotope niche ellipses between populations and δ15N between muscle and liver. This is consistent with other studies that have found Round Goby to have a plastic diet across invaded ranges in North America (Brush et al. 2012) and

Europe (Brandner et al. 2013, Polačik et al. 2009), as well as in prey-choice laboratory experiments (Coulter et al. 2011). Kornis et al. (2012) suggested diet plasticity allows this

41 species to exploit locally abundant food sources in invaded locations. Given other studies

have suggested plasticity in trophic niche of invasive fish species facilitate rapid growth

and invasion success (Hayden et al. 2014) and reduced competition with sympatric native

species (Hayden et al. 2013) and other invasive species (Jackson and Britton 2014), niche

plasticity is likely a common attribute of successful invasive fish species. Layman and

Allgeier (2012) found individuals of the invasive lionfish (Pterois volitans/miles) to have

a specialist feeding strategy, which suggests that there could be exceptions to this

conclusion. This was, however, a marine species and the study did not compare directly

to a less successful invasive species.

In the present study, Round Goby was found to have a higher δ15N (higher trophic

position) relative to Tubenose Goby that was within the same size range, while δ13C was

not significantly different between the species, suggested they consume resources from

the same habitat. Higher trophic position implies that Round Goby could be more of a

piscivore than similar-size Tubenose Goby and feed on other small fishes, such as

Tubenose Goby juveniles. The lower trophic position of Tubenose Goby suggests the

reverse is unlikely, although Tubenose Goby has been reported to consume Round Goby

eggs in very small quantities relative to other prey available (Vašek et al. 2014). Round

Goby has been reported to feed on eggs and fry of several fishes (Kornis et al. 2012)

including Tubenose Goby, although also in small quantities (Vašek et al. 2014). It should

be noted that the differences in δ15N and δ13C between W. Lake Superior Round Goby and Tubenose Goby seem to be primarily ecosystem driven (i.e. different baseline signatures). Although the two locations in W. Lake Superior share relatively similar fish communities (Schloesser et al. 2012, Schloesser et al. 2013), prey communities could be

42 different between the two locations, which could also be driving differences in trophic niche between the two goby species.

In Lake St Clair, the higher δ15N of Round Goby seemed to be a catalyst for a clear distinction in the isotopic niches of similar-sized Round Goby and Tubenose Goby.

It is unlikely that separate species will occupy the same niche in one place and time

(Elton 1927). Although, since that publication, several studies have demonstrated that niche overlap can occur under certain conditions. For instance, when species invade a novel environment, niche overlap can occur due to a lack of prior co-existence (Davis

2003, Guzzo et al. 2013, Jackson and Britton 2014). The unique isotopic niches of these gobiids could have been facilitated by either their co-existence in the Ponto-Caspian region prior to invasion, or their relatively long co-existence in Lake St. Clair (> 20 years since invasion; Kornis et al. 2012). Round Goby and Tubenose Goby have been reported to have some dietary overlap in Lake St. Clair (French and Jude 2001) and in invaded ranges in Europe (Simonović 2001, Vašek et al. 2014) based on stomach contents, although Adámek et al. (2007) also reported diet divergence between the two species at an invasion front in the Danube River. These somewhat conflicting findings could relate to time since invasion, but the prevalence of trophic niche plasticity in Round Goby or

Tubenose Goby at invasion fronts in the Great Lakes has not been thoroughly investigated.

In the present study, a broader isotopic niche in Round Goby was often associated with higher isotopic niche overlap with Tubenose Goby and/or a different size group of

Round Goby. Prolonged niche overlap is thought possible if resources are in abundance and/or if the overlap is short-lived. Otherwise, competition could increase and lead to the

43 diversification of niches, competitive exclusion, or even extirpation (Bolnick 2001, Elton

1927). Jackson and Britton (2014) also suggested trophic (δ13C and δ15N) niche overlap in sympatric aquatic invasive species is avoided through plasticity in resource use, which leads to the diversification of niches. Round Goby is often found in high abundances

(Lynch and Mensinger 2011, Moran and Simon 2013), which is expected to increase intra-specific competition and is, thus, a logical driving force for niche plasticity (Bolnick

2001, Bolnick et al. 2003). Lynch and Mensinger (2011) suggested high abundances in

Round Goby and the associated resource competition could ultimately drive individuals to move or change their diet. Interestingly, Tubenose Goby can also be found in high abundances in native Ukraine (Kvash, Y., National Academy of Sciences of Ukraine,

Pers. Comm.) and invaded North America (Lake St. Clair and western Lake Erie;

Mandrak, N., Fisheries and Oceans Canada, Pers. Comm.; Thunder Bay, Schloesser et al.

2012), but this does not appear to have provided plasticity in trophic niche in North

American populations (present study).

We found body size-based ontogenetic shifts in niche breadth and niche plasticity in Round Goby, but the trends were not consistent which suggests it is a plastic trait.

Ontogenetic niche shifts relating to morphological divergence are commonly found in invasive fishes (Borcherding et al. 2013, Groen et al. 2012), including the Round Goby

(Brandner et al. 2013) and fishes in general. With increased body size, Round Goby increased its capacity for omnivory; to feed at multiple trophic positions and/or multiple species within the same trophic position simultaneously and, thus, inflating niche size and demonstrating plasticity. The narrower niche of larger Round Goby in W. Lake Superior could be due to a shift towards bivalves, as larger individuals of Round Goby (> 70mm)

44 generally had a higher proportion of dreissenids in their diet in this study (Pettitt-Wade,

H. Pers. Obs.) and in other studies (Brandner et al. 2013, Ray and Corkum 1997). The

ability of Round Goby to shift to alternate prey, such as dreissenid mussels, beyond the

gape size of potential competitors, such as Tubenose Goby, has previously been

suggested as a facilitator of invasion success (French and Jude 2001, Ray and Corkum

1997). Although Tubenose Goby possess pharyngeal teeth, dreissenids have never been

reported in its diet, nor in this study, and limited gape size driven by total body size has

been suggested to be the cause (Diggins et al. 2002).

We found Tubenose Goby to have plasticity in habitat niche, as determined by

variation in δ13C between tissues, which was also suggested by Erős et al. (2005) in comparison to other invasive gobiids. But the lack of trophic niche breadth and niche plasticity (variation in δ15N) indicates a lack of an ability to avoid competition for specific prey, which suggests Tubenose Goby could be associated with prolonged and sustained competition with native species. Both Tubenose Goby and Round Goby choose dipteran chironomid larvae over other prey (Adámek et al. 2010, Kocovsky et al. 2011) and lower contributions of dipteran chironomid in the diet of Tubenose Goby have been associated with competition with native Rainbow Darter (Etheostoma caeruleum) in Lake

St Clair (French and Jude 2001) and Lake Erie (Kocovsky et al. 2011). Van Kessel et al.

(2011) suggested competition for shelter would occur with native Cottus perifretum in

European rivers invaded by Tubenose Goby. With exception of Rainbow Darter

(Etheostoma caeruleum), minimal competition for prey has been suggested for Tubenose

Goby with the majority of co-occurring native fishes in the Great Lakes (French and Jude

2001, Kocovsky et al. 2011). Conversely, Round Goby has been associated with niche

45 displacement of several native fish species in the Great Lakes (e.g. Balshine et al. 2005,

Bergstrom and Mensinger 2009, Groen et al. 2012). In the Dyje River, where Tubenose

Goby overlap with Round Goby, Tubenose Goby was suggested to avoid dipterans in place of Ephemeroptera and Trichoptera (Vašek et al. 2014). Further research would be required to determine if niche displacement occurs between these species during novel interactions but as previously mentioned, distinct trophic niches were found for the two

Gobiidae where they share the same habitat niche.

Our findings promote the hypothesis that a broad and flexible niche provides scope for acclimatization to available resources and is associated with the expanding range of invasive species following introduction (Peterson and Vieglais 2001). A broad niche in Round Goby increased opportunity for niche overlap, but high niche plasticity suggests omnivory and that prolonged niche overlap can be avoided. A strong dependence on specific prey species, as indicated in the Tubenose Goby, could be a risk to food web stability following invasion, particularly in unstable food webs such as those that suffer perpetual invasions (Ricciardi 2001). The maintenance of many weak and few strong omnivorous interactions is thought to be critical to ecosystem stability (Gellner and McCann 2012) and a high frequency of niche differences are necessary for the maintenance of species diversity (Levine and HilleRisLambers 2009). Niche separation can be expected to occur as part of a natural progression following long-term establishment of invasive species. Comparison with native Ponto-Caspian populations could help determine if the niches displayed by gobies in North America are part of an adaptive response to a novel environment and the potential for community resistance

46 from further invasion (Shea and Chesson 2002), such as from the other species of

Gobiidae invasive in Europe.

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52 Table 2.1 Length, weight and stable isotope data (mean ± S.E.), population metrics, SIBER ellipses and ellipse overlap between Round Goby and Tubenose Goby collected at mouth (Mitchell’s Bay) and outflow (Sand Point) of Lake St. Clair and in western Lake Superior (Thunder Bay and Duluth) A B C D 13 15 E F G H n Wet Wt LT LS δ C δ N CR NR SEAC Overlap (%) Baseline Bivalves I Mitchell’s Bay 30 70.4 ± 0.4 10.0 ± 0.1 5.1 ± 0.1 -19.1 ± 0.1a 7.2 ± 0.1b 1.5 1.4 0.4a Sand Point 27 80.2 ± 0.4 12.5 ± 0.1 6.4 ± 0.1 -20.5 ± 0.2a 8.2 ± 0.1c 1.0 1.2 0.2a Thunder Bay 12 25.6 ± 0.3 8.0 ± 0.1 6.7 ± 0.1 -25.9 ± 0.2b 3.5 ± 0.1a 1.6 0.8 0.3a Duluth 14 21.9 ± 0.3 9.2 ± 0.1 5.2 ± 0.1 -27.9 ± 0.1b 13.5 ± 0.2d 1.0 1.9 0.2a Mitchell’s Bay Muscle Round Goby 32 1.5 ± 0.1 48.0 ± 1.2 40.6 ± 1.2 -18.7 ± 0.1b 12.0 ± 0.1b 2.7 1.9 1.2c 1. (10.0) Larger Round Goby 34 4.6 ± 0.3 69.0 ± 1.2 58.0 ± 1.1 -19.6 ± 0.1a 12.1 ± 0.1b 2.9 1.4 0.7a 1. (30.0) Tubenose Goby 29 1.4 ± 0.1 49.1 ± 1.2 39.5 ± 1.0 -18.7 ± 0.1b 10.5 ± 0.1a 2.7 1.9 1.0b Mitchell’s Bay Liver Round Goby 25 1.6 ± 0.2 49.2 ± 1.1 41.8 ± 1.3 -18.9 ± 0.1b 10.2 ± 0.1b 1.4 2.7 0.8a 2. (73.8), 3. (2.5) Larger Round Goby 27 4.3 ± 0.3 67.5 ± 1.3 57.0 ± 1.3 -19.3 ± 0.2a 10.3 ± 0.1b 3.2 2.9 1.3b 2. (45.5) Tubenose Goby 22 1.4 ± 0.1 49.5 ± 1.4 39.9 ± 1.2 -19.1 ± 0.1a 9.3 ± 0.1a 2.4 1.4 0.8a 3. (2.5) Sand Point Muscle Round Goby 38 0.7 ± 0.1 41.9 ± 1.3 34.3 ± 1.1 -17.2 ± 0.1b 11.5 ± 0.1b 2.2 2.6 0.9a 4. (3.3) Larger Round Goby 36 8.3 ± 1.0 84.0 ± 2.5 69.7 ± 2.2 -17.8 ± 0.1a 10.7 ± 0.2a 2.4 4.3 1.6c 5. (57.5), 4. (1.9) Tubenose Goby 29 0.6 ± 0.1 39.4 ± 1.4 31.8 ± 1.3 -17.8 ± 0.1a 10.6 ± 0.1a 2.5 2.9 1.1b 5. (83.6) Sand Point Liver Larger Round Goby 25 10.1 ± 1.3 90.0 ± 2.6 74.6 ± 2.2 -18.5 ± 0.1b 9.4 ± 0.2a 2.5 3.3 1.7b 6. (8.8) Tubenose Goby 22 0.6 ± 0.1 41.0 ± 1.7 33.3 ± 1.5 -19.0 ± 0.1a 10.3 ± 0.1b 2.6 1.2 0.7a 6. (21.4) West Superior Muscle Round Goby 27 0.6 ± 0.0 36.7 ± 0.5 30.5 ± 0.4 -30.5 ± 0.3a 12.3 ± 0.2d 6.0 3.4 3.0c 7. (28.3) Larger Round Goby 23 2.1 ± 0.2 54.8 ± 1.4 45.3 ± 1.3 -30.4 ± 0.3a 10.6 ± 0.2c 4.7 3.3 1.9b 8. (67.4) Tubenose Goby 23 0.4 ± 0.0 35.1 ± 1.1 28.0 ± 0.9 -19.4 ± 0.2c 5.4 ± 0.1a 2.2 2.1 1.1a 9. (14.5) YOY Tubenose Goby 21 0.1 ± 0.0 22.4 ± 0.8 17.6 ± 0.6 -21.1 ± 0.2b 5.9 ± 0.2b 3.7 2.6 1.9b West Superior Liver Round Goby 13 0.6 ± 0.1 37.3 ± 0.1 30.6 ± 0.1 -30.3 ± 0.4c 11.7 ± 0.2c 4.3 1.8 2.5c 10. (10.0), 7. (34) Larger Round Goby 20 2.2 ± 0.2 55.1 ± 1.6 45.7 ± 1.5 -30.6 ± 0.3c 10.7 ± 0.2b 4.0 2.6 1.7b 10. (14.7), 8. (75.3)

53 A B C D 13 15 E F G H n Wet Wt LT LS δ C δ N CR NR SEAC Overlap (%) Tubenose Goby 21 0.4 ± 0.0 35.0 ± 1.1 27.9 ± 0.1 -19.6 ± 0.1a 4.7 ± 0.1a 2.3 1.4 0.9a 9. (17.8) YOY Tubenose Goby 8 0.1 ± 0.0 25.5 ± 0.1 19.8 ± 0.1 -20.9 ± 0.2b 4.9 ± 0.2a 1.8 1.4 1.0a abcd Different lower case letters denote significantly different groups for each tissue within each location (LSD post-hoc to MANOVA, p < 0.05) A n denotes total sample numbers obtained for analysis from each location for each species, size group and tissue. Liver tissue sample numbers were less than muscle due to the difficulty in obtaining sufficient sample of liver for stable isotope analysis. B Wet weight of whole fish (g) or Baseline bivalve tissue (mg) C Total length (mm) of fish or Baseline bivalve shell D Standard length (mm) of fish or width of Baseline bivalve shell E δ15N range F δ13C range G SEAC is the Standard Ellipse Area calculated from stable isotope population metrics with sample size correction (additional degree of freedom) and incorporates 40 % of the total stable isotope data range H SIBER overlap function, which compares the degree of overlap between two ellipses (SEAC). Matching numbers (1-10) denote the overlapping population or tissue ellipses, with % of ellipse that is overlapping in parenthesis. See Fig. 2 to observe ellipse overlap on δ15N and δ13C bi-plots. I Bivalves used as baseline for spatial comparison of stable isotope data were dreissenids (Lake St Clair and Duluth) and unionids (Thunder Bay) Larger Round Goby were individuals that were significantly larger in LS and Wet Wt than other fishes at each location (ANOVA, p < 0.05) YOY indicates young-of-year Tubenose Goby that were significantly smaller than all other fishes and within the size range of YOY Tubenose Goby in the Great Lakes (Leslie et al. 2002)

54

Figure 2.1 Collection sites for Round Goby and Tubenose Goby in Lake St. Clair (a) Mitchell’s Bay (September 2011) and (b) Sand Point (October 2012) and western Lake Superior (August 2012), Duluth and Thunder Bay.

55

13 15 Figure 2.2 Bi-plot of δ C and δ N with Standard Ellipse Areas (SEAC) of bulk muscle and lipid-extracted liver from Lake St Clair (Mitchell’s Bay and Sand Point) and western Lake Superior Round Goby and Tubenose Goby. For same size Round Goby (open circles, solid gray ellipses) and Tubenose Goby (solid gray circles, black ellipses), Round Goby larger than all other fishes (standard Length, p < 0.05 T-Test; open triangle, dashed gray ellipses) and Tubenose Goby significantly smaller than all other fishes (black star and black dashed ellipses). Stable isotope data (Mean ± S.D.) are shown for bivalves from Duluth (black square) and Thunder Bay (black diamond), western Lake Superior. Note different range on the x and y-axis for western Lake Superior. See Table 2.1 for niche metrics, total ellipse areas and ellipse overlap data.

56

Figure 2.3 Density box-plots of Bayesian estimates of Standard Ellipse Area (SEAB) for bulk muscle and lipid extracted liver tissue for size-matched Round Goby and Tubenose Goby and larger Round Goby (> 6cm) that were significantly larger than all other fishes (T-test, p < 0.05). Note different y-axis maximum for western Lake Superior. Black circles are mode total area (‰2) and grey boxes represent 50%, 75% and 95% credible 5 abc intervals produced from 10 Bayesian iterations of SEA (SEAB). Different lower case letters denote significant difference in SEAB between groups within each location for muscle and liver independently. * Probability of difference between muscle and liver SEAB within each population, higher number denotes higher probability * 0.6-0.69, ** 0.7-0.79, *** 0.8-0.89, **** 0.9-1.

57

Figure 2.4 (a) Mean difference ± S.E. between bulk muscle and lipid extracted liver δ13C and δ15N in Round Goby and Tubenose Goby in Mitchell’s Bay, Sand Point (both Lake St. Clair) and western Lake Superior. * Significant difference between muscle and liver δ13C or δ15N within each population (paired T-tests) * p < 0.05, ** < 0.01, *** < 0.001. abcd Different lower case letters denote significantly different calculated mean difference of liver and muscle between each group (p < 0.05, ANOVA or independent T-test). (b) Standard Ellipses Areas (SEAC) of bulk muscle and lipid extracted liver (arrows point from muscle to liver) δ13C and δ15N in Round Goby (gray) and Tubenose Goby (black).

58 CHAPTER 3

NICHE BREADTH CHANGES WITH TIME ESTABLISHED, HABITAT

COMPLEXITY AND GENETIC DIVERSITY FOR A WIDESPREAD INVASIVE

FISH

59 INTRODUCTION

Non-native species that cause harm to ecosystems or economy (invasive species) are one of the leading causes of species extinction and have one of the biggest impacts on global economy (Clavero and García-Berthou 2005). Study of these prolific invaders across established ranges can help us determine the dynamics of species spread and distribution, crucial for predicting long term impacts and patterns of biodiversity through time (Strayer et al. 2006). The influence of time can be particularly important during the colonisation or spread to a novel environment, providing opportunity for acclimation or adaptation to local climates, resources available, and hazards to survival and reproduction. Study of species with broad spatial distributions provides a framework for understanding how species respond to different environments through time (Guisan et al.

2014), yet studies of invasive species rarely incorporate the influence of time since establishment (Strayer et al. 2006).

The term ‘ecological niche’ is often used to describe the ecology of an individual, population or species at a point in time, and has classical foundations in the study of species spread and distribution (Holt 2009). A modern perspective incorporates multiple classical definitions to define an individual’s ecological niche as dependent on the traits of the individual, local environmental, and ecological parameters. Analysis of different niche metrics and their relative interactions in driving niche breadth can highlight the mechanisms that influence phenotypic diversity in space and time. Phenotypic traits derive from environment, genotype and their interactions. Invasive species are often subject to considerable selective pressures that act on genetic diversity, and consequently, phenotypic diversity (Lambrinos 2004). Therefore, study of ecological niche in relation

60 to genetic diversity, genetic relatedness and environmental parameters can provide

considerable insights on the drivers of inter-individual variation in resource use, and the

combined and interactive processes that promote survival across a broad geographic

range.

A new quantitative method to depict the trophic and habitat niche of an organism

uses stable isotopes of carbon (δ13C) and nitrogen (δ15N) as baseline variables.

Historically, δ13C and δ15N have been used in trophic and food web ecology to determine diet and habitat use (Peterson and Fry 1987). More recently, variation in δ13C and δ15N

signatures within and among populations are increasingly examined using Bayesian

ellipses that encapsulate the variability among individuals using metrics from niche

theory and trophic ecology (Jackson et al. 2011, Newsome et al. 2007). The diet of

primary consumers represents base level changes in isotope signature and that which is

available to higher trophic levels (Vander Zanden and Rasmussen 1999). As such, the

variation in stables isotopes of primary consumers can be used to adjust for environment

specific changes in consumer isotope values in space and time. Termed an ‘isotopic

niche’, this method has been shown to be particularly useful for comparing populations of

aquatic invasive species (Comte et al. 2016, Guzzo et al. 2013, Jackson et al. 2012,

Pettitt-Wade et al. 2015).

One such widely established aquatic invasive species is the Round Goby

(Neogobius melanostomus). This benthic fish was first sighted in North America in 1990,

in the river system that links lakes Huron and Erie (St. Clair River, Lake St. Clair, Detroit

River). Most likely introduced via ship ballast water from the Ponto-Caspian, the species

has since spread in abundance to the majority of locations in the Great Lakes and

61 continues to make its way to other regions of North America through connecting tributaries (Kornis et al. 2012). Different regions have different times of establishment

(See USGS 2015 for map of distribution through time), so populations have had different lengths of time to respond to the various levels of environmental heterogeneity and habitat complexity they encounter. Populations in different regions also often have different demographics, such the proportion of male/female/immature, size ranges and relative body condition that could influence feeding ecology (Kornis et al. 2012).

Invasive Round Goby populations throughout the Great Lakes basin also have lower genetic diversity and relatedness to the original establishment source in the St Clair-

Detroit river region (Bronnenhuber et al. 2011), but the association between ecological niche, genetic diversity and time of establishment has yet to be investigated. As Round

Goby continues to expand its distribution in North America and Europe, the importance of studying this species, and others with similar invasion characteristics, becomes increasingly clear. Furthermore, study of invasive species across different spatial scales provides an opportunity to improve our understanding of long-term impacts and the process of naturalisation.

In this study, we investigate the relative importance of time since establishment for variation in trophic (δ15N) and habitat (δ13C) niche by incorporating multiple populations and site-specific parameters as measures of demography, environmental heterogeneity and habitat complexity. The role of genetic diversity was investigated as an indication of propagule pressure because of the known association between genetic diversity and distance from the longest established location (Bronnenhuber et al. 2011).

Overall, we predict that time of establishment (first recorded sighting) has a significant

62 influence on niche breadth, despite environmental and population specific parameters.

From the perspective that longer time provides more opportunity for diversification in

feeding strategies, especially in species that exhibit high intraspecific competitive

interaction (Bolnick 2001, Svanbäck and Bolnick 2007), we predict that longer

established populations of Round Goby exhibit greater variation in isotopic niche and

broader niches than more recently established populations in littoral areas of the Great

Lakes. But it is predicted that the strength of the interactions between establishment time

and niche breadth is dependent on regional environmental variation, local habitat

complexity and population specific genetic diversity. In association with temporal

variation in resource availability, it is predicted that the influence of establishment time is

less significant for liver tissue (fast turnover) than muscle tissue (slower turnover). This

study not only characterises a remarkable invasion process in the Great Lakes, it also

tests basic ecological principles on the role of competitive interactions on niche breadth

evolution.

METHODS

Sample collection Round Goby were collected from 12 locations in the Great Lakes basin, for which first recorded sightings ranged from 1990 to 2004 (USGS.gov accessed January 2015,

Figure 2.1). Fish were collected in 2011, 2012 and 2013 from the littoral fringes of lakes at a depth ranging from 0.5 – 2 m using a beach seine net (SEM-03, 50' long, 4' tall, 4' x

4' x 4' cod end, 1/4" mesh, Franklyn Net and Twine, Wheatley, ON), angling, and minnow traps (16.5'' length with 9'' diameter). The fish were euthanized on capture, individually bagged and placed on ice (-20°C) before returning to the laboratory where

63 measurements were taken, sex determined using urogenital papilla and whole body

frozen to -20°C (wet mass min ± 0.1g; total length min ± 0.1mm). Fish were later thawed

and whole liver, skinless and boneless dorsal muscle was removed and tissues were re-

frozen before freeze-drying. Dreissenid mussels (Zebra mussel Dreissena polymorpha

and Quagga mussel D. bugensis) were collected from each site and frozen to -20°C in the

laboratory then later thawed, measurements taken (shell length, tissue wet mass), whole

tissue freeze dried and prepped for stable isotope analysis. The carbon (δ13C) and nitrogen (δ15N) stable isotope composition of primary consumer bivalves (dreissenids) at

each location were used as a measure of environmental variability and source-driven

changes in trophic (δ15N) and diet-derived habitat (δ13C) niche of goby fishes.

Population specific parameters Total length, body condition factor, sex proportional diversity, genetic diversity

and genetic divergence were characterised as population specific parameters that could

influence the trophic and habitat niches of goby fishes. Fulton’s condition factor (Kn) was

calculated for each individual fish (�) using a slope-adjusted ratio index from the

following equation (Ricker 1975):

��� ���� K = ����� �����ℎ where ����� was generated from the regression of whole body wet mass against total length for all Round Goby in the present study (Power regression, y = 6 Ŋ 10-6 x3.1853, n =

2 905, R = 0.98). Proportional diversity of sexes (SexD) was calculated for each

population/year using the following equation:

��� = �� + �� + �� + (��)

64 where M, F, I and U are the number of male/female/immature/unidentified, respectively,

in each population/year, R is the proportion of the corresponding category across all populations (0.466, 0.319, 0.035, 0.180 for muscle, 0.508, 0.350, 0.009, 0.132 for liver,

M/F/I/U, respectively). This method was chosen to avoid exclusion of fish identified as immature or unidentified. Genetic diversity (allelic richness and heterozygosity) and genetic divergence from the longest established populations in Lake St Clair (pairwise

FST) were based on microsatellite data for the same goby populations as the ecological

data (methods of Bronnenhuber et al. 2011, Table 3S.1 for details).

Site-specific habitat parameters In addition to the isotope composition of primary consumer ‘baseline’, I

characterized environmental heterogeneity and habitat complexity that could influence

trophic and habitat niche of goby fishes in different water bodies by measuring substrate

diversity, macrophyte density, detritus density, mean surface water temperature and

significant wave height. All of these parameters are established as important drivers of

the diversity and abundance of Round Goby prey (macro-invertebrates; Barton and Carter

1982, Johnson et al. 1987).

Substrate was visually determined at each location while seine netting and

snorkeling for primary consumers with an adaptation of the methods routinely used by

the Ontario Ministry of Natural Resources and Forestry in fish habitat assessments

(OMNRF 1999). Proportional composition of five particle sizes was estimated (silt, clay,

sand, gravel, boulder) and converted to a substrate diversity index using the weighted

average of each particle size. Macrophyte and detritus density were recorded as fractions

ranging from 0 – 1 and then combined in statistical analyses to provide a metric for

productivity, vegetation and/or cover. Surface water temperature and significant wave

65 height were obtained from Environment Canada buoys in the vicinity of each sampling

location (Great Lakes Observation System; http://www.glos.us). Data was summarized

for the months May – Oct within each sampling year 2011-2013. Trent River was

excluded from the analysis of temperature and wave height as the data was not available.

