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A central goal in evolutionary biology is to understand how different evolutionary processes cause trait change in wild populations. However, quantifying evolutionary change in the wild requires linking trait change to shifts in allele frequencies at causal loci. Nevertheless, datasets that allow for such tests are extremely rare and existing theoretical approaches poorly account for the evolutionary dynamics that likely occur in ecological settings. Using a decade-long integrative phenome-to-genome time-series dataset on wild threespine stickleback (Gasterosteus aculeatus), we identified how different modes of selection (directional, episodic, and balancing) drive microevolutionary change in correlated traits over time. Most strikingly, we show that feeding traits changed by as much 25% across 10 generations which was driven by changes in the genetic architecture (i.e., in both genomic breeding values and allele frequencies at genetic loci for feeding traits). Importantly, allele frequencies at genetic loci related to feeding traits changed at a rate greater than expected under drift, suggesting that the observed change was a result of directional selection. Allele frequency dynamics of loci related to swimming traits appeared to be under fluctuating selection evident in periodic population crashes in this system. Our results show that microevolutionary change in a wild population is characterized by different modes of selection acting simultaneously on different traits, which likely has important consequences for the evolution of correlated traits. Our study provides one of the most thorough descriptions to date of how microevolutionary processes result in trait change in a natural population.

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AbstractUncovering the demographic basis of population fluctuations is a central goal of population biology. This is particularly challenging for spatially structured populations, which require disentangling synchrony in demographic rates from coupling via movement between locations. In this study, we fit a stage-structured metapopulation model to a 29-year time series of threespine stickleback abundance in the heterogeneous and productive Lake Mývatn, Iceland. The lake comprises two basins (North and South) connected by a channel through which the stickleback disperse. The model includes time-varying demographic rates, allowing us to assess the potential contributions of recruitment and survival, spatial coupling via movement, and demographic transience to the population's large fluctuations in abundance. Our analyses indicate that recruitment was only modestly synchronized between the two basins, whereas survival probabilities of adults were more strongly synchronized, contributing to cyclic fluctuations in the lake-wide population size with a period of approximately 6 years. The analyses further show that the two basins were coupled through movement, with the North Basin subsidizing the South Basin and playing a dominant role in driving the lake-wide dynamics. Our results show that cyclic fluctuations of a metapopulation can be explained in terms of the combined effects of synchronized demographic rates and spatial coupling.

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Adaptive genetic divergence occurs when selection imposed by the environment causes the genomic component of the phenotype to differentiate. However, genomic signatures of natural selection are usually identified without information on which trait is responding to selection by which selective agent(s). Here, we integrate whole-genome sequencing with phenomics and measures of putative selective agents to assess the extent of adaptive divergence in threespine stickleback occupying the highly heterogeneous lake Mývatn, NE Iceland. We find negligible genome wide divergence, yet multiple traits (body size, gill raker structure and defence traits) were divergent along known ecological gradients (temperature, predatory bird densities and water depth). SNP based heritability of all measured traits was high (h2  = 0.42-0.65), indicating adaptive potential for all traits. Environment-association analyses further identified thousands of loci putatively involved in selection, related to genes linked to, for instance, neuron development and protein phosphorylation. Finally, we found that loci linked to water depth were concurrently associated with pelvic spine length variation - supporting the conclusion that divergence in pelvic spine length occurred in the face of gene flow. Our results suggest that whilst there is substantial genetic variation in the traits measured, phenotypic divergence of Mývatn stickleback is mostly weakly associated with environmental gradients, potentially as a result of substantial gene flow. Our study illustrates the value of integrative studies that combine genomic assays of multivariate trait variation with landscape genomics.

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Oceanic archipelagos have long been treated as a Petri dish for studies of evolutionary and ecological processes. Like archipelagos, cities exhibit similar patterns and processes, such as the rapid phenotypic divergence of a species between urban and nonurban environments. However, on a local scale, cities can be highly heterogenous, where geographically close populations can experience dramatically different environmental conditions. Nevertheless, we are yet to understand the evolutionary and ecological implications for populations spread across a heterogenous cityscape. To address this, we compared neutral genetic divergence to quantitative trait divergence within three native riparian and four city park populations of an iconic urban adapter, the eastern water dragon. We demonstrated that selection is likely acting to drive divergence of snout-vent length and jaw width across native riparian populations that are geographically isolated and across city park populations that are geographically close yet isolated by urbanization. City park populations as close as 0.9 km exhibited signs of selection-driven divergence to the same extent as native riparian populations isolated by up to 114.5 km. These findings suggest that local adaptation may be occurring over exceptionally small geographic and temporal scales within a single metropolis, demonstrating that city parks can act as archipelagos for the study of rapid evolution.

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The koala, one of the most iconic Australian wildlife species, is facing several concomitant threats that are driving population declines. Some threats are well known and have clear methods of prevention (e.g., habitat loss can be reduced with stronger land-clearing control), whereas others are less easily addressed. One of the major current threats to koalas is chlamydial disease, which can have major impacts on individual survival and reproduction rates and can translate into population declines. Effective management strategies for the disease in the wild are currently lacking, and, to date, we know little about the determinants of individual susceptibility to disease. Here, we investigated the genetic basis of variation in susceptibility to chlamydia using one of the most intensively studied wild koala populations. We combined data from veterinary examinations, chlamydia testing, genetic sampling and movement monitoring. Out of our sample of 342 wild koalas, 60 were found to have chlamydia. Using genotype information on 5007 SNPs to investigate the role of genetic variation in determining disease status, we found no evidence of inbreeding depression, but a heritability of 0.11 (95% CI: 0.06-0.23) for the probability that koalas had chlamydia. Heritability of susceptibility to chlamydia could be relevant for future disease management, as it suggests adaptive potential for the population.

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Effective conservation requires accurate data on population genetic diversity, inbreeding, and genetic structure. Increasingly, scientists are adopting genetic non-invasive sampling (gNIS) as a cost-effective population-wide genetic monitoring approach. gNIS has, however, known limitations which may impact the accuracy of downstream genetic analyses. Here, using high-quality single nucleotide polymorphism (SNP) data from blood/tissue sampling of a free-ranging koala population (n = 430), we investigated how the reduced SNP panel size and call rate typical of genetic non-invasive samples (derived from experimental and field trials) impacts the accuracy of genetic measures, and also the effect of sampling intensity on these measures. We found that gNIS at small sample sizes (14% of population) can provide accurate population diversity measures, but slightly underestimated population inbreeding coefficients. Accurate measures of internal relatedness required at least 33% of the population to be sampled. Accurate geographic and genetic spatial autocorrelation analysis requires between 28% and 51% of the population to be sampled. We show that gNIS at low sample sizes can provide a powerful tool to aid conservation decision-making and provide recommendations for researchers looking to apply these techniques to free-ranging systems.

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In the evolutionary transition from solitary to group living, it should be adaptive for animals to respond to the environment and choose when to socialize to reduce conflict and maximize access to resources. Due to the associated proximate mechanisms (e.g. neural network, endocrine system), it is likely that this behavior varies between individuals according to genetic and non-genetic factors. We used long-term behavioral and genetic data from a population of eastern water dragons (Intellagama lesueurii) to explore variation in plasticity of social behavior, in response to sex ratio and density. To do so, we modeled individual variation in social reaction norms, which describe individuals' mean behavior and behavioral responses to changes in their environment, and partitioned variance into genetic and non-genetic components. We found that reaction norms were repeatable over multiple years, suggesting that individuals consistently differed in their behavioral responses to changes in the social environment. Despite high repeatability of reaction norm components, trait heritability was below our limit of detection based on power analyses (h2 < 0.12), leading to very little power to detect heritability of plasticity. This was in contrast to a relatively greater amount of variance associated with environmental effects. This could suggest that mechanisms such as social learning and frequency-dependence may shape variance in reaction norms, which will be testable as the dataset grows.

