Understanding the factors that affect dispersal is a fundamental question in ecology and conservation biology, particularly as populations are faced with increasing anthropogenic impacts. Here we collected georeferenced genetic samples (n?=?2,540) from three generations of black bears (Ursus americanus) harvested in a large (47,739 km2), geographically isolated population and used parentage analysis to identify mother-offspring dyads (n?=?337). We quantified the effects of sex, age, habitat type and suitability, and local harvest density at the natal and settlement sites on the probability of natal dispersal, and on dispersal distances. Dispersal was male-biased (76% of males dispersed) but a small proportion (21%) of females also dispersed, and female dispersal distances (mean ± SE ?=? 48.9±7.7 km) were comparable to male dispersal distances (59.0±3.2 km). Dispersal probabilities and dispersal distances were greatest for bears in areas with high habitat suitability and low harvest density. The inverse relationship between dispersal and harvest density in black bears suggests that 1) intensive harvest promotes restricted dispersal, or 2) high black bear population density decreases the propensity to disperse. Multigenerational genetic data collected over large landscape scales can be a powerful means of characterizing dispersal patterns and causal associations with demographic and landscape features in wild populations of elusive and wide-ranging species.
Many plants and some animal species are polyploids. Nondisomically inherited markers (e.g. microsatellites) in such species cannot be analysed directly by standard population genetics methods developed for diploid species. One solution is to transform the polyploid codominant genotypes to pseudodiploid-dominant genotypes, which can then be analysed by standard methods for various purposes such as spatial genetic structure, individual relatedness and relationship. Although this data transformation approach has been used repeatedly in the literature, no systematic study has been conducted to investigate how efficient it is, how much marker information is lost and thus how much analysis accuracy is reduced. More specifically, it is unknown whether or not the transformed data can be used to infer parentage and sibship jointly, and how different sampling schemes (number and polymorphism of markers, number of individuals) and ploidy level affect the inference accuracy. This study analyses both simulated and empirical data to examine the effects of polyploid levels, actual pedigree structures and marker number and polymorphism on the accuracy of joint parentage and sibship assignments in polyploid species. We show that sibship, parentage and selfing rates in polyploids can be inferred accurately from a typical set of microsatellite loci. We also show that inferences can be substantially improved by allowing for a small genotyping error rate to accommodate the distortion in assumed Mendelian inheritance of the converted markers when large sibship groups are involved. The results are discussed in the context of polyploid data analysis in molecular ecology.
We investigated microbial succession on lake sturgeon (Acipenser fulvescens) egg surfaces over the course of their incubation period as a function of simulated stream flow rate. The primary objective was to characterize the microbial community assembly during succession and to examine how simulated stream flow rate affect the successional process. Sturgeon eggs were reared under three flow regimes; high (0.55 m/s), low (0.18 m/s), and variable (0.35 and 0.11 m/s alternating 12 h intervals). Eggs were collected from each flow regime at different egg developmental stages. Microbial community DNA was extracted from egg surface and the communities were examined using 16S rRNA gene-based terminal restriction fragment length polymorphism and 454 pyrosequencing. Analysis of these datasets using principal component analysis revealed that microbial communities were clustered by egg developmental stages (early, middle, and late) regardless of flow regimes. 454 pyrosequencing data suggested that 90-98 % of the microbial communities were composed of the phyla Proteobacteria and Bacteroidetes throughout succession. ?-Protebacteria was more dominant in the early stage, Bacteroidetes became more dominant in the middle stage, and ?-Proteobacteria became dominant in the late stage. A total of 360 genera and 5,826 OTUs at 97 % similarity cutoff were associated with the eggs. Midway through egg development, the egg-associated communities of the low flow regime had a higher diversity than those communities developed under high or variable flow regimes. Results show that microbial community turnover occurred during embryogenesis, and stream flow rate influenced the microbial succession processes on the sturgeon egg surfaces.
For many long-lived animal species, individuals do not breed every year, and are often not accessible during non-breeding periods. Individuals exhibit site fidelity if they return to the same breeding colony or spawning ground when they breed. If capture and recapture is only possible at the breeding site, temporary emigration models are used to allow for only a subset of the animals being present in any given year. Most temporary emigration models require the use of the robust sampling design, and their focus is usually on probabilities of annual survival and of transition between breeding and non-breeding states. We use lake sturgeon (Acipenser fulvescens) data from a closed population where only a simple (one sample per year) sampling scheme is possible, and we also wish to estimate abundance as well as sex-specific survival and breeding return time probabilities. By adding return time parameters to the Schwarz-Arnason version of the Jolly-Seber model, we have developed a new likelihood-based model which yields plausible estimates of abundance, survival, transition and return time parameters. An important new finding from investigation of the model is the overestimation of abundance if a Jolly-Seber model is used when Markovian temporary emigration is present.
Quantifying interannual variation in effective adult breeding number (N(b)) and relationships between N(b), effective population size (N(e)), adult census size (N) and population demographic characteristics are important to predict genetic changes in populations of conservation concern. Such relationships are rarely available for long-lived iteroparous species like lake sturgeon (Acipenser fulvescens). We estimated annual N(b) and generational N(e) using genotypes from 12 microsatellite loci for lake sturgeon adults (n = 796) captured during ten spawning seasons and offspring (n = 3925) collected during larval dispersal in a closed population over 8 years. Inbreeding and variance N(b) estimated using mean and variance in individual reproductive success derived from genetically identified parentage and using linkage disequilibrium (LD) were similar within and among years (interannual range of N(b) across estimators: 41-205). Variance in reproductive success and unequal sex ratios reduced N(b) relative to N on average 36.8% and 16.3%, respectively. Interannual variation in N(b)/N ratios (0.27-0.86) resulted from stable N and low standardized variance in reproductive success due to high proportions of adults breeding and the species polygamous mating system, despite a 40-fold difference in annual larval production across years (437-16 417). Results indicated environmental conditions and features of the species reproductive ecology interact to affect demographic parameters and N(b)/N. Estimates of N(e) based on three single-sample estimators, including LD, approximate Bayesian computation and sibship assignment, were similar to annual estimates of N(b). Findings have important implications concerning applications of genetic monitoring in conservation planning for lake sturgeon and other species with similar life histories and mating systems.
Wild carnivores in zoos, conservation breeding centres, and farms commonly live in relatively small, unstimulating enclosures. Under these captive conditions, in a range of species including giant pandas, black-footed ferrets, and European mink, male reproductive abilities are often poor. Such problems have long been hypothesized to be caused by these animals housing conditions. We show for the first time that rearing under welfare-improving (i.e., highly valued and stress-reducing) environmental enrichments enhances male carnivores copulatory performance: in mate choice competitions, enriched male American mink (Neovison vison) mated more often than non-enriched males. We screened for several potential mediators of this effect. First was physiological stress and its impact on reproductive physiology; second, stress-mediated changes in morphology and variables related to immunocompetence that could influence male attractiveness; and third, behavioural changes likely to affect social competence, particularly autistic-like excessive routine and repetition (perseveration) as is reflected in the stereotypies common in captive animals. Consistent with physiological stress, excreted steroid metabolites revealed that non-enriched males had higher cortisol levels and lower androgen levels than enriched conspecifics. Their os penises (bacula) also tended to be less developed. Consistent with reduced attractiveness, non-enriched males were lighter, with comparatively small spleens and a trend to greater fluctuating asymmetry. Consistent with impaired social competence, non-enriched males performed more stereotypic behaviour (e.g., pacing) in their home cages. Of all these effects, the only significant predictor of copulation number was stereotypy (a trend suggesting that low bodyweights may also be influential): highly stereotypic males gained the fewest copulations. The neurophysiological changes underlying stereotypy thus handicap males sexually. We hypothesise that such males are abnormally perseverative when interacting with females. Investigating similar problems in other taxa would be worthwhile, since many vertebrates, wild and domestic, live in conditions that cause stereotypic behaviour and/or impair neurological development.
Measures of genetic structure among individuals or populations collected at different spatial locations across a landscape are commonly used as surrogate measures of functional (i.e. demographic or genetic) connectivity. In order to understand how landscape characteristics influence functional connectivity, resistance surfaces are typically created in a raster GIS environment. These resistance surfaces represent hypothesized relationships between landscape features and gene flow, and are based on underlying biological functions such as relative abundance or movement probabilities in different land cover types. The biggest challenge for calculating resistance surfaces is assignment of resistance values to different landscape features. Here, we first identify study objectives that are consistent with the use of resistance surfaces and critically review the various approaches that have been used to parameterize resistance surfaces and select optimal models in landscape genetics. We then discuss the biological assumptions and considerations that influence analyses using resistance surfaces, such as the relationship between gene flow and dispersal, how habitat suitability may influence animal movement, and how resistance surfaces can be translated into estimates of functional landscape connectivity. Finally, we outline novel approaches for creating optimal resistance surfaces using either simulation or computational methods, as well as alternatives to resistance surfaces (e.g. network and buffered paths). These approaches have the potential to improve landscape genetic analyses, but they also create new challenges. We conclude that no single way of using resistance surfaces is appropriate for every situation. We suggest that researchers carefully consider objectives, important biological assumptions and available parameterization and validation techniques when planning landscape genetic studies.
Understanding the genetic basis of species adaptation in the context of global change poses one of the greatest challenges of this century. Although we have begun to understand the molecular basis of adaptation in those species for which whole genome sequences are available, the molecular basis of adaptation is still poorly understood for most non-model species. In this paper, we outline major challenges and future research directions for correlating environmental factors with molecular markers to identify adaptive genetic variation, and point to research gaps in the application of landscape genetics to real-world problems arising from global change, such as the ability of organisms to adapt over rapid time scales. High throughput sequencing generates vast quantities of molecular data to address the challenge of studying adaptive genetic variation in non-model species. Here, we suggest that improvements in the sampling design should consider spatial dependence among sampled individuals. Then, we describe available statistical approaches for integrating spatial dependence into landscape analyses of adaptive genetic variation.
Landscape features exist at multiple spatial and temporal scales, and these naturally affect spatial genetic structure and our ability to make inferences about gene flow. This article discusses how decisions about sampling of genotypes (including choices about analytical methods and genetic markers) should be driven by the scale of spatial genetic structure, the time frame that landscape features have existed in their current state, and all aspects of a species life history. Researchers should use caution when making inferences about gene flow, especially when the spatial extent of the study area is limited. The scale of sampling of the landscape introduces different features that may affect gene flow. Sampling grain should be smaller than the average home-range size or dispersal distance of the study organism and, for raster data, existing research suggests that simplifying the thematic resolution into discrete classes may result in low power to detect effects on gene flow. Therefore, the methods used to characterize the landscape between sampling sites may be a primary determinant for the spatial scale at which analytical results are applicable, and the use of only one sampling scale for a particular statistical method may lead researchers to overlook important factors affecting gene flow. The particular analytical technique used to correlate landscape data and genetic data may also influence results; common landscape-genetic methods may not be suitable for all study systems, particularly when the rate of landscape change is faster than can be resolved by common molecular markers.
Population genetics theory is primarily based on mathematical models in which spatial complexity and temporal variability are largely ignored. In contrast, the field of landscape genetics expressly focuses on how population genetic processes are affected by complex spatial and temporal environmental heterogeneity. It is spatially explicit and relates patterns to processes by combining complex and realistic life histories, behaviours, landscape features and genetic data. Central to landscape genetics is the connection of spatial patterns of genetic variation to the usually highly stochastic space-time processes that create them over both historical and contemporary time periods. The field should benefit from a shift to computer simulation approaches, which enable incorporation of demographic and environmental stochasticity. A key role of simulations is to show how demographic processes such as dispersal or reproduction interact with landscape features to affect probability of site occupancy, population size, and gene flow, which in turn determine spatial genetic structure. Simulations could also be used to compare various statistical methods and determine which have correct type I error or the highest statistical power to correctly identify spatio-temporal and environmental effects. Simulations may also help in evaluating how specific spatial metrics may be used to project future genetic trends. This article summarizes some of the fundamental aspects of spatial-temporal population genetic processes. It discusses the potential use of simulations to determine how various spatial metrics can be rigorously employed to identify features of interest, including contrasting locus-specific spatial patterns due to micro-scale environmental selection.
Reintroductions and translocations are increasingly used to repatriate or increase probabilities of persistence for animal and plant species. Genetic and demographic characteristics of founding individuals and suitability of habitat at release sites are commonly believed to affect the success of these conservation programs. Genetic divergence among multiple source populations of American martens (Martes americana) and well documented introduction histories permitted analyses of post-introduction dispersion from release sites and development of genetic clusters in the Upper Peninsula (UP) of Michigan <50 years following release. Location and size of spatial genetic clusters and measures of individual-based autocorrelation were inferred using 11 microsatellite loci. We identified three genetic clusters in geographic proximity to original release locations. Estimated distances of effective gene flow based on spatial autocorrelation varied greatly among genetic clusters (30-90 km). Spatial contiguity of genetic clusters has been largely maintained with evidence for admixture primarily in localized regions, suggesting recent contact or locally retarded rates of gene flow. Data provide guidance for future studies of the effects of permeabilities of different land-cover and land-use features to dispersal and of other biotic and environmental factors that may contribute to the colonization process and development of spatial genetic associations.
The genetic basis of susceptibility to chronic wasting disease (CWD) in free-ranging cervids is of great interest. Association studies of disease susceptibility in free-ranging populations, however, face considerable challenges including: the need for large sample sizes when disease is rare, animals of unknown pedigree create a risk of spurious results due to population admixture, and the inability to control disease exposure or dose. We used an innovative matched case-control design and conditional logistic regression to evaluate associations between polymorphisms of complement C1q and prion protein (Prnp) genes and CWD infection in white-tailed deer from the CWD endemic area in south-central Wisconsin. To reduce problems due to admixture or disease-risk confounding, we used neutral genetic (microsatellite) data to identify closely related CWD-positive (n=68) and CWD-negative (n=91) female deer to serve as matched cases and controls. Cases and controls were also matched on factors (sex, location, age) previously demonstrated to affect CWD infection risk. For Prnp, deer with at least one Serine (S) at amino acid 96 were significantly less likely to be CWD-positive relative to deer homozygous for Glycine (G). This is the first characterization of genes associated with the complement system in white-tailed deer. No tests for association between any C1q polymorphism and CWD infection were significant at p<0.05. After controlling for Prnp, we found weak support for an elevated risk of CWD infection in deer with at least one Glycine (G) at amino acid 56 of the C1qC gene. While we documented numerous amino acid polymorphisms in C1q genes none appear to be strongly associated with CWD susceptibility.
Chronic wasting disease (CWD) is a fatal, transmissible spongiform encephalopathy that affects free-ranging and captive North American cervids. Although the impacts of CWD on cervid survival have been documented, little is known about the disease impacts on reproduction and recruitment. We used genetic methods and harvest data (2002-04) to reconstruct parentage for a cohort of white-tailed deer (Odocoileus virginianus) fawns born in spring 2002 and evaluate the effects of CWD infection on reproduction and fawn harvest vulnerability. There was no difference between CWD-positive and CWD-negative male deer in the probability of being a parent. However, CWD-positive females were more likely to be parents than CWD-negative females. Because our results are based on harvested animals, we evaluated the hypothesis that higher parentage rates occurred because fawns with CWD-positive mothers were more vulnerable to harvest. Male fawns with CWD-positive mothers were harvested earlier (>1 mo relative to their mothers date of harvest) and farther away from their mothers than male fawns with CWD-negative mothers. Male fawns with CWD-positive mothers were also harvested much earlier and farther away than female fawns from CWD-positive mothers. Most female fawns (86%) with CWD-positive mothers were harvested from the same section as their mothers, while almost half of male and female fawns with CWD-negative mothers were farther away. We conclude that preclinical stages of CWD infection do not prohibit white-tailed deer from successfully reproducing. However, apparently higher harvest vulnerability of male fawns with CWD-positive mothers suggests that CWD infection may make females less capable of providing adequate parental care to ensure the survival and recruitment of their fawns.
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