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Conservation genetics of small populations Marr, Amy Beth 2005

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CONSERVATION GENETICS OF SMALL POPULATIONS by A M Y B E T H M A R R A . B . , Princeton University, 1996 M . S c , University of Wisconsin - Madison, 1999 A THESIS SUBMITTED IN P A R T I A L F U L F I L L M E N T OF THE REQUIREMENTS FOR THE D E G R E E OF DOCTOR OF PHILOSOPHY in THE F A C U L T Y OF G R A D U A T E STUDIES Program in Forest Sciences THE UNIVERSITY OF BRITISH C O L U M B I A February 2005 © Amy Beth Marr, 2005 THESIS ABSTRACT Many species of plants and animals exist in small populations because human activities have fragmented and reduced natural habitats. Individuals in small, relatively isolated populations tend to have lower survival and reproductive success due to inbreeding and loss of genetic variation. To reverse these genetic problems, some biologists have advocated managing rare species by building dispersal corridors among populations or by translocating individuals. However, conservation strategies that manipulate gene flow are risky. This thesis uses long-term data on a population of song sparrows to study the various genetic phenomena that can be vital to the biology and management of small populations. The data on the song sparrows (Melospiza melodia) of Mandarte Island are somewhat extraordinary because, since 1975, virtually all individuals have been colour-banded and there exists an extensive pedigree of the population. Chapter one introduces the study population, provides background on inbreeding depression and genetic drift, and discusses the objectives of this thesis. Chapter two describes the survival and reproductive success of irnmigrants and their descendants in the Mandarte Island song sparrow population. The performance differences between immigrant and native females and between F.jS (birds with an immigrant and a native parent) and the average of immigrants and natives suggest that immigrants were disadvantaged by a lack of site experience, and that FiS benefited from heterosis. However, none ofthe gains experienced by Fjs were seen in the subsequent generation, probably due to outbreeding depression. Chapter three uses a simulation model to demonstrate that errors in the pedigree cause errors in inbreeding coefficients and bias in inbreeding depression estimates. Chapter four tests for the interactive effects of inbreeding and environmental stress on four reproductive traits. It is shown that the eggs laid by inbred female song sparrows had particularly low hatching success during rainy periods. Pedigree error and interactions between inbreeding and environmental stress are two factors that may contribute to variation in inbreeding depression estimates across studies. Chapter five explains why the findings for this study population and other academic research on inbreeding and outbreeding are relevant to the management of small populations of conservation concern. T A B L E O F C O N T E N T S Thesis abstract ii Acknowledgements vii Thesis format and co-authorship statement ix Chapter 1: Thesis introduction - Habitat loss and genetic issues affecting small populations . 1 1.1 The current mass extinction event on planet Earth 1 1.2 Genetic concerns of relevance to small populations 2 1.3 Case study overview and research objectives 2 1.4 Literature cited 5 Chapter 2: Heterosis and outbreeding depression in descendants of natural irrvmigrants to an inbred population of song sparrows (Melospiza melodia) 8 2.1 Introduction 9 2.2 Methods : 12 2.2.1 Study site and field methods 12 2.2.2 Pedigree groups and inbreeding calculations 13 2.2.3 Performance analyses 14 2.3 Results 17 2.3.1 Irnrnigration rate 17 2.3.2 Performance of immigrants 18 2.3.3 Performance of F]S 18 2.3.4 Performance of F2s 18 2.4 Discussion 19 2.4.1 Performance of immigrants 19 2.4.2 Performance of F]S 20 2.4.3 Performance of F2s 21 2.5 Conclusions 23 2.6 Literature cited 23 2.7 Acknowledgements 31 2.8 Figures and tables 32 Chapter 3: Pedigree errors bias estimates of inbreeding depression 40 3.1 Introduction 40 3.2 Methods 42 3.2.1 Field methods and genetic data 42 3.2.2 Calculation of inbreeding coefficients and inbreeding depression 43 3.2.3 The simulation : 44 3.2.4 Extrapolated estimates of inbreeding depression 46 - iii -3.3 Results 46 3.3.1 Effect of paternity error on estimates of inbreeding depression 46 3.3.2 Extrapolated estimates of inbreeding depression 47 3.4 Discussion 47 3.4.1 Considerations for applying this approach to other studies 48 3.5 Conclusions 49 3.6 Literature cited 49 3.7 Acknowledgements 52 3.8 Figures and tables 53 Chapter 4: Effects of natural environmental stress and inbreeding on fitness traits in a wild bird population 56 4.1 Introduction 56 4.2 Methods 58 4.2.1 Field site, methods, and pedigree 58 4.2.2 Statistical analyses 59 4.3 Results 63 4.4 Discussion 65 4.5 Conclusion 67 4.6 Literature cited 67 4.7 Acknowledgements : 72 4.8 Figures and tables 73 Chapter 5: Thesis conclusion - Managing for connectivity and genetic health in small populations 84 5.1 Introduction 84 5.2 Immigrant genes may spread quickly: Heterosis 85 5.3 Immigration may save declining populations: Genetic rescue 86 5.4 Immigration may lower individual and population fitness: Outbreeding depression 87 5.5 High immigration rates may cause gene swamping 88 5.6 From theory to practice 89 5.7 Immigration and the genetic health of Mandarte Island song sparrows 90 5.8 Heterosis and outbreeding depression in immigrant descendants 91 5.9 The spread of immigrant lineages and gene pool turnover 92 5.10 The competitiveness of immigrant genes 94 5.11 The effect of immigrants on neutral genetic variation 94 5.12 Summary and synthesis 96 5.13 Literature cited 97 5.14 Statistical notes 103 5.15 Acknowledgements 103 5.16 Figures and tables • 105 - iv -LIST OF FIGURES Figure 2.1 Number of immigrants versus nonimmigrants in the Mandarte Island song sparrow population each year from 1982 to 2000 32 Figure 3.1 Effect of simulated paternity error on estimates of inbreeding depression for three fitness traits 53 Figure 4.1 Effects of inbreeding and stress on four fitness traits for outbred and highly inbred birds 73 Figure 5.1 Lifetime reproductive success of breeding males and females and survival of juveniles by pedigree group 105 Figure 5.2 Fraction of new recruits in the population that have an immigrant ancestor who arrived after 1981 . 106 Figure 5.3 Fraction ofthe gene pool of the population that can be traced to immigrants arriving after 1981 107 Figure 5.4 The contributions of individual female and male song sparrows to the Mandarte Island gene pool over time 108 Figure 5.5 Count of alleles present in the population at each of 8 micfosatellite genetic marker loci from 1987 to 1996 109 - v -L I S T O F T A B L E S Table 2.1 Studies of wild birds that compared the performance of immigrant and resident-hatched individuals or long-distance and short-distance dispersers 33 Table 2.2 Factors potentially contributing to differences in survival and reproductive success between immigrants and natives 35 Table 2.3 Results of three discrete-time proportional hazards models comparing survival rates of juveniles, adult females, and adult males in five pedigree groups 36 Table 2.4 Seasonal reproductive success of females and males in five pedigree groups 37 Table 2.5 Lifetime reproductive success of breeding males and females in five pedigree groups 39 Table 3.1 Discrete-time proportional hazards analysis of the effects of inbreeding on survival of juveniles to age one based on the social pedigree 54 Table 3.2 ANCOVA of the effects of cohort and inbreeding on the lifetime reproductive success of males and females based on the social pedigree 55 Table 4.1 Comparison of eight models examining the effects of a male's age, his inbreeding level, and competition on the number of nests he fathered in a year 74 Table 4.2 Effects of>a male's age, his inbreeding level, and the number of males per female in the population on the number of nests that he fathers in a year 75 Table 4.3 Effects of inbreeding and various environmental stresses on four fitness traits 76 Table 4.4 Comparison of 17 generalized logistic regressions examining the effects of a father's age, his inbreeding level, and rain on the survival of his offspring from day 12 to day 24 78 Table 4.5 Effects of a male's age, his inbreeding level, and rain (3-day interval) on the survival of his offspring from day 12 to day 24 79 Table 4.6 Comparison of 20 general linear models examining the effects of a female's age, her inbreeding level, and air temperature on the date that she lays her first egg in spring 80 Table 4.7 Effects of a female's age, her inbreeding level, and the daily average air temperature in February and March on the Julian date that a female lays her first egg in spring 81 Table 4.8 Comparison of 17 generalized logistic regressions examining the effects of a mother's age, her inbreeding level, and rain on hatching success of her eggs 82 Table 4.9 Effects of a mother's age, her inbreeding level, and rain (4-day interval) on the hatching success of her eggs 83 Table 5.1 The total number of adult birds in the population and the percentage that were genotyped in each year from 1987 to 1996 110 Table 5.2 Allelic contributions of nine immigrant song sparrows to the population gene pool for six autosomal and two sex-linked microsatellite loci 111 - vi -A C K N O W L E D G E M E N T S I would like to express my sincere gratitude to everyone who supported me during graduate school. My supervisor, Peter Arcese, gave me an incredible opportunity as his student. Peter's broad knowledge of ecology improved the quality of this thesis. I was also fortunate to have a supervisor who was keen to share his ideas and who was consistently enthusiastic about my work. My committee members Kermit Ritland, Michael Whitlock, and Dolph Schluter inspired me with their many challenging questions. Special thanks also go to Michael Whitlock for giving me some of the most insightful critiques of my work that I have ever received. Although not official members of my committee, Lukas Keller, Jane Reid, and Jamie Smith also made vital contributions to my education and thesis. Lukas greatly improved my understanding of population genetics and statistics, Jane provided expert editorial suggestions, and Jamie's advice improved my writing skills. The Department of Forest Sciences with its faculty, staff, and graduate students provided a stimulating environment for this work. Thanks also go to the faculty and students in the Department of Zoology for hosting seminars and discussions that greatly enriched my experience at UBC. I am grateful to Val Lemay for answering statistical questions that no book seemed to address. Deb Feduik was always helpful with my administrative concerns. Norm Hodges solved my computer networking and hardware problems. Of the many students that I met in graduate school, I would like to extend a special thanks to Katie O'Connor, Simone Runyan, Charles Chen, Anna Estes, and Yvonne Chan. Anna and Yvonne made sure that my first year at UBC was great fun, and Katie, Charles, and Simone were always there for me during the subsequent years. I also benefited from many discussions with Katie and Simone about ecology, birds, and statistics, and I learned a lot from Yvonne and Katie about genetics labwork. Charles always had encouraging words and was a great help with population genetics. Thanks also go to fellow graduate students Justin Brashares, Christie Staudhammer, Emily Gonzalez, Scott Wilson, Bruce Catton, Amy Wilson, and Marco Albani for many stimulating discussions. Dozens of people over many years contributed to the collection of field data. Since 2000, field biologists have included Scott Wilson, Jane Reid, Katie O'Connor, Simone Runyan, Danielle Dagenais, Andrew Johnston, Carolyn Saunders, Rob Landucci, Andy Davis, Lukas Keller, Peter Arcese, and Jamie Smith. Special thanks also go to the Tsawout and Tseycum First Nations Bands for allowing us to work on Mandarte Island. - vn -Financial support for this thesis was provided by a grant to Peter Arcese from the National Science and Engineering Research Council and by scholarships to me from the National Science Foundation Graduate Study Fellowship Program, the UBC Graduate Fellowship Program (Josephine T. Berthier Award), the Adrian Weber Memorial Scholarship in Forest Ecology, the Gene Namkoong Family Scholarship in Forest Genetics, the Bert Hoffmeister Scholarship in Forest Wildlife, the UBC International Student Partial Tuition Waver Program, Sigma Xi's Grants-in-Aid-of-Research Program, the Frank M. Chapman Fund for Ornithology Research, the E. Alexander Bergstrom Memorial Grant Program in Ornithology, and the Western Bird Banding Association. This thesis would not have been possible without the support of my friends from elsewhere and my family. I thank my mother, Diane Marr, for showing that she was often thinking of me. My father, Harold Marr, was a source of ceaseless encouragement. My brothers Chris and Mike, my sister Laurie, and my friends Regina Hirsch, Nancy Hess, Anne Bolger, and Jackie Memlo always had stories to make me laugh. Last, but certainly not least, I am sincerely grateful to my partner, Louis Dallaire, for helping make this thesis possible in many ways, including vastly improving my SAS programming abilities, building computers for me, taking me away from Vancouver when I needed to escape the rain, and, most of all, for listening with great patience on countless occasions when I just wanted to talk about my research. - viii -THESIS F O R M A T A N D C O - A U T H O R S H I P S T A T E M E N T Upon the recommendation of my academic committee, I prepared this thesis as a series of independent but related manuscripts to be submitted for publication. Chapter 1 provides background and summarizes the objectives of this thesis. Chapter 2 was published as an article in the journal Evolution. Chapter 3 and 4 will be submitted as articles to journals for publication. Chapter 5 will be published as a chapter in a book titled the Biology of Small Populations. As such, the format of Chapter 5 differs from the other three manuscript chapters in this thesis. Chapters 2, 3, and 4 follow the format typical of a scientific paper in having an abstract, introduction, methods, results, and discussion. Chapter 5 follows the format of other chapters in the Biology of Small Populations book in beginning with an extended introduction of the literature on the topic, then raising a few difficult but unresolved questions and trying to address those questions by using the Mandarte song sparrow data. In Chapter 5, methods are discussed briefly prior to each result. Analyses highlight the potential ecological importance of results without emphasizing statistical significance testing (i.e., p-values). For the sake of readability, statistics are placed in footnotes at the end of the chapter. For all chapters of this thesis, I took the lead in developing ideas, analyzing data, and producing draft manuscripts, figures, and tables. However, this research would not have been possible without the contributions of others. My supervisor, Peter Arcese, helped me plan and fund my thesis and he gave me unrestricted access to a remarkable dataset collected by him, his students, his former supervisor Jamie Smith, and Jamie's former graduate students. Various other individuals also made key contributions. To recognize the efforts of others, I have included co-authors for selected chapters of this thesis as described below. Chapter 2: Heterosis and outbreeding depression in descendants of immigrants to an inbred population of song sparrows (Melospiza melodia) - Lukas Keller advised me on the SAS code for analyses of survival and seasonal reproductive success. Peter Arcese improved the content of the literature reviewed in this chapter based on his knowledge of ecology, and both Lukas and Peter critiqued drafts of the manuscript. - ix -Chapter 3: Pedigree errors bias estimates of inbreeding depression - Louis Dallaire helped automate the macros in the model simulation in SAS. Lukas Keller made suggestions about key references and provided editorial suggestions. Chapter 4: Effects of natural environmental stress and inbreeding on fitness traits in a wild bird population - Peter Arcese, Jane Reid, and Lukas Keller helped me refine my research question and critiqued drafts of the manuscript. In addition to those individuals that were co-authors, each of Chapters 2-5 ends with an acknowledgements section thanking others who made vital contributions through discussions, by reviewing manuscripts, and by collecting field data. CHAPTER 1: THESIS INTRODUCTION - HABITAT LOSS AND GENETIC ISSUES AFFECTING SMALL POPULATIONS 1.1 T H E C U R R E N T M A S S E X T I N C T I O N E V E N T O N P L A N E T E A R T H The primary productivity of our planet is the total amount of plant mass created on Earth in a given year. Recent estimates suggest that we humans, a single species, use about 40% of Earth's terrestrial primary productivity (Vitousek et al. 1986; Pimm 2001). We consume that biomass primarily with agriculture and grazing, and by harvesting our forests for the energy and fibre stored in the trees. Millions of other species also compete for existence in the food chain that begins when plants store the energy from the sun, but no other single species is as successful as humans at exploiting that energy for their own benefit. In the struggle to compete with human activities and land use, many species are failing entirely. In North America, for example, 631 species of plants and animals have gone extinct since 1642 (Center for Biological Diversity 2001). Conservative estimates suggest that the current extinction rate of species is 100 to 1000 times greater than the level before humans dominated Earth (Pimm et al. 1995). Habitat destruction, degradation, and fragmentation are among the most important causes of species declines (Lande 1999). If land-use policies continue on their current trajectory, the most dire predictions contend that as many as half of all species will go extinct during the next 50 to 100 years (Dobson 1996). Mass extinctions of this magnitude have occurred only five other times over the last half billion years, with the last episode resulting in disappearance of the dinosaurs 65 million years ago. This thesis was inspired by my concern about how humans are accelerating extinction rates by developing and fragmenting natural habitats. Conservation biologists have shown that population size is inversely correlated with persistence time for species in habitat fragments (Diamond 1984). In most habitat fragments, however, it is not known what factors drive populations to extinction. Ecologists have often found that environmental factors can limit population growth and influence population size (Lack, 1954, 1966; Newton 1980), but the contributions of genetic factors to population vulnerability are less well understood (Saccheri et al. 1998), and few studies have explored interactions between environmental and genetic causes of population declines. 1.2 GENETIC CONCERNS OF RELEVANCE TO SMALL POPULATIONS Random drift and inbreeding are two genetic factors that might contribute to the decline of small populations. Within a population, the alleles for genes passed from one generation to the next are a sample of the alleles present in the parent generation. This sampling process can lead to random changes in allele frequencies (random drift) between successive generations (Wright 1977; Falconer and Mackay 1996). Sampling variation is greater when there are fewer potential parents. Therefore, small populations that are isolated from immigration tend to become genetically depauperate at loci that are selectively neutral, or nearly neutral (Hedrick 2000). Over generations, random drift can fix mildly deleterious mutations, lead to loss of beneficial mutations, decrease heterozygosity for loci where heterozygotes are more fit, and cause the loss of genetic variation that would allow for future adaptation (Kimura 1983; Keller and Waller 2002). Inbreeding yields offspring that are homozygous at more loci in their genome than offspring produced by unrelated individuals (Hedrick 2000). Thus, inbred individuals are more likely to have deleterious recessives that are exposed in homozygous combination, and they often experience inbreeding depression (Charlesworth and Charlesworth 1999). Inbreeding depression is a reduction in phenotypic value shown by traits associated with reproductive capacity or physiological efficiency (Falconer and Mackay 1996). For centuries, breeders of domesticated animals and plants have known that inbreeding can depress fitness (e.g., Darwin 1877). However, just over a decade ago, there were few studies demonstrating inbreeding depression in wild populations. This led some scientists, like Caughley (1994) and Caro and Laurenson (1994), to question if genetic factors that affect small populations, such as random drift and inbreeding depression, were important management concerns given the much greater evidence for environmental causes of population declines. Since that time, there have been a number of convincing case studies demonstrating random drift and inbreeding depression in wild populations (Keller 1998 and references therein; Daniels and Walters 2000; Slate et al. 2000; Kruuk et al. 2002). However, one vital question raised by Caughley, Caro, and Laurenson remains unresolved. We do not yet understand the extent to which genetic factors are causes of endangerment or merely symptoms of small population size. 1.3 CASE STUDY OVERVIEW AND RESEARCH OBJECTIVES The song sparrows of Mandarte Island, a small island in British Columbia, Canada, are not a conservation concern, but the population is being used as a model system for understanding factors that -2 -affect the persistence of small, relatively isolated populations. The song sparrow (Melospiza melodia) is a common passerine bird that inhabits a variety of brushy and moist habitats throughout most of North America south of the tree line, except for the southeastern United States (Arcese et al. 2002). Song sparrows are a popular subject of ornithological studies because both sexes vocalize frequently enough to make observations relatively easy and because the life history of song sparrows is typical of many songbird species (Smith et al, in review). The song sparrow data for Mandarte Island are somewhat extraordinary because the breeding success and survival of the entire population has been intensively monitored for 29 years (1975 - 2003). Prior work on the Mandarte Island song sparrows showed that the genetic variation of the population has varied over time and that inbreeding depresses survival and reproductive success (Keller et al. 1994; Keller 1998; Keller et al. 2001). My goals for this thesis were to build on this past work by studying other genetic factors affecting this population and by furthering our understanding of inbreeding depression. Dispersers to a small population (immigrants) may reduce extinction risk simply because they increase the number of individuals when population size is low (rescue effect, Brown and Kodric-Brown 1977; see Stacey et al. 1997 for examples). However, predicting the true effect of dispersal on population persistence is complicated. Based on theory in population genetics, the contribution of immigrants might be greater than their numbers would imply, because immigrants can reduce inbreeding levels and enhance and restore genetic diversity. However, it is also possible that immigrants may be detrimental because they are not well adapted to local conditions or because their descendants experience outbreeding depression. Outbreeding depression is a loss of fitness associated with the mixing of dissimilar gene pools. So far to date, a general understanding of the genetic contribution of immigrants to natural populations has been hindered by a scarcity of empirical studies. My objective in Chapter 2 was to help address this gap in scientific knowledge by: 1. Reviewing prior work on the fitness of immigrants in natural populations 2. Examining the fitness of immigrant song sparrows to Mandarte Island and discussing the ecological and genetic factors that could have contributed to performance differences between immigrant and native individuals 3. Describing and interpreting the performance of immigrant descendants Soon after completing Chapter 2 of this thesis, work conducted on the Mandarte Island song sparrows revealed that the social fathers of offspring are not the true genetic fathers for about 28% of birds hatched on the island (O'Connor 2003). These paternity errors, in turn, affect estimates of -3 -inbreeding and outbreeding depression. This information led to crucial questions about the evidence of inbreeding depression and other genetic factors for the Mandarte Island song sparrow data. Therefore, to address this concern, I developed a simulation model (Chapter 3) asking how pedigree errors bias our estimates of the effects of genetic phenomena, such as inbreeding depression. Even when pedigree error is not a concern, however, accurately estimating inbreeding depression poses other challenges. A potentially important issue is that the strength of inbreeding depression may depend on environmental factors. If strong interactions between inbreeding and environmental factors exist, it would be wise to incorporate them in management plans for species of conservation concern. Unfortunately, few studies of wild populations have tested for interactions between inbreeding and environmental stressors. Therefore, in Chapter 4,1 present the data from the Mandarte Island song sparrows as a much-needed example from a natural system. In discussing my research from Chapters 2, 3, and 4 of this thesis with biologists outside of academia, I learned that most recognized inbreeding depression could be a problem affecting the persistence of small populations. Some also knew that mixing genetically differentiated populations could lead to loss of local adaptation and genetic incompatibilities. However, many biologists were unsure what academic studies on Mandarte Island and elsewhere implied about strategies to encourage gene pool mixing for species of conservation concern. Therefore, my objective for the final data chapter of my thesis (Chapter 5) was to advance discussion of this topic by: 1. Summarizing the ways that immigrants maintain and restore the genetic health of small populations (Sections 5.1 - 5.5) 2. Reviewing recommendations by academics for managing the genetic health of actual populations and noting unresolved questions (Section 5.6) 3. Describing the relevance of past work on the genetic contributions of immigrant song sparrows to Mandarte Island (Sections 5.7 - 5.8) 4. Conducting new analyses to explore the effect of immigrants on the genetic health of the Mandarte Island song sparrow population (Sections 5.9 - 5.11) M y aim, in writing Chapter 5, was to make case studies on inbreeding and outbreeding more accessible to biologists outside academia with only a limited background in population genetics. I also emphasized the implications of this thesis for managing small populations of conservation concern. 1.4 LITERATURE CITED Allendorf, F.W., and N. Ryman. 2002. The role of genetics in population viability analysis, pp. 5-17, in S. R. Beissinger and D. R. McCullough. Population Viability Analysis. University of Chicago Press, Chicago. Arcese, P., M. K. Sogge, A. B. Marr, M. A. Patten. 2002. Song sparrow (Melospiza melodia), pp. 1-40, in A. Poole and F. Gill (eds.), The Birds of North America, No. 704. The Birds of North America, Inc., Philadelphia. Beissinger, S.R. 2002. Population viability analysis: past, present, future, pp. 5-17, in S. R. Beissinger and D. R. McCullough (eds.), Population Viability Analysis. University of Chicago Press, Chicago. Brook, B.W., D. W. Tonkyn, J. J. O'Grady, and R. Frankham. 2002. Contribution of inbreeding to extinction risk in threatened species. Conserv. Ecol. 6: art. no. 16. Brown, J. H., and A. Kodric-Brown. 