Population Characteristics of Interior Double-Crested Cormorants Breeding Across the Southern Border of Ontario

Mississippi State University Scholars Junction

Theses and Dissertations Theses and Dissertations

1-1-2008

Population characteristics of interior double-crested cormorants breeding across the southern border of Ontario

Jennifer Erin Chastant

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Recommended Citation Chastant, Jennifer Erin, "Population characteristics of interior double-crested cormorants breeding across the southern border of Ontario" (2008). Theses and Dissertations. 3564. https://scholarsjunction.msstate.edu/td/3564

This Graduate Thesis - Open Access is brought to you for free and open access by the Theses and Dissertations at Scholars Junction. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of Scholars Junction. For more information, please contact [email protected]. POPULATION CHARACTERISTICS OF INTERIOR DOUBLE-CRESTED

CORMORANTS BREEDING ACROSS THE SOUTHERN

BORDER OF ONTARIO

Jennifer Erin Chastant

A Thesis Submitted to the Faculty of Mississippi State University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Wildlife and Fisheries Science in the Department of Wildlife and Fisheries

Mississippi State, Mississippi

December 2008

Jennifer Erin Chastant

2008

POPULATION CHARACTERISTICS OF INTERIOR DOUBLE-CRESTED

CORMORANTS BREEDING ACROSS THE SOUTHERN

BORDER OF ONTARIO

Jennifer Erin Chastant

Approved:

Richard B. Minnis Bronson K. Strickland Assistant Professor of Wildlife and Assistant Extension Professor of Fisheries Wildlife and Fisheries (Co-Director of Thesis) (Committee Member)

D. Tommy King Bruce D. Leopold USDA/APHIS/WS/NWRC Graduate Coordinator (Co-Director of Thesis) Department of Wildlife and Fisheries

Bruce D. Leopold George M. Hopper Professor and Head Dean Department of Wildlife and Fisheries College of Forest Resources

Name: Jennifer Erin Chastant

Date of Degree: December 12, 2008

Institution: Mississippi State University

Major Field: Wildlife Ecology

Major Professor: Dr. Richard B. Minnis

Title of Study: POPULATION CHARACTERISTICS OF INTERIOR DOUBLE- CRESTED CORMORANTS BREEDING ACROSS THE SOUTHERN BORDER OF ONTARIO

Pages in Study: 136

Candidate for Degree of Master of Science

Interior Double-crested cormorant reproduction was examined on a large geographical scale to evaluate management actions. Three distinct breeding areas across Ontario were selected. Beginning in 2002, over 11,000 pre-fledged cormorants have been marked. During 2006 and 2007, re-observation of banded birds, colony data such as nest, egg, and chick measurements, and island morphology, were collected. Data revealed no significant regional differences in adult size. However, eggs in eastern Lake Ontario (ELO) were larger than North

Channel of Lake Huron (NChan) and Lake of the Woods (LOW). Chicks in ELO throughout development were smaller than NChan and LOW. Number of gulls was correlated inversely to cormorant fledge rate. Survival estimates were <20%

for young of the year, but increased to >80% after year 2. Elasticity analysis revealed that a 50% reduction in adult survival combined with 100% fecundity reduction would result in a 42% reduction in population growth.

Key words: Double-crested cormorant, Phalacrocorax auritus, reproduction, survival estimates

ACKNOWLEDGEMENTS

I would like to thank Tommy King and Rich Minnis, my co-major professors, for giving me the opportunity to work on such an amazing project. I am grateful to Bronson Strickland, for his guidance while serving on my committee. I would like to thank the USDA/WS National Wildlife Research

Center for providing funding for the project and Regina Snow for always having the paperwork ready even when it seemed impossible. I appreciate all the technical and logistics support provided by the technicians at the

USDA/WS/NWRC, Mississippi field station. Chip Weseloh and Dave Moore with the Canadian Wildlife Service, Jim McNullty, Lori Skitt and Scott Lockheart with the Ontario Ministry of Natural Resources, and the many others who have helped with this project, it has been a pleasure working with you all. I also am indebted to Steve Elliott and Peter Rubens for their logistical and boat support and Dr.

James Day for granting access to the study sites. Finally, I would like to give special thanks to my parents who have supported me throughout this endeavor – without you two I would not have been able to do this. You listened and encouraged me to stay focused and achieve my goals.

TABLE OF CONTENTS

ACKNOWLEDGEMENTS...... ii

LIST OF TABLES ...... vi

LIST OF FIGURES ...... xvi

CHAPTER

1. INTRODUCTION ...... 1

Literature cited ...... 9

2. VARIATION IN EGGS, CHICKS AND ADULTS THROUGHOUT THE BREEDING RANGE OF THE INTERIOR METAPOPULATION OF DOUBLE-CRESTED CORMORANTS...... 14

Abstract...... 14 Introduction ...... 15 Methods ...... 17 Study sites...... 17 Study design and analysis...... 18 Results ...... 20 Cormorant Eggs ...... 20 Naked Cormorant Chicks ...... 22 Fledgling Cormorants ...... 22 ELO Fledgling Cormorants...... 23 NChan Fledgling Cormorants...... 24 LOW Fledgling Cormorants...... 24 Adult Cormorants ...... 24 Adult and Fledgling Cormorants...... 25 ELO Adult and Fledgling Cormorants...... 26 iii

NChan Adult and Fledgling Cormorants...... 26 LOW Adult and Fledgling Cormorants...... 27 Discussion...... 27 Summary...... 31 Future Research ...... 33 Literature cited ...... 35 Tables ...... 39 Figures ...... 44

3. ISLAND AND COLONY PARAMETERS INFLUENTIAL IN DOUBLE- CRESTED CORMORANT REPRODUCTIVE SUCCESS...... 45

Abstract...... 45 Introduction ...... 46 Methods ...... 48 Site description...... 48 Study design and analysis...... 49 Results ...... 52 Discussion...... 54 Management suggestion...... 58 Literature cited ...... 59 Tables ...... 62 Figures ...... 64

4. POPULATION PARAMETERS SUCH AS SURVIVAL, RECRUITMENT, AGE AT FIRST BREEDING AND RATE OF CHANGE FOR THE INTERIOR DOUBLE-CRESTED CORMORANT ...... 78

Abstract...... 78 Introduction ...... 79 Methods ...... 81 Study sites...... 81 Banding...... 82 Resighting ...... 83 Reproduction...... 84 Survival estimates ...... 86 Population models...... 87 Results ...... 88 Age at first breeding ...... 88

Lake of the Woods ...... 89 North Channel of Lake Huron...... 89 Eastern Lake Ontario ...... 90 Discussion...... 91 Future research...... 96 Literature cited ...... 97 Tables ...... 101 Figures ...... 115

5. SUMMARY AND CONCLUSIONS...... 120

Literature cited ...... 127

APPENDIX

EGG, CHICK, FLEDGLING, AND ADULT ANOVA TABLES ...... 130

LIST OF TABLES

2.1 Measurements (Mean (SD)) of Double-crested cormorant eggs from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. N = number of nests, eggs averaged within the nest. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Letters in the same row represent LSD codes differing significantly at α = 0.05...... 39

2.2 Measurements (Mean (SD)) of Double-crested cormorant eggs in Eastern Lake Ontario (ELO) Ontario, summers 2006 – 2007. N = number of nests, eggs averaged within the nest. Nest status is considered late if laid after June 1st (McNeil and Lèger 1987)...... 39

2.3 Measurements (Mean (SD)) of Double-crested cormorant eggs in the North Channel of Lake Huron (NChan) Ontario, summers 2006 – 2007. N = number of nests, eggs averaged within the nest. Nest status is considered late if laid after June 1st (McNeil and Lèger 1987)...... 40

2.4 Measurements (Mean (SD)) of Double-crested cormorant eggs in Lake of the Woods (LOW) Ontario, summers 2006 – 2007. N = number of nests, eggs averaged within the nest. Nest status is considered late if laid after June 1st (McNeil and Lèger 1987)...... 40

2.5 Morphology (Mean (SD)) of naked (eyes closed: EC, and eyes open: EO) Double-crested cormorant nestlings from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Letters (case sensitive) in the same row represent LSD codes differing significantly at α = 0.05...... 41

2.6 Morphology (Mean (SD)) of fledgling Double-crested cormorants from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Letters in the same row represent LSD codes differing significantly at α = 0.05...... 42

2.7 Morphology (Mean (SD)) of adult Double-crested cormorants from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Letters in the same row represent LSD codes differing significantly at α = 0.05...... 43

2.8 Egg measurements (Mean) for Double-crested cormorants reported in the literature. SLE = Saint Lawrence Estuary, ME = Maine, UT = Utah. Values are given as the mean from each study...... 43

2.9 Morphology (Mean) of adult Double-crested cormorants reported in the literature. MS = Mississippi, SLE = Saint Lawrence Estuary. Values are given as the weighted average of males and females combined...... 43

3.1 Island variables, number of islands sampled (N), mean, and standard deviation (SD) from 3 geographically separated regions of Double -crested cormorants (DCCO) breeding across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. When applicable, island variables were adjusted as a density (per unit area of the island) to account for various island sizes...... 62

3.2 Double-crested cormorant colony growth rates (CGR), by island, from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods...... 63

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4.1 Summary (by year) of number of Double-crested cormorant bands deployed in Lake of the Woods, number of hours spent observing (Hours), during which part of the breeding season, and number of bands reported (Dead) for each cohort throughout the study...... 101

4.2 Summary (by year) of number of Double-crested cormorant bands deployed in the North Channel of Lake Huron and number of bands reported (Dead) for each cohort throughout the study...... 101

4.3 Summary (by year) of number of green (GN) Double-crested cormorant bands deployed by the U.S. Department of Agriculture, National Wildlife Research Center (NWRC), the number of white (WH) bands deployed in Eastern Lake Ontario by the Canadian Wildlife Service (CWS), number of hours spent observing (Hours), by which agency (Resight Observer), during which part of the breeding season, and number of bands reported (Dead) for each cohort throughout the study...... 101

4.4 Breeding statistics by age class of banded Double-crested cormorants breeding in Lake of the Woods (LOW) and Eastern Lake Ontario (ELO). T = the percentage of birds classified as breeding out of the total number of banded birds seen. Number (n) of birds seen in each age class presented as a percentage of breeding birds (Breed %) and as a breeding percentage of total number of banded birds seen in each age class (Total %). Cormorants banded as young of the year by both the U.S. Department of Agriculture, National Wildlife Research Center (NWRC; green) and the Canadian Wildlife Service (CWS; white) since 2000. A total of 150 cormorants were recorded as breeding out of 650 banded cormorants observed during the 2006 and 2007 breeding seasons...... 102

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4.5 Set of 20 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 4, considered in Program MARK with the Burnham joint live-encounter dead- recovery model for estimation of survival and fidelity of Double- crested cormorants in Lake of the Woods, banded as young of the year. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time- specific models for both r and F were also considered...... 103

4.6 Set of 8 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 2, considered in Program MARK with the Seber dead-recovery model for estimation of survival of Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year. Seber model provides the following parameterization: survival (S) and probability that a band from a dead bird is reported (r). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for r were also considered...... 104

4.7 Set of 8 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 3.5, considered in Program MARK with the Brownie dead-recovery model for estimation of survival of Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year. Brownie model provides the following parameterization: survival (S) and probability that a band from a dead bird is recovered (f). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for f were also considered...... 104

4.8 Set of 20 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 2.5, considered in Program MARK with the Burnham joint live-encounter dead- recovery model for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by the Canadian Wildlife Service (white). Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered...... 105

4.9 Set of 20 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 4, considered in Program MARK with the Burnham joint live-encounter dead- recovery model for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by the U.S. Department of Agriculture, National Wildlife Research Center (green). Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered...... 106

4.10 Set of 20 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 4, considered in Program MARK with the Burnham joint live-encounter dead- recovery model for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by both the U.S. Department of Agriculture, National Wildlife Research Center (green) and the Canadian Wildlife service (white). Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered...... 107

4.11 Stage-classified projection matrix for Double-crested cormorants in Lake of the Woods, Ontario. Cormorants were considered reproductively mature at age 3. Fecundity was estimated using fledge rates from the 2006 and 2007 breeding seasons, divided by two to account for an assumed 50:50 sex ratio. Survival estimates were generated in Program MARK from birds banded as young of the year since 2002. Cormorants were grouped into 4 stages, with the first 3 stages age-specific. The first age class is young of the year (YOY) surviving to the next breeding season the following year. The second and third age classes are birds aged 1 and 2 surviving to the next breeding season the following year. Survival estimates for ages 3, 4, and 5 were averaged together for the fourth age class, ≥3. First row represents fecundity, diagonal represents age class survival...... 108

4.12 Stage-classified projection matrix for Double-crested cormorants in the North Channel of Lake Huron. Cormorants were considered reproductively mature at age 3. Fecundity was estimated using fledge rates from the 2006 and 2007 breeding seasons, divided by two to account for an assumed 50:50 sex ratio. Survival estimates were generated in Program MARK from birds banded as young of the year since 2002. Cormorants were grouped into 4 stages, with the first 3 stages age-specific. The first age class is young of the year (YOY) surviving to the next breeding season the following year. The second and third age classes are birds aged 1 and 2 surviving to the next breeding season the following year. The fourth age class is comprised of birds aged ≥3. First row represents fecundity, diagonal represents age class survival...... 108

4.13 Stage-classified projection matrix for Double-crested cormorants in Eastern Lake Ontario. Cormorants were considered reproductively mature at age 3. Fecundity was estimated using fledge rates from the 2006 and 2007 breeding seasons, divided by two to account for an assumed 50:50 sex ratio. Survival estimates were generated in Program MARK from birds banded as young of the year since 2000. Cormorants were grouped into 4 stages, with the first 3 stages age-specific. The first age class is young of the year (YOY) surviving to the next breeding season the following year. The second and third age classes are birds aged 1 and 2 surviving to the next breeding season the following year. The fourth age class is comprised of birds aged ≥3. First row represents fecundity, diagonal represents age class survival...... 109

4.14 Survival estimates from the top two Quasi Akaike’s Information Criterion (QAICc) ranked Burnham models and their weighted model average for Double-crested cormorants in Lake of the Woods, banded as young of the year (YOY). Age is in years. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered...... 109

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4.15 Survival estimates from the top three Quasi Akaike’s Information Criterion (QAICc) ranked Seber models and their weighted model average for Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year (YOY). Age is in years. Seber model provides the following parameterization: survival (S) and probability that a band from a dead bird is reported (r). For survival, models with time- specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time- specific models for r were also considered...... 110

4.16 Survival estimates from the top two Quasi Akaike’s Information Criterion (QAICc) ranked Brownie models and their weighted model average for Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year (YOY). Age is in years. Brownie model provides the following parameterization: survival (S) and probability that a band from a dead bird is recovered (f). For survival, models with time- specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time- specific models for f were also considered...... 111

4.17 Survival estimates from the top three Quasi Akaike’s Information Criterion (QAICc) ranked Burnham joint live-encounter dead- recovery models and their weighted model average for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year (YOY) by the Canadian Wildlife Service (white). Age is in years. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered...... 111

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4.18 Survival estimates from the top three Quasi Akaike’s Information Criterion (QAICc) ranked Burnham joint live-encounter dead- recovery models and their weighted model average for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year (YOY) by the U.S. Department of Agriculture, National Wildlife Research Center (green). Age is in years. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered...... 112

4.19 Survival estimates from the top two Quasi Akaike’s Information Criterion (QAICc) ranked Burnham joint live-encounter dead- recovery models and their weighted model average for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year (YOY) by both the U.S. Department of Agriculture, National Wildlife Research Center (green) and the Canadian Wildlife service (white). Age is in years. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered...... 112

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4.20 Estimates of sensitivity (Sens) and elasticity (Elas) of fecundity and survival for Double-crested cormorants in Lake of the Woods (LOW), North Channel of Lake Huron (NChan), and Eastern Lake Ontario (ELO) estimated with stage-classified projection matrices. Cormorants were considered reproductively mature at the age of three. Fecundity was estimated using fledge rates from the 2006 and 2007 breeding seasons, divided by two to account for an assumed 50:50 sex ratio. Survival estimates were generated in Program MARK from birds banded as young of the year since 2000. Cormorants were grouped into 4 stages, with the first 3 stages age-specific. The first age class is young of the year (YOY) surviving to the next breeding season the following year. The second and third age classes are birds aged 1 and 2 surviving to the next breeding season the following year. The fourth age class is comprised of birds aged ≥3...... 113

4.21 Estimates for finite rate of increase (λ), intrinsic rate of increase (r), expected number of replacements (Ro), generation time (T), and mean age of parents of offspring of a cohort (mu1) for Double- crested cormorants in Lake of the Woods (LOW), North Channel of Lake Huron (NChan), and Eastern Lake Ontario (ELO) estimated with stage-classified projection matrices. Survival estimates were generated in Program MARK from birds banded as young of the year since 2000...... 114

LIST OF FIGURES

2.1 Location of the 3 geographically separated Double-crested cormorant breeding areas sampled for population characteristics during 2006 - 2007. LOW = Lake of the Woods, NChan = North Channel of Lake Huron, ELO = Eastern Lake Ontario...... 44

3.1 Location of the 3 geographically separated Double-crested cormorant breeding areas sampled for population characteristics during 2006 - 2007. LOW = Lake of the Woods, NChan = North Channel of Lake Huron, ELO = Eastern Lake Ontario...... 64

3.2 Double-crested cormorant fledge rate (chicks fledged per nest) from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Bar represents the mean with upper and lower confidence intervals...... 65

3.3 Double-crested cormorant fledge rate (chicks fledged per nest) by island, in Eastern Lake Ontario, summers 2006 – 2007. SBonnet = Scotch Bonnet, WBro = West Brothers Island...... 65

3.4 Double-crested cormorant fledge rate (chicks fledged per nest) by island, in the North Channel of Lake Huron, summers 2006 – 2007. MGrant = Middle Grant Island, WCousins = West Cousins Island...... 66

3.5 Double-crested cormorant fledge rate (chicks fledged per nest) by island, in Lake of the Woods, Ontario, summers 2006 – 2007. NEBathe = Island Northeast of Bathe Island, NLem = Island North of Lemmon Island ...... 66

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3.6 Double-crested cormorant fledge rate (chicks fledged per nest) separated by the presence of disease, all three breeding regions of Ontario combined, summers 2006 – 2007. Bar represents the mean with upper and lower confidence intervals...... 67

3.7 Double-crested cormorant fledge rate (chicks fledged per nest) separated by the presence of disease, and broken down by island, summers 2006 – 2007...... 67

3.8 Relationship between numbers of Double-crested cormorant (DCCO) nests and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.28, P = 0.16...... 68

3.9 Relationship between the density (number of nests/island size) of Double-crested cormorant (DCCO) nests present on the island and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.27, P = 0.20...... 68

3.10 Relationship between the percentages of total vegetation present on the Double-crested cormorant colony island and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.14, P = 0.55...... 69

3.11 Relationship between the Double-crested cormorant colony island sizes and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.09, P = 0.67...... 69

3.12 Relationship between the Double-crested cormorant colony sizes and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.51, P = 0.01...... 70

3.13 Relationship between the average Double-crested cormorant nest height and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.29, P = 0.31...... 70

3.14 Relationship between the average distance between (Dist b/t) Double- crested cormorant nests and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.33, P = 0.35...... 71

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3.15 Relationship between the maximum numbers of gulls present on the Double-crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.77, P = 0.04...... 71

3.16 Relationship between the maximum density of gulls (maximum number of gulls/island size) present on the Double-crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.82, P = 0.02... 72

3.17 Relationship between the median numbers of gulls present on the Double-crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.73, P = 0.06...... 72

3.18 Relationship between the median density of gulls (median number of gulls/island size) present on the Double-crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.76, P = 0.05...... 73

3.19 Relationship between number of gull nests present on the Double- crested cormorant colony island and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.30, P = 0.41...... 73

3.20 Relationship between the density of gull nests present (number of nests/island size) on the Double-crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.28, P = 0.43...... 74

3.21 Relationship between the number of gull nests present within a 0 – 5 m radius of the Double-crested cormorant colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.33, P = 0.38...... 74

3.22 Relationship between the number of gull nests present within a 5 – 10 m radius of the Double-crested cormorant colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.28, P = 0.54...... 75

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3.23 Relationship between the maximum numbers of adult Double-crested cormorants (DCCO) present in the colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.49, P = 0.32...... 75

3.24 Relationship between the maximum density (maximum number of adults/island size) of adult Double-crested cormorants (DCCO) present in the colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.10, P = 0.86...... 76

3.25 Relationship between the median numbers of adult Double-crested cormorants (DCCO) present in the colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.72, P = 0.11...... 76

3.26 Relationship between the median density (median number of adults/island size) of adult Double-crested cormorants (DCCO) present in the colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.26, P = 0.62...... 77

3.27 Relationship between Double-crested cormorant clutch size and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.01, P = 0.96...... 77

4.1 Location of the 3 geographically separated Double-crested cormorant breeding areas sampled for population characteristics during 2006 - 2007. LOW = Lake of the Woods, NChan = North Channel of Lake Huron, ELO = Eastern Lake Ontario...... 115

4.2 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Burnham model average for Double-crested cormorants in Lake of the Woods (LOW), banded as young of the year. Survival represented as a rate, age is in years...... 116

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4.3 Graphical depiction of the survival estimates with upper and lower confidence intervals from the second “best” Burnham model {S(t)p(t)r(-)F(t)} ranked by QAIC for Double-crested cormorants in Lake of the Woods (LOW), banded as young of the year. Survival represented as a rate, age is in years...... 116

4.4 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Seber model average for Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year. Survival represented as a rate, age is in years...... 117

4.5 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Brownie model average for Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year. Survival represented as a rate, age is in years...... 117

4.6 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Burnham joint live- encounter dead-recovery model average for Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by the Canadian Wildlife Service (WH). Survival represented as a rate, age is in years...... 118

4.7 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Burnham joint live- encounter dead-recovery model average for Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by the U.S. Department of Agriculture, National Wildlife Research Center (GN). Survival represented as a rate, age is in years...... 118

4.8 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Burnham joint live- encounter dead-recovery model average for Double-crested cormorants in Eastern Lake Ontario (ELO), banded as young of the year by both the U.S. Department of Agriculture, National Wildlife Research Center (GN) and the Canadian Wildlife Service (WH)...... 119

4.9 Graphical depiction of the survival estimates with upper and lower confidence intervals from all models in each region for the Interior metapopulation of Double-crested cormorants, banded as young of the year. Survival represented as a rate, age is in years. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. ELO both =both the U.S. Department of Agriculture, National Wildlife Research Center (NWRC; GN) and the Canadian Wildlife Service (WH). NChan brown = Brownie model, NChan Seber = Seber model...... 119

xxi

CHAPTER 1

INTRODUCTION

Of the 6 North American species of cormorants, the Double-crested cormorant (Phalacrocorax auritus) is the most numerous. The most recent population estimate for Double-crested cormorants across North America, including breeding and non-breeding birds, was estimated conservatively at

1,000,000 birds; realistically, this number is probably closer to 2,000,000 (Hatch

1995, Tyson et al. 1999). Their expansive breeding range can be divided into 5

metapopulations: Alaska, the Pacific coast from southern British Columbia to

northern Mexico, central Canada and interior U.S., the Atlantic coast from

Newfoundland to New York, and the western Caribbean including Florida (Hatch

and Weseloh 1999). The northern reaches of the breeding range for the central

Canada and interior U.S. sub-species of Double-crested cormorants (P. a.

auritus; hereafter termed, cormorant) extends from the southern boreal forest in

northern Alberta, Saskatchewan, and Manitoba, spanning the Great Lakes region

in Ontario and into southwestern Quebec. Their breeding range expands south

into central Utah, Colorado and Nebraska, southeastern South Dakota, central

western Minnesota, northeastern Iowa, central Wisconsin, and northern

Michigan; west into southwestern Idaho; and east along the Great Lakes over into the lower Gulf of the Saint Lawrence River (Hatch and Weseloh 1999).

Cormorants first began nesting in the Great Lakes between 1913 and

1920, slowly increasing their breeding numbers to approximately 900 pairs by

1950 (Weseloh and Ewins 1994, Weseloh et al. 1995). Beginning in the mid-

1950s, cormorant reproductive success was diminished severely from widespread contamination of the Great Lakes by organochlorine compounds

(e.g., PCBs, DDT, DDE), causing severe thinning of eggshells; resulting in reproductive failure. Human persecution, namely fishermen destroying nests, eggs, and adults also was attributed to cormorant population suppression. From

1954 to 1977, not a single cormorant was known to have fledged from any of the colonies in Lake Ontario (Price and Weseloh 1986).

Since the late 1970s, cormorant breeding populations have increased throughout much of their breeding range at an annual rate of 29%; from 89 nests in 1970 to over 38,000 nests in 1991 (Weseloh and Ewins 1994, Weseloh et al.

1995, Glahn et al. 1999, Tyson et al. 1999, Werner and Hanisch 2003). This resurgence is attributed to the decline of persistent pesticides in the environment, protection under the 1972 Migratory Bird Treaty Act, increases in man-made water impoundments, and increased food availability at their breeding and over wintering sites (Price and Weseloh 1986, Hobson et al. 1989, Weseloh et al.

1995, Glahn et al. 1999, Tyson et al. 1999, Hatch and Weseloh 1999).

Cormorants are very social, nesting in conspicuous colonies ranging in size from 3 to >3000 nests. Cormorant colonies are most often found on islands because they offer the advantage of typically being devoid of mammalian predators. Cormorants use one or more of the following nesting strategies within a colony: on the ground (typically bare, flat rock), on cliffs, or in trees. If undisturbed, cormorants will commonly reuse the same general nesting site year after year (Lewis 1929, Clapp et al. 1982, Hatch and Weseloh 1999).

The entire island is considered a colony; space permitting, cormorants will aggregate (nests averaging 66-85 cm apart) in several clusters throughout the colony forming sub-colonies that are typically >10 meters apart from one another

(Mendall 1936, Vermeer 1970, Weseloh et al. 1995, Hatch and Weseloh 1999).

Cormorants typically build their nests by interweaving finger-sized sticks and cementing the structure with a thick coat of guano. There appears to be no nest material preference; cormorants will incorporate seaweed, plastic, rope, and trash into their nest. Vegetation used in the structure typically depends on the plant species near the colony; however, cormorants may bring material from several kilometers away (Lewis 1929, Podolsky and Kress 1989, Hatch and

Weseloh 1999). Successful nest structures lasting through winter are reused year after year with a new layer of nest material added each season, producing tall cylindrical turret-like structures, some reaching heights of 2 meters (Vermeer

1970, Siegel-Causey and Hunt 1986, Hatch and Weseloh 1999). Because cormorant guano is highly acidic, nesting activities tend to destroy the local 3

vegetation, change the colony soil chemistry and vegetation species

composition, and cause irreversible damage to trees in less than 3 years (McNeil

and Lèger 1987, Lemmon et al. 1994, Bèdard et al. 1995, Rippey et al. 2002).

Little is known about cormorant population dynamics, such as age- and gender-specific survival, fecundity, and immigration and emigration between

colonies (Price and Weseloh 1986, Nettleship and Duffy 1995, Hatch and

Weseloh 1999, Tobin 1999). It is widely accepted that cormorants do not

typically breed until 2 or 3 years of age (Price and Weseloh 1986, Hatch and

Weseloh 1999). Older, more experienced males are believed to arrive at the

colony first, selecting the best nesting sites, generally in the center of the colony and elevated on previous nest foundations when available (McLeod and Bondar

1953, Blomme 1981, Siegel-Causey and Hunt 1986, McNeil and Lèger 1987).

A clutch is considered complete with 3 to 4 eggs (mean = 3.8; Mitchell

1977). If the entire clutch is lost early in the breeding season, a replacement clutch is laid (Lewis 1929, Mendall 1936, Mitchell 1977, Hatch and Weseloh

1999). The average mass of the cormorant egg is around 46 grams (Lewis 1929,

Mitchell 1977), however, eggs can vary in size and shape between region, colony, sub-colony, and even within the nest (Coulson et al. 1969, Mitchell 1977).

Wide variation among Shag (P. aristotelis) eggs led Coulson et al. (1969) to

postulate egg volume may reflect the quality of the contents; older Shags laid

larger eggs and had greater breeding success. The shag is of the same genus

and a very close relative to the cormorant (Johnsgard 1993). 4

Eggs are laid in intervals of one to 3 days (Johnsgard 1993), and

incubation is estimated to last 25 to 28 days (Lewis 1929, Mendall 1936, Mitchell

1977, Johnsgard 1993, Hatch and Weseloh 1999). Hatching is asynchronous

and the young are altricial. Chick development is rapid, reaching asymptotic

mass in 40 to 45 days (Dunn 1975, DesGranges 1982). Colony differences in chick growth and development may reflect age and experience of the adults.

DesGrange (1982) found that the most rapid growth rates and largest asymptotic weights came from the oldest colonies where the older, more experienced adults breed. Potts et al. (1980) claimed that nest site quality had a greater affect on

Shag (P. aristotelis) fledging success than previous breeding experience.

Overall, annual cormorant hatching success is typically 50 to 75% with a fledge rate of 74 to 95%, or 1.2 to 2.4 chicks per nest, but highly variable throughout the region (Hatch and Weseloh 1999).

Cormorants are inherently migratory, their winter range extending along the North American coast from North Carolina west through the Gulf of Mexico and south to Belize (Hatch and Weseloh 1999). Glahn and Stickley (1995) reported a possible shift in cormorant winter range northeast from the Gulf of

Mexico coast to encompass areas of high channel catfish (Ictalurus punctatus) production, including the Delta region of Mississippi. Satellite telemetry data revealed the summer/breeding ranges of cormorants captured near southeastern aquaculture facilities include the Great Lakes and the prairie pothole region of the

Northern Great Plains (King et al. In Press). Cormorant band recovery analysis 5

confirmed migration patterns from central Canada and the Great Lakes region

flying south/southeast along the East Coast and the Mississippi River flyway to

the southeastern United States (Dolbeer 1991). Dolbeer (1991) also reported

that 70% of the birds banded in Saskatchewan and the Great Lakes region were

recovered in the lower Mississippi River Alluvial Valley.

The Catfish aquaculture industry in the United States began to expand

rapidly in 1985, increasing production from 86,917 kg in 1985 to 255,991 kg live

weight of channel catfish in 1998. Arkansas, Louisiana, and Mississippi increased their water area in production from about 24,000 ha in 1987 to >58,000 ha of ponds in 1999 (U.S. Department of Agriculture 1999). Concomitant with the rise of the aquaculture industry in this region during the last 30 years, wintering populations of cormorants have increased dramatically in the southeastern United States. These piscivorous birds are increasingly found foraging at commercial aquaculture facilities particularly in March, before migration, when 87% of their diet is catfish (Glahn et al. 1995). Glahn et al.

(1999) also found that cormorants increased their overall body condition through catfish exploitation which aided in their over winter survival. Estimated cost of cormorant predation on channel catfish in the Mississippi aquaculture industry is

$25 million annually (Glahn et al. 2002, Glahn and King 2004). Research has shown that although local control of cormorants at aquaculture facilities can reduce site-specific impacts, these efforts have minimal effects on the large-scale

regional problem; researchers are now turning their attention/efforts to the breeding grounds (Nettleship and Duffy 1995, Tobin 1999).

In addition to southeastern aquaculturists, sport and commercial fishermen in the Great Lakes and northeastern regions of the United States also are impacted by increasing cormorant populations (Michigan Department of

Natural Resources 1997, Schneider et al. 1999). Various interest groups are seeking ecologically sound strategies for dealing with effects of burgeoning cormorant populations on the local fisheries and vulnerable island habitats. In

2003, the US Fish and Wildlife Service (US FWS), in cooperation with the US

Department of Agriculture, Wildlife Services (USDA/WS), finalized an

Environmental Impact Statement (EIS) for cormorant management (Hanisch

2003).

Recent reviews of the literature have indicated there is a lack of reliable information with which to analyze population changes, evaluate management efforts, and predict future population trends (Nettleship and Duffy 1995, Tobin

1999, Hanisch 2003). Weseloh et al. (1995:55) stated that “detailed demographic studies of this population have not been made.” Erwin (1995) and

Weseloh and Lewis (1999) recommend that a large-scale banding and color- marking program with an intensive re-observation regimen be coordinated between the US and Canada. This study was designed to compare reproductive parameters on a large geographical scale to provide data necessary to evaluate

approved management actions outlined in the Double-crested cormorant Final

EIS.

The objectives for this study coincide with the research objectives of the

2003, US FWS, USDA/WS Final Double-crested cormorant Environmental

Impact Statement. More specifically, this project will:

1) estimate overall reproductive success of the Interior Double-crested

cormorant breeding across southern Ontario, as well as site-specific

reproductive success for 3 geographically distinct areas within the

region.

2) investigate whether spatial and temporal differences within the region

affect cormorant egg size and chick morphology.

3) estimate age-specific survivorship and reproductive parameters such

as age at first breeding and fledging rates.

The information obtained in this study will be used to develop population models to provide scientific guidelines for adaptive management strategies that reduce cormorant impacts to commercial and natural resources.

Literature cited

Bèdard, J., A. Nadeau, and M. Lepage. 1995. Double-crested cormorant culling in the St. Lawrence River Estuary. Colonial Waterbirds 18 (Spec. Pub. 1):78-85.

Blomme, C. 1981. Status and breeding success of Double-crested cormorant in two North Channel (Lake Huron) colonies in 1979. Ontario Field Biology 35:70-78.

Clapp, R. B., R. C. Banks, D. Morgan-Jacobs, and W. A. Hoffman. 1982. Marine birds of the Southeastern United States and Gulf of Mexico, Part I: Gaviiformes through Pelecaniformes. U.S. Fish and Wildlife Service, Office of Biological Services, FWS/OBS-82/01, Washington, D.C., USA.

Coulson, J. C., G. R. Potts, and J. Horobin. 1969. Variation in the eggs of the Shag (Phalacrocorax aristotelis). Auk 86:232-245.

DesGranges, J. L. 1982. Weight growth of young Double-crested cormorants in the St. Lawrence Estuary, Quebec. Colonial Waterbirds 5:79-86.

Dolbeer, R. A. 1991. Migration patterns of Double-crested cormorants east of the Rocky Mountains. Journal of Field Ornithology 62:83-93.

Dunn, E. H. 1975. Growth, body components and energy content of nestling Double-crested cormorants. Condor 77:431-438.

Erwin, R. M. 1995. Ecology of cormorants: some research needs and recommendations. Colonial Waterbirds 18 (Spec. Pub. 1): 240-246.

Glahn, J. F., P. J. Dixon, G. A. Littauer, and R. B. McCoy. 1995. Food habits of Double-crested cormorants wintering in the Delta region of Mississippi. Colonial Waterbirds 18 (Spec. Pub. 1):158-167.

Glahn, J. F., and A. R. Stickley, Jr. 1995. Wintering Double-crested cormorants in the Delta region of Mississippi: population levels and their impact on the catfish industry. Colonial Waterbirds 18 (Spec. Pub. 1):137-142.

Glahn, J. F., M. E. Tobin, and B. Harrel. 1999. Possible effects of catfish exploitation on overwinter body condition of Double-crested cormorants. Pages 107-113 in M. E. Tobin, technical coordinator. Symposium on Double-crested cormorants: population status and management issues in the Midwest. U.S. Department of Agriculture Tech. Bulletin No.1879. Milwaukee, Wisconsin, USA.

Glahn, J. F., S. J. Werner, T. Hanson, and C. R. Engle. 2002. Cormorant depredation losses and their prevention at catfish farms: economic considerations. Pages 138-146 in L. Clark, editor. Human conflicts with wildlife: economic considerations. Proceedings of the Third National Wildlife Research Center Special Symposium, Fort Collins, Colorado, USA.

Glahn, J. F., and D. T. King. 2004. Bird depredation. Pages 503-529 in C. S. Tucker and J. A. Hargreaves, editors. Biology and culture of channel catfish. Elsevier B. V. Amsterdam, Netherlands.

Hanisch, S. L. 2003. Final environmental impact statement – Double-crested cormorant management in the United States. U.S. Fish and Wildlife Service, Division of Migratory Bird Management, Arlington, Virginia, USA.

Hatch, J. J. 1995. Changing populations of Double-crested cormorants. Colonial Waterbirds 18 (Spec. Pub. 1):8-24.

Hatch, J. J., and D. V. Weseloh. 1999. Double-crested cormorant (Phalacrocorax auritus). Pages 1-36 In A. Poole and F. Gill, editors. The Birds of North America, No. 441. The birds of North America, Inc., Philadelphia, Pennsylvania, USA.

Hobson, K. A., R. W. Knapton, and W. Lysack. 1989. Population, diet and reproductive success of Double-crested cormorants breeding on Lake Winnipegosis, Manitoba, in 1987. Colonial Waterbirds 12:191-197.

Johnsgard, P. A. 1993. Cormorants, darters, and pelicans of the world. Smithsonian Institution Press, Washington,D.C. USA. 445 pp.

King, D. T., B. K. Strickland, and A. A. Radomski. In Press. Winter and summer home ranges and core use areas of Double-crested cormorants captured near aquaculture facilities in the southeastern United States. Symposium: Double-crested cormorants of the Great Lakes - St. Lawrence River Basin: recent studies, movements, and responses to management actions on their biology, ecology. International Association for Great Lakes Research 50th Annual Conference, Penn State University, University Park, PA. 28 May -1 June 2007. Waterbirds Special Publication 2008.

Lemmon, C. R., G. Bugbee, and G. R. Stephens. 1994. Tree damage by nesting Double-crested cormorants in Connecticut. The Connecticut Warbler 14:27-30.

Lewis, H. F. 1929. The natural history of the Double-crested cormorant (Phalacrocorax auritus auritus [Lesson]). Ru-Mi-Lu Books. Ottawa.

McLeod, J. A., and F. F. Bondar. 1953. A brief study of the Double-crested cormorants on Lake Winnipegosis. Canadian Field-Naturalist 67:1-11.

McNeil, R., and C. Lèger. 1987. Nest-site quality and reproductive success of early- and late-nesting Double-crested cormorants. Wilson Bulletin 99:262-267.

Mendall, H. L. 1936. The home-life and economic status of the Double-crested cormorant, Phalacrocrorax auritus auritus Lesson. Maine Bulletin 39:1- 159.

Michigan Department of Natural Resources. 1997. History, status, and trends in populations of yellow perch and Double-crested cormorants in Les Cheneaux Islands, Michigan. J. S. Diana, G. Y. Belyea, and R. D. Clark, Jr., editors. Fisheries Division Special Report.

Mitchell, R. M. 1977. Breeding biology of the Double-crested cormorant on Utah Lake. Great Basin Naturalist 37:1-23.

Nettleship, D. N. and D. C. Duffy. 1995. The Double-crested cormorant: biology, conservation, and management. Colonial Waterbirds 18 (Spec. Pub. 1):1- 256.

Podolsky, R. H. and S. W. Kress. 1989. Plastic debris incorporated into Double- crested cormorant nests in the gulf of Maine. Journal of Field Ornithology 60:248-250.

Potts, G. R., J. C. Coulson, and I. R. Deans. 1980 Population dynamics and breeding success of the shag, Phalacrocorax aristotelis, on the Farne Islands, Northumberland. Journal of Animal Ecology 49:465-484.

Price, I. M., and D. V. Weseloh. 1986. Increased numbers and productivity of Double-crested cormorants, Phalacrocorax auritus, on Lake Ontario. Canadian Field-Naturalist 100:474-482.

Rippey, E., J. J. Rippey, and J. N. Dunlop. 2002. Increasing numbers of pied cormorants breeding on the islands off Perth, western Australia and consequences for the vegetation. Corella 26:61-64.

Schneider, C. P., A. Schiavone, Jr., T. H. Eckert, R. D. McCullough, B. F. Lantry, D. W. Einhouse, J. R. Chrisman, C. M. Adams, J. H. Johnson, and R. M. Ross. 1999. Double-crested cormorant predation on smallmouth bass and other fishes of the eastern basin of Lake Ontario: overview and summary. Pages 1-6 in New York State Department of Environmental Conservation, Special Report. New York, New York, USA.

Siegel-Causey, D. and G. L. Hunt, Jr. 1986. Breeding-site selection and colony formation in Double-crested and Pelagic cormorants. Auk 103:230-234.

Tobin, M. E. 1999. Symposium on Double-crested cormorants: population status and management issues in the Midwest. US Department of Agriculture Technical Bulletin No.1879. Milwaukee, Wisconsin, USA.

U.S. Department of Agriculture. 1999. Catfish Production. National Agricultural Statistics Service.

Vermeer, K. 1970. Some aspects of the nesting of Double-crested cormorants at Cypress Lake, Saskatchewan, in 1969: a plea for protection. The Blue Jay 28:11-13.

Werner, S. J. and S. L. Hanisch. 2003. Status of Double-crested cormorant Phalacrocorax auritus research and management in North America. Vogelwelt 124, supplement: 369-374. 12

Weseloh, D. V. C. and P. J. Ewins. 1994. Characteristics of a rapidly increasing colony of Double-crested cormorants (Phalacrocorax auritus) in Lake Ontario: population size, reproductive parameters and band recoveries. Journal of Great Lakes Research 20:443-456.

Weseloh, D. V., P. J. Ewins, J. Struger, P. Mineau, C. A. Bishop, S. Postupalsky, and J. P. Ludwig. 1995. Double-crested cormorants of the Great Lakes: changes in population size, breeding distribution and reproductive output between 1913 and 1991. Colonial Waterbirds 18 (Spec. Pub. 1):48-59.

Weseloh, D. V. C. and S. J. Lewis. 1999. Information needs for the Double- crested cormorant in Midwestern North America, as identified by an audience survey. Pages 157-158 in M. E. Tobin, technical coordinator. Symposium on Double-crested cormorants: population status and management issues in the Midwest. US Department of Agriculture Technical Bulletin No.1879. Milwaukee, Wisconsin, USA.

CHAPTER 2

VARIATION IN EGGS, CHICKS AND ADULTS THROUGHOUT THE

BREEDING RANGE OF THE INTERIOR METAPOPULATION OF

DOUBLE-CRESTED CORMORANTS

Abstract

To better understand the Interior metapopulation of Double-crested

cormorants (Phalacrocorax auritus), 3 geographically distinct breeding areas

across the southern border of Ontario [Eastern Lake Ontario (ELO), North

Channel of Lake Huron (NChan), and Lake of the Woods (LOW)] were selected

for empirical measures of variation in population characteristics. During the breeding seasons of 2006 - 2007, various egg, naked young, fledgling and adult morphologic data were collected. Eggs in ELO (vol = 46,575.59 ± 3,959 mm³) on

average were larger than eggs in NChan (vol = 45,810.66 ± 3,322 mm³) and

LOW (vol = 45,167.58 ± 3,844 mm³). However, chicks in ELO, not only at

hatching but throughout development into fledging, were smaller than the other 2

regions. However, there were no significant differences in adult size among the

regions (ELO adult wt = 2,074.46 ±181.02 g; NChan adult wt = 2,008.82 ± 221.04

g; LOW adult wt = 2,067.19 ± 176.26 g). ELO and NChan mean clutch sizes 14

were significantly larger than LOW but did not differ significantly. Overall egg and morphologic variation observed in this study may be the product of environmental plasticity, a regional gradient, and/or 2 sub-species of cormorants. The information obtained in this study will help to reveal cormorant metapopulation dynamics, which will provide information needed to create population models.

These models may be used to develop management strategies to reduce cormorant impacts to commercial and natural resources.

Introduction

Since the late 1970s, the Interior metapopulation of Double-crested cormorants (Phalacrocorax auritus; hereafter termed, cormorant) have increased throughout much of their breeding range at a rate of 29% annually (Weseloh and

Ewins 1994; Ewins et al. 1995; Weseloh et al. 1995; Werner and Hanisch 2003).

During the last 30 years, wintering populations of cormorants in the southeastern

United States also have been increasing, concomitant with growth of the channel catfish (Ictalurus punctatus) aquaculture industry in this region. Glahn and

Stickley (1995) reported a possible shift in cormorant winter range northeast from the Gulf of Mexico coast to encompass areas of high catfish production, including the Delta region of Mississippi. These piscivorous birds are increasingly found foraging at commercial aquaculture facilities, costing the Mississippi aquaculture industry $25 million annually (Glahn et al. 2002; Glahn and King 2004).

Cormorant band recovery analysis and satellite telemetry data reveal migration

patterns from central Canada and the Great Lakes region along the East Coast and the Mississippi River flyway to the southeastern United States (Dolbeer

1991; King et al. In Press). Although local control of cormorants at aquaculture facilities can reduce site-specific impacts, these efforts have minimal effects on the large-scale regional problem. Therefore, researchers are now turning their attention to the management of cormorants on their breeding grounds (Nettleship and Duffy 1995; Tobin 1999). Similarly, various interest groups are seeking ecologically sound strategies for dealing with effects of burgeoning cormorant populations on the local fisheries and vulnerable island habitats. Therefore, management of cormorant populations has focused on understanding and manipulating the breeding ecology of these birds (Nettleship and Duffy 1995;

Tobin 1999; Hanisch 2003).

Although substantial regional variation in cormorant egg size and chick morphology has been documented, most of the information has been based on small spatial scales and small sample sizes, none of which were measured by the same investigator (Nettleship and Duffy 1995; Hatch and Weseloh 1999;

Tobin 1999; Hanisch 2003). Weseloh et al. (1995) and Hanisch (2003) stated that while a necessary step in cormorant management, detailed demographic studies of this population have not been made. This study was designed to compare reproductive parameters on a large geographic scale in order to provide data necessary to evaluate approved management actions.

Methods

Study sites

Three geographically distinct breeding areas across the southern border

of Ontario were selected for empirical measures of variation in population characteristics (Figure 2.1). The study sites included: Lake of the Woods

(LOW), near Kenora, in the southwestern corner of Ontario (49.663, -94.507);

North Channel of Lake Huron (NChan), near Blind River, in south-central Ontario

(46.108, -83.026); and Eastern Lake Ontario (ELO), near Kingston, in the far southeastern corner of Ontario (44.191, -76.543). Each of these geographically distinct areas consisted of ground nesting cormorant colonies on a series of small islands within approximately 15 km of the adjacent city. The islands were comprised of granite slabs and/or outcroppings ranging in size from 0.2 ha to 3 ha. These areas were chosen for this study due to their geographic location, logistics, and nest placement on the ground. The Lake of the Woods area comprised 4 islands: Manitou Island; Lemon Island; Island North of Lemon

Island; and Guano Rock. The North Channel area was comprised of 7 islands: the 2 largest colonies on West Island and Middle Grant Island. The Eastern Lake

Ontario area was comprised of 3 islands: Snake Island; Pigeon Island; and West

Brothers Island.

Study design and analysis

During 2006 – 2007, observers systematically visited the colonies once

monthly during the breeding season (weather permitting); the first visit occurred

soon after cormorants initiated egg laying (May), the second visit during mid-

incubation (June), the third visit before chick fledging (July), and the fourth visit at

the end of the season (post-fledging, September-October). Clutch size data and

egg measurements were taken on the first (May) and second (June) visits. Egg

measurements included maximum length (L), and maximum width (W) using dial

calipers to the nearest 0.01 mm, weight using a pesola scale to the nearest 0.1 g,

and status labeled as early or late breeders (a nest was considered late if laid

after June 1st; McNeil and Lèger 1987). Egg volume (EV) was calculated using the equation (Coulson et al. 1969):

EV = 0.51 x ² x LW

Egg shape index (SI) was calculated using the equation:

W SI = 100x L

Coulson et al. (1969) developed these equations for the Shag (P.

aristotelis) egg by adjusting the correction factor for the negative biconal shape.

The shag is of the same genus and a very close relative to the cormorant

(Johnsgard 1993). To avoid pseudo-replication, nests were used as the

independent sample unit; eggs within the nest were averaged sub-samples. A

50-meter tape measure was stretched randomly across each sub-colony. Nests

were chosen systematically in 5-meter increments, all the eggs in the

corresponding nest were measured. Colony clutch size was recorded as the

mean number of eggs observed within each sampled nest on the initial visit into

the colony.

Naked cormorant chicks were chosen from randomly selected nests

based on their size, skin color (“pink”), egg tooth, and whether or not the eyes

were closed (EC) or open (EO; 3-4 days after hatching but before short down

begins to appear in 6-7 days) (Hatch and Weseloh 1999). Modified from Dunn

(1975), naked chick measurements included culmen, tarsus, and ulna lengths using dial calipers to the nearest 0.01 mm, and body-weight using a 50, 100, or

500-g pesola scale (dependent on chick size) to the nearest gram. Fledglings with ≤15 mm of the primary feather sheath present were pulled randomly from the crèche and measured. Fledgling measurements included culmen and tarsus lengths using dial calipers to the nearest 0.01 mm, flattened wing chord length using a ruler to the nearest mm, and body-weight using a 5-kg pesola scale to the nearest 0.1 kg. Adult cormorants were trapped at the beginning of the breeding season at randomly selected active nests using modified padded leg hold traps (King et al. 1998; King et al. 2000) and measured similarly as

fledglings.

Using the GLM procedure (SAS Institute 2003), 3-way ANOVAs were

used on the egg data to test for effects and interaction of region, year, and

breeding status. Even if a 3-way interaction was not detected, 2-way ANOVAs 19

by region were used to test for effects and interaction between year and breeding

status. Egg response variables included length, width, volume, shape, and

clutch size. Two-way ANOVAs were used on the naked chick, fledgling, and

adult data to test for effects and interaction of region and year. One-way

ANOVAs by region were used on fledgling and adult data to test for effects of

age. Response variables included culmen, tarsus, flattened wing cord, ulna, and

weight. Fisher’s Least Significant Difference test (LSD; Fisher 1935) was used to

test for differences in mean egg, naked chick, fledgling, and adult measurements

when significant effects were detected. Statistical significance was concluded at

α = 0.05.

Results

Cormorant Eggs

I used 318 cormorant nests to examine differences in egg size among

regions, years, and breeding status (Tables 2.1 – 2.4, Appendix). Even though

there was no interaction in egg volume between year, region, and breeding

status (F2, 317 = 0.72; P = 0.486), significant interactions existed between year

and region as well as year and breeding status when both years of egg volume

data were pooled (F2, 317 = 4.69; P = 0.010; F2, 317 = 4.11; P = 0.044;

respectively). Egg volume varied among regions (F2, 317 = 3.62; P = 0.028) with

ELO eggs significantly larger than LOW but both not significantly different from

NChan. There was no significant difference in egg volume between years or

breeding status (F1, 317 = 0.83; P = 0.364; F1, 317 = 1.45; P = 0.230; respectively).

Egg shape data revealed no interaction between year, region, or status (F11, 317 =

0.64; P = 0.529). There were no significant differences in egg shape between years, regions, or breeding status (F1, 317 = 0.54; P = 0.461; F2, 317 = 0.21; P =

0.810; F1, 317 = 1.58; P = 0.210; respectively).

No significant interactions existed between year, region, or breeding

status for egg length (F11, 317 = 0.14; P = 0.867). There also were no significant

main effects of year, region or status for egg length (F1, 317 = 1.89; P = 0.170; F2,

317 = 2.26; P = 0.106; F1, 317 = 2.11; P = 0.147; respectively). There was a

significant interaction between year and region for egg width (F2, 317 = 5.56; P =

0.004), but no significant difference between years, regions, or breeding status

(F1, 317 = 0.42; P = 0.517; F2, 317 = 1.92; P = 0.149; F1, 317 = 0.01; P = 0.907;

respectively).

Clutch sizes revealed a significant interaction between year, region, and

status (F2, 317 = 6.32; P = 0.002). Mean clutch size varied among regions (F2, 317

= 5.25; P = 0.006) with ELO and NChan significantly larger than LOW but not significantly different from each other. Clutch size in 2007 was significantly larger than in 2006 and early breeder clutches were significantly larger than late breeder clutches (F1, 317 = 36.10; P < 0.001; F1, 317 = 12.79; P < 0.001;

respectively).

Naked Cormorant Chicks

I used 205 naked cormorant chicks to analyze differences in chick

morphology among regions (Table 2.5, Appendix). Culmen length varied across

regions for eyes closed (F2, 111 = 12.00; P < 0.001), with NChan and LOW significantly longer than ELO but not significantly different from each other.

Culmen length varied across regions for eyes open (F1, 92 = 16.15; P < 0.001),

with LOW significantly longer than ELO. Tarsus length did not vary among

regions for eyes closed (F2, 111 = 2.11; P = 0.126). Tarsus length varied across

regions for eyes open (F1, 92 = 4.56; P = 0.035), with LOW significantly longer

than ELO. Ulna length varied across regions for eyes closed (F2, 111 = 4.83; P =

0.009), with LOW significantly longer than ELO; however, both did not differ

significantly from NChan. Ulna length varied across regions for eyes open (F1, 92

= 6.38; P = 0.013), with LOW significantly longer than ELO. Weight did not differ

among regions for eyes closed (F2, 111 = 1.79; P = 0.172). Weight did not differ among regions for eyes open (F1, 92 = 3.67; P = 0.059).

Fledgling Cormorants

I used 373 fledgling cormorants to analyze among regions and years

(Table 2.6, Appendix). A significant year and regional interaction was found for

all measurements of fledgling cormorant chicks except weight. Fledgling culmen 22

length varied among regions (F2, 372 = 3.41; P = 0.034), with LOW significantly

longer than NChan, which was significantly longer than ELO. Overall fledgling

culmen length in 2007 was significantly longer than 2006 (F1, 372 = 31.07; P <

0.001). Fledgling tarsus length varied among regions (F2, 372 = 11.98; P < 0.001),

with LOW significantly longer than the other two regions. Overall fledgling tarsus

length in 2006 was significantly longer than 2007 (F1, 372 = 5.69; P = 0.018).

Fledgling flattened wing chord length varied among regions (F2, 372 = 7.01; P =

0.001), with LOW and NChan not significantly different from each other, but both

significantly longer than ELO. Overall fledgling wing chord length in 2007 was

significantly longer than 2006 (F1, 372 = 39.05; P < 0.001). Fledgling ulna length

did not vary among regions in 2007 (F2, 190 = 2.14; P = 0.121). Fledgling weight varied among regions (F2, 372 = 65.02; P < 0.001), with LOW significantly larger than ELO and NChan which did not differ significantly from each other. Overall fledgling weight in 2007 was significantly larger than 2006 (F1, 372 = 20.67; P <

0.001).

ELO Fledgling Cormorants

In Eastern Lake Ontario, fledgling culmen length in 2007 was significantly

longer than 2006 (F1, 124 = 14.14; P < 0.001, Appendix). Tarsus length did not

differ significantly between years (F1, 124 = 1.46; P = 0.229). Fledgling flattened

wing chord length in 2007 was significantly longer than 2006 (F1, 124 = 9.51; P =

0.003). Fledgling weight in 2007 was significantly larger than 2006 (F1, 124 = 23

12.90; P < 0.001).

NChan Fledgling Cormorants

In the North Channel of Lake Huron, fledgling culmen length in 2007 was

significantly longer than 2006 (F1, 119 = 14.90; P < 0.001, Appendix). Fledgling

tarsus length, flattened wing chord length and weight did not differ significantly

between years (F1, 119 = 0.00; P = 0.967; F1, 119 = 0.69; P = 0.408; F1, 119 = 3.03; P

= 0.084; respectively).

LOW Fledgling Cormorants

In Lake of the Woods, fledgling culmen length did not differ significantly

between years (F1, 127 = 3.26; P = 0.074, Appendix). Tarsus length was significantly longer in 2006 than 2007 (F1, 127 = 23.89; P < 0.001). Flattened wing chord length was significantly longer in 2007 than 2006 (F1, 127 = 93.32; P <

0.001). Fledgling weight was significantly heavier in 2007 than 2006 (F1, 127 =

7.05; P = 0.009).

Adult Cormorants

I used 178 cormorants to analyze differences in adult morphology among

regions (Table 2.7, Appendix). Adult culmen length varied among regions (F2, 177

= 9.65; P < 0.001), with ELO significantly longer than LOW and NChan. Adult tarsus length varied among regions (F2, 177 = 13.51; P < 0.001), with NChan and 24

LOW significantly longer than ELO. Adult flattened wing chord length did not

differ significantly among regions (F2, 177 = 1.70; P = 0.186). Adult weight did not

differ significantly among regions (F2, 177 = 1.61; P = 0.204).

Adult and Fledgling Cormorants

I used 373 fledglings and 178 adults to analyze morphological differences

among regions and age (Appendix). Significant interaction existed between

region and age for fledgling and adult culmen length (F2, 550 = 25.09; P < 0.001).

Combined fledgling and adult culmen length varied among regions (F2, 550 = 3.19;

P = 0.042) with LOW significantly longer than NChan and ELO which did not differ significantly. Overall adult culmen length did not differ significantly from fledgling culmen length (F1, 550 = 0.55; P = 0.459). Significant interaction existed

between region and age for fledgling and adult tarsus length (F2, 550 = 10.87; P <

0.001). Combined fledgling and adult tarsus length varied among regions (F2, 550

= 21.58; P < 0.001) with LOW significantly longer than NChan which was

significantly longer than ELO. There was no significant difference between

fledgling and adult tarsus length (F1, 550 = 0.22; P = 0.636). Significant interaction existed between region and age for fledgling and adult flattened wing chord length (F2, 550 = 26.31; P < 0.001). Combined fledgling and adult wing chord length varied among regions (F2, 550 = 39.49; P < 0.001) with NChan and LOW not differing significantly, but both significantly longer than ELO. Overall adult

wing chord length was significantly longer than fledgling wing cord length (F1, 550 25

= 714.12; P < 0.001). Significant interaction existed between region and age for

fledgling and adult weight (F2, 550 = 15.26; P < 0.001). Combined fledgling and

adult weight varied among regions (F2, 550 = 18.64; P < 0.001) with LOW

significantly heavier than ELO which was significantly heavier than NChan.

Overall adult weight was significantly heavier than fledgling weight (F1, 550 =

183.03; P < 0.001).

ELO Adult and Fledgling Cormorants

In Eastern Lake Ontario, adult culmen length was significantly longer than

fledglings (F1, 236 = 28.30; P < 0.001, Appendix). Fledgling tarsus length was

significantly longer than adults (F1, 236 = 7.77; P = 0.006). Adult flattened wing

chord length was significantly longer than fledglings (F1, 236 = 674.87; P < 0.001).

Adult weight was significantly heavier than fledglings (F1, 236 = 220.68; P < 0.001).

NChan Adult and Fledgling Cormorants

In the North Channel of Lake Huron, fledgling and adult culmen length did

not vary significantly between ages (F1, 153 = 2.90; P = 0.091, Appendix). Adult tarsus length was significantly longer than fledglings (F1, 153 = 17.06; P < 0.001).

Adult flattened wing chord length was varied significantly longer than fledglings

(F1, 153 = 119.91; P < 0.001). Adult weight was significantly heavier than

fledglings (F1, 153 = 55.98; P < 0.001).

LOW Adult and Fledgling Cormorants

In Lake of the Woods, fledgling culmen length was significantly longer

than adults (F1, 159 = 24.30; P < 0.001, Appendix). Fledgling and adult tarsus

length did not vary significantly between ages (F1, 159 = 3.72; p = 0.056). Adult

flattened wing chord length was significantly longer than fledglings (F1, 159 =

199.53; P < 0.001). Adult weight was significantly heavier than fledglings (F1, 159

= 11.79; P < 0.001).

Discussion

Cormorant reproductive morphology tends to vary regionally from East to

West, with some inconsistencies in direction and timing. The western and upper

Great Lakes cormorant colonies initiate nesting about 2 – 3 weeks later than

cormorants in the eastern and lower Great Lakes, possibly due to weather

conditions (Ewins et al. 1995). In an attempt to account for this regional

variation, cormorants were classified into age groups on a large geographic

scale.

Data revealed that mass of adult cormorants across the Great Lakes

region did not vary. However, adults in LOW were producing smaller eggs that

developed into larger naked and fledgling young, whereas adults in ELO

produced larger eggs that developed into smaller naked and fledgling young.

The eggs and chicks in NChan were intermediate to the other regions. Fledgling tarsus length in ELO and fledgling culmen length in LOW were significantly longer than the adults from their respective regions. This may be an indication of nutrient quality in yolk sack and forage fish available in the region or perhaps an evolutionary shift in morphology.

Eggs can vary in size and shape between region, colony, sub-colony, and even within the nest (Coulson et al. 1969; Mitchell 1977; Table 2.8). Wide variation among Shag (P. aristotelis) eggs led Coulson et al. (1969) to postulate that egg volume may reflect quality of contents whereby older Shags laid larger eggs and had greater breeding success. In this study, early breeding cormorants produced larger eggs supporting the assertion that older, more experienced birds arrive on the breeding grounds and initiate nesting before the younger birds arrive (Coulson et al. 1969; Mitchell 1977; Hatch and Weseloh 1999). Perhaps many of the late breeders were breeding for the first time or replacing lost clutches and thus produced smaller eggs.

Preston (1969) stated that when dealing with egg volume, a bird cannot change the size of its urethra. Therefore egg width is fixed, with direct implications to the bird itself, and changes in egg volume can occur only by changes in egg length. Accordingly, these data revealed no significant difference in egg width across the region, the variation occurred in egg length. This supports the hypothesis that adults are relatively uniform in size across all regions studied. Egg measurements documented in the literature (Table 2.8) 28

mirror the measurements collected in this study. One exception was that egg

length in the Saint Lawrence estuary noted by Lewis (1929) was shorter than the

egg length found in ELO during this study.

Eastern Lake Ontario had a larger clutch size than the other two more western regions. Similarly, early breeders in all three regions had larger clutch

sizes than late breeders. A typical cormorant clutch is considered complete with

three to four eggs (mean = 3.8; Mitchell 1977). Ellison and Cleary (1978) and

DesGranges (1982) found average clutch sizes of 2.35 and 3.2 eggs/nest

(respectively) in undisturbed colonies in the St. Lawrence Estuary. However,

Ellison and Cleary (1978) also found that mean clutch sizes in human disturbed

colonies within the same region were 2.06 eggs/nest. Kury and Gochfeld (1975)

found that over time, cormorants can attenuate to human disturbance.

Therefore, one possible explanation for the regional clutch size difference in this

study is that birds in ELO tended to be more accustomed to human visitation

and, thus, flushed off their nests less often and for shorter durations than the

birds in NChan and LOW. The longer the adults are off the nest, the more

opportunity for gulls to enter and depredate the cormorant colony (Kury and

Gochfeld 1975; Ellison and Cleary 1978).

Measurement values of naked chicks increased from west to east. While

the data were significant, it must be understood that chicks used for these

measurements were of the same age class, not the exact same age. Ages

ranged from 0 to 3 or 4 days. Combining data from ages 0 to 3 days, Dunn 29

(1975) found the average weight for eyes-closed nestlings in New Hampshire to

be 48.08 g (N = 142), the average culmen to be 9.31 mm (N = 13), the average

tarsus to be 18.54 mm (N = 13), and the average ulna to be 19.06 mm (N = 18).

Dunn’s results, from an Atlantic cormorant metapopulation colony, are most

similar to the results found in ELO in this study suggesting that the birds in ELO

may be more similar to the Atlantic metapopulation than LOW and NChan.

Lake of the Woods fledglings were morphologically largest both years.

However, in 2006, outbreaks of New Castle’s Disease and Botulism in ELO

(D.V.C. Weseloh pers. comm.) may have caused stunted chick development in that region. While differences were significant, it must be understood that fledglings used for these measurements were of the same age class, not the exact same age. Fledglings with ≤15 mm of the primary feather sheath present

were used for measurement. Therefore, these parameters may need to be

evaluated more closely with known age birds. Combining data from ages 36 and

37 days, Dunn (1975) found the average weight for fledglings in New Hampshire

to be 1834.93 g (N = 3), the average culmen to be 57.00 mm (N = 2), the

average tarsus to be 77.50 mm (N = 2), and the average ulna to be 174.00 mm

(N = 2). Dunn’s results, from an Atlantic cormorant metapopulation colony, are

most similar to the results found in LOW for this study suggesting that the birds in

LOW may be more similar to the Atlantic metapopulation than NChan and ELO.

In this study, adult cormorants across the Great Lakes region showed

variation in culmen and tarsus. Adult culmen and tarsus measurements in 30

NChan and LOW were most similar to measurements from adults collected in

Mississippi (MS; Glahn and McCoy 1995; Table 2.9; male and female data were combined), except for body mass. This difference in mass is most likely due to the time of year the data were collected. Birds were collected at winter roost sites in Mississippi whereas the measurements from NChan and LOW were collected during the breeding season when the birds were under reproductive stress. Breeding adult culmen and tarsus measurements in ELO were most similar to measurements from adults in the St. Lawrence Estuary (SLE; Bédard et al. 1995; male and female data were combined).

Summary

Cormorant eggs and clutch sizes in ELO were larger than eggs and clutch sizes from NChan and LOW. The chicks in ELO, not only at hatching but throughout development (naked through fledgling), were smaller than the other 2 regions. However, adults were ultimately relatively the same size for all 3 regions. I have three working theories that may explain the size differences observed in this study:

1) Adult body condition upon arrival and subsequent nest site quality:

Egg production is energetically expensive for a bird. Perhaps adult

body condition in ELO was better, thus, producing larger eggs. But the

breeding site quality in ELO was poor, therefore retarding chick

development. In contrast, adult body condition in NChan and LOW

was poor, producing smaller eggs but the breeding site quality was

rich, aiding the chicks in development.

2) Nutrient quality and availability: A larger egg infers a larger yolk sack.

Perhaps because the quality of the yolk was poor, requiring a larger

egg to accommodate the increased resource requirements needed to

generate the same amount of nutrients (Hanbidge and Fox 1996). It

also was possible that food availability and quality in ELO was less

than that of the other 2 sites again, stunting chick development.

3) Two sub-species of cormorants: Traditionally, the line dividing the

Atlantic coast metapopulation and the Interior metapopulation is the St.

Lawrence River (Hatch and Weseloh 1999). These data suggest that

the metapopulation dividing line may need to be shifted west to include

the breeding birds of ELO in the Atlantic coast metapopulation.

Research is needed to determine if these are sub-populations or sub-

species.

While each of these theories may explain most of the variation found in this study, a combination of all 3 theories may be more appropriate. Overall variation observed may be the product of environmental plasticity, a regional gradient, and 2 sub-species of cormorants.

Future Research

Although body mass differences were observed, weight is highly variable

in cormorants. For example, the individual may have consumed a large meal, or

regurgitated just prior to its weight being taken, thereby having a significant effect

on the measurement (Mendall 1936; Coulter 1981; DesGranges 1982).

Therefore weight measurements should be analyzed with caution. Another highly variable measurement for comparison is wing chord length. Cormorants have a continuous feather molt (Hatch and Weseloh 1999) which may lead to biased flattened wing chord measurements. Ulna length varied less than wing chord and therefore, I recommend ulna length as a more consistent measurement of wing length.

In this study, I used a cormorant breeding area classification of “rich or poor” as a possible explanation for some of the variations observed. These “rich or poor” classifications were based on mostly anecdotal information. I suggest

that by including research in the design of future studies to determine nutrient

content and availability of a site would allow more accurate classification of the

breeding area.

Lastly, a large geographic scale genetics study would help determine if the

Double-crested cormorants sampled for this study are, in fact, actually 2 sub-

species. Analyses of cormorant band recoveries and telemetry data show little

overlap of Interior and Atlantic metapopulations (Dolbeer 1991; King et al. In

Press; King unpublished data). A thorough genetic study would provide valuable 33

information needed to properly evaluate Double-crested cormorant management strategies.

Literature cited

Bédard, J., A. Nadeau, and M. Lepage. 1995. Double-crested cormorant morphometry and field sexing in the St. Lawrence River Estuary. Colonial Waterbirds 18 (Spec. Pub. 1):86-90.

Coulson, J. C., G. R. Potts, and J. Horobin. 1969. Variation in the eggs of the Shag (Phalacrocorax aristotelis). Auk 86:232-245.

Coulter, M. C. 1981. A source of variation in avian growth studies: undigested food. Journal of Field Ornithology 52:62.

DesGranges, J. L. 1982. Weight growth of young Double-crested cormorants in the St. Lawrence Estuary, Quebec. Colonial Waterbirds 5:79-86.

Dolbeer, R. A. 1991. Migration patterns of Double-crested cormorants east of the Rocky Mountains. Journal of Field Ornithology 62:83-93.

Dunn, E. H. 1975. Growth, body components and energy content of nestling Double-crested cormorants. Condor 77:431-438.

Ellison L. N. and L. Cleary. 1978. Effects of human disturbance on breeding of Double-crested cormorants. Auk 95:510-517.

Ewins P. J., D. V. Weseloh, and H. Blokpoel. 1995. Within-season variation in nest numbers of Double-crested cormorants (Phalacrocorax auritus) on the Great Lakes: implications for censusing. Colonial Waterbirds 18:179- 192.

Fisher, R. A. 1935. The design of experiments. Edinburgh: Oliver and Boyd. 252 pp.

Glahn, J. F., and R. B. McCoy. 1995. Measurements of wintering Double- crested cormorants and discriminant models of sex. Journal of Field Ornithology 66:299-304.

Glahn, J. F., and D. T. King. 2004. Bird depredation. Pages 503-529 In C. S. Tucker and J. A. Hargreaves, editors. Biology and culture of channel catfish. Elsevier B.V. Amsterdam, Netherlands.

Hanbidge, B. A. and G. A. Fox. 1996. Egg characteristics, growth and developmental landmarks of known-age embryos of Double-crested cormorants from Manitoba. Colonial Waterbirds 19:139-142.

Johnsgard, P. A. 1993. Cormorants, darters, and pelicans of the world. Smithsonian Institution Press, Washington, USA 445 pp.

King, D. T., J. D. Paulson, D. J. LeBlanc, and K. Bruce. 1998. Two capture techniques for American white pelicans and Great blue herons. Colonial Waterbirds 21:258-260.

King, D. T., M. E. Tobin, and M. Bur. 2000. Capture and telemetry techniques for Double-crested cormorants (Phalacrocorax auritus). Pages 225-234 Proc. 19th Veter. Pest Conf., T. P. Salmon and A. C. Crabb, editors. Published at University of California, Davis, USA.

Kury, C. R. and M. Gochfeld. 1975. Human interference and gull predation in cormorant colonies. Biological Conservation 8:23-34.

Lewis, H. F. 1929. The natural history of the Double-crested cormorant (Phalacrocorax auritus auritus [Lesson]). Ru-Mi-Lu Books. Ottawa.

McNeil, R., and C. Lèger. 1987. Nest-site quality and reproductive success of early- and late-nesting Double-crested cormorants. Wilson Bulletin 99:262-267.

Mendall, H. L. 1936. The home-life and economic status of the Double-crested cormorant, Phalacrocrorax auritus auritus Lesson. Maine Bulletin 39:1- 159.

Mitchell, R. M. 1977. Breeding biology of the Double-crested cormorant on Utah Lake. Great Basin Naturalist 37:1-23.

Nettleship, D. N. and D. C. Duffy. 1995. The Double-crested cormorant: biology, conservation, and management. Colonial Waterbirds 18 (Spec. Pub. 1):1- 256.

Preston, F. W. 1969. Shapes of birds’ eggs: extant North American families. Auk 86:246-264.

SAS Institute 2003. Version 9.13, Service Pack 4. SAS Institute, Cary, North Carolina, USA.

Tobin, M. E. 1999. Symposium on Double-crested cormorants: population status and management issues in the Midwest. US Department of Agriculture Tech. Bull. No.1879. Milwaukee, Wisconsin, USA.

Werner, S. J. and S. L. Hanisch. 2003. Status of Double-crested cormorant Phalacrocorax auritus research and management in North America. Vogelwelt 124, supplement: 369-374. 37

Tables

Table 2.1 Measurements (Mean (SD)) of Double-crested cormorant eggs from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. N = number of nests, eggs averaged within the nest. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Letters in the same row represent LSD codes differing significantly at α = 0.05.

Region ELO NChan LOW N 105 90 123 Vol (mm³) 46,575.59 (3,959)A 45,810.66 (3,322)A,B 45,167.58 (3,844)B Shape 63.05 (2.94)A 63.27 (3.33)A 63.40 (3.08)A Length (mm) 61.27 (2.36)A 60.83 (2.51)A,B 60.44 (2.68)B Width (mm) 38.57 (1.32)A 38.41 (1.17)A 38.24 (1.24)A # eggs/nest 2.99 (1.01)A 2.90 (1.03)A 2.54 (1.04)B

Table 2.2 Measurements (Mean (SD)) of Double-crested cormorant eggs in Eastern Lake Ontario (ELO) Ontario, summers 2006 – 2007. N = number of nests, eggs averaged within the nest. Nest status is considered late if laid after June 1st (McNeil and Lèger 1987).

Region ELO Year 2006 2007 Status Early Late Mean Early Late Mean N 25 20 45 30 30 60 48,519.74 46,142.68 47,463.27 45,479.32 46,340.36 45,909.84 Vol (mm³) (4,162) (5,489) (4,887) (3,040) (2,863) (2,960) Shape 64.02 (2.68) 63.24 (3.11) 63.67 (2.87) 62.11 (3.19) 63.06 (2.62) 62.59 (2.94) Length (mm) 61.47 (2.42) 60.91 (2.77) 61.22 (2.57) 61.43 (2.11) 61.18 (2.33) 61.3 (2.21) Width (mm) 39.29 (1.27) 38.47 (1.78) 38.92 (1.55) 38.09 (1.20) 38.52 (0.84) 38.30 (1.05) # eggs/nest 3.2 (1.08) 2.0 (0.92) 2.67 (1.17) 3.13 (1.01) 3.33 (0.55) 3.23 (0.81)

Table 2.3 Measurements (Mean (SD)) of Double-crested cormorant eggs in the North Channel of Lake Huron (NChan) Ontario, summers 2006 – 2007. N = number of nests, eggs averaged within the nest. Nest status is considered late if laid after June 1st (McNeil and Lèger 1987).

Region NChan Year 2006 2007 Status Early Late Mean Early Late Mean N 10 26 36 30 24 54 45,685.46 44,706.65 44,978.54 46,428.90 46,286.03 46,365.40 Vol (mm³) (3,047) (3,439) (3,322) (2,908) (3,667) (3,235) Shape 62.49 (2.52) 63.63 (4.10) 63.31 (3.73) 62.77 (3.08) 63.83 (3.02) 63.24 (3.07) Length (mm) 60.86 (1.90) 60.3 (3.06) 60.45 (2.77) 61.40 (2.20) 60.66 (2.43) 61.07 (2.31) Width (mm) 37.99 (1.06) 38.25 (1.27) 38.18 (1.21) 38.50 (1.08) 38.64 (1.21) 38.56 (1.13) # eggs/nest 3.1 (1.10) 2.6 (1.33) 2.75 (1.27) 3.4 (0.62) 2.5 (0.78) 3.0 (0.82)

Table 2.4 Measurements (Mean (SD)) of Double-crested cormorant eggs in Lake of the Woods (LOW) Ontario, summers 2006 – 2007. N = number of nests, eggs averaged within the nest. Nest status is considered late if laid after June 1st (McNeil and Lèger 1987).

Region LOW Year 2006 2007 Status Early Late Mean Early Late Mean N 19 44 63 30 30 60 44,995.60 44,100.82 44,370.67 45,821.67 46,187.00 46,004.34 Vol (mm³) (2,871) (4,497) (4,073) (3,592) (3,303) (3,426) Shape 63.27 (3.20) 63.49 (3.28) 63.43 (3.23) 63.25 (2.66) 63.48 (3.26) 63.36 (2.95) Length (mm) 60.46 (2.59) 59.89 (3.04) 60.06 (2.90) 60.82 (2.31) 60.87 (2.48) 60.82 (0.50) Width (mm) 38.19 (0.95) 37.94 (1.41) 38.02 (1.29) 38.41 (1.15) 38.55 (1.15) 38.48 (1.14) # eggs/nest 1.95 (0.78) 1.95 (0.99) 1.95 (0.92) 3.13 (0.73) 3.2 (0.81) 3.17 (0.76)

Table 2.5 Morphology (Mean (SD)) of naked (eyes closed: EC, and eyes open: EO) Double-crested cormorant nestlings from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Letters (case sensitive) in the same row represent LSD codes differing significantly at α = 0.05.

Region ELO NChan LOW Status EC EO EC EO EC EO N 61 60 10 0 41 33 Culmen (mm) 10.31 (1.20)B 13.83 (2.39)b 11.75 (1.27)A - 11.33(1.19)A 15.62 (1.19)a Tarsus (mm) 15.03 (1.50)A 21.51 ( 4.16)b 15.34 (1.79)A - 15.81 (2.36)A 23.15 (1.98)a Ulna (mm) 20.00 (2.40)B 28.45 (5.82)b 20.39 (2.13)A,B - 21.40 (1.99)A 31.20 (3.04)a Weight (g) 46.82 (11.47)A 111.27 (45.64)a 43.40 (7.43)A - 50.27 (13.13)A 127.70 (24.71)a

Table 2.6 Morphology (Mean (SD)) of fledgling Double-crested cormorants from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Letters in the same row represent LSD codes differing significantly at α = 0.05.

Region ELO NChan LOW Year 2006 2007 Mean 2006 2007 Mean 2006 2007 Mean N 60 65 125 60 60 120 62 66 128 C B A Culmen 52.84 56.77+ 54.88 56.20 59.00+ 57.60 58.78 59.79+ 59.30 (mm) (4.35) (6.93) (6.14) (4.21) (3.72) (4.19) (2.99) (3.36) (3.21) B B A Tarsus 67.27 67.76 67.53 67.56 67.54 67.55 70.45 68.25 69.32 (mm) (2.33) (2.21) (2.27) (2.23) (1.97) (2.10) (2.51) (2.56) (2.76) B A A Wing 220.42 238.97+ 230.06 268.88 273.32 271.10 251.61 282.25 267.47 (mm) (37.53) (29.53) (34.74) (35.12) (21.91) (29.22) (18.88) (2.56) (23.65) A A A Ulna 171.08 171.08 170.93 170.93 172.95 172.95 (mm) - (6.79) (6.79) - (6.46) (6.46) - (5.27) (5.28) B B A Weight 1,581.67 1,730.00+ 1,658.80 1611.67 1,691.17 1,651.42 1,888.71 1,979.55 1,935.55 (g) (265.69) (192.85) (241.49) (245.70) (254.61) (252.31) (189.14) (197.48) (198.04)

+ distinguish significantly larger between the 2 years within that region at α = 0.05.

Table 2.7 Morphology (Mean (SD)) of adult Double-crested cormorants from three geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Letters in the same row represent LSD codes differing significantly at α = 0.05.

Region ELO NChan LOW N 112 34 32 Culmen (mm) 58.25 (2.83)A 56.27 (3.38)B 56.32 (2.32)B Tarsus (mm) 66.51 (3.29)B 69.20 (1.90)A 68.31 (2.09)A Wing (mm) 323.46 (16.39)A 326.88 (9.27)A 328.15 (10.79)A Weight (g) 2,074.46 (181.02)A 2,008.82 (221.04)A 2,067.19 (176.26)A

Table 2.8 Egg measurements (Mean) for Double-crested cormorants reported in the literature. SLE = Saint Lawrence Estuary, ME = Maine, UT = Utah. Values are given as the mean from each study.

Region SLE ME UT N eggs 50 15 20* Vol (mm³) 43,418.99 43,621.56 46,638.47 Shape 62.94 62.15 64.52 Length (mm) 59.90 60.50 60.34 Width (mm) 37.70 37.60 38.93 # eggs/nest N/A 3.46 3.80 Source Lewis 1929 Mendall 1936 Mitchell 1977

* Eggs were randomly taken at different times and from different Utah Lake colonies.

Table 2.9 Morphology (Mean) of adult Double-crested cormorants reported in the literature. MS = Mississippi, SLE = Saint Lawrence Estuary. Values are given as the weighted average of males and females combined.

Region MS SLE N 201 1,135 Culmen (mm) 54.80 57.05 Tarsus (mm) 68.47 N/A Wing (mm) 332.37 311.10 Weight (g) 2,429.58 2,003.99 Source Glahn and McCoy 1995 Bédard et al. 1995

Figures

O ONTARI

BEC QUE [_ LOW [_NChan ELO Minnesota [_

k sin Yor Wiscon New n Michiga

ania nsylv Pen

Ohio ylan Mar of C t ict

Figure 2.1 Location of the 3 geographically separated Double-crested cormorant breeding areas sampled for population characteristics during 2006 - 2007. LOW = Lake of the Woods, NChan = North Channel of Lake Huron, ELO = Eastern Lake Ontario.

CHAPTER 3

ISLAND AND COLONY PARAMETERS INFLUENTIAL IN DOUBLE-CRESTED

CORMORANT REPRODUCTIVE SUCCESS

Abstract

Ecologists are constantly trying to identify quick and easy techniques to predict reproductive success. To better understand the Interior metapopulation of Double-crested cormorants (Phalacrocorax auritus) and predict fledging success based on a few island/colony criteria, 3 geographically distinct breeding areas across the southern border of Ontario were selected for empirical measures of island and colony characteristics. During the breeding seasons of

2006 - 2007, various gull and cormorant nesting activities as well as island and colony morphologic data were collected. Of the island/colony parameters measured, number of gulls present on the island, and to a lesser extent cormorant colony size and number of adult cormorants present, were correlated most with cormorant fledging success (r = -0.82, P = 0.02; r = 0.51, P = 0.01; r =

0.72, P = 0.11; respectively). The information obtained in this study will help to reveal cormorant metapopulation dynamics, and provide information needed to

create population models. These models will be used to develop management

strategies to reduce cormorant impacts to commercial and natural resources.

Introduction

The Interior metapopulation of Double-crested cormorants (Phalacrocorax

auritus; hereafter termed, cormorant) first began nesting in the Great Lakes

between 1913 and 1920, slowly increasing their breeding range to encompass

the entire Great Lakes region from the lower Gulf of the Saint Lawrence River

over into central Canada and the interior United States (Weseloh and Ewins

1994, Weseloh et al. 1995). After a major population crash primarily attributed to

DDT, cormorant breeding populations have increased throughout much of their breeding range at a rate of 29% annually since the late 1970s (Weseloh and

Ewins 1994, Ewins et al. 1995, Weseloh et al. 1995, Werner and Hanisch 2003).

Cormorants are very social, often nesting on islands in conspicuous colonies ranging in size from 3 to >3000 nests. If undisturbed, cormorants commonly reuse the same general nesting site year after year (Lewis 1929,

Clapp et al. 1982, Hatch and Weseloh 1999). The entire island is considered a colony, and space permitting, cormorants will aggregate (nests averaging 66-85 cm apart) in several clusters throughout the colony forming sub-colonies that are typically >10 meters apart (Mendall 1936, Vermeer 1970, Weseloh et al. 1995,

Hatch and Weseloh 1999). Density of breeding birds may be affected by availability of colony sites as well as distribution of local prey items (Hatch and

Weseloh 1999). There also may be intense intraspecific competition for the best nesting sites when numbers of breeding cormorants are not limited by site availability. Factors influential in formation of cormorant colonies as well as their size, movement, and foraging overlaps, have yet to be examined (Hatch and

Weseloh 1999).

It is widely accepted that older, more experienced males arrive at the colony first, selecting the best nesting sites, generally in the center of the colony and elevated on previous nest foundations when available (McLeod and Bondar

1953, Blomme 1981, Siegel-Causey and Hunt 1986, McNeil and Lèger 1987).

Potts et al. (1980) claimed that nest site quality (e.g., capacity, exposure to the elements, access to and protection from the sea) had a greater effect on Shag

(P. aristotelis) fledging success than previous breeding experience. They also found that average nest site quality significantly declined as the breeding population increased (Potts et al. 1980). Studies conducted on cormorants during the 1970 and 1980s in the Great Lakes region to monitor recovery from near extinction by DDT (Postupalsky 1978, Blomme 1981, Weseloh et al. 1983,

Weseloh and Ewins 1994, Weseloh et al. 1995, Hatch and Weseloh 1999) document fledge rates of 0.06 to 2.28 chicks/nest.

There is a lack of reproductive data extending across the entire Interior cormorant breeding range. Most of the information available in the literature is based on a few colonies located in eastern Lake Ontario as well as subject to inconsistent observer effects and subsequent predation (Nettleship and Duffy 47

1995, Hatch and Weseloh 1999, Tobin 1999, Hanisch 2003). This study was

designed to compare reproductive parameters on a large geographical scale to

provide data necessary to evaluate approved management actions. The

information obtained in this study will provide current, standardized baseline

data, across the entire breeding region, for scientific guidelines used to design

adaptive management strategies to reduce cormorant impacts to commercial and

natural resources.

Methods

Site description

Three geographically distinct breeding areas across the southern border

of Ontario were selected for empirical measures of variation in population characteristics (Figure 3.1). The study sites included: Lake of the Woods

(LOW), near Kenora, in the southwestern corner of Ontario (49.663, -94.507);

North Channel of Lake Huron (NChan), near Blind River, in south-central Ontario

and placement of nests on the ground. The Lake of the Woods area comprised 5

islands: Island Northeast of Bathe; Manitou Island; Lemon Island; Island North of

Lemon Island; and Guano Rock. The North Channel area was comprised of 7

islands: the 2 largest colonies on West Island and Middle Grant Island. The

Eastern Lake Ontario area was comprised of 4 islands: Snake Island; Pigeon

Island; Scotch Bonnet Island; and West Brothers Island.

Study design and analysis

Western and upper Great Lakes cormorant colonies initiate nesting about

2 – 3 weeks later than cormorants in the eastern and lower Great Lakes (Ewins

et al. 1995). To standardize data collection, observers systematically visited the

colonies in ELO and LOW once monthly during the breeding season in 2006 and

2007; the first visit just after cormorants have initiated egg laying (May), the

second visit during mid-incubation (June), the third visit just before chick fledging

(July), and the fourth visit at the end of the season (post-fledging, September-

October). The colonies in NChan were only visited during July, just before chick

fledging.

Chick growth is rapid until the individual reaches the fledging stage

(averaging 35 to 40 days old), when the growth rate greatly declines (Dunn

1975); fledglings with ≤15 mm of the primary feather sheath present (Chastant et al. In Review) were used to estimate island fledge rates. A technique modified from Weseloh et al. (1995), was used to estimate island-specific fledge rate

(IFR). A census of all nests and fledglings in the colonies, using direct

observation/count, was conducted in July during the preflight stage of chick

development. The total count of fledglings on the island (F) was divided by the

total nest count (Tn) minus the “full” nest count (Fn - nests containing eggs

and/or naked young, for these nests are considered too young to contribute to

the island fledge rate) in the following equation:

F IFR = − FnTn

Direct nest counts were used to estimate the annual average colony

growth rate for each geographic area using the formula developed by Weseloh

and Ewins (1994):

− lnln ICRC CGR = t

Colony growth rate (CGR), recent nest count (RC), initial nest count (IC),

number of intervening years (t).

Island spatial and descriptive data were collected to understand cormorant

nest-site selection and compare reproductive success of the various nest-site

types. Qualitative variable measured: ocular estimation of island vegetation as a

percentage total cover. Quantitative variables included total cormorant and gull

nest numbers on the island, and gull nest numbers within 5-meter concentric

circles out from the perimeter of the cormorant colony. Nest height was

measured on nests inside the central 5-meter radius of the sub-colony (adapted from Siegel-Causey and Hunt 1986). The height of the tallest edge of the 50

cormorant nest from the ground and the distance between nests from nest bowl center to center was measured with a ruler to the nearest whole cm. A tape measure was stretched randomly across the sub-colony and nests were chosen systematically in corresponding 5-meter increments for estimation of average clutch size. Clutch size was recorded as number of eggs observed within each chosen nest on the initial visit into the colony (taken on the first (May) and second (June) visits).

Direct counts also were used to quantify the total number of cormorants and gulls present (nesting and/or loafing) on the island. Maximum counts as well as median counts were used to have a more representative sample of island inhabitants throughout the entire season. Nest density was calculated by dividing number of nests by area of the colony. Gull and cormorant densities were calculated by dividing the maximum or median number observed by the area of the island. A Trimble Pro XR Global Positioning System was used to obtain spatial variables such as area of the island and area of the sub-colonies.

Due to the small sample size of island characteristics, the association between cormorant fledging success and many island/colony characteristics was examined using the Pearson Correlation coefficient in SAS (SAS Institute 2003).

Using the GLM procedure in SAS, ANOVA and LSD were used to test for differences in average fledge rate among the regions and years. All results were considered significant at α = 0.05.

Results

Each island variable measured displayed high variability possibly due to

different island sizes and limited sampling (Table 3.1). Mean colony growth rate

for Interior Double-crested cormorants I studied from 2006 to 2007 was -0.169

(ELO = -0.393, NChan = 0.005, LOW = -0.120; Table 3.2). While not significant,

the fledge rate in each region decreased in 2007 compared to 2006 (F2, 5 = 4.84;

P = 0.1152; Figure 3.2 – 3.5). In 2006, ELO suffered from outbreaks of New

Castle’s Disease and Botulism (D.V.C. Weseloh pers. comm.) and one colony in

LOW suffered a severe unknown mortality event; however, fledge rates were insignificant between the 2 conditions (F1, 23 = 1.04; P = 0.3180; Figures 3.6, 3.7).

There was no association between total number of cormorant nests on the

island and cormorant fledge rate (Figure 3.8; Pearson’s r = 0.28, P = 0.16). Even

after adjusting for the various island sizes, the relationship between cormorant nest density (number of nests per unit area of the colony) and fledge rate was

still unassociated (Figure 3.9; Pearson’s r = -0.27, P = 0.20). Total percentage of

the island covered with vegetation (Figure 3.10; Pearson’s r = 0.14, P = 0.55)

and island size (Figure 3.11; Pearson’s r = -0.09, P = 0.67) were not correlated to

cormorant fledge rate. Colony size was correlated significantly with cormorant

fledge rate (Figure 3.12; Pearson’s r = 0.51, P = 0.01). Average nest height

(Figure 3.13; Pearson’s r = -0.29, P = 0.31) and average distance between

cormorant nests (Figure 3.14; Pearson’s r = -0.33, P = 0.35) had no association

to cormorant fledge rate. 52

Numbers of individuals present on the island fluctuated throughout the day and season; therefore maximum and median numbers of gulls and cormorants throughout the season were analyzed. The maximum number of gulls (Herring gull; Larus argentatus and Ring-billed gull; L. delawarenis) recorded on the island was correlated negatively with cormorant fledge rate (Figure 3.15; Pearson’s r = -

0.77, P = 0.04). Adjusting for the various island sizes, density of the maximum number of gulls (per unit area of the island) and fledge rate also had a significant negative correlation (Figure 3.16; Pearson’s r = -0.82, P = 0.02). Median number of gulls recorded on the island showed weak association with cormorant fledge rate (Figure 3.17; Pearson’s r = -0.73, P = 0.06). However, when adjusted for the various island sizes, density of the median number of gulls (per unit area of the island) and fledge rate had a significant negative correlation (Figure 3.18;

Pearson’s r = -0.76, P = 0.05). There was no correlation between total number of gull nests on the island (Figure 3.19; Pearson’s r = -0.30, P = 0.41) nor gull nest density (number of nests per unit area of the island; Figure 3.20; Pearson’s r = -

0.28, P = 0.43) and cormorant fledge rate.

There was no correlation between number of gull nests within 0-5 meters

(Figure 3.21; Pearson’s r = -0.33, P = 0.38) nor 5-10 meters (Figure 3.22;

Pearson’s r = -0.28, P = 0.54) of the cormorant colony and cormorant fledge rate.

The maximum number of cormorants recorded on the island (Figure 3.23;

Pearson’s r = 0.49, P = 0.32) as well as the density of the maximum number of cormorants (per unit area of the island; Figure 3.24; Pearson’s r = -0.10, P = 53

0.86) were not correlated with cormorant fledge rate. Median number of cormorants recorded on the island (Figure 3.25; Pearson’s r = 0.72, P = 0.11) and density of median number of cormorants (per unit area of the island; Figure

3.26; Pearson’s r = 0.26, P = 0.62) had no association with cormorant fledge rate. The average cormorant clutch size and cormorant fledge rate showed no apparent trend (Figure 3.27; Pearson’s r = 0.01, P = 0.96).

Discussion

Cormorant fledge rate seemed to improve with disease, but there are a few precautions to consider when reviewing these data. Fledge rate was collected just before chick fledging and based on number of chicks at a specific age, regardless of whether they died after this number was estimated.

Newcastle’s Disease did not begin to affect the colony (ELO) until after these data were already collected. Perhaps there also was a decline in the 2007 fledge rate because many of the breeding adult birds died due to Newcastle’s Disease the previous year and were not available to contribute to the next generation’s cohort (Figure 3.2). Total number of nests in all the colonies which had

Newcastle’s Disease present in 2006 declined in 2007 (Table 3.1). In Figure 3.6, the sick column contains only 4 values, 3 of which are from ELO in 2006 which in general had a greater fledge rate than both LOW and NChan. The not sick column in Figure 3.6 contains all the other fledge rate values from all 3 regions and both years.

Snake Island fledge rate decreased by more than 50% in 2007 (Figure

3.3). This decline is most likely attributed to a semi-permanent observation blind erected in the middle of the largest breeding sub-colony on the island in 2007.

The blind removed quality breeding habitat and displaced many of the breeding birds to a new sub-colony on the north end of the island. Many of the gulls loaf on that end of the island and it was used as the boat mooring site throughout the season resulting in frequent disturbance and consequent predation.

In NChan, 2006 was the first year since 2002 that there were enough chicks to band; the cormorant population is slowly recovering from a reproductive crash, presumably related to the local Alewife (Alosa pseudoharengus) population decline (D.T. King, personal communication). In LOW, the fledge rate for Island Northeast of Bathe (NE Bathe) in 2006 was more than double the fledge rate of any of the other islands in the region (Figure 3.5). NE Bathe was only visited once during banding; eliminating researcher disturbance that the other islands were subjected to all season. The chicks on NE Bathe were 2 weeks behind in development compared to the other islands which may have overestimated the fledge rate. The delayed development may have been from re-location of birds due to failed nesting attempts at other colonies or a re-nesting of the colony due to human disturbance or high wave activity. In 2007, the chicks on NE Bathe were at the same developmental stage as the rest of the region with a fledge rate of 1.1 chicks/nest, similar to the other colonies in LOW. The small cormorant colony on Lemmon Island in LOW that declined from a fledge rate of 55

1.7 in 2006 to 0 in 2007 was located in the middle of a large Ring-billed gull

(Larus delawarenis) colony. The gull colony grew from 0.04 ha in 2006 to 0.12 ha in 2007. Growth of the Ring-billed gull colony most likely lead to intense competition for space and increased predation on cormorant eggs and chicks.

In general, cormorant fledge rate and colony growth rate went down in all regions; researcher presence during this study likely had a negative impact due to increased disturbance and gull depredation (Kury and Gochfeld 1975, Ellison and Cleary 1978, DesGranges and Reed 1981). Number of gulls present on an island was the most strongly correlated of all the variables investigated; the more gulls present on the island, the less cormorant reproductive success.

Correlations may have been effected by strong outlier influence; however, I believe the information is biologically significant. Cormorants are very susceptible to disturbance, they are the first to leave the island and the last to return, providing ample opportunity for the gulls to eat cormorant eggs, and newly hatched young (Kury and Gochfeld 1975, Ellison and Cleary 1978, Hatch and

Weseloh 1999). Cormorant nests on the edge of the colony are visited more frequently by gulls than in the center of the colony; gulls also prefer to depredate nests on flat level ground as opposed to nests on steep cliffs/inclines (Siegel-

Causey and Hunt 1981). Ellison and Cleary (1978) found mean clutch sizes between human disturbed colonies and control colonies in the St. Lawrence

Estuary as 2.06 eggs/nest and 2.35 eggs/nest, respectively.

Gulls benefit from eating cormorant eggs and chicks made vulnerable by disturbances; however, expanding cormorant colonies may usurp the nesting and/or loafing space occupied by gulls, and vegetation modification by cormorants may alter the range of nest sites available to gulls (Hatch and

Weseloh 1999). Somers et al. (2007) in western Lake Ontario found cormorants not only compete with Herring gulls (Larus argentatus) for nest sites but encourage gulls to engage in more aggressive interactions thus having a negative impact on gull reproduction (reduced gull nesting success). They were however, unable to determine the role of human disturbance during nest checks in either instigating or exacerbating the interspecific interactions.

The 3 other important variables correlated to cormorant fledge rate were colony size, number of cormorant nests, and number of cormorants present on the island. These variables are intuitively related, a larger colony is going to have more nests and more cormorants. Similarly, Siegel-Causey and Hunt

(1986) found that when the nesting density of the central nests reached about 0.4 nests/m², cormorants shifted nest construction to the edge of the sub-colony at a density of about 0.2 nests/m². They also asserted that cormorant nest success was highly correlated with the date of nest initiation, nearest-neighbor distance, and nest density.

Cormorants are larger than gulls and will defend the area within bill range of their nest (Hatch and Weseloh 1999). Siegel-Causey and Hunt (1981) believe that the reduced number of visits by gulls to the center of a cormorant colony is 57

due to the aggressive defense behavior of adult cormorants. Kury and Gochfeld

(1975) agree the “neighborhood effect” is an important advantage of colonial

nesting. Human disturbance impedes the natural defense behavior by

cormorants and may lead to colony constriction or an abrupt shift to a new

location (Hatch and Weseloh 1999); however, over time, cormorants can

attenuate to human disturbance (Kury and Gochfeld 1975). In ELO, the colonies

have been under study since the early 1970s; the birds are conditioned for

human visitation and thus flush off their nests less often and for shorter durations

than the birds in NChan and LOW. In 2007, the birds in LOW were much more accustomed to human disturbance and flushed off their nests less readily; especially on Island North of Lemmon Island where an observation blind was placed.

Management suggestion

Rather than spending the time, effort, and money oiling eggs or culling adults, a possible natural cormorant population management technique would be to walk through the colony once every few weeks during incubation and early hatching, causing cormorants to disperse and allow the gulls to depredate the colony. While this method would not be 100% effective at eliminating cormorant reproduction, it is a cheap and easy way to reduce fledging success

(DesGranges and Reed 1981).

Literature cited

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Blomme, C. 1981. Status and breeding success of Double-crested cormorant in two North Channel (Lake Huron) colonies in 1979. Ontario Field Biology 35:70-78.

Chastant, J. E., D. T. King, B. K. Strickland, and R.B. Minnis. In Review. Variation in eggs, chicks and adults throughout the breeding range of the Interior metapopulation of Double-crested cormorants (Phalacrocorax auritus). Symposium: Double-crested cormorants of the Great Lakes - St. Lawrence River Basin: recent studies, movements, and responses to management actions on their biology, ecology. International Association for Great Lakes Research 50th Annual Conference, Penn State University, University Park, PA. 28 May -1 June 2007. Waterbirds Special Publication 2008.

DesGranges, J. L. and A. Reed. 1981. Disturbance and control of selected colonies of Double-crested cormorants in Quebec. Colonial Waterbirds 4:12-19.

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Kury, C. R. and M. Gochfeld. 1975. Human interference and gull predation in cormorant colonies. Biological Conservation 8:23-34.

Lemmon, C. R., G. Bugbee, and G. R. Stephens. 1994. Tree damage by nesting Double-crested cormorants in Connecticut. The Connecticut Warbler 14:27-30.

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McLeod, J. A., and F. F. Bondar. 1953. A brief study of the Double-crested cormorants on Lake Winnipegosis. Canadian Field-Naturalist 67:1-11.

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Postupalsky S. 1978. Toxic chemicals and cormorant populations in the Great Lakes. Canadian Wildlife Service, Wildlife Toxicology Division Manuscript Report. 40:1–25.

Potts, G. R., J. C. Coulson, and I. R. Deans. 1980. Population dynamics and breeding success of the shag, Phalacrocorax aristotelis, on the Farne Islands, Northumberland. Journal of Animal Ecology 49:465-484.

Price, I. M., and D. V. Weseloh. 1986. Increased numbers and productivity of Double-crested cormorants, Phalacrocorax auritus, on Lake Ontario. Canadian Field-Naturalist 100:474-482.

Rippey, E., J. J. Rippey, and J. N. Dunlop. 2002. Increasing numbers of pied cormorants breeding on the islands off Perth, Western Australia and consequences for the vegetation. Corella 26:61-64.

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Siegel-Causey, D. and G. L. Hunt, Jr. 1981. Colonial defense behavior in Double-crested and Pelagic cormorants. Auk 98:522-531.

Siegel-Causey, D. and G. L. Hunt, Jr. 1986. Breeding-site selection and colony formation in Double-crested and Pelagic cormorants. Auk 103:230-234.

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Werner, S. J. and S. L. Hanisch. 2003. Status of Double-crested cormorant Phalacrocorax auritus research and management in North America. Vogelwelt 124, supplement: 369-374.

Weseloh, D. V., S. M. Teeple, M. Gilbertson. 1983. Double-crested cormorants of the Great Lakes: egg-laying parameters, reproductive failure and contaminant residues in eggs. Canadian Journal of Zoology 61:427-436.

Tables

Table 3.1 Island variables, number of islands sampled (N), mean, and standard deviation (SD) from 3 geographically separated regions of Double-crested cormorants (DCCO) breeding across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. When applicable, island variables were adjusted as a density (per unit area of the island) to account for various island sizes.

ELO NChan LOW Island Variable N Mean SD N Mean SD N Mean SD

# nests 6 871 450 11 357 262 10 177 137 nest density 5 8,103.40 3,269.69 11 8,240.82 3,655.34 8 16,999.04 14,216.89 % total veg. on the island 3 28.33 12.58 10 49.70 33.38 8 49.25 38.46 island size (ha) 5 0.712 0.564 11 1.61 1.33 8 0.5025 0.374 colony size (ha) 5 0.140 0.127 11 0.04 0.023 8 0.018 0.020 Avg. nest height 3 24.57 5.51 8 29.85 4.32 3 23.68 10.09 Avg. distance between nests 3 73.43 5.97 3 77.60 5.43 4 70.80 2.94 max gull 3 140 53 0 - - 4 733 1183 max gull density 3 380.62 296.22 0 - - 4 1,224.62 1,771.11 median gull 3 97 25 0 - - 4 689 1209 median gull density 3 236.17 162.42 0 - - 4 1,096.68 1,833.64 # gull nests 3 101 48 2 11 1 5 196 294 gull nest density 3 231.44 191.83 2 20.36 21.72 5 382.23 430.39 gull 0-5 (m) from colony 2 5.50 0.71 2 4 0 5 16 15.22 gull 5-10 (m) from colony 2 2.00 1.41 2 4 0 3 67 28.51 Max DCCO 2 1088 159 0 - - 4 474 490 Max DCCO density 2 2,076.13 1,660.11 0 - - 4 2,253.94 2,362.55 Median DCCO 2 790 581 0 - - 4 213 190 Median DCCO density 2 1,082.79 255.32 0 - - 4 626.00 429.96 Avg. Clutch size 5 3.04 0.34 8 2.64 0.45 9 2.41 0.66 62

Table 3.2 Double-crested cormorant colony growth rates (CGR), by island, from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods.

2006 # 2007 # Region Island of Nests of Nests CGR

ELO Snake 617 411 -0.406 Pigeon 1,606 1,099 -0.379 Mean 1,112 755 -0.393 NChan West 761 578 -0.275 WCousins 165 185 0.114 MGrant 589 732 0.217 Doucet 137 132 -0.037 Mean 413 407 0.020 LOW NLem 288 254 -0.126 Lemmon 43 27 -0.465 Manitou 393 322 -0.199 Guano 42 31 -0.304 NEBathe 143 234 0.492 Mean 182 174 -0.120

Figures

O ONTARI

BEC QUE [_ LOW [_NChan ELO Minnesota [_

k sin Yor Wiscon New n Michiga

nia sylva Penn

Ohio lan Mary of C t ict

Figure 3.1 Location of the 3 geographically separated Double-crested cormorant breeding areas sampled for population characteristics during 2006 - 2007. LOW = Lake of the Woods, NChan = North Channel of Lake Huron, ELO = Eastern Lake Ontario.

Fledge Rate for Each Region by Year

2.5

2006 1.5 2007

1 Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge

0.5

0 LOW NChan ELO

Figure 3.2 Double-crested cormorant fledge rate (chicks fledged per nest) from 3 geographically separated regions across the southern border of Ontario, summers 2006 – 2007. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. Bar represents the mean with upper and lower confidence intervals.

Eastern Lake Ontario

3.0 2.5 2.5 2.3 2.2 2.1 2.0 1.6 2006 1.5 2007 0.9 1.0

Fledge (chicks/nest) Rate 0.5 N/A N/A 0.0 Pigeon SBonnet Snake WBro

Figure 3.3 Double-crested cormorant fledge rate (chicks fledged per nest) by island, in Eastern Lake Ontario, summers 2006 – 2007. SBonnet = Scotch Bonnet, WBro = West Brothers Island.

North Channel

2.5 2.3

2.0

1.5 1.5 1.2 2006 1.1 1.01.0 1.0 2007 1.0 0.8 0.6 0.5

Fledge (chicks/nest)Rate 0.5 0.1 N/A N/A 0.0 N/A Doucet Fortin Hurburt Ivor MGrant WCousins West

Figure 3.4 Double-crested cormorant fledge rate (chicks fledged per nest) by island, in the North Channel of Lake Huron, summers 2006 – 2007. MGrant = Middle Grant Island, WCousins = West Cousins Island.

Lake of the Woods

5.0 4.5 4.3 4.0 3.5 3.0 2006 2.5 2.3 2007 1.7 2.0 1.5 1.4 1.5 1.2 1.1 1.2 1.0

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 0.3 0.5 0.0 0.0 Guano Lemmon Manitou NEBathe NLem

Figure 3.5 Double-crested cormorant fledge rate (chicks fledged per nest) by island, in Lake of the Woods, Ontario, summers 2006 – 2007. NEBathe = Island Northeast of Bathe Island, NLem = Island North of Lemmon Island.

Fledge Rate: Sick vs. Not Sick

2.5

1.5

0.5 Fledge(chicks/nest) Rate

0 sick not sick

Figure 3.6 Double-crested cormorant fledge rate (chicks fledged per nest) separated by the presence of disease, all three breeding regions of Ontario combined, summers 2006 – 2007. Bar represents the mean with upper and lower confidence intervals.

Sick vs. Not Sick by Island

3.0

2.5 2.5 2.3 2.2

2.0 1.6 sick 1.5 1.2 not sick 0.9 1.0

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 0.5 0.3 0.0N/A 0.0 Guano Pigeon SBonnet Snake

Figure 3.7 Double-crested cormorant fledge rate (chicks fledged per nest) separated by the presence of disease, and broken down by island, summers 2006 – 2007.

4.5

3.5

2.5

2 Fledge Rate (chicks/nest) Fledge Rate 1.5

0.5

0 0 200 400 600 800 1000 1200 1400 1600 1800 No. of DCCO Nests

Figure 3.8 Relationship between numbers of Double-crested cormorant (DCCO) nests and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.28, P = 0.16.

2.5

1.5

Fledge Rate (chicks/nest) 1

0.5

0 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 DCCO Nest Density (nests/ha)

Figure 3.9 Relationship between the density (number of nests/ha) of Double-crested cormorant (DCCO) nests present on the island and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.27, P = 0.20.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 102030405060708090100 % total veg. (veg/island)

Figure 3.10 Relationship between the percentages of total vegetation present on the Double-crested cormorant colony island and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.14, P = 0.55.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 00.511.522.533.54 Island Size (ha)

Figure 3.11 Relationship between the Double-crested cormorant colony island sizes and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.09, P = 0.67.

2.5

1.5

Fledge Rate (chicks/nest) 1

0.5

0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 Colony Size (ha)

Figure 3.12 Relationship between the Double-crested cormorant colony sizes and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.51, P = 0.01.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 10 15 20 25 30 35 40 Avg nest height (cm)

Figure 3.13 Relationship between the average Double-crested cormorant nest height and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.29, P = 0.31.

2.5

1.5

Fledge Rate (chicks/nest) Fledge (chicks/nest) Rate 1

0.5

0 65 67 69 71 73 75 77 79 81 83 85 Nest Dist. Between (cm)

Figure 3.14 Relationship between the average distance between Double-crested cormorant nests and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.33, P = 0.35.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 500 1000 1500 2000 2500 3000 Max Gull

Figure 3.15 Relationship between the maximum numbers of gulls present on the Double- crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.77, P = 0.04.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 500 1000 1500 2000 2500 3000 3500 4000 4500 Max Gull Density (gulls/ha)

Figure 3.16 Relationship between the maximum density of gulls (maximum number of gulls/island size) present on the Double-crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.82, P = 0.02.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 500 1000 1500 2000 2500 3000 Med. Gull

Figure 3.17 Relationship between the median numbers of gulls present on the Double- crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.73, P = 0.06.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 500 1000 1500 2000 2500 3000 3500 4000 4500 Med. Gull Density (gulls/ha)

Figure 3.18 Relationship between the median density of gulls (median number of gulls/island size) present on the Double-crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.76, P = 0.05.

2.5

1.5

Fledge Rate (Chicks/nest) (Chicks/nest) Rate Fledge 1

0.5

0 0 100 200 300 400 500 600 700 800 Gull Nests

Figure 3.19 Relationship between number of gull nests present on the Double-crested cormorant colony island and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.30, P = 0.41.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 200 400 600 800 1000 1200 Gull Nest Density (gulls/ha)

Figure 3.20 Relationship between the density of gull nests present (number of nests/island size) on the Double-crested cormorant colony islands and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.28, P = 0.43.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 5 10 15 20 25 30 35 40 45 Gull Nests w/in 0-5 m

Figure 3.21 Relationship between the number of gull nests present within a 0 – 5 m radius of the Double-crested cormorant colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.33, P = 0.38.

2.5

1.5

Fledge Rate (chicks/nest) Rate Fledge 1

0.5

0 0 102030405060708090100 Gull Nests w/in 5-10 m

Figure 3.22 Relationship between the number of gull nests present within a 5 – 10 m radius of the Double-crested cormorant colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.28, P = 0.54.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 200 400 600 800 1000 1200 1400 Max DCCO

Figure 3.23 Relationship between the maximum numbers of adult Double-crested cormorants (DCCO) present in the colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.49, P = 0.32.

2.5

1.5

Fledge Rate (chicks/nest) Fledge (chicks/nest) Rate 1

0.5

0 0 1000 2000 3000 4000 5000 6000 Max DCCO Density (DCCO/ha)

Figure 3.24 Relationship between the maximum density (maximum number of adults/island size) of adult Double-crested cormorants (DCCO) present in the colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = -0.10, P = 0.86.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 200 400 600 800 1000 1200 1400 Med. DCCO

Figure 3.25 Relationship between the median numbers of adult Double-crested cormorants (DCCO) present in the colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.72, P = 0.11.

2.5

1.5

Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1

0.5

0 0 200 400 600 800 1000 1200 1400 Med. DCCO Density (DCCO/ha)

Figure 3.26 Relationship between the median density (median number of adults/island size) of adult Double-crested cormorants (DCCO) present in the colony and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.26, P = 0.62.

4.5

3.5

2.5

2 Fledge Rate (chicks/nest) (chicks/nest) Rate Fledge 1.5

0.5

0 1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9 3.1 3.3 3.5 Clutch Size (avg # eggs/nest)

Figure 3.27 Relationship between Double-crested cormorant clutch size and fledge rate (chicks fledged per nest), across Ontario for summers 2006 – 2007. Pearson’s r = 0.01, P = 0.96.

CHAPTER 4

POPULATION PARAMETERS SUCH AS SURVIVAL, RECRUITMENT, AGE AT

FIRST BREEDING AND RATE OF CHANGE FOR THE INTERIOR

DOUBLE-CRESTED CORMORANT

Abstract

Information is lacking about key demographic parameters for the Interior

metapopulation of Double-crested cormorants (Phalacrocorax auritus). Three geographically distinct breeding areas across the southern border of Ontario

[Lake of the Woods (LOW), North Channel of Lake Huron (NChan), and Eastern

Lake Ontario (ELO)] were selected to study cormorant population parameters.

Beginning in 2000 for ELO and in 2002 for LOW and NChan, over 11,000 pre- fledged cormorants were color banded. During the breeding seasons of 2000 through 2007 in ELO and 2006 and 2007 in LOW, data from re-observation of uniquely banded cormorants were collected. In ELO, 2% of the breeding population are age 1, 26% are age 2, and 72% are age 3 and older. In LOW, zero birds were observed breeding their first year, 22% of the breeding population are age 2 and 78% are age 3 and older. Survival estimates indicate

<20% survival for first year birds, increasing to >80% after the second year.

Elasticity analysis revealed a 50% reduction in adult survival will reduce the

population’s finite rate of increase (λ) by 25% for one time step. A 100%

reduction in fecundity resulted in a 12 – 15% reduction in λ for one time step. A

combined 50% reduction in adult survival and 100% reduction in fecundity resulted in a 41 – 42% reduction in λ for one time step. The information obtained

in this study revealed cormorant metapopulation dynamics. These models were

used to develop management strategies for reducing cormorant impacts to

commercial and natural resources.

Introduction

Double-crested cormorants (Phalacrocorax auritus, hereafter termed

cormorant) first began nesting in the Great Lakes between 1913 and 1920,

slowly increasing their breeding numbers to approximately 900 pairs by 1950

(Weseloh and Ewins 1994, Weseloh et al. 1995). Beginning in the mid-1950s,

cormorant reproductive success was diminished severely primarily from

widespread contamination of the Great Lakes by organochlorine compounds

(e.g., PCBs, DDT, DDE), causing severe thinning of eggshells; resulting in

reproductive failure (Hatch and Weseloh 1999). Human persecution, namely

fishermen destroying nests, eggs, and adults also was attributed to cormorant

population suppression (Hatch and Weseloh 1999). During the years of 1954 to

1977, not a single cormorant was known to have fledged from any of the colonies

in Lake Ontario (Price and Weseloh 1986).

Since the late 1970s, cormorant breeding populations have increased throughout much of their breeding range at a rate of 29% annually; from 89 nests in 1970 to over 38,000 nests in 1991 (Weseloh and Ewins 1994, Weseloh et al.

1995, Glahn et al. 1999, Tyson et al. 1999, Hatch and Weseloh 1999).

The most recent population estimate for Double-crested cormorants across North America, including breeding and non-breeding birds, was conservatively estimated at 1,000,000 birds; however, this number may be closer to 2,000,000 (Hatch 1995, Tyson et al. 1999). As cormorant populations have increased, concerns have been mounting about the potential negative effects to vegetation, adjoining colonial nesting waterbird species, and farmed, as well as, wild fish stocks in North America (Weseloh and Ewins 1994, Bèdard et al. 1995,

Nettleship and Duffy 1995, Glahn et al. 2002, Cuthbert et al. 2002).

A major obstacle influencing management decisions is that little is known

about cormorant population dynamics such as age- and gender-specific survival,

fecundity, and immigration and emigration between colonies (Nettleship and

Duffy 1995, Hatch and Weseloh 1999, Tobin 1999, Blackwell et al. 2002).

Demographics on a large spatial scale have not been examined and a 80

comprehensive life table has yet to be constructed (Hatch and Weseloh 1999).

Various interest groups are seeking ecologically sound strategies for dealing with the effects of burgeoning cormorant populations on local fisheries, other wildlife species, and vulnerable island habitats.

Recent reviews of the literature have indicated there is a lack of reliable information with which to analyze population changes, evaluate management

efforts, and predict future population trends (Nettleship and Duffy 1995, Tobin

1999, Hanisch 2003). This study was designed to estimate demographic

parameters for 3 cormorant sub-populations of the Interior metapopulation. The

objective of this study is to develop population models that can be used for

adaptive management strategies to reduce cormorant impacts to commercial and

natural resources.

Methods

Study sites

Three geographically distinct breeding areas across the southern border

of Ontario were selected for empirical measures of variation in population characteristics (Figure 4.1). The study sites included: Lake of the Woods

(LOW), near Kenora, in the southwestern corner of Ontario (49.663, -94.507);

North Channel of Lake Huron (NChan), near Blind River, in south-central Ontario

(46.108, -83.026); and Eastern Lake Ontario (ELO), near Kingston, in the far

southeastern corner of Ontario (44.191, -76.543). Each of these geographically

distinct areas consisted of ground nesting cormorant colonies on a series of

small islands within approximately 15 km of the adjacent city. The islands were comprised of granite slabs and/or outcroppings ranging in size from 0.2 ha to 3

ha. These areas were chosen for this study due to their geographic location,

logistics, and nest placement on the ground. The Lake of the Woods area

comprised 5 islands: Manitou Island; Lemon Island; Island North of Lemon

Island; Guano Rock; and Island Northeast of Bathe Island. The North Channel

area was comprised of 7 islands: the 2 largest colonies on West Island and

Middle Grant Island. The Eastern Lake Ontario area was comprised of 4 islands:

Snake Island; Pigeon Island; West Brothers Island; and Scotch Bonnet Island.

Banding

Beginning in 2000 for ELO and in 2002 for LOW and NChan, over 11,000

pre-fledged cormorants have been color banded by the US Department of

Agriculture, Wildlife Services, National Wildlife Research Center (NWRC). In

ELO, mass banding has been a joint endeavor between the Canadian Wildlife

Service (CWS) and NWRC. Each year during June and July, crèches of

flightless young cormorants that appeared healthy and close to fledging were

rounded up, individual birds were pulled out of the crèche, banded, and then

immediately released back into the colony.

Each cormorant was double banded with a uniquely numbered US

Geological Survey, Biological Research Division (USGS/BRD) Bird Banding Lab

metal band and a unique alpha-coded color plastic leg band. These bands were

field readable and allowed for quick identification of the bird’s banding site and

year. A total of 150 to 1,200 pre-fledged cormorants were banded per region per

year (Tables 4.1, 4.2, 4.3). Banding effort was distributed among the islands

according to colony size with larger colonies receiving most of the effort. At the

end of each breeding season, each island where mass banding occurred was

searched visually and/or with a metal detector to collect any bands off young

cormorants that died before leaving the colony.

Resighting

Resighting was done by observers scanning the legs of cormorants with

binoculars and/or a spotting scope, looking for and reading color band alpha-

codes. Observers would either walk through the colony or resight from a semi-

permanent blind erected before the breeding season began. Blinds were located on Island North of Lemmon Island (NLem) in LOW and Snake Island in ELO.

Because the alphanumeric-coded, colored leg band of each cormorant is unique, the exact age and natal colony of each resighted bird can be determined.

In LOW during 2006 and 2007, observers systematically visited NLem

once a month over the course of the breeding season; the first visit during nest construction and initial laying (May), the second visit during mid-incubation

(June), the third visit just before chick fledging (July), and the fourth visit after

fledging at the end of the season (Sept). In 2005, resighting was done the 2

days prior to banding in July. In 2006, observation of the colony was conducted

for consecutive 24-hours each visit, to search for color-marked cormorants (the

hours during which it was too dark to read bands have been omitted from the

total count of observation hours). In 2007, observations were changed to

consecutive 24-daylight-hours (Table 4.1).

In ELO resighting effort was a joint endeavor between the CWS and the

NWRC. In the initial years, the CWS would visit cormorant colonies while

conducting gull toxicology research and collect band resight information

serendipitously while collecting gull data. The observation blind was first erected

on Snake Island in 2004. In 2004 and 2005, the NWRC augmented CWS data

by resighting the 2 days prior to banding; for 6 to 8 hours at a time. In 2006 and

2007, observers systematically visited Snake Island once monthly during the

breeding season; the first visit during mid-incubation (May), the second visit just

before chick fledging (June), the third visit after fledging (July), and the fourth visit

at the end of the season (Sept). In 2006 and 2007, observation of the colony

was conducted comparable to that of LOW (Table 4.3).

Reproduction

Western and upper Great Lakes cormorant colonies (LOW and NChan)

initiate nesting about 2 – 3 weeks later than cormorants in the eastern and lower

Great Lakes (ELO; Ewins et al. 1995). During colony observations, a banded bird was considered breeding if it was seen defending territory, bringing nesting

material to a mate, nest building, and/or incubating. Breeding statistics were

calculated as a percentage of the breeding birds and as a breeding percentage

of the total number of banded birds seen for each age class (Table 4.4).

Cormorants are monomorphic; therefore, the gender of the observed banded

bird, as well as colony gender ratios, were not attainable.

Chick growth is rapid until the individual reaches the fledging stage

(averaging 35 to 40 days old), upon which the growth rate greatly declines (Dunn

1975). Fledglings with ≤15 mm of the primary feather sheath present (Chastant

et al. In Review) were used to estimate fledge rates. A technique modified from

Weseloh et al. (1995), was used to estimate island-specific fledge rate (IFR –

number of chicks produced/nest/island) with the following equation:

F IFR = − FnTn

The total count of fledglings on the island (F) was divided by the total nest

count (Tn) minus the “full” nest count (Fn - nests containing eggs and/or naked

young; full nests are considered to be too late in the breeding season to

contribute to the island fledge rate). A census of all nests and fledglings in the

colonies, using direct observation/count, was conducted during the fledging stage

of chick development.

Survival estimates

Survival and site fidelity for banded cohorts was estimated with Program

MARK (White and Burnham 1999). In LOW and ELO, the Burnham joint live- encounter dead-recovery model (Burnham 1993) was used. The Burnham

model provides the following parameterization: survival (S), probability that a

band from a dead bird is recovered (r), probability of a live bird being resighted

and the band read (p), and site fidelity (F). Due to the variability of resighting

effort, only time-specific p models were considered. Because there was no

resighting done during the years of 2003 and 2004 in LOW and 2003 in ELO,

those parameters were fixed to zero for all of the models in the model set. For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time- specific models for both r and F were also considered. Although resighting was done throughout the breeding season, time of banding (June = ELO, July =

LOW) was used as the anniversary date.

No resighting was done in NChan; therefore, the Seber (Seber 1970) and

Brownie (Brownie et al. 1985) dead-recovery models were used. Seber model provides the following parameterization: survival (S) and probability that a band from a dead bird is reported (r). For survival, models with time-specific survival

(t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for r also were considered.

Brownie model provides the following parameterization: survival (S) and 86

probability that a band from a dead bird is recovered (f). For survival, models

with time-specific survival (t), constant survival (-), and two (a2), three (a3), and

four (a4) age classes were considered. Constant and time-specific models for f also were considered. The anniversary date was set at the time of banding in

July each year for both model types.

For each location, an exhaustive model set was chosen to avoid any loss of information (LOW = 20 models, Table 4.5; NChan = 8 models, Tables 4.6, 4.7;

ELO = 20 models, Tables 4.8, 4.9, 4.10). A goodness-of-fit test was run on the saturated model and then all models were adjusted for over-dispersion using c- hat. Selection among models for survival parameter estimation was performed with Quasi Akaike’s Information Criterion (QAICc) based on information-theoretic methods (Burnham and Anderson 2002). Only the models with the least QAICc values and a ΔQAIC of ≤2 were considered the best models to approximate the data, given the set of models considered, and the best models were averaged together.

Population models

For each region, stage-specific matrix models of the female segment of the Interior cormorant metapopulation were constructed in an Excel spreadsheet

and analyzed with the PopTools application (Table 4.11, 4.12, 4.13). The models

were 4 x 4 grids of stage-classified matrices (Leslie 1945, Lefkovitch 1965)

based on the estimates of survival, pooled together when applicable, and

fecundity. Breeding was considered to begin at the age of 3 (van der Veen 1973)

for model simplification. Island-specific fledge rates from 2006 and 2007 were

averaged for each region, divided by 2 to account for an assumed 50:50 sex

ratio, and then used as a constant fecundity rate. Immigration and emigration

were considered equal and therefore had no influence on the models.

Cormorants were grouped into 4 stages, with the first 3 stages age-

specific. The first age class was young of the year (YOY) surviving to the next

breeding season the following year. The second and third age classes were

birds aged 1 and 2 surviving to the next breeding season the following year. The

fourth age class was comprised of birds aged ≥3. In LOW, survival estimates

were time-specific; therefore, ages 3, 4, and 5 were averaged together to

produce the fourth age class. Similar to Blackwell et al. (2002), the decision to

pool the fourth age class was influenced by Program MARK’s preferential QAIC

ranking of models with 3 and 4 age classes.

Results

Age at first breeding

A total of 150 cormorants were recorded as breeding out of 650 banded

cormorants observed during the 2006 and 2007 breeding seasons (41 out of 238

in LOW and 109 out of 412 in ELO; Table 4.4). In LOW, no marked birds were

observed breeding their first year, 22% of the breeding population were age 2

and 78% were age 3 and older. In ELO, 2% of the breeding population were age

1, 26% were age 2, and 72% were age 3 and older.

Lake of the Woods

A total of 94 color banded cormorants were observed in 2006 and 144 were observed in 2007. Based on ΔQAICc values, the 2 models with the best fit,

model 1 {S(t)p(t)r(t)F(-)} and model 2 {S(t)p(t)r(-)F(t)} were model averaged

(Table 4.14). Although model 1 had the least QAICc score, precision of the survival estimates was unacceptable (Figure 4.2). Survival estimates were estimated with model 2 only and were 17% for the first year, 94% for the second year, and 83% for ≥3 years (Figure 4.3). Elasticity analysis of the Lefkovitch matrix reveals that adult survival (aged ≥3) is the most sensitive parameter

(Table 4.20), and a 50% reduction in adult survival would reduce the population’s finite rate of increase (λ) by 25% for one time step. A 100% reduction in

fecundity results in only a 12% reduction in λ for one time step. Combining a

50% reduction in adult survival and 100% reduction in fecundity would result in a

42% reduction in λ for one time step. The intrinsic rate of population increase (r) was -0.05242 with a generation time of 10.08 years (Table 4.21).

North Channel of Lake Huron

A total of 319 color bands have been recovered since 2002. Based on the

Seber model ΔQAICc values, the 3 models with the best fit, model 1 {S(3a)r(-)}, model 2 {S(2a)r(-)}, and model 3 {S(4a)r(-)} were model averaged (Table 4.15).

Survival estimates from the model averaged Seber dead-recovery models were

66% for the first year, 85% for the second year, and 88% for ≥3 years (Figure

4.4). Based on the Brownie model ΔQAICc values, the 2 models with the best fit

for the data set, model 1 {S(2a)f(-)}, and model 2 {S(3a)f(-)} were model

averaged (Table 4.16). Survival estimates from the model averaged Brownie

dead-recovery models were 23% for the first year, 59% for the second year, and

82% for ≥3 years (Figure 4.5). Elasticity analysis of the Lefkovitch matrix reveals

that adult survival (aged ≥3) is the most sensitive parameter (Table 4.20), and a

50% reduction in adult survival would reduce the population’s finite rate of

increase (λ) by 25% for one time step. A 100% reduction in fecundity results in

only a 13% reduction in λ for one time step. Combining a 50% reduction in adult

survival and 100% reduction in fecundity would result in a 42% reduction in λ for

one time step. The intrinsic rate of population increase (r) was -0.01468 with a

generation time of 9.94 years (Table 4.21).

Eastern Lake Ontario

A total of 951 color banded cormorants have been observed and 548 have

been recovered since 2000. Based on ΔQAICc values when analyzing the CWS

(white) band data, the 3 models with the best fit for the data set, model 1

{S(3a)p(t)r(t)F(-)}, model 2 {S(2a)p(t)r(t)F(-)}, and model 3 {S(4a)p(t)r(t)F(-)} were model averaged (Table 4.17). The model averaged survival estimates were 19% for the first year, 79% for the second year, and 88% for ≥3 years (Figure 4.6).

Based on ΔQAICc values when analyzing the NWRC (green) band data, the 3 models with the best fit for the data set, model 1 {S(a2)p(t)r(t)F(t)}, model 2

{S(a3)p(t)r(t)F(t)}, and model 3 {S(a2)p(t)r(t)F(-)} were model averaged (Table

4.18). The model averaged survival estimates were 23% for the first year and

78% for ≥2 years (Figure 4.7).

Based on ΔQAICc values when analyzing the NWRC (green) and the

CWS (white) band data combined, the 2 models with the best fit for the data set, model 1 {S(a2)p(t)r(t)F(-)} and model 2 {S(a3)p(t)r(t)F(-)} were model averaged

(Table 4.19). The model averaged survival estimates were 19% for the first year,

79% for the second year, and 81% for ≥3 years (Figure 4.8). Elasticity analysis of the Lefkovitch matrix reveals that adult survival (aged ≥3) was the most sensitive parameter (Table 4.20), and a 50% reduction in adult survival would reduce the population’s finite rate of increase (λ) by 25% for one time step. A

100% reduction in fecundity would result in only a 15% reduction in λ for one time step. Combining a 50% reduction in adult survival and 100% reduction in fecundity would result in a 41% reduction in λ for one time step. The intrinsic rate of increase (r) was -0.02732 with a generation time of 9.11 years (Table 4.21).

Discussion

The survival estimates produced in Program MARK are similar for each

age class in each region throughout the breeding range of the Interior Double-

crested cormorant (Figure 4.9). Although a Burnham joint encounter model was

used in LOW and ELO, I was unable to combine the data collected from both

regions due to specific model assumptions. In LOW, no resighting was done in

2003 or 2004, thus those parameters were set to zero; in ELO, resighting was

done annually. The dead recovery data collected in NChan differed from LOW

and ELO. Therefore it was inappropriate to compare different model types with

different data types using AICc.

Dead recovery models in Program MARK require data from birds banded

as adults as well as birds banded as YOY to estimate survival. Only YOY were

banded during this project; therefore, the models developed for NChan violate

this requirement. Both the Seber and Brownie models were made for accuracy

assessment and regional comparison and the survival estimates should be used

with caution.

This study’s survival estimates were similar to Ludwig (1984) and van der

Veen’s (1973) survival estimates of 30-35% for YOY cormorants and 85% for birds aged 2 and older. However, van der Veen (1973) calculated a population

projection of an 8.4% increase per year. This differs from the negative rate of

increase in all 3 breeding regions from this study. When Bèdard et al. (1995: 80)

used van der Veen’s survival estimates, preliminary modeling “proved impossible

to maintain, let alone generate growth, in a population with such mortality levels.”

Bèdard et al. (1995) adjusted the YOY survival rate to 50% for the predicted

number of breeding adults to coincide with actual census figures. Perhaps this

explains my negative population projection; my survival estimates were too low. 92

Bèdard’s adjusted survival rates more closely resemble Duerr’s (2007) apparent survival estimates of 42% for YOY, 77% for ‘subadults’ aged 1 and 2, and 82%

for adults age 3 and older, and Blackwell et al. (2002) survival estimates of 50% for YOY and 88% for adult survival.

The general trend in the data revealed that cormorants in ELO bred at an earlier age than in LOW. Perhaps there is a regional gradient or a difference between metapopulations that might be the source of variation. The breeding

estimates found in this study were less than van der Veen (1973) who calculated

that 3.7% of cormorants bred their first year, 17.5% at age 2, and 98.4% at age 3

on Mandarte Island, British Columbia. They also are less than Duerr’s (2007)

breeding percentages of 26-30% for 2 year-olds and 97% for cormorants aged 3

and older in Lake Champlain. The method for calculating the breeding percentages varied between studies; nevertheless, I believe my breeding estimates were low due to the nature of collection. The main objective during colony observation was to record presence of banded birds. If a bird was breeding was opportunistically recorded. Once a banded bird was identified, it was only observed for a few minutes, if the bird did not quickly display any signs of breeding it was not recorded as such.

The parameters used in the matrix models were conservative. Similar to

Blackwell et al. (2002), fecundity values of ≤1 fledgling per nest were used.

Researcher presence during this study likely had a significant impact on

cormorant fledge rate due to increased disturbance and resultant gull 93

depredation (Kury and Gochfeld 1975, Ellison and Cleary 1978). Furthermore, I specified that breeding initially occurs at 3 years of age whereas the data showed that a proportion of the birds did breed in their second year. Blackwell et al.

(2002) models actually adjusted for this proportion, likely explaining why their projections differed from my results. The models also were simplified by assuming no immigration or emigration even though it was likely that some occurred. When dealing with a dispersive species like cormorants, survival estimates suffer from an unknown bias due to permanent emigration away from the study area (Frederiksen and Bregnballe 2000a).

Previous studies also have concluded that a joint reduction in adult survival and fecundity would have the greatest efficacy for reducing population growth. In response to rising concerns for endemic island vegetation, a five-year management plan was introduced in the St. Lawrence River estuary in 1989 with the goal of reducing cormorant populations to 10,000 breeding pairs. Initial modeling predicted that a combination of oiling 75% of all ground nests and culling 2,000 tree-nesting adults per year would reduce the population over a five-year period (Bèdard et al. 1995). Monitoring during the program however, revealed greater than anticipated declines and culling was stopped after 4 years.

While modeling different combinations of culling and egg oiling scenarios,

Frederiksen et al. (2001) and Smith et al. (2008) found that density-dependent mechanisms played a much more significant role in the efficacy of management strategies for the Great cormorant (P. carbo) in Europe than first realized. If a 94

population is at carrying capacity (density-dependence) the effects of

management actions would be much more pronounced. The negative population

growth estimates reported in this study may be due to cormorants surpassing

carrying capacity and thus adjusting back to a more ‘biologically acceptable’

level. Similarly, Ridgeway et al. (2006) stated that cormorant nesting colonies in

the North Channel and Georgian Bay of Lake Huron exhibit density-dependent

population regulation. The results of this study cannot definitively determine if

density-dependence has been observed, further research is needed.

Bèdard et al. (1995: 84) stated that egg-oiling was “the most effective tool

when large scale intervention is required” and culling should be considered as a

last resort. Their model simulations revealed that by lowering recruitment by

70% for 5 years resulted in a near disappearance of the subadult birds (Bèdard

et al. 1995). Shonk et al. (2004) investigated the efficiency of egg oiling during

different weeks of incubation in Double-crested cormorant colonies. They found

that spraying techniques were 95-98% effective at preventing hatching when

applied to a colony with a maximum number of eggs present; 4 weeks after the

first egg has been laid, when most nests have reached full clutch size. Egg oiling

may be a more socially acceptable method of control than culling; however,

disturbance to sympatric nesting bird species also must be considered when

using any of the techniques mentioned. Depending on the situation at hand,

culling produces an immediate response, even though oiling activities are

effective, the results may take several years to appear. 95

Future research

Based upon the results of this study, further investigation is needed to

determine the cause of the apparent population decline. Continuing color

banding efforts would improve matrix models by adding a post-breeding age

class, complete with survival estimates. Also to complete a comprehensive life

table for the entire breeding range of the Interior Double-crested cormorant, color

banding efforts should continue on this large spatial scale for another 10 to 15

years, to encompass the bird’s lifespan. Frederiksen and Bregnballe (2000a,

2000b), Ridgeway et al. (2006), and Smith et al. (2008) had roughly 20 years

worth of data to support their claims of density dependence. I agree with Smith et

al.’s (2008) recommendation that Adaptive Resource Management (ARM) be

practiced with yearly monitoring of the controlled population to ensure that

appropriate management decisions are made to avoid over harvest.

Literature cited

Bèdard, J., A. Nadeau, and M. Lepage. 1995. Double-crested cormorant culling in the St. Lawrence River Estuary. Colonial Waterbirds 18 (Spec. Pub. 1):78-85.

Blackwell, B. F., M. A. Stapanian, and D. V. C. Weseloh. 2002. Dynamics of the Double-crested cormorant population on Lake Ontario. Wildlife Society Bulletin 30:345-353.

Brownie, C., D. R. Anderson, K. P. Burnham, and D. S. Robson. 1985. Statistical inference from band recovery data - a handbook. 2 Ed. U. S. Department of Interior, Fish and Wildlife Service Resource Publication 156. 305 pp.

Burnham, K. P. 1993. A theory for combined analysis of ring recovery and recapture data. Pages 199-213 in J. D. Lebreton and P. M. North, editors. Marked individuals in the study of bird populations. Birkhàuser Verlag, Basel, Switzerland.

Burnham, K. P. and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second edition. Springer-Verlag, New York, New York, USA.

Chastant, J. E., D. T. King, B. K. Strickland, and R. B. Minnis. In Review. Variation in eggs, chicks and adults throughout the breeding range of the Interior metapopulation of Double-crested cormorants (Phalacrocorax auritus). Symposium: Double-crested cormorants of the Great Lakes - St. Lawrence River Basin: recent studies, movements, and responses to management actions on their biology, ecology. International Association for Great Lakes Research 50th Annual Conference, Penn State University, University Park, PA. 28 May -1 June 2007. Waterbirds Special Publication 2008.

Cuthbert, F. J., L. R. Wires, and J. E. McKearnan. 2002. Potential impacts of nesting Double-crested cormorants on Great blue herons and Black- crowned night herons in the U.S. Great Lakes region. Journal of Great Lakes Research 28:145-154.

Duerr, A. E. 2007. Population dynamics, foraging ecology, and optimal management of Double-crested cormorants on Lake Champlain. Dissertation, University of Vermont, Burlington, USA.

Dunn, E. H. 1975. Growth, body components and energy content of nestling Double-crested cormorants. Condor 77:431-438.

Ellison L. N. and L. Cleary. 1978. Effects of human disturbance on breeding of Double-crested cormorants. Auk 95:510-517.

Frederiksen, M., and T. Bregnballe. 2000a. Evidence for density-dependent survival in adult cormorants from a combined analysis of recoveries and resighting. Journal of Animal Ecology 69:737-752.

Frederiksen, M., and T. Bregnballe. 2000b. Diagnosing a decline in return rate of 1-year-old cormorants: mortality, emigration or delayed return? Journal of Animal Ecology 69:753-761.

Frederiksen, M., J. D. Lebreton, and T. Bregnballe. 2001. The interplay between culling and density-dependence in the Great cormorant: a modeling approach. Journal of Applied Ecology 38:617-627.

Glahn, J. F., M. E. Tobin, and B. Harrel. 1999. Possible effects of catfish exploitation on overwinter body condition of Double-crested cormorants. Pages 107-113 in Tobin M. E., technical coordinator. Symposium on Double-crested cormorants: population status and management issues in the Midwest. US Department of Agriculture Tech. Bull. No.1879. Milwaukee, Wisconsin, USA.

Hatch, J. J. 1995. Changing populations of Double-crested cormorants. Colonial Waterbirds 18 (Spec. Pub. 1):8-24. 98

Kury, C. R. and M. Gochfeld. 1975. Human interference and gull predation in cormorant colonies. Biological Conservation 8:23-34.

Lefkovitch, L. P. 1965. The study of population growth in organisms grouped by stages. Biometrics 21:1-18.

Leslie, P. H. 1945. On the use of matrices in certain population mathematics. Biometrika 33:183-212.

Ludwig, J. P. 1984. Decline, resurgence and population dynamics of Michigan and Great Lakes Double-crested cormorants. Jack-Pine Warbler 62:92- 102.

Nettleship,D. N. and D. C. Duffy. 1995. The Double-crested cormorant: biology, conservation, and management. Colonial Waterbirds 18 (Spec. Pub. 1):1- 256.

Price, I. M., and D. V. Weseloh. 1986. Increased numbers and productivity of Double-crested cormorants, Phalacrocorax auritus, on Lake Ontario. Canadian Field-Naturalist 100:474-482.

Ridgeway, M. S., J. B. Pollard, and D. V. C. Weseloh. 2006. Density-dependent growth of Double-crested cormorant colonies on Lake Huron. Canadian Journal of Zoology 84:1409-1420.

Seber, G. A. F. 1970. Estimating time-specific survival and reporting rates for adult birds from band returns. Biometrika 57:313-318.

Shonk, K. A., S. D. Kevan, and D. V. Weseloh. 2004. The effects of oil spraying on eggs of Double-crested cormorants. The Environmentalist 24:119-124.

Smith, G. C., D. Parrott, and P. A. Robertson. 2008. Managing wildlife populations with uncertainty: cormorants Phalacrocorax carbo. Journal of Applied Ecology 45:1-9.

Tobin, M. E. 1999. Symposium on Double-crested cormorants: population status and management issues in the Midwest. U.S. Department of Agriculture Technical Bulletin No.1879. Milwaukee, Wisconsin, USA.

Tyson, L. A., J. L. Belant, F. C. Cuthbert, and D. V. Weseloh. 1999. Nesting populations of Double-crested cormorants in the United States and Canada. Pages 17-25 in M. E. Tobin, technical coordinator. Symposium on Double-crested cormorants: population status and management issues in the Midwest. US Department of Agriculture Technical Bulletin No.1879. Milwaukee, Wisconsin, USA. van der Veen, H. E. 1973. Some aspects of the breeding biology and demography of the Double-crested cormorants (Phalacrocorax auritus) of Mandarte Island. Ph.D. thesis, Zoologisch Laboratorium der Rijksuniversiteit te Groningen, Groningen.

Werner, S. J. and S. L. Hanisch. 2003. Status of Double-crested cormorant Phalacrocorax auritus research and management in North America. Vogelwelt 124, supplement: 369-374.

White, G. C. and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement: 120-138. .

100

Tables

Table 4.1 Summary (by year) of number of Double-crested cormorant bands deployed in Lake of the Woods, number of hours spent observing (Hours), during which part of the breeding season, and number of bands reported (Dead) for each cohort throughout the study.

Year Deployed Hours Season Dead 2002 697 - - 101 2003 751 - - 44 2004 647 - - 26 2005 608 21 Middle 49 2006 659 53 Entire 36 2007 400 72 Entire 19

Table 4.2 Summary (by year) of number of Double-crested cormorant bands deployed in the North Channel of Lake Huron and number of bands reported (Dead) for each cohort throughout the study.

Year Deployed Dead 2002 899 134 2003 181 28 2004 0 0 2005 376 47 2006 725 68 2007 374 42

Table 4.3 Summary (by year) of number of green (GN) Double-crested cormorant bands deployed by the U.S. Department of Agriculture, National Wildlife Research Center (NWRC), the number of white (WH) bands deployed in Eastern Lake Ontario by the Canadian Wildlife Service (CWS), number of hours spent observing (Hours), by which agency (Resight Observer), during which part of the breeding season, and number of bands reported (Dead) for each cohort throughout the study.

GN WH Resight GN WH Year Deployed Deployed Hours Observer Season Dead Dead 2000 0 220 - - - 0 15 2001 0 398 33 CWS End 0 16 2002 350 204 18 CWS Beginning 27 6 2003 499 196 10 CWS Beginning 42 4 2004 578 65 50 Both Entire 29 1 2005 699 204 46 Both Entire 94 6 2006 900 300 180 Both Entire 170 74 2007 324 179 146 Both Entire 33 7

101

Table 4.4 Breeding statistics by age class of banded Double-crested cormorants breeding in Lake of the Woods (LOW) and Eastern Lake Ontario (ELO). T = the percentage of birds classified as breeding out of the total number of banded birds seen. Number (n) of birds seen in each age class presented as a percentage of breeding birds (Breed %) and as a breeding percentage of total number of banded birds seen in each age class (Total %). Cormorants banded as young of the year by both the U.S. Department of Agriculture, National Wildlife Research Center (NWRC; green) and the Canadian Wildlife Service (CWS; white) since 2000. A total of 150 cormorants were recorded as breeding out of 650 banded cormorants observed during the 2006 and 2007 breeding seasons.

LOW ELO n Breed % Total % n Breed % Total % age 1 0 0.000 0.000 2 0.018 0.026 2 9 0.220 0.155 28 0.257 0.220 3 16 0.390 0.232 24 0.220 0.324 4 14 0.341 0.389 21 0.193 0.404 5 2 0.049 0.167 16 0.147 0.390 6 - - - 14 0.128 0.424 7 - - - 4 0.037 0.500 T 0.138 0.138 0.138 0.276 0.276 0.276

102

Table 4.5 Set of 20 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 4, considered in Program MARK with the Burnham joint live-encounter dead-recovery model for estimation of survival and fidelity of Double-crested cormorants in Lake of the Woods, banded as young of the year. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered.

QAICc Model Num. Model QAICc Δ QAICc Weights Likelihood Par QDeviance 1 {S(t)p(t)r(t)F(-)} 1119.043 0.000 0.560 1.000 15 65.832 2 {S(t)p(t)r(-)F(t)} 1120.804 1.761 0.232 0.415 14 69.608 3 {S(t)p(t)r(t)F(t)} 1122.295 3.252 0.110 0.197 18 63.033 4 {S(t)p(t)r(-)F(-)} 1122.551 3.509 0.097 0.173 11 77.394 5 {S(-)p(t)r(t)F(-)} 24444.710 23325.669 0.000 0.000 11 23399.550 6 {S(-)p(t)r(t)F(t)} 24449.420 23330.374 0.000 0.000 15 23396.210 7 {S(a4)p(t)r(t)F(-)} 24966.380 23847.340 0.000 0.000 14 23915.190 8 {S(a4)p(t)r(t)F(t)} 24973.790 23854.748 0.000 0.000 18 23914.530 9 {S(a4)p(t)r(-)F(-)} 24995.830 23876.785 0.000 0.000 9 23954.690 10 {S(a4)p(t)r(-)F(t)} 25003.070 23884.030 0.000 0.000 13 23953.890 11 {S(a3)p(t)r(t)F(-)} 43677.540 42558.501 0.000 0.000 13 42628.360 12 {S(a3)p(t)r(t)F(t)} 43685.210 42566.163 0.000 0.000 17 42627.960 13 {S(a3)p(t)r(-)F(-)} 43704.870 42585.823 0.000 0.000 7 42667.750 14 {S(a3)p(t)r(-)F(t)} 43710.540 42591.497 0.000 0.000 10 42667.390 15 {S(a2)p(t)r(t)F(-)} 55630.170 54511.123 0.000 0.000 12 54583.000 16 {S(a2)p(t)r(t)F(t)} 55635.650 54516.610 0.000 0.000 15 54582.440 17 {S(-)p(t)r(-)F(t)} 67246.600 66127.562 0.000 0.000 9 66205.470 18 {S(a2)p(t)r(-)F(-)} 96398.300 95279.258 0.000 0.000 6 95363.190 19 {S(a2)p(t)r(-)F(t)} 96405.620 95286.578 0.000 0.000 11 95360.470 20 {S(-)p(t)r(-)F(-)} 108233.500 107114.478 0.000 0.000 6 107198.400

103

Table 4.6 Set of 8 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 2, considered in Program MARK with the Seber dead- recovery model for estimation of survival of Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year. Seber model provides the following parameterization: survival (S) and probability that a band from a dead bird is reported (r). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for r were also considered.

QAICc Model Num. Model QAICc Δ QAICc Weights Likelihood Par QDeviance 1 {S(3a)r(-)} 1240.754 0.000 0.448 1.000 4 13.073 2 {S(2a)r(-)} 1241.337 0.584 0.335 0.747 3 15.662 3 {S(4a)r(-)} 1242.452 1.698 0.192 0.428 5 12.763 4 {S(3a)r(t)} 1247.974 7.220 0.012 0.027 9 10.238 5 {S(2a)r(t)} 1248.745 7.991 0.008 0.018 8 13.023 6 {S(4a)r(t)} 1249.976 9.222 0.004 0.010 10 10.224 7 {S(-)r(-)} 1255.057 14.303 0.000 0.001 2 31.387 8 {S(t)r(t)} 1255.513 14.759 0.000 0.001 10 15.761

Table 4.7 Set of 8 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 3.5, considered in Program MARK with the Brownie dead-recovery model for estimation of survival of Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year. Brownie model provides the following parameterization: survival (S) and probability that a band from a dead bird is recovered (f). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for f were also considered.

QAICc Model Num. Model QAICc Δ QAICc Weights Likelihood Par QDeviance 1 {S(2a)f(-)} 711.910 0.000 0.467 1.000 3 8.950 2 {S(3a)f(-)} 712.440 0.527 0.359 0.769 4 7.470 3 {S(4a)f(-)} 714.250 2.343 0.145 0.310 5 7.279 4 {S(-)f(-)} 718.890 6.981 0.014 0.031 2 17.935 5 {S(2a)f(t)} 720.450 8.539 0.007 0.014 8 7.442 6 {S(3a)f(t)} 720.850 8.934 0.005 0.012 9 5.823 7 {S(4a)f(t)} 722.860 10.950 0.002 0.004 10 5.823 8 {S(t)f(t)} 726.040 14.133 0.000 0.001 10 9.006

104

Table 4.8 Set of 20 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 2.5, considered in Program MARK with the Burnham joint live-encounter dead-recovery model for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by the Canadian Wildlife Service (white). Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered.