A PCA was conducted on all habitat and environmental parameters across all sites to

investigate for any outliers with regards to habitat complexity.

Stable isotope analysis Freeze dried tissue samples were ground using mortar and pestle until

homogeneous. Liver from fish and whole body from dreissenids were lipid extracted

(Solvent Distillation Method: 2x agitation of tissue in 2:1 chloroform/methanol solution

for 24 h, solvent decanted, sample air dried (modification of method outlined by Bligh

and Dyer 1959). Low C:N ratios (< 3.5) in Round Goby muscle tissue without lipid

extraction indicated the lack of a requirement to lipid extract (Post et al. 2007). Dried

homogenous samples were weighed into tin cups (5mm x 9mm) and run for δ13C and

δ15N, and C% and N%, using a Delta V IRMS (Thermo Electron Corporation, Waltham,

Massachusetts, USA) equipped with an elemental analyser (Costech, Santa Clarita,

California, USA). The following equation was used to calculate delta (δ) values of stable isotope ratios from the abundances of carbon and nitrogen stable isotopes in each sample relative to standard materials that were run simultaneously (Peterson and Fry 1987):

δ�(‰) = (�/� − 1) ×1000 where R is the ratio 15N/14N or 13C/12C. Pee Dee Belemnite (PDB) carbonate, and atmospheric Nitrogen were the standard reference materials for CO2 and N2, respectively.

Precision of analysis from standard deviation of reference standards was 0.07 ‰ and 0.09

‰ δ13C, 0.16 ‰ and 0.15 ‰ δ15N for muscle (NIST Bovine muscle 8414 and internal

66 fish muscle standard, respectively, n = 406), and 0.09 ‰ δ13C and 0.18 ‰ δ15N for liver

(NIST Bovine liver 1577c, n = 241). Accuracy based on the difference between our NIST

standard data and certified data for NIST standards was 0.02 ‰ and 0.06 ‰ for δ13C

(NIST 8573 and 8542, respectively, n = 174), and 0.01 ‰, 0.18 ‰ and 0.05 ‰ for δ15N

(NIST 8573, 8548 and 8549, respectively, n = 196).

Isotopic niche Variation in δ13C and δ15N (standard errors and ranges) was used as a measure of habitat (δ13C) and trophic (δ15N) niche. Standard Ellipse Areas (SEA) were also formed

of bivariate δ13C and δ15N data for all individuals in each population using the package

Stable Isotope Bayesian Ellipses in R (SIBER 2.0) developed by Jackson et al. (2011).

Each ellipse represents the core variation (40%) in bivariate isotope space and was used

to measure population ‘isotopic niche breadth’. Ellipses were corrected for the use of

bivariate data by adding an additional degree of freedom (SEAC), which also provides a

correction for sample size differences. Multiple Bayesian iterations (105) provided further robust correction for differences in sample size and a more accurate depiction of the niche area of each population that can be compared using 95% credible intervals (SEAB).

General Linear Models Total length and stable isotope data for each population of fish or mussel at each

location and year of collection were determined to not differ significantly from a normal

distribution (Kolmogorov-Smirnov) or homoscedastic variance (Levene’s). A General

Linear Model (GLM, Sum of Squares III) was then conducted on bootstrapped (Simple

design in SPSS, n = 1000, 95% CI) baseline mussel whole tissue δ13C and δ15N, with shell length (SL) as a covariate, to produce sample size and SL-adjusted-bootstrapped means, standard error (S.E.b) and 95% confidence interval ranges (95CIRb) for each

67 population. A GLM with a test of between-subject-effects was then run independently for

both muscle and liver tissue of invasive fish populations with six isotopic niche metrics

13 15 (S.E. and ranges for both δ C and δ N, SEAB and S.D. of SEAB) as dependents, year

established (Year Est.) as an independent factor, and the covariates proportional diversity

of sexes (sexD), total length (TL), Fulton’s body condition (Kn), temporal variation

(sampling year and month interaction), substrate diversity index, vegetation cover

(macrophyte and detritus density interaction), mean surface water temperature, mean

significant wave height and variation in baseline mussel δ13Cb and δ15Nb (S.E.b and

95CIRb interactions). Collinearity of independent variables was assessed using the

Variance Inflation Factor (VIF < 3 indicated low collinearity). Akaike Information

Criterion (AIC) was then used to determine the most parsimonious model for each niche

metric. Analysis of temperature and wave height did not include Trent River because the

data was not available. Using the GLM for muscle and liver tissue, mean isotopic niche

metrics were produced for invasive fish from each year of establishment that were

adjusted for significant population specific covariates and variation in baseline δ13Cb and

δ15Nb (estimated marginal means using covariates at mean values).

Regressions with year established Covariate adjusted means were then used in regressions of invasive fish isotopic

niche metrics and year established, for muscle and liver independently. Regressions were

also run for genetic diversity (allelic richness and heterozygosity) and genetic divergence

(FST, genetic distance from Lake St Clair populations) with year established due to the

known association between these parameters and distance from the longest established

region. Units were standardised by converting all data to percentage difference from the

longest established location (Lake St Clair). The equations of the regressions for

68 parameters that had a significant trend with time were used to adjust the equation of the

regression for isotopic niche of invasive fish and time. All statistics were performed using

SPSS 22 or R 3.2.3 with α = 0.05.

RESULTS

Population specific parameters Population specific parameters and isotopic niche data are presented in Tables

3.1, 3.2 and 3.3 for the 894 invasive fish and 654 mussels used in this study. Fewer

samples were available for liver tissue (657), due to the difficulty of obtaining sufficient

tissue for stable isotope analysis from small fish. There were some differences in data

obtained from 2011, 2012 and 2013. Samples for 2012 and 2013 covered a broader range

of sites, had larger mean body size and covered a broader size range than for 2011 for

both fish and mussels (generally higher mean and S.E. TL or SL, Table 3.1, 3.2 and 3.3).

For goby fishes, males comprised the highest percentage overall (47-51% male compared

to 31-35% female, muscle-liver, respectively), but sex was not determined for a high

number of 2011 fish (Table 3.1 and 3.2). Fulton’s condition factor (Kn) was also variable between sampling years (e.g. Kn was lowest in Hamilton for 2011, but highest for 2012

and 2013).

Across all fish and primary consumers, δ13C was generally lowest in the only site

on a river system (Trent River) and highest (more negative) in one of the sites in Lake St

Clair (Table 3.1, 3.2 and 3.3). Sites that consistently had the highest δ15N (Hamilton and

Nanticoke) for fish populations also had highest δ15N for primary consumers. Site and

year/month sampled had a significant influence on at least one of the baseline mussel

13 15 isotopic niche metrics δ C and δ N standard error (S.E.), ranges, or the bivariate SEAB

69 5 and standard deviation of 10 SEAB scores (SEAB S.D., GLMs, p < 0.001). SL did not have a significant influence on δ13C and δ15N across all populations, but there were

significant linear relationships within most populations. SL was subsequently used as a

covariate in the GLM to produce bootstrapped SL-corrected-baseline-niche data for each

location/year for use in the GLMs for invasive fish.

Site-specific habitat parameters Each site had a unique set of environmental and habitat characteristics (Table

3.4). There was also annual variation in these parameters, particularly mean surface water

temperature. Wave height fluctuated among years, with exception for Lake St Clair.

Detritus density was notably high in long-established Mitchells Bay (Lake St Clair) and

the most recently established sites (Lake Seymour on Trent River and Lake Simcoe).

Macrophyte density was highest in Collingwood (Georgian Bay). SexD was consistently high for Mitchells Bay, Port Elgin (Lake Huron), Collingwood and Lake Seymour (Table

3.4). Georgian Bay and Lake Huron sites also generally had the highest mean significant wave height and lowest surface water temperature (Table 3.4). PCA analysis of habitat and environmental parameters across all sites revealed Georgian Bay as a unique outlier on the primary axis (PC 1, explained 64% of the data, Fig. 3S.2).

Variation in isotopic niche explained Percent variation in isotopic niche explained by year established (Year Est.) in relation to population, environmental and habitat specific covariates is provided in Figure

3.2 (Table 3S.2 and 3S.3 for between-subject-effects statistics output, Table 3S.3 and

Table 3S.4 for most parsimonious model based on backward variable selection using

15 Akaike Information Criterion (AIC)). With exception for liver tissue δ N S.E. and SEAB

S.D., Year Est. explained more variation in isotopic niche of invasive fish than any other

70 covariate (6/6 niche metrics for muscle, 4/6 for liver compared to 4 population specific

and 7 site specific covariates, Figure 3.2). In muscle tissue, the combined percentage

variation explained by all covariates was generally lower than the percentage explained

by Year Est. (e.g. Year Est. significantly explained 53% variation in muscle SEAB,

compared to 32% explained by all population covariates and 12% by site specific

covariates, Figure 3.2). Variation in baseline primary consumer δ13Cb (S.E.b by 95CIRb interaction) explained significant variation in NR (10%) and SEAB (6%) for fish muscle,

13 δ C S.E. (4%) and SEAB S.D. (5%) for liver.

Besides Year Est., there were several key differences in the dominant drivers of variation in isotopic niche for muscle tissue compared to liver. In muscle, more variation was significantly explained by genetic diversity than in liver (e.g. 28% in NR and 18% in

13 SEAB for muscle, 11% in δ C S.E. and 5% SEAB S.D. for liver). For liver, sexD and

habitat characteristics explained more variation (Figure 3.2). For example, substrate

diversity significantly explained 9% and 13% variation in CR and NR, respectively.

Macrophyte and detritus density (Macro&Detr) explained 11% variation in NR. SexD in liver was the only covariate that explained more variation than Year Est. (~15% more in δ

15 15 N S.E. and SEAB S.D., Figure 3.2). Variation in δ N (S.E. and/or range) explained by

TL and Kn was significant for both muscle and liver. But in muscle, Kn also significantly explained 12% variation in SEAB. Due to the significant influence of TL and/or Kn on

variation in goby isotopic niche for both muscle and liver, and sexD in liver, these parameters were included as covariates in addition to baseline variation in δ13C and δ15N to produce corrected means for plotting regressions with Year Est.

71 Regressions with year established For both muscle and liver, covariate corrected mean isotopic niche of Round

Goby populations in each year of first discovery was found to progressively decrease

from the longest established water body (i.e. longer time = broader niche, Figure 3.3 and

13 3.4). Linear regressions were significant for both SEAB and δ C S.E. in muscle, and

13 SEAB, δ C S.E. and CR in liver. These trends excluded Collingwood (Georgian Bay), which was a significant outlier (> 3 S.D. for muscle, > 2 S.D. for liver, all other sites < 1

S.D.). Interestingly, goby populations from Collingwood (Georgian Bay) and Nanticoke

(Lake Erie EB) were also the only consistent outliers in strong relationships for both NR and SEAB with TL (Fig. 3S.1), and Georgian Bay had a unique set of habitat and environmental parameters (Fig. 3S.2).

The same increasing trend with time of first recorded sighting was found for allelic richness, but not heterozygosity, genetic distance (FST), baseline dreissenid

isotopic niche or any of the covariates in the GLMs. Adjustment of the isotopic niche

linear regression using the linear regression for allelic richness and first recorded sighting

reduced the slopes for isotopic niche by 37 – 47 % (Fig. 3.3 and 3.4). This resulted in the

isotopic niche of populations established since 2004 being ~20 % less than populations

established since 1990, as opposed to ~40 % less. For muscle δ13C S.E., differences in

isotopic niche were ~10 % more than for the other regressions.

DISCUSSION

Invasive species are model organisms that continue to play a pivotal role in

supplementing our understanding of the spread and distribution of species. Description of

ecological niches can be useful for determining the relative influence of different biotic

72 and abiotic forces for survival in novel environments (Guisan et al. 2014, Holt 2009). In

this study we demonstrate how niche breadth, quantified using δ13C and δ15N, changes with time established for a widespread invasive fish that is continuously expanding its distribution. Inter-individual variation in resource use is often suggested to be a driver of ecological success (Forsman and Wennersten 2015, Pettitt-Wade et al. 2015), or widespread geographic distribution (Slatyer et al. 2013), but is rarely determined for natural populations in relation to time established (Forsman and Wennersten 2015). Our findings suggest that over time, the niche of this invasive species increases, and, in particular, diet-derived habitat niche (inter-individual variation in δ13C).

We found that year established explained most of the variation in isotopic niche,

despite temporal and spatial variation in habitat complexity, environmental parameters

and population demographics. This included the influence of variability in the isotopic

niche of baseline primary consumers, which were incorporated in the GLMs and used as

covariates to produce corrected means for use in regressions. Filter-feeding primary

consumers are considered the best option as baseline for aquatic systems (Vander Zanden

and Rasmussen 1999), and dreissenid mussels generally contribute to the diet of Round

Goby (Kornis et al. 2012) so are likely to indicate source-driven changes in stable isotope

composition. Indeed, variation in baseline δ13Cb did explain 5-10% variation in fish muscle and liver isotopic niche, but this was much less than that explained by year established (41 – 57% in muscle, 18 – 50% in liver).

The overall strength of the interaction between time established and niche breadth was limited by population specific demographics (sex, condition, size range), genetic diversity (i.e. propagule pressure) and habitat complexity in the established region.

73 Combined, these parameters explain a significant amount of variation in trophic and

habitat niche determined from tissue specific δ13C and δ15N. In contrast to our findings,

Comte et al. (2016) did not find a significant effect from time since introduction (23.6 –

338.4 years) on the isotopic niche of 32 freshwater fish species in invaded ranges. This

indicates that niche expansion effects level off after the temporal scale of the current

study (~7 – 23 years), and that the process of naturalization and the effects of biotic

resistance are likely to be on the order of decades. However, lack of a significant trend in

the literature (Comte et al. 2016) could also be due to sample size (13.4 ± 2.4 individuals

per population, mean ± S.E.), large gaps in the data set between times of introduction, or

species-specific differences in propagule pressure.

Our findings demonstrated the importance of habitat complexity (substrate

diversity, macrophyte and detritus density), water temperature and wave height as drivers

of short-term variation in resource use (i.e. liver tissue). In goby fishes, stable isotopes

(δ13C and δ15N) have a turnover of weeks in liver, compared to months for muscle tissue

(Guelinckx et al. 2007). It is, therefore, not surprising that in liver tissue, broad trends with time in established region were slightly blurred by environmental stochasticity.

Moreover, the dominant influence of year established on isotopic niche breadth integrated across a period of weeks emphasises the potential restrictions from less time spent in established regions.

A particularly large amount of variation in isotopic niche from liver tissue was also explained by sexD. Our samples were collected between May and October which encompasses the seasonal breeding times of Round Goby (MacInnis and Corkum 2000).

In Lake Erie, Perello and Simon (2015) found females fed on a smaller diversity of prey

74 than males. During breeding, females and males will alter the allocation of energy from growth to reproduction and large adult males will spend time guarding nests instead of searching for prey (Všetičková et al. 2015). Therefore, the strong influence of sexD on isotopic niche could be due to periods of fasting during reproductive investment.

Although the lack of isotopic niche explained by sexD for muscle tissue suggests that males, females and immature fish have similar diets when averaged across broad time scales. Round Goby males can also exhibit different reproductive strategies that are characterised by different body sizes (i.e. small sneakers and large guarders, Marantette et al. 2009). But little is known of how this associates with different feeding strategies, besides the limitations of gape size.

Different reproductive (and energetic) investment could associate with differences in body condition and, in the present study; body condition explained a significant amount of variation in isotopic niche for both muscle and liver, and trophic niche (δ15N) in particular. This suggests that omnivory across a variety of trophic levels is associated with maintaining optimum condition. Optimal foraging theory suggests that better use of energy through time can provide an edge to survival (Pyke 1984), and trophic niche plasticity is often suggested to be important for survival across spatial and temporal scales (Comte et al. 2016), as previously demonstrated in the invasive Round Goby

(Pettitt-Wade et al. 2015). Condition was particular important for muscle tissue, which has a slower turnover, and events that are particularly demanding would require more time for recovery. Although the variation between sampling years of each site suggests the differences in condition are not due to site-specific stressors and more likely residual stress from reproductive investment. Significant trends were not found between Kn and

75 Year Est. This could be due to the use of TL as a covariate to produce corrected means

for the regressions and the use of TL to calculate Kn. Alternatively, this could be because populations in this study have already been established for long enough to move beyond the initial stresses of colonisation (min 7 years since first sighting and sample collection).

Although, it is unclear how long the stress from establishment lasts in general, or how long it takes for species to become integrated within a community (i.e. naturalisation).

Genetic diversity (allelic richness and heterozygosity) was the second most important driver of long-term variation in isotopic niche. Combined with the similarity in trends with time established, this suggests there is a strong association between genetic diversity and ecological niche. The change in slope following correction of the regression for genetic diversity suggests smaller niche breadth in more recently established locations is partly explained by reduced genetic diversity (i.e. ~20% of the trend). Variation in phenotype can also be reduced under low genetic diversity and isolation from a source population that has high genetic diversity (Lucek et al. 2014). Low genetic diversity at more recently established locations and low relatedness to the longest established location is most likely due to lower propagule pressure (number of successful introduced viable populations) coupled with minimal gene flow. Likewise, small ecological niche could be associated with a low diversity of phenotypes associated with feeding behaviour resulting from genetic patterns. Propagule pressure is recognised as one of the most important factors driving variation in established populations (Britton and Gozlan 2013).

However, the remaining difference between populations following adjustment for genetic diversity suggests that there are other factors driving variation in ecological niche that are not associated with genetic diversity and/or propagule pressure.

76 Contrary to the trend with time of establishment, populations of invasive fish in

Georgian Bay were found to exhibit an uncharacteristically broad isotopic niche.

Georgian Bay was a significant outlier to overall trends with time established, and

15 between trophic (δ N) and bivariate niche (SEAB) against body size (TL). Our Georgian

Bay Site (Collingwood) also had the highest macrophyte density compared to any other site, high wave action and substrate diversity. Wave action has been shown to influence the diversity of benthic macro-invertebrates in the shallow near shore, and in Georgian

Bay, specifically, including the density of Chironomidae and Oligochaeta (Barton and

Carter 1982, Barton and Griffiths 1984) that are often the most common items in the diet of Round Goby (Diggins et al. 2002, Kornis et al. 2012). Johnson et al. (1987) found water temperature to be most influential among several environmental factors in determining the abundance of benthic macro-invertebrates in Georgian Bay, and oligochaetes and chironomids, in particular, to be influenced by substrate richness at low temperatures. A high diversity of macro-invertebrates was found at this site in 2013

(Pettitt-Wade Pers. obs. 2013) and the sampling location is adjacent to a protected wetland (Krantzberg and Houghton 1996), which would promote high biodiversity in the vicinity (Ciborowski, J., Great Lakes Coastal Wetland Monitoring Project, Uzarski et al.

2005). Furthermore, in 1994, Collingwood Harbour was the first Area of Concern out of

43 in North America to be delisted due to a successful remediation and clean-up operation (Krantzberg and Houghton 1996). This suggests that a high abundance of alternative prey, driven by habitat complexity and environmental remediation, could be the drivers of a broad isotopic niche for goby in this location. Furthermore, higher availability and subsequent consumption of more energetically profitable alternatives to

77 dreissenids in this location, as observed elsewhere (Borcherding et al. 2013, Coulter et al.

2011, Polačik et al. 2009), could explain why base adjustments to the data did not correct for Collingwood as it did for the other locations.

The finding of more variable δ13C in longer established populations could be due to the invasive fish travelling further and feeding on prey from a broader range of habitats. Populations of Round Goby form dense aggregations and are aggressively competitive for habitat space and prey (Lynch and Mensinger 2011, Moran and Simon

2013), which provides a mechanism for intraspecific competition and niche diversification (Bolnick 2001, Svanbäck and Bolnick 2007, Evangelista et al. 2014). High densities in long-established populations could lead to displacement of less-competitive individuals to sub-optimal habitats, and/or longer and further search required to find prey.

Lynch and Mensinger (2011) suggested that the long-distance movements exhibited by a few individuals in Round Goby populations results from habitat saturation, and Brandner et al. (2015) found Round Goby movement (variation in δ13C) in invaded sections of the

Danube river, Europe, to be highly dependent on the availability of suitable habitats.

These findings, and those of the current study, suggest that habitat complexity, and associated diversity of prey, is essential for intraspecific variation in resource use in species with small home ranges. However, longer establishment provides more time to find a greater diversity of prey and habitats, which can ultimately lead to the diversification of traits and have consequences of evolutionary significance (Lambrinos et al. 2004). To see if the different ecological niches are part of an adaptive, plastic response to environmental heterogeneity and the process of naturalisation, the expression of functional genes in association with appropriate phenotypic traits would need to be

78 examined. It would also be of interest to include parameters of community composition, anthropogenic stressors and mechanisms of facilitated transport, although quantifying this information across broad scales is not a trivial task.

Understanding what limits the spread of invasive species following long establishment is crucial for predicting impact of the invaders (Strayer et al. 2006). The obvious outlier in this study (Georgian Bay) suggests that particularly favorable environmental and habitat characteristics can drive expansion of niche breadth beyond that which is expected based on the general trends for the species across invaded ranges; it would be interesting to take a more detailed look at how the role and impact of Round

Goby in this system compares with the other locations in association with niche breadth, prey consumption and ecosystem stability. The traits that associate with widespread distribution can also be applied towards Species Distribution Models (SDMs) to better understand spatial and temporal patterns in biodiversity (Garcia-Berthou 2007, Guisan et al. 2014, Pearman et al. 2008). Modern Species Distribution Models (SDMs) are often based on the principle that species have a static distribution in space and time (Pearman et al. 2008) and lack plastic responses to environmental and ecological variables. This study, however, has demonstrated the important association between time, habitat complexity and genetic diversity for the diversification of ecological niches in a widespread invasive species. Others have emphasised the importance of habitat niche requirements for species range limits (Pulliam 2000, Thomas et al. 2001), including for centrarchid fishes in Ontario (Alofs and Jackson 2015). Combined, these highlight the importance of incorporating dynamic responses of species to environmental and

79 ecological change in modern SDMs, risk assessments following long-establishment of invasive species, and the time scale associated with the naturalization process.

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84 Table 3.1 Population specific demographic and isotopic niche data for invasive Round Goby (muscle tissue) in the Great Lakes from water bodies with different times since first recorded sighting (Year Est.).

YY/ Water Body: Sex 13 15 Site n TL (mm) δ C δ N CR NR SEAB MM Year Est (M/F/I/U) Kn 11/09 Lake St Clair: 1990 Mitchells Bay 49 2/30/0/17 57.4 ± 2.1 0.95 ± 0.02 -18.8 ± 0.1 11.9 ± 0.1 4.6 1.5 1.2 11/11 Sand Point 23 0/0/12/11 31.1 ± 1.3 1.07 ± 0.03 -20.4 ± 0.2 12.3 ± 0.1 3.0 2.4 1.9 11/07 Lake Erie: 1993 Nanticoke 46 8/9/1/28 60.4 ± 1.2 0.98 ± 0.03 -20.7 ± 0.2 14.2 ± 0.1 5.6 2.4 2.0 11/07 Lake Huron: 1994 Port Elgin 27 0/1/1/25 40.6 ± 1.2 1.06 ± 0.05 -19.5 ± 0.2 7.4 ± 0.1 3.7 1.5 1.4 11/07 Lake Ontario: 1999 Hamilton 24 3/4/0/17 44.4 ± 1.5 0.83 ± 0.03 -21.3 ± 0.1 14.7 ± 0.1 1.8 1.5 1.0 11/07 Trent River: 2003 Lake Seymour 47 8/6/2/31 69.1 ± 2.6 1.00 ± 0.02 -26.2 ± 0.1 10.5 ± 0.1 3.4 1.8 1.1 11/08 Lake Simcoe: 2004 Sibbald 33 2/3/0/28 63.2 ± 1.9 1.10 ± 0.05 -21.1 ± 0.1 11.4 ± 0.1 3.9 2.5 1.2 12/09 Lake St Clair: 1990 Mitchells Bay 42 26/15/0/1 57.5 ± 2.0 0.89 ± 0.01 -16.3 ± 0.2 11.1 ± 0.1 4.6 2.6 1.2 12/10 Sand Point 28 22/6/0/0 88.1 ± 2.4 0.91 ± 0.01 -17.4 ± 0.2 10.5 ± 0.2 3.8 3.7 2.2 12/07 Lake Erie: 1993 Nanticoke 48 19/24/5/0 49.4 ± 1.7 0.91 ± 0.02 -20.0 ± 0.2 15.0 ± 0.1 6.2 1.8 1.4 12/07 Lake Huron: 1994 Port Elgin 37 31/6/0/0 75.1 ± 2.1 0.90 ± 0.01 -18.6 ± 0.1 8.3 ± 0.1 1.9 2.4 1.0 12/07 South Bay 35 22/12/0/1 80.2 ± 2.6 0.94 ± 0.01 -17.5 ± 0.2 8.5 ± 0.1 4.6 2.1 2.1 12/07 Tobermory 33 30/3/0/0 83.4 ± 2.3 0.97 ± 0.03 -19.6 ± 0.2 8.8 ± 0.1 3.8 2.5 1.9 12/07 Georgian Bay: 1998 Collingwood 18 11/7/0/0 69.3 ± 3.2 0.89 ± 0.02 -18.2 ± 0.3 10.0 ± 0.2 4.9 1.3 3.4 12/06 Lake Ontario: 1999 Hamilton 48 27/21/0/0 93.3 ± 1.5 1.03 ± 0.01 -22.6 ± 0.1 14.7 ± 0.1 3.3 4.1 2.2 12/08 Trent River: 2003 Lake Seymour 49 24/19/5/1 67.2 ± 2.4 0.94 ± 0.02 -25.5 ± 0.1 10.6 ± 0.1 3.2 1.9 0.9 12/08 Lake Simcoe: 2004 Sibbald 33 15/18/0/0 60.6 ± 1.9 0.96 ± 0.03 -20.9 ± 0.1 11.6 ± 0.1 1.7 2.2 0.8 13/05 Lake St Clair: 1990 Mitchells Bay 17 7/10/0/0 59.2 ± 2.8 0.95 ± 0.01 -17.7 ± 0.5 11.2 ± 0.1 7.8 0.9 2.5 13/10 Peche Island 36 22/13/0/1 63.7 ± 2.9 0.92 ± 0.03 -18.1 ± 0.2 10.6 ± 0.1 3.5 3.1 2.1 13/07 Lake Erie: 1993 Nanticoke 30 18/12/0/0 56.9 ± 1.6 0.98 ± 0.01 -21.0 ± 0.2 15.1 ± 0.3 4.0 9.3 4.9 13/07 Lake Huron: 1994 Port Elgin 37 25/10/2/0 69.6 ± 3.0 0.87 ± 0.02 -18.7 ± 0.1 8.3 ± 0.1 2.8 2.1 1.2 13/07 Tobermory 33 27/6/0/0 84.4 ± 1.4 0.91 ± 0.02 -19.7 ± 0.2 8.6 ± 0.1 4.0 2.2 2.0 13/07 Georgian Bay: 1998 Collingwood 36 19/15/2/0 70.3 ± 1.6 0.95 ± 0.01 -18.7 ± 0.2 8.3 ± 0.2 6.8 6.3 4.6 13/07 Lake Ontario: 1999 Hamilton 28 15/13/0/0 89.1 ± 1.7 1.02 ± 0.02 -21.4 ± 0.2 14.6 ± 0.2 4.5 3.3 2.7 13/07 Trent River: 2003 Lake Seymour 27 14/13/0/0 72.7 ± 2.1 0.96 ± 0.03 -26.3 ± 0.2 10.6 ± 0.1 3.4 1.7 1.3 13/10 Lake Simcoe: 2004 Sibbald 30 20/9/1/0 51.0 ± 1.9 0.88 ± 0.01 -20.7 ± 0.1 11.1 ± 0.1 2.2 2.5 0.9 13 15 13 15 Mean ± S.E. for total length (TL), Fulton’s condition factor (Kn) δ C, δ N, δ C range (CR), δ N range (NR) and Bayesian standard ellipse area 5 13 15 (SEAB). SEAB was calculated from 10 Bayesian iterations of ellipses from δ C and δ N bivariate data. YY/MM denotes year and month sampled.

85 Year Est denotes year of first recorded sighting of Round Goby (USGS.gov). n denotes numbers of individuals/samples. Sex ratio is provided (male/female/immature/unidentified). See Figure 3.1 for map of collection sites.

86 Table 3.2 Population specific demographic and isotopic niche data for invasive Round Goby (liver tissue) in the Great Lakes from water bodies with different times since first recorded sighting (Year Est.).

YY/ Water Body: 1 Sex 13 15 Site n TL (mm) δ C δ N CR NR SEAB MM Year Est (M/F/I/U) Kn 11/09 Lake St Clair: 1990 Mitchells Bay 38 1/24/0/13 57.8 ± 2.4 0.92 ± 0.13 -19.1 ± 0.2 10.0 ± 0.1 5.1 2.4 1.7 11/07 Lake Erie: 1993 Nanticoke 27 7/3/0/17 62.9 ± 1.6 0.95 ± 0.21 -21.1 ± 0.2 13.0 ± 0.1 3.4 2.8 2.0 11/07 Lake Huron: 1994 Port Elgin 5 0/1/0/4 48.3 ± 3.0 0.95 ± 0.12 -21.1 ± 0.5 6.1 ± 0.1 2.8 0.9 2.5 11/07 Lake Ontario: 1999 Hamilton 8 1/1/0/6 46.0 ± 2.1 0.77 ± 0.13 -22.5 ± 0.2 13.4 ± 0.3 1.7 3.2 2.2 11/07 Trent River: 2003 Lake Seymour 32 6/3/0/23 71.9 ± 2.7 1.02 ± 0.17 -26.5 ± 0.1 9.2 ± 0.1 2.7 2.0 1.2 11/08 Lake Simcoe: 2004 Sibbald 24 1/1/0/22 65.0 ± 2.3 1.12 ± 0.25 -22.4 ± 0.2 9.9 ± 0.1 3.1 1.9 1.3 12/09 Lake St Clair: 1990 Mitchells Bay 28 18/10/0/0 53.4 ± 2.3 0.85 ± 0.06 -16.9 ± 0.2 9.1 ± 0.1 4.8 1.7 1.3 12/10 Sand Point 27 21/6/0/0 88.6 ± 2.5 0.91 ± 0.05 -18.2 ± 0.2 9.1 ± 0.2 3.8 3.7 2.3 12/07 Lake Erie: 1993 Nanticoke 36 19/17/0/0 54.1 ± 1.4 0.92 ± 0.16 -19.3 ± 0.1 13.5 ± 0.1 4.1 2.9 1.6 12/07 Lake Huron: 1994 South Bay 30 21/9/0/0 79.1 ± 2.9 0.94 ± 0.09 -18.2 ± 0.2 7.4 ± 0.1 3.8 3.2 2.2 12/07 Tobermory 30 27/3/0/0 83.4 ± 2.4 0.99 ± 0.2 -20.6 ± 0.2 8.3 ± 0.2 4.3 3.8 3.1 12/07 Georgian Bay: 1998 Collingwood 6 4/2/0/0 77.1 ± 7.2 0.92 ± 0.07 -18.4 ± 0.5 8.5 ± 0.7 3.2 1.7 5.3 12/06 Lake Ontario: 1999 Hamilton 45 25/20/0/0 93.4 ± 1.5 1.02 ± 0.09 -23.1 ± 0.1 13.9 ± 0.1 2.7 3.4 1.5 12/08 Trent River: 2003 Lake Seymour 39 21/15/2/1 72.5 ± 2.1 0.93 ± 0.10 -24.9 ± 0.1 9.0 ± 0.1 3.4 1.8 1.1 12/08 Lake Simcoe: 2004 Sibbald 30 14/16/0/0 61.3 ± 2.0 0.97 ± 0.15 -20.8 ± 0.1 9.9 ± 0.1 2.1 2.5 1.0 13/05 Lake St Clair: 1990 Mitchells Bay 17 7/10/0/0 59.2 ± 2.8 0.95 ± 0.06 -19.2 ± 0.3 10.2 ± 0.2 4.5 3.9 3.8 13/10 Peche Island 27 14/12/0/1 57.4 ± 1.6 0.92 ± 0.19 -18.1 ± 0.2 8.7 ± 0.1 3.8 2.7 1.5 13/07 Lake Erie: 1993 Nanticoke 34 17/17/0/0 57.6 ± 1.5 0.99 ± 0.06 -22.0 ± 0.1 13.5 ± 0.1 2.2 1.2 1.2 13/07 Lake Huron: 1994 Port Elgin 30 21/8/1/0 71.5 ± 3.4 0.88 ± 0.11 -19.7 ± 0.1 6.6 ± 0.2 3.0 4.8 2.5 13/07 Tobermory 31 26/5/0/0 84.5 ± 1.5 0.91 ± 0.09 -20.4 ± 0.2 8.1 ± 0.2 4.0 3.7 2.9 13/07 Georgian Bay: 1998 Collingwood 31 16/13/2/0 69.9 ± 1.7 0.94 ± 0.07 -19.4 ± 0.2 6.5 ± 0.2 6.1 5.6 4.4 13/07 Lake Ontario: 1999 Hamilton 29 16/13/0/0 89.3 ± 1.7 1.03 ± 0.11 -23.0 ± 0.2 12.6 ± 0.2 4.2 4.0 3.9 13/07 Trent River: 2003 Lake Seymour 42 24/17/1/0 71.8 ± 1.9 0.95 ± 0.14 -26.7 ± 0.2 9.3 ± 0.1 3.1 1.3 1.7 13/10 Lake Simcoe: 2004 Sibbald 11 7/4/0/0 57.8 ± 4.1 0.89 ± 0.05 -21.4 ± 0.2 9.6 ± 0.2 1.7 2.2 1.5 Notation is as described in Table 3.1 1Sample numbers were different from muscle samples due to the difficulty in obtaining sufficient sample of liver tissue from small fishes.

87 Table 3.3 Shell length (SL) and isotopic niche of baseline primary consumer dreissenids (whole tissue) corresponding to site collections of Round Goby in the Great Lakes. YY/ Water Body Site n SL (mm) δ13Cb δ15Nb C95b N95b SEA MM B 11/09 Lake St Clair Mitchells Bay 31 4.6 ± 0.2 -19.8 ± 0.1 6.4 ± 0.1 2.4 1.3 0.9 11/11 Sand Point 8 14.6 ± 0.9 -21.4 ± 0.2 4.6 ± 0.1 0.6 1.0 1.2 11/07 Lake Erie Nanticoke 26 10.7 ± 0.5 -30.8 ± 0.4 15.7 ± 0.3 2.0 2.8 1.2 11/07 Lake Huron Port Elgin 28 16.3 ± 0.7 -25.6 ± 0.4 10.5 ± 0.3 0.5 0.9 1.1 11/07 Lake Ontario Hamilton 28 11.6 ± 0.3 -23.3 ± 0.2 9.5 ± 0.2 1.2 1.6 0.7 11/07 Trent River Lake Seymour 28 13.3 ± 0.7 -15.8 ± 0.5 8.3 ± 0.4 1.9 0.6 0.8 11/08 Lake Simcoe Sibbald 43 15.2 ± 0.6 -19.1 ± 0.2 7.3 ± 0.1 1.0 0.3 1.9 12/09 Lake St Clair Mitchells Bay 15 18.8 ± 1.0 -21.1 ± 0.3 13.0 ± 0.2 1.4 0.3 3.8 12/10 Sand Point 18 12.9 ± 0.7 -22.7 ± 0.2 12.2 ± 0.2 0.7 0.9 0.6 12/07 Lake Erie Nanticoke 9 14.7 ± 1.0 -27.1 ± 0.2 12.1 ± 0.2 0.6 0.9 1.9 12/07 Lake Huron Port Elgin 31 21.1 ± 0.6 -22.4 ± 0.2 2.3 ± 0.1 0.5 0.4 0.8 12/07 South Bay 15 23.8 ± 0.8 -20.5 ± 0.1 4.2 ± 0.1 0.5 0.5 0.7 12/07 Tobermory 13 16.0 ± 1.4 -21.4 ± 0.1 4.1 ± 0.1 0.5 0.8 1.4 12/07 Georgian Bay Collingwood 30 23.0 ± 0.5 -20.3 ± 0.2 6.4 ± 0.2 0.6 0.4 0.6 12/06 Lake Ontario Hamilton 6 13.1 ± 1.2 -28.0 ± 0.2 7.7 ± 0.1 1.7 1.8 0.4 12/08 Trent River Lake Seymour 30 16.2 ± 0.4 -23.4 ± 0.2 8.1 ± 0.2 0.5 0.2 1.0 12/08 Lake Simcoe Sibbald 30 15.4 ± 0.4 -23.2 ± 0.2 7.6 ± 0.1 0.3 0.2 1.1 13/10 Lake St Clair Peche Island 23 14.8 ± 0.6 -20.6 ± 0.2 4.6 ± 0.1 0.8 0.3 0.7 13/07 Lake Erie Nanticoke 10 16.4 ± 0.9 -21.6 ± 0.4 8.8 ± 0.3 0.9 0.9 0.9 13/07 Lake Huron Port Elgin 39 21.9 ± 0.5 -19.3 ± 0.3 8.4 ± 0.3 0.4 0.4 0.6 13/07 Tobermory 30 18.9 ± 0.8 -21.5 ± 0.2 2.8 ± 0.1 0.5 0.7 1.7 13/07 Georgian Bay Collingwood 10 20.1 ± 1.8 -21.6 ± 0.2 3.1 ± 0.1 0.5 0.7 1.0 13/07 Lake Ontario Hamilton 10 16.2 ± 1.1 -30.5 ± 0.2 7.4 ± 0.2 0.5 0.4 1.0 13/07 Trent River Lake Seymour 20 14.8 ± 0.3 -28.6 ± 0.2 7.2 ± 0.1 0.7 0.5 0.8 13/10 Lake Simcoe Sibbald 10 17.3 ± 1.0 -29.8 ± 0.2 6.5 ± 0.2 0.3 0.3 1.1 Data are mean ± S.E., 95% confidence interval ranges for δ13C (C95) and δ15N (N95), and Bayesian Standard 5 Ellipse Areas (SEAB, 10 iterations) YY/MM denotes year and month sampled n number of individuals and samples analyzed b bootstrapped (n = 1000) and produced using SL as a covariate (at 16.69 mm)

88 Table 3.4 Environmental and habitat characteristics of each site corresponding to Round Goby collection in the Great Lakes. Substrate Macrophyte Detritus Wave Water Year Site 1.clay 2.silt 3.sand 4.gravel 5.boulder diversity density density Height (m)d Temp (∘C)d 2011 Mitchells Bay 0.1 0.4 0.2 0.3 0.70 0.4 0.4 0.23 17.31 2011 Sand Point 0.2 0.7 0.1 0.46 0.2 0.2 0.23 17.31 2011 Nanticoke 0.2 0.7 0.1 0.46 0.2 0.1 0.42 17.11 2011 Port Elgin 0.1 0.2 0.4 0.3 0.70 0.2 0.39 13.31 2011 Hamilton 0.2 0.7 0.1 0.46 0.2 0.24 15.30 2011 Lake Seymour 0.4 0.2 0.3 0.1 0.70 0.5 0.6 - - 2011 Simcoe 0.4 0.2 0.2 0.2 0.72 0.5 0.6 0.31 16.19 2012 Mitchells Bay 0.1 0.4 0.2 0.3 0.70 0.5 0.6 0.23 18.07 2012 Sand Point 0.1 0.7 0.1 0.1 0.48 0.2 0.1 0.23 18.07 2012 Nanticoke 0.2 0.7 0.1 0.46 0.2 0.1 0.34 19.12 2012 Port Elgin 0.1 0.2 0.3 0.4 0.70 0.3 0.50 14.48 2012 South Bay 0.5 0.4 0.1 0.58 0.3 0.50 13.78 2012 Tobermory 0.2 0.2 0.6 0.56 0.3 0.40 14.05 2012 Collingwood 0.1 0.2 0.3 0.4 0.70 0.7 0.3 0.40 14.04 2012 Hamilton 0.2 0.7 0.1 0.46 0.3 0.26 16.51 2012 Lake Seymour 0.4 0.2 0.3 0.1 0.70 0.5 0.7 - - 2012 Simcoe 0.5 0.3 0.2 0.62 0.5 0.6 0.18 17.34 2013 Mitchells Bay 0.2 0.4 0.2 0.2 0.72 0.4 0.8 0.22 16.59 2013 Peche Island 0.2 0.7 0.1 0.46 0.2 0.22 16.59 2013 Nanticoke 0.2 0.6 0.2 0.56 0.2 0.2 0.37 17.48 2013 Port Elgin 0.2 0.1 0.2 0.5 0.66 0.3 0.39 16.42 2013 Tobermory 0.2 0.2 0.6 0.56 0.3 0.35 13.42 2013 Collingwood 0.1 0.2 0.3 0.4 0.70 0.8 0.2 0.38 14.04 2013 Hamilton 0.1 0.4 0.1 0.4 0.66 0.3 0.2 0.18 16.04 2013 Lake Seymour 0.4 0.2 0.3 0.1 0.70 0.4 0.8 - - 2013 Simcoe 0.5 0.2 0.2 0.1 0.66 0.5 0.6 0.17 17.38 c Substrate (particles sizes 1-5 and overall diversity score), macrophyte and litter are each represented as a proportion ranging from 0-1. d Mean significant wave height and surface water temperature for May-Oct of each sampling year from Environment Canada buoys in the vicinity of each sample site.

89

Figure 3.1 Map of sampling sites for invasive Round Goby (Neogobius melanostomus) and dreissenid mussels from the Great Lakes basin collected 2011-2013. See Table 3.1 for year of first recorded sighting of Round Goby in each water body.

90

Figure 3.2 Variation in isotopic niche of invasive Round Goby (a) muscle and (b) liver explained by time of establishment in each water body (Year Est., USGS.org), population specific demographics and site-specific habitat characteristics. Sum of Squares (III) of each variable from General Linear Models Test of Between-subject-effects was used to determine % variation explained. Niche variation is represented by δ13C and δ15N standard error (S.E.), ranges (CR, NR), Bayesian Standard Ellipse Area (SEAB) and 5 standard deviation of SEAB (S.D., from 10 Bayesian iterations). See Table 3S.2 and Table 3S.3 for output summary, Table 3S.4 and Table 3S.5 for most parsimonious model using AIC. SexD= proportional sex diversity, Condition (Kn) = Fulton’s condition factor, Genetic diversity = allelic richness by heterozygosity interaction (Table 3S.1), Year&Month = year and month sampled interaction, Wave Height = mean significant wave height, Water Temp = mean surface water temperature, Substrate = substrate

91 diversity index, Macro&Detr = macrophyte and detritus density interaction, Dreiss 13 15 δ Cb/δ Nb = bootstrapped S.E. and 95% confidence interval range interactions for both δ13C and δ15N of baseline dreissenid mussels at each site/year. Unexplained = variation unexplained by the model.

92

Figure 3.3 Linear regressions for Round Goby muscle tissue covariate adjusted mean ± 13 S.E. SEAB (a) and δ C S.E. (b) with time of first recorded sighting in the Great lakes. Only isotopic niche metrics that had a significant trend with year of first sighting are shown. Regressions exclude Georgian Bay as a significant outlier (> 3 S.D. of the mean). Estimated means for each water body were produced from 2011-2013 data using GLMs with the covariates total length (TL) and baseline dreissenid mussel S.E.b by 95% CIRb interactions for both δ13C and δ15N. ‘Cov & A Adj’ indicates the trend with time of first sighting and isotopic niche metric following adjustment of the ‘Covariate Adj’ linear regression by the linear regression for allelic richness (A) and time of first sighting. Table 3S.1 for genetic data, Table 3.1 for all other population specific data.

93

Figure 3.4 Linear regressions for Round Goby liver tissue covariate adjusted mean ± S.E. 13 SEAB (a), δ C S.E. (b) and CR (c) with time of first recorded sighting in the Great lakes. Notice the different maximum on y-axis than in Figure 3. Only isotopic niche metrics that had a significant trend with year of first sighting are shown. Regressions exclude

94 Georgian Bay as a significant outlier (> 2 S.D. of the mean). Estimated means for each water body were produced from 2011-2013 data using GLMs with the covariates total b b length (TL), sexD and baseline dreissenid mussel S.E. by 95% CIR interactions for both δ13C and δ15N.‘Cov & A Adj’ indicates the trend with time of first sighting and isotopic niche metric following adjustment of the ‘Covariate Adj’ linear regression by the linear regression for allelic richness (A) and time of first sighting. Table 3S.1 for genetic data, Table 3.1 for all other population specific data.

95 SUPPLEMENTAL MATERIAL

Table 3S.1. Genetic diversity for Round Goby populations and genetic divergence from longest established population in Lake St Clair based on microsatellite data from Wellband and Heath (unpublished).

Waterbody: Year Est. n A H FST Lake St Clair: 1990 3 6.71 ± 0.38 0.56 ± 0.02 n/a Lake Erie: 1993 2 6.74 ± 0.09 0.61 ± 0.03 0.0548 Lake Huron: 1994 2 6.07 ± 0.52 0.56 ± 0.03 0.0570 Georgian Bay: 1998 2 5.78 ± 0.75 0.46 ± 0.00 0.0525 Lake Ontario: 1999 3 6.08 ± 0.10 0.53 ± 0.05 0.0735 Trent River: 2003 2 5.12 ± 0.04 0.48 ± 0.02 0.1536 Lake Simcoe: 2004 2 5.73 ± 0.22 0.55 ± 0.04 0.0439 Microsatellites (N = 9, Dufour et al. 2007: Nme 2-10) were genotyped following Bronnenhuber et al. (2011). Mean ± standard deviation for n years of Allelic richness (A), observed heterozygosity (H) and genetic distance (θ, an unbiased estimator of FST following Wier and Cockerham 1984). All genetic parameters were calculated in MSA v4.05 (Dieringer and Schlotterer 2003). Year Est. = Year of first recorded sighting of Round Goby in the water body. See Figure 3.1 for collection sites within each water body, with exception for Tobermory and South Bay. n indicates number of pooled collection years/sites from 2011-2013. A = Allelic richness H = heterozygosity FST = fixation index (genetic distance from Lake St Clair)

96 Table 3S.2. Statistics output for a General Linear Model Test of Between-Subject Effects on the isotopic niche of Round Goby (muscle tissue) in the littoral Great Lakes basin. Niche Type III Mean Partial Eta Noncent. Observed Variable df F Sig. a metric Sum of Sq. Sq. Squared b Par. c Power d δ13C S.E. Year Est. 0.068 5 0.014 4.998 0.038 0.806 24.992 0.714 Sex 0.006 1 0.006 2.146 0.193 0.263 2.146 0.236 D TL 0.002 1 0.002 0.718 0.429 0.107 0.718 0.111

K 0.009 1 0.009 3.35 0.117 0.358 3.35 0.338 n A x H 0.001 1 0.001 0.458 0.524 0.071 0.458 0.089

Year&Month 0.002 1 0.002 0.857 0.39 0.125 0.857 0.123

Wave Height 0.001 1 0.001 0.311 0.597 0.049 0.311 0.076

Water Temp 0.003 1 0.003 0.947 0.368 0.136 0.947 0.131

Substrate 0.003 1 0.003 1.148 0.325 0.161 1.148 0.149

Macro&Detr 0.008 1 0.008 3.108 0.128 0.341 3.108 0.318

Dreiss δ13Ca 0.002 1 0.002 0.845 0.393 0.123 0.845 0.122

Dreiss δ15Nb <0.001 1 <0.001 0.154 0.708 0.025 0.154 0.063

Unexplained 0.016 6 0.003

δ15N S.E. Year Est. 0.052 5 0.01 9.914 0.007 0.892 49.568 0.953 Sex <0.001 1 <0.001 0.138 0.723 0.022 0.138 0.062 D TL 0.005 1 0.005 4.59 0.076 0.433 4.59 0.437

K 0.009 1 0.009 9.041 0.024 0.601 9.041 0.709 n A x H 0.007 1 0.007 6.56 0.043 0.522 6.56 0.574

Year&Month 0.003 1 0.003 3.013 0.133 0.334 3.013 0.31

Wave Height <0.001 1 <0.001 0.012 0.916 0.002 0.012 0.051

Water Temp 0.01 1 0.01 9.416 0.022 0.611 9.416 0.726

Substrate 0.001 1 0.001 0.695 0.436 0.104 0.695 0.109

Macro&Detr 0.001 1 0.001 0.92 0.374 0.133 0.92 0.129

Dreiss δ13Ca 0.007 1 0.007 6.288 0.046 0.512 6.288 0.556

Dreiss δ15Nb 0.004 1 0.004 3.58 0.107 0.374 3.58 0.357

Unexplained 0.006 6 0.001

CR Year Est. 30.783 5 6.157 7.283 0.016 0.859 36.415 0.871 Sex 0.014 1 0.014 0.016 0.902 0.003 0.016 0.051 D TL 3.301 1 3.301 3.906 0.096 0.394 3.906 0.384

K 4.783 1 4.783 5.658 0.055 0.485 5.658 0.514 n A x H 2.26 1 2.26 2.674 0.153 0.308 2.674 0.281

Year&Month 0.387 1 0.387 0.458 0.524 0.071 0.458 0.089

Wave Height 0.309 1 0.309 0.366 0.567 0.058 0.366 0.081

Water Temp 1.052 1 1.052 1.245 0.307 0.172 1.245 0.157

Substrate 0.018 1 0.018 0.021 0.888 0.004 0.021 0.052

Macro&Detr 1.167 1 1.167 1.38 0.285 0.187 1.38 0.169

Dreiss δ13Ca 0.495 1 0.495 0.585 0.473 0.089 0.585 0.1

Dreiss δ15Nb 0.139 1 0.139 0.165 0.699 0.027 0.165 0.064

Unexplained 5.072 6 0.845

NR Year Est. 50.126 5 10.025 12.552 0.004 0.913 62.761 0.984 Sex 4.762 1 4.762 5.963 0.05 0.498 5.963 0.535 D TL 8.46 1 8.46 10.592 0.017 0.638 10.592 0.774

K 7.202 1 7.202 9.017 0.024 0.6 9.017 0.708 n A x H 19.375 1 19.375 24.259 0.003 0.802 24.259 0.982

Year&Month 0.316 1 0.316 0.395 0.553 0.062 0.395 0.083

Wave Height 0.742 1 0.742 0.929 0.372 0.134 0.929 0.129

Water Temp 6.001 1 6.001 7.514 0.034 0.556 7.514 0.63

Substrate 0.062 1 0.062 0.078 0.79 0.013 0.078 0.056

Macro&Detr 0.079 1 0.079 0.099 0.763 0.016 0.099 0.058

Dreiss δ13Ca 11.957 1 11.957 14.971 0.008 0.714 14.971 0.894

Dreiss δ15Nb 8.078 1 8.078 10.114 0.019 0.628 10.114 0.755

97 Niche Type III Mean Partial Eta Noncent. Observed Variable df F Sig.a metric Sum of Sq. Sq. Squared b Par. c Power d Unexplained 4.792 6 0.799

SEAB Year Est. 20.671 5 4.134 15.471 0.002 0.928 77.357 0.995 Sex 0.051 1 0.051 0.189 0.679 0.031 0.189 0.066 D TL 3.056 1 3.056 11.438 0.015 0.656 11.438 0.803

K 4.735 1 4.735 17.719 0.006 0.747 17.719 0.936 n A x H 4.594 1 4.594 17.193 0.006 0.741 17.193 0.929

Year&Month 0.026 1 0.026 0.099 0.764 0.016 0.099 0.058

Wave Height 0.287 1 0.287 1.074 0.34 0.152 1.074 0.142

Water Temp 0.477 1 0.477 1.783 0.23 0.229 1.783 0.204

Substrate 0.246 1 0.246 0.92 0.375 0.133 0.92 0.129

Macro&Detr 0.275 1 0.275 1.03 0.349 0.146 1.03 0.138

Dreiss δ13Ca 2.482 1 2.482 9.289 0.023 0.608 9.289 0.72

Dreiss δ15Nb 0.894 1 0.894 3.345 0.117 0.358 3.345 0.338

Unexplained 1.603 6 0.267

SEAB SD Year Est. 0.769 5 0.154 8.826 0.01 0.88 44.132 0.927 Sex 0.009 1 0.009 0.529 0.494 0.081 0.529 0.095 D TL 0.07 1 0.07 3.993 0.093 0.4 3.993 0.391

K 0.186 1 0.186 10.677 0.017 0.64 10.677 0.777 n A x H 0.113 1 0.113 6.497 0.044 0.52 6.497 0.57

Year&Month 0.001 1 0.001 0.066 0.806 0.011 0.066 0.056

Wave Height 0.003 1 0.003 0.169 0.695 0.027 0.169 0.064

Water Temp 0.026 1 0.026 1.518 0.264 0.202 1.518 0.181

Substrate 0.021 1 0.021 1.221 0.312 0.169 1.221 0.155

Macro&Detr 0.035 1 0.035 1.983 0.209 0.248 1.983 0.222

Dreiss δ13Cb 0.079 1 0.079 4.535 0.077 0.43 4.535 0.433

Dreiss δ15Nb 0.018 1 0.018 1.043 0.347 0.148 1.043 0.139

Unexplained 0.105 6 0.017

See Figure 3.2 for description of variables included. Total degrees of freedom (df) for the corrected model was 16 (23 total populations). Statistics were conducted in SPSS v22. a Sig. Significance of the test (p value). Computed using alpha = 0.05 b Partial Eta squared is the effect size determined by the proportion of variability in the associated dependent measure that is attributed to a factor. c Noncentrality parameter indicates the sampling distribution of the F statistic. This is used to calculate observed power. d Observed power is the probability of correctly rejected the null hypothesis. Note: parameters with a low power (<7) did not have a high Sum of Squares, which was used to determine % variation explained in Figure 3.2.

98 Table 3S.3. Statistics output for a General Linear Model Test of Between-Subject Effects on the isotopic niche of Round Goby (liver tissue) in the littoral Great Lakes basin. Niche Type III Mean Partial Eta Noncent. Observed Variable df F Sig. a Metric Sum of Sq. Sq. Squared b Parameter c Power d δ13C S.E. Year Est. 0.071 5 0.014 13.598 0.013 0.944 67.99 0.926 Sex 0.059 1 0.059 56.793 0.002 0.934 56.793 1 D TL 0.001 1 0.001 0.789 0.424 0.165 0.789 0.107

K 0.008 1 0.008 7.587 0.051 0.655 7.587 0.551 n A x H 0.026 1 0.026 24.596 0.008 0.86 24.596 0.952

Year&Month <0.001 1 <0.001 0.42 0.552 0.095 0.42 0.08

Wave Height 0.012 1 0.012 11.481 0.028 0.742 11.481 0.719

Water Temp <0.001 1 <0.001 0.16 0.709 0.039 0.16 0.061

Substrate 0.004 1 0.004 3.87 0.121 0.492 3.87 0.327

Macro&Detr 0.005 1 0.005 4.778 0.094 0.544 4.778 0.387

Dreiss δ13Ca 0.009 1 0.009 8.875 0.041 0.689 8.875 0.614

Dreiss δ15Nb 0.007 1 0.007 6.887 0.059 0.633 6.887 0.513

Unexplained 0.004 4 0.001 δ15N S.E. Year Est. 0.071 5 0.014 2.864 0.165 0.782 14.318 0.342 Sex 0.129 1 0.129 25.899 0.007 0.866 25.899 0.96 D TL 0.044 1 0.044 8.821 0.041 0.688 8.821 0.611

K 0.008 1 0.008 1.655 0.268 0.293 1.655 0.17 n A x H 0.002 1 0.002 0.456 0.537 0.102 0.456 0.083

Year&Month 0.003 1 0.003 0.639 0.469 0.138 0.639 0.096

Wave Height 0.002 1 0.002 0.491 0.522 0.109 0.491 0.085

Water Temp 0.012 1 0.012 2.326 0.202 0.368 2.326 0.219

Substrate 0.007 1 0.007 1.453 0.295 0.266 1.453 0.155

Macro&Detr 0.027 1 0.027 5.358 0.082 0.573 5.358 0.424

Dreiss δ13Ca 0.016 1 0.016 3.224 0.147 0.446 3.224 0.283

Dreiss δ15Nb 0.03 1 0.03 6.067 0.069 0.603 6.067 0.467

Unexplained 0.02 4 0.005 CR Year Est. 14.069 5 2.814 9.622 0.024 0.923 48.111 0.821 Sex 4.246 1 4.246 14.521 0.019 0.784 14.521 0.81 D TL 0.058 1 0.058 0.198 0.679 0.047 0.198 0.064

K 0.005 1 0.005 0.017 0.902 0.004 0.017 0.051 n A x H 1.155 1 1.155 3.95 0.118 0.497 3.95 0.333

Year&Month 0.215 1 0.215 0.734 0.44 0.155 0.734 0.103

Wave Height 0.137 1 0.137 0.468 0.532 0.105 0.468 0.084

Water Temp 4.441 1 4.441 15.186 0.018 0.792 15.186 0.825

Substrate 0.159 1 0.159 0.544 0.502 0.12 0.544 0.089

Macro&Detr 2.738 1 2.738 9.364 0.038 0.701 9.364 0.636

Dreiss δ13Ca 0.673 1 0.673 2.3 0.204 0.365 2.3 0.217

Dreiss δ15Nb 0.078 1 0.078 0.266 0.633 0.062 0.266 0.069

Unexplained 1.17 4 0.292 NR Year Est. 10.939 5 2.188 3.721 0.114 0.823 18.607 0.428 Sex 5.716 1 5.716 9.724 0.036 0.709 9.724 0.651 D TL 3.059 1 3.059 5.203 0.085 0.565 5.203 0.414

K 7.212 1 7.212 12.268 0.025 0.754 12.268 0.745 n A x H 3.96 1 3.96 6.736 0.06 0.627 6.736 0.505

Year&Month 4.059 1 4.059 6.905 0.058 0.633 6.905 0.514

Wave Height 0.355 1 0.355 0.604 0.48 0.131 0.604 0.093

Water Temp 0.893 1 0.893 1.52 0.285 0.275 1.52 0.16

Substrate 6.764 1 6.764 11.506 0.027 0.742 11.506 0.72

Macro&Detr 7.812 1 7.812 13.289 0.022 0.769 13.289 0.777

Dreiss δ13Ca 4.785 1 4.785 8.139 0.046 0.67 8.139 0.579

Dreiss δ15Nb 2.467 1 2.467 4.197 0.11 0.512 4.197 0.349

99 Niche Type III Mean Partial Eta Noncent. Observed Variable df F Sig. a metric Sum of Sq. Sq. Squared b Parameter c Power d Unexplained 2.351 4 0.588 SEAB Year Est. 7.585 5 1.517 10.249 0.021 0.928 51.243 0.844 Sex 1.094 1 1.094 7.392 0.053 0.649 7.392 0.54 D TL 3.001 1 3.001 20.272 0.011 0.835 20.272 0.912

K 0.164 1 0.164 1.111 0.351 0.217 1.111 0.13 n A x H 0.37 1 0.37 2.502 0.189 0.385 2.502 0.231

Year&Month 0.521 1 0.521 3.521 0.134 0.468 3.521 0.303

Wave Height 0.65 1 0.65 4.393 0.104 0.523 4.393 0.362

Water Temp 0.39 1 0.39 2.637 0.18 0.397 2.637 0.241

Substrate 0.041 1 0.041 0.28 0.625 0.065 0.28 0.07

Macro&Detr 0.416 1 0.416 2.811 0.169 0.413 2.811 0.254

Dreiss δ13Ca 0.357 1 0.357 2.415 0.195 0.376 2.415 0.225

Dreiss δ15Nb <0.001 1 <0.001 0.001 0.979 <0.001 0.001 0.05

Unexplained 0.592 4 0.148 SEAB SD Year Est. 1.022 5 0.204 9.465 0.025 0.922 47.325 0.815 Sex 1.341 1 1.341 62.082 0.001 0.939 62.082 1 D TL 0.076 1 0.076 3.507 0.134 0.467 3.507 0.302

K 0.004 1 0.004 0.176 0.696 0.042 0.176 0.063 n A x H 0.229 1 0.229 10.607 0.031 0.726 10.607 0.687

Year&Month 0.034 1 0.034 1.556 0.28 0.28 1.556 0.163

Wave Height 0.174 1 0.174 8.07 0.047 0.669 8.07 0.575

Water Temp 0.035 1 0.035 1.606 0.274 0.286 1.606 0.167

Substrate 0.071 1 0.071 3.283 0.144 0.451 3.283 0.287

Macro&Detr 0.158 1 0.158 7.333 0.054 0.647 7.333 0.537

Dreiss δ13Ca 0.185 1 0.185 8.586 0.043 0.682 8.586 0.6

Dreiss δ15Nb 0.222 1 0.222 10.299 0.033 0.72 10.299 0.675

Unexplained 0.086 4 0.022 See Figure 3.2 for description of variables included. Total degrees of freedom (df) for the corrected model was 16 (23 total populations). Statistics were conducted in SPSS v22. a Sig. Significance of the test (p value). Computed using alpha = 0.05 b Partial Eta squared is the effect size determined by the proportion of variability in the associated dependent measure that is attributed to a factor. c Noncentrality parameter indicates the sampling distribution of the F statistic. This is used to calculate observed power. d Observed power is the probability of correctly rejected the null hypothesis. Note: parameters with a low power (<7) did not have a high Sum of Squares, which was used to determine % variation explained in Figure 3.2.

100 Table 3S.4. Results from backward variable selection using Akaike Information Criterion 13 15 (AIC) for each niche metric (δ C S.E., δ N S.E., CR, NR, SEAB, and SEAB S.D.; Muscle tissue) where the starting variables in each case were Year Est., SexD, TL, Kn, A & H, PC 1, and PC 2. A & H is allelic richness by heterozygosity interaction (Table 3S.1). PC 1 and PC 2 are the site-specific scores from the first two principle components of a PCA analysis performed on the habitat and environmental parameters (Figure 3S.2a and Table 3.4). Analyses were conducted using the Mass package in R (Version 3.2.3). Niche metric Step Df Deviance Resid. Df Resid. Dev AIC δ13C S.E.a 1 14 0.10 -106.58 2 - TL 1 3.98E-07 15 0.10 -108.58 3 - Year Est. 1 1.34E-03 16 0.10 -110.28 4 - A & H 1 4.37E-03 17 0.11 -111.33 5 - Kn 1 7.35E-03 18 0.12 -111.82 6 - PC 2 1 7.34E-03 19 0.12 -112.40 7 - PC 1 1 3.04E-03 20 0.13 -113.83 δ15N S.E.b 1 14 0.05 -124.44 2 - Year Est. 1 9.64E-06 15 0.05 -126.44 3 - SexD 1 9.32E-04 16 0.05 -127.99 4 - A & H 1 1.58E-03 17 0.05 -129.24 5 - Kn 1 1.92E-03 18 0.05 -130.37 6 - TL 1 2.36E-03 19 0.05 -131.33 CRc 1 14 30.23 24.28 2 - Year Est. 1 9.75E-01 15 30.32 22.36 3 - TL 1 3.27E-01 16 30.65 20.60 4 - SexD 1 4.80E-01 17 31.13 18.96 5 - A x H 1 2.19E00 18 33.32 18.53 NRd 1 14 57.58 39.11 2 - Year&Month 1 5.01E-02 15 57.63 37.13 3 - A & H 1 1.59E-01 16 57.79 35.19 4 - PC1 1 7.90E-01 17 58.58 33.50 5 - Year Est. 1 1.05E00 18 59.63 31.91 6 - Kn 1 1.20E00 19 60.83 30.37 7 - PC 2 1 1.09E00 20 61.92 28.78 8 - TL 1 1.74E00 21 63.66 27.42 e SEAB 1 14 15.05 8.24 2 - SexD 1 2.79E-02 15 15.07 6.28 3 - Year Est. 1 8.88E-02 16 15.16 4.42 4 - TL 1 6.54E-01 17 15.82 3.39 5 - A & H 1 1.04E00 18 16.86 2.85 f SEAB S.D. 1 14 0.58 -66.50 2 - Year Est. 1 4.84E-03 15 0.59 -68.31 3 - TL 1 5.40E-03 16 0.59 -70.10 4 - SexD 1 2.99E-02 17 0.62 -70.97 5 - A & H 1 3.66E-02 18 0.66 -71.66 a 13 Final Model: δ C S.E ~ Year Est. + SexD b Final Model: δ15N S.E ~ Year Est. + PC 1 + PC 2 c Final Model: CR ~ Year Est. + Kn + PC 1 + PC 2 d Final Model: NR ~ SexD e Final Model: SEAB ~ Year Est. + Kn + PC 1 + PC 2 f Final Model: SEAB S.D. ~ Year Est. + Kn + PC 1 + PC 2

101 Table 3S.5. Results from backward variable selection using Akaike Information Criterion 13 15 (AIC) for each niche metric (δ C S.E., δ N S.E., CR, NR, SEAB, and SEAB S.D.; Liver Tissue) where the starting variables in each case were Year Est., SexD, TL, Kn, A x H, PC 1, and PC 2. A & H is allelic richness by heterozygosity interaction (Table 3S.1). PC 1 and PC 2 are the site-specific scores from the first two principle components of a PCA analysis performed on the habitat and environmental parameters (Figure 3S.2b and Table 3.4). Analyses were conducted using the Mass package in R (Version 3.2.3). Niche metric Step Df Deviance Resid. Df Resid. Dev AIC δ13C S.E.a 1 12 0.04 -114.27 2 - A & H 1 5.86E -03 13 0.04 -115.96 3 - Year&Month 1 1.27E-03 14 0.04 -117.29 4 - TL 1 2.96E-03 15 0.04 -117.80 δ15N S.E.b 1 12 0.06 -106.39 2 - Year&Month 1 3.34E -03 13 0.06 -107.18 CRc 1 12 8.60 -0.75 2 - TL 1 6.20E -02 13 8.66 -2.60 3 - SexD 1 2.30E-01 14 8.90 -4.05 4 - Year&Month 1 8.14E-01 15 9.71 -4.20 NRd 1 12 12.69 7.41 2 - Year Est. 1 5.69E -01 13 13.25 6.34 3 - PC 1 1 4.05E-01 14 13.66 4.97 4 - PC 2 1 5.31E-01 15 14.19 3.77 5 - SexD 1 9.25E-01 16 15.11 3.09 e SEAB 1 12 4.18 -15.89 2 - Kn 1 3.61E -02 13 4.22 -17.71 3 – A & H 1 7.72E-02 14 4.29 -19.33 f SEAB S.D. 1 12 0.64 -55.25 2 - Kn 1 3.30E -03 13 0.64 -57.15 3 - Year&Month 1 1.78E-02 14 0.66 -58.57 a 13 Final Model: δ C S.E ~ Year Est. + SexD + Kn + PC 1 + PC 2 b 15N Final Model: δ S.E ~ Year Est. + SexD + TL + Kn + A & H + PC 1 + PC 2 c Final Model: CR ~ Year Est. + Kn + A & H + PC 1 + PC 2 d Final Model: NR ~ TL + Kn + A & H + Year&Month e Final Model: SEAB ~ Year Est. + SexD + TL + Year&Month + PC 1 + PC 2 f Final Model: SEAB S.D. ~ Year Est. + SexD + TL + A & H + PC 1 + PC 2

102

Figure 3S.1 Regressions of nitrogen ranges, carbon ranges and SEAB for muscle and liver tissues by Total Length (mm) for Round Goby populations in the Great Lakes Basin. Nitrogen range (top panel), carbon range (middle panel) and SEAB (bottom panel) were calculated for bulk muscle (left panels, a-c) and lipid extracted liver (right panels, d- f) of Round Goby populations collected in 2011, 2012 and 2013 across the Great Lakes Basin. Each symbol represents a site/year of collection. Populations that were prominent outliers in one of the regressions are represented in all the figures using the same symbols (e.g. black square = Collingwood 2013). Collingwood 2013 and Nanticoke 2013 were not used in regression calculations. Regressions for nitrogen range and carbon range were linear, regressions for SEAB were parabolic.

103 (a)

(b)

Figure 3S.2 Variation in sites based on a PCA of environmental and habitat parameters (water temperature, wave height, substrate diversity, Macrophyte density, detritus density, dreissenid baseline δ13C S.Eb. and 95 % CIRb, δ15N S.Eb and 95% CIRn) for (a) muscle tissue sites and (b) liver tissue sites. In both cases, PC 1 summarized 64 % of the data, while PC 2 summarized 24 %. PCAs for muscle and liver were conducted on similar data, with exception for two additional sites for muscle tissue (Sand Point, Lake St Clair in 2011, and South Bay Mouth, Lake Huron in 2012).

104 CHAPTER 4

CONTRASTING NICHES OF INVASIVE FISHES IN NATIVE AND INVADED

REGIONS

105 INTRODUCTION

The anthropogenic spread of species to non-native regions has had and continues to have repercussions for ecosystems, biodiversity and the economy (Simberloff et al.

2013). One unintentional consolation is the insight gained regarding fundamental ecological and evolutionary theory (Sax et al. 2007). Characterisation of traits in closely related species that co-occur in the same regions but with different distributions can help determine the mechanisms for survival across broad or narrow ranges (Soberón 2007).

Furthermore, determining the factors that influence the spread and distribution of species is crucial for monitoring biodiversity, ecosystem stability and impact from species introduction (Hayes and Barry 2008, Sax et al. 2007). The term ‘pre-adaptation’ implies that native populations of certain invasive species have traits that improve their chances of success in invaded regions (Ricciradi and Mottiar 2006) and species that are introduced to novel environments are generally considered to benefit from a flexible phenotype, particularly in association with diet (Broennimann et al. 2007, Guisan et al.

2014). Novel resources can test the limits of a dietary niche (i.e. range of prey consumed), and efficient acquisition of different prey may require alternative techniques that lead to niche shifts in the individual and a change in niche breadth of a population

(Tingley et al. 2014).

Several stages in the invasion process (transport, establishment, spread) provide opportunity for bottlenecks which could reduce phenotypic diversity, and/or that favour adaptive change due to the presence of novel competitors, predators, prey, climate and anthropogenic stressors (Blackburn et al. 2011, Mahoney et al. 2015). Niche breadth of invaded populations could be restricted due to the stressors of the invasion process, or the

106 characteristics of the invaded region, such as less heterogeneity in environment/habitat or

resources (i.e. restricted fundamental niche, Holt 2009). Alternatively, niche breadth of

invaded populations could have expanded due to, for example, enemy release hypothesis

(lack of predators, competitors and/or parasites), empty niches or competitor superiority

(compared to other species in invaded region, Jeschke 2014). Invasive species are often

suggested to perform better in their new ranges than native ranges, although the pattern

does not seem to be universal (Parker et al. 2013). A broader niche in invaded

populations, but not native region populations, would imply that niche breadth is a result,

or potentially a requirement, of the invasion process.

Stable isotopes of carbon (δ13C) and nitrogen (δ15N) provide a useful tool for quantifying diet history and prey-related habitat use (Post 2002, Vander Zanden et al.

1997). Bayesian estimates of population δ13C and δ15N have been shown to be

particularly useful in depicting dietary and habitat niches of invasive species (isotopic

niche; Comte et al. 2016, Guzzo et al. 2013, Jackson et al. 2014). Furthermore, different

tissues have different turn-over rates, and thus, represent different time periods of diet

integration (Guelinckx et al. 2007, Phillips and Eldridge 2006). It is, therefore, feasible to

infer changes in diet through time within each individual by comparing isotopic niche

from muscle and liver tissues (Quevedo et al. 2009).

Values of δ13C and δ15N vary temporally and spatially in association with inputs to the system and fractionation of isotopes within the system (Newsome et al. 2007, Post et al. 2007). It is recommended that primary and secondary consumers be used to distinguish variation in δ13C and δ15N that is driven by changes at the base of the

ecosystem (i.e. baseline), as opposed to changes in consumer prey consumption

107 (Cummings et al. 2012). The diet of consumers is also dependent on prey and resource

availability, and incorporating the dominant trophic base of the ecosystem can broadly

help identify the diversity of prey available for species at higher trophic levels.

By comparing populations in native and invaded regions, this study aims to

develop our understanding of widespread establishment in invasive species by focusing

on the importance of niche breadth in native regions for survival in novel ecosystems.

The fishes within this study are among the most widespread of all aquatic invasive

species (Round Goby / Neogobius melanostomus), along with closely related but less

widespread species from the same family (Gobiidae) (Tubenose Goby / Proterorhinus

semilunaris, Racer Goby / Babka gymnotrachelus and Monkey Goby / Neogobius fluviatilis), and have a high likelihood of establishment in novel regions given successful transportation (Lowry et al. 2012, Snyder et al. 2014). We hypothesise that more widespread and abundant (i.e.. successful) invasive species (Round Goby) in the

Laurentian Great Lakes will have greater trophic and habitat niche breadth than less successful invasive species (Tubenose Goby) or those that have yet to invade (Racer and

Monkey Goby) in their native ranges (Black Sea region), as was previously found to be the case for Round Goby compared to Tubenose Goby in the invaded ranges of the Great

Lakes (Pettitt-Wade et al. 2015). We also predict that broader isotopic niches would be found in populations that have been established for 15-20 years in the Great Lakes basin than current native populations in the NW Black Sea region. Dietary and habitat niche are often recognised to be important for the success of aquatic invasive species (Hayes and

Barry 2008, Lucek et al. 2014, Vázquez 2006), particularly goby fishes (Järv et al. 2011,

Pettitt-Wade et al. 2015, Polačik et al. 2009), but are rarely characterised for multiple co-

108 occurring invasive species in native and invaded regions simultaneously. This study will

help identify if feeding ecology characteristics, or metrics of potential invading species,

can predict their impact and success in new or invaded regions.

METHODS

Study species and regions Samples of goby (invasive fishes) and invertebrates (baseline) were collected from littoral fringes of the invaded North American Great Lakes basin Aug-Sep 2011-

2013 and native Ukrainian Black Sea region Aug 2013 (Figure 4.1, Table 4.1). In both the Great Lakes basin and North West Black Sea region, sampling locations were partly restricted by specific locations where Tubenose Goby can be found in abundance.

Locations were also chosen due to significance as source/sink locations for goby invasion

(i.e. Kherson [source] and Lake St Clair [sink]; Stepien and Tumeo 2006), proximity to ports, large river systems or prominent water bodies. In the Great Lakes basin, fishes were captured using a bag seine net (SEM-03, 50' long, 4' tall, 4' x 4' x 4' cod end, 1/4" mesh, Franklyn Net and Twine, Wheatley, ON), angling and minnow traps (16.5'' length with 9'' diameter). In the Ukraine, fishes were collected using angling and a small sled- dredge (Bottom Sled, mesh net 243µm, 20.5 x 15 x 5"). Fishes were euthanized on collection, placed on ice and either frozen (-40°C) and returned to the lab for further processing or processed immediately on collection. Measurements were taken (wet mass

± 0.1g; total length and standard length minimum ± 0.1mm using 150mm callipers), sex determined and dorsal muscle and liver tissue were removed and either oven dried (>48 h at 40-50°C) or re-frozen and freeze-dried. The proportion of male/female/immature/unidentified fish were later converted in to a proportional sex

109 diversity index (SexD) for each population using the methods in Chapter 3 of this dissertation (page 63).

Baseline invertebrates were collected by hand or by sled-dredge from specific locations where fishes were obtained. Plankton/suspension filter-feeding bivalves

(Dreissenidae and Unionidae) were targeted as the dominant group for spatial and temporal comparisons. Baseline comparisons were supported by detritivores shredders/collectors (Amphipoda, Chironomidae, Isopoda, Oligochaeta), and detrivore/herbivore-grazers (Neritidae, Hydrobiidae), depending on the availability of species within each ecosystem. Methods used for the preparation of fishes for isotope analysis were also applied towards baseline organisms. Bivalves and gastropods were measured (shell length, tissue wet mass and dry mass), shells removed and other invertebrates pooled for stable isotope analysis. When obtained in sufficient quantity, multiple baseline species were included in addition to bivalves as a measure of benthic productivity, niche diversification at the base of the food web and species density/packing within each location.

Stable isotope analysis Dried samples were ground until homogeneous using mortar and pestle and scissors. High lipid content drives unpredictable variation in δ13C (Post et al. 2007), thus all liver and whole invertebrate tissues were lipid extracted using solvent distillation, see

(Pettitt-Wade et al. (2015) for details). All samples were individually weighed into tin cups (5mmx9mm, 400-700µg; ± 1µg), then run alongside standards for δ13C and δ15N,

C% and N%, using a Delta V IRMS (Costech, Santa Clarita, California, USA). The

following equation was used to calculate δ13C and δ15N:

110 � δR ‰ = − 1 × 1000 � where R refers to the isotope ratio for 15N/14N or 13C/12C and delta (δ) is the standard

notation for the abundances of stable isotopes in samples relative to standard materials.

Atmospheric nitrogen was used as a standard for N2 and Pee Dee Belemnite (PDB)

th carbonate for CO2. Every 10 sample was run in triplicate to assess repeatability. NIST

standards and an internal fish muscle standard (Tilapia, Oreochromis niloticus) were run

every 12th sample to assess precision, which was 0.15, 0.16 and 0.20‰ for δ15N and 0.07,

0.1 and 0.1‰ for δ13C for NIST bovine muscle 8414, n = 407; bovine liver 1577c, n =

450; Tilapia, n = 618, respectively. Accuracy from standards run in 2012 – 2015

compared to certified data was within 0.01, 0.18 and 0.05‰ for δ15N (NIST 8563, 8548

and 8549 respectively, n = 196-198), -0.06 and -0.02‰ for δ13C (NIST 8542 and 8573

respectively, n = 173).

Statistical analysis

Total length, shell length, Log10 wet mass and stable isotope data for each population did not differ significantly from a normal distribution (Kolmogorov-Smirnov) or homoscedastic variance (Levene’s). Comparisons were made for δ13C and δ15N

between different spatial and temporal collections of the same species of invertebrate and

fish within each region. General Linear Models (GLMs) were used to determine the

influence of standard length/shell length, number of samples pooled (non-bivalve

invertebrates only), C:N ratio (high C:N indicates remaining lipid despite lipid

extraction), sex proportional diversity (sexD, fishes only), year and month of collection

and baseline niche variation (see Baseline community and Niche metrics and ellipses

sections) on δ13C and δ15N. Parameters that had a significant effect were used as

111 covariates for intra and inter specific comparisons between populations for fish muscle,

liver and invertebrate whole tissue using Analysis of Covariance (ANCOVA) and

Tukey’s post-hoc test for least significant difference among pairwise comparisons. When

a strong sample size effect (Cohen’s power analysis) was found, data was bootstrapped

(Simple design in SPSS, n = 1000, 95% CI) prior to ANCOVA. All analyses were

conducted in SPSS v.22 or R v3.1.0 with a significance threshold of p < 0.05.

Niche metrics and ellipses Standard Ellipse Areas (SEA) of bivariate δ13C and δ15N data from multiple

individuals were used to depict the isotopic niche of a population using the package

Stable Isotope Bayesian Ellipses in R - SIBER (Jackson et al. 2011). Each ellipse

captures the concentration of variability (40%) in δ13C and δ15N of a population relative to the mean (centromere of the population bi-plot). The addition of an additional degree of freedom provides a correction for the use of bivariate data and differences in sample

5 size (SEAC). Multiple Bayesian iterations (10 ) were run to provide for quantifiable comparison of ellipse size (SEAB) using credible intervals about the mode, and further robust correction of sample size differences.

Baseline community Comparisons of bivalve filter feeders (dreissenidae and unionidae), detritivore/shredders and the detrivotre/herbivore grazers were made among sites to determine source-driven changes in stable isotopes. For comparisons of goby populations between regions, data was baseline corrected using the methods of Olsson et al. (2009) and Chapter 5 in this dissertation (page 143).

112 Niche plasticity Niche plasticity was quantified for goby fishes by subtracting stable isotope data of liver tissue from muscle tissue (Pettitt-Wade et al. 2015). Muscle has a longer nutritional turnover than liver tissue and thus provides a longer inference of diet history than liver tissue, and comparison of these tissues can provide a measure of change in diet through time by each individual (Quevedo et al. 2009). The differences between muscle

13 15 and liver were calculated for δ C, δ N, CR, NR and SEAB within each individual and averaged for each population to depict dietary plasticity of each population. Baseline community niche metrics were used as covariates in comparisons of dietary niche

13 15 plasticity between goby populations (i.e. difference in δ C, δ N, CR, NR and SEAB between tissues, ANCOVA).

RESULTS

Baseline community There were some distinct differences in stable isotope values of the baseline communities obtained from different sampling locations in the NW Black Sea region and

Great Lakes basin (227 and 213 samples, respectively)(Table 4.1). Filter feeders were not found in one location (Obitoshnia, tributary ~100m from Sea of Azov), whereas

Detritivores and Detrivore/Herbivore grazers were not found in several locations (Table

4.1). Filter-feeder baseline organism CR, NR and SEAB were lowest at Sand Point (Lake

St Clair) and highest at Collingwood (South Georgian Bay), Vylkove (tributary in the

Danube estuary) and Kherson2 (small tributary in the Dnieper estuary)(Table 4.1).

Invasive fishes Of 705 goby fishes processed, 422 were Round Goby (128 native region, 298 invaded region) and 219 were Tubenose Goby (131 native, 88 invaded). The remaining

113 were species that have not invaded North America, although have invaded throughout

Europe, and were collected in their native region (Racer Goby and Monkey Goby, 80 and

38, respectively)(Table 4.2). Multiple species of goby were found at each site in the

native region, with exception for Obitoshnia (Azov region, Tubenose Goby only).

Species of goby sampled from each location were the most abundant goby species

present, but other species of goby were often found at each site in the Ukraine (e.g.,

Syrman Goby (Ponticola syrman): Sasyk Lake, both Dniester sites and Kherson1).

Tubenose Goby generally had the smallest body size, followed by Round Goby,

Racer Goby then Monkey Goby (Table 4.2). Some of the smallest fish were not sampled

for liver but were sampled for muscle, so average body size was slightly higher at each

site for liver (Tables 4.2 and 4.3). Some notable significant linear relationships were

13 15 found between δ C, δ N, body size (TL and Log10 wet mass) and sexD. The relationship between δ13C and body size was positive for Danube Round Goby and Racer Goby, and

Lake Superior Tubenose Goby (linear regression for muscle δ13C and TL, R2 0.1 – 0.3, p

< 0.05), but negative for Mitchells Bay (Lake St Clair) Round Goby and Tubenose Goby

and Danube Monkey Goby (Muscle δ13C and TL, R2 0.2 – 0.5, p < 0.05). A significant

positive trend between δ15N and body size was found for Danube Racer Goby muscle (R2

= 0.35), but negative for all Danube populations for liver tissue (R2 = 0.1) and Lake

2 Superior Tubenose Goby muscle (negative, R = 0.1). SexD had a significant effect on

δ13C and δ15N for some populations (Mitchells Bay Round Goby and Sand Point muscle only, all populations in Dnieper estuary and Sasyk Lake Monkey Goby liver), with individuals that were unidentified having a significantly different δ13C and δ15N than

males and females (ANCOVA with covariates TL and Log10 wet mass, p < 0.05).

114 Within region species comparisons In the native NW Black Sea region, Round Goby generally had a significantly

smaller isotopic niche (SEAB) than other goby species sampled from each site (Figure 4.2

and 4.3, Tables 4.2 and 4.3). This contrasted with what was found for the invaded Great

Lakes basin, in which Round Goby had a significantly larger isotopic niche than

Tubenose Goby in most comparisons (Mitchells Bay muscle tissue was the exception,

comparisons between species within the same region only). The two species within our

study that have not established in the Great Lakes basin, Monkey Goby and Racer Goby,

had a significantly higher isotopic niche than sympatric populations of Round Goby and

Tubenose Goby, with exception for Tubenose Goby in Dnieper estuary and Danube

Estuary when comparing muscle tissue (15/17 comparisons). For comparisons, data were

either bootstrapped or based on Bayesian estimates for niche metrics, although Bayesian

estimates can be spurious for generating ellipses with samples sizes <10 (Jackson et al.

2011).

Comparing muscle and liver δ13C and δ15N as a measure of change in diet history and niche plasticity revealed further region-specific differences among species, that were less consistent than found from individual tissue analysis (Figs 4.2, 4.3 and Table 4.4).

Differences between muscle and liver tissue were highest among individuals (δ13C, δ15N)

and for total population (CR, NR, SEAB) of Round Goby compared to Racer Goby and

Tubenose Goby in the Dnieper estuary, but the opposite was found for all other locations

within the NW Black Sea region (Table 4.4). Muscle and liver tissue ellipses were very

similar in size in the Dniester estuary for both Round Goby and Tubenose Goby (<0.05

SEAB difference), despite a difference in both CR and NR (Table 4.4). The largest

difference in SEAB between tissues was in Tubenose Goby from the Sea of Azov

115 tributary (Obitoshnia; -2.3 ‰2 difference muscle –liver, >90% simulations show larger

niche in muscle tissue).

Comparisons across all regions

In muscle tissue, CR, NR and SEAC were found to be significantly smaller for

native Round Goby populations than invasive Round Goby populations (Table 4.2, Table

4.3 and Fig 4.4a). This contrasted with Tubenose Goby for which, overall, no difference

was found between native and invaded region CR, NR and SEAC. For liver tissue, no

overall difference was found between native and invasive populations of each species,

although invasive Tubenose Goby did have a smaller SEAC and NR than both native and

invasive Round Goby. Monkey Goby and Racer Goby generally had the highest SEAC and NR than other species (native and invasive). Dnieper Tubenose Goby had the highest

CR for muscle and liver tissue, which drove a high SEAC (i.e. low NR). In contrast,

Dnieper Round Goby had high CR and NR that drove the high SEAC (Table 4.3, Fig 4.3).

DISCUSSION

Variability in a species’ diet, either temporally or spatially, implies a capacity for responding to fluctuations in available resources, which can be favourable when species are introduced to a new location. Successful invasive species are often assumed to have this capacity, as invaded regions are likely to have a different resource base than native ecosystems. Yet the difference in dietary niche of invasive species in native and invaded ranges is rarely focussed on and could provide important clues for understanding why some invasive species are more successful than others (wider distribution, higher abundance etc.). Using stable isotopes, I compared the trophic and habitat niche of four taxonomically similar invasive fish species (Gobiidae), with contrasting invasion

116 histories (relative success), in their native NW Black Sea region with non-native

Laurentian Great Lakes. Values of δ13C and δ15N revealed a divergence in isotopic niche breadth and niche plasticity between species in native and invaded regions, and an increase in niche breadth from native to invasive populations for the most successful and widespread invasive species but not for the less successful invader. Surprisingly, the species with the most widespread distribution and abundance, and largest isotopic niche breadth in the invaded Great Lakes (Round Goby), had the smallest niche breadth in the native region.

Niches in the invaded region In the Great Lakes basin, we found Round Goby to have a broader trophic and habitat niche than the less successful Tubenose Goby in all comparisons, with exception for the most recently established location for the tissue with the longest turnover (Trent

River, muscle tissue). These findings were supported in Pettitt-Wade et al. (2015) for

Great Lakes populations of the two species where they are found in sympatry. Gut contents analysis has revealed broader diet in Round Goby compared to Tubenose Goby for several invasive populations in Europe (Vašek et al. 2014), and for Round Goby compared to several other invasive gobiids (Brandner et al. 2013b, Roşca and Surugiu

2010).

Greater size range of Round Goby has been suggested as a mechanism (larger gape size and ontogenic diet shifts) for broader isotopic niche and greater niche plasticity than in the less successful Tubenose Goby (Brandner et al. 2013a, Pettitt-Wade et al.

2015, Vašek et al. 2014). Body size is often a driving force of variation in diet and can have a prominent influence on the trophic position of goby fishes (Brandner et al. 2013b), as indicated by the relationships between δ15N and body size for Racer Goby and

117 Tubenose Goby in the present study. Additionally, we found body size, and in some instances sex/gender, to have a significant relationship with isotopic niche breadth. Large reproductive male Round Goby are characterised with having an aggressive behaviour, which has been suggested as a mechanism for outcompeting native species for prey and habitat space (Balshine et al. 2005, Groen et al. 2012).

It is possible that the non-native locations in which Round Goby and Tubenose

Goby overlap in distribution are not optimal for Tubenose Goby (i.e. Lake St Clair in this study). In Ukraine, Round Goby and Tubenose Goby were not found in the same exact location and baseline comparisons did reveal some ecosystem differences (i.e. Tubenose

Goby obtained from small tributaries in each region of Ukraine, whereas Round Goby was obtained from exposed lake or larger connecting river). Several studies have argued that Round Goby establishment is facilitated by broad habitat use (Brandner et al. 2013b,

Kornis et al. 2013), and that narrow diet, including the lack of ontogenetic diet shifts, provides a restriction to colonisable habitats for the Tubenose Goby (Eros et al. 2005,

Vašek et al. 2014). However, Tubenose Goby had a larger isotopic niche than Round

Goby in their native range, suggesting that available habitat, or diet plasticity, may be the limiting factor in the more limited distribution of Tubenose Goby.

Genetic and phenotypic bottlenecks during the invasion process, driven by differences in propagule pressure, could have also driven restricted dietary or habitat niche in one species than the other. Propagule pressure, the number of viable populations that are introduced (propagules) multiplied by the number of introduction events, is one of the main factors that influences establishment success (Simberloff 2009). It could be that fewer propagules of Tubenose Goby were transferred to the Great Lakes from a less

118 diverse range of locations than for Round Goby (Dillon and Stepien 2001, Stepien et al.

2005). The genetic diversity of Round Goby in the Lake St Clair region is particularly high (Brown and Stepien 2008). Although Kherson (Dnieper) has been pinpointed as the predominant source location (Stepien et al. 2005), populations in Lake St Clair were reportedly sourced from multiple locations, and could have greater genetic diversity than any single native region population.

Niches in the native region Our hypothesis of a broader isotopic niche in native regions for more successful aquatic invasive species in invaded regions (i.e. most widespread in invaded region) was rejected when comparing species in their native ranges. Populations of Round Goby, the most widespread invasive goby species in the invaded Great Lakes, had a niche breadth that was generally smaller than Tubenose Goby, Monkey Goby and Racer Goby in their native range. This contrasted with populations of Round Goby that had previously been found to have greater niche breadth than populations of Tubenose Goby in the invaded regions of the Great lakes (Pettitt-Wade et al. 2015), further confirmed in this study, and in Europe (Vašek et al. 2014). A long history of intra and interspecific competition in the native region would provide more opportunity to develop feeding strategies that are more optimum for specific prey (Emlen 1966). For the Round Goby, this could have driven specialisation (i.e. feeding on a narrow range of prey) in native region populations and/or longer established invasive populations.

Anthropogenic stressors could have been a driving force for specialisation in

Round Goby populations in the Ponto-Caspian region. Industrialisation can lead to nutrient run-off, habitat destruction and reduced system-wide productivity, factors that are potential mechanisms for reduced size range and dietary niche of native Azov goby

119 populations from a reduction in diversity of prey available (Sokołowska and Fey 2011).

These stressors would be expected to impact all species. Round Goby are also commercially targeted and have been subject to overfishing in the past, particularly in the

Sea of Azov (Sokołowska and Fey 2011). Sokolowska and Frey (2011) suggest that the overfishing led to a bottleneck in native populations of Round Goby that had reduced maximum size range. Changes to the prey community, coupled with relatively high abundance of con-specific species (i.e. other non-target goby species) when resources are limited, could have further increased interspecific competition, and driven a greater dependence on specific prey for which Round Goby is better adapted for consuming than are other competitors (e.g. bivalves; Devictor et al. 2010, Svanbäck and Persson 2004).

Contrasting niches in native and invaded regions Isotopic niche sizes differed between native and invaded regions for both the successful and less successful goby species, and the relative ranking of niche breadth also differed between regions. This suggests that the invasion process can have a strong impact on the feeding ecology of the invading species. It also highlights that feeding ecology metrics in the native range may not be a good indicator of behaviour in a new ecosystem. There are several general hypotheses in invasion ecology that could explain the incidence of a broader niche in invaded regions for invasive species (Jeschke 2014,

Parker et al. 2013).

Round Goby has demonstrated competitive superiority to many native species regarding prey and habitat space in the Great Lakes (Balshine et al. 2005, Groen et al.

2012) and across invaded Europe (Ustups et al. 2015, Van Kessel et al. 2011). In contrast to the invaded Great Lakes, the Ponto-Caspian region is home to many parasites, predators and competitors that have co-evolved with Gobiid fishes and could restrict the

120 niche of Round Goby (Brandner et al. 2013b, Van Kessel et al. 2011), including the other three species of goby in this study that have been shown to compete for habitat space and prey (Borcherding et al. 2013, Števove and Kovac 2013, Van Kessel et al. 2011). i.e.

Enemy Release/Darwin’s Naturalisation Hypothesis (Diez et al. 2008). Introduced populations of a species are generally less parasitized than native populations (Torchin et al. 2003), as is the case for these goby fishes (Gendron et al. 2011, Kvach and Stepien,

2008). In the present study, dissections revealed macro-parasites in abundance in native

Ukraine goby populations, but not in invasive Great Lakes populations (Pettitt-Wade, H.

Pers. Obs, 2013). Although, Gendron et al. (2011) suggested that native parasites are beginning to adapt to the goby in long-established regions, as they have more parasites than recently established populations and numbers have increased over time.

Empty Niche Hypothesis implies that invasive species are not in competition for particular resources in invaded regions because other species do not capitalise on those resources (Parker et al. 2013). Round Goby can avoid competition by feeding on

Dreissenid bivalves, or other molluscs, for which many other native species are not well adapted (Diggins et al. 2002, Thompson and Simon 2014). Although in the Great Lakes basin, invasive dreissenids now contribute a considerable portion of the diet for a number of native species of fish, birds and reptiles (Magoulick and Lewis 2002, Naddafi and

Rudstam 2014), as do invasive gobiids as prey for birds, fishes and reptiles in the Great

Lakes (Coleman et al. 2012, King et al. 2006, Ontario Ministry of Natural Resources and

Forestry 2015) and Europe (Płąchocki et al. 2012; Wellband, K. W. Pers. Obs. 2013).

Increase in ‘enemies’ for these invaders suggest biotic resistance increases over time following perpetual invasions. More recently invaded populations might have reduced to

121 a niche breadth more comparable to native populations, as we found for the most recently

established site in the Great Lakes (Trent River). Indeed, more recently invaded

populations of Round Goby in the Great Lakes were shown by others to have reduced

predation risk than longer established Trent River populations (Brownscombe and Fox

2012).

Habitat suitability and invasion success Several Tubenose Goby populations had broader niches in native regions than

invaded regions. Broader niche of Tubenose Goby in the native range was often tied with

much higher CR than Round Goby, indicating Tubenose Goby feed on prey from a

broader habitat range. Populations of Tubenose Goby in invaded ranges were also found

to have higher CR and difference in δ13C between tissues than the more widespread

Round Goby in the Great Lakes, despite greater overall isotopic niche breadth in Round

Goby (Pettitt-Wade et al. 2015). Habitat preference is an important factor to consider when determining the ability of species to survive facilitated transportation via ballast exchange, or the distance that can be covered via natural dispersal in lakes, rivers and tributaries (Hayes and Barry 2008, Vanderploeg et al. 2002). Genetic analysis suggests that Tubenose Goby in the Great Lakes, and some invasive Ukraine populations, share some relatedness with Tubenose Goby forms from both the Caspian and Black Sea regions (Dillon and Stepien 2001). The ‘Pontic’ form originates in the Black Sea and

Azov region, the ‘Caspian’ form originates in the Caspian Sea (Naseka et al. 2005). Both forms have spread throughout major river basins in the Ukraine via canals and reservoirs, but they could have different habitat preferences (Eros et al. 2005, Naseka et al. 2005,

Vašek et al. 2014). As opposed to habitat generalist, the species could specialize on habitats that have a particularly diverse carbon source (i.e. variable δ13C in baseline

122 organisms). In some regions, Tubenose Goby are suggested to have particular preference

for small tributaries with high macrophytes (Eros et al. 2005, Janáč et al. 2012). Baseline

for our Ukraine Tubenose Goby sites often had variable δ13C, and tributaries can have

particularly variable δ13C due to both terrestrial and aquatic inputs and high residence time of the shallow water in places where flow is minimal (Hoffman et al. 2010). This variation would have been accounted for in our baseline corrections prior to niche comparisons between regions. But this adds to the often implied but rarely tested notion that Tubenose Goby has a different optimal habitat than other invasive gobiids, and indicates the importance of flexible habitat requirements for invasion success.

Performance in invaded regions compared to native regions varies depending on the invasive species (Parker et al. 2013). Our findings of a different dietary niche in invaded regions than native regions for the more successful species, and not less successful species, implies dietary niche can influence species-specific differences in success. Dietary niche is also associated with environmental heterogeneity and prey diversity and abundance. We corrected for ecosystem differences using primary and secondary consumers that were also common prey species of the invasive fishes in this study. Incorporating variation in stable isotope composition of these functional groups and of prey provided a measure of baseline productivity and resources available to higher trophic levels. Some locations that had high baseline variability correlated with high variability between goby individuals (e.g. Georgian Bay and Sea of Azov sites). It would be of interest to investigate more thoroughly the influence of environmental heterogeneity on niche breadth, which is often suggested to promote niche expansion and

123 could be a mechanism for the success of Ponto-Caspian species invasions in Europe and

North America (Reid and Orlova 2002).

Conclusions The anthropogenic spread of species across the globe is occurring at an unprecedented scale and understanding the primary forces that facilitate survival of species across different environments is essential for mitigating biodiversity loss. Our findings indicate that more successful invasive species have variable niches across different environments, but that the niche of source populations alone will not necessarily provide this information. This suggests that, in this case, it is a factor of the invasion process and that a plastic or adaptive change in the population is required to respond to a novel environment. The niches occupied by species in their home range are influenced by many factors that are likely to differ from a potentially invaded region (e.g. species composition, environmental and anthropogenic stressors). Thus, one cannot rely on the ecological niches of native populations to be predictive of their invasion potential and associated risk of impact. However, simulating the introduction event for native populations in a controlled laboratory setting could provide further insight on the association between a history of environmental heterogeneity (i.e. Ponto-Caspian, Reid and Orlova 2002) and invasion potential.

Taxonomically similar invasive species with different distributions are rarely compared in both native and invaded regions (but see Comte et al. 2016). Indeed, this was the first study to directly compare the dietary niche of goby species in native Ukraine with invaded Great Lakes, despite their prevalence in the literature. More detailed analysis of genetic diversity in association with ecological data in native and invaded ranges could help determine the relative impact of founder effects versus multiple

124 invasion events on niche breadth and invasion success. Considering the spatial scope of our study, it is unlikely that our findings were limited to the year sampled (years in case of invaded region). But incorporating the influence of time into the analysis would provide a measure of scale for long term forecasting, for instance, under different climate scenarios. Analysis of functional genotypes in individuals at a scale from native, long- established invasive and recently introduced would also help us understand the importance of specific traits for adaptation or phenotypic plasticity in promoting species spread and distribution.

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130 Table 4.1 Stable isotope data of macro-invertebrate baseline community in the North West Black Sea and Great Lakes regions Plankton/Suspension Filter Feeders Detritivore Shredders/Collectors Detritivore/Herbivore Grazers Region Site 13 15 13 15 13 15 # δ C δ N SEAC # δ C δ N SEAC # δ C δ N SEAC NW Black Sea region 125 45 57

Kherson1 20 -29.4 ± 0.1 10.7 ± 0.1 0.5E 6 -26.1 ± 0.4 15.3 ± 0.1 0.7 11 -24.8 ± 0.4 12.6 ± 0.1 1.9 Dnieper Estuary Kherson2 19 -27.6 ± 0.1 12.3 ± 0.1 1.0F 7 -24.2 ± 0.5 13.0 ± 0.3 2.1 7 -21.9 ± 0.4 13.2 ± 0.2 2 Bilhorod-Dn 20 -26.4 ± 0.1 10.7 ± 0.1 0.5E 5 -23.7 ± 0.3 11.6 ± 0.2 8 -21.7 ± 0.4 12.3 ± 0.1 1.4 Dniester Estuary Bilyaivska 20 -26.2 ± 0.1 10.7 ± 0.1 0.5E 5 -26.6 ± 0.4 13.0 ± 0.3 3 -26.9 ± 0.2 10.8 ± 0.2

Sasyk Lake 13 -21.9 ± 0.2 6.4 ± 0.1 0.9G 6 -23.4 ± 0.2 15.1 ± 0.2 0.7 6 -26.1 ± 0.3 10.9 ± 0.4 Danube Estuary Vylkove 14 -28.9 ± 0.2 8.9 ± 0.2 1.2H 5 -24.0 ± 0.4 9.6 ± 0.2 1.6 8 -25.6 ± 0.1 10.9 ± 0.2 0.6 Berdyansk 19 -22.5 ± 0.1 14.0 ± 0.1 0.4D 5 -26.0 ± 0.8 11.1 ± 0.6 5 -16.8 ± 0.8 7.1 ± 0.0 Sea of Azov Obitoshnia 6 -16.9 ± 0.1 15.4 ± 0.1 0.2 9 -30.8 ± 0.6 17.4 ± 0.5 6.7

Great Lakes basin 133 50 30

Sand Point 17 -19.9 ± 0.1 8.1 ± 0.0 0.1A 10 -17.6 ± 0.1 8.8 ± 0.0 0.4 2 -17.0 ± 0.1 9.5 ± 0.2 Lake St Clair Mitchells Bay 30 -19.1 ± 0.1 7.2 ± 0.1 0.4D 5 -13.3 ± 0.3 7.6 ± 0.1 0.7 4 -19.2 ± 0.2 8.1 ± 0.2

Duluth 14 -27.9 ± 0.1 13.6 ± 0.1 0.2C 3 -22.4 ± 0.1 2.2 ± 0.2 6 -12.7 ± 0.4 1.0 ± 0.2 W Lake Superior Thunder Bay 9 -25.9 ± 0.2 3.5 ± 0.1 0.3C 3 -17.3 ± 0.3 3.3 ± 0.2 11 -17.3 ± 0.3 2.7 ± 0.2 1.5

Lake Erie EB Nanticoke 20 -26.9 ± 0.1 12.0 ± 0.0 0.2B 15 -19.5 ± 0.2 11.1 ± 0.2 2.3

Georgian Bay Collingwood 23 -21.2 ± 0.1 4.1 ± 0.1 0.8G 8 -16.0 ± 0.3 3.2 ± 0.3 1.9

Trent River Lake Seymour 20 -29.0 ± 0.1 6.5 ± 0.1 0.6F 6 -26.0 ± 0.4 6.1 ± 0.6 7 -21.7 ± 0.4 6.6 ± 0.1

ABCD Capital letters denote significantly different groups for comparisons made across all sites within NW Black Sea region and Great Lakes basin. # Denotes number of stable isotope samples. Filter Feeders were processed individually, whereas multiple individuals (3-10) of Detritivores and Detrivore/Herbivores were pooled to make each sample. Only species groups that were not significantly different were pooled for each site. Filter Feeders were Dreissenidae or Unionidae (Thunder Bay only), Detritivores were Gammarid Amphipods or Oligochaets (Duluth only) and Grazers were Hydrobiidae, Neritidae, Bithyniidae, Viviparidae: Viviparus, Pleurocidae or Physidae. See Table 4S.1 for species-specific data.

131 Table 4.2 Biometric and stable isotope data for goby fishes (muscle tissue) collected from the native North West Black Sea and invaded Great Lakes regions. Region Site Species n Wet mass (g)b TL (mm)b δ13C δ15N CR NR SEA

North West Black Sea region 348 Racer Goby 32 2.0 ± 0.3E 54.5 ± 2.1FG -24.2 ± 0.3ab 13.8 ± 0.1ab 5.4 3.3 2.9b (2.4) Dnieper Kherson 1 Round Goby 39 2.9 ± 0.2F 59.9 ± 1.3HI -24.4 ± 0.1a 13.6 ± 0.1a 3.6 2.3 1.6a (1.1) estuary Kherson 2 Tubenose Goby 25 0.4 ± 0.0BC 34.2 ± 1.0B -23.2 ± 0.3b 14.1 ± 0.1b 7.1 2.7 3.4c (2.4) Racer Goby 28 0.9 ± 0.2D 42.7 ± 2.2CD -27.9 ± 0.1a 14.5 ± 0.2a 2.8 3.3 1.8c (1.3) Dniester Bilhorod-Dn Round Goby 28 7.4 ± 0.5I 80.1 ± 1.5K -25.4 ± 0.1b 15.8 ± 0.1b 1.4 1.5 0.3a (-0.2) estuary Bylaivska Tubenose Goby 28 0.4 ± 0.0BC 33.7 ± 0.8B -27.8 ± 0.1a 15.4 ± 0.1b 2.4 1.8 0.8b (0.3) Monkey Goby 28 5.9 ± 0.5H 84.3 ± 2.0K -21.2 ± 0.1 10.9 ± 0.1b 2.1 2.6 1.4b (0.5) Sasyk Lake F I a a Danube Round Goby 28 3.0 ± 0.3 61.8 ± 1.6 -21.1 ± 0.1 10.2 ± 0.1 2.0 1.8 0.6 (-0.3) estuary Racer Goby 20 0.8 ± 0.1D 41.1 ± 2.2C -26.6 ± 0.1 12.2 ± 0.2 1.9 2.9 1.4a (0.2) Vylkove Tubenose Goby 24 0.4 ± 0.0BC 35.1 ± 1.0B -26.7 ± 0.1 11.8 ± 0.2 2.6 3.2 1.6b (0.4) Monkey Goby 10 16.3 ± 2.0J 107.9 ± 3.5L -17.6 ± 0.3b 18.9 ± 0.4 3.5 4.0 4.1b (3.7) Berdyansk Sea of Azov Round Goby 29 14.6 ± 1.5J 101.1 ± 3.4L -19.5 ± 0.1a 19.1 ± 0.1 2.1 2.7 1.1a (0.7) Obitoshnia Tubenose Goby 29 0.4 ± 0.0B 33.5 ± 1.0B -30.9 ± 0.1 21.6 ± 0.2 2.0 4.5 1.7 (1.5)

Great Lakes basin 357 Round Goby 57 3.5 ± 0.5EF 60.9 ± 2.8GHI -17.5 ± 0.1 11.2 ± 0.1b 2.9 2.5 1.4b (1.3) Sand Point Tubenose Goby 29 0.6 ± 0.1CD 39.4 ± 1.4C -17.8 ± 0.1 10.6 ± 0.1a 2.5 2.9 1.1a (1.0) Lake St Clair Round Goby 69 3.4 ± 0.3F 59.6 ± 1.7GHI -19.1 ± 0.1 12.0 ± 0.1b 4.0 2.0 1.1b (0.7) Mitchells Bay Tubenose Goby 30 1.8 ± 0.2E 51.4 ± 1.4EF -18.7 ± 0.1 10.6 ± 0.1a 2.8 1.5 0.9a (0.5) E DE Western Lake Duluth Round Goby 38 1.5 ± 0.2 47.6 ± 1.7 -30.3 ± 0.2 11.3 ± 0.2 4.9 4.3 4.9 (4.7) Superior Thunder Bay Tubenose Goby 43 0.3 ± 0.0A 28.9 ± 1.2A -20.3 ± 0.2 5.6 ± 0.1 4.8 2.6 2.1 (1.8) Lake Erie EB Nanticoke Round Goby 32 2.4 ± 0.2F 56.7 ± 1.5GH -21.0 ± 0.2 15.4 ± 0.1 4.0 2.2 1.7 (1.5) Georgian Bay Collingwood Round Goby 33 4.7 ± 0.4G 70.7 ± 1.7J -18.5 ± 0.1 8.1 ± 0.1 3.9 2.9 2.0 (1.2) Trent River Lake Seymour Round Goby 26 5.1 ± 0.5GH 71.8 ± 1.9J -26.2 ± 0.2 10.6 ± 0.1 2.9 1.7 1.0 (0.4) Wet mass (g), total length (TL, in mm), δ13C and δ15N are presented as mean ± S.E. SEA denotes Standard Ellipse Area corrected for bivariate data and in parenthesis the Bayesian estimated mode (SEAB) following baseline correction. For comparison of stable isotope data the following covariates were used where a significant interaction was found: TL, wet mass (log10), upper limit of 95% confidence interval for C:N ratio and baseline isotopic niche metrics.

132 abc Different lower case letters denote significantly different groups within each lake/estuary. SEAB differences were calculated within the SIBER package using Bayesian data (see Figure 4.4 for total differences). ABCD Different capital letters denote significantly different groups for comparisons made across all sites within NW Black Sea region and Great Lakes basin. b Data was bootstrapped (n =1000) for statistical analyses to account for differences in sample size. Wet mass was log10 transformed for statistical analyses.

133 Table 4.3 Biometric and stable isotope data for goby fishes (liver tissue) collected from the native North West Black Sea and invaded Great Lakes regions b b 13 15 Region Site Species n Wet mass (g) TL (mm) δ C δ N CR NR SEAC

North West Black Sea region 260 Racer Goby 20 2.5 ± 0.3F 59.4 ± 2.8F -24.0 ± 0.3a 13.7 ± 0.2b 4.7 3.4 3.3b (2.8) Kherson 1 Dnieper estuary Round Goby 36 2.8 ± 0.2F 59.4 ± 1.3F -25.6 ± 0.2a 12.1 ± 0.2a 4.4 4.2 2.7a (2.2) Kherson 2 Tubenose Goby 14 0.4 ± 0.1B 34.9 ± 1.3AB -23.1 ± 0.5b 13.5 ± 0.1b 5.4 2.2 2.8a (1.8) Racer Goby 21 1.1 ± 0.2D 45.5 ± 2.5E -28.0 ± 0.2a 13.1 ± 0.3a 3.7 4.5 3.7c (3.2) Bilhorod-Dn Dniester estuary Round Goby 23 7.3 ± 0.5I 79.3 ± 1.6H -26.3 ± 0.1b 13.6 ± 0.1a 1.1 1.9 0.4a (-0.1) Bylaivska Tubenose Goby 12 0.5 ± 0.1BC 35.1 ± 1.3AB -27.3 ± 0.2a 14.6 ± 0.1b 2.4 1.3 0.8b (0.3) Monkey Goby 28 5.9 ± 0.5H 84.4 ± 2.0I -20.8 ± 0.2 9.7 ± 0.2b 3.0 3.9 2.4b (1.5) Sasyk Round Goby 26 2.9 ± 0.3F 61.5 ± 1.7F -20.4 ± 0.1 8.0 ± 0.1a 3.1 2.3 1.3a (0.4) Danube estuary Racer Goby 9 1.1 ± 0.2DE 46.7 ± 3.8DE -26.5 ± 0.2 11.6 ± 0.3 1.7 2.7 1.8b (0.6) Vylkove Tubenose Goby 15 0.5 ± 0.0C 36.6 ± 1.0BC -27.4 ± 0.2 11.8 ± 0.2 2.5 2.2 1.3a (0.1) Monkey Goby 9 16.3 ± 2.3J 107.3 ± 3.9J -18.8 ± 0.3 18.1 ± 0.5 2.9 4.4 5.9b (5.5) Berdyansk Sea of Azov Round Goby 27 15.0 ± 1.6J 102.0 ± 3.6J -20.4 ± 0.2 18.3 ± 0.2 3.4 3.7 2.5a (2.1) Obitoshnia Tubenose Goby 20 0.4 ± 0.0AB 34.1 ± 1.3AB -31.4 ± 0.2 20.1 ± 0.3 3.1 4.3 3.7 (3.5)

Great Lakes basin 253 Round Goby 19 7.8 ± 0.6I 85.0 ± 1.7I -18.5 ± 0.1 9.7 ± 0.1a 2.5 2.2 0.9b (0.8) Sand Point Tubenose Goby 19 0.5 ± 0.1BC 39.5 ± 1.3CD -18.9 ± 0.1 10.3 ± 0.1b 2.0 1.2 0.7a (0.6) Lake St Clair Round Goby 58 3.3 ± 0.3F 59.6 ± 1.7F -19.2 ± 0.1 10.3 ± 0.1b 5.0 2.9 1.5b (1.1) Mitchells Bay Tubenose Goby 20 1.5 ± 0.1E 50.5 ± 1.3E -19.0 ± 0.1 9.4 ± 0.1a 2.0 1.3 0.7a (0.3) Duluth Round Goby 31 1.6 ± 0.2E 48.7 ± 1.9E -30.5 ± 0.2 11.0 ± 0.1 4.3 3.0 2.7 (2.5) W Lake Superior Thunder Bay Tubenose Goby 28 0.3 ± 0.0A 32.2 ± 1.2A -19.9 ± 0.2 4.7 ± 0.1 3.4 1.7 1.2 (0.9) Lake Erie EB Nanticoke Round Goby 24 2.7 ± 0.3F 58.8 ± 1.8F -22.0 ± 0.2 13.5 ± 0.1 2.5 1.5 0.9 (0.7) Georgian Bay Collingwood Round Goby 28 4.6 ± 0.4G 70.4 ± 1.8G -19.2 ± 0.1 6.3 ± 0.2 3.3 3.6 2.3 (1.5) Trent River Lake Seymour Round Goby 26 5.1 ± 0.5GH 71.8 ± 1.9G -26.4 ± 0.2 9.3 ± 0.1 3.3 2.2 1.5 (0.9) Wet mass (g), total length (TL, in mm), δ13C and δ15N are presented as mean ± S.E. SEA denotes Standard Ellipse Area corrected for bivariate data and in

134 parenthesis the Bayesian estimated mode (SEAB) following baseline correction. For comparison of stable isotope data the following covariates were used where a significant interaction was found: TL, wet mass (log10), upper limit of 95% confidence interval for C:N ratio and baseline isotopic niche metrics. abc Different lower case letters denote significantly different groups within each lake/estuary. SEAB differences were calculated within the SIBER package using Bayesian data (see Figure 4.4 for total differences). ABCD Different capital letters denote significantly different groups for comparisons made across all sites within NW Black Sea region and Great Lakes basin. b Data was bootstrapped (n =1000) for statistical analyses to account for differences in sample size. Wet mass was log10 transformed for statistical analyses.

135 Table 4.4 Tissue specific differences (from muscle to liver) in isotopic niche of goby fishes from the native North West Black Sea and invaded Great Lakes regions Difference muscle - liver Region Site Species 13 b 15 b b b δ C δ N CR NR SEAB

North West Black Sea region Racer Goby -0.4 0.2 0.6 -0.1 -0.3 Dneiper Kherson 1 estuary Round Goby 1.2 1.6 -1.0 -2.0 -1.3* Kherson 2 Tubenose Goby -0.1 0.5 0.6 0.1 0.3 Racer Goby 0.2 1.4 -1.0 -1.2 -1.7* Dniester Bilhorod-Dn estuary Round Goby 0.8 2.2 -0.1 -1.4 <0.1 Bylaivska Tubenose Goby -0.8 1.0 -3.9 -1.0 <0.1 Monkey Goby -0.5 1.3 -0.8 -2.0 -1.0* Sasyk Danube Round Goby -0.8 2.3 -2.5 -0.4 -0.8* estuary Vylkove Racer Goby -0.0# 1.5 -0.3 -4.8 -0.3 Tubenose Goby 0.5 0.2 -0.2 1.0 0.7 Monkey Goby 1.0 0.9 -0.3 -0.4 -2.2 Sea of Azov Berdyansk Round Goby 0.9 0.8 -1.4 -1.0 -1.4*

Obitoshnia Tubenose Goby 0.4 1.5 -1.4 -0.4 -2.3*

Great Lakes basin Sand Point Round Goby 0.7 1.4 -1.0 0.1 -0.2 Tubenose Goby 1.3 0.5 -0.1 1.6 0.4* Lake St Clair Mitchells Bay Round Goby 0.9 1.7 -1.0 -1.1 -0.3* Tubenose Goby 0.6 1.2 0.3 0.4 0.2

W Lake Duluth Round Goby 0.5 0.7 0.6 1.3 1.5* Superior Thunder Bay Tubenose Goby 0.4 0.8 1.4 0.7 0.3 Lake Erie EB Nanticoke Round Goby 1.2 2.1 1.5 0.7 1.1* Georgian Bay Collingwood Round Goby 0.7 1.8 0.6 -0.7 -0.2 Trent River Lake Seymour Round Goby 0.3 1.3 -0.9 -0.8 -0.6* Differences between muscle and liver tissue were used to indicate changes in diet history through time. b Bootstrapped (x1000) differences in mean δ13C and δ15N and ranges (CR, NR) between tissues of individuals b 5 Bayesian Standard Ellipse Area (SEAB) calculated from 10 Bayesian iterations * Indicates significant SEAB difference between tissues (> 95% simulations)

136

Figure 4.1 Map of sampling sites for goby fishes and macro-invertebrates in the Black Sea drainage (native, Aug 2013) and Great Lakes basin (invasive, June – Oct 2011-2013). Black dots indicate sampling sites. Black star indicates location of first sighting of goby fishes in the Great Lakes (St Clair River, Jude et al. 1992) and sampling site in the Black Sea region which is the estimated location from which invasive goby fishes were predominantly sourced (Stepien et al. 2005). Base map sources: WW F, USGS, Esri, EPA, NOAA.

137

Figure 4.2 Bi-plot of isotopic niches (ellipses of δ13C and δ15N) for (a) muscle tissue and (b) liver tissue in goby fishes from their native NW Black Sea and invasive Great Lakes regions. Letters denote waterbody/site: A. Dnieper, B. Dniester, C. Danube, D. Sea of Azov. a. Sand Point (Lake St Clair), b. Mitchells Bay (L St Clair), c. Duluth (Lake Superior), d. Thunder Bay (Lake Superior), e. Lake Erie EB, f. Georgian Bay, g. Trent River.

138

139 Figure 4.3 Density plots of Bayesian Standard Ellipse Area (SEAB ± 95, 75 and 50 % credible intervals) for goby bulk muscle, lipid extracted liver and baseline invertebrate lipid extracted whole tissue from (a) the North West Black Sea region and (b) Great Lakes basin. Dotted lines denote different water body/region. Letters on the x-axis denote different species: Round Goby (R), Monkey Goby (M), Tubenose Goby (T) and Racer Goby (RA) or, for baseline, different specific sampling locations (See Fig 4.1 for sampling sites).

140

Figure 4.4 Mean ± S.E. SEAC, CR and NR from native and invaded region goby fish (a) muscle and (b) liver tissue following baseline corrections. Base used were filter feeders or in one case Gammaridae (for Native Azov Tubenose region only). See Table 4.1 for baseline niche metrics and stable isotope data. See Table 4.2 (muscle) and Table 4.3 (liver) for fish population data including number of fish populations of each species, number of individuals used for each population and significant differences between groups.

141 SUPPLEMENTAL MATERIAL

Table 4S.1 Biometrics and stable isotope data (mean ± S.E.) for macro-invertebrate species collected from the NW Black Sea region and Great Lakes basin. Family/sub- Dry tissue Length Region Site Order/sub-order n δ13C δ15N SEA family mass (mg) (mm) C

NW Black Sea region 238 Dnieper estuary -26.4 ± 0.4 12.3 ± 0.2

Kherson 1 Veneroida Dreissenidae 20 19.8 ± 1.6 18.7 ± 0.5 -29.4 ± 0.1 10.7 ± 0.1 0.8

Neritopsina Neritidae 10 15.0 ± 2.8 10.0 ± 0.4 -22.5 ± 0.8 13.0 ± 0.2

Amphipoda Gammaridae 5 -24.8 ± 0.2 13.2 ± 0.2

Kherson 2 Veneroida Dreissenidae 19 18.0 ± 0.5 -27.6 ± 0.1 10.3 ± 0.1 Odonata/Anisoptera Aeshnidae 8 146.8 ± 26.6 33.0 ± 4.1 -24.0 ± 0.3 14.3 ± 0.2 Odonata/Anisoptera Corduliidae 5 32.8 ± 1.8 11.8 ± 0.6 -23.4 ± 0.5 12.8 ± 0.1 Dniester estuary, Bylaivska and Bilhorod Dnistrofksy 56 -25.9 ± 0.2 11.1 ± 0.1

Veneroida Dreissenidae 40 7.6 ± 0.6 10.1 ± 0.2 -26.3 ± 0.1 10.7 ± 0.1 0.5

Neritopsina Neritidae 5 8.5 ± 1.2 8.0 -24.5 ± 1.1 11.6 ± 0.5

Odonata/Zygoptera 1 -24.4 11.5

Amphipoda Gammaridae 10 -25.1 ± 0.5 12.3 ± 0.3

Danube estuary 48 -24.7 ± 0.5 8.6 ± 0.2

Sasyk Lake 14 15.2 ± 4.0 13.9 ± 0.3 -21.5 ± 0.4 6.6 ± 0.2

Veneroida Dreissenidae 13 15.2 ± 4.2 13.9 ± 0.6 -21.9 ± 0.1 6.4 ± 0.1

Amphipoda Gammaridae 1 -17.1 9.1

Vylkove 34 -26.0 ± 0.6 9.5 ± 0.2

Veneroida Dreissenidae 14 6.2 ± 1.5 10.8 ± 0.6 -28.9 ± 0.1 8.9 ± 0.2 1.3

Veneroida Veneridae 2 -29.7 ± 0.3 8.7 ± 0.1

142 Family/sub- Dry tissue Length Region Site Order/sub-order n δ13C δ15N SEA family mass (mg) (mm) C Neotaenioglossa Hydrobiidae 5 14.8 ± 2.7 5.4 ± 0.2 -24.0 ± 0.9 10.2 ± 0.2

Odonata/Anisoptera Aeshnidae 4 21.8 ± 6.7 17.3 ± 3.0 -25.2 ± 0.1 11.3 ± 0.1

Odonata/Zygoptera 1 -26.3 11.9

Amphipoda Gammaridae 5 -24.0 ± 0.4 9.6 ± 0.2

Decapoda/Brackyura 3 -17.2 ± 0.3 7.6 ± 0.1

-24.2 ± 0.8 15.7 ± 0.3 Sea of Azov North shore 67 Berdyansk

Veneroida Dreissenidae 19 13.2 ± 3.3 12.8 ± 0.5 -22.7 ± 0.1 14.0 ± 0.1 0.4

Obytochna 48 -24.9 ± 1.1 16.4 ± 0.4

Neotaenioglossa Hydrobiidae 5 5.4 ± 0.6 4.8 ± 0.8 -28.4 ± 0.8 15.4 ± 1.4

Diptera Chironomidae 3 -16.3 ± 0.2 17.4 ± 0.2

Odonata/Anisoptera Aeshnidae 11 74.8 ± 8.9 26.6 ± 1.4 -31.1 ± 0.2 18.8 ± 0.4

Odonata/Zygoptera 13 6.6 ± 0.7 10.5 ± 0.6 -30.8 ± 0.4 17.0 ± 0.7

Amphipoda Gammaridae 1 -17.2 15.8

Isopoda 14 6.3 ± 1.2 7.3 ± 0.7 -15.3 ± 0.3 13.9 ± 0.3

Great Lakes basin 201 Lake St Clair 77 -19.6 ± 0.3 7.9 ± 0.1

Mitchells Bay 48 -19.9 ± 0.4 7.7 ± 0.1

Veneroida Dreissenidae 46 39.1 ± 3.3 17.2 ± 0.6 -20.1 ± 0.4 7.7 ± 0.1 0.4

Neotaenioglossa Hydrobiidae 2 3.6 ± 0.4 5.8 ± 0.3 -16.1 ± 0.2 7.9 ± 0.4

Sand Point 29 -19.1 ± 0.2 8.3 ± 0.1

Veneroida Dreissenidae 18 16.8 ± 2.2 12.9 ± 0.7 -19.9 ± 0.1 8.0 ± 0.1 0.1

Diptera Chironomidae 1 -20.5 8.5

Amphipoda Gammaridae 10 -17.6 ± 0.2 8.8 ± 0.1

W Lake Superior 43 -24.3 ± 0.8 6.1 ± 0.7

143 Family/sub- Dry tissue Length Region Site Order/sub-order n δ13C δ15N SEA family mass (mg) (mm) C Thundery Bay, Mission Marsh 23 -20.7 ± 0.9 3.1 ± 0.1

Unionoida Unionidae 9 -25.9 ± 0.2 3.5 ± 0.1 0.4

Neotaenioglossa Hydrobiidae 11 -17.3 ± 0.3 2.7 ± 0.2

Amphipoda Gammaridae 3 -17.3 ± 0.3 3.3 ± 0.2

Duluth 20 -28.5 ± 0.2 9.5 ± 1.0

Veneroida Dreissenidae 19 46.5 ± 9.3 19.3 ± 1.8 -28.5 ± 0.2 9.6 ± 1.1 0.2

Diptera Chironomidae 1 -28.2 8.7

Lake Erie EB, Nanticoke 30 -25.2 ± 0.7 11.8 ± 0.1

Veneroida Dreissenidae 24 33.6 ± 3.7 15.5 ± 0.6 -27.0 ± 0.1 11.9 ± 0.0 0.2

144 CHAPTER 5

DIFFERENT NICHES IN SUCCESSFUL AND LESS SUCCESSFUL AQUATIC

INVASIVE INVERTEBRATES

145 INTRODUCTION

Invasive species are a leading cause of extinction, second only to habitat destruction (Baillie et al. 2004, Dirzo and Raven 2003). Many species of aquatic invertebrate are easily transported, extremely taxonomically diverse and often occur in high abundances. It is, therefore, not surprising that some of the most widespread and problematic invasive species are aquatic invertebrates (Holeck et al. 2004). Risk of invasion from novel species continues to be a threat to ecosystem stability, biodiversity and the economy, with increasing challenges in predictability presented by our current rapidly changing global climate (Rahel and Olden 2008). Yet the ecology of many invasive invertebrates is poorly understood, particularly in invaded ranges.

Despite taxonomic similarity, some invasive species spread more rapidly and over greater distance than others (Arim et al. 2006). Comparison of traits between successful

(rapid/widespread establishment) and less successful (less rapid/rare establishment) taxonomically similar invasive species can highlight characteristics that promote survival of species in novel environments (Pettitt-Wade et al. 2015, Van Kleunen et al. 2010,

Williamson and Fitter 1996). Such traits can subsequently be used in screening of species to predict risk of impact under given environmental scenarios (McKinney and Lockwood

1999).

Ecological niche is a term that can be used to describe the interaction between an organism and the environment, and the ability for an organism to respond to changes in the environment with the resources available (Hutchinson 1978). An ecological niche- based approach has long been central to the field of invasion ecology and has helped form the basis of fundamental concepts (Facon et al. 2006, Guisan et al. 2014). It is often

146 suggested that successful establishment by invasive species is facilitated by a broad

dietary niche, but the importance of broad dietary niche for the successful establishment

and spread of aquatic invertebrates has not been adequately determined (Hayes and Barry

2008).

Stables isotopes of carbon (δ13C) and nitrogen (δ15N) are commonly used in trophic and food web ecology due to the predictable way stable isotope ratios change through trophic levels, and across different temporal and spatial landscapes (Post 2002,

Vander Zanden et al. 1997). Variation in δ13C and δ15N for a population is sometimes termed ‘isotopic niche’ (Newsome et al. 2007). Several studies have demonstrated the potential value of using the bi-plot of δ13C and δ15N to depict the dietary niche of aquatic

invasive species, their interaction with native species and risk of ecological and economic

impact (Hayden et al. 2013, Jackson et al. 2014, Jackson and Britton 2014, Pettitt-Wade

et al. 2015). In addition to niche breadth, niche plasticity is also expected to increase

opportunity for successful establishment and spread of invasive species (Guisan et al.

2014), and was previously found for the more successful fish Round Goby compared to

Tubenose Goby in the Great Lakes (Pettitt-Wade et al. 2015).

High niche plasticity could indicate greater response to fluctuations in

environment and resources, and an ability to respond to the change in environment and

resources associated with a novel ecosystem. It is generally recommended that

comparisons of stable isotope data between regions be accompanied by analysis of

primary and/or secondary consumers as a ‘baseline’ (Cabana and Rasmussen 1996, Post

et al. 2007). Environmental effects on isotopic stochasticity can be accounted for using a

baseline and used to explain the origin of variation in δ13C and δ15N. After accounting for

147 baseline ecosystem effects (using bivalves or aquatic snails), we predict greater niche breadth in more rapidly spreading and widespread invasive invertebrate species. Our matched species pairs were violet tunicate (Botryllus violaceus) and golden star tunicate

(Botryllus schlosseri) in the North West Atlantic (coast of Nova Scotia, Canada), Pacific oyster (Crassostrea gigas) and Eastern oyster (Crassostrea virginica) in the North East

Pacific (Vancouver, BC region, Canada), and spiny water flea (Bythotrephes longimanus) and fish-hook water flea (Cercopagis pengoi) in the Laurentian Great Lakes region

(successful and less successful, respectively). This is the first study to compare the isotopic niche of these important invasive species pairs.

Although we predict a general pattern of greater niche breadth in the more

‘successful’ invaders, there are important distinctions between the species pairs (i.e. oysters, tunicates, waterflea) that are expected to cause divergence in the outcome of our species-specific comparisons. This includes a different amount of time in established regions, different transport vectors (i.e. ballast water, hull fouling, bait bucket), natural dispersal strategies (although all have a pelagic dispersal stage), and different fundamental biology and ecology. Less within-and between-population variation in isotopic niche is expected to occur in the more colonial and sedentary invertebrates, such as the tunicate ascidians, as opposed to the greater potential for mobility expected from the active foraging Cladoceran water flea. Sessile suspension feeders have been shown to selectively sort particles based on their nutritional quality (Beninger et al. 2007), with consequences for isotopic niche breadth and trophic diversity (Dubois and Colombo

2014). But the sedentary lifestyle of oysters and tunicates makes them heavily dependent on flow and turbidity for variability in prey, and emphasises the importance of settling in

148 an optimum location. Cladoceran waterflea are better equipped to exhibit prey selectivity,

although still essentially subject to the constraints of currents and flow for prey

availability. Ultimately, the findings of this research will provide a better understanding

of the mechanisms for survival across broad geographic ranges and to enhance trait-based

analysis for species distribution models.

METHODS

Study sites and sample collections Samples of waterflea, tunicate, oyster and baseline organisms were collected during the summer of 2011 and 2012 (Fig. 5.1). Bivalves (Mytilus sp. in marine,

Dreissenidae or Unionidae in freshwater) were collected and used as baseline where possible. In the absence of bivalves, snails were obtained and compared with locations where both bivalves and snails were obtained (i.e. Serpentine River, BC, aquatic snails

(Gastropod molluscs) were collected and compared with aquatic snails and mussels from

Croften, Buckley Bay and Okeover Arm). Individual colonies of golden star tunicate, violet tunicate and Mytilus mussels were collected from the coast of Nova Scotia by benthic trawl (Fig. 5.1). Oysters, Mytilus mussels and aquatic snails were obtained from littoral areas close to Vancouver, BC. Waterflea were collected from throughout the

Great Lakes basin using plankton tow nets (750um or 250um mesh 5-10m tow off a 19 foot boat) and baseline bivalves were collected by ponar (Petit Ponar, 2.4L). Samples of waterflea were kept in shallow trays on collection to allow gut evacuation and to sort from other organisms prior to placing in individual sample vials and placing on ice. All samples were frozen and returned to the lab for processing.

149 Stable isotope analysis All samples were cleaned of other materials or organisms prior to freeze-drying and prep for stable isotope analysis. Whole tunicate colonies were subsampled and measured for wet mass. Similar size individuals of waterflea were pooled (17-120) to provide sufficient sample for analysis. Baseline mussels were measured (shell length, wet tissue mass; Dreissenidae for Great Lakes basin, Mytilus edulis for Vancouver). Wet mass was taken for whole oyster tissue and baseline mussel tissue (minus shell). Oysters were measured (wet tissue mass, tissue length) and samples of adductor muscle tissue taken for stable isotope analysis, since δ13C and δ15N have previously been shown to differentiate substantially between tissues in oysters (Paulet et al. 2006, Piola et al. 2006).

Adductor muscle was also used for Mytilus mussels, whereas whole tissue was sampled from Dreissenidae, and multiple individuals were pooled for analysis.

All samples were freeze-dried (-80°C) and ground to homogeneity using a mortar and pestle. Lipids in tunicates, water flea and baseline organisms were removed prior to analysis using a modified Solvent Distillation method (See Pettitt-Wade et al. 2015 for details). Samples and standards were weighed (± 0.001g) into 5mm x 9mm tin cups and run for δ13C and δ15N, C % and N %, on a Delta V IRMS (Thermo Electron Corporation,

Waltham, Massachusetts, USA) equipped with an elemental analyzer (Costech, Santa

Clarita, California, USA). The relative abundances of carbon and nitrogen stable isotopes within each sample are expressed in delta notation, which is calculated using the following equation:

� δR ‰ = − 1 × 1000 �

150 where R is the ratio of 15N/14N or 13C/12C for sample and standard reference materials Pee

Dee Belemnite (PDB, for CO2) and atmospheric nitrogen (for N2). Each run included triplicates of every 10th sample and internal fish muscle standard (Tilapia, Oreochromis niloticus) and NIST standards every 12th sample. Precision respectively for δ15N and δ13C was 0.16 and 0.1 ‰ for Tilapia (n = 618), 0.2 and 0.1 ‰ for NIST bovine liver (1577c) and 0.15 and 0.07 for NIST bovine muscle (8414). Accuracy based on the difference between NIST standards run in the lab from 2012 - 2015 and certified data was 0.01, 0.18 and 0.05 ‰ for δ15N (NIST 8573, 8548 and 8549, respectively), -0.06 and -0.02 ‰ for

δ13C (NIST 8542 and 8573, respectively).

Baseline corrections For comparison of invasive species pairs collected in different years and/or sites

(i.e. waterflea and oysters), baseline corrections were made to the stable isotope data of each individual using data for primary consumers from the same sampling time and location. Following the methods of several others who compared isotopic niche across spatial and temporal scales (e.g. Jackson et al. 2014, Jackson and Britton 2014, Olsson et

15 al. 2009), δ N was converted to trophic position (TP) using the equation:

δN − δN TP = + 2 3.4

where TP is invader trophic position, δ N is invader isotope ratio, δ N is mean baseline isotope ratio, 3.4 is the fractionation between trophic levels and 2 is the baseline

13 trophic position (Post 2002). Invader δ C was corrected (δ C) using the equation:

δ C − δ C δ C = C95

151 13 where δ C is the invader isotope value, δ C is baseline mean δ C and C95 is

the baseline δ13C 95% confidence interval range. We modified the original equation from

Olsson et al. (2009) to include 95% confidence interval range in place of carbon range to avoid bias associated with the two extremes. Baseline data were bootstrapped to account for differences in sample size (Simple design in SPSS, n = 1000, 95%CI). For the purposes of baseline-correcting oyster data at locations where only snails were obtained

(Serpentine River), mean difference between mussels and snails where both were found in the same location was added to snail data prior to use in baseline corrections (-4.54 and

-3.59 for δ13C, -0.17 and -0.40 for δ15N, mean and C95 difference, respectively, for

Croften, Buckley Bay and Okeover Arm).

Isotopic niches Standard ellipse areas were constructed from δ13C and δ15N bi-plot data (baseline corrected data for oysters and waterflea) and used as a conservative measure of population isotopic niche. Ellipses were constructed using ‘Stable Isotope Bayesian

Ellipses in R (SIBER 2.0, Jackson et al. 2011). Each standard ellipse area (SEA) is a measure of core variability in x (δ13C) and y (δ15N) representing 40% of the spread of data and is insensitive to sample size. The following equation is used to correct SEA for the use of bivariate data (Jackson et al. 2011):

� − 1 ��� = ��� × � − 2

The SEAC correction accounts for the loss of a second degree of freedom and provides unbiased correction for differences in sample size. Credible intervals from multiple

5 Bayesian iterations of SEAC (10 posterior draws; SEAB) were used to calculate the

152 probability of broader isotopic niche in one population compared to another with a

significance threshold of > 95% of Bayesian iterations (i.e. p < 0.05).

Statistical analysis 13 15 Log10 wet mass, δ C and δ N (baseline-corrected for waterflea and oysters) did not differ significantly from a normal distribution (Shapiro-Wilk, p < 0.05), and in most cases, homoscedastic variance (Levene’s). The effect of log10 wet mass, total length, year/month sampled and mean individuals pooled to make each sample (waterflea only; more individuals pooled for each sample implies smaller total length as similar size individuals were pooled) on δ13C and δ15N was first determined for baseline populations

then focal invasive species pairs using General Linear Models (GLMs). Comparisons of

δ13C and δ15N were then made between populations of different site and/or species using

Analysis of Variance (ANOVA) with post-hoc pairwise comparisons using Tukey’s test, or Games-Howell test for heteroscedastic data and/or different sample sizes. Performing analysis on bootstrapped data (Simple design in SPSS, n = 1000, 95% CI) provided further correction for differences in sample size. Regressions and coefficients were used on population isotopic niche data to determine the relative influence of variation in the x- axis (δ13C standard error and range) and y-axis (δ15N standard error and range) on the

spatial distribution of individual points in bivariate isotopic niche space (SEAB). SPSS v.22 and R v.3.1.0 were used to conduct all statistical analyses. A significance threshold of p < 0.05 was used for all statistical analyses.

RESULTS

A total of 370 tunicate colonies, 270 Cladoceran waterflea samples (7818 individuals) and the adductor muscle of 168 oysters were processed for stable isotope

153 analysis. Once divided by species, site, and year of collection, the number of individuals

used for each population of successful or less successful invader ranged from 14 to 24

(with exception for waterflea for which multiple individuals were pooled to make each

sample, Tables 5.1, 5.2 and 5.3). Samples of waterflea and oysters were not obtained in

sufficient quantity from the same location and time for comparison of isotopic niche

breadth, thus baseline corrections were used for spatial and temporal comparisons. Site

was the strongest predictor of variation in baseline organism δ13C and δ15N for the Great

Lakes region and Vancouver region, followed by year and shell length (GLM with Type

III Sum of Squares, p < 0.05). Lack of significant annual variation for several sites led to

baseline data being combined across years for several sites (ANOVA, p > 0.05, Table

5S.1). Baseline corrections for tunicates were not necessary as comparisons were

restricted to populations from the same place and time.

Invasive tunicates In most comparisons for which significant differences were found (3/4 significant,

10 total), isotopic niche (Bayesian Standard Ellipse Area, SEAB) was significantly broader in the more successful invasive species of tunicate (>95% of 105 iterations for each comparison, Table 5.1, Fig. 5.2). The exceptions of broader isotopic niche in the less successful species were often associated with particularly high overlap in isotopic niche, although, some degree of overlap was exhibited by all populations (Fig 5.2a). Lack of overlap was predominantly driven by δ15N variation (y-axis, Fig 5.2a), and the more

successful violet tunicate (B. violatious) had significantly higher δ15N than less successful golden star tunicate (B. schlosseri) in 6/10 possible comparisons (Table 5.1). Conversely,

δ13C was significantly different in only one case (Port de Grat 2012, Table 5.1, Fig 5.2a).

Broader isotopic niche in the more successful species was associated with greater spread

154 of individuals both close to the center of the ellipse (standard error, S.E.) and at extremes

(ranges, CR and NR). For the more successful invader, δ13C S.E. and NR explained most

15 of the variation in SEAB (explained 15% and 25%, respectively, compared to 1% for δ N

S.E. and <0.1% CR, GLM). For the less successful species, variation in SEAB was associated with variation close to the center of the ellipse (δ13C S.E. and δ15N S.E., 25%

and 11%, respectively) more than variation at extremes (CR and NR, 3% and 5%,

respectively, GLM).

Invasive Cladoceran waterflea In the majority of comparisons (40/60), the less successful fishhook waterflea, C.

pengoi, had a broader isotopic niche (SEAB on baseline corrected data) than more successful spiny waterflea, B. longimanus (3/60 for most successful species, Table 5.2,

Fig 5.3). Furthermore, fishhook waterflea had a broader isotopic niche than spiny waterflea in all comparisons where they were collected from the same specific location

(3/3 comparisons of SEAB). Smallest isotopic niches were often associated with inland lakes for the most successful invader (Peninsula, Kashawakamak and Cayuga Lake in the

Finger Lakes, Table 5.2). But the less successful fishhook waterflea in Cayuga Lake still had a broader isotopic niche than spiny waterflea in 8/15 comparisons, including sites that are not inland lakes (Fig 5.3).

Broader isotopic niche in the less successful fishhook waterflea was often associated with more variation between individuals close to the mean for δ15N (δ15N S.E.)

and at the extremes for δ13C (CR) (higher in 67% of comparisons for δ15N S.E., 77% for

CR, Table 5.2). Although, for all populations combined, CR was the only metric that was

significantly different between the two species (ANOVA, F1, 17 = 5.56, p = 0.03). Several populations of the most successful species, spiny waterflea, had higher δ13C S.E. than the

155 less successful species (35% of comparisons, Table 5.1) and δ13C S.E. had the strongest

2 correlation with SEAB overall (R = 0.86, Power regression). But this was not sufficient

to drive a broader ellipse area than fishhook waterflea, largely due to higher NR in

2 fishhook waterflea and NR had the strongest relationship with SEAB overall (R = 0.92,

Power regression).

Invasive oysters As with waterflea, the less successful Eastern oyster (C. virginica) had a broader

isotopic niche than the more successful Pacific oyster (C. gigas) in the majority of cases

in which significant differences were found (SEAB calculated from baseline corrected data, 3/5 significant comparisons, Table 5.3, Fig. 5.4). However, Eastern oyster is only found in one location in this non-native region (Serpentine River, Fig. 5.1) and several comparisons resulted in no significant difference (Fig. 5.4). Broader isotopic niche

13 (SEAB) was again associated most with δ C S.E. and NR (Linear and Power regressions

on baseline corrected data, respectively, R2 > 0.90). This was reflected with higher NR in the less successful Eastern oyster than most populations of more successful Pacific oyster, but the opposite was found for δ13C S.E. (Table 5.1). The less successful Eastern

oyster also had the significant smallest body size and δ15N (Table 5.3, Fig. 5.3), and populations of Pacific oyster that had the broadest isotopic niche overall were also the largest in body size (Table 5.3).

DISCUSSION

We found that dietary niche, as determined by δ13C and δ15N, was most often

broader in the less successful aquatic invasive species of crustacean and oyster, but the

more successful species of tunicate. This inconsistency was contrary to our hypothesis of

156 broader isotopic niche in more successful aquatic invasive species, and contrasts with studies that have found broader dietary niches in more successful aquatic vertebrates

(Brandner et al. 2013; Pettitt-Wade et al. 2015). We defined success based on wider spatial distribution and/or more rapid dispersal in invaded ranges. Thus, our findings suggest that broad dietary niche is less crucial for widespread distribution of aquatic invasive invertebrates than it is for vertebrates, potentially due to more limited mobility and low trophic level compared to vertebrates. Ability to tolerate a wider temperature and salinity extremes, or rapid dispersal tactics could have greater importance for the success of invasive invertebrates than differences in dietary niche.

Invasive tunicates Significant differences in isotopic niche breadth were found between species of tunicate, despite their sedentary life style. Very few studies have investigated the feeding ecology of colonial tunicates. Ascidians are mucus filter feeders and capable of filtering sub-micrometer particles for food (Sutherland et al. 2010), and the range of particles consumed is limited by the size of the oesophagus (Bone et al. 2003), thus differences in the ability or preference for particle size may explain the different niche breadth for tunicates. Rinkevich and Shapira (1998) found that a mixed diet (i.e. broader dietary niche) was superior to a monotype diet and availability of a variable diet affected condition, growth and reproductive activity (asexual or sexual budding) of the golden star tunicate. This promotes the concept that the competitive resource for these species is most likely optimal surface for a colony to settle (Gittenberger and Moons 2011), which determines the quality of prey available and potential niche size. Despite the differences in niche size, there was considerable overlap in isotopic niche of the two species of tunicate in this study. This suggests the two species are consuming similar prey, and

157 could be in competition for prey where they occur in sympatry. Alternatively, the association of niche overlap with cases in which broader niche was found in the golden star tunicate could be driven by an abundance of shared prey resource (i.e. minimal competition).

Abiotic factors could also play a role in dietary niche size, for example, salinity tolerance. The invertebrates in this study are able to avoid intense Allee effects by reproducing asexually (Carver et al. 2006, Drake 2004), or changing sex to suit the needs of the population (Eastern Oyster Biological Review Team 2007). But allocation of energy towards any form of reproduction (including asexual budding) involves an energy investment, and Rinkevich and Shapira (1998) found that reproductively active parts of tunicate colonies do not filter the water. More surface area of a colony directed towards reproduction instead of feeding would provide less opportunity for obtaining a broad diversity of prey (i.e. result in narrow dietary niche). The golden star tunicate, the less successful species, tolerates a wider salinity range than the violet tunicate (Gittenberger and Moons 2011) which gives an advantage in variable salinity zones (Epelbaum et al.

2009). However, the violet tunicate has been found to be a better competitor for space/prey than the golden star tunicate when salinity range is limited (Gittenberger and

Moons 2011). This might explain a broader dietary niche for the violet tunicate in locations where salinity range is closer to optimum. Likewise, significantly broader isotopic niche in the golden star tunicate, as we found in one comparison, could be due to higher salinity range and reduced condition in violet tunicate colonies leading to suppression of feeding activity (Rinkevich and Shapira 1998).

158 Invasive Cladoceran waterflea Different temperature preferences (i.e. habitat) and associated species

compositions, predation pressure and competitive interactions could have a role in

driving differences in dietary niche breadth of the Cladocerans (Cavaletto et al. 2010).

Several authors have found spatial segregation of the species to occur in lakes with

fishhook waterflea showing a preference for warmer, near-shore environments, and spiny

waterflea preferring colder, off-shore environments (Cavaletto et al. 2010, Keeler et al.

2015, Witt and Cáceres 2004). Higher productivity and availability of diverse prey in

near-shore areas compared to off-shore (or deeper) (Beeton and Edmondson 1972) could

also explain a broader dietary niche in the less successful species. For example, near-

shore areas of Lake Erie have bouts of particularly high productivity (Beeton and

Edmondson 1972, Ludsin and Höök 2013), and we found Lake Erie Cladocerans to have

among the broadest isotopic niches. Keeler et al. (2015) found temperature to best

explain spiny waterflea biomass compared to predation by fish or zooplankton prey

density, which further suggests abiotic factors may play a greater role in the invasion

success of these invertebrates than dietary niche breadth.

The smaller size and feeding appendages of less successful species of Cladoceran

waterflea (Rivier 1998) were expected to provide for a smaller range of consumable prey,

and thus, smaller dietary niche than the more successful species. We found the opposite:

broader niche in the smaller, less successful species. In contrast to waterflea, broadest

dietary niche was associated with largest body size and higher δ15N for Pacific oyster.

These findings suggest the relationship between body size and dietary niche is inconsistent among invertebrate species, and does not necessarily relate to invasion

159 success. In a review of the literature, Hayes and Barry (2008) also found body size not to be a consistent predictor of invasion success for invertebrates (shellfish and insects).

Invasive oysters As with tunicates and waterflea, environmental tolerance could have a dominant role in the limited distribution of less successful Eastern oyster despite a broad dietary niche. The Eastern oyster favours a narrow salinity range, relative to Pacific oyster, and is only found in abundance in estuarine habitats, whereas Pacific oyster are most abundant in marine environments (Eastern Oyster Biological Review Team 2007). Serpentine

River Eastern oyster are at the edge of the non-native range, but this less successful species is found in abundance in other non-native regions (Eastern Oyster Biological

Review Team 2007, Ruesink et al. 2005); the species could even be extirpated (failed collection attempts were made in 2013; Therriault, T. Department of Fisheries and

Oceans, Canada. Pers. Comm. 2013). The species has been established in the region since at least 1917 (introduced 1883 – 1940) and has been document to lie dormant for up to a decade until conditions are more favourable, leading to times when it was previously mistaken as extirpated (Ruesink et al. 2005). Dormancy is a common feature of oysters, and for the egg clutches of Cladoceran waterflea, which could lead to discrepancy as to which species will dominate as environmental conditions change in the future (Briski et al. 2011).

The contrast in isotopic niche breadth between successful and less successful species was less clear for the invasive oysters compared to waterflea. Broadest isotopic niche overall was actually found for two populations of the more successful Pacific oyster and several populations of the two species had exactly the same isotopic niche breadth following baseline corrections. Differences in niche breadth could be associated

160 with the relative condition of the organisms, such as particularly high condition of the more successful species in Stanley Park and Okeover Arm. Eastern oyster in the North

West Pacific has had such limited abundance for so long that there is discrepancy as to whether it should still be considered as invasive in the region (Eastern Oyster Biological

Review Team 2007). In contrast to the oysters, although species pairs of tunicate and waterflea were designated as successful and less successful, in a number of locations the less successful species were found in higher abundance (Pettitt-Wade, H. Pers. Obs.

2012). Furthermore, although these species have less widespread /slower rate of non- native spread than their more successful counterparts, they are considered to have a considerable impact as invasive species in these regions (Benoít et al. 2002).

The potential role of invasion history Differences in dietary niche between successful and less successful invasive species could be a consequence of native origin and/or establishment time. For example, both species of Cladoceran waterflea were introduced via ballast water or ship fouling from populations originating from the Ponto-Caspian, but the species that is more successful was discovered much earlier (spiny waterflea: 1984) than the less successful species that has a broader isotopic niche (fishhook waterflea: 1998; Holeck et al. 2004).

Longer time in invaded region provides more opportunity for predators and potential competitors to respond, and for the invasive species to alter community composition.

Spiny waterflea generally occur more frequently in the diets of fish than fishhook waterflea (Thomas et al. 2015), and seem to have a larger impact on zooplankton species composition (Cavaletto et al. 2010, Holliland et al. 2012, Rennie et al. 2011). Restricted dietary niche following longer establishment for the most successful species could be a consequence of the restructured prey community, and reduced diversity of prey available.

161 Propagule pressure is another aspect of the invasion process that can have a considerable influence on establishment success of invasive species, although small propagules can also lead to widespread invasions (Simberloff 2009). Wider distribution of the more successful species could be a result of greater propagule pressure, as opposed to, for instance, greater capacity for responding to the environment and resources available (as implied by niche breadth). Violet tunicates in Nova Scotia most likely spread from a number of isolated introductions to the eastern United States, from populations that were already invasive in the western United States (Bock et al. 2011).

Golden star tunicate populations on the eastern coast of North America were seeded from the Mediterranean, likely from hull fouling, and several decades prior to the estimated introduction of violet tunicate (Lejeusne et al. 2011). Both species of oyster were introduced from the aquaculture trade (Green and Crowe 2014, Wolff and Reis 2002), but the more successful Pacific oyster is the favoured species and is likely to have experienced greater propagule pressure as a result.

Conclusions Even for suspension feeders that occur in sympatry, we found significant differences in dietary niche breadth. This demonstrates the use of stable isotopes as tools for examining niche differences is not limited to mobile predators. The lack of universality (many non-significant differences) suggests dietary niche breadth is not as crucial for widespread distribution of invertebrates as, for example, environmental tolerance. The literature is often divided on whether dietary niche breadth is important for the success of aquatic invasive species, but information for dispersal stages is scarce, particularly for invertebrates (Kolar and Lodge 2001). There are many cases in which a broad dietary niche has been found in the most widespread invasive species of fishes

162 (Garcia-Berthou 2007, Pettitt-Wade et al. 2015), reptiles (Reed et al. 2012), birds and mammals (Hayes and Barry 2008). Our findings suggest that less successful species could have an edge over more successful species in the more limited locations they have spread to. But where distributions overlap, the more successful species have broader niches, indicating the strong association between invasion success and competitive superiority for space and prey. Predicting the spread of invasive species is becoming increasingly problematic with rapid changes in climate and persistence of anthropogenic stressors (Rahel and Olden 2008), and changes in processes at the regional and global scale will undoubtedly favour some species more than others (Dukes and Mooney 1999).

Coupled with a broader dietary niche, changes in climate that favour the species that is currently less successful could lead to a switch in the more/less successful of each pair.

Our findings indicate the importance of considering the significant role some invasive species have in the food web (broad dietary niche) despite restricted spread compared to other closely related species. This suggests we should continue to closely monitor not just widespread invasive species, but also those that currently have a limited distribution.

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167 Table 5.1 Stable isotope data and isotopic niche of successful (Botryllus schlosseri, Golden Star) and less successful (Botrylloides violatious, Violet) invasive tunicates in the North East Atlantic (Nova Scotia) 13 15 Site/Year n δ C δ N CR NR SEAB More successful violet tunicate Botrylloides violatious Clark's Harbour ‘11 22 -20.03 ± 0.14 7.89 ± 0.10 2.4 1.8 0.88 (0.58 - 1.38) Dingwall ‘11 17 -21.36 ± 0.11 7.94 ± 0.09 * 1.7 1.4 0.52 (0.32 - 0.88) Lockeport ‘11 21 -19.43 ± 0.20 5.90 ± 0.13 3.6 2.1 1.39 (0.90 - 2.20) Port de Grat ‘11 18 -18.09 ± 0.11 8.03 ± 0.08 * 1.8 1.0 0.41 (0.26 - 0.68) Yarmouth Bar ‘11 19 -20.09 ± 0.17 6.88 ± 0.08 2.9 1.4 0.71 (0.46 - 1.17) Clark's Harbour ‘12 19 -20.06 ± 0.08 7.86 ± 0.10 * 1.3 1.7 0.44 (0.29 - 0.73) Dingwall ‘12 21 -20.78 ± 0.10 7.43 ± 0.13 * 1.7 2.3 0.63 (0.42 - 1.01) Lockeport ‘12 17 -21.05 ± 0.11 7.57 ± 0.05 * 1.7 0.7 0.27 (0.17 - 0.46) Port de Grat ‘12 14 -18.97 ± 0.17 * 7.70 ± 0.11 * 2.6 1.3 0.76 (0.45 - 1.36) Yarmouth Bar ‘12 16 -19.19 ± 0.09 7.04 ± 0.07 1.2 0.9 0.33 (0.20 - 0.56) Less successful golden star tunicate Botryllus schlosseri Clark's Harbour ‘11 16 -19.85 ± 0.10 7.88 ± 0.08 1.5 1.1 0.32 (0.20 - 0.56) Dingwall ‘11 19 -21.41 ± 0.13 7.36 ± 0.07 2.1 1.2 0.50 (0.33 - 0.83) Lockeport ‘11 19 -19.74 ± 0.13 6.43 ± 0.13 * 1.7 2.3 0.96 (0.61 - 1.56) Port de Grat ‘11 16 -18.22 ± 0.10 7.48 ± 0.09 1.4 1.4 0.46 (0.29 - 0.80) Yarmouth Bar ‘11 16 -20.13 ± 0.22 6.67 ± 0.09 3.2 1.2 0.93 (0.57 - 1.59) Clark's Harbour ‘12 19 -19.94 ± 0.06 7.29 ± 0.07 0.9 1.2 0.20 (0.13 - 0.34) Dingwall ‘12 21 -20.95 ± 0.07 6.93 ± 0.09 1.5 1.4 0.34 (0.22 - 0.55) Lockeport ‘12 20 -21.25 ± 0.10 7.21 ± 0.15 1.7 3.1 0.84 (0.56 - 1.38) Port de Grat ‘12 19 -19.76 ± 0.13 7.41 ± 0.09 2.2 1.3 0.65 (0.42 - 1.07) Yarmouth Bar ‘12 21 -19.21 ± 0.11 7.01 ± 0.08 2.2 1.4 0.54 (0.35 - 0.85) Mean ± S.E. δ13C and δ 15N with ranges (CR and NR) 5 SEAB Bayesian Standard Ellipse Area with lower-upper 95% credible intervals calculated from 10 Bayesian iterations of δ13C and δ15N bi-plot ellipses using SIBER 2.0 in R. * denotes significant difference between successful and less successful invasive tunicates at each site/year using ANOVA with post-hoc Games-Howell. See Fig. 2 for SEAB significant differences.

168 Table 5.2 Stable isotope data and isotopic niche of successful (Bythotrephes longimanus, Spiny) and less successful (Cercopagis pengoi, Fish-hook) Cladoceran waterflea in the Great Lakes region 13 15 10 Site/Year n # Ind δ Ccorr δ Ncorr CR NR SEAB More successful spiny waterflea Bythotrephes longimanus Cayuga Lake ‘11 23 690 (30) 0.91 ± 0.03I 1.77 ± 0.01D 0.19 0.40 0.17 (0.11 - 0.26) Collingwood ‘11 7 151 (16-33) -14.63 ± 0.04B 1.94 ± 0.01E 0.11 0.30 0.09 (0.04 - 0.22) Erieau ‘11 12 337 (15-30) 2.40 ± 0.05K 2.70 ± 0.02HI 0.28 0.59 0.30 (0.18 - 0.61) Kashawakamak ‘11 7 210 (30) 1.47 ± 0.01J 2.73 ± 0.01I 0.10 0.11 0.03 (0.02 - 0.08) Lake Simcoe ‘11 4 120 (30) 0.57 ± 0.60 2.68 ± 0.01 - - - Nanticoke ‘11 2 55 (25-30) 5.10 ± 0.04 3.28 ± 0.02 - - - Peninsula ‘11 22 635 (20-33) 0.62 ± 0.03H 2.83 ± 0.01J 0.22 0.53 0.27 (0.19 - 0.44) Port Elgin ‘11 3 80 (20-30) -2.59 ± 0.21 2.68 ± 0.08 - - - Stoney Lake ‘11 9 240 (30) -0.32 ± 0.08G 2.55 ± 0.01G 0.05 0.64 0.13 (0.06 - 0.29) Thunder Bay ‘11 3 90 (30) 7.10 ± 0.08 1.39 ± 0.01 - - - Collingwood '12 13 291 (20-28) -10.42 ± 0.09C 1.34 ± 0.01B 0.16 1.41 0.47 (0.29 - 0.91) Erieau '12 16 445 (20-30) 7.24 ± 0.15M 3.24 ± 0.02L 0.29 2.26 1.51 (0.93 - 2.61) Kashawakamak '12 10 200 (20) -0.81 ± 0.11FG 3.03 ± 0.01K 0.14 1.27 0.41 (0.22 - 0.83) Kingston Basin '12 15 465 (30-35) -1.29 ± 0.15F 1.27 ± 0.01A 0.15 1.93 0.63 (0.39 - 1.11) Lake Simcoe '12 11 223 (17-24) 5.68 ± 0.06L 2.61 ± 0.02GH 0.14 0.65 0.27 (0.15 - 0.55) Nanticoke '12 15 311 (15-30) -7.04 ± 0.08D 1.59 ± 0.01C 0.12 1.04 0.34 (0.21 - 0.61) Peninsula '12 15 510 (30-40) 0.46 ± 0.03H 2.39 ± 0.01F 0.15 0.36 0.12 (0.07 - 0.21) Port Elgin '12 6 178 (27-31) -11.05 ± 0.15C 2.41 ± 0.02F 0.14 1.08 0.57 (0.26 - 1.49) Stoney Lake '12 14 281 (20) -2.84 ± 0.18E 2.63 ± 0.02GHI 0.30 2.04 1.27 (0.76 - 2.27) Less successful fishhook waterflea Cercopagis pengoi Collingwood '11 3 119 (20-74) -14.74 ± 0.26 1.90 ± 0.02 - - - Hamilton '11 16 480 (30) -6.63 ± 0.13D 2.33 ± 0.02F 0.21 2.27 0.93 (0.59 - 1.64) Nanticoke '11 15 450 (30) -19.71 ± 0.13A 1.40 ± 0.01B 0.17 1.74 0.72 (0.44 - 1.26) Peninsula '11 1 23 (23) 0.90 3.07 - - - Port Elgin '11 1 18 (18) -1.43 2.85 - - - Cayuga Lake '12 11 780 (60-120) 2.51 ± 0.07K 2.91 ± 0.03JK 0.30 0.90 0.57 (0.32 - 1.12) Nanticoke '12 14 820 (40-80) -2.88 ± 0.10E 2.30 ± 0.04F 0.44 1.13 1.47 (0.89 - 2.69) Port Elgin '12 2 66 (27-39) -10.76 ± 0.07 2.43 ± 0.05 - - - 13 15 13 15 Mean ± S.E. δ Ccorr and δ Ncorr , range for δ Ccorr (CR) and δ Ncorr (NR). 10 SEAB Bayesian Standard Ellipse Area multiplied by 10 for clarity, with upper-lower 95% credible intervals in parenthesis. n number of samples processed for stable isotope analysis. Isotopic niche was not compared for n < 6. # Ind total number of individuals processed, min-max individuals per sample in parenthesis 13 13 δ Ccorr baseline corrected δ C using methods of Olsson et al. (2009) 15 15 δ Ncorr baseline corrected δ N. Corrected using baseline data as recommended for calculating trophic position by Anderson and Cabana (2007) and also carried out by Olsson et al. (2009) and Jackson et al. (2014) Samples were collected in 2011 (’11) and 2012 (’12) 5 13 SEAB was calculated from 10 Bayesian iterations of δ Ccorr and TP bi-plot ellipses using SIBER 2.0 in R. ABC denotes significant differences between populations determined using ANOVA with Games-Howell post-hoc.

169 Table 5.3 Body size and isotopic niche of successful (Crassostrea gigas, Pacific oyster) and less successful (Crassostrea virginica, Eastern oyster) invasive oysters in the North East Pacific (Vancouver region) b 13 b 15 b b b Site/Year n TL (mm) δ C corr δ N corr CR NR SEAB More successful Pacific oyster Crassostrea gigas Buckley Bay ‘12 18 76.09 ± 2.34C -1.42 ± 0.06A 2.25 ± 0.03B 0.8 0.5 0.10 (0.06 - 0.17) Cigarette Cove ‘12 20 64.18 ± 1.71B 3.23 ± 0.14F 2.6 ± 0.02CD 2.4 0.4 0.18 (0.12 - 0.30) Croften ‘12 20 80.54 ± 2.15C 0.50 ± 0.10C 2.67 ± 0.03D 1.5 0.7 0.18 (0.12 - 0.29) Okeover Arm ‘12 19 86.37 ± 2.98C 0.09 ± 0.26BC 2.62 ± 0.03CD 4.0 0.5 0.37 (0.24 - 0.60) Quadrat Island ‘12 15 74.21 ± 3.14BC 1.33 ± 0.09E 2.28 ± 0.03B 1.1 0.5 0.11 (0.07 - 0.19) Sooke ‘12 15 78.14 ± 1.95C -0.46 ± 0.11B 2.49 ± 0.04C 1.4 0.4 0.18 (0.11 - 0.31) Stanley Park ‘12 19 81.37 ± 2.02C 4.61 ± 0.22G 2.99 ± 0.04E 3.5 0.6 0.45 (0.28 - 0.72) Thetis Island ‘12 18 76.15 ± 2.46C -0.17 ± 0.05B 2.21 ± 0.03B 0.7 0.5 0.07 (0.05 - 0.12) Less successful Eastern oyster Crassostrea virginica Serpentine River ‘12 24 55.02 ± 1.77A 0.31 ± 0.07C 1.58 ± 0.04A 1.4 0.7 0.19 (0.13 - 0.29) b 13 b 15 b 13 b 15 b Mean ± S.E. (TL , δ C corr and δ N corr), range for δ Ccorr (CR ) and δ Ncorr (NR ) SEAB Bayesian Standard Ellipse Area with upper-lower 95% credible intervals in parenthesis. TL (mm) Length of whole tissue 13 13 δ Ccorr baseline corrected δ C using methods of Olsson et al. (2009) 15 15 δ Ncorr baseline corrected δ N. Corrected using baseline data as recommended for calculating trophic position by Anderson and Cabana (2007) and also carried out by Olsson et al. (2009) and Jackson et al. (2014) b data presented and significant differences are for bootstrapped data (n x1000). n number of individuals and samples processed for stable isotope analysis. Note invasive C. virginica has a distribution restricted to one specific location in the region sampled (personal comm. Chris McKindsey, DFO) 13 b 15 b SEAB Bayesian ellipses of δ C corr and δ N corr ABC Denotes significant differences between populations determined using ANOVA with Games-Howell post-hoc on bootstrapped data.

170

Figure 5.1 Map of sites where invasive (a) oysters, (b) Cladoceran waterflea and (c) tunicates were collected Aug-Nov 2011-2012. See text for sample collection methods and Table 5.1, 5.2 and 5.3 for species and year of collection for each site. Service layer credits for ArcGIS basemap: Esri, DeLome, GEBCO, NOAA, NGDC.

171

Figure 5.2 Isotopic niche bi-plots (a) and Bayesian density plots (b) of successful invasive violet tunicate (Botryllus schlosseri, sold lines and dark gray boxes) and less successful golden star tunicate (Botrylloides violatious, dashed lines and white boxes). Standard Ellipse Areas (SEAC in bi-plot, SEAB in density plot) were calculated using δ13C and δ15N bivariate data. See Table 5.1 for data and sites corresponding to the figure (first two letters of each site and year of collection are given in the figure). * Indicates significant differences in isotopic niche (SEAB) between successful and less successful invasive species at each site/year * p < 0.05, ** p < 0.01, *** p < 0.001 (i.e. > 95% 105 Bayesian iterations of SEAC).

172

Figure 5.3 Isotopic niche bi-plot (a) and Bayesian density plots (b) of successful invasive spiny waterflea (Bythotrephes longimanus) and less successful fishhook waterflea (Cercopagis pengoi). Standard Ellipse Areas (SEAC in bi-plot, SEAB in density plot) were calculated using baseline corrected δ13C and δ15N. See Table 5.2 for data and site names corresponding to the figure (first two letters of each site provided in the figure). Ratio above each density plot indicates total comparisons for which isotopic niche (SEAB) of most successful species was significantly broader (∧) or smaller (∨) than the 5 less successful species (p < 0.05 or > 95% of 10 Bayesian iterations of SEAC).

173

Figure 5.4 Isotopic niche bi-plots (a) and Bayesian density plots (b) of invasive oysters: successful Pacific oyster (Crassostrea gigas) and less successful Eastern oyster (Crassostrea virginica). Bayesian Standard Ellipse Areas (SEAB) were calculated using baseline corrected δ13C and δ15N. See Table 5.3 for data and site names corresponding to the figure legends (first two letters of each site presented in figure). * Indicates significant differences in isotopic niche (SEAB) between successful and less successful invasive species * p < 0.05, ** p < 0.01, *** p < 0.001 (i.e. > 95% 105 Bayesian iterations of SEAC).

174 100 5

25 30 80 43

10 60 67 38 Successful

40 Less successful

60 57 No Difference

20 38 28

Broader isotopic niche (% populations sampled) 0 Tunicates Oysters Fishes (10) (60) (8) (14)

Figure 5.5 Total significant differences in isotopic niche between successful and less- successful aquatic invasive species of tunicate, Cladoceran waterflea, oysters and goby fishes. Data presented are % number of comparisons with higher Bayesian standard 5 ellipse area (SEAB, p < 0.05 or > 95% of 10 simulations). SEAB represents core variation (40%) in δ13C and δ15N bivariate population data (baseline corrected for comparisons that involved temporal and spatial comparisons). Total number of comparisons in parenthesis. Comparisons for the less successful oyster species were restricted to one population. Data for comparisons of goby fishes was from Pettitt-Wade et al. (2015). Fish comparisons included two different size groups for the most successful invader. Pooling of data across size groups increased % broader isotopic niche in the most successful invader and reduced % comparisons that were not significantly different.

175 SUPPLEMENTAL MATERIAL

Table 5S.1 Shell length (SL) and stable isotope data (δ13C and δ15N) of bivalve primary consumers used as baseline for spatial and temporal comparison of invasive Cladoceran waterflea in the Great Lakes region and oysters in the North Each Pacific Site/Year Genus/Species # ind SLb (mm) δ13Cb δ15Nb C95b N95b Baseline for invasive Cladoceran waterflea in the Great Lakes region Cayuga Lake '11-12 Dreissena sp. 13 21.7 ± 0.6D -28.1 ± 0.3CD 13.2 ± 0.1K 1.0 0.4 Collingwood '11-12C Dreissena sp. 43 20.8 ± 0.6D -19.1 ± 0.1L 6.4 ± 0.0F 0.4 0.2 Erieau '11 Dreissena sp. 10 9.3 ± 1.8ABC -25.9 ± 0.2F 7.6 ± 0.2G 0.6 0.7 Erieau '12 Dreissena sp. 13 27.2 ± 0.4E -24.7 ± 0.1G 9.5 ± 0.1H 0.3 0.4 Hamilton Harbour '11 Dreissena sp. 68 12.0 ± 0.5B -21.9 ± 0.1I 7.9 ± 0.1G 0.6 0.5 Kashawakamak '11-12C Unionid sp. 11 69.7 ± 1.7F -29.3 ± 0.2ABC 3.0 ± 0.1B 0.9 0.4 Kingston Basin '12 Dreissena sp. 20 30.3 ± 0.6E -26.6 ± 0.1EF 9.0 ± 0.1H 0.3 0.4 Lake Simcoe '11 Dreissena sp. 57 14.6 ± 0.5C -28.2 ± 0.0D 7.7 ± 0.1G 0.1 0.2 Lake Simcoe '12 Dreissena sp. 15 14.1 ± 0.4BC -29.6 ± 0.1B 7.5 ± 0.1G 0.4 0.5 Nanticoke '11 Dreissena sp. 34 9.6 ± 0.2A -21.0 ± 0.1J 11.1 ± 0.0I 0.3 0.2 Nanticoke '12 Dreissena sp. 13 15.3 ± 0.9BC -22.8 ± 0.1H 11.7 ± 0.1J 0.4 0.4 Peninsula '11-12C Unionid sp. 21 59.9 ± 2.3F -27.6 ± 0.3DE 5.0 ± 0.1E 1.2 0.4 Port Elgin '11 Dreissena sp. 26 16.0 ± 0.6C -22.3 ± 0.1HI 2.1 ± 0.1A 0.5 0.3 Port Elgin '12 Dreissena sp. 29 20.8 ± 0.6D -20.1 ± 0.1K 3.6 ± 0.0C 0.3 0.2 Stoney Lake '11-12C Dreissena sp. 68 9.7 ± 0.3A -30.3 ± 0.1A 4.3 ± 0.1D 0.4 0.2 Thunder Bay '11 Dreissena sp. 8 19.3 ± 1.8BCD -29.3 ± 0.1B 4.2 ± 0.2CDE 0.5 0.8 Baseline for invasive oysters in the North East Pacific (Vancouver region) Buckley Bay ‘12 Littorina scutulata 4 5.7 ± 0.3 -10.9 ± 1.1G 9.1 ± 0.0B 7.0 0.1 Buckley Bay ‘12 Mytilus edulis 30 31.1 ± 1.1 -16.0 ± 0.1CD 10.0 ± 0.0C 0.8 0.4 Cigarette Cove ‘12 Mytilus edulis 28 25.5 ± 0.9 -17.6 ± 0.0BC 9.3 ± 0.1B 0.6 1.7 Croften ‘12 Littorina scutulata 14 5.6 ± 0.3 -14.0 ± 0.3EF 9.2 ± 0.1B 1.3 0.6 Croften ‘12 Mytilus edulis 30 29.4 ± 1.5 -18.7 ± 0.1AB 8.1 ± 0.1A 0.9 0.8

176 Site/Year Genus/Species # ind SLb (mm) δ13Cb δ15Nb C95b N95b Okeover Arm ‘12 Littorina scutulata 4 5.6 ± 0.6 -12.8 ± 0.7F 9.3 ± 0.3B 4.4 2.2 Okeover Arm ‘12 Mytilus edulis 30 36.8 ± 1.6 -16.7 ± 0.0C 9.0 ± 0.0B 0.2 0.5 Quadrat Island ‘12 Mytilus edulis 30 30.5 ± 1.1 -18.8 ± 0.1AB 9.5 ± 0.0BC 1.0 0.2 Serpentine River ‘12 Ilyanassa obsoleta 4 14.9 ± 0.8 -20.2 ± 1.0A 12.9 ± 0.2D 6.7 1.4 Sooke ‘12 Mytilus edulis 30 30.9 ± 0.9 -15.0 ± 0.1DE 9.3 ± 0.0B 0.7 0.4 Stanley Park ‘12 Mytilus edulis 43 23.7 ± 0.5 -20.3 ± 0.0A 7.5 ± 0.0A 0.4 0.4 Thetis Island ‘12 Mytilus edulis 29 28.9 ± 1.0 -17.0 ± 0.1C 9.4 ± 0.1B 1.4 0.7 Data presented are mean ± S.E. (SL, δ13C and δ15N), 95% confidence interval range for δ13C (C95) and δ15N (N95). SL (mm) Shell length # ind number of individuals processed for stable isotope analysis (similar size individuals pooled to make min 4 stable isotope samples per site) b data presented and significant differences are for bootstrapped data (n x 1000) C data was pooled across years due to lack of significant differences (p < 0.05, ANOVA with Games-Howell post-hoc). ABC denotes significant differences between populations determined using ANOVA with Games-Howell post-hoc pairwise comparisons on bootstrapped data

177 CHAPTER 6

GENERAL DISCUSSION

178

The association between variation in the traits of organisms and geographical distribution has fascinated scientists for centuries (Wallace 1865). The continuing spread of invasive species across the globe provides a model for understanding the mechanisms involved for widespread distribution, importance of certain traits, such as dietary niche breadth, and implications for survival in novel environments (Sexton et al. 2009).

Variation in resource use can lead to divergence in associated phenotypes with the potential for evolutionary consequences (Sax 2007, Snell-Rood 2013). Emerging insights from species invasions suggest that the ability to respond rapidly to changes in the availability of resources is crucial for survival in novel environments. But comparisons of dietary niches are rarely made between closely related species from multiple animal taxa across broad, long-established distributions (Garcia-Berthou 2007).

Invasive species have long been recognized as unplanned experiments for testing fundamental theory in ecology, evolution and island biogeography (Sax 2007). This dissertation reveals some of the mechanisms that help explain why some species survive over others in space and time. As such, the findings are of interest not only for improving the management of non-indigenous invasive species, but also for understanding the mechanisms that influence the spread and distribution of species in general. Information on the breadth of resources consumed by species introduced to novel environments can assist analysis of the development of food web inter-connectivity, intra-guild predation and niche displacement of native species with potential for evolutionary repercussions

(Ingram et al. 2012). For instance, a broad dietary niche suggests consumption of a wide range of prey and high food web interconnectivity. Greater interconnectivity among niches is thought to promote ecosystem stability (Levine and HilleRisLambers 2009).

179 The findings of this research can be used in trait-based analysis for invasion risk and impact assessments (Jiménez-Valverde et al. 2011) and Species Distribution Models

(Soberón 2010). Moreover, testing the generality of hypotheses across multiple species and scales benefits the development of general theories in ecology and evolution.

MAJOR FINDINGS

This dissertation has demonstrated that study of invasive species can help determine the role of variation in dietary niche for widespread distribution. The combined findings of chapters 2, 3 and 4 indicate that widespread distribution of invasive fishes is associated with dietary plasticity. In chapter 4, the finding of niche expansion from native to invaded regions for the most widespread invasive fish and the reverse for the less widespread species indicated the powerful impact of translocation. These findings further indicate that widespread distribution is facilitated by dietary plasticity, but that source populations do not necessarily share this trait. Broader niches are also associated with longer establishment time (~23 years in the longest established water body), habitat complexity and genetic diversity (Chapter 3). Although more recently established populations still had broader niches than in the native region (Chapter 3 and 4), a minimum of 7 years had passed, which suggests this is long enough for niche divergence to occur. Genetic and phenotypic variation become more important in increasingly stressful conditions (Forsman and Wennersten 2015), such as establishment or spread to novel environments. The association between a broad niche (high inter-individual variation) and success in invasive species could be limited to species in invaded distributions because of the influence of the invasion process in producing inter- individual variation in resource use.

180 In order to determine the relevance of hypotheses for general ecological theory, potential limitations must be examined. For example, the association between dietary niche breadth and post-established spread is reversed for invasive Cladoceran waterflea and oysters in comparison to invasive colonial tunicates and fishes (Chapter 5). These findings suggest that invertebrate species with narrow ranges have an advantage over those with broad ranges in the more limited locations to which they have spread (the tunicates have similar geographic ranges), but that dietary niche breadth is not crucial for widespread establishment of invertebrates. Few studies have compared the dietary niches of invasive invertebrates in relation to invasion success. From a review of the literature,

Hayes and Barry (2008) found inconsistency in whether dietary niche breadth was a facilitator of invasion success and spread. But none of the studies reviewed on invertebrates included dietary niche breadth as a parameter. For insects, Crawley (1987) found life span and tolerance to be positively associated with invasion success, and others have found climate tolerance (Locke 2009) and diapause in dispersal (Panov et al. 2004) to be positively associated with invasion success in aquatic invertebrates. Heino and

Grönroos (2014) also suggested that site-specific environmental variation determines the regional abundance and distribution of stream invertebrates, as opposed to species- specific niche breadth.

Contributions to niche theory Neutral theory in ecology is the ecological equivalent of genetic drift and implies that organisms are mere passengers of environmental stochasticity (Gaston and Chown

2005). It suggests a particularly heavy reliance on environmental parameters for changes in the niche of sessile organisms that exhibit little trophic variation. Our findings promote the relevance of neutral niche theory for the ecological niche of aquatic invertebrates, in

181 that; a broad trophic niche does not consistently associate with widespread distribution

and many comparisons resulted in no significant differences. But the finding of niche

differences in several populations of tunicates and oysters emphasizes the many

exceptions to neutral theory, even in sessile invertebrates.

Evelyn Hutchinson’s perspective of the ecological niche was that individuals have

specific tolerance levels and traits that determine the limits of their niche, contrary to

those before him that perceived environments to be niches that are occupied by

individuals (i.e. Joseph Grinnel, Charles Elton; Colwell and Rangel 2009). Hutchinson

also suggested that niches should be represented as an n-dimensional hypervolume with

multiple niche axes. This dissertation has demonstrated the potential benefits of using

bivariate stable isotope data (δ13C and δ15N) as tracers of dietary and habitat niche,

especially when multiple abiotic and biotic parameters are incorporated as covariates

(Chapter 3). Hutchinson’s recognition of the relevance of environmental and habitat

niches for foraging activity implied, from early on, that there was an inseparable link

between dietary niche and habitat niche.

Habitat niches and invasion success A recurring theme in this dissertation was the role of habitat niche in driving

exceptions to general trends in isotopic niche. Habitat complexity has a significant

influence on short-term variation in fish diets (weeks) and habitats that are particularly

unique are associated with outliers to trends that are otherwise consistent across a species

distribution (Chapter 3). Less successful invaders have instances of broader isotopic

niches (contrary to what was hypothesised and found in overall patterns) in association

with more intraspecific variation in δ13C (Chapters 2, 4 and 5), and specialisation for unique habitats compared to more successful invaders (Chapter 4 and 5). Lack of a

182 general trend for the importance of dietary niche breadth for invasion success (Hayes and

Barry 2008, Kolar and Lodge 2001, and this dissertation), could be due to the lack of recognition of the important association between dietary niche and habitat niche. The findings of this dissertation suggest that dietary niches should not be examined without reference to habitat niches. From review of the literature, Pulliam (2000) also found that niche theory was hampered by lack of appropriate quantification of what defines a suitable habitat.

Ecosystem engineers vs ecosystem stability It is important to recognize that species not only respond to variation in resources and the environment, but their presence also alters the environment, resources available

(Cuddington and Hastings 2004, Simberloff et al. 2013) and the isotopic structure of the community (i.e. ecosystem engineers - changes to fundamental niche, Sagouis et al. 2015,

Vander Zanden et al. 1999). Greater habitat complexity should support a more diverse community and have greater stability and resistance to impact from invasions (i.e. biotic resistance/ecosystem stability, Jeschke 2014). For example, establishment of Round

Goby has been associated with considerable changes to the fish (Campbell et al. 2009,

Rush et al. 2012) and macro-invertebrate community (Barton et al. 2005, Krakowiak and

Pennuto 2008, Kuhns and Berg 1999). Broad niche from long establishment (Chapter 3) could result from a repeated process of high predation pressure on specific prey, followed by a switch to novel prey as the previous prey becomes depleted. This would ultimately lead to more predator – prey interactions and more feeding experience with a broader variety of prey, particularly with high intraspecific competition (Bolnick 2001, Svanback and Bolnick 2007). But this process would require a highly productive community that could support such repeated bouts of intensive foraging and sufficient diversity for prey

183 switching. If this is the mechanism for niche diversification, lack of a restricted niche in long-established populations (~23 yrs) indicates that there is sufficient productivity to support the invasive species in these locations. Although, lack of a significant trend between isotopic niche breadth and time established in other invasive fishes for the time scale proceeding that of the current study (~23 – 340 yrs, Comte et al. 2016) suggests that natural constraints to niche expansion, such as biotic resistance, have a dominant impact at >23 years of establishment.

Long-term establishment is often associated with higher predation pressure on the invader, food web inter-connectivity, and ultimately, increase in positive net value that would lead to the species being considered as naturalised instead of invasive (Schlaepfer et al. 2011, Strayer et al. 2006, Pintor and Bayes 2015). A species needs to be present and reproducing for ‘sufficient duration’ before they can be called naturalised (Copp et al.

2005), but it is unclear how long is required and what parameters determine the limits to the naturalisation process. For example, Round Goby has been established in North

America for at least 25 years and is increasingly recognised as a key component of local food webs (King et al. 2006, Rush et al. 2012). In some Great Lakes locations, such as

Lake St Clair, positive impacts on the community could be balancing (or surpassing) the negative (e.g. significant contribution to predator diets). This could mean that these long- established populations are closer to naturalisation, and removal at this stage would cause more harm than good. But it is likely that some populations of this invasive fish are in locations in which their net impact will continue to be negative, despite long establishment, because the community is unable to support their broad and expanding dietary niches. Density-dependent effects (i.e. constraints on reproductive output as

184 populations increase, Berryman et al. 2002), which regulate spread dynamics in many species invasions (Arim et al. 2006), could regulate niche diversification in invasive populations that spread to systems with low productivity. Fridley et al. (2007) also suggests that diverse ecosystems are likely hotspots of invasion and that reduced species richness accelerates vulnerability to successful invasions. Evidence for both positive and negative impacts on biodiversity from species invasion is termed the ‘invasion-paradox’

(Fridley et al. 2007) and presents an interesting avenue for future research, particularly in relation to the influence of non-indigenous species introductions on evolutionary diversification (Vellend et al. 2007).

Future distributions Rapid changes in climate and associated processes at the regional and global scale will undoubtedly favour the spread of some species more than others (Dukes and Mooney

1999). This makes predicting the spread of invasive species increasingly problematic, particularly as species distributions in general are increasingly shifting in response to changing climates (Parmesan 2006, Rahel and Olden 2008). For example, rising sea levels could soon shift the distribution of invasive oysters, particularly species restricted to estuarine ecosystems (e.g. Eastern oyster; Lefebvre et al. 2009). Dubois et al. (2007) found elevation above sea level (i.e. foraging time) and percentage of mud in surface sediments (affects turbidity and microalgal biomass) to have a strong influence on the feeding ecology of suspension feeders, including tunicates and oysters. Carver et al.

(2006) suggests increasing temperatures will also increase the spread and northern distribution of invasive tunicates in Canada, and different tolerances suggest changes in salinity would favour one species over the other. Increasing temperatures since initial introduction of spiny waterflea and fishhook waterflea could have already driven changes

185 in local abundance, since the less successful fishhook waterflea favours warmer conditions (Cavaletto et al. 2010), and was found to have a broader dietary niche (present study). Considering the influence suspension feeders and Cladoceran predators have on ecosystem function (Green and Crowe 2013), these changes will no doubt have a considerable influence on the health of ecosystems in the future.

FUTURE DIRECTIONS

In this dissertation, hypotheses were tested across broad spatial and temporal ranges and for multiple taxa. Future study should continue to expand across a variety of scales to investigate the broad applicability of hypotheses. For example, analysis of microorganisms in the gut could indicate the role of a diverse gut micro-flora for widespread distribution and broad dietary niches. By comparing populations in native and invaded regions, one could determine how long the same micro-flora lasts and whether it constrains geographic spread. I investigated populations that were well established (min 7 years), comparison with populations at invasion fronts could help determine whether broad niches are important for initial colonization. Conversely, stable isotope analysis of archived samples from initial stages of invasion could provide insight as to whether niche breadth has changed since initial introduction and if restricted niche breadth is a consequence of long time since establishment. To determine the long-term implications of species invasions and broad niches, parallels can be drawn with events in the geological record. For example, Stigall (2014) suggested that the spread of generalists between basins during the Richmondian Invasion (Laurentian craton, ~450Ma) led to a suppression of speciation and loss of biodiversity. To understand the evolutionary significance of ecological variability (i.e. adaptive flexibility hypothesis, Wright et al.

186 2010), studies need to incorporate analysis of functional genotypes in tandem with analysis of associated phenotypes. It is only with such methods that long-term impacts of translocation can truly be investigated. Such investigation could indicate the role of heritability of variation, and the interaction between ecology and evolution for species spread and distribution.

Expanding on niche metrics This dissertation incorporated niche divergence within and among individuals, populations and species at several spatial and temporal scales. This provided for an in- depth assessment of the association between isotopic niche breadth and widespread distribution. To my knowledge, this is the first study to compare the Bayesian isotopic niches of the invasive species pairs in this dissertation. I have demonstrated that study of isotopic niche in invasive species has considerable potential for increasing our understanding of the importance of a varied diet for survival in novel environments.

Furthermore, divergence in trophic niche for similar species of invertebrate that share the same habitat space demonstrated that the application of stable isotopes for dietary niche breadth is not limited to mobile organisms. The use of stable isotopes as tracers of niche metrics is becoming increasingly popular and is rapidly developing towards a closer representation of Hutchinson’s n-dimensional hypervolume with the potential for inclusion of more than two metrics (Swanson et al. 2015). Future studies should work to incorporate climate indices and more life-history traits in analysis of niche breadth, particularly in invasive invertebrates that remain alarmingly understudied and for which environmental parameters seem to be particularly important for dispersal. It would be interesting to incorporate community composition information (i.e. diversity and abundance), and the role of competition and predation in driving variation in realized

187 niches. Incorporating reproductive output would indicate relative fitness of the population and potential for density-dependent effects (Arim et al. 2006). The role of anthropogenic association was also not investigated in this dissertation, which has been suggested as one of the primary predictors of successful spread in established vertebrates (Jeschke and

Strayer 2006) and invertebrates (Panov et al. 2004). Incorporating these parameters in relation to time established would help determine the changes in functional role of invasive species throughout their invasion history.

CLOSING REMARKS

Invasive species are of major global concern. With 7.4 billion people on the planet, 11 billion projected by 2100 (UN, www.worldometers.info/world-population/, accessed 27th Feb 2016), increasingly convenient mechanisms of transportation, and persistent fragmentation of natural habitats from multiple stressors (Walther et al. 2009); reliance of species on anthropogenic dispersal for survival is unlikely to subside.

Avoiding further human assisted dispersal in these species that are already established continues to be a critical factor. Not just for those that are perceived to be the most invasive, but also species that currently have a more limited distribution and could have a stronger reliance on human transport mechanisms for post-established spread. Invasive species are one of many multiple stressors that culminate in the current loss of biodiversity (Ceballos et al. 2015). Our understanding of the role of species that spread to novel environments is to be thoroughly tested, for instance, by the added complication of rapid and persistent climate change (Walther 2009). These challenges increase the importance of the current research findings, and although daunting, provide a stimulating prospect for research in the future.

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195 VITA AUCTORIS

NAME: Harri Pettitt-Wade

PLACE OF BIRTH: Carmarthen, Wales, UK

YEAR OF BIRTH: 1985

EDUCATION: 1996 – 2003: A-Level Biology, History, Sociology, AS-Level Media Queen Elizabeth Cambria School, Carmarthen, Wales, UK.

2003 – 2004: A- Level Chemistry Coleg Sir Gâr, Llanelli, Wales, UK.

2004 – 2007: BSc Marine Biology University of Plymouth, Plymouth, UK.

2007 – 2008: MRes Applied Fish Biology University of Plymouth, Plymouth, UK.

196