1977. Turnover rates in insular biogeography: effect of immigration on extinction. Ecology 58: 445-449. Caro, T. M., and M. K. Laurenson. 1994. Ecological and genetic factors in conservation - a cautionary tale. Science 263 (5146): 485-486. Caughley, G. 1994. Directions in conservation biology. J. Anim. Ecol. 63: 215-244. Center for Biological Diversity. 2001. 631 extinct North American species identified as of 6-29-01. http://www.biologicaldiversity.org/swcbd/activist/ESA/631extinctspecies.pdf (Accessed 15 May, 2004). Charlesworth, B., and D. Charlesworth. 1999. The genetic basis of inbreeding depression. Genet. Res. 74: 329-340. Daniels, S. J., and J. R. Walters. 2000. Inbreeding depression and its effect on natal dispersal in Red-cockaded Woodpeckers. Condor 102: 482-491. Darwin, C. 1877. The Effects of Cross and Self Fertilisation in the Vegetable Kingdom. D. Appleton, New York. Diamond, J. M. 1984. 'Normal' extinction of isolated populations, pp. 191-246, in M. H. Nitecki (ed.), Extinctions. Chicago University Press, Chicago. Dobson, A. P. 1996. Conservation and Biodiversity. W. H. Freeman and Company, New York. Falconer, D. S., and T. F. C. Mackay. 1996. Introduction to Quantitative Genetics, 4th edition. Longman, Essex, England. -5 -Hedrick, P. W. 2000. Genetics of Populations, 2nd edition. Jones and Bartlett Publishers, Sudbury, MA. Keller, L. F. 1998. Inbreeding and its fitness effects in an insular population of song sparrows (Melospiza melodia). Evolution 52: 240-250. Keller, L. F., P. Arcese, J. N. M. Smith, W. M. Hochachka, and S. C. Stearns. 1994. Selection against inbred song sparrows during a natural population bottleneck. Nature 372: 356-357. Keller, L. F., K. J. Jeffery, P. Arcese, M. A. Beaumont, W. M. Hochachka, J. N. M. Smith, and M. W. Bruford. 2001. Immigration and the emphemerality of a natural population bottleneck: evidence from molecular markers. Proc. R. Soc. London Ser. B 268: 1387-1394. Keller, L. F., and D. M. Waller. 2002. Inbreeding effects in wild populations. Trends Ecol. Evol. 17: 230-241. Kimura, M. 1983. The Neutral Theory of Molecular Evolution. Cambridge University Press, Cambridge, England. Kruuk, L. E. B., B. C. Sheldon, and J. Merila. 2002. Severe inbreeding depression in collared flycatchers (Ficedula albicollis) Proc. R. Soc. London Ser. B 269: 1581-1589. Lack, D. L. 1954. The Natural Regulation of Animal Numbers. Clarendon Press, Oxford. Lack, D. L. 1966. Population Studies of Birds. Clarendon Press, Oxford. Lande, R. 1988. Genetics and demography in biological conservation. 241 (4872): 1455-1460. Lande, R. 1999. Extinction risks from anthropogenic, ecological, and genetic factors, pp. 1-22, in L. F. Landweber and A. P. Dobson (eds.), Genetics and the Extinction of Species. Princeton University Press, Princeton, NJ. Newton, I. 1980. The role of food in limiting bird numbers. Ardea 68: 11-30. O'Connor, K. D. 2003. Extra-pair Mating and Effective Population Size in the Song Sparrow (Melospiza melodia). MSc diss., University of British Columbia, Vancouver, BC, Canada. Pimm, S. L., G. J. Russell, J. L. Gittleman, and T. M. Brooks. 1995. The future of biodiversity. Science 269 (5222): 347-350. Pimm, S. L. 2001. The World According to Pimm: A Scientist Audits the Earth. McGraw-Hill, New York. Saccheri, I., M. Kuussaari, M. Kankare, P. Vikman, W. Fortelius, and I. Hanski. 1998. Inbreeding and extinction in a butterfly metapopulation. Nature 392: 491-494. Slate, J, L. E. B. Kruuk, T. C. Marshall, J. M. Pemberton, and T. H. Clutton-Brock. 2000. Inbreeding depression influences lifetime breeding success in a wild population of red deer (Cervus elaphus). Proc. R. Soc. London Ser. B 267 (1453): 1657-1662. Smith, J. N. M., A. B. Marr, and W. M. Hochachka. In review. Life history: Reproduction and survival in J. N. M. Smith (ed.), The Biology of Small Populations: The Song Sparrows of Mandarte Island. Oxford University Press, London. Stacey, P. B., V. A. Johnson, and M. L. Taper. 1997. Migration within metapopulations: the impact upon local population dynamics, pp. 267-291, in I. A. Hanski and M. E. Gilpin (eds.), Metapopulation Biology: Ecology, Genetics, and Evolution. Academic Press, San Diego. Wright, S. 1977. Evolution and the Genetics of Populations, Experimental Results and Evolutionary Deductions, vol. 3. Univ. of Chicago Press, Chicago. Vitousek, P. M., P. R. Ehrlich, A. H. Ehrlich, and P. A. Matson. 1986. Human appropriation of the products of photosynthesis. Bioscience 36(6): 368-373. CHAPTER 2: HETEROSIS AND OUTBREEDING DEPRESSION IN DESCENDANTS OF NATURAL IMMIGRANTS TO AN INBRED POPULATION OF SONG SPARROWS (MELOSPIZA MELODIA) By Amy B. Marr, Lukas F. Keller, and Peter Arcese ABSTRACT We studied heterosis and outbreeding depression among immigrants and their descendants in a population of song sparrows on Mandarte Island, Canada. Using data spanning 19 generations, we compared survival, seasonal reproductive success, and lifetime reproductive success of immigrants, natives (birds with resident-hatched parents and grandparents), and their offspring (FiS, birds with an immigrant and a native parent, and F 2s, birds with an immigrant grandparent and resident-hatched grandparent in each of their maternal and paternal lines). Lifetime reproductive success of immigrants was no worse than that of natives, but other measures of performance differed in several ways. Immigrant females laid later and tended to lay fewer clutches, but they had relatively high success raising offspring per egg produced. The few immigrant males survived well but were less likely to breed than native males of the same age that were alive in the same year. Female FjS laid earlier than expected based on the average for immigrant and native females, and adult male F]S were more likely to breed than expected based on the average for immigrant and native males. The performance differences between immigrant and native females and between F]S and the average of immigrants and natives are consistent withthe hypothesis that immigrants were disadvantaged by a lack of site experience, and that immigrant offspring benefited from heterosis. However, we could not exclude the possibility that immigrants had a different strategy for optimizing reproductive success or that they experienced ecological compensation for life-history parameters. For example, the offspring of immigrants may have survived well, because immigrants laid their eggs later and produced fewer clutches, thereby raising offspring during a period of milder climatic conditions. Although sample sizes were small, we found large performance differences between FiS and F 2s which suggested that either heterosis was associated with epistasis in F]S, that F 2s experienced outbreeding depression, or that both phenomena occurred. These findings indicate that the performance of dispersers may be affected more by fine-scale genetic differentiation than previously assumed in this and comparable systems. 2.1 I N T R O D U C T I O N Evolutionary biologists study inbreeding and outbreeding in plants and animals because these phenomena affect speciation (Lynch 1991; Grant and Grant 1996) and drive the evolution of mating systems, mate recognition, dispersal, and other behaviours (Greenwood 1980; Ralls et al. 1986; Pusey 1987; Pusey and Wolf 1996). There is also growing concern among conservation biologists that recovery plans for rare species will fail more often if individual fitness and genetic variation are reduced by inbreeding, or if local adaptations are lost via outbreeding (Schonewald-Cox et al. 1983; Allendorf and Leary 1986; Templeton 1986; Avise and Hamrick 1996; Lacy 1997). So far, however, specific hypotheses for the effects of dispersal on inbreeding and outbreeding in natural systems have escaped rigorous tests, due primarily to a lack of empirical data. Here, we present data from a pedigreed population of song sparrows that resides year-round on Mandarte Island, British Columbia, to compare the survival and reproductive success of immigrants and their descendants to that of natives. Below, we review briefly studies on inbreeding and outbreeding, describe our prior work on the study population, and present our main hypotheses and predictions. A reduction in the performance of inbred individuals relative to outbred individuals, called inbreeding depression, has been demonstrated in a wide range of plants (Darwin 1876; Wright 1977; Charlesworth and Charlesworth 1987; Dudash 1990; Husband and Schemske 1996) and domesticated and captive wild animals (Darwin 1868; Bereskin et al. 1968; Dinkel et al. 1968; Lamberson and Thomas 1984; Templeton and Read 1984; Ralls et al. 1988). More recently, ecologists have shown that inbreeding can depress individual performance in populations of wild animals (Brown and Brown 1998; Keller 1998 and references therein; Saccheri et al. 1998; Daniels and Walters 2000). Inbreeding depression is usually attributed to the expression of deleterious recessives or a loss of favourable heterozygosity at loci where heterozygotes are more fit than homozygotes (Charlesworth and Charlesworth 1987; Lynch and Walsh 1998, p. 252). Empirical work suggests that most inbreeding depression is caused by deleterious recessives (Charlesworth and Charlesworth 1999). Studies on inbreeding depression to date have focused primarily on the effects of genes at independent loci, but some inbreeding depression is likely due to genes that function epistatically (Lynch 1991; Charlesworth 1998). Song sparrows in our study population did not avoid inbreeding (Keller and Arcese 1998), even though inbreeding reduced survival and reproductive success in each sex (Keller 1998). In particular, inbred birds survived poorly after independence from parental care, and inbred males suffered reduced - 9 -reproductive rates seasonally because their mates produced relatively few clutches. Inbred females hatched fewer eggs and raised fewer young to independence. In 1989, a population bottleneck was also associated with selection against inbred sparrows (Keller et al. 1994). Thus, because inbreeding is deleterious in our study population, we expected that the fitness of direct descendants of immigrants to the population might differ from natives, which are often inbred. We now describe briefly the theory and empirical results underlying these expectations. Breeders routinely cross individuals from lines within species of domestic animals because F)S from these crosses are often more fit than purebred individuals (e.g., beef cattle: Cundiff 1970; Gregory etal. 1991; dairy cattle: Turton 1981; poultry: Sheridan 1986; Omeje and Nwosu 1988; Fairfull 1990; Dunnington and Siegel 1991a,b; Emmerson et al. 1991; Flock et al. 1991; see also references in tables 2, 3 of Sheridan 1981; swine: Sellier 1976; McLaren et al. 1987; sheep: Al Nakib et al. 1997). The term "heterosis" describes this phenomenon of hybrid vigor. F]S may experience heterosis for fitness-related traits because recessive deleterious alleles contributed by one parent are more likely to be masked by alleles contributed by a parent from a different population with different alleles. In addition, the offspring of crosses between populations that are genetically differentiated may be more heterozygous at loci where heterozygotes have superior fitness (Crow 1948; Paul 1992). Heterosis resulting from between-population crosses is sometimes said to "reverse" inbreeding depression within populations (Falconer and Mackay 1996, p. 253), but that description may not be entirely accurate. Recent theoretical work suggests that inbreeding depression may be caused by alleles of somewhat larger effect than heterosis, because inbreeding depression is largely independent of the strength of selection (Whitlock et al. 2000). It is also possible that crosses between genetically differentiated populations within species yield F]S that exhibit lower viability and fecundity than purebred individuals. This is called "outbreeding depression" or "hybrid breakdown" (Templeton 1986). Outbreeding depression always involves crosses between populations and occurs if individuals express genes that are not adapted to local conditions or if coadapted gene complexes are broken apart (Lynch and Walsh 1998, p. 225). Outbreeding depression may not be expressed until the F 2 generation or later, because F]S carry a haploid set of chromosomes from each parental line, and segregation and recombination only begin to break apart coadapted genes from a single line in the F 2 generation (Dobzhansky 1950, 1970; Lynch and Walsh 1998, p. 224). Studies of heterosis and outbreeding depression in situ in animal populations not associated with a hybrid zone are rare, perhaps because few zoologists have examined these phenomena at fine spatial scales (Waser 1993). -10-Studies of birds show that the reproductive output and survival of immigrants is often equal or inferior to philopatric individuals (Table 2.1), although Orell et al. (1999) found that immigrants showed greater reproductive effort at early stages of nesting. Theory suggests that differences in performance between immigrants and residents may be attributed to one or more nonexclusive factors (Table 2.2). However, evidence to disentangle these factors may be confounded in the absence of data from Fi and F 2 descendants of immigrants. Thus, we studied birds in a natural population assignable to groups by their pedigree: (1) natives were birds with a complete set of resident-hatched parents and grandparents; (2) immigrants were birds that did not hatch on Mandarte Island; (3) F)S were the offspring of an immigrant and a second-generation resident (a resident whose parents both hatched on Mandarte Is.); (4) F2s had an immigrant grandparent and resident grandparent in each of their maternal and paternal lines; (5) backcrosses had three resident grandparents and one immigrant grandparent. Based on prior ecological work and existing genetic theory, we then attempted to predict how the performance of immigrants and their descendants would be affected by the factors listed in Table 2.2. Several studies suggest site experience gives philopatric individuals an advantage over immigrants (factor 1, Table 2.2; Part 1995). For example, birds that are new to an area sometimes experience disadvantages when foraging and establishing territories (Greenwood 1980; Smith and Metcalfe 1997), identifying predators (Greenwood 1980), and attracting mates (Part 1994; Bensch et al. 1998). Exposure to local parasites and pathogens has also been shown to improve subsequent reproductive success (Brown and Brown 1992; Heeb et al. 1999). Thus, we expected that if site-experience had an effect on the birds that we studied, it should confer an advantage to natives over immigrants. Other factors potentially associated with performance differences among natives, immigrants, and their offspring include environmental heterogeneity, natural selection, random genetic drift and the potential for these to facilitate local adaptation and genetic divergence (factors 2-5, Table 2.2). For example, studies show that environmental conditions or patterns of energy allocation by parents may differ among populations and have lasting effects on development and breeding performance (factor 2, Table 2.2; Larsson and Forslund 1991; Rhymer 1992; Leafloor et al. 1998). Evidence for local adaptation (factor 3, Table 2.2) has been found in populations of birds separated by distances of several hundred kilometers. For example, bobwhite quail (Colinus virginianus) translocated from the southern United States to Ontario contributed to production of hybrids that were maladapted to northern winters (Clarke 1954). Nevertheless, because several potential sources of immigrants exist within a few kilometers of Mandarte Island, we expected that migration between populations was sufficiently frequent -11 -that immigrants and natives would be similar in their genetic adaptations and development. We also did not know if immigrants would be more or less inbred on average than natives of Mandarte Island (factor 4, Table 2.2). Thus, we had no a priori expectation that the performance of immigrants and natives would differ as a consequence of factors 2-4. However, we did expect that the reproductive performance of immigrants might reveal some evidence of heterosis (factor 5, Table 2.2), because inbreeding reduces the fitness of birds on Mandarte Island and the offspring of immigrants should be relatively outbred. Heterosis has yet to be reported as a result of natural immigration in birds. However, Westemeier et al. (1998) reported that the eggs of Greater prairie-chickens (Tympanuchus cupido) translocated to a remnant population in Illinois showed greater viability than the eggs of resident-hatched birds, ostensibly because translocated hens were less closely related to their mates. We also expected that if Fjs experienced heterosis, and only dominance interactions were contributing to that heterosis, then half of the performance gains shown by F]S should be lost in F2s due to segregation of chromosomes during meiosis (Lynch and Walsh 1998, p. 223). Epistasis can be shown to also contribute to heterosis when the performance of F2s is not intermediate to the average of F]S and the original parental lines {i.e., immigrants and natives in this study). Outbreeding depression is demonstrated when the performance of F2s is less than the average of immigrants and natives (Lynch and Walsh 1998, p. 225). Therefore, because we expected that heterosis might be observed in the performance of F)S, we also expected that F2s might perform worse than F]S and that the magnitude of this performance difference would depend on the role of dominance and types of epistatic interactions involved. 2.2 METHODS 2.2.1 Study site and field methods Mandarte Island is a small, rocky island about 6 ha in size that is located about 20 km north of Victoria, British Columbia, Canada. Song sparrows reside year-round on the island and inhabit the dense, mixed shrubs that cover roughly 30% of the island. The remainder of the island is composed primarily of meadows and rock beds, which are used for nesting by gulls and other seabirds (Drent et al. 1964). Since 1975, the survival and reproductive success of song sparrows has been monitored every year except 1980 (Smith 1981; Arcese et al. 1992; Keller 1998). From 1981 to 2000, unhanded birds were mistnetted and assigned a unique combination of colour bands. Thus, we were able to identify all immigrants from 1982 -12-to 2000. The territories of mated and unrnated males were monitored every 7-10 days throughout the breeding season to check for newly settled females. Sightings of nonterritorial males were also recorded. Mated pairs were visited every 5-7 days from March or April through July or August to monitor breeding activity. An effort was made to locate all nests of every pair on the island. Song sparrows produced from one to seven nests each season, although two or three was typical. All known nests were monitored regularly and nestlings were colour-banded, usually 6 days post-hatch. Offspring were counted again on approximately day 24 by listening for begging calls, observing parental feeding behaviour, and by sight. Birds were categorized as surviving to independence if they were identified by the observation of colour bands on or after day 24, although some birds received parental care to about 30 days of age. A few emigrants from Mandarte Island survived to breed on other islands locally, and three emigrants from Mandarte Island were identified up to 30 km away. Despite banding on several nearby islands since 1988, the origin of only one immigrant, banded as a nestling on an island located about 3 km to the east, is known. Other dispersal events between neighboring islands have also been recorded (A. B. Marr, L. F. Keller, and P. Arcese, unpubl. data). Thus, the islands surrounding Mandarte Island are a likely source of immigrants, but some immigrants may have traveled further. We are also fairly confident that birds identified as irnmigrants in this study were hatched off Mandarte Island. First, we found all but one or two nests in each year of the study and the fledglings from those unfound nests were mistnetted and banded in the two weeks that their parents fed them post-fledging. Second, many immigrants carry alleles at microsatellite loci that are distinct from those present on Mandarte Island (Keller et al. 2001). 2.2.2 Pedigree groups and inbreeding calculations The results of five planned comparisons are presented for each table of survival and reproductive success. These comparisons were chosen a priori to examine the ecological and genetic factors described in the introduction. Using the terminology "Im-Na mean" to denote the average of immigrants and natives, the five comparisons are between (1) immigrants and natives (listed in the tables as lm - Na), (2) F]S and the Im-Na mean (F, - M), (3) F2s and F]S (F2 - Fi), (4) F2s and the average of F|S and the Im-Na mean (F2 - (Fi + M) / 2), and (5) F2s and the Im-Na mean (F2 - M). The latter four planned comparisons were nonorthogonal. Therefore, p-values for those four comparisons were adjusted by the Bonferroni procedure by multiplying each of these p-values by 4 to maintain an experiment-wise error rate of a = 0.05 (Sokal and Rohlf 1998, p. 239). -13-No irrimigrant was observed to have mated with another irnmigrant in the study population. Only five Frirrirnigrant pairs were observed, and we excluded their offspring from analyses because so few became adults (N=2 females, N= 3 males). To maximize sample size, we also grouped F] offspring of male immigrants with F i offspring of female immigrants, and we disregarded the sex of irnmigrant parents when classifying birds as F2s or as backcrosses. We followed Keller (1998) in using the Stevens-Boyce algorithm (Boyce 1983) in PEDSYS (Southwest Foundation for Biomedical Research, San Antonio, TX) to calculate Wright's coefficient of inbreeding,/ for individuals hatched on Mandarte Island. We assumed immigrants to Mandarte Island were unrelated to each other and to birds hatched on the island. This assumption seems fairly robust, because there are dozens of potential source populations in the area, some with hundreds of individuals. 2.2.3 Performance analyses Survival analysis — We used a discrete-time proportional-hazards model (Heisey 1992; Keller 1998) to estimate the survival probabilities of birds by pedigree group that hatched between 1981 and 1999 inclusive (Table 2.3). Individuals were counted as alive in a particular year if they were sighted after April 1. Birds involved in a supplemental feeding experiment in 1985 were excluded from this and all other performance analyses because the experiment had unnatural effects on their survival and reproductive success (Arcese and Smith 1988). Survival data were analyzed using the GENMOD procedure in SAS and by specifying a complementary log-log tranformation and a binomial error distribution (SAS Institute 1997). This model is appropriate for left-truncated data and makes no assumption about the dependence of the hazard on time (Agresti 1990, p. 194). Birds alive in 2000 were right-censored, because they contributed information about survival but not mortality (Heisey 1992; Keller 1998). To estimate juvenile survival from independence to age 1, we included only birds that were sighted at or after 24 days of age. An exploratory analysis showed that year of hatch and lay date in the season helped to predict juvenile survival. However, survival was unrelated to clutch size at hatch, the number of young in the brood that survived to independence, or the total number of full-siblings that survived to independence in the year of hatch. Thus, we presented analyses here that controlled statistically for the effects of year and lay date on survival from independence to age 1. When comparing the performance of adults, we included immigrants in the analyses for comparative purposes. Immigrants were assumed to be age one in the year that they were first identified - 14 -on the island. Because birds in this and several nearby islands show strong philopatry to the population after natal dispersal, this seems to be a reasonable assumption. We determined the gender of birds alive at age 1 by their morphology and behaviour (Arcese 1989). Sex differences in survival and reproductive success were found and sex interacted with pedigree group in all analyses. Therefore, we presented separate analyses of performance for adult males and females. Given the aims of the present analyses, it is unclear whether each individual or each family should be considered an independent datapoint. Exploratory analyses suggested that using only one individual from each clutch or pair of parents increased the variance of least squares estimates of performance for resident-hatched individuals (because of reduced sample sizes) but had little effect on the means of those estimates. Thus, the analyses presented in this paper use all available individuals. Exploratory analyses also showed that, for birds age 1 and older (adults), survival depended on year of hatch and age, but was unrelated to lay date, clutch size, the number of young in the clutch raised to independence, or the total number of siblings raised to independence by the mother or father in the year of hatch. Therefore, analyses of adult survival were stratified by pedigree group and year-age group. Hence, our survival analyses of adults compared the viability of birds in different pedigree groups using birds that were the same sex, same age, and hatched in the same year. Strata for which all individuals survived or died were removed from analyses because they did not contribute information about the difference in survival among pedigree groups (Heisey 1992). As a result, not all individuals studied could be used in survival analyses, and sample sizes reflect the number of individuals contributing to the analysis, not the total number present in the population. This also explains why the number of individuals in the survival analyses differs slightly from those in analyses of reproductive success. Seasonal reproductive success — Using breeding adults hatched from 1981 to 1999 that bred from 1982 to 2000, we studied four measures of seasonal reproductive success (SRS): laying date, clutch size, number of clutches, and percent survival of eggs to independence (Table 2.4). These measures were chosen because exploratory analyses suggested that they were largely independent. Reproductive success of song sparrows on Mandarte Island is influenced strongly by environmental conditions and population size (Arcese et al. 1992). Thus, we incorporated year as a categorical variable before comparing birds in different pedigree groups to minimize effects of these factors on the traits of interest. We verified the absence of discernable year effects by plotting residuals for each analysis against population size, sex ratio, and year, and checking that the residuals were randomly distributed. We also explored if sibling competition or measurable parental effects influenced individual reproductive success, but found that -15-individual SRS and lifetime reproductive success (LRS) varied independently of clutch size at hatch and the number of siblings raised to independence from that clutch, the total number of full-siblings that survived to independence in the year of hatch, and date of hatch. Significance levels for analyses of SRS were determined by bootstrapping, assuming that each bird constituted an independent observation. Bootstrapping is a well-accepted method for obtaining standard errors of complicated functions (Sokal and Rohlf 1998, p. 823) and was necessary in our case because many birds produced multiple nests or bred in successive years, but different observations for the same bird are not independent (Keller 1998). By bootstrapping, we alleviated potential problems of nonindependence by selecting with replacement N individuals at random from the actual data of sample size N. For each bird chosen, all data from all nests contributed by that individual were used to generate the bootstrap sample. An analysis of variance (ANOVA) was then performed on each bootstrap sample by specifying year, age, and pedigree group as categorical predictors of each measure of reproductive success. The least square means for the five pedigree groups were saved and the bootstrap routine was repeated 5000 times. Five planned comparisons were then assessed by paired t-test of the least square means. Because we sampled with replacement, some individuals were represented more than once and some individuals from the actual data were not represented in each bootstrap sample. This resampling procedure allowed us to calculate the desired t-statistic by dividing the difference in the least square estimates of the actual data by the bootstrap estimate of the standard error of the least square difference, because the latter equals the standard deviation of the bootstrapped differences (Sokal and Rohlf 1998, p. 823). Only three of 303 females failed to lay eggs in each year that they were recorded as adults. Males are primarily monogamous and were categorized as breeders if they defended a territory with a female during the period that the female laid eggs in at least one nest. Some males failed to breed in each year of this study, particularly those that were age 1 or more than 4 years old, or those that lived in years when adult males greatly outnumbered females. Therefore, we estimated the percent of males that bred for the various pedigree groups by comparing same-age birds alive in the same year (Table 2.4). Probability of breeding was analyzed using a generalized linear model for a repeated categorical variable following Agresti (1990, p. 411). The analysis was run using GENMOD in SAS with a logit transformation, binomial error distribution, and an exchangeable correlation structure (SAS Institute 1997). Strata in which all individuals bred or failed to breed were removed from analyses because they did not contribute information about differences among pedigree groups (Heisey 1992). -16-Lifetime reproductive success of breeders — Analyses of LRS used birds hatched from 1981 to 1996 that bred in at least one year from 1982 to 2000 (Table 2.5). Thirteen males and two females that hatched in 1996 or earlier were still alive in spring 2001 but were included in our analyses. These birds were five or more years old in 2001, and thus LRS of these individuals should be close to their final values (Nol and Smith 1987). Estimates of the least square mean number of independent offspring produced by individuals in five pedigree groups were obtained by ANOVA adjusted for year of hatch (categorical variable), because LRS depends on population density and other environmental factors in the year of recruitment (Hochachka et al. 1989). Raw data were transformed using v(LRS + 0.5) to achieve a normal error structure and homoscedasticity. We used the Box-Cox method to select this power transformation by maximum likelihood (Draper and Smith 1998, p. 279). It is commonly used for data with a Poisson distribution that includes counts with zero values (Sokal and Rohlf 1998, p. 415). About 12% of nests were found after the eggs had hatched or had failed after egg-laying. For these nests, clutch size was assumed to equal the number of eggs or individuals found when the nest was discovered. This convention underestimated slightly the true clutch sizes produced by some individuals. However, had we discarded all information for an individual when some information for a particular nest was incomplete, birds that produced many clutches, such as long-lived birds, would have been preferentially excluded from analyses. This would have resulted in a greater bias than the slight underestimate of some clutch sizes. 