QAICc Model Num. Model QAICc Δ QAICc Weights Likelihood Par QDeviance 1 {S(3a)p(t)r(t)F(-)} 1128.065 0.000 0.434 1.000 19 169.183 2 {S(2a)p(t)r(t)F(-)} 1128.685 0.612 0.318 0.734 18 171.841 3 {S(4a)p(t)r(t)F(-)} 1129.422 1.357 0.220 0.507 20 168.500 4 {S(3a)p(t)r(t)F(t)} 1134.945 6.879 0.014 0.032 24 165.840 5 {S(2a)p(t)r(t)F(t)} 1136.147 8.081 0.008 0.018 23 169.092 6 {S(4a)p(t)r(t)F(t)} 1136.521 8.456 0.006 0.015 25 165.366 7 {S(3a)p(t)r(-)F(-)} 1177.573 49.507 0.000 0.000 12 232.915 8 {S(2a)p(t)r(-)F(-)} 1178.027 49.961 0.000 0.000 11 235.393 9 {S(4a)p(t)r(-)F(-)} 1178.487 50.421 0.000 0.000 13 231.803 10 {S(3a)p(t)r(-)F(t)} 1183.227 55.161 0.000 0.000 17 228.419 11 {S(2a)p(t)r(-)F(t)} 1184.289 56.223 0.000 0.000 16 231.515 12 {S(4a)p(t)r(-)F(t)} 1184.454 56.388 0.000 0.000 18 227.610 13 {S(t)p(t)r(t)F(-)} 1210.803 82.737 0.000 0.000 23 243.747 14 {S(t)p(t)r(t)F(t)} 1220.734 92.669 0.000 0.000 28 243.416 15 {S(-)p(t)r(t)F(-)} 1224.878 96.813 0.000 0.000 17 270.070 16 {S(-)p(t)r(t)F(t)} 1232.712 104.647 0.000 0.000 22 267.703 17 {S(t)p(t)r(-)F(-)} 1250.527 122.462 0.000 0.000 17 295.719 18 {S(t)p(t)r(-)F(t)} 1253.309 125.243 0.000 0.000 22 288.299 19 {S(-)p(t)r(-)F(-)} 1285.502 157.437 0.000 0.000 10 344.891 20 {S(-)p(t)r(-)F(t)} 1292.569 164.504 0.000 0.000 15 341.828

105

Table 4.9 Set of 20 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 4, considered in Program MARK with the Burnham joint live-encounter dead-recovery model for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by the U.S. Department of Agriculture, National Wildlife Research Center (green). Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered.

QAICc Model Num. Model QAICc Δ QAICc Weights Likelihood Par QDeviance 1 {S(a2)p(t)r(t)F(t)} 1308.966 0.000 0.484 1.000 17 60.536 2 {S(a3)p(t)r(t)F(t)} 1310.963 1.997 0.178 0.368 18 60.514 3 {S(a2)p(t)r(t)F(-)} 1311.101 2.135 0.167 0.344 14 68.723 4 {S(a3)p(t)r(t)F(-)} 1312.770 3.804 0.072 0.149 15 68.376 5 {S(a4)p(t)r(t)F(t)} 1312.785 3.819 0.072 0.148 19 60.315 6 {S(a4)p(t)r(t)F(-)} 1314.780 5.814 0.026 0.055 16 68.369 7 {S(a2)p(t)r(-)F(t)} 1337.054 28.088 0.000 0.000 12 98.706 8 {S(a3)p(t)r(-)F(t)} 1338.989 30.023 0.000 0.000 13 98.626 9 {S(a2)p(t)r(-)F(-)} 1339.708 30.742 0.000 0.000 9 107.395 10 {S(a4)p(t)r(-)F(t)} 1340.908 31.942 0.000 0.000 14 98.531 11 {S(a3)p(t)r(-)F(-)} 1341.220 32.254 0.000 0.000 10 106.897 12 {S(a4)p(t)r(-)F(-)} 1343.227 34.261 0.000 0.000 11 106.892 13 {S(-)p(t)r(t)F(-)} 1367.317 58.351 0.000 0.000 13 126.955 14 {S(t)p(t)r(t)F(-)} 1369.277 60.311 0.000 0.000 17 120.848 15 {S(-)p(t)r(t)F(t)} 1371.414 62.448 0.000 0.000 16 125.003 16 {S(t)p(t)r(t)F(t)} 1373.574 64.608 0.000 0.000 20 119.082 17 {S(t)p(t)r(-)F(-)} 1380.985 72.019 0.000 0.000 13 140.622 18 {S(t)p(t)r(-)F(t)} 1383.509 74.543 0.000 0.000 16 137.098 19 {S(-)p(t)r(-)F(-)} 1396.660 87.694 0.000 0.000 8 166.358 20 {S(-)p(t)r(-)F(t)} 1400.717 91.751 0.000 0.000 11 164.382

106

Table 4.10 Set of 20 models, based on Quasi Akaike’s Information Criterion (QAICc) adjusted with a c-hat estimation of 4, considered in Program MARK with the Burnham joint live-encounter dead-recovery model for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by both the U.S. Department of Agriculture, National Wildlife Research Center (green) and the Canadian Wildlife service (white). Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered.

QAICc Model Num. Model QAICc Δ QAICc Weights Likelihood Par QDeviance 1 {S(a2)p(t)r(t)F(-)} 2034.677 0.000 0.555 1.000 18 155.551 2 {S(a3)p(t)r(t)F(-)} 2035.878 1.201 0.304 0.549 19 154.738 3 {S(a4)p(t)r(t)F(-)} 2037.728 3.051 0.121 0.218 20 154.574 4 {S(a2)p(t)r(t)F(t)} 2042.632 7.955 0.010 0.019 23 153.432 5 {S(a3)p(t)r(t)F(t)} 2043.405 8.729 0.007 0.013 24 152.189 6 {S(a4)p(t)r(t)F(t)} 2045.139 10.462 0.003 0.005 25 151.904 7 {S(a2)p(t)r(-)F(-)} 2097.291 62.614 0.000 0.000 11 232.239 8 {S(a3)p(t)r(-)F(-)} 2098.645 63.968 0.000 0.000 12 231.584 9 {S(a4)p(t)r(-)F(-)} 2100.593 65.916 0.000 0.000 13 231.523 10 {S(a2)p(t)r(-)F(t)} 2104.294 69.617 0.000 0.000 16 229.192 11 {S(a3)p(t)r(-)F(t)} 2105.322 70.645 0.000 0.000 17 228.208 12 {S(a4)p(t)r(-)F(t)} 2107.205 72.528 0.000 0.000 18 228.079 13 {S(t)p(t)r(t)F(-)} 2162.094 127.417 0.000 0.000 23 272.894 14 {S(-)p(t)r(t)F(-)} 2171.540 136.863 0.000 0.000 17 294.426 15 {S(t)p(t)r(t)F(t)} 2172.185 137.508 0.000 0.000 28 272.894 16 {S(-)p(t)r(t)F(t)} 2181.610 146.933 0.000 0.000 22 294.426 17 {S(t)p(t)r(-)F(-)} 2188.929 154.252 0.000 0.000 17 311.816 18 {S(t)p(t)r(-)F(t)} 2197.926 163.249 0.000 0.000 22 310.742 19 {S(-)p(t)r(-)F(-)} 2238.402 203.726 0.000 0.000 10 375.358 20 {S(-)p(t)r(-)F(t)} 2248.448 213.771 0.000 0.000 15 375.358

107

Table 4.11 Stage-classified projection matrix for Double-crested cormorants in Lake of the Woods, Ontario. Cormorants were considered reproductively mature at age 3. Fecundity was estimated using fledge rates from the 2006 and 2007 breeding seasons, divided by two to account for an assumed 50:50 sex ratio. Survival estimates were generated in Program MARK from birds banded as young of the year since 2002. Cormorants were grouped into 4 stages, with the first 3 stages age-specific. The first age class is young of the year (YOY) surviving to the next breeding season the following year. The second and third age classes are birds aged 1 and 2 surviving to the next breeding season the following year. Survival estimates for ages 3, 4, and 5 were averaged together for the fourth age class, ≥3. First row represents fecundity, diagonal represents age class survival.

YOY 1 2 ≥3 0 0 0 0.740364 0.169126 0 0 0 0 0.944678 0 0 0 0 0.821443 0.835212

Table 4.12 Stage-classified projection matrix for Double-crested cormorants in the North Channel of Lake Huron. Cormorants were considered reproductively mature at age 3. Fecundity was estimated using fledge rates from the 2006 and 2007 breeding seasons, divided by two to account for an assumed 50:50 sex ratio. Survival estimates were generated in Program MARK from birds banded as young of the year since 2002. Cormorants were grouped into 4 stages, with the first 3 stages age-specific. The first age class is young of the year (YOY) surviving to the next breeding season the following year. The second and third age classes are birds aged 1 and 2 surviving to the next breeding season the following year. The fourth age class is comprised of birds aged ≥3. First row represents fecundity, diagonal represents age class survival.

YOY 1 2 ≥3 0 0 0 0.470667 0.452844 0 0 0 0 0.718035 0 0 0 0 0.849305 0.849599

108

Table 4.13 Stage-classified projection matrix for Double-crested cormorants in Eastern Lake Ontario. Cormorants were considered reproductively mature at age 3. Fecundity was estimated using fledge rates from the 2006 and 2007 breeding seasons, divided by two to account for an assumed 50:50 sex ratio. Survival estimates were generated in Program MARK from birds banded as young of the year since 2000. Cormorants were grouped into 4 stages, with the first 3 stages age- specific. The first age class is young of the year (YOY) surviving to the next breeding season the following year. The second and third age classes are birds aged 1 and 2 surviving to the next breeding season the following year. The fourth age class is comprised of birds aged ≥3. First row represents fecundity, diagonal represents age class survival.

YOY 1 2 ≥3 0 0 0 1.020812 0.204364000 0 0.789452 0 0 0 0 0.830068 0.824665

Table 4.14 Survival estimates from the top two Quasi Akaike’s Information Criterion (QAICc) ranked Burnham models and their weighted model average for Double-crested cormorants in Lake of the Woods, banded as young of the year (YOY). Age is in years. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered.

Model Age Estimate SE LCI UCI {S(t)p(t)r(t)F(-)} YOY 0.239 0.117 0.082 0.525 1 0.947 0.287 0.000 0.999 2 0.632 0.197 0.246 0.901 3 0.454 0.126 0.235 0.692 4 0.453 0.247 0.105 0.854 ≥5 0.102 0.000 0.102 0.102 {S(t)p(t)r(-)F(t)} YOY 0.169 0.077 0.065 0.372 1 0.945 0.048 0.741 0.990 2 0.821 0.081 0.608 0.932 3 0.844 0.071 0.654 0.939 4 0.780 0.092 0.553 0.910 ≥5 0.881 0.061 0.704 0.959 Average YOY 0.218 0.111 0.072 0.501 1 0.946 0.242 0.001 0.999 2 0.688 0.192 0.276 0.927 3 0.568 0.210 0.197 0.876 4 0.549 0.260 0.134 0.905 ≥5 0.330 0.357 0.021 0.921

109

Table 4.15 Survival estimates from the top three Quasi Akaike’s Information Criterion (QAICc) ranked Seber models and their weighted model average for Double- crested cormorants in the North Channel of Lake Huron, banded as young of the year (YOY). Age is in years. Seber model provides the following parameterization: survival (S) and probability that a band from a dead bird is reported (r). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for r were also considered.

Model Age Estimate SE LCI UCI {S(3a)r(-)} YOY 0.692 0.583 0.010 0.998 1 0.881 0.327 0.016 0.999 ≥2 0.944 0.187 0.016 0.999 {S(2a)r(-)} YOY 0.462 0.065 0.339 0.589 ≥1 0.726 0.087 0.529 0.862 {S(4a)r(-)} YOY 0.912 0.008 0.895 0.926 1 0.974 0.005 0.962 0.982 2 0.988 0.004 0.975 0.994 ≥3 0.991 0.003 0.984 0.995 Average YOY 0.656 0.429 0.044 0.988 1 0.846 0.246 0.120 0.996 2 0.878 0.176 0.224 0.994 ≥3 0.878 0.176 0.221 0.995

110

Table 4.16 Survival estimates from the top two Quasi Akaike’s Information Criterion (QAICc) ranked Brownie models and their weighted model average for Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year (YOY). Age is in years. Brownie model provides the following parameterization: survival (S) and probability that a band from a dead bird is recovered (f). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time- specific models for f were also considered.

Model Age Estimate SE LCI UCI {S(2a)f(-)} YOY 0.235 0.065 0.131 0.385 ≥1 0.726 0.115 0.460 0.892 {S(3a)f(-)} YOY 0.268 0.077 0.145 0.442 1 0.413 0.209 0.114 0.793 ≥2 0.944 0.247 0.002 0.999 Average YOY 0.249 0.073 0.134 0.416 1 0.590 0.225 0.188 0.899 ≥2 0.821 0.214 0.209 0.988

Table 4.17 Survival estimates from the top three Quasi Akaike’s Information Criterion (QAICc) ranked Burnham joint live-encounter dead-recovery models and their weighted model average for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year (YOY) by the Canadian Wildlife Service (white). Age is in years. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (- ), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered.

Model Age Estimate SE LCI UCI {S(3a)p(t)r(t)F(-)} YOY 0.192 0.031 0.139 0.260 1 0.764 0.078 0.581 0.883 ≥2 0.899 0.043 0.780 0.957 {S(2a)p(t)r(t)F(-)} YOY 0.179 0.027 0.132 0.239 ≥1 0.854 0.038 0.763 0.913 {S(4a)p(t)r(t)F(-)} YOY 0.188 0.031 0.135 0.255 1 0.760 0.079 0.576 0.880 2 0.946 0.056 0.669 0.993 ≥3 0.874 0.057 0.714 0.951 Average YOY 0.187 0.030 0.135 0.253 1 0.792 0.080 0.595 0.908 2 0.895 0.056 0.726 0.965 ≥3 0.879 0.049 0.746 0.947

111

Table 4.18 Survival estimates from the top three Quasi Akaike’s Information Criterion (QAICc) ranked Burnham joint live-encounter dead-recovery models and their weighted model average for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year (YOY) by the U.S. Department of Agriculture, National Wildlife Research Center (green). Age is in years. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (-), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered.

Model Age Estimate SE LCI UCI {S(a2)p(t)r(t)F(t)} YOY 0.236 0.045 0.159 0.334 ≥1 0.793 0.056 0.662 0.882 {S(a3)p(t)r(t)F(t)} YOY 0.234 0.046 0.157 0.335 1 0.797 0.063 0.647 0.894 ≥2 0.783 0.087 0.568 0.908 {S(a2)p(t)r(t)F(-)} YOY 0.223 0.043 0.149 0.319 ≥1 0.758 0.066 0.608 0.864 Average YOY 0.233 0.045 0.156 0.332 1 0.787 0.061 0.643 0.883 ≥2 0.784 0.067 0.625 0.887

Table 4.19 Survival estimates from the top two Quasi Akaike’s Information Criterion (QAICc) ranked Burnham joint live-encounter dead-recovery models and their weighted model average for estimation of survival of Double-crested cormorants in Eastern Lake Ontario, banded as young of the year (YOY) by both the U.S. Department of Agriculture, National Wildlife Research Center (green) and the Canadian Wildlife service (white). Age is in years. Burnham model provides the following parameterization: survival (S), probability of a live bird being resighted and the band read (p), probability that a band from a dead bird is recovered (r), and site fidelity (F). For survival, models with time-specific survival (t), constant survival (- ), and two (a2), three (a3), and four (a4) age classes were considered. Constant and time-specific models for both r and F were also considered.

Model Age Estimate SE LCI UCI {S(a2)p(t)r(t)F(-)} YOY 0.192 0.025 0.147 0.245 ≥1 0.801 0.038 0.716 0.865 {S(a3)p(t)r(t)F(-)} YOY 0.196 0.027 0.149 0.254 1 0.769 0.055 0.644 0.859 ≥2 0.831 0.049 0.714 0.907 Average YOY 0.193 0.026 0.148 0.249 1 0.789 0.047 0.682 0.868 ≥2 0.812 0.044 0.709 0.884

112

Table 4.20 Estimates of sensitivity (Sens) and elasticity (Elas) of fecundity and survival for Double-crested cormorants in Lake of the Woods (LOW), North Channel of Lake Huron (NChan), and Eastern Lake Ontario (ELO) estimated with stage-classified projection matrices. Cormorants were considered reproductively mature at the age of three. Fecundity was estimated using fledge rates from the 2006 and 2007 breeding seasons, divided by two to account for an assumed 50:50 sex ratio. Survival estimates were generated in Program MARK from birds banded as young of the year since 2000. Cormorants were grouped into 4 stages, with the first 3 stages age-specific. The first age class is young of the year (YOY) surviving to the next breeding season the following year. The second and third age classes are birds aged 1 and 2 surviving to the next breeding season the following year. The fourth age class is comprised of birds aged ≥3.

LOW NChan ELO Fecundity Survival Fecundity Survival Fecundity Survival Sens Elas Sens Elas Sens Elas Sens Elas Sens Elas Sens Elas age YOY 0.000 0.000 0.495 0.088 0.000 0.000 0.212 0.098 0.000 0.000 0.498 0.105 1 0.000 0.000 0.089 0.088 0.000 0.000 0.134 0.098 0.000 0.000 0.129 0.105 2 0.000 0.000 0.102 0.088 0.000 0.000 0.113 0.098 0.000 0.000 0.123 0.105 ≥3 0.113 0.088 0.736 0.647 0.204 0.098 0.707 0.610 0.099 0.105 0.686 0.581

113

Table 4.21 Estimates for finite rate of increase (λ), intrinsic rate of increase (r), expected number of replacements (Ro), generation time (T), and mean age of parents of offspring of a cohort (mu1) for Double-crested cormorants in Lake of the Woods (LOW), North Channel of Lake Huron (NChan), and Eastern Lake Ontario (ELO) estimated with stage-classified projection matrices. Survival estimates were generated in Program MARK from birds banded as young of the year since 2000.

LOW NChan ELO λ 0.973 0.985 0.973 r -0.052 -0.015 -0.027 Ro 0.590 0.864 0.779 T 10.076 9.942 9.109 mu1 9.068 9.649 8.703

114

Figures

O ONTARI

BEC QUE [_ LOW [_NChan ELO Minnesota [_

k sin Yor Wiscon New n Michiga

ania nsylv Pen

Ohio ylan Mar of C t ict

Figure 4.1 Location of the 3 geographically separated Double-crested cormorant breeding areas sampled for population characteristics during 2006 - 2007. LOW = Lake of the Woods, NChan = North Channel of Lake Huron, ELO = Eastern Lake Ontario.

115

Survival Estimates for LOW

1.2

0.8

0.6 Survival 0.4

0.2

0 123456 Age

Figure 4.2 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Burnham model average for Double-crested cormorants in Lake of the Woods (LOW), banded as young of the year. Survival represented as a rate, age is in years.

Survival Estimates for LOW

1.2

0.8

0.6 Survival 0.4

0.2

0 123456 Age

Figure 4.3 Graphical depiction of the survival estimates with upper and lower confidence intervals from the second “best” Burnham model {S(t)p(t)r(-)F(t)} ranked by QAIC for Double-crested cormorants in Lake of the Woods (LOW), banded as young of the year. Survival represented as a rate, age is in years.

116

Survival Estimates for NChan - Seber

1.2

0.8

0.6 Survival 0.4

0.2

0 1234 Age

Figure 4.4 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Seber model average for Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year. Survival represented as a rate, age is in years.

Survival Estimates for NChan - Brownie

1.2

0.8

0.6 Survival 0.4

0.2

0 123 Age

Figure 4.5 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Brownie model average for Double-crested cormorants in the North Channel of Lake Huron, banded as young of the year. Survival represented as a rate, age is in years.

117

Survival Estimates for ELO - WH

1.2

0.8

0.6 Survival 0.4

0.2

0 1234 Age

Figure 4.6 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Burnham joint live-encounter dead-recovery model average for Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by the Canadian Wildlife Service (WH). Survival represented as a rate, age is in years.

Survival Estimates for ELO - GN

0.9

0.8

0.7

0.6

0.5

Survival 0.4

0.3

0.2

0.1

0 123 Age

Figure 4.7 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Burnham joint live-encounter dead-recovery model average for Double-crested cormorants in Eastern Lake Ontario, banded as young of the year by the U.S. Department of Agriculture, National Wildlife Research Center (GN). Survival represented as a rate, age is in years. 118

Survival Estimates for ELO - both

0.9 0.8

0.7

0.6

0.5

Survival 0.4

0.3 0.2

0.1 0 123 Age

Figure 4.8 Graphical depiction of the survival estimates with upper and lower confidence intervals from the weighted Burnham joint live-encounter dead-recovery model average for Double-crested cormorants in Eastern Lake Ontario (ELO), banded as young of the year by both the U.S. Department of Agriculture, National Wildlife Research Center (GN) and the Canadian Wildlife Service (WH).

Survival Estimates for all Region

1.2

0.8

0.6 Survival 0.4

0.2

0 123456 Age

ELO both ELO GN ELO WH LOW NChan brown NChan Seber

Figure 4.9 Graphical depiction of the survival estimates with upper and lower confidence intervals from all models for the Interior metapopulation of Double-crested cormorants, banded as young of the year. Survival represented as a rate, age is in years. ELO = Eastern Lake Ontario, NChan = North Channel of Lake Huron, LOW = Lake of the Woods. ELO both =both the U.S. Department of Agriculture, National Wildlife Research Center (NWRC; GN) and the Canadian Wildlife Service (WH). NChan brown = Brownie model, NChan Seber = Seber model. 119

CHAPTER 5

SUMMARY AND CONCLUSIONS