Copy number variation and population-specific immune genes in the model vertebrate zebrafish.

Copy number variation in large gene families is well characterized for plant resistance genes, but similar studies are rare in animals. The zebrafish (Danio rerio) has hundreds of NLR immune genes, making this species ideal for studying this phenomenon. By sequencing 93 zebrafish from multiple wild and laboratory populations, we identified a total of 1513 NLRs, many more than the previously known 400. Approximately half of those are present in all wild populations, but only 4% were found in 80% or more of the individual fish. Wild fish have up to two times as many NLRs per individual and up to four times as many NLRs per population than laboratory strains. In contrast to the massive variability of gene copies, nucleotide diversity in zebrafish NLR genes is very low: around half of the copies are monomorphic and the remaining ones have very few polymorphisms, likely a signature of purifying selection.

Humans and other animals have immune systems that protect them from bacteria, viruses and other potentially harmful microbes. Members of a family of genes known as the NLR family play various roles in helping to recognize and destroy these microbes. Different species have varying numbers of NLR genes, for example, humans have 22 NLRs, but fish can have hundreds. 400 have been found in the small tropical zebrafish, also known as zebra danios. Zebrafish are commonly used as model animals in research studies because they reproduce quickly and are easy to keep in fish tanks. Much of what we know about fish biology comes from studying strains of those laboratory zebrafish, including the 400 NLRs found in a specific laboratory strain. Many NLRs in zebrafish are extremely similar, suggesting that they have only evolved fairly recently through gene duplication. It remains unclear why laboratory zebrafish have so many almost identical NLRs, or if wild zebrafish also have lots of these genes. To find out more, Schäfer et al. sequenced the DNA of NLRs from almost 100 zebrafish from multiple wild and laboratory populations. The approach identified over 1,500 different NLR genes, most of which, were previously unknown. Computational modelling suggested that each wild population of zebrafish may harbour up to around 2,000 NLR genes, but laboratory strains had much fewer NLRs. The numbers of NLR genes in individual zebrafish varied greatly ­ only 4% of the genes were present in 80% or more of the fish. Many genes were only found in specific populations or single individuals. Together, these findings suggest that the NLR family has expanded in zebrafish as part of an ongoing evolutionary process that benefits the immune system of the fish. Similar trends have also been observed in the NLR genes of plants, indicating there may be an evolutionary strategy across all living things to continuously diversify large families of genes. Additionally, this work highlights the lack of diversity in the genes of laboratory animals compared with those of their wild relatives, which may impact how results from laboratory studies are used to inform conservation efforts or are interpreted in the context of human health.

A new genomic resource to enable standardized surveys of SNPs across the native range of brook trout (Salvelinus fontinalis).

Understanding how genetic diversity is distributed across spatiotemporal scales in species of conservation or management concern is critical for identifying large-scale mechanisms affecting local conservation status and implementing large-scale biodiversity monitoring programmes. However, cross-scale surveys of genetic diversity are often impractical within single studies, and combining datasets to increase spatiotemporal coverage is frequently impeded by using different sets of molecular markers. Recently developed molecular tools make surveys based on standardized single-nucleotide polymorphism (SNP) panels more feasible than ever, but require existing genomic information. Here, we conduct the first survey of genome-wide SNPs across the native range of brook trout (Salvelinus fontinalis), a cold-adapted species that has been the focus of considerable conservation and management effort across eastern North America. Our dataset can be leveraged to easily design SNP panels that allow datasets to be combined for large-scale analyses. We performed restriction site-associated DNA sequencing for wild brook trout from 82 locations spanning much of the native range and domestic brook trout from 24 hatchery strains used in stocking efforts. We identified over 24,000 SNPs distributed throughout the brook trout genome. We explored the ability of these SNPs to resolve relationships across spatial scales, including population structure and hatchery admixture. Our dataset captures a wide spectrum of genetic diversity in native brook trout, offering a valuable resource for developing SNP panels. We highlight potential applications of this resource with the goal of increasing the integration of genomic information into decision-making for brook trout and other species of conservation or management concern.

Identifying mechanisms underlying individual body size increases in a changing, highly seasonal environment: The growing trout of West brook.

