Hilltopping influences spatial dynamics in a patchy population of tiger moths

Dispersal is a key driver of spatial population dynamics. Dispersal behavior may be shaped by many factors, such as mate-finding, the spatial distribution of resources, or wind and currents, yet most models of spatial dynamics assume random dispersal. We examined the spatial dynamics of a day-flying moth species (Arctia virginalis) that forms mating aggregations on hilltops (hilltopping) based on long-term adult and larval population censuses. Using time-series models, we compared spatial population dynamics resulting from empirically-founded hilltop-based connectivity indices, and modeled the interactive effects of temperature, precipitation, and density dependence. Model comparisons supported hilltop-based connectivity metrics over random connectivity, suggesting an effect of hilltopping behavior on dynamics. We also found strong interactive effects of temperature and precipitation on dynamics. Simulations based on fitted time series models showed lower patch occupancy and regional synchrony, and higher colonization and extinction rates when hilltopping was included, with potential implications for the probability of persistence of the patch network. Overall, our results show the potential for dispersal behavior to have important effects on spatial population dynamics and persistence, and we advocate inclusion of such non-random dispersal in metapopulation models.

Spatial population genetic structure and colony dynamics in Damaraland mole-rats (Fukomys damarensis) from the southern Kalahari

Background Non-random associations within and among groups of social animals can provide valuable insight into the function of group living and the evolution of social behaviour. Damaraland mole-rats (Fukomys damarensis) demonstrate extremely high levels of reproductive skew, and dispersal is considered to be male-biased in onset and frequency, although asymmetry in dispersal distance is yet to be investigated. Dispersal may be positively correlated with increasing favourable environmental conditions, such as rainfall, however, the effects of ecological constraints on dispersal and colony fission–fusion dynamics have not previously been demonstrated on a spatial scale. Here we provide the first spatial population genetic study for this species. We investigated genetic structure in a population of Damaraland mole-rats from the southern Kalahari in South Africa over 3 years, combining observational dispersal data from mark-recapture with population genetic data to evaluate (1) sex-bias in frequency and distance of dispersal in this species, and (2) the effect of rainfall on fission–fusion dynamics of colonies. Results Our results demonstrate (1) that both males and females favour local dispersal but on rare occasions may disperse over distances greater than 400 m, (2) that males may disperse over greater distances than females, and (3) that males more frequently immigrate into established neighbouring colonies than females, who predominantly disperse by colony fission, i.e. multiple individuals “budding” from their native colony into a neighbouring territory, thereby establishing new colonies. Furthermore, our results demonstrate (4) elevated dispersal and colony fission in association with increased rainfall, supporting the hypothesis that rainfall may play a significant role in the maintenance and/or disruption of reproductive skew in Damaraland mole-rat populations. Conclusion This study represents the first fine-scale spatial population genetic study in Damaraland mole-rats, and provides relevant insights into colony fission–fusion dynamics in a social and cooperatively breeding species.

Population Genetics and Spawning Time of Lake Taupo Rainbow Trout

<p>The rainbow trout (Oncorhynchus mykiss) of Lake Taupo, New Zealand provide an exceptional opportunity to explore the contemporary adaptation of an introduced aquatic species. Recently it has become evident that their spawning migration time has shifted to later in the season. I investigated the genetic basis of these changes in spawning time by (1) using genetic markers to determine the origins of Taupo trout in California, (2) determining the pattern and extent of spatial population genetic variation throughout the Lake Taupo catchment and in comparison to nearby Lake Tarawera in the Rotorua district, (3) analysing genetic variation at the OtsClock1b spawning time gene in temporal replicates from several sites from Taupo, and (4) comparing contemporary genetic variation at this gene and microsatellite markers to genetic variation from three Taupo tributaries in 1980s. I compared the ability of single nucleotide polymorphism (SNP) and microsatellite markers to determine the origins of Lake Taupo rainbow trout, translocated from California around 120 years ago. Data were collected from 15 microsatellite and 93 SNP markers, using samples from the Lake Taupo population and ten populations throughout California, which included all historically indicated populations of origin. Results revealed that the Lake Taupo population has significantly diverged from Californian populations at both microsatellite and SNP loci. These analyses also showed that the Lake Taupo population was probably derived from several sources in California (the most likely origins being the McCloud River and Lake Almanor), and an indeterminate California coastal population. This conclusion was supported with simulations of founder events, which suggested that the genetic patterns of a single source of introduction would still be detectable 100 years post-founding, but with multiple introductions exact source populations become more difficult to detect. Approximately 50 individuals from 10 locations throughout the catchment were then analysed using 15 microsatellite loci to determine if there was any spatial population genetic differentiation. There was no significant difference in genetic distance between locations within Lake Taupo, although there was a significant difference between these populations and Rotorua and Waipakihi, which are isolated by geographic barriers. Lake Taupo rainbow trout do appear to diverge at markers potentially under selection, though, because genotyping of the poly-Q region of the timing locus OtsClock1b shows significant differentiation between individuals sampled at different times in the Waipa River. Two other sites, however, did not show the same pattern of significant seasonal variation in OtsClock1b allele frequencies. This suggests that genotypes at this locus could be influencing spawning migration time, but that this variation could also be site specific, and therefore have a strong environmental component. Scale samples from the 1980s show no significant divergence at 5 microsatellites and OtsClock1b, indicating that allele frequencies have not changed significantly over the last 20 years at neutral markers or markers under selection. I therefore conclude that while Taupo rainbow trout have diverged from their origins in California, they have only slightly diverged within their new environment, and do not show a consistent pattern of genetic change over time. This information will contribute not only to the management of the Taupo fishery but also to the current understanding of the population genetic structuring of introduced salmonids.</p>

Population Genetics and Spawning Time of Lake Taupo Rainbow Trout

<p>The rainbow trout (Oncorhynchus mykiss) of Lake Taupo, New Zealand provide an exceptional opportunity to explore the contemporary adaptation of an introduced aquatic species. Recently it has become evident that their spawning migration time has shifted to later in the season. I investigated the genetic basis of these changes in spawning time by (1) using genetic markers to determine the origins of Taupo trout in California, (2) determining the pattern and extent of spatial population genetic variation throughout the Lake Taupo catchment and in comparison to nearby Lake Tarawera in the Rotorua district, (3) analysing genetic variation at the OtsClock1b spawning time gene in temporal replicates from several sites from Taupo, and (4) comparing contemporary genetic variation at this gene and microsatellite markers to genetic variation from three Taupo tributaries in 1980s. I compared the ability of single nucleotide polymorphism (SNP) and microsatellite markers to determine the origins of Lake Taupo rainbow trout, translocated from California around 120 years ago. Data were collected from 15 microsatellite and 93 SNP markers, using samples from the Lake Taupo population and ten populations throughout California, which included all historically indicated populations of origin. Results revealed that the Lake Taupo population has significantly diverged from Californian populations at both microsatellite and SNP loci. These analyses also showed that the Lake Taupo population was probably derived from several sources in California (the most likely origins being the McCloud River and Lake Almanor), and an indeterminate California coastal population. This conclusion was supported with simulations of founder events, which suggested that the genetic patterns of a single source of introduction would still be detectable 100 years post-founding, but with multiple introductions exact source populations become more difficult to detect. Approximately 50 individuals from 10 locations throughout the catchment were then analysed using 15 microsatellite loci to determine if there was any spatial population genetic differentiation. There was no significant difference in genetic distance between locations within Lake Taupo, although there was a significant difference between these populations and Rotorua and Waipakihi, which are isolated by geographic barriers. Lake Taupo rainbow trout do appear to diverge at markers potentially under selection, though, because genotyping of the poly-Q region of the timing locus OtsClock1b shows significant differentiation between individuals sampled at different times in the Waipa River. Two other sites, however, did not show the same pattern of significant seasonal variation in OtsClock1b allele frequencies. This suggests that genotypes at this locus could be influencing spawning migration time, but that this variation could also be site specific, and therefore have a strong environmental component. Scale samples from the 1980s show no significant divergence at 5 microsatellites and OtsClock1b, indicating that allele frequencies have not changed significantly over the last 20 years at neutral markers or markers under selection. I therefore conclude that while Taupo rainbow trout have diverged from their origins in California, they have only slightly diverged within their new environment, and do not show a consistent pattern of genetic change over time. This information will contribute not only to the management of the Taupo fishery but also to the current understanding of the population genetic structuring of introduced salmonids.</p>

Strong spatial population structure shapes the temporal coevolutionary dynamics of costly female preference and male display

Female mating preferences for exaggerated male display traits are commonplace. Yet, comprehensive understanding of the evolution and persistence of costly female preference through indirect (Fisherian) selection in finite populations requires some explanation for the persistence of additive genetic variance (Va) underlying sexual traits, given that directional preference is expected to deplete Va in display and hence halt preference evolution. However, the degree to which Va, and hence preference-display coevolution, may be prolonged by spatially variable sexual selection arising solely from limited gene flow and genetic drift within spatially structured populations has not been examined. Our genetically and spatially explicit model shows that spatial population structure arising in an ecologically homogeneous environment can facilitate evolution and long-term persistence of costly preference given small subpopulations and low dispersal probabilities. Here, genetic drift initially creates spatial variation in female preference, leading to persistence of Va in display through migration-bias of genotypes maladapted to emerging local sexual selection, thus fuelling coevolution of costly preference and display. However, costs of sexual selection increased the probability of subpopulation extinction, limiting persistence of high preference-display genotypes. Understanding long-term dynamics of sexual selection systems therefore requires joint consideration of coevolution of sexual traits and metapopulation dynamics.

Fast and flexible estimation of effective migration surfaces

Spatial population genetic data often exhibits ‘isolation-by-distance,’ where genetic similarity tends to decrease as individuals become more geographically distant. The rate at which genetic similarity decays with distance is often spatially heterogeneous due to variable population processes like genetic drift, gene flow, and natural selection. Petkova et al., 2016 developed a statistical method called Estimating Effective Migration Surfaces (EEMS) for visualizing spatially heterogeneous isolation-by-distance on a geographic map. While EEMS is a powerful tool for depicting spatial population structure, it can suffer from slow runtimes. Here, we develop a related method called Fast Estimation of Effective Migration Surfaces (FEEMS). FEEMS uses a Gaussian Markov Random Field model in a penalized likelihood framework that allows for efficient optimization and output of effective migration surfaces. Further, the efficient optimization facilitates the inference of migration parameters per edge in the graph, rather than per node (as in EEMS). With simulations, we show conditions under which FEEMS can accurately recover effective migration surfaces with complex gene-flow histories, including those with anisotropy. We apply FEEMS to population genetic data from North American gray wolves and show it performs favorably in comparison to EEMS, with solutions obtained orders of magnitude faster. Overall, FEEMS expands the ability of users to quickly visualize and interpret spatial structure in their data.