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The niche describes the ecological and social environment that an organism lives in, as well as the behavioural tactics used to interact with its environment. A species niche is key to both ecological and evolutionary processes, including speciation, and has therefore been a central focus in ecology. Recent evidence, however, points to considerable individual variation in a species' or population's niche use, although how this variation evolves or is maintained remains unclear. We used a large longitudinal dataset to investigate the drivers and maintenance of individual variation in bottlenose dolphins' Tursiops aduncus niche. Specifically, we (a) characterised the extent of individual differences in habitat use, (b) identified whether there were maternal effects associated with this variation and (c) investigated the relationship between habitat use and calving success, a component of reproductive fitness. By examining patterns of habitat use, we provide evidence that individual dolphins vary consistently between one another in their niche. We further show that such individual variation is driven by a strong maternal effect. Finally, habitat use and calving success were not related, suggesting that use of different habitats results in similar fitness outcomes. Niche partitioning, maintained by maternal effects, likely facilitates the coexistence of multiple ecotypes within this population.

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Individuals should alter when they socially associate with conspecifics to avoid potentially costly interactions. Moreover, individuals may vary in their propensity to use information about conspecifics when making such social decisions. However, surprisingly little is known about either the determinants of or the individual variation in such "social plasticity." We show here that eastern water dragons (Intellegama lesueurii lesueurii) may simultaneously use information from different components of their social environment when deciding whether to socially associate. In particular, we found that individuals altered when they socially associated with conspecifics according to the levels of potential conflict and competition in their social environment; both sexes socially associated more at higher local density than would be expected under increased random encounters. Further, females were more likely to socially associate during the breeding season and when there were more males and/or conspecifics whom they typically avoided in their social environment. This suggests that females may seek safety in numbers when the potential for intrasexual conflict or sexual harassment is high. Using a behavioral reaction norm framework, we also provide novel evidence to show that individuals vary in the extent and direction of their social plasticity and that males varied more than females. Our study thus implies that individuals use multiple cues in their environment when deciding to socially associate and that the resulting social plasticity varies between the sexes and between individuals.

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Animal sociality is of significant interest to evolutionary and behavioural ecologists, with efforts focused on the patterns, causes and fitness outcomes of social preference. However, individual social patterns are the consequence of both attraction to (preference for) and avoidance of conspecifics. Despite this, social avoidance has received far less attention than social preference. Here, we detail the necessary steps to generate a spatially explicit, iterative null model which can be used to identify non-random social avoidance in longitudinal studies of social animals. We specifically identify and detail parameters which will influence the validity of the model. To test the usability of this model, we applied it to two longitudinal studies of social animals (Eastern water dragons (Intellegama lesueurii) and bottlenose dolphins (Tursiops aduncus)) to identify the presence of social avoidances. Using this model allowed us to identify the presence of social avoidances in both species. We hope that the framework presented here inspires interest in addressing this critical gap in our understanding of animal sociality, in turn allowing for a more holistic understanding of social interactions, relationships and structure.

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Ectothermic vertebrates face many challenges of thermoregulation. Many species rely on behavioral thermoregulation and move within their landscape to maintain homeostasis. Understanding the fine-scale nature of this regulation through tracking techniques can provide a better understanding of the relationships between such species and their dynamic environments. The use of animal tracking and telemetry technology has allowed the extensive collection of such data which has enabled us to better understand the ways animals move within their landscape. However, such technologies do not come without certain costs: they are generally invasive, relatively expensive, can be too heavy for small sized animals and unreliable in certain habitats. This study provides a cost-effective and non-invasive method through photo-identification, to determine fine scale movements of individuals. With our methodology, we have been able to find that male eastern water dragons (Intellagama leuseurii) have home ranges one and a half times larger than those of females. Furthermore, we found intraspecific differences in the size of home ranges depending on the time of the day. Lastly, we found that location mostly influenced females' home ranges, but not males and discuss why this may be so. Overall, we provide valuable information regarding the ecology of the eastern water dragon, but most importantly demonstrate that non-invasive photo-identification can be successfully applied to the study of reptiles.

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