2.3 RESULTS 2.3.1 Immigration rate Immigration was female biased, with immigrants accounting for 16 of 303 females (5.3 %) and 8 of 416 males (1.9 %) recorded as adults on Mandarte Island (log-likelihood ratio test for goodness of fit, G = 5.663, df = 1, p = 0.017). Zero to three female immigrants arrived annually during the 19-year period from 1982 to 2000, whereas only one male immigrant arrived in eight of 19 years. Four male immigrants remained unmated throughout their lifetimes. The fraction of birds that were immigrants was correlated negatively with population size (r = -0.81, Ny e a r s= 19, p < 0.001), but the number of immigrants and nonirnrnigrants in the population each year were unrelated (Fig. 2.1). The number of female immigrants that settled was unrelated to the number of other females in the population (Spearman rank test, rs = -0.14, N y e a r s = 19, p = 0.54), to the total number of males (rs= -0.15, N y e a r S = 19, p = 0.50), and to the number of unmated males (rs= -0.28, -17-Nyears = 19, p = 0.21). Immigration by males was also unrelated to the number of males and females in the population. Three of eight immigrant males arrived in years when male and female population size was higher than the median size. 2.3.2 Performance of immigrants The performance of female immigrant song sparrows on Mandarte Island differed from natives in several ways. Female immigrants bred eight days later than natives, on average, and tended to produce fewer clutches, but they also raised more independent offspring per egg laid (Table 2.4). However, clutch size and adult survival in female immigrants and natives were similar (Tables 2.3, 2.4) and, during their lifetimes, female immigrants raised as many independent offspring as natives (Table 2.5). The performance of male immigrants also differed from male natives for some traits but was not consistently better or worse; male immigrants survived better (Table 2.3), but failed to breed more often than natives (Table 2.4). 2.3.3 Performance of F]S The performance of F\S resembled the averaged performance of immigrants and natives (i.e., the Im-Na mean) for several measures of SRS, but differed significantly in two instances (Table 2.4). Female F]S bred earlier and male F]S were more likely to breed. Differences in adult survival and LRS between F|S and the Im-Na mean were not significant for females or males (Tables 2.3, 2.5). 2.3.4 Performance of F2s The average inbreeding coefficient of F2s was comparable to natives (e.g., for birds included in our analyses of survival to age one;/F2 = 0.076 ± 0.102 n = 67,/N a = 0.066 ± 0.059 n = 853, t = 0.088, p = 0.93). Because FiS are outbred (/FI - 0), we expected that F2s might perform somewhat worse than F]S based solely on the documented effects of inbreeding in this population. Indeed, adult male F2s survived 35.1% worse than Fjs annually and breeding male F2s raised only about one-third as many independent offspring as F]S over their lifetime (Tables 2.3, 2.5). However, differences in SRS of F i and F 2 males were small and nonsignificant (Table 2.4). We also found that juvenile survival in F2s was 46 % lower than in FiS (Table 2.3). Juvenile survival of female F2s may have been particularly poor, because just four of 18 F2s (22.2 %) alive at age 1 were females as compared to 126 of 290 natives (43.4 %; log--18-likelihood ratio test for goodness of fit, G = 3.366, df = 1, p = 0.067). Unfortunately, this small sample of female F2s (N = 4) precluded reliable estimation of their breeding performance and survival as adults. To determine if differences in performance between male F]S and F2s might have resulted from epistatic interactions (see Introduction), we also compared the performance of F2s to: (1) the average of Fis and the lm - Na mean (F2 - (Fi + M) / 2) and (2) the lm - Na mean (F2 - M). Male F2s had lower survival as adults and lower LRS than the average of F|S and the Im-Na mean (Table 2.3, 2.5). Male F2s were also estimated to have survived 26.7% worse than the Im-Na mean and have 56.4 % fewer offspring (Table 2.3, 2.5), but these F 2 - M differences were not significant. 2.4 DISCUSSION Settlement of immigrant song sparrows on Mandarte Is. was relatively constant over the years and female biased, but immigration rates of each sex were unrelated to the number of available mates or same sex competitors. Immigrants represented a larger fraction ofthe population when there were fewer individuals present. 2.4.1 Performance of immigrants After factoring out environmental and population effects, our results suggest that the LRS of immigrants and natives was similar overall (Table 2.5). However, male immigrants survived well compared to natives of the same age, but relatively few bred each year as adults (Table 2.3, 2.4). Female immigrants bred later and produced slightly fewer clutches seasonally than natives, but raised more offspring per egg laid (Table 2.4). At least three explanations for differences in reproductive effort and output between immigrants and natives exist. First, birds originating from other habitats or populations may optimize their reproductive success in different ways for developmental or genetic reasons. For example, as compared to natives, immigrant males may be more likely to trade off access to females for their own survival, and immigrant females may lay later and fewer clutches but devote more to parental care than native females. Second, the pattern of performance differences between immigrants and natives may reflect compensating ecological effects. For example, lack of site-experience could make immigrant males less desirable as mates if they are unable to gain access to the best territories; however, remaining unmated or settling in lower-quality habitats might reduce the energy required for parental care and male-male competition, thereby leaving immigrants with more to invest in their own survival. For females, lack of -19-site-experience could be associated with energy constraints causing immigrants to lay later and fewer clutches, but result in some compensation as offspring would be raised during periods of milder climatic conditions. Third, any disadvantage associated with lack of site-experience in immigrant females might be alleviated somewhat by heterosis in their offspring. One way to disentangle these hypotheses would be to use data on age-related changes in immigrant and native performance. We would expect, for example, that performance differences due to lack of site-experience and associated ecological compensation would diminish among older birds. In contrast, the performance of immigrants and residents might change little with age when patterns have a developmental or genetic basis. Unfortunately, sample sizes of immigrants surviving beyond age 1 were too small to consider in the current analysis, but we were able to provide some evidence suggesting that heterosis has an effect by studying F]S and F2s after independence from parental care. 2.4.2 Performance of F ] S Evidence that F]S experienced heterosis is supported by the observation that they performed well compared to other pedigree groups for most performance measures (Tables 2.3, 2.4, 2.5) and sometimes did substantially better than the Im-Na mean. For example, Fjs survived well from independence to age 1 compared to other resident-hatched individuals (Table 2.3). Adult female Fjs bred early when compared to the average of immigrants and natives, and male FiS were considerably more likely to be mated (Table 2.4). In an analysis including only breeding individuals, female F]S were estimated to have had 27.1% more offspring than the Im-Na mean, and male FiS were estimated to have had 30.2% more, but these LRS differences were not significant (Table 2.5). Although some differences (such as these for LRS) were not statistically significant, we mention the results because their large magnitude suggests biological importance if confirmed statistically by additional data. Small sample sizes here and elsewhere limited the power of statistical tests. It is often assumed that small amounts of gene flow will prevent heterosis. Immigrants to Mandarte Island result in considerable amounts of gene flow (Keller et al. 2001), and thus heterosis may seem an unlikely explanation of our results. However, recent theoretical work has shown that heterosis can be substantial even in the presence of appreciable rates of gene flow (Whitlock et al. 2000). Using an infinite-island model and Wright's distribution of equilibrium allele frequencies, Whitlock et al. (2000) showed that F]S produced from crosses between small populations connected by low to moderate levels -20-of migration might be expected to show positive heterosis of several and sometimes tens of percentage points. Heterosis seems to be a better explanation for differences between Fts and the Im-Na mean than alternatives such as different parental investment by immigrants or ecological compensation. Despite that lasting influences of natal environment on adult fitness traits are known (Schluter and Gustafsson 1993; Griffith et al. 1999), many studies show that such effects are absent or decay as growth proceeds and dissipate before adulthood (Schifferli 1973; Smith and Dhondt 1980; Price and Grant 1985; Roulin et al. 1998). Second, as in an earlier study (Hochachka 1993), our own exploratory analyses yielded no evidence that natal environment affected adult performance in the system that we studied (see Methods). Offspring survival and reproductive success were unrelated to clutch size at the time of hatch, the number of siblings raised to independence in a clutch, or to the number of full-siblings that survived to independence. Following Arcese and Smith (1985) and Hochachka (1990), we also found that survival to age 1 was related negatively to hatch date. But because we included hatch date as a covariate in our analysis, juvenile survival was unaffected by date. Thus, although we had no direct estimates of maternal investment in eggs or young, the available data did not suggest that ecological compensation or differences in parental care between immigrants and natives explain the performance of their offspring after independence in this population. 2.4.3 Performance of F2s Additional evidence for the existence of heterosis in this system comes from analysis of F 2 performance. According to genetic theory, if the performance of F]S is enhanced by heterosis, some of that heterosis will be lost in the F2 generation (Lynch and Walsh 1998, p. 223). This occurs because half of the heterozygosity gained by F,s should be lost in F2s due to segregation of chromosomes during meiosis (Ehiobu and Goddard 1990). Thus, if heterosis improves the performance of F]S, we would expect F2s to perform worse than F]S, and we found that our results were generally consistent with this expectation. Too few female F2s survived to adulthood to analyze in detail their performance relative to Fis . However, we found that juvenile F2s survived worse than F]S (Table 2.3) and male F2s survived worse and produced fewer independent offspring than male F]S over their lifetimes (Tables 2.3, 2.5). Although we expected F2s to perform worse than F]S, we were surprised by the large magnitude of differences observed. Juvenile and adult male F2s survived only about half as well as F]S (Table 2.3), and male F2s that bred had only one-third the lifetime reproductive success of F)S (Table 2.5). According to -21 -genetic theory, the performance of F2s should be intermediate to the average of F,s and the Im-Na mean (see introduction), unless epistasis also contributed to the heterosis observed in F,s or a breakup of coadapted gene complexes occurred in F2s (Lynch and Walsh 1998, p. 224). Our analyses suggested that the survival and LRS of male F2s was significantly worse than the average of F|S and the Im-Na mean, but evidence for a breakup of coadapted gene complexes was inconclusive; whereas the survival and LRS of male F2s appeared lower than the Im-Na mean, these contrasts relied on small sample sizes of immigrant males and were not statistically significant. Elsewhere, it has been shown that in the F 2 generation selection can occur against individuals in whom locally coadapted gene complexes have been broken apart by segregation and recombination (Dobzhansky 1950, 1970; Wallace and Vetukhiv 1955; Lynch and Walsh 1998, p. 223). In addition, populations exposed to the same environment can become genetically differentiated by drift alone (Templeton et al. 1976; Templeton 1981, 1986; Waser and Price 1985; Galen et al. 1991). Templeton (1981) showed that different and incompatible gene arrangements arose in separate parthenogenetic strains of Drosophila derived from a single ancestral population, even though these strains were raised in the same environment at the same time. Thus, F 2 outbreeding depression is also a plausible outcome of crosses between populations in which combinations of alleles differ due in part to genetic drift or in which genes are identical but coadapted gene complexes have become fixed in different arrangements on chromosomes by chance. Without invoking either heterosis in Fis, a breakup of coadapted gene complexes in F2s, or both phenomena, we find no other reasonable explanation for the large performance differences between F]S and F2s that we observed. Experience with site will be identical in Fjs and F2s. Natal environment, resource provisioning, and other parental effects with a developmental or genetic basis should be similar between Fis and F2s unless immigrant females confer large, lasting advantages to Fi offspring. Finally, our analyses of survival and reproductive success accounted for year effects that might otherwise influence our result if F2s were hatched more often in periods of high population density or by chance when environmental conditions were poor. Evidence for genetic drift in the system that we studied was also suggested by our recent analyses of genetic differentiation at eight microsatellite loci in the 15-km2 region around Mandarte Island. We found moderate but significant variation in allele frequencies, exceeding that estimated with the same methods between five recognized subspecies of song sparrows in the San Francisco Bay (unpubl. data; Chan and Arcese, 2001). Song sparrows on Mandarte Island also have shorter tarsi than birds on nearby -22-islands (unpubl. data), and natural selection on morphological traits has been demonstrated (Schluter and Smith 1986). Other studies have found evidence of large performance differences between F]S and F2s. In a wide range of taxa, laboratory breeding experiments conducted with animals obtained recently from the wild have shown that FpIs exhibited normal or heterotic performance, whereas the performance of F2s was inferior to purebreds due to a breakup of coadapted gene complexes (e.g., copepods: Burton 1986, 1987, 1990; echinostomes: Trouve et al. 1998; Drosophila: see references in table 5.6 of Endler 1977; grasshoppers: Shaw 1981; Shaw et al. 1986; salmon: Gharrett and Smoker 1991; Gharrett et al. 1999; newts: Callan and Spurway 1951; Spurway 1953; mice: Adkins et al. 1991). 2.5 CONCLUSIONS Several studies of individually-marked birds have demonstrated that immigrants to a population or long-distance dispersers from a population have lower survival or reproductive output (Table 2.1). Given the high immigration rates reported in those studies, site experience appears to have been a key factor favouring the performance of philopatric individuals. In the system that we studied, immigration rates were lower than observed in previous studies conducted elsewhere and inbreeding depression has been documented (Keller et al. 1994; Keller 1998). Thus, we were not surprised to find evidence that disadvantages experienced by immigrants may have been alleviated by heterosis in their offspring. However, contrary to our expectations, we could not dismiss the possible role of outbreeding depression after observing the large magnitude of differences in survival and LRS between FiS and F2s. Overall, our results suggest that drawing conclusions about how much gene flow results from immigration may be misleading without monitoring performance of immigrants and their descendants over at least three generations. However, to our knowledge, few studies of natural populations have tracked the contribution of immigrants beyond the F i generation. 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Whitlock, and an anonymous reviewer for helpful comments on earlier drafts of this article. J. R. Cary, P. M. Crump, and B. Yandell generously provided advice about data analyses. Many people helped us collect the data presented here, most recently: A. K. Davis, D. A. Grosshuesch, W. Jess, R. Landucci, B. T. Martinez, T. Poldmaa, and T. Sullivan. The Tsawout and Tseycum First Nations bands kindly allowed us to work on Mandarte Island. Essential financial support for this research was provided by a grant to P. Arcese from NSF (IBN 9458122) and grants to A. B. Marr from the NSF Predoctoral Fellowship Program, Sigma Xi Scientific Research Society, the Association of Field Ornithologists, the. Western Bird-Banding Association, and the American Museum of Natural History Chapman Fund. -31 -2.8 FIGURES AND TABLES Figure 2.1 Number of immigrants versus nonirnmigrants in the Mandarte Island song sparrow population each year from 1982 to 2000 (r = -0.226, N y e a r s = 19, p = 0.352). - i 1 1 1 1 r 0 20 40 60 80 100 120 140 160 Population size of nonimmigrants -32-Table 2.1 Studies of wild birds that compared the performance of immigrant (I) and resident-hatched (R) individuals or long-distance (L) and short-distance (S) dispersers. I, R, L, and S indicate groups reported to perform better (p < 0.05), wherein larger clutch and brood size, higher survival, and earlier laying indicated better performance. A dash indicates no significant difference reported for the trait. NA indicates data were unavailable. LRS refers to lifetime reproductive success. Immigration rates (%) for females (F) and males (M) were taken from the text or estimated from data in figures for each sex and species when possible. All species except savannah sparrows typically raise single broods. Species Females Males Trait Blue tits - - Loca l adult survival rate Pants caeruleus - - Lay ing date 8 3 % F, 67% M approx. R - Clutch size Jul l iard et al. 1996 - - Probabil i ty o f f ledging at least one young - - Fledglings/egg from nests wi th fledglings R - Probabil i ty that a f ledgling recruits local ly Great tits (o fV l ie land) R N A Loca l survival rate o f first year breeders Pants major R ' N A Philopatry o f adults after breeding 2 7 % F, 15% M - N A Breeding recruits by first year breeders Verhulst & van Eck 1996 R - L R S o f breeding recruits by breeding birds Great tits (of Wytham, U K ) - - Loca l survival rate o f breeding adults 54% F, 4 5 % M approx. R - Lay ing date C lobe r t e /a / . 1988, - - Brood size per nest McC lee ry & Clobert 1990 R R Loca l recruits per nest Northern willow tits - - Loca l survival rate o f breeding adults Parus montanus - R Lay ing date 7 6 % F, 6 3 % M I - Clutch size Ore l l etal. 1999 I - Hatchl ings - - Fledgl ings R - Loca l recruits from nests with fledglings R - Probabil i ty that a f ledgling recruits local ly -33 -Table 2.1 continued Great reed warblers - - Life span (in study area) Acrocephalus arundinaceus - - Spring arrival date 55% F, 53% M - - Territory quality Bensche/a/. 1998 NA R Song repertoire size NA R Lifetime number of mates - R LRS of fledglings (includes nonbreeders) - R LRS of local recruits Collared flycatchers - - Local adult survival rate Ficedula albicollis NA - Spring arrival date of yearlings 62% M approx. NA R Speed of acquiring a mate as a yearling Part 1991 (study compared NA R Probability of acquiring a mate as a yearling pairs of sisters differing - R Nest-box rank of yearlings in natal dispersal distance) - - Laying date of yearlings Part 1994 (study compared S - Clutch size of mated yearlings immigrant and resident S - Fledglings by mated yearlings males) - - Breeding recruits by mated yearlings S NA Fledglings/egg by mated yearlings - NA Clutch size of second year birds - NA Fledglings of second year birds Savannah sparrows - - Age at first breeding Passerculus sanwichensis - - Lifetime number of nests <29% F, <27% M - - LRS of eggs Wheelwright & Mauck 1998 - - LRS of fledglings - R LRS of recruits -34-Table 2.2 Factors potentially contributing to differences in survival and reproductive success between immigrants and natives. Factors 1. Lack of site experience might affect the performance of individuals hatched in different populations. 2. Environmental conditions experienced in early life might differ among populations and have lasting effects on development. 3. Immigrants might have unique genetic adaptations or life-history strategies. 4. Individuals from some populations might be more inbred than those from other populations. 5. The performance of immigrant descendants might show benefits of heterosis. - 3 5 -Table 2.3 Results of three discrete-time proportional hazards models comparing survival rates of juveniles of both sexes combined, adult females, and adult males in five pedigree groups (see Methods). Table shows the least square mean estimates of percent annual survival and associated 95% confidence intervals in parentheses; N gives the number of individuals in each pedigree group. Significance levels for planned comparisons appear in five columns on the right side of the table. The only comparison in the analysis of juvenile survival was between F2s and F\S because no data on the survival of juvenile immigrants were available. P-values were adjusted by Bonferroni correction to maintain an experiment-wise error rate of a = 0.05 (see Methods). LS mean P Sex Natives Immigrants F,s F2s Backcrosses Im-Na F,-M F2-F, F2-(F,+M)/2 F2-M Juveniles 44.1 (38.8-49.3) - 55.1 (43.3-65.5) 30.0 (17.6-43.4) 42.1 • (34.4-49.6) — — 0.003 N 853 93 67 266 Females 64.5 (56.0-71.7) 54.1 (29.1-73.6) 49.3 (27.7-67.7) 23.0 (0.9-63.0) 46.1 (29.3-61.3) 0.395 .1.000 1.000 0.698 0.478 N 111 13 18 4 32 Males 58.0 (50.2-65.0) 86.7 (62.8-95.7) 81.7 (70.4-89.0) 53.0 (30.9-70.9) 61.6 (49.8-71.3) 0.008 1.000 0.032 0.048 0.221 N 147 7 26 14 56 -36-Table 2.4 Seasonal reproductive success of females and males in five pedigree groups as estimated by ANOVA. Least square mean estimates ± 95% confidence intervals (CIs) are given for laying date (January 1 = 1), number of clutches, and clutch size. Estimates of offspring survival (expressed as percentage of eggs per clutch that yield independent offspring) have asymmetrical 95% CIs in parentheses because the data were transformed by arcsin (sqrt (offspring / egg)) prior to analysis and then back-transformed for presentation. The sample size of breeders that contributed data to these analyses is given as A7^ breeders- The number of records of laying date for first clutch in a season and seasonal number of clutches laid is given as N iaying records- The total number of clutches used to estimate clutch size and offspring survival is given as ./Vciutch records- Significance levels for planned comparisons of breeding performance (five columns on the right side of the table) were estimated by bootstrap because some individuals contributed data in multiple years or for more than one nest in a year (see Methods). The percent of males that bred is also shown with its 95% CI; sample size for this analysis is given as N m a ] e s . P-values were adjusted by Bonferroni correction to maintain an experiment-wise error rate of a = 0.05 (see Methods). - 3 7 -Table 2.4 LS mean P Sex Trait Natives Immigrants F,s F2s Backcrosses Im-Na F , - M F 2 - F , F2-(F1+M)/2 F 2 - M Females Laying date 107.1 ± 3 . 2 115.1 ± 6 . 3 102.0 ± 3 . 7 111.4+11.0 103.3 ± 3 . 8 0.009 0.001 0.355 1.000 1.000 Clutches 2.41 ± 0 . 2 2 2.16 ± 0.31 2.67 ± 0 . 3 5 2.48 + 0.54 2.60 ± 0.26 0.081 0.174 1.000 1.000 1.000 Clutch size 3.31 ± 0 . 1 8 3.13 + 0.25 3.33 ± 0 . 2 1 3.40 ± 0 . 8 6 3.29 ± 0 . 2 1 0.159 1.000 1.000 1.000 1.000 % offspring/egg 23.1 (14.4-33.1) 35.2 (22.4-49.1) 36.5 (18.4-56.8) 19.1 (2.1-47.5) 29.2 (16.9-43.3) 0.044 1.000 0.992 1.000 1.000 N breeders 118 15 20 4 30 N laying records Nclutch records 266 618 33 75 47 124 6 14 64 156 Males Laying date 109.1 ± 3 . 4 105.5 ± 11.4 107.6 ± 4 . 5 115.4 ± 9 . 2 106.0 ± 4 . 2 0.528 1.000 0.422 0.521 0.384 Clutches 2.29 ± 0.20 2.90 ± 0 . 3 2 2.50 ± 0 . 2 7 2.26 ± 0 . 5 8 2.41 ± 0 . 2 6 O . 0 0 1 1.000 1.000 1.000 1.000 Clutch size 3.28 ± 0 . 1 2 3.00 ± 0 . 3 7 3.17 ± 0.17 3.11 ± 0 . 3 3 3.18 ± 0.15 0.124 1.000 1.000 1.000 1.000 % offspring/egg 23.1 (15.8-31.3) 24.0 (11.1-39.9) 29.2 (19.8-39.6) 16.8 (3.0-38.5) 25.1 (16.8-34.6) 0.904 1.000 1.000 1.000 1.000 % males that 65.2 31.3 84.2 69.2 57.5 0.054 0.017 0.914 1.000 0.841 bred (57.4-72.3) (9.3-67.1) (69.0-92.8) (44.2-86.4) (44.4-69.7) N breeders 113 4 23 12 41 N laying records N clutch records N males 236 496 157 12 33 8 • 73 171 27 29 55 14 102 218 57 -38 -Table 2.5 Lifetime reproductive success of breeding males and females in five pedigree groups, estimated by ANOVA as the adjusted least square mean number of independent offspring produced (see Methods). Asymmetry in the 95% CIs (parentheses) occurs because the raw data were transformed to accommodate their Poisson distribution, and the results back-transformed for presentation. N gives the number of birds in each pedigree group. P-values for planned comparisons are presented in the five columns on the right side ofthe table. P-values were adjusted by Bonferroni correction to maintain an experiment-wise error rate of a = 0.05 (see Methods). LS mean P Sex Natives Immigrants F,s F2s Backcrosses Im - Na F i - M F 2 - F , F 2-(F, + M)/2 F 2 - M Females 5.59 (4.61-6.65) 4.44 (2.50-6.87) 6.37 (4.16-9.02) 3.04 (0.43-7.33) 5.41 (3.69-7.43) 0.381 0.643 0.383 0.652 1.000 N 111 14 19 4 28 Males 4.45 (3.54-5.44) 8.44 (3.53-15.27) 8.39 (5.66-11.61) 2.81 (0.98-5.38) 4.98 (3.40-6.84) 0.168 1.000 0.004 0.011 0.128 N 110 4 19 12 38 -39-CHAPTER 3: PEDIGREE ERRORS BIAS ESTIMATES OF INBREEDING DEPRESSION By Amy B. Marr, Louis C. Dallaire, and L. F. Keller ABSTRACT When pedigrees of social associations are used to describe genetic relationships among individuals, errors arise when females mate outside their social unit. For example, in a long-term population study of song sparrows (Melospiza melodia), 28% of offspring were sired by extrapair fertilizations. In studies of other systems, pedigree errors can arise when parentage is assigned by likelihood-based statistics using molecular markers. Here, we use modeling to explore how pedigree errors influence estimates of inbreeding depression for the song sparrows on Mandarte Island. Adding random paternity error through simulation led to underestimates of inbreeding depression and increased the spread of confidence intervals on those estimates. Thus, prior studies on the song sparrows are likely to have underestimated the deleterious effects of inbreeding. The results presented in this paper provide one reason why inbreeding depression may be underestimated or go undetected in some studies of captive-bred and free-living wild animals. 3.1 INTRODUCTION An inbred individual is an individual whose parents are related. Inbred individuals often show lower survival rates and reproductive success than outbred individuals, a phenomenon called inbreeding depression. Studies of inbreeding depression are important, because inbreeding depression has been shown to reduce the persistence of small populations (Ralls, Ballou & Templeton, 1988; Saccheri et al. 1998; Crnokrak & Roff, 1999; Hedrick & Kalinowski, 2000; Keller & Waller, 2002). Conservation biologists are particularly interested in studies of plants and animals which estimate the magnitude of inbreeding depression, because such estimates are needed to evaluate population viability of various threatened and endangered species (Brito & Fernandez, 2000; Galimberti et al, 2001; Allendorf & Ryman, 2002). To estimate the magnitude of inbreeding depression, one must first calculate a measure called an inbreeding coefficient. An inbreeding coefficient (F) for an individual describes the probability that two alleles at a randomly chosen locus will be identical by descent from an ancestor shared by the mother and - 40 -father (Falconer & Mackay, 1996). Thus, individuals that are more inbred have higher inbreeding coefficients. One of the best ways to estimate inbreeding coefficients is by using a pedigree (Pemberton 2004). Inbreeding depression is then measured by comparing the survival and reproductive success for individuals with different inbreeding coefficients (see Methods). Here, the goal of our paper is to examine a problem that affects estimates of inbreeding depression from various studies. Namely, errors made when identifying the parents of some offspring will lead to errors in pedigrees and, therefore, errors in inbreeding coefficients and estimates of inbreeding depression. Pedigree errors can arise when pedigrees are based on social associations or when parents are identified with less than 100% certainty using molecular markers. In birds, social pedigrees (i.e., pedigrees based on behavioral associations between parents and offspring) usually differ from genetic pedigrees because females of most species lay some eggs sired by males other than the attending male. A recent review by Griffith, Owens & Thuman (2002) found that extrapair paternity (EPP) occurred in about 90% of bird species for which data were available. Even among socially monogamous birds, the mean EPP rate was over 11% and rates as high as 55% were reported. Errors in maternity assignment may occur for some species because females lay eggs in nests of conspecifics (Yom-Tov, 2001). Even when parentage is assigned with molecular markers using likelihood-based statistics (see Marshall et al., 1998), work on mammals and plants demonstrates that eliminating errors may be difficult without considerable labwork (Devlin, Roeder & Ellstrand, 1988; Marshall et al., 1999; Slate, Marshall & Pemberton, 2000; Constable et ai, 2001). As a result, parentage misidentification rates of 5 - 20% are routinely acknowledged and even higher rates of pedigree error can occur. The song sparrows on Mandarte Island have been the subject of intensive, long-term research on inbreeding effects in a natural population. Based on inbreeding coefficients calculated from the social pedigree, inbreeding depression was found to reduce performance of inbred song sparrows (Keller et al., 1994; Keller, 1998). Inbred juveniles in this population are less likely to live to age one, and those inbred birds that reach maturity raise fewer offspring annually and show poor survival as adults. While Keller (1998) noted that extrapair paternity might influence the accuracy of inbreeding coefficients for some individuals, only recent molecular work has shown that the error created by extrapair fertilizations is high. Using genetic data available for a four-year period, O'Connor (2003) found that 28% of offspring that were reared to independence from parental care had not been sired by the social father. In this paper, we use simulation modeling to understand how pedigree errors influence estimates of inbreeding depression for the Mandarte song sparrow population. Data for the song sparrows are -41 -typical of many long-term studies in natural systems because it is possible to estimate error rates in the social pedigree using molecular data collected in recent years, but DNA samples are not available for building a genetic pedigree in the early years of the study. We used simulation modeling because we anticipated that pedigree errors might have complex effects on estimates of inbreeding depression. If females choose social and extrapair mates at random with respect to kinship, then extrapair young should be assigned inbreeding coefficients using the social pedigree that are uncorrelated with their true genetic inbreeding coefficients. However, even for those individuals where the social father is the genetic father, errors in inbreeding coefficients are still possible when grandmothers or more remote ancestors engaged in extrapair matings. This latter source of error cannot be easily represented by explicit mathematical equations because it is likely to depend on demographic features of the population that change over time, such as the population size, the sex ratio, and the variance in reproductive success for breeding individuals. The general method of our simulation in this paper was to introduce additional paternity errors to the social pedigree to evaluate how paternity errors affect estimates of inbreeding depression. We then plotted the relationship between paternity error and our inbreeding depression estimates and used extrapolation to suggest the direction and approximate the bias in our inbreeding depression estimates that results from paternity identification errors. Details of our approach are given in the methods. 3.2 METHODS 3.2.1 Field methods and genetic data The population of song sparrows that we studied is resident on Mandarte Island, B.C., Canada. Every year from 1975 to 2003 except 1980, the breeding success and survival of all individuals was monitored. Nests were found and offspring were color-banded for individual identification, usually as nestlings (see Arcese et al., 1992 for details). Parentage was assigned to the male and female seen raising the brood. Immigrants to the population were identified by the absence of leg bands and were usually mistnetted for banding before they bred. Because all birds in the population were tracked and the generation time is relatively short (~2.3 years; Smith et al, in review), there exists an unusually deep social pedigree. The social pedigree for the Mandarte song sparrows, however, is not the same as the genetic pedigree. Using up to nine microsatellites and data from 471 offspring that survived to independence from parental care during 1993 - 1996, O'Connor (2003) found that EPP averaged 27.8% ± 4.4% and -42-EPP rates did not vary significantly across years. No cases of intraspecific brood parasitism were identified, thus suggesting that egg dumping is absent or rare in this population. 3.2.2 Calculation of inbreeding coefficients and inbreeding depression We began this study by calculating Wright's inbreeding coefficient, F, for each individual hatched on Mandarte Island by using the social pedigree and the INBREED procedure in SAS (SAS Institute, 1999). By necessity, the coefficients that we calculated were underestimated for some birds, because individuals at the start of data collection in 1975, those that hatched locally during the one-year lapse in data collection in 1980, and immigrants to the population were assumed to be unrelated. Therefore, to limit the bias in inbreeding depression estimates created by individuals with poorly known pedigrees, we followed Keller et al. (1994) and Keller (1998) in excluding individuals with unknown grandparents from statistical analyses, unless they were offspring of an immigrant. Analysis of juvenile survival— To determine the effect of inbreeding on survival probabilities of juvenile birds, we used a discrete-time proportional hazards model (Heisey, 1992; Keller, 1998). Data were analyzed using the GENMOD procedure in SAS with a complementary log-log transformation (i.e., log (-log(l-p))) and binomial error distribution (SAS Institute, 1999). The complementary log-log is the appropriate transformation for survival data that is interval censored, i.e. the exact time of death is not known but the time interval when death occurred is known. Survival of juveniles depends on population density and other environmental factors and is higher among birds that hatch early in the year. Thus, we also incorporated 'cohort' (year of hatch) as a categorical factor and 'laying date' (Julian date of clutch initiation) as a linear covariate in the survival analysis. Because we only know sex of juveniles if they survive to age one, we could not consider sex differences. The analysis included any birds that were locally hatched and sighted on or after 24 days of age. Individuals were counted as surviving to age one if they were seen on Mandarte Island after April 1st in the year following hatch; thus, our analysis describes local survival. We suspect that most birds died if they were not seen in the population at age one. Analyses of lifetime reproductive success (LRS) —We used generalized linear models to examine the effect of inbreeding on LRS. LRS was measured as the number of offspring that an individual raised to 24 days of age during its lifetime. Data were analyzed using the GENMOD procedure in SAS with a logarithmic transformation and negative binomial error distribution (Allison, 1999). Reproductive success of song sparrows on Mandarte Island is influenced by environmental conditions and population -43 -size (Arcese et al, 1992). Thus, we incorporated 'cohort' as a categorical variable. Separate analyses of LRS were performed for males and females to allow independent estimates of inbreeding depression by gender. Prior work on this population showed that seasonal reproductive success tends to decline after age two or three, and LRS of birds that are at least four years old should be close to their final values (Nol & Smith, 1987). Therefore, only birds hatched between 1981 and 1999 that bred from 1982 to 2003 were included in analyses. Inbreeding depression in juvenile survival and LRS of males and females was then calculated by using our statistical models to estimate trait values for outbred (F = 0) and inbred (F= 0.25) individuals. We then calculated the measure of inbreeding depression (8) as: 8 = (X/r= 0-Xf = 0.25) / Xjr= 0=1" (Xf = 0.25 / Xf = Q) where X^= 0 and XF= 0.25 are the trait value estimates (survival rate or number of offspring) for individuals with inbreeding coefficients of F= 0 and F= 0.25 respectively. We measured inbreeding depression by comparing individuals with F = 0 and F = 0.25 because this is the level commonly reported in experimental studies {e.g., Crnokrak & Roff, 1999). An individual withF= 0 has parents that are not related. An individual with F = 0.25 could be the offspring of a mating between full sibs or between a parent and offspring with no previous relationship deeper in the pedigree (Falconer & Mackay, 1996). 8 is a convenient measure of inbreeding depression because it describes the fractional decline in fitness due to inbreeding. For example, in this paper, if 8 = 0.15 then individuals with an inbreeding coefficient of F = 0.25 perform 15% worse than those with F = 0. Based on calculations from the social pedigree, inbreeding coefficients of adult song sparrows on Mandarte Island have averaged F= 0.06 in recent years (range of annual averages: F= 0.05 to F= 0.07 in 1993-2002). However, inbreeding coefficients for individual juvenile birds have ranged from F = 0 to F = 0.36, and birds with inbreeding coefficients as high as F = 0.31 have survived to adulthood (age 1). 3.2.3 The simulation Based on the comparison of social and genetic parentage for four years by O'Connor (2003), we assumed that an extrapair paternity error rate of 28% was naturally built into our entire social pedigree. From that starting point, we calculated the amount of error that we needed to add to the social pedigree to increase paternity error rates to 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%. We calculated the -44-amount of error that should be added to achieve those eight paternity error rates from the following equation: I = (D-X)/(1 -X) where I is the input paternity error rate for the simulation, D is the desired paternity error rate, and X is the paternity error rate in the social pedigree due to EPP. This equation was necessary because an estimated 28% of the random paternity error that we added to the social pedigree through simulation simply changed fathers that were already identified incorrectly as sires. For example, to achieve an EPP error rate of 40%, we would need to change 17% of the fathers in our social pedigree because I = (D - X) / (1 - X) = (0.40 - 0.28) / (1 - 0.28) = 0.17. For each year, we then created paternity errors in the social pedigree by randomly selecting the appropriate percentage of offspring (according to the equation above) and changing their social fathers to other randomly chosen adult males alive in that year. Simulations were repeated 1000 times at each of the eight arbitrarily-chosen paternity error rates from 30% to 100%. Based on prior work, randomly reassigning fathers seemed appropriate for five reasons: (1) females choose social mates at random with respect to kinship in this population (Keller & Arcese, 1998), (2) females that are related more closely to their social mate do not have a higher or lower fraction of extrapair young (O'Connor et al., in review), (3) females choose extrapair sires at random with respect to kinship (O'Connor et al, in review), (4) extrapair young survive as well as within-pair young to age one and show no difference in reproductive success or survival as adults (O'Connor et al, in review), and (5) many different males gained and lost EPPs. Estimates of the variance in male reproductive success using social parentage data were very similar to estimates based on genetic parentage data for the four years that we had genotype data (O'Connor, 2003). This occurred because males often lost some paternities in their own territory but gained paternities in other territories (O'Connor & L. F. Keller, unpubl. data). After creating random paternity errors in each run of our simulation, we then calculated inbreeding coefficients and analyzed inbreeding depression (8) for the three performance traits: survival of juveniles to age one and lifetime reproductive success of adult males and females. We kept the field observations of survival and reproductive success unchanged for all birds during all runs of our simulations; hence, our estimates of inbreeding depression changed only via error in inbreeding coefficients. -45 -3.2.4 Extrapolated estimates of inbreeding depression To provide a rough estimate of inbreeding depression in the absence of paternity error, we plotted simulation results and fit linear and cubic polynomial equations to our data by using least-squares regression (Figs. 3.1a, 3.1c, 3.1e). We then extended our best-fit regression lines back to the y-axis of each graph to approximate the magnitude of inbreeding depression at 0% paternity error. We showed the results of extrapolation for both linear and cubic polynomials because, by definition, extrapolation of more than a few percent beyond the available data can never be done with much certainty. Close inspection of the data, however, suggested that the cubic polynomial equations fit slightly better (i.e., datapoints in Figs. 3.1a, 3.1c, 3.le deviated less from the cubic polynomial fit than the straight line fit). 3.3 RESULTS 3.3.1 Effect of paternity error on estimates of inbreeding depression Juvenile survival — Adding paternity errors to the social pedigree reduced our mean estimate of inbreeding depression in juvenile survival and increased the confidence interval around that estimate. Thus, increasing paternity error also reduced our ability to detect statistically significant evidence of inbreeding depression in juvenile survival. For example, when we used the social pedigree to calculate inbreeding coefficients, we estimated that inbreeding depression in juvenile survival was 0.279 (p = 0.02; Table 3.1). When we increased the amount of paternity error in our pedigree from an estimated 28% (i.e., the error rate occurring naturally in the social pedigree) to 40%, our mean estimate of inbreeding depression in juvenile survival decreased to 0.203 (Fig.3.la) and most runs were not statistically significant (median p = 0.11; Fig. 3.1b). Lifetime reproductive success — The effects of increased pedigree error rates on inbreeding depression in male LRS were similar to the effects on juvenile survival in that the mean estimate of inbreeding depression in male LRS declined and the spread of the confidence interval increased. However, unlike analyses of juvenile survival, statistically significant evidence of inbreeding depression was still found in most simulations with a paternity error rate of 40%. For example, we estimated that outbred males reared an average of 4.3 offspring whereas males with F = 0.25 reared 1.5 offspring using the social pedigree; this corresponded to inbreeding depression in male LRS of 0.656 (p = 0.002; Table 3.2). When we increased error in the pedigree to 40%, our mean estimate of inbreeding depression in male LRS was 0.545 (Fig. 3.1c) and the median p-value was 0.02 (Fig. 3.Id). -46-Interestingly, creating paternity error in all offspring did not completely eliminate our ability to detect some indication of inbreeding depression in male LRS. For example, despite 100% paternity error, we estimated that inbreeding depression in male LRS still averaged 0.110 (Fig. 3.1c). Further analysis to understand this seemingly paradoxical finding revealed that randomizing fathers did not randomize inbreeding coefficients of all offspring; the offspring of an irnmigrant female were always assigned an inbreeding coefficient of F= 0 unless the immigrant female mated with one of her own sons or grandsons. When we performed a simulation excluding the offspring of immigrant females, randomizing all fathers randomized inbreeding coefficients of all individuals and the mean estimate of inbreeding depression in male lifetime reproductive success fell to zero. Unlike analyses of juvenile survival and male LRS, we could not show conclusive evidence of inbreeding depression in female LRS using the social pedigree. Although we estimated that inbreeding depression in female LRS was 0.369 (xF= 0 = 5.4 offspring, x F = 0.25 =3.4 offspring), the confidence interval on that estimate was large (95% CI: -0.097 to 0.637) and the difference was not quite statistically significant (p = 0.11; Table 3.2). Nonetheless, adding paternity error affected the analyses of inbreeding depression in female LRS in the same way that it affected analyses of juvenile survival and male LRS. Namely, the mean estimates of inbreeding depression decreased gradually, the width of the confidence intervals increased gradually, and the median p-value increased (i.e., became less statistically significant) until it levelled off at p = 0.5 (Figs. 3.1e, 3.If). 3.3.2 Extrapolated estimates of inbreeding depression By extrapolating from the simulations (see Methods), we see that true inbreeding depression is probably greater than we detected using the social pedigree. For example, if we use linear extrapolation to estimate inbreeding depression, our mean estimate of inbreeding depression would be 0.354 for juvenile survival, 0.858 for male LRS, and 0.494 for female LRS. Extrapolation using a cubic polynomial yields inbreeding depression estimates of 0.519 for juvenile survival, 0.853 for male LRS, and 0.553 for female LRS (Figs. 3.1a, 3.1c, 3.1e). 3.4 DISCUSSION Many studies of inbreeding depression are vulnerable to incorrect paternity assignments. For the song sparrows on Mandarte Island, adding random paternity errors to the social pedigree reduced pur inbreeding depression estimates on average and increased confidence intervals around those estimates - 47 -(Figs. 3.1a, 3.1c, 3.1e). By extrapolating from our simulations, we suggest that the true magnitude of inbreeding depression is probably much greater than we could detect from the social pedigree. Our best estimates are that juveniles with F = 0.25 are 52% less likely to survive to age one than outbred juveniles, males with F= 0.25 that survive to age one produce 85% fewer offspring than outbred males, and females with F = 0.25 that survive to age one produce 55% fewer offspring than outbred females (see Section 3.3.2). The gradual decline in average estimates of inbreeding depression with increasing error suggests that the inbreeding depression detected in prior studies (e.g., Keller et al, 1994; Keller, 1998) is real and not due to type II errors. However, our results also show that the significance levels (i.e., p-values) reported for analyses of inbreeding depression are not very robust to moderate amounts of paternity error. For example, despite the.large sample of birds in our analysis of juvenile survival, statistically significant evidence of inbreeding depression was eliminated in most simulations when we increased error from an estimated 28% (i.e., the error rate of the social pedigree) to 40% (median p = 0.11; Fig. 3.1b). Detecting inbreeding depression with the sample sizes typical of many studies is difficult even without paternity errors (Kalinowski & Hedrick 1999). To avoid a publication bias, it is therefore important for researchers to report estimates for inbreeding depression (8) or inbreeding load (B) irrespective of p-values. Our results also demonstrate that a simulation approach might reveal how the type of errors in the pedigree determines what is randomly possible and what is not. For example, we estimated that inbreeding depression in male LRS averaged 0.11 (rather than 0) in runs with 100% paternity error (Fig. lc). Because prior work on this population suggested that heterosis affects LRS among the male offspring of immigrants (Marr, Keller & Arcese, 2002), we realized that the lack of maternity error might be imposing this outcome. We hypothesized that randomizing fathers, but not mothers, might not randomize inbreeding coefficients of all offspring because the offspring of immigrant females were likely to remain outbred. This idea was supported by further analysis in which we found no indication of inbreeding depression with 100% paternity error when we excluded the offspring of female immigrants. 3.4.1 Considerations for applying this approach to other studies In other studies, the bias in inbreeding depression estimates may be influenced by aspects of pedigree structure that we did not need to model for song sparrows. For example, non-random mate choice and differential fitness of extrapair young may be important considerations. Although song -48 -sparrows do not use relatedness to select extrapair mates (O'Connor, 2003), wolves and mandarin voles engage in extrapair matings to avoid inbreeding (Sillero-Zubiri, Gottelli & Macdonald, 1996; Fadao, Tingzheng & Yajun, 2000), and a strong relationship between the genetic similarity of social mates and the occurrence of extrapair paternity has been found in three shorebird species (Blomqvist et al, 2002). If females tend to outbreed when choosing extrapair mates and extrapair young perform better, then fit individuals should be more outbred than suggested by inbreeding coefficients from a social pedigree. Thus, correcting for EPP errors could lead to even greater upward-revision of inbreeding depression estimates than if pedigree errors were random. Alternatively, it is also plausible that other combinations of mate choice and differential fitness of extrapair young might result in downward-revised estimates of inbreeding depression. 3.5 CONCLUSIONS Eliminating errors with molecular techniques is the best way to improve inbreeding depression estimates but it may require a large number of molecular markers. When it is not possible to eliminate pedigree errors, studies may report biased estimates of inbreeding depression or fail to detect inbreeding depression altogether. For the song sparrows on Mandarte Island, we found that adding random paternity errors led to underestimates of inbreeding depression. Variation in pedigree error rates may therefore be one of the factors contributing to variation in inbreeding depression estimates between populations and temporally within populations. 3.6 LITERATURE CITED Allendorf, F. W. & Ryman, N. (2002). The role of genetics in population viability analysis. In Population viability analysis: 5-17. Beissinger, S.R. & McCullough, D.R. (Eds). Chicago: University of Chicago Press. Allison, P. D. (1999). Logistic regression using SAS System: theory and application. Cary, NC: SAS Institute Inc. Arcese, P., Smith, J. N. M., Hochachka, W. M., Rogers, C. M. & Ludwig, D. (1992). Stability, regulation, and the determination of abundance in an insular song sparrow population. Ecology 73: 805-822. -49-Blomqvist, D., Andersson, M., Kiipper, C , Cuthill, I. C , Kis, J., Lanctot, R. B., Sandercock, B. K., Szekely, T., Wallander, J. & Kempenaers, B. (2002). Genetic similarity between mates and extra-pair parentage in three species of shorebirds. Nature 419: 613-615. Brito, D. & Fernandez, F. A. S. (2000). Metapopulation viability of the marsupial Micoureus demerarae in small Atlantic forest fragments in south-eastern Brazil. Anim. Conserv. 3: 201-209. Constable, J. L., Ashley, M. V., Goodall, J. & Pusey, A. E. (2001). Noninvasive paternity assignment in Gombe chimpanzees. Mol. Ecol. 10: 1279-1300. Crnokrak, P. & Roff, D. A. (1999). Inbreeding depression in the wild. Heredity 83: 260-270. Devlin, B., Roeder, K. & Ellstrand, N. C. (1988). Fractional paternity assignment: theoretical development and comparison to other methods. Theor. Appl. Genet. 76: 369-380. Fadao, T., Tingzheng, W. & Yajun, Z. (2000). Inbreeding avoidance and mate choice in the mandarin vole (Microtus mandarinus). Can. J. Zool. 78: 2119-2125. Falconer, D. S. & Mackay, T. F. C. (1996). Introduction to quantitative genetics. (4th edn). Essex, England: Longman Group Ltd. Galimberti, F., Sanvito, S., Boitani, L. & Fabiani, A. (2001). Viability of the southern elephant seal population of the Falkland Islands. Anim. Conserv. 4: 81-88. Griffith, S. C , Owens, I. P. F. & Thuman, K. A. (2002). Extra pair paternity in birds: a review of interspecific variation and adaptive function. Mol. Ecol. 11: 2195-2212. Hedrick, P. W. & Kalinowski, S. T. (2000). Inbreeding depression in conservation biology. Annu. Rev. Ecol. Syst.31: 139-162. Heisey, D. (1992). Proportional hazards analysis of left-truncated survival data. In SAS Institute, Inc., Proceedings ofthe 17th annual SAS user's group international conference: 1271-1276. Cary, NC: SAS Institute, Inc. Kalinowski, S. T. & Hedrick, P. W. (1999). Detecting inbreeding depression is difficult in captive endangered species. Anim. Conserv. 2: 131-136. Keller, L. F. (1998). Inbreeding and its fitness effects in an insular population of song sparrows (Melospiza melodia). Evolution 52: 240-250. Keller, L. F. & Arcese, P. (1998). No evidence for inbreeding avoidance in a natural population of song sparrows (Melospiza melodia). Am. Nat. 152: 380-392. Keller, L. F., Arcese, P., Hochachka, W. M., Smith, J. N. M. & Stearns, S. C. (1994). Selection against inbred song sparrows during a natural population bottleneck. Nature 372: 356-357. -50-Keller, L. F. & Waller, D. M. (2002). Inbreeding effects in wild populations. Trends Ecol. Evol. 17: 230-241. Marr, A. B., Keller, L. F. & Arcese, P. (2002). Heterosis and outbreeding depression in descendants of natural immigrants to an inbred population of song sparrows (Melospiza melodia). Evolution 56: 131-142. Marshall, T. C , Slate, J., Kruuk, L. E. B. & Pemberton, J. M. (1998). Statistical confidence for likelihood-based paternity inference in natural populations. Mol. Ecol. 7: 639-655 Marshall, T. C , Sunnucks, P., Spalton, J. A., Greth, A. & Pemberton, J. M. (1999). Use of genetic data for conservation management: the case of the Arabian oryx. Anim. Conserv. 2: 269-278. Nol, E. & Smith, J. N. M. (1987). Effects of age and breeding experience on seasonal reproductive success in the song sparrow. J. Anim. Ecol. 56: 301-314. O'Connor, K. D. (2003). Extra-pair mating and effective population size in the song sparrow (Melospiza melodia). MSc diss., University of British Columbia, Vancouver, B. C , Canada. O'Connor, K. D, Marr, A. B., Arcese, P. & L. F. Keller. In review. No evidence that female song sparrows (Melospiza melodia) choose extra-pair mates as a mechanism of inbreeding avoidance. Pemberton, J. (2004). Measuring inbreeding depression in the wild: the old ways are the best. Trends Ecol. Evol. 19: 613-615. Ralls, K., Ballou, J. D. & Templeton, A. (1988). Estimates of lethal equivalents and the cost of inbreeding in mammals. Conserv. Biol. 2: 185-193. SAS Institute. (1999). SAS/STAT(r) user's guide, version 8. Cary, NC: SAS Institute Inc. Sillero-Zubiri, C , Gottelli, D. & Macdonald, D. W. (1996). Male philopatry, extra-pack copulations and inbreeding avoidance in Ethiopian wolves (Canis simensis). Behav. Ecol. Sociobiol. 38: 331-340. Slate, J., Marshall, T. & Pemberton, J. (2000). A retrospective assessment of the accuracy of the paternity inference program CERVUS. Mol. Ecol. 9:801-808. Smith, J. N. M., Marr, A. B., Keller, L. F. & Arcese, P. (In review). Fluctuations in numbers: Population limitation, regulation, and catastrophic mortality. To be published in J. N. M. Smith (ed.), Biology of Small Populations: The Song Sparrows of Mandarte Island. Oxford University Press. Yom-Tov, Y. (2001). An updated list and some comments on the occurrence of intraspecific nest parasitism in birds. Ibis 143: 133-143. 3.7 ACKNOWLEDGEMENTS P. Arcese, J. N. M. Smith, M. C. Whitlock, K. Ritland, D. Schluter, J. M. Reid, R. Frankham, K. D. O'Connor, and S. E. Runyan provided helpful comments on earlier drafts. The Tsawout and Tseycum First Nations bands kindly allowed us to work on Mandarte Island. Many people helped collect the field data presented here, including most recently S. D. Wilson, J. M. Reid, A. Johnston, D. Dagenais, R. M. Landucci, K. D. O'Connor, S. E. Runyan, and C. A. Saunders. Support for this research was provided by grants to P. Arcese from NSERC of Canada, and to A. B. Marr from a Josephine T. Berthier Fellowship, the NSF Pre-doctoral Fellowship Program of the US, a Gene Namkoong Family Scholarship in Forest Genetics, a Bert Hoffmeister Scholarship in Forest Wildlife, Sigma Xi Scientific Research Society, the Association of Field Ornithologists, the Western Bird-Banding Association, and the American Museum of Natural History Chapman Fund. -52 -3.8 FIGURES AND TABLES Figure 3.1 Effect of simulated paternity error on estimates of inbreeding depression for three fitness traits: (a.) juvenile survival, (c.) male LRS, and (e.) female LRS. Black circles show the estimate of inbreeding depression ± 95% CI according to the social pedigree. Open circles show the mean estimate of inbreeding depression ± the mean 95% CI derived from 1000 simulations at each of 8 paternity error rates. Lines show extrapolation from the simulation data using linear (dotted line) and cubic polynomial equations (black curve). The bottom three graphs show the statistical significance of inbreeding depression for (b.) juvenile survival, (d.) male LRS, and (f.) female LRS based on the social pedigree (black squares) and the median p-values for the 1000 simulations at 8 paternity error rates (open squares). Juvenile survival t o Male LRS Female LRS ~i 1 1 r 20 40 60 80 100 (b.) 1.0 -I 0.8 -0.6 -CO > 1 Q . 0.4 -0.2 -0.0 - i r 0 20 40 60 80 100 Paternity error rate ~i 1 1 r 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Paternity error rate - | 1 1 r 0 20 40 60 80 100 Paternity error rate -53-Table 3.1 Discrete-time proportional hazards analysis ofthe effects of inbreeding on survival of juveniles to age one based ori the social pedigree. Separate coefficients were estimated for each cohort but these coefficients are not shown here for simplicity. A positive coefficient indicates a negative effect of the variable on juvenile survival because proportional hazards models analyze the effect of covariates on mortality. N shows the number of individuals included in the analysis. df Coefficient SE x 2 P Cohort 20 211.95 <0.001 Laying date 1 0.010 0.001 49.33 <0.001 F 1 1.392 0.587 5.42 0.020 Log likelihood = -1005.21 N= 1735 - 5 4 -Table 3.2 ANCOVA of the effects of cohort and inbreeding (F) on the lifetime reproductive success of males and females based on the social pedigree. A negative coefficient indicates a negative effect of the variable on LRS. N shows the number of individuals used in each analysis. df Coefficient SE x 2 P Male LRS Cohort F 17 49.07 <0.001 1 -4.257 1.278 9.84 0.002 Log likelihood = -1130.58 N = 324 Female LRS Cohort F 17 67.04 O.001 1 -1.840 1.127 2.59 0.108 Log likelihood = -1195.33 N = 226 -55 -CHAPTER 4: EFFECTS OF NATURAL ENVIRONMENTAL STRESS AND INBREEDING ON FITNESS TRAITS IN A WILD BIRD POPULATION By Amy B. Marr, Peter Arcese, Jane M. Reid, and Lukas F. Keller ABSTRACT Understanding how inbreeding depression varies with environmental stress is important to the conservation of small populations, because populations that show greater inbreeding depression during stressful periods may need to be larger or better connected to other populations to ensure their persistence. However, few studies have shown how natural sources of environmental stress affect inbreeding depression in natural populations. We used data from a long-term population study on song sparrows (Melospiza melodia) to examine the effect of inbreeding and environmental stress on four fitness traits that are known to exhibit inbreeding depression: hatching success, laying date, male mating success, and fledgling survival. We found that inbreeding depression interacted with environmental stress to affect one of four traits studied; inbreeding depression in hatching success was greater during rainy periods. For another trait, laying date, it was not clear whether the effects of inbreeding and environmental stress interacted or were independent. If anything, inbred birds experienced less inbreeding depression in laying date under more stressful conditions (i.e., cooler years). For two other traits, there was no evidence that the strength of inbreeding depression varied with environmental stress. First, mated males fathered fewer nests per season if they were inbred or if the ratio of males to females in the population was high, but inbreeding depression did not depend on the sex ratio skew. And, second, fledglings survived poorly during rainy periods and if their father was inbred, but the effects of paternal inbreeding and rain did not interact. Therefore, although we found interactive effects of inbreeding and environmental stress on hatching success, other traits did not show clear evidence of this pattern. Our findings are consistent with those of other studies of natural and laboratory populations, in suggesting that the effects of inbreeding and environmental stress often appear independent. However, if an interactive relationship is found, stress usually exacerbates inbreeding depression. 4.1 INTRODUCTION The offspring of closely related mates are likely to show lower phenotypic values for characters associated with reproductive capacity and physiological efficiency than the offspring of distantly related mates (Falconer and Mackay 1996). This phenomenon, called inbreeding depression, is regularly observed in experimental and natural populations (Ralls et al. 1988; Lacy 1997; Crnokrak and Roff -56-1999). Inbreeding depression occurs because inbred offspring are more homozygous than outbred offspring on average, and homozygosity tends to reduce fitness because recessive deleterious alleles contributed by one parent are less often masked by dominant alleles contributed by the other parent (Charlesworth and Charlesworth 1999). The magnitude of inbreeding depression, however, varies among populations within species and within populations over time (Keller and Waller 2002). One factor contributing to this variation may be that stressors in the environment mediate or interact with the effects of inbreeding (Pray et al. 1994; Haag et al. 2003). Based on genetic theory, an interaction between the effects of stress and inbreeding might be expected if genes that affect tolerance to environmental stress are also affected by inbreeding or if selection against deleterious mutations is more intense under stress (Kondrashov and Houle 1994). The empirical evidence, however, is mixed. Experimental studies in greenhouses and laboratories have often found no clear relationship between environmental stress and the intensity of inbreeding depression (Waller 1984; Mitchell-Olds and Waller 1985; Dahlgaard et al. 1995; Goodwillie 2000; Fowler and Whitlock 2002; Haag et al. 2003; Kristensen et al. 2003; Salathe and Ebert 2003). However, among those studies where an interaction was found, inbreeding depression was usually greater in more stressful environments (Wright 1977; Schmitt and Ehrhardt 1990; Wolfe 1993; Miller 1994; Latter etal. 1995; Hauser and Loeschcke 1996; Bijlsma et al. 1999; Cheptou et al. 2000; Joron and Brakefield 2003; but see Dahlgaard and Loeschcke 1997). It is often assumed that artificial environments are more benign than field conditions, but studies that compare the effects of inbreeding between environments have not always found greater inbreeding depression in the field. Work on root voles (Microtus oeconomus) and freshwater snails (Physa acuta), for example, showed that inbreeding depression was greater in the laboratory (Gundersen et al. 2001; Henry et al. 2003). Work on land snails (Arianta arbustorum), white-footed mice (Peromyscus leucopus noveboracensis), and house mice (Mus domesticus), however, showed the expected pattern of greater inbreeding depression in the field (Chen 1993; Jimenez et al. 1994) or in a semi-natural environment (Meagher et al. 2000). No difference in inbreeding depression under laboratory and field conditions was found for tree-hole-breeding mosquitoes (Aedes geniculatus, Armbruster et al. 2000). Henry (2003) speculated that some laboratory studies may find greater inbreeding depression if lab conditions are more energetically demanding than field conditions. Regardless of the reason, these mixed results suggest that field studies may offer different insights about factors affecting the intensity of inbreeding depression in wild populations than work in highly controlled environments. -57-To date, however, only a handful of studies have examined the effects of natural variation in environmental conditions on inbreeding depression in the wild. Some of those conducted so far have successfully identified factors that mediate or interact with inbreeding depression; others have reported null results. Inbred Soay sheep (Ovis aries), for example, had higher parasite burdens and lower survival than more outbred sheep and the difference between inbred and outbred sheep was particularly pronounced in years of high population density (Coltman et al. 1999). In cactus finches (Geospiza scandens), inbreeding depression in survival of juveniles from banding to age one was only present in dry years, and adult finches experienced greater inbreeding depression in survival when conditions were dry and intraspecific competition was high (Keller et al. 2002). For collared flycatchers (Ficedula albicollis), body condition was measured for fledglings as the residual from a linear regression of body mass on tarsus length, and environmental stress was measured as the average body condition for all fledglings in a given year. Average body condition explained significant variance in several fitness traits, but there were no interactions between the effects of population body condition and inbreeding (Kruuk et al. 2002). Here, we study the influence of environmental stress on the observed level of inbreeding depression in a natural population of song sparrows. We used long-term research on the song sparrows of Mandarte Island for this purpose, because data for this population are somewhat extraordinary. The song sparrows have been intensively monitored since 1975 and there is extensive pedigree data. Prior work found that mated song sparrows showed a wide range of kinship levels and inbreeding affected survival and certain reproductive traits (Keller 1998; Keller and Arcese 1998). Here, we took the subset of reproductive traits that showed inbreeding depression and examined them against potential biotic and abiotic stressors that we expected to also influence these traits. We then evaluated the effects of inbreeding, stress, and their interaction. 4.2 METHODS 4.2.1 Field site, methods, and pedigree We studied a population of song sparrows that is resident year-round on Mandarte Island, B.C., Canada. Mandarte is a 6 hectare island located in the Haro Strait between Vancouver Island and the mainland of British Columbia, Canada. During each breeding season from 1975 to 2003 except 1980, nests of song sparrows were found and monitored to determine clutch size, hatching success, and offspring survival. Birds were colour-banded for individual identification, usually as nestlings at age 5 to -58-7 days. Any immigrants to the population were identified by the absence of leg bands and were typically mist-netted and banded in early spring. A pedigree was constructed for the population based on social associations between parents and offspring. Mothers were identified as the parent that built the nest and incubated the eggs. Fathers were assumed to be the male that defended the territory in which the female resided during egg-laying. Based on this social pedigree, we calculated Wright's inbreeding coefficient, F, for each individual in the population using the INBREED procedure in SAS (SAS Institute 1999). An inbreeding coefficient describes the probability that two alleles at a randomly chosen locus will be identical by descent from an ancestor shared by the mother and father (Falconer and Mackay 1996). Genetic data show that all 751 genotyped young from 1993 to 1996 matched their mothers. Therefore, intraspecific brood parasitism (i.e., egg dumping by females in the nests of other females) is absent or rare in the song sparrows on Mandarte Island. However, female song sparrows engage in extrapair matings, and genetic data show that the male identified as the social father was not the genetic father for 27% of 751 genotyped offspring (O'Connor 2003). Extrapair paternities (EPPs) will have introduced errors to inbreeding coefficients and inbreeding depression estimates (chapter 3). There were only 12 birds in the breeding population of song sparrows on Mandarte Island following a severe winter storm in February 1989. Due to the small population size in this year and the identity of bottleneck survivors, we had relatively complete pedigree data (at least all grandparents known) for most birds in the population after 1989. We therefore restricted analyses to the period from 1990 to 2003 to limit bias created by variation in pedigree length across years. To be conservative, individuals with unknown parents or grandparents were also excluded from analyses unless they were the offspring of an immigrant. Immigrants to the population were assumed to be unrelated to each other and to birds already in the population when they arrived. Further analyses, however, showed that leaving the few individuals with poorly-known pedigrees in analyses would have had little influence on estimates of inbreeding depression and tests of statistical significance. 4.2.2 Statistical analyses To analyze the effects of inbreeding and stress, we began with a list of four reproductive traits that were known from prior work (Keller 1998; Keller et al., in review) to exhibit inbreeding depression in the song sparrows: male mating success (inbred males father fewer nests per season), fledgling survival (the offspring of inbred males survive poorly from the age of day 12 to day 24), laying date (inbred -59-females begin laying eggs later in spring), and hatching success (inbred females have poor hatching success in the eggs that they lay and incubate). We then created a list of known or suspected sources of environmental stress that influenced each fitness trait. Our ideas for likely stressors came from prior studies on song sparrows and other songbirds and from our own field observations (discussed later in methods). Fitness data were analyzed for each trait using generalized linear models with an appropriate error structure. Statistical analyses were conducted in SAS using the GENMOD procedure (SAS Institute 1999). For each trait, we explored a suite of statistical models to assess the effects of inbreeding, a measure of environmental stress, and their interaction. Support for particular models was judged using the bias-corrected version of Akaike's Information Criterion (AICC, Burnham and Anderson 2002), for which lower AICc scores indicate better model support. All models included age as a categorical variable, because reproductive success is known to vary with age in this population (Smith et al, in review). We inspected plots of residuals versus fitted Y, values, and we examined the various normality test statistics generated by the UNIVARIATE procedure in SAS to look for evidence that response variables needed to be transformed. Following the advice of Draper (1998), we also plotted residuals against each term in our models to determine if higher-order predictive terms were warranted. Some individuals contributed more than one observation to the dataset in analyses for each trait. For example, for analyses of male nesting attempts, each adult male contributed an observation every year. For analyses of female laying date, each female contributed an observation every year that she laid at least one egg. For analyses of fledgling survival and hatching success, all breeding attempts with at least one fledgling or one egg respectively were included. Ignoring the possible lack of independence among multiple observations collected on an individual could yield standard errors that are underestimated and test statistics that are overestimated. We therefore used generalized estimating equations (GEE). The GEE approach is a method which extends the generalized linear regression model (GLM) approach to accommodate data where repeated observations have been collected on subjects and, thus, there may be correlation between responses within subjects (Allison 1999; Ballinger 2004). To discuss the range of our results for each fitness trait, we used our statistical models to calculate the average fitness of age 2 outbred birds (i.e., birds with F = 0) and age 2 highly inbred birds (F = 0.25) at the lowest and highest levels of environmental stress observed for each trait. Age 2 birds were chosen for comparisons because the median age of breeding birds in the population is two years for both males and females. Comparisons for other age groups could be calculated from the models in Tables 4.2, 4.5, -60-4.7, and 4.9. Inbreeding levels of F= 0 and F= 0.25 were used for descriptive purposes, because these are the levels most commonly reported in experimental studies (e.g., Crnokrak and Roff 1999). An individual with F= 0.25 could be the offspring of a mating between full sibs or between a parent and offspring with no previous relationship deeper in the pedigree (Falconer and Mackay 1996). An inbreeding coefficient of F = 0.0625 corresponds to a mating between first cousins. Based on calculations from the social pedigree, inbreeding coefficients of adult song sparrows have ranged from F = 0 to F= 0.31 on Mandarte Island and averaged F = 0.06 in recent years. Male mating success— Male song sparrows are primarily responsible for territory defence and for helping females feed offspring before and after fledging. Prior studies on Mandarte song sparrows have shown that males devote considerable energy to attracting females to their territories and defending their territories from other males (Arcese 1989). Female song sparrows typically produce 2 or 3 nests annually (range 0 to 6, Smith et al., in review), and, since 1975, an average of 40% of females had multiple mates in a breeding season. Mate switches usually occurred because males were evicted from their territories by competing males or because females moved to different territories between nests. Most successful males attracted a single female to their territory at a time, but an average of 4% of territorial males had two female mates simultaneously. We, therefore, hypothesized that the number of nests fathered by a male might depend on competition among males. Two measures of competition were explored: the total number of males in the population and the number of males per female. Fledgling survival— Song sparrows leave the nest at around 9-11 days after hatch but depend on their parents for food until about 25-30 days. To assess fledgling survival, offspring were counted at day 12 and day 24 by listening for begging calls of offspring and observing parents delivering food. We knew from exploratory analyses that the survival of fledglings was no worse when air temperatures were cool. However, field observations and exploratory analyses suggested that fledglings beg with greater persistence, and may be hungrier, on damp mornings that follow rainy days. We, therefore, explored several measures of rainfall including: the daily average rainfall during the entire period that fledglings were day 12 to day 24 and the daily average rainfall during the rainiest 2, 3, 4, or 5-day interval within the period from day 12 to day 24. We explored models with rainy intervals of 2 to 5 days because we noticed during fieldwork that storms usually lasted for about 2 to 5 days, and we hypothesized that parents might be unable to meet the energy needs of their offspring during such periods. Analyses were conducted using generalized logistic regressions with the number of day 24 offspring per day 12 -61 -offspring as the response variable. Thus, birds from the same brood were grouped as a unit in analyses. Weather data were obtained from Environment Canada for the nearest weather station, located at Victoria International Airport, 11 km west of Mandarte Island. Laying date — Many studies of songbirds have shown that temperatures or rain correlate with the onset of breeding (Dhondt et al. 1984; Brown and Li 1996; Hussell 2003). For the song sparrows on Mandarte Island, females that begin breeding early in a season have more nesting opportunities, more fledglings, and more recruits than females that begin breeding later in the same year. Most females lay their first eggs between late March and early May (median date of first egg: April 15,h). Rain is a poor predictor of laying date for song sparrows on Mandarte Island, but air temperatures have a strong influence (Smith et al., in review; Wilson and Arcese 2003). Prior work and our own exploratory analyses showed that females began laying later in years when temperatures were cool in February, March, or April (Smith et al., in review). We, therefore, tested for the influence of daily average air temperature during 6 time intervals: February, March, April, February-March, March-April, and February-April. Analyses were conducted using general linear models with the Julian date that females laid their first eggs in spring as the response variable. Hatching success — Like most open-cup nesting songbirds in North America, female song sparrows work alone to incubate eggs (Ehrlich et al. 1988; Smith et al., in review). We knew from past work that the survival of fledglings was no worse when air temperatures were cool (our unpubl. data). However, field observations on Mandarte Island suggested that poor hatching success sometimes coincided with stormy weather. Therefore, as for the analysis of post-fledgling survival, we explored several measures of rainfall including: the daily average rainfall during the 13 days that typically span incubation and the daily average rainfall during the rainiest 2, 3, 4, or 5-day interval within the incubation period. Analyses were conducted using generalized logistic regressions (Allison 1999), for which the number of hatchlings per egg in a clutch was the response variable in each model. Brown-headed cowbirds (Molothrus ater) are brood parasites that lay their eggs in the nests of other species. From 1990 to 2003, cowbirds have been absent in 9 years, rare in 2 years, and common in 3 years. When cowbirds are common, the association between climatic variables and hatching success is obscured, because rain usually declines during a breeding season but nest failure due to cowbirds greatly increases. This occurs because cowbirds usually begin egg-laying a few weeks later than song sparrows and will destroy unparasitized song sparrow nests to enhance future laying opportunities (Smith and -62-Arcese 1994; Smith et al, in review). Therefore, we eliminated nests from periods when cowbirds were common before analyzing relationships between hatching success and climatic variables. 4.3 RESULTS Male mating success — Males fathered fewer nests annually when there were more males in the population overall and when there were more males per female in the population, but of the two measures of competition tested, the number of males per female explained more variation in the data (Table 4.1). Males also fathered fewer nests seasonally if they were inbred (Table 4.1). Judging from the AICC scores for the various models examined, the model with the best support predicted the number of nests fathered from a male's age, his inbreeding coefficient, and the number of males per female in the population (Tables 4.1, 4.2A). Also including a term for the interaction between inbreeding and the number of males per female in the population yielded a model with a higher AICc score; therefore, the model with the interaction term was less well supported by the data (Tables 4.1, 4.2B). Based on the model which included a male's age, his inbreeding coefficient, the number of males per female, and the interaction between inbreeding and the number of males per female (Tables 4.2B, 4.3; Figure 4.1 A), we estimate that inbred males fathered 28.8% fewer nests than outbred males when the number of males per female was at its lowest level (i.e., M/F was 0.96; x F=o = 2.71, xF=o.25 = 1-93 nests); whereas, when males greatly outnumbered females (M/F was 3.07), both outbred and inbred males fathered considerably fewer nests, but the performance difference between outbred and inbred males was similar (xF=o = 0.55, x F=o.25 = 0.42 nests; a difference between outbred and inbred males of 23.6%). Fledgling survival — The survival of fledglings, measured from day 12 to day 24, was lower during rainy periods. Of the measures of environmental stress that we examined, the average daily rainfall during the rainiest 3-day interval explained the most variation in fledgling survival (Table 4.4). However, fledgling survival was also reduced when rain was measured during shorter (2-day) and longer intervals (4-day, 5-day, entire period from day 12 to day 24; Tables 4.3, 4.4). Fledglings experienced lower survival rates if their father was inbred (Tables 4.4, 4.5A), but there was no evidence of an interaction between the effects of paternal inbreeding and rain (Table 4.5B; also note parallel lines in Figure 4. IB). For example, in the absence of rain, we estimate from the model in Table 4.5B that fledglings with inbred fathers survived 31.8% worse than fledglings with outbred fathers (xF=o = 0.803, x F =0.25 = 0.548; Table 4.3, 4.5B); whereas, under the rainiest conditions, fledglings with inbred fathers - 63 -had 32.3% lower survival than fledglings with outbred fathers (x F = 0 = 0.665, x F= 0.25 = 0.450; Table 4.3). Laying date — Females laid their first eggs later in spring if they were inbred or if temperatures were cool. The best model predicted laying date from a female's age, her inbreeding coefficient, and the average daily temperature in February and March (Tables 4.6, 4.7A). The second best model, which included the terms in the best model and a term for the interaction between inbreeding and temperature, had only slightly less support than the best model according to the AICC scores (Tables 4.6, 4.7B). Thus, there was evidence of a possible interaction between inbreeding and temperature. Based on the model which included the interaction term (Table 4.7B; Figure 4.1C), we estimate that inbred females laid their first eggs 20 days later than outbred females when temperatures were warm ( x F = 0 = March 28th, x F= 0.25 = April 17th); whereas, when temperatures were cool, the estimated difference in laying date between inbred and outbred females was only 8 days (x F = 0 = April 20th, x F= 0.25 = April 28th). Therefore, if anything, the difference in laying date between inbred and outbred birds was greater under less stressful circumstances (i.e., warmer years; see also Table 4.3). Hatching success — Hatching success, unlike the other traits studied, showed a strong interaction between inbreeding and environmental stress. Hatching success was lower for inbred females, particularly when it was rainy (Tables 4.3, 4.8). Of the measures of rain that we considered, the rainiest 4-day interval during the incubation period was the best predictor of hatching success (Table 4.8). The best model for hatching success included terms for a female's age, her inbreeding level, the daily average rainfall during the rainiest 4-day interval, and the interaction between inbreeding and the rainiest 4-day interval (Tables 4.8, 4.9). A similar model, based on the rainiest 5-day interval, was almost as good as the best model (Table 4.8). Hatching success was also lower during shorter (2-day, 3-day) and longer intervals (entire incubation period) of rain. According to our best model (Table 4.9; Figure 4. ID), the hatching success of outbred females was about 0.866 in the absence of rain, whereas highly inbred females (f = 0.25) had hatching success of 0.782 in the absence of rain; during periods of heavy rain, outbred females had only slightly diminished hatching success (x F = 0 = 0.831), but inbred females were severely affected, performing less than 1/10,h as well as outbred birds on average (x F= 0.25 = 0.069; Table 4.3). -64-4.4 DISCUSSION Laboratory and greenhouse studies often detect no relationship between the degree of environmental stress and the severity of inbreeding depression. However, when interactive relationships are found, environmental stress usually exacerbates inbreeding depression. Studies of interactions between environmental stress and inbreeding depression in natural populations are uncommon, but the few conducted so far have found that inbreeding depression was either exacerbated by environmental stress or independent of it. For the small, relatively isolated population of song sparrows on Mandarte Island, we found that inbreeding interacted with stress for one of four traits that was affected by inbreeding and an environmental factor. Namely, hatching success was lower in the nests of inbred females, particularly during rainy periods. For another trait, laying date, it was not clear whether the effects of inbreeding and environmental factors interacted or were independent. However, i f anything, the data suggested that inbreeding depression in laying date was less pronounced under more stressful conditions (i.e., cooler years). For two other traits, the effects of inbreeding and environmental stress seemed to be largely independent. Hatching success, the only trait that showed clear evidence of an interaction between inbreeding and an environmental factor, is a trait that is attracting much interest in other studies. Recent publications have shown that many species of birds experience inbreeding depression in hatching success in the wild. Hatching success, for example, was found to be lower between more closely related pairs of red-cockaded woodpeckers (Picoides borealis, Daniels and Walters 2000) and collared flycatchers (Ficedula albicollis, Kruuk et al. 2002). Inbred pairs and inbred mothers had reduced hatching success in great tits (Parus major, Noordwijk and Scharloo 1981). Increased genetic similarity between mates was associated with lower hatching success in great reed warblers (Acrocephalus arundinaceus) and blue tits (Parus caeruleus, Bensch et al. 1994; Kempenaers et al. 1996). inbreeding depression is thought to be the cause of declining hatching success in a population of Greater prairie chickens (Tympanuchus cupido, Westemeier et al. 1998) and hatching failure in reintroduced populations of several bird species in New Zealand that have passed through population bottlenecks (Briskie and Mackintosh 2004). And, finally, a study of 99 bird species found that species with higher band-sharing coefficients of microsatellites have higher rates of hatching failure (Spottiswoode and Moller 2004). It is not yet clear, however, i f it is easier to detect inbreeding depression in hatching success than in other traits. And i f detection does not differ across traits, why is hatching success so often affected, and what factors mediate inbreeding depression in hatching success? Our work on song sparrows suggests that environmental stressors, like rain, may be - 6 5 -one factor that exacerbates inbreeding depression in hatching success. However, there is still a need for detailed behavioural studies on this and other natural populations. Experimental work on the physiological and genetic basis of inbreeding depression in hatching success of birds could also be rewarding. For other traits that we studied, there may be no evidence for interactions between inbreeding and environmental factors, because inbreeding and environmental factors affect different components of a trait or affect a trait at different times. However, there are also several reasons why an interaction may exist but may not be detected. One possible cause of null results may be that we were unable to account for key explanatory variables. It seems likely, for example, that predators, like deer mice (Peromyscus maniculatus) and Northwestern crows (Corvus caurinus), cause some nests to fail before we detect them and reduce the survival of fledglings from day 12 to day 24. However, measures of predator numbers have never been collected and, therefore, it is not possible to account for variation in reproductive success that was due to differences in predator abundance across years. Pedigree errors are a second factor that may have reduced our ability to detect interactions between inbreeding depression and environmental stress. As discussed in chapter 3 of this thesis, pedigree errors create errors in inbreeding coefficients and reduce the accuracy of inbreeding depression estimates. It follows that pedigree errors could also make it more difficult to detect associations between environmental factors and inbreeding depression. Ideally, we would have eliminated paternity errors from our pedigree but that was not feasible here. Genotype data are only complete enough to correct paternity of extrapair offspring for the four-year period from 1993 to 1996. This represents a relatively small fraction of the pedigree. In addition, removing extrapair young from analyses in only some years could have created biases in our analyses. Problems with the distribution of data available are a third possible cause of null results. Inbreeding coefficients of adult song sparrows on Mandarte Island have ranged from.F= 0 to 0.31, but most birds have relatively low inbreeding coefficients. For example, only 55 of 650 observations in the analysis of male nesting attempts were for males with inbreeding coefficients of F> 0.125 (i.e., birds with parents that were at least as closely related as half-siblings). In addition, data for our stressor was also not ideally distributed. The sex ratio in the population ranged from 0.96 to 3.07 males per female, but there were only 102 observations of male nesting success when the sex ratio was in the upper half of that range. Given that there were relatively few highly inbred males and few males breeding in years -66-when there were highly skewed sex ratios, it might have also been difficult to detect an interaction between inbreeding and the number of males per female in the population. Studies of other natural systems are likely to encounter some of the same problems with unidentified or unmeasured environmental stressors, pedigree errors, and poor distribution of inbreeding coefficients and environmental stress data. While it would be difficult to eliminate the problem of unidentified environmental stressors in any natural environment, semi-natural experiments could be used to avert the problems of pedigree error and poor distribution of inbreeding coefficients and environmental stress data. One could, for example, follow Jimenez et al. (1994) in bringing wild organisms into the laboratory to create good sample sizes of inbred and outbred individuals. These organisms could then be re-released into the wild. However, unlike the study of Jimenez et al. (1994), one could conduct releases in environments that differ in quality or degree of environmental stress to allow for analyses of interactive relationships between stress and inbreeding. 4.5 CONCLUSION Conservation biologists are concerned about the potential for interactions between environmental stressors and inbreeding, because such interactions may affect the extinction risk of endangered species. Studies that have examined the links between environmental stress and inbreeding depression in natural populations are uncommon. We used data from a long-term study on the song sparrows of Mandarte Island to study interactions between stress and inbreeding, because it is one of few studies of a natural population with suitable data. We found that environmental stress exacerbated inbreeding depression in hatching success and possibly mitigated inbreeding depression in laying date. For two other traits, there was no evidence of an interaction between inbreeding depression and environmental stress. However, several factors may have contributed to our finding null results. Semi-natural experiments seem to be an underutilized way to learn about stress by inbreeding interactions, because such studies can eliminate the problems of pedigree error and poorly distributed inbreeding coefficients and environmental stress data. 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Spottiswoode, C , and A. P. Moller. 2004. Genetic similarity and hatching success in birds. Proc. R. Soc. Lond. B 271:267-272. Waller, D. M. 1984. Differences in fitness between seedlings derived from cleistogamous and chasmogamous flowers in Impatiens capensis. Evolution 38:427-440. Westemeier, R. L., J. D. Brawn, S. A. Simpson, T. L. Esker, R. W. Jansen, J. W. Walk, E. L. Kershner, J. L. Bouzat, and K. N. Paige. 1998. Tracking the long-term decline and recovery of an isolated population. Science 282:1695-1698. Wilson, S., and P. Arcese. 2003. El Nino drives timing of breeding but not population growth in the song sparrow (Melospiza melodia). Proc. Natl. Acad. Sci. USA 100:11139-11142. Wolfe, L. M. 1993. Inbreeding depression in Hydrophyllum appendiculatum: Role of maternal effects, crowding, and parental mating history. Evolution 47:374-386. Wright, S. 1977. Evolution and the genetics of populations, Vol. 3, Experimental results and evolutionary deductions. Univ. of Chicago Press, Chicago. -71 -4.7 ACKNOWLEDGEMENTS M . C. Whitlock, D. Schluter, and K. Ritland provided helpful comments on earlier drafts. The Tsawout and Tseycum First Nations bands kindly allowed us to work on Mandarte Island. Many people helped collect the field data presented here, including most recently S. D. Wilson, J. M . Reid, J. N . M . Smith, A. Johnston, D. Dagenais, R. M . Landucci, K. D. O'Connor, S. E. Runyan, and C. A. Saunders. Support for this research was provided by grants to P. Arcese from NSERC of Canada, and to A. B. Marr from a National Science Foundation Fellowhship, a Gene Namkoong Family Scholarship in Forest Genetics, an Adrian Weber Scholarship in Forest Ecology, Sigma X i Scientific Research Society, the Association of Field Ornithologists, the Western Bird-Banding Association, and the American Museum of Natural History Chapman Fund. -72 -4.8 FIGURES AND TABLES Figure 4.1 Effects of inbreeding and stress on four fitness traits for outbred and highly inbred birds. Graphs show the predicted values for age 2 outbred (F= 0) birds and inbred (F= 0.25) birds based on the models in tables 4.2B, 4.5B, 4.7B, and 4.9. These models include terms describing the interaction between inbreeding and stress, even if the interaction term was not statistically significant. Moving from left to right, the x-axis of each graph depicts the range of stress levels observed from lowest to highest. The y-axes are arranged such that lower performance (fewer nests, lower survival, later breeding, or lower hatching success) is lower on the page. Therefore, both axes for the graph of laying date (4.1C) are reversed so that later breeding is lower on the page and cooler temperatures are further to the right. (A) Male mating success (B) Fledgling survival 0 s CD ro w to CD c E 3 1.0 1.5 2.0 2.5 3.0 Males per female C 1.0 i Q. v22 ay 0.8 O o O 0.6 CD CM rati 0.4 CO BAjAJ •o E o 0.2 Su M— 0.0 0 2 4 6 8 10 12 14 16 18 Rain (mm/day) during rainiest 3-day interval (C) Laying date (D) Hatching success 80 c 90 o> n <D ^— W c ro 100 \ —j 4— O c 110 1_ » ro Q. W 120 Q 130 8.0 7.5 7.0 6.5 6.0 5.5 5.0 4.5 Average temperature °C (Feb.-Mar.) 6 8 10 12 14 Rain (mm/day) during rainiest 4-day interval Outbred (F = 0) Inbred (F = 0.25) -73 -Table 4.1 Comparison of eight models examining the effects of a male's age, his inbreeding level (F), and competition on the number of nests he fathered in a year. The column titled F x Competition refers to the interaction between the male's inbreeding level and either the total number of males in the population or the number of males per female, depending on which measure of competition was included in the model. Models are listed in order from best to worst based on the bias-corrected version of Akaike's Information Criterion scores (AICc). AICc values come from general linear models. Age was included in all models, because past studies showed that age was an important predictor of the number of nests fathered. Separate coefficients were estimated for each of five age classes. Analyses were based on a dataset comprised of 650 observations of male seasonal reproductive success. Age Males Males per female Fx Competition Parameters AICc X X X 7 2019.17 X X X X 8 2020.57 X X 6 2026.70 X X X 7 2137.13 X X X X 8 ' 2138.94 X X 6 2143.63 X X 6 2145.50 X 5 2152.16 - 7 4 -Table 4.2 Effects of a male's age, his inbreeding level (F), and the number of males per female in the population on the number of nests that he fathers in a year. Based on Table 4.1, Model A is the best statistically-supported model. Model B, the second best model in Table 4.1, shows the contribution of the interaction term between a male's inbreeding level and the number of males per female in the population. ./Vis the number of observations of male seasonal reproductive success that were included in analyses. Coefficient SE df x2 P Intercept 3.551 0.226 Age 4 75.34 <0.001 1 -0.842 0.149 2 0.033 0.154 3 0.112 0.167 4 -0.080 0.187 5+ 0.000 F -2.399 0.717 1 9.94 0.002 Males per female -0.953 0.086 1 52.35 O.001 TV =650 Intercept 3.662 0.311 Age 4 74.49 <0.001 1 -0.848 0.151 2 0.024 0.157 3 0.104 0.169 4 -0.086 0.189 5+ 0.000 F -4.267 3.123 1 2.12 0.145 Males per female -1.021 0.141 1 30.88 <0.001 F x Males per female 1.211 1.904 1 0.43 0.514 TV =650 -75 -Table 4.3 Effects of inbreeding and various environmental stresses on four fitness traits: male mating success (measured as number of nests fathered), fledgling survival (day 24 offspring per day 12 offspring), laying date (date of first egg in spring, Jan. 1 = 1), and hatching success (hatchlings per egg). Trait value estimates are the predicted values for outbred birds (F=0) and highly inbred birds (F = 0.25) at the lowest and highest stress levels observed. Estimates are derived from those models in tables 4.1, 4.4, 4.6, and 4.8 that included age, inbreeding, an environmental stressor, and a term for the interaction between inbreeding and environmental stress. The last four columns of the table show the effect on fitness of: (1) stress for birds with F = 0, (2) stress for birds with F= 0.25, (3) inbreeding at low stress levels, and (4) inbreeding at high stress levels. For mating success, fledgling survival, and hatching success, the effect of stress was reported as a percentage by calculating the difference in trait value estimates between the highest and lowest stress levels and then dividing by the trait value estimate for the lowest stress level (i.e., (Xhigh stress - X ] o w stre s) / X t o w s t r e s s ) . Similarly, the effect of inbreeding was reported as a percentage by calculating the difference in trait value estimates between birds with F - 0.25 and birds with F = 0 and then dividing by the trait value estimate for birds with F = 0 (/. e., (XF=0.25 - X F = 0 ) / X F = 0) • For laying date, earlier laying (/. e., a smaller Julian date) indicates better performance. Therefore, for laying date, the effect of stress was calculated as the difference in Julian date between the highest and lowest stress levels (i.e., Xhigh stress - X i o w stress); the effect of inbreeding was calculated as the difference in Julian date between birds withF= 0.25 and birds with.F = 0 (i.e., Xf=o.2s-Xf=o)--76-Table 4.3 Trait Stressor Trait value estimate Effect of Effect of Effect of Effect of F=0 F=0 F=0.25 F=0.25 stress on stress on inbreeding at inbreeding at low high low high F = 0 F = 0.25 low stress high stress - stress stress stress stress Male mating success Males per female 2.71 0.55 1.93 0.42 -79.7 % -78.2 % -28.8 % -23.6 % Males 2.49 1.63 1.78 1.14 -34.5 % -36.0 % -28.5 % -30.1% Fledgling survival Rain for entire period 0.794 0.652 0.654 0.529 -17.9 % -19.1 % -17.6% -18.9% Rainiest 2-day interval 0.805 0.515 0.656 0.469 -36.0 % -28.5 % -18.5% -8.9 % Rainiest 3-day interval 0.803 0.548 0.665 0.449 -31.8% -32.5 % -17.2 % -18.1 % Rainiest 4-day interval 0.794 0.639 0.661 0.487 -19.5 % -26.3 % -16.8 % -23.8 % Rainiest 5-day interval 0.796 0.633 0.656 0.508 -20.5 % -22.6 % -17.6% -19.7 % Laying date Temp. Feb. 92 109 107 116 17 days 9 days 15 days 7 days. Temp. Mar. 90 110 110 119 20 days 9 days 20 days 9 days Temp. Apr. 93 115 104 110 22 days 6 days 11 days -5 days Temp. Feb. - Mar. 87 107 110 118 20 days 8 days 23 days 11 days Temp. Mar. - Apr. 91 112 108 ' 115 21 days 7 days 17 days 3 days Temp. Feb. - Apr. 86 108 111 ' 118 22 days 7 days 25 days 10 days Hatching success Rain for entire period 0.857 0.867 0.779 0.108 1.17% -86.1 % -9.1 % -87.5 % Rainiest 2-day interval 0.866 0.831 • 0.778 0.122 -4.04 % -84.3 % -10.2 % -85.3 % Rainiest 3-day interval 0.866 0.827 0.780 0.115 -4.50 % -85.3 % -9.9 % -86.1 % Rainiest 4-day interval 0.866 0.831 0.782 0.069 -4.04 % -91.2% -9.7 % -91.7% Rainiest 5-day interval 0.864 0.833 0.782 0.059 -3.59 % -92.5 % -9.5 % -92.9 % -77-Table 4.4 Comparison of 17 generalized logistic regressions examining the effects of a father's age, his inbreeding level (Paternal F), and various measures of rain on the survival of his offspring from day 12 to day 24. The column titled Paternal F x Rain refers to the interaction between the father's inbreeding coefficient and the daily average rain for the entire period that fledglings were day 12 to day 24 or during the rainiest 2, 3, 4, or 5-day interval within that period, depending on which measure of rain was in the model. Analyses are based on data from 638 nests with at least one fledgling. Models are listed in order from best to worst based on the AICc scores. Paternal age Paternal F Rain for entire period Rainiest 2-day interval Rainiest 3-day interval Rainiest 4-day interval Rainiest 5-day interval Paternal F x Rain Parameters AICc X X X 7 1787.43 X X X 7 1787.82 X X X X 8 1789.41 X X X X 8 1789.68 X X X 7 1790.24 X X X 7 1790.38 X X X 7 1790.45 X X X X 8 1792.26 X X X X 8 1792.42 X X X X 8 1792.45 X X 6 1793.62 X X 6 1793.95 X X 6 1793.97 X X 6 1796.75 X X 6 . 1796.77 X X 6 1796.88 X 5 1800.89 -78 -Table 4.5 Effects of a male's age, his inbreeding level (Paternal F), and rain (3-day interval) on the survival of his offspring from day 12 to day 24. Rain.was measured for each brood as the average amount of rain (measured in mm) during the rainiest 3-day interval during the period that offspring were day 12 to day 24. Model A is the best overall model according to the analysis in Table 4.4. Model B shows the best model with a term for the interaction between inbreeding and rain (third best model in Table 4.4). Coefficient SE df I2 P Intercept 1.960 0.221 Paternal age 4 7.59 0.108 1 -0.699 0.251 2 -0.570 0.227 3 -0.317 0.261 4 -0.539 0.270 5+ 0.000 0.000 Paternal F -2.603 1.037 1 4.36 0.037 Rain (3-day) -0.066 0.024 1 6.56 0.010 N=63S Intercept 1.977 0.226 Paternal age 4 7.62 0.107 1 -0.699 0.251 2 -0.571 0.227 3 -0.319 0.260 4 -0.541 0.270 5+ 0.000 Paternal F -2.887 1.620 1 2.19 0.139 Rain (3-day) -0.071 0.029 1 5.00 0.025 Paternal F x Rain (3-day) 0.076 0.304 1 0.06 0.807 N=63S - 7 9 -Table 4.6 Comparison of 20 general linear models examining the effects of a female's age, her inbreeding level (F), and air temperature on the date that she lays her first egg in spring. Temperature was measured for each year as the daily average temperature (°C) during Feb., Mar., Apr., Feb.-Mar., Mar.-Apr., or Feb.-Apr. Each analysis includes data from 358 nests. Models are listed in order from best to worst based on the AICc scores. Age Temp. Feb. Temp. Mar. Temp. Apr. Temp. Feb.-Mar. Temp. Mar.-Apr. Temp. Feb-Apr. Fx Temp. Parameters AICc X X X 7 2673.42 X X X X 8 2673.66 X X X X 8 2674.15 X X X 7 2674.44 X X 6 2699.12 X X 6 2702.18 X X X 7 2710.24 X X X X 8 2711.57 X X X 7 2719.06 X X X X 8 2719.61 X X X 7 2722.70 X X X X 8 2722.88 X X 6 2739.85 X X 6 2740.57 X X X X 8 2749.33 X X X 7 2750.92 X X 6 2752.03 -X X 6 2764.71 X X 6 2778.15 X 5 2789.39 -80-Table 4.7 Effects of a female's age, her inbreeding level (F), and the daily average air temperature (°C) in February and March on the Julian date that a female lays her first egg in spring. Separate coefficients were estimated for each of five age classes. Coefficients are positive for terms that increase the laying date (i.e., delay laying). Model A is the best statistically-supported model from the analysis in Table 4.6. Model B, the second best model in Table 4.6, shows the contribution of the interaction between inbreeding and air temperature. Coefficient SE df x2 P Intercept 140.470 4.060 Age 4 23.39 <0.001 1 3.312 2.300 2 -1.064 2.291 3 -1.794 2.394 4 2.904 2.512 5+ 0.000 F 52.761 15.297 1 14.18 O.001 Temp. (Feb.-Mar.) -6.356 0.573 1 47.57 O.001 N=358 Intercept 145.282 5.021 Age 4 23.43 <0.001 1 3.281 2.283 2 -1.107 2.280 3 -1.805 2.368 4 2.775 2.485 5+ 0.000 F -39.762 68.269 1 0.34 0.559 Temp. (Feb.-Mar.) -7.119 0.757 1 34.16 <0.001 F x Temp (Feb.-Mar.) 14.944 11.497 1 1.79 0.180 N=358 -81 -Table 4.8 Comparison of 17 generalized logistic regressions examining the effects of a mother's age, her inbreeding level (Maternal F), and various measures of rain on the hatching success of her eggs. The column titled Maternal F x Rain refers to the interaction between the mother's inbreeding coefficient and the daily average rain for the entire incubation period or during the rainiest 2, 3, 4, or 5-day interval, depending on which measure of rain was in the model. Analyses used data from 604 nests. Models are listed in order from best to worst based on the AICc scores. Maternal age Maternal F Rain for entire period Rainiest 2-day interval Rainiest 3-day interval Rainiest 4-day interval Rainiest 5-day interval Maternal F x Rain Parameters AICc X X X X 8 2371.29 X X X X 8 2371.49 X X X X 8 2374.31 X X X 7 2375.63 X X X 7 2376.61 X X X X 8 2376.71 X X X 7 2377.35 X X X X 8 2378.66 X X X 7 2379.35 X X X 7 2384.81 X X 6 2391.90 X X 6 2396.16 X X 6 2397.03 X X 6 2397.69 X X 6 2400.02 X X 6 2405.12 X 5 2413.04 -82-Table 4.9 Effects of a mother's age, her inbreeding level (Maternal F), and rain (4-day interval) on the hatching success of her eggs. Rain was measured for each nest as the average daily rainfall (in mm) during the rainiest 4-day interval in the 13-day incubation period. Coefficients are negative for terms that reduce hatching success. Data are plotted in Figure 4.ID. Coefficient SE df I2 P Intercept 2.106 0.573 Maternal Age 4 18.81 O.001 1 -1.018 0.541 2 -0.240 0.547 3 -0.530 0.529 4 -0.725 0.470 5+ 0.000 Maternal F -2.363 2.633 1 0.65 0.422 Rain (4-day) , -0.020 0.051 1 0.17 0.682 Maternal F x Rain (4-day) 1 -1.074 0.583 1 4.57 0.033 N =604 -83 -CHAPTER 5: THESIS CONCLUSION - MANAGING FOR CONNECTIVITY AND GENETIC H E A L T H IN SMALL POPULATIONS By Amy B. Marr Conservation biologists often plan to manage the genetic health of small populations by encouraging natural dispersal or by translocating individuals among populations. According to theory in population genetics, offspring produced by parents from different subpopulations may benefit from heterosis, a phenomenon of increased vigour. Mixing gene pools may also help reverse genetic problems like inbreeding depression and loss of genetic variation. However, gene flow from non-native individuals (immigrants) may constrain local adaptation or cause genetic incompatibilities. My aim here is to provide definitions and examples of the potential genetic effects of immigrants on small populations. I then discuss the relevance of academic work on inbreeding and outbreeding to the management of small populations. In reviewing recommendations made by other academics, I note that two important questions remain unanswered. These are: what constitutes a genetically healthy population? And, how likely is it that mixing gene pools will improve the genetic health of a population? In the latter half of this chapter, I advance discussion of these lingering questions by explaining the implications of past work on the Mandarte song sparrow (Melospiza melodia) population and then presenting three new analyses that use the song sparrow data as a case study. 5.1 INTRODUCTION Many endangered species live in fragmented habitat patches (Wilcove et al. 1986, Diamond 1989, Wilson 1992). This is a concern to conservation biologists because individuals in small populations typically have fewer choices of potential mates and are more likely to inbreed as a consequence. Isolated populations also tend to lose the genetic variation that would allow them to adapt to changing environmental conditions and new diseases (Keller and Waller 2002). The song sparrows of Mandarte Island are one of very few cases in which it has been possible to study the consequences of inbreeding in a natural population that is open to immigrants. In previous chapters of this thesis, we learned that inbred song sparrows show reduced survival and reproductive success. Other work on the Mandarte song sparrows has shown that, without the occasional arrival of immigrants, genetic variation in the . population would eventually become depleted (Keller et al. 2001). -84-To avert the problems of inbreeding and loss of genetic variation, conservation biologists use a variety of management strategies. Usually these strategies aim to increase the size of existing populations by expanding habitat, or managing predators, competitors, and resources (e.g., Stockwell et al. 1996, Black et al. 1997, Rothstein and Cook 2000, Engeman et al. 2003). These strategies seem sufficient when inbreeding and random genetic drift are not threatening the genetic health of a population. Other strategies, however, may be warranted when small population size is contributing to genetic deterioration. Two approaches to restore lost genetic variation are to build dispersal corridors that encourage natural gene flow or to mimic natural dispersal by capturing individuals from other populations and translocating them to the population of concern. Field studies have demonstrated that gene flow sometimes has beneficial consequences for small populations (Wildt et al. 1987, Madsen et al. 1996, Saccheri et al. 1998). However, as you will read, conservation strategies that augment gene flow are controversial because of problems that can arise after gene pools are mixed. 5.2 IMMIGRANT GENES MAY SPREAD QUICKLY: HETEROSIS Crosses between populations of a species sometimes yield first generation progeny (Fis) that are more fit than purebred offspring from within either population. The botanist George H. Shull (1914) introduced the term "heterosis" to describe this phenomenon of hybrid vigour. Working soon after the rediscovery of Mendel's laws of inheritance, Shull created lines of corn that declined in vigour and productivity with progressive inbreeding. When, however, he crossed these lines, the F]S were highly uniform, viable, and productive (Shull 1908). Shull's experiments were soon replicated on experimental farms and word of their economic potential spread quickly. Over the next two decades, the discovery of heterosis had a revolutionary impact on agricultural productivity. James F. Crow (1998) described the exploitation of heterosis in plant breeding as one of genetics' "greatest triumphs". Today, heterosis is routinely exploited to increase crop yields and improve weight gain in farm animals (e.g., Sellier 1976, Sprague 1983, Fairfull 1990). Heterosis occurs in the offspring of crosses between populations because recessive deleterious alleles contributed by one parent are masked by normal alleles from the other parent (dominance). In addition, the offspring of crosses between genetically differentiated populations may be more heterozygous at loci where heterozygotes have superior fitness (overdominance Crow 1948). It is often said that heterosis is the reverse of inbreeding depression (e.g., Falconer and Mackay 1996), but this explanation of heterosis has created confusion in the literature. The frequencies of deleterious alleles are -85 -likely to differ among populations due to selection and random drift (Crow 1948, Whitlock et al. 2000). Therefore, matings between populations can yield offspring that show heterosis, even if offspring from the most inbred and outbred crosses within populations perform equally well. Heterosis has management implications for small populations because immigrant genes will spread rapidly in a population when the descendants of immigrants are more fit (Ingvarsson and Whitlock 2000). Recently, two empirical studies have demonstrated the potential impact of heterosis. First, Saccheri and Brakefield (2002) established six laboratory populations of the squinting bush brown butterfly (Bicyclus anynand). Each was comprised of 29 purebred families from matings between resident males and females and one hybrid family from a mating between a resident male and an immigrant female. Four generations later, the contribution of the irnmigrant founders to the six gene pools was 2 to 71 times greater than the average contribution of the resident founders. Second, Ebert et al. (2002) removed water fleas (Daphnia magna) and their eggs from rock pools. After rain refilled the pools, they reintroduced 200 of the original residents and added 200 individuals of an immigrant clone to each pool. Hybrids between immigrants and residents increased in frequency in all rock pools where . hybrids were recovered. In most cases, hybrid genotypes dominated the gene pool. These demonstrations of heterosis are important because they show that gene flow from individuals translocated to an inbred population may greatly exceed the levels expected from numbers of immigrants alone. 5.3 IMMIGRATION MAY SAVE DECLINING POPULATIONS: GENETIC RESCUE If the flow of immigrant genes reverses the genetic deterioration of an inbred population, the population is said to have experienced "genetic rescue". As discussed above, heterosis may accelerate the genetic rescue of a population by enhancing population productivity (Richards 2000). However, even if the offspring of immigrants have average or below average fitness, gene flow can reverse or prevent the genetic deterioration of a population in the long term. Work on Scandinavian grey wolves (Canis lupus) provides a nice example of genetic rescue in a natural system (Vila et al. 2003). For several generations after a population was founded by only two individuals, the population failed to grow beyond a single pack. This resulted in matings between relatives and a decline in heterozygosity at DNA marker loci. The arrival of a single irnmigrant female led to inbreeding avoidance, increased heterozygosity, rapid spread of the immigrant's genes, and exponential population growth. -86-For Greater prairie chickens (Tympanuchus cupido pinnatus), managers attempted genetic rescue of a remnant population via translocation. Over a 28-year period, population size had declined from over 2000 individuals to 50 and there was. a marked reduction in egg hatching rates (Westemeier et al. 1998). Prairie chickens in that population also had lower mean heterozygosity and allelic diversity at DNA marker loci than populations in other states (Bouzat et al. 1998), suggesting loss of genetic variation. Concern that extinction was imminent prompted managers to capture 271 individuals from larger and more genetically diverse populations in Minnesota, Kansas, and Nebraska and introduce them to the small population in Illinois. After the translocation, egg viability was restored to historical levels, and the numbers of males at one mating ground increased. It is uncertain, however, how much this genetically "restored" population increased in size, as only data for males were reported (Westemeier et al. 1998). It is also questionable whether this example represents genetic rescue of the original population or genetic replacement by the genes ofthe transplanted individuals (see Section 5.5). 5.4 IMMIGRATION MAY LOWER INDIVIDUAL AND POPULATION FITNESS: OUTBREEDING DEPRESSION Although translocating animals and building corridors can rescue populations genetically, there is a risk that problems may be created rather than resolved. The problem, outbreeding depression or hybrid breakdown (Templeton 1986), arises when the offspring of crosses between populations show lower survival or reproductive success than one or both of the original populations. Outbreeding depression can occur when individuals carry variants of a gene that are not well adapted to local environmental conditions. It can also arise when mixing of two gene pools breaks apart pairs or sets of alleles that are intrinsically coadapted. Two alleles are coadapted if the selective advantage of an allele for one gene depends on interaction with an allele for a gene at a different locus. Alleles are intrinsically coadapted if the compatibility is largely independent ofthe environment (Edmands 2002). The breakup of coadapted alleles does not occur immediately because Fjs carry a haploid set of chromosomes from each parental line. Segregation and recombination only begin to break apart pairs or sets of alleles in the second (F2) generation (Dobzhansky 1948, Lynch and Walsh 1998, p. 223). An example of intrinsic coadaptation is found in platyfish (Xiphophorus maculatus), a small bony fish familiar to aquarists. These fish carry a gene, Tu, that makes them vulnerable to melanomas, but most individuals also carry a masking tumour-suppressor gene, R. When tumour-free fish carrying the tumour gene and the suppressor (genotype: TuITu, RIR) are crossed with a strain that carries neither of -87-these alleles (genotype: -/-, -/-), the ¥\S (genotype: Tul-, RI-) are all tumour-free because they all carry the suppressor (Adam et al. 1993). Crosses among F^, however, yield some F2s that have extensive tumours. These unfit individuals have an allele for melanoma formation at the tumour-forming locus but no tumour suppressor allele (genotype: Tul-, -I- or TuITu, -/-). A recent study of freshwater shrimp (Paratya australiensis) shows how outbreeding depression can have disastrous consequences in a conservation program. When shrimp were translocated between pools from two different sub-catchments in the same river system in Australia, all resident genotypes were extirpated in one pool after only 7 years (Hughes et al. 2003). The extirpation occurred in two steps. First, translocated males were preferred as mates by both resident and translocated females; second, crosses between translocated males and resident females produced unfit offspring. 5.5 HIGH IMMIGRATION RATES MAY CAUSE GENE SWAMPING High levels of gene flow can also be a problem when they cause maladaptation via lost genetic variance at loci under selection. This is called "gene swamping" (Lenormand 2002). A natural example of gene swamping comes from work on blue tits (Parus caeruleus) of the Mediterranean region. In a study by Blondel and others (1992, 1993), birds in evergreen habitats laid more eggs and bred earlier than expected based on the low levels and seasonality of food availability for that habitat. The maladaptation occurred because populations in these poor quality evergreen habitats were maintained by immigration from deciduous habitats, where there was an abundant and early food supply and, thus, selection for larger clutches and earlier laying (Blondel et al. 2001). The genetic restoration program for the endangered Florida panther (Puma concolor coryi), a sub-species of the cougar (Puma concolor), has proven highly controversial because of concerns about gene swamping. Cougars from a closely related subspecies were translocated from Texas to Florida to reverse symptoms of inbreeding depression in the tiny Florida panther population (Mansfield and Land 2002). Based on a simulation study of expected evolutionary effects, a scientific panel recommended 20% gene flow from Texas cougars in the first generation of translocation, followed by 2-4% gene flow in later generations (Hedrick 1995). In 1995, eight female cougars were moved from Texas to Florida and the genetic consequences were monitored. By 2000, introgression levels had reached 20% and successful genetic restoration was proclaimed (McBride 2000, Jansen and Logan 2002). By 2001, however, the contribution of Texas individuals to the population gene pool had exceeded 24% and Maehr and Lacy (2002) denounced claims of successful restoration as premature. They showed that inbreeding had resumed, and they suggested that demographic and social variation might promote swamping.that largely eliminates the Florida genome. Four individuals with Texas ancestry were from father-daughter matings and almost half of the Texas genes in the population were descended from just one female. Maehr and Lacy called for major changes in management strategy, including removal of panthers with high levels of Texas ancestry. 5.6 FROM THEORY TO PRACTICE While reading papers that reviewed the potential benefits and pitfalls of enhancing gene flow, I encountered six recommendations to biologists considering this approach for managing small populations: (1) gene pools should only be mixed if significant inbreeding depression has been demonstrated (Edmands 2002), (2) populations should live in a similar habitat and show similar adaptive traits (Edmands 2002), (3) tests ofthe consequences of hybridization should be conducted prior to their use in a conservation context (Edmands 2002), (4) translocated individuals should be marked and their performance compared to natives over several generations in the wild (Scott and Carpenter 1987, Edmands 2002), (5) a minimum of 1 and a maximum of 10 migrants per generation is a desirable amount of connectivity among populations (Mills and Allendorf 1996), and (6) there should be a plan of action for when gene flow exceeds target levels (Maehr and Lacy 2002). While these guidelines are clearly helpful, managers still face two difficult questions before manipulating the genetics of a population of conservation concern. First, what are the best ways to assess the genetic health of a population? And second, how likely is it that mixing gene pools will improve genetic health when the six guidelines above are followed? One reason that answers to these two questions are unclear is because there have been few studies describing how gene flow "normally" affects the genetic health of small populations that are not thought to be at high risk of going extinct. Such studies are rare because they are logistically difficult to conduct. Until recently, immigrants . to a population could only be detected if all non-immigrants were marked before the arrival of immigrants, or if immigrants themselves were marked before arriving. Immigrant individuals can now be identified with molecular markers via parentage assignment (e.g., Telfer et al. 2003) or multilocus genotyping (e.g., Rannala and Mountain 1997, Wilson and Rannala 2003). These methods, however, require considerable time and expense and have been applied in only a few studies to date. -89-5.7 IMMIGRATION AND THE GENETIC H E A L T H OF MANDARTE ISLAND SONG SPARROWS The data on the song sparrows of Mandarte Island are extraordinary because it is possible to identify immigrants and their descendants and monitor their fitness over time. Since 1975, the breeding success and survival of all birds has been tracked every year except 1980. Throughout the 28-year study period (1975 - 2002), virtually all nests were found and offspring were banded prior to independence from parental care. Immigrants to the population were identified by the absence of leg bands and were typically mist netted and banded before the breeding season in early spring. Because all immigrants and all residents in the population were individually marked, and the average generation time in these birds is only about 2.3 years (Smith et al, in review), there exists an unusually deep pedigree. Prior work has shown that inbred matings occur regularly in the song sparrow population and that inbreeding depression reduces the fitness of some individuals in the population in most years (Keller et ai, in review; Keller 1998). However, there are several indications that the genetic health of this population is satisfactory and not deteriorating. First, pedigree analysis suggests that average inbreeding levels have remained relatively stable for more than five generations (Keller et al, in review). Second, song sparrows in this population show heritable variation for morphological traits that are under natural selection (Smith and Zach 1979, Smith and Dhondt 1980, Schluter and Smith 1986), thus suggesting that • individuals in the population carry differing adaptations. Third, genetic variation at neutral molecular markers recovered quickly after the population bottleneck in 1989 (Keller et al. 2001). Fourth, and perhaps most importantly, the population has rebounded from periods of low density three times since 1975 (Smith et al., in review). Immigrants may play an important role in maintaining the genetic health of this population. To explore their contributions in a natural population, I discuss past work on the fitness of immigrant song sparrows and their descendants on Mandarte Island (Section 5.8) and then present three new analyses. First, I track immigrant lineages to understand how irnmigrant genes spread through the pedigree and contribute to gene pool turnover (Section 5.9). Second, I compare the relative fitness of immigrant and native genes (Section 5.10). Third, I examine the contribution of immigrants to the gain and loss of alleles at neutral marker loci (Section 5.11). -90-5.8 HETEROSIS AND OUTBREEDING DEPRESSION IN IMMIGRANT DESCENDANTS Two to three immigrants join Mandarte Island per generation (Smith et al, in review). Due to the regular recruitment of immigrants to Mandarte, it is possible to study immigrants, natives (birds with parents and grandparents that all hatched oh the island), and crosses between them in nearly all years. Recently, this fact allowed Lukas Keller, Peter Arcese, and me to explore how an individual's ancestry influenced its breeding success and survival (Marr et al. 2002, Chapter 2). Some findings of that work were surprising and they inspired the new analyses presented in sections 5.9 and 5.10 below. In our study, we made a prediction that the offspring of immigrants would out-perform those of residents because they would be relatively outbred. We also expected gains seen in the offspring of immigrants to gradually diminish in subsequent generations because heterosis is maximized in F i crosses between populations and is expected to decline thereafter (Lynch and Walsh 1998). We considered the possibility that Fi or F 2 descendants of immigrants might experience outbreeding depression but thought it unlikely. Although the origin of only one immigrant to Mandarte Island was known (Smith et al, in review), work on nearby island populations of song sparrows had detected frequent short-range dispersal by juveniles among islands (Smith et al. 1996; A. B. Marr, unpublished data). These data suggested that most dispersers between populations arrived from nearby islands that shared similar habitat and environmental conditions, leading us to think that outbreeding depression was an unlikely outcome. To test our predictions, we divided the population into five frequently occurring pedigree groups: (1) immigrants, birds that did not hatch on Mandarte Island; (2) natives, birds with two resident-hatched parents and four resident-hatched grandparents; (3) Fjs, with an immigrant parent from either their maternal side or their paternal side. The other parent and its parents were both resident-hatched individuals; (4) F2s, individuals with an immigrant grandparent and resident-hatched grandparent on both their maternal and their paternal sides; and (5) resident backcrosses, individuals with one immigrant grandparent and three resident-hatched grandparents. For these five pedigree groups, we conducted analyses of fitness. As predicted, F]S generally performed well. For example, adult FjS reared as many or more offspring over their life spans than the average for natives and immigrants (Figs. 5.1a,b; statistical note 1). The survival of juvenile FjS in their first year also exceeded that of juvenile natives (Fig. 5.1c). However, in both adults and juveniles, the gains shown by F]S were not seen in F2s. For example, F2 females reared only half as many offspring as Fi females. F 2 males fared even worse, rearing only about one third as many offspring as Fi males. Survival of F 2 juveniles was about half the survival of F i -91 -juveniles. On average, F2s also tended to show poor survival compared to native juveniles (p = 0.06; Fig. 5.1a) and F2s had poor breeding success when compared to immigrants and natives of the same sex (Figs. 5.1b,c). However, differences in breeding success between F2s, immigrants, and natives were not significant. The magnitude of the performance differences between F]S and F2s surprised us. Theory in population genetics suggests that F2s should not reproduce or survive as well as Fjs because heterozygosity in F2s should be reduced relative to Fjs. We did not, however, anticipate such a marked difference between FjS and F2s. One possibility that we explored in the discussion of that paper (Chapter 2) was that the poor performance in F2s might be evidence that mixing gene pools disrupted coadapted gene complexes. This finding was important because it suggested that the song sparrows on Mandarte Island formed a population that was genetically differentiated from neighbouring populations. Soon after our study was published, I read about studies on plants and fruit flies showing that hybrid breakdown in F3s can be even greater than in F2s because recombination continues to break apart coadapted gene complexes (Fenster and Galloway 2000, Andersen et al. 2002). These papers led me to question how much immigrant genes were actually contributing to the gene pool of the Mandarte song sparrow population over the long term. 5.9 THE SPREAD OF IMMIGRANT LINEAGES AND GENE POOL TURNOVER To better understand the contribution of immigrants to the population gene pool, I first used pedigree analysis. Because not all immigrants produced breeding recruits and the fitness of F2s was poor, immigrant genes could have remained rare and confined to a small fraction of the pedigree. Alternatively, they could have spread widely through the population, diluting or replacing the contributions of their predecessors. My method was to use the lines of descent from the pedigree to estimate the genetic contribution of each immigrant to the gene pool of the population. If an individual had one immigrant parent and one native parent, I assumed that half of its genome could be attributed to the immigrant parent. If a native bred with a bird that was half immigrant-half native, I assumed that the genome of their offspring would be one-quarter immigrant, and so forth. I then summed the contributions that each immigrant made to its descendants and divided by the number of individuals in the population to determine what percent of the population gene pool could be attributed to each immigrant each year. If an irnmigrant died without rearing offspring that became breeders, then the immigrant contributed to the gene pool during its -92-lifetime but not beyond. I studied only those immigrants arriving after 1981 even though the population was studied in earlier years (i.e., 1975 - 1979), because many lineages could not be tracked through a one-year gap in the banding of nestlings in 1980. One problem with this analysis is that female song sparrows sometimes mate with males other than their social mates, and this is a source of error in the pedigree (Chapter 3). Ideally, we would have eliminated these errors with molecular techniques, but this was not feasible here. DNA samples were not collected in early years of the study and genotypes of Mandarte song sparrows have yet to be determined for several recent years. Rather than correcting known paternity errors for a few years in the middle of the pedigree, I left any suspected errors unchanged. Although extra-pair paternity may hamper the interpretation of my findings here and in section 5.10,1 proceeded with my analyses because some of my methods for studying immigrant contributions are novel and, therefore, might be helpful to others. Also, paternity errors here may have had little impact on the results because males that lost paternities in their own territory often fathered similar numbers of offspring in other territories (O'Connor 2003). In analyses where groups of individuals were compared, misclassification of some individuals is likely to have reduced differences between groups, making my statistical analyses conservative (see Chapter 3). By tracking lineages, I discovered that eventually all recruits to the population had immigrant ancestors and that the genes of some immigrants had spread throughout the pedigree. By 1995, all new recruits to the population had at least one irnmigrant ancestor that arrived since 1981 (Fig. 5.2). Four of 8 male immigrants and 11 of 17 female immigrants reared at least one offspring that later recruited. Of those immigrants whose lineage could be tracked for at least 10 years, 1 of 5 male immigrants and 7 of 12 female immigrants had descendants in the population a decade later. The three most successful female immigrants arriving before 1993 appeared in the pedigree of every new recruit to the population in 2002. Some immigrants made a substantial contribution to the gene pool of breeding birds. Four females that arrived in the two years after the 1989 bottleneck when population density was low made a particularly large contribution. In 2002, 4% to 6% of the gene pool stemmed from each of these four immigrant females (Fig. 5.3). The male immigrant that arrived in 1990 also contributed to the gene pool, but his contribution was a meagre 0.3% in 2002. Overall, 39% of the gene pool of the population in 2002 could be attributed to immigrants that joined the population after 1981 (Fig. 5.3). The remaining 61% of genes stemmed from descendants of 21 of the 47 birds that were present in 1981 and from 3 resident-hatched birds of unknown parentage that fledged unhanded in 1992. -93 -5.10 THE COMPETITIVENESS OF IMMIGRANT GENES To understand the relationship between immigrants and gene flow, I also wanted to determine if immigrant genes were out-competing native Mandarte genes or vice versa. Based on the analyses of lifetime reproductive success and juvenile survival discussed previously (Section 5.8, Fig. 5.1), one might hypothesize that immigrant genes would spread quickly relative to native genes for a short period and more slowly thereafter. This pattern might be expected because F]S survive well to age one and are fecund as adults, but F2s perform poorly. However, the spread of immigrant genes also depends strongly on the relative fitness of backcrosses and their descendants in later generations. In addition, in species that breed in multiple years, the rate at which an individual's genes spread can depend on when in life it breeds, the breeding age of its offspring, and so forth. These facts suggested that I needed to compare the contributions over time of individual immigrants with the contributions of natives ofthe same sex from the same cohort. To do so, I used the method for calculating immigrant gene pool contributions discussed in Section 5.9 to calculate gene pool contributions of native individuals. I then compared the gene pool contributions for immigrants with natives that were the same age and same sex in the same year. My analysis showed that female immigrants contributed more to the gene pool of the breeding population than natives one year after their arrival, but their advantage diminished just two years after their arrival (Fig. 5.4a; statistical note 2). Eight years after their arrival, the genes of female immigrants were 25% less common on average than the genes of native females from their cohort. This difference of 25% after eight years, however, was not statistically significant (Fig. 5.4a). For males, the spread of immigrant genes progressed erratically for the first few years after their arrival, probably due to the small sample sizes of immigrant males (n = 4 breeding males; Fig. 5.4b; statistical note 2). However, over the long term, immigrant males appeared to be about as successful as native males. 5.11 THE EFFECT OF IMMIGRANTS ON NEUTRAL GENETIC VARIATION In studies of other systems, molecular markers that are selectively neutral sometimes have been shown to correlate with adaptive variation (Allendorf and Leary 1986, Avise 1994, Hansson and Westerberg 2002, Reed and Frankham 2003). For the Mandarte song sparrows, genetic data were available at eight microsatellite loci for song sparrows alive from 1987-1996. Six microsatellite markers were developed for use on the Mandarte song sparrows by Jeffery et al. (2001) and two markers were obtained from research on other passerines (Escfil; Hanotte et al. 1994; GF5: Petren 1998). A prior study -94-using these markers showed that the population bottleneck in 1989 was associated with a decline in allelic diversity and heterozygosity (Keller et al. 2001). However, heterozygosity returned to pre-bottleneck levels after one year, and allelic diversity recovered within three years. Keller et al. (2001) also showed, by removing irnmigrant ancestors from pedigrees, that there would have been a continued decline in allelic diversity and heterozygosity without the arrival of immigrants. I performed new analyses here to clarify the extent to which immigrants affected genetic variation across the bottleneck. In particular, I wanted to determine if immigrants primarily reintroduced genetic variation that had been present before the bottleneck or if the bottleneck changed the genetic variation present in the population. This required me to track each allele that was lost and gained across years. For this analysis, I used a slightly expanded dataset from the one available to Keller et al. (2001). In particular, I added genotypes for a few unmated and floater males based on labwork by K. D. O'Connor, L. F. Keller, and me. As shown in Table 5.1, blood sampling effort varied over time, ranging from 45% to 100% of the population across years. Analysis of these data showed that some alleles that were extirpated during the 1989 bottleneck were reintroduced over the next 7 years. In 1987, genotypes were available for 92 resident adults (73% of all adults alive in that year; Table 5.1). Together, these birds carried 60 alleles at the 8 loci (Fig. 5.5). Ten years later, 12 of the 60 alleles (20%) had been extirpated from the population, 9 other alleles (15%) were extirpated and reintroduced, and 39 of 60 alleles (65%) were present continuously in the population. Over this same 10-year period, 21 new alleles that were not observed in 1987 were detected (Fig. 5.5). Two of the 21 novel alleles were extirpated a year after being introduced. Thus, by 1996, 128 adults carried 67 alleles at the 8 loci (genotypes were available for all adults; Table 5.1). Nineteen of 67 (28%) had not been observed in the two years before the bottleneck. I also found that the two genotyped immigrants that arrived in 1987 and 1988 when the breeding population was large (>105 individuals) carried no unique alleles. In contrast, the seven genotyped immigrants that arrived after the bottleneck in February 1989 each carried 2-8 alleles that were not present in the population upon their arrival (Table 5.2). Together, these analyses suggest that immigrants reintroduced some alleles that had been lost and introduced new alleles to the gene pool of the population. -95 -5.12 SUMMARY AND SYNTHESIS A fundarnental challenge in conservation biology is developing strategies that restore and maintain the genetic health of small populations. Enhancing gene flow by translocating animals between populations is one approach that has had variable success. In one possibly successful case, translocations reversed symptoms of inbreeding depression and perhaps halted the decline in population size of Greater prairie chickens in Illinois (Westemeier et al. 1998). However, translocations led to outbreeding depression and extirpation of resident genotypes in a freshwater shrimp population in Australia (Hughes et al. 2003), and some scientists are concerned that the genetic restoration program for Florida panthers is causing gene swamping (Maehr and Lacy 2002). While biologists have recommended guidelines for management strategies to enhance gene flow, managers still face questions about how to assess the genetic health of a population and how to judge if greater gene flow is likely to be beneficial. One difficulty in answering these questions is that there have been few detailed studies demonstrating the contributions of natural immigrants to wild populations. One exception is work on Scandinavian gray wolves, where irnmigration restored genetic variation to a population that had suffered from random genetic drift and inbreeding (Vila et al. 2003). In this chapter, I have presented another case study on the contributions of immigrants in a natural population. Immigrant song sparrows to Mandarte Island arrived at a trickle of two to three birds per generation (Smith et al., in review), a level that is within the range recommended for maintaining genetic health of small populations (Mills and Allendorf 1996). At this level of immigration, inbreeding still occurred regularly and inbreeding depression affected the fitness of some individuals in most years. (Keller et al, in review; Chapter 3). However, there were reasons to believe that the genetic health of the Mandarte song sparrows was satisfactory. Namely, inbreeding levels and reproductive performance have held steady in recent years, morphological traits that are under selection show heritable variation, heterozygosity and allelic diversity of molecular markers recovered quickly after the severe population bottleneck in 1989, and numbers of breeding sparrows rebounded after three bottlenecks. Female survival, however, has declined recently (Smith et al, in review). New analyses presented in this chapter show that immigrants had a large and lasting effect on the gene pool of this population and, thus, immigrants likely play an important role in maintaining its genetic health. I estimated that 39% of genes in the gene pool in 2002 stemmed from immigrants that joined the population since 1981. Although extra-pair fertilizations created error in this analysis, it appears that the genes of immigrants spread widely through the pedigree. After the severe population bottleneck in 1989, - 96 -analysis of neutral molecular markers showed that immigrants played a key role in reintroducing genetic variation that was lost during the bottleneck and in introducing novel genetic variation. Although more work is needed to understand the links between variation in molecular markers and variation in quantitative traits in this and other populations, the changes at neutral marker loci raise the possibility that immigrants restored adaptive variation present in the population after the bottleneck. Interestingly, despite evidence that immigrants contributed extensively to the overall gene pool, close inspection of the data revealed that the genes of immigrants did not out-compete the genes of natives from their cohort over the long term. This contrasts with recent empirical studies on water fleas and butterflies, which found that heterosis increased the success of immigrant genes by several fold. One speculation for this difference is that the genetic health of the water flea and butterfly populations may have been greatly diminished prior to the arrival of immigrants (Gaggiotti 2003). Thus, the strong heterosis observed in those studies may have been a symptom of genetic rescue. In contrast, for Mandarte song sparrows, there was no long-term benefit to being an immigrant. Like others, I have struggled to determine what constitutes a genetically healthy population and to measure the role of immigrants. The song sparrow data were not ideal for this purpose due to the problem of pedigree error. However, few studies from natural populations will be free of this particular problem (Chapter 3). Nonetheless, I hope that my approach will inspire more dialogue on this topic. I strongly urge others with even better datasets to try assessing the genetic health of their study populations. Only with more case studies will we be able to understand the 'normal' influence of immigrants on the genetic health of natural populations. Such an understanding could help managers of threatened populations to set goals for gene flow levels among populations and to assess the risks of genetic restoration programs. There would also be value in theoretical and experimental work to clarify what genetic phenomena characterize small but genetically healthy populations. Such studies are crucial because destruction and fragmentation of habitat is likely to continue to threaten the population viability of many species of conservation concern. 5.13 LITERATURE CITED Adam, D., N. Dimitrijevic, and M. Schartl. 1993. Tumor suppression mXiphophorus by an accidentally acquired promoter. Science 259:816-819. -97-Allendorf, F. W., and R. F. Leary. 1986. Heterozygosity and fitness in natural populations of animals. In M. E. Soule (ed), Conservation biology: The science of scarcity and diversity, pages 57-76. Sinauer Associates, Inc., Sunderland, MA. Andersen, D. H., C. Pertoldi, V. Scab, and V. Loeschcke. 2002. Intraspecific hybridization, developmental stability and fitness in Drosophila mercatorum. Evolutionary Ecology Research 4:603-621. Avise, J. C. 1994. Molecular markers, natural history and evolution. Chapman & Hall, New York. Black, J. M., A. P. Marshall, A. G. A, N. Santos, H. Hoshide, J. Medeiros, J. Mello, C. N. Hodges, and L. K. L. 1997. Survival, movements, and breeding of released Hawaiian geese: An assessment of the reintroduction program. Journal of Wildlife Management 61:1161-1173. Blondel, J., P. C. Dias, M. Maistre, and P. Perret. 1993. Habitat heterogeneity and life-history variation of Mediterranean Blue Tits (Parus caeruleus). Auk 110:511-520. Blondel, J., P. Perret, M. Maistre, and P. C. Dias. 1992. Do harlequin mediterranean environments function as source sink for Blue Tits (Parus caeruleus L.). Landscape Ecology 6:213-219. Blondel, J., P. Perret, P. C. Dias, and M. M. Lambrechts. 2001. Is phenotypic variation of blue tits (Parus caeruleus L.) in Mediterranean mainland and insular landscapes adaptive? Genetics, Selection and Evolution. 33:S121-S139. Bouzat, J. L., H. H. Cheng, H. A. Lewin, R. L. Westemeier, J. D. Brawn, and K. N. Paige. 1998. Genetic evaluation of a demographic bottleneck in the Greater Prairie Chicken. Conservation Biology 12:836-843. Crow, J. F. 1948. Alternative hypotheses of hybrid vigor. Genetics 33:477-487. Crow, J. F. 1998. 90 years ago: The beginning of hybrid maize. Genetics 148:923-928. Diamond, J. M. 1989. Overview of recent extinctions. In D. Western and M. Pearl (eds), Conservation for the twenty-first century, pages 37-41. Oxford University Press, New York. Dobzhansky, T. 1948. Genetics of natural populations. XVIII. Experiments on chromosomes of Drosophilapseudoobscura from different geographical regions. Genetics 33:588-602. Ebert, D., C. Haag, M. Kirkpatrick, M. Riek, J. W. Hottinger, and V. I. Pajunen. 2002. A selective advantage to immigrant genes in a Daphnia metapopulation. Science 295:485-488. Edmands, S. 2002. Does parental divergence predict reproductive compatibility? Trends in Ecology and Evolution 17:520-527. -98 -Engeman, R. M., R. E. Martin, B. Constantin, R. Noel, and J. Woolard. 2003. Monitoring predators to optimize their management for marine turtle nest protection. Biological Conservation 113:171-178. Fairfull, R. W. 1990. Heterosis. In R. D. Crawford (ed), Poultry breeding and genetics, pages 913-933. Elsevier, Amsterdam. Falconer, D. S., and T. F. C. Mackay. 1996. Introduction to Quantitative Genetics, 4th edition. Longman Group Ltd, Essex, England. Fenster, C. B., and L. F. Galloway. 2000. Population differentiation in an annual legume: Genetic architecture. Evolution 54:1157-1172. Fisher, R. A. 1949. The theory of inbreeding, Edinburgh. Gaggiotti, O. E. 2003. Genetic threats to population persistence. Annales Zoologici Fennici 40:155-168. Hanotte, O., C. Zanon, A. Pugh, C. Breig, A. Dixon, and T. Burke. 1994. Isolation and characterization of microsatellite loci in a passerine bird: the reed bunding Emberiza schoeniclus. Molecular Ecology 3: 529-530. Hansson, B., and L. Westerberg. 2002. On the correlation between heterozygosity and fitness in natural populations. Molecular Ecology 11:2467-2474. Hedrick, P. W. 1995. Gene flow and genetic restoration: The Florida panther as a case study. Conservation Biology 9:996-1007. Hochachka, W. M. In review. Unequal lifetime reproductive success, and its implications for small isolated populations. In J. N. M. Smith (ed), Biology of Small Populations: The Song Sparrows of Mandarte Island. Oxford University Press, London, UK. Hughes, J., K. Goudkamp, D. Hurwood, M. Hancock, and S. Bunn. 2003. Translocation causes extinction of a local population of the freshwater shrimp Paratya australiensis. Conservation Biology 17:1007-1012. Ingvarsson, P. K., and M. C. Whitlock. 2000. Heterosis increases the effective migration rate. Proceeding of the Royal Society of London B 267:1321-1326. Jansen, D., and T. Logan. 2002. Improving prospects for the Florida panther. United States Fish and Wildlife Service Endangered Species Bulletin 27:16-17. Jeffery, K. J., L. F. Keller, P. Arcese, and M. W. Bruford. 2001. The development of microsatellite loci in the song sparrow, Melospiza melodia (Aves) and genotyping errors associated with good quality DNA. Molecular Ecology Notes 1: 11-13. -99-Keller, L. F. Inbreeding and its fitness effects in an insular population of song sparrows (Melospiza melodia). Evolution 52: 240-250. Keller, L. F., K. J. Jeffery, P. Arcese, M. A. Beaumont, W. M. Hochachka, J. N. M. Smith, and M. W. Bruford. 2001. Immigration and the emphemerality of a natural population bottleneck: Evidence from molecular markers. Proceedings of the Royal Society of London B 268:1387-1394. Keller, L. F., A. B. Marr, and J. M. Reid. In review. The genetic consequences of small population size: Inbreeding and loss of genetic variation. In J. N. M. Smith (ed), Biology of Small Populations: The Song Sparrows of Mandarte Island. Oxford University Press, London, UK Keller, L. F., and D. M. Waller. 2002. Inbreeding effects in wild populations. Trends in Ecology and Evolution 17:230-241. Lenormand, T. 2002. Gene flow and the limits to natural selection. Trends in Ecology and Evolution 17:183-189. Lynch, M., and B. Walsh. 1998. Genetics and analysis of quantitative traits. Sinauer Associates, Sunderland, MA. Madsen, T., B. Stille, and R. Shine. 1996. Inbreeding depression in an isolated population of adders Vipera berus. Biological Conservation 75:113-118. Maehr, D. S., and R. C. Lacy. 2002. Avoiding the lurking pitfalls in Florida panther recovery. Wildlife Society Bulletin 30:971-978. Mansfield, K. G., and E. D. Land. 2002. Cryptorchidism in Florida panthers: Prevalence, features, and influence of genetic restoration. Journal of Wildlife Diseases 38:693-698. Marr, A. B., L. F. Keller, and P. Arcese. 2002. Heterosis and outbreeding depression in descendants of natural immigrants to an inbred population of song sparrows (Melospiza melodia). Evolution 56:131-142. McBride, R. 2000. Current panther distribution and habitat use a review of field notes fall 1999-winter 2000. Florida Fish and Wildlife Commission contract #95128. Livestock Protection Company, Alpine, Texas, USA. Mills, L. S., and F. W. Allendorf. 1996. The one-migrant-per-generation rule in conservation and management. Conservation Biology 10:1509-1518. O'Connor, K. D. 2003. Extra-pair mating and effective population size in the song sparrow (Melospiza melodia). M.Sc. Thesis, University of British Columbia, Vancouver. -100-Petren, K. 1998. Microsatellite primers from Geospiza fortis and cross species amplication in Darwin's finches. Molecular Ecology 7: 1782-1784. Rannala, B., and J. L. Mountain. 1997. Detecting immigration by using multilocus genotypes. Proceedings of the National Academy of Sciences 94:9197-9201. Reed, D. H., and R. Frankham. 2003. Correlation between fitness and genetic diversity. Conservation Biology 17:230-237. Richards, C. M. 2000. Inbreeding depression and genetic rescue in a plant metapopulation. American Naturalist 155:383-394. Rothstein, S. I., and T. L. Cook. 2000. Cowbird management, host population limitation, and efforts to save endangered species. In J. N. M. Smith, T. L. Cook, S. I. Rothstein, S. K. Robinson, and S. G. Sealy (eds), Ecology and management of cowbirds and their hosts, pages 323-332. University of Texas Press, Austin, TX. Saccheri, I., M. Kuussaari, M. Kankare, P. Vikman, W. Fortelius, and I. Hanski. 1998. Inbreeding and extinction in a butterfly metapopulation. Nature 392:491-494. Saccheri, I. J., and P. M. Brakefield. 2002. Rapid spread of immigrant genomes into inbred populations. Proceedings of the Royal Society of London B 269:1073-1078. Schluter, D., and J. N. M. Smith. 1986. Natural selection on beak and body size in the song sparrow. Evolution 40:221-231. Scott, J. M., and J. W. Carpenter. 1987. Release of captive-reared or translocated endangered birds: What do we need to know? Auk 104:544-545. Sellier, P. 1976. The basis of crossbreeding in pigs: A review. Livestock Production Science 3:203-226. Shull, G. H. 1908. The composition of a field of maize. American Breeders Association Report 4:296-301. Shull, G. H. 1914. Duplicated genes for capsule form in Bursa bursapastoris. Zeitschrift fur Induktive Abstammungs und Vererbungslehre 12:97-149. Smith, J. N. M., and A. A. Dhondt. 1980. Experimental confirmation of heritable morphological variation in a natural population of song sparrows. Evolution 34:1155-1158. Smith, J. N. M., A. B. Marr, L. F. Keller, and P. Arcese. In review. Fluctuations in numbers: Population limitation, regulation, and catastrophic mortality. In J. N. M. Smith (ed), Biology of Small Populations: The Song Sparrows of Mandarte Island. Oxford University Press, London, UK. -101 -Smith, J. N. M., M. J. Taitt, C. M. Rogers, P. Arcese, L. F. Keller, A. L. E. V. Cassidy, and W. M. Hochachka. 1996. A metapopulation approach to the population biology of the song sparrow Melospiza melodia. Ibis 138:120-128. Smith, J. N. M., and R. Zach. 1979. Heritability of some morphological characters in a song sparrow population. Evolution 33:460-467. Sprague, G. F. 1983. Heterosis in maize: Theory and practice. In R. Frankel (ed), Heterosis: Reappraisal of theory and practice. Monographs on theoretical and applied genetics; 6, pages 47-70. Springer-Verlag, Berlin. Stockwell, C. A., M. Mulvey, and G. L. Vinyard. 1996. Translocations and the preservation of allelic diversity. Conservation Biology 10:1133-1141. Telfer, S., S: B. Piertney, J. F. Dallas, W. A. Stewart, F. Marshall, J. L. Gow, and X. Lambin. 2003. Parentage assignment detects frequent and large-scale dispersal in water voles. Molecular Ecology 12:1939-1949. Templeton, A. R. 1986. Coadaptation and outbreeding depression. In M. E. Soule (ed), Conservation biology: The science of scarcity and diversity, pages 105-116. Sinauer Associates, Inc., Sunderland, MA. Vila, C , A. Sundqvist, 0. Flagstad, J. Seddon, S. Bjornerfeldt, I. Kojola, A. Casulli, H. Sand, P. Wabakken, and H. Ellegren. 2003. Rescue of a severely bottlenecked wolf (Canis lupus) population by a single immigrant. Proceedings of the Royal Society of London B 270:91-97. Westemeier, R. L., J. D. Brawn, S. A. Simpson, T. L. Esker, R. W. Jansen, J. W. Walk, E. L. Kershner, J. L. Bouzat, and K. N. Paige. 1998. Tracking the long-term decline and recovery of an isolated population. Science 282:1695-1698. Whitlock, M. C, P. K. Ingvarsson, and T. Hatfield. 2000. Local drift load and the heterosis of interconnected populations. Heredity 84:452-457. Wilcove, D. S., C. H. McLellan, and A. P. Dobson. 1986. Habitat fragmentation in the temperate zone. In M. E. Soule (ed), Conservation biology: The science of scarcity and diversity, pages 237-256. Sinauer Associates, Inc., Sunderland, MA. Wildt, D. E., M. Bush, K. L. Goodrowe, C. Packer, A. E. Pusey, J. L. Brown, P. Joslin, and S. J. O'Brien. 1987. Reproductive and genetic consequences of founding isolated lion populations. Nature 329:328-333. Wilson, E. O. 1992. The diversity of life. Belknap Press, Cambridge, MA. -102 -Wilson, G. A., and B. Rannala. 2003. Bayesian inference of recent migration rates using multilocus genotypes. Geneticsl63:1177-1191. 5.14 STATISTICAL N O T E S 1) Details of the statistical methods are given in Marr et al. (2002). In brief, LRS was calculated as the total number of offspring that a bird reared to 24 days of age. This analysis included only birds that laid or fathered eggs at some point during their lifetimes. The mean number of offspring raised in each pedigree group was obtained by using the least-square mean estimates from an ANOVA adjusted for year of hatch (a categorical variable). It was necessary to account for year effects because LRS depends strongly on population density, the presence of cowbirds (Molothrus ater), weather variables, and perhaps other environmental factors in the year of recruitment (Hochachka, in review). For the analysis of juvenile survival to age one, a discrete-time proportional-hazards model was used to compare survival rates by pedigree group (see also Chapter 2 Methods). The analysis accounted for year of hatch (a categorical variable) and lay date (a linear variable) in the season. Planned comparisons between pedigree groups were then assessed by t-tests of the least-square mean estimates. 2) The gene pool contribution of immigrant and native birds were compared using general linear models that first controlled for year effects. Immigrants introduced more genes to the gene pool than native females one year after they arrived (p = 0.0036, n = 90) but there were no statistically significant differences between females in subsequent years (all p = NS). Note, however, that there were only 16 immigrant females in this analysis, making statistical interpretation of small differences difficult. The contribution of male immigrants and male natives did not differ significantly in any year (all p = NS) after immigrants arrived but sample sizes were very small (n = 4). 5.15 ACKNOWLEDGEMENTS P. Arcese, J. N. M. Smith, W. M. Hochachka, M. C. Whitlock, K. Ritland, D. Schluter, J. M. Reid, and L. F. Keller provided helpful comments on earlier drafts. The Tsawout and Tseycum First Nations bands kindly allowed us to work on Mandarte Island. Many people helped collect the field data presented here, including most recently S. D. Wilson, J. M. Reid, R. M. Landucci, K. D. O'Connor, S. E. Runyan, and C. A. Saunders. Support for this research was provided by grants to A. B. Marr from an Adrian Weber Memorial Scholarship in Forest Ecology, a Gene Namkoong Family Scholarship in Forest -103-Genetics, the Sigma Xi Scientific Research Society, the Association of Field Ornithologists, the Western Bird-Banding Association, and the American Museum of Natural History Chapman Fund. -104-5.16 FIGURES AND TABLES Figure 5.1 Lifetime reproductive success of breeding males and females and survival of juveniles by pedigree group. The points show the mean values ± 95% confidence intervals for the two parent groups, natives (Na) and immigrants (Im), and for first- (Fis) and second-generation offspring (F2s). Asymmetry in the 95% CIs for the LRS data occurs because the raw data were transformed to accommodate their Poisson distribution, and the results back-transformed for presentation. Data come from Tables 2.3 and 2.5 of Chapter 2. - 105-Figure 5.2 Fraction of new recruits in the population that have an immigrant ancestor who arrived after 1981. The spike in 1989 and dip in 1990 should not be over-interpreted due to small sample sizes of recruits in those years {n = 5 in 1989, 18 in 1990). Figure 5.3 Fraction of the gene pool of the population that can be traced to immigrants arriving after 1981. The contribution of each of 25 immigrants is depicted with a different pattern. Some contributions are so small that they are barely noticeable. - 107-Figure 5.4 The contributions of individual female and male song sparrows to the Mandarte Island gene pool over time. Points show the fraction of the gene pool of the population attributed to the average immigrant individual (open circles) and native individual (closed circles) ± 95% CIs in the eight years following their recruitment (see explanation of data in sections 5.9 and 5.10). (a.) Females c o 3 .o 0.030 0.025 0.020 c J 0.015 o §. 0.010 CD J 0.005 0.000 (b.) c o "-»—' -9 c o o 0.030 0.025 0.020 0.015 o a. 0.010 CD .1 0.005 0.000 1 2 3 4 5 6 7 8 Years after recruitment Males 2 3 4 5 6 7 8 Years after recruitment -108-Figure 5.5 Count of alleles present in the population at each of 8 microsatellite genetic marker loci from 1987 to 1996. The names of the microsatellite loci are listed at the top of each graph. The population experienced a severe bottleneck in 1989. Alleles that were,present continuously Alleles that were extirpated and reintroduced Alleles that were extirpated Novel alleles that were introduced Mme12 i^EIS|S | i l i | i | i 87 88 89 90 91 92 93 94 95 96 87 88 89 90 91 92 93 94 95 96 4 • 3 • 2 1 1 Mme3 BI mimm 0 1 ^ 1 87 88 89 90 91 92 93 94 95 96 14 12 10 8 6 4 2 0 GF5 87 88 89 90 91 92 93 94 95 96 12 10 8 6 4 2 0 ^ Mme7 mmii 87 88 89 90 91 92 93 94 95 96 Year -109-Table 5.1 The total number of adult birds in the population and the percentage that were genotyped in each year from 1987 to 1996. Note that in 1989, the year that was most crucial to analyses because of small population size, samples were available for 11 of 12 birds. The one bird that was not sampled was an unmated male who never bred. Year Number of birds % genotyped 1987 126 73 1988 105 84 1989 12 92 1990 24 63 1991 55 45 1992 87 72 1993 113 93 1994 127 99 1995 112 99 1996 128 100 -110-Table 5.2 Allelic contributions of nine immigrant song sparrows to the population gene pool for six autosomal and two sex-linked microsatellite loci. Shown are the number of alleles that were novel (N), re-introduced in the same year that they were extirpated from other lineages (S), or re-introduced at least one year after extirpation (R) for each immigrant bird. Females carry two alleles at autosomal loci and one allele at sex-linked loci. Because males are the homogametic sex in birds, they carry two alleles at autosomal and sex-linked loci. Immigrant identification number 86159 86163 86268 54544 54571 20681 64118 64339 64258 Sex-linked loci Mm el 0 0 IS IN 0 0 0 0 0 Mme2 0 0 2S IN IN 0 0 IN 0 Mine 8 0 0 IN 0 0 0 IN 0 0 Mmel2 0 0 IS IR IN 0 IN IS 0 Escpl 0 0 0 IS 0 0 0 0 0 GF5 0 0 IN/IS 0 0 IN 0 0 0 Sex-linked loci Mme3 0 0 IN 0 0 0 0 0 0 Mme7 0 0 0 IN 1N/1R 0 0 IN IN Sex F F F F M F F F M Year of arrival 88 88 89 90 90 91 94 95 95 -111 -

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