As air temperature increases, it has been suggested that smaller individual body size may be a general response to climate warming. However, for ectotherms inhabiting cold, highly seasonal environments, warming temperatures may increase the scope for growth and result in larger body size. In a long-term study of individual brook trout Salvelinus fontinalis and brown trout Salmo trutta inhabiting a small stream network, individual lengths increased over the course of 15 years. As size-selective gains and losses to the population acted to reduce body sizes and mean body size at first tagging in the autumn (<60 mm) were not observed to change substantially over time, the increase in body size was best explained by higher individual growth rates. For brook trout, increasing water temperatures during the spring (when both trout species accomplish most of their total annual growth) was the primary driver of growth rate for juvenile fish and the environmental factor which best explained increases in individual body size over time. For brown trout, by contrast, reduction in and subsequent elimination of juvenile Atlantic salmon Salmo salar midway through the study period explained most of the increases in juvenile growth and body size. In addition to these major trends, a considerable amount of interannual variation in trout growth and body size was explained by other abiotic (stream flow) and biotic (population density) factors with the direction and magnitude of these effects differing by season, age-class and species. For example, stream flow was the dominant growth rate driver for adult fish with strong positive effects in the summer and autumn, but flow variation could not explain increases in body size as we observed no trend in flow. Overall, our work supports the general contention that for high-latitude ectotherms, increasing spring temperatures associated with a warming climate can result in increased growth and individual body size (up to a point), but context-dependent change in other factors can substantially contribute to both interannual variation and longer-term effects.

Climate change and expanding invasive species drive widespread declines of native trout in the northern Rocky Mountains, USA.

Climate change and invasive species are major threats to native biodiversity, but few empirical studies have examined their combined effects at large spatial and temporal scales. Using 21,917 surveys collected over 30 years, we quantified the impacts of climate change on the past and future distributions of five interacting native and invasive trout species throughout the northern Rocky Mountains, USA. We found that the occupancy of native bull trout and cutthroat trout declined by 18 and 6%, respectively (1993­2018), and was predicted to decrease by an additional 39 and 16% by 2080. However, reasons for these occupancy reductions markedly differed among species: Climate-driven increases in water temperature and decreases in summer flow likely caused declines of bull trout, while climate-induced expansion of invasive species largely drove declines of cutthroat trout. Our results demonstrate that climate change can affect ecologically similar, co-occurring native species through distinct pathways, necessitating species-specific management actions.

Supporting the adaptive capacity of species through more effective knowledge exchange with conservation practitioners.

There is an imperative for conservation practitioners to help biodiversity adapt to accelerating environmental change. Evolutionary biologists are well-positioned to inform the development of evidence-based management strategies that support the adaptive capacity of species and ecosystems. Conservation practitioners increasingly accept that management practices must accommodate rapid environmental change, but harbour concerns about how to apply recommended changes to their management contexts. Given the interest from both conservation practitioners and evolutionary biologists in adjusting management practices, we believe there is an opportunity to accelerate the required changes by promoting closer collaboration between these two groups. We highlight how evolutionary biologists can harness lessons from other disciplines about how to foster effective knowledge exchange to make a substantive contribution to the development of effective conservation practices. These lessons include the following: (1) recognizing why practitioners do and do not use scientific evidence; (2) building an evidence base that will influence management decisions; (3) translating theory into a format that conservation practitioners can use to inform management practices; and (4) developing strategies for effective knowledge exchange. Although efforts will be required on both sides, we believe there are rewards for both practitioners and evolutionary biologists, not least of which is fostering practices to help support the long-term persistence of species.

Multiscale assessment of functional connectivity: Landscape genetics of eastern indigo snakes in an anthropogenically fragmented landscape in central Florida.

Landscape features can strongly influence gene flow and the strength and direction of these effects may vary across spatial scales. However, few studies have evaluated methodological approaches for selecting spatial scales in landscape genetics analyses, in part because of computational challenges associated with optimizing landscape resistance surfaces (LRS). We used the federally threatened eastern indigo snake (Drymarchon couperi) in central Florida as a case study with which to compare the importance of landscape features and their scales of effect in influencing gene flow. We used genetic algorithms (ResistanceGA) to empirically optimize LRS using categorical land cover surfaces, multiscale resource selection surfaces (RSS), and four combinations of landscape covariates measured at multiple spatial scales (multisurface multiscale LRS). We compared LRS where scale was selected using pseudo- and full optimization. Multisurface multiscale LRS received more empirical support than LRS optimized from categorical land cover surfaces or RSS. Multiscale LRS with scale selected using full optimization generally outperformed those with scale selected using pseudo-optimization. Multiscale LRS with large spatial scales (1200-1800 m) received the most empirical support. Our results highlight the importance of considering landscape features across multiple spatial scales in landscape genetic analyses, particularly broad scales relative to species movement potential. Different effects of scale on home range-level movements and dispersal could explain weak associations between habitat suitability and gene flow in other studies. Our results also demonstrate the importance of large tracts of undeveloped upland habitat with heterogenous vegetation communities and low urbanization for promoting indigo snake connectivity.

The ecological causes and consequences of hard and soft selection.

Interactions between natural selection and population dynamics are central to both evolutionary-ecology and biological responses to anthropogenic change. Natural selection is often thought to incur a demographic cost that, at least temporarily, reduces population growth. However, hard and soft selection clarify that the influence of natural selection on population dynamics depends on ecological context. Under hard selection, an individual's fitness is independent of the population's phenotypic composition, and substantial population declines can occur when phenotypes are mismatched with the environment. In contrast, under soft selection, an individual's fitness is influenced by its phenotype relative to other interacting conspecifics. Soft selection generally influences which, but not how many, individuals survive and reproduce, resulting in little effect on population growth. Despite these important differences, the distinction between hard and soft selection is rarely considered in ecology. Here, we review and synthesize literature on hard and soft selection, explore their ecological causes and implications and highlight their conservation relevance to climate change, inbreeding depression, outbreeding depression and harvest. Overall, these concepts emphasise that natural selection and evolution may often have negligible or counterintuitive effects on population growth-underappreciated outcomes that have major implications in a rapidly changing world.

Ultrasound imaging identifies life history variation in resident Cutthroat Trout.

Human activities that fragment fish habitat have isolated inland salmonid populations. This isolation is associated with loss of migratory life histories and declines in population density and abundance. Isolated populations exhibiting only resident life histories may be more likely to persist if individuals can increase lifetime reproductive success by maturing at smaller sizes or earlier ages. Therefore, accurate estimates of age and size at maturity across resident salmonid populations would improve estimates of population viability. Commonly used methods for assessing maturity such as dissection, endoscopy and hormone analysis are invasive and may disturb vulnerable populations. Ultrasound imaging is a non-invasive method that has been used to measure reproductive status across fish taxa. However, little research has assessed the accuracy of ultrasound for determining maturation status of small-bodied fish, or reproductive potential early in a species' reproductive cycle. To address these knowledge gaps, we tested whether ultrasound imaging could be used to identify maturing female Westslope Cutthroat Trout (Oncorhynchus clarkii lewisi). Our methods were accurate at identifying maturing females reared in a hatchery setting up to eight months prior to spawning, with error rates ≤ 4.0%; accuracy was greater for larger fish. We also imaged fish in a field setting to examine variation in the size of maturing females among six wild, resident populations of Westslope Cutthroat Trout in western Montana. The median size of maturing females varied significantly across populations. We observed oocyte development in females as small as 109 mm, which is smaller than previously documented for this species. Methods tested in this study will allow researchers and managers to collect information on reproductive status of small-bodied salmonids without disrupting fish during the breeding season. This information can help elucidate life history traits that promote persistence of isolated salmonid populations.

Evaluating the outcomes of genetic rescue attempts.

Augmenting gene flow is a powerful tool for the conservation of small, isolated populations. However, genetic rescue attempts have largely been limited to populations at the brink of extinction, in part due to concerns over negative outcomes (e.g., outbreeding depression). Increasing habitat fragmentation may necessitate more proactive genetic management. Broader application of augmented gene flow will, in turn, require rigorous evaluation to increase confidence and identify pitfalls in this approach. To date, there has been no assessment of best monitoring practices for genetic rescue attempts. We used genomically explicit, individual-based simulations to examine the effectiveness of common approaches (i.e., tests for increases in fitness, migrant ancestry, heterozygosity, and abundance) for determining whether genetic rescue or outbreeding depression occurred. Statistical power to detect the effects of gene flow on fitness was high (≥0.8) when effect sizes were large, a finding consistent with those from previous studies on severely inbred populations. However, smaller effects of gene flow on fitness can appreciably affect persistence probability but current evaluation approaches fail to provide results from which reliable inferences can be drawn. The power of the metrics we examined to evaluate genetic rescue attempts depended on the time since gene flow and whether gene flow was beneficial or deleterious. Encouragingly, the use of multiple metrics provided nonredundant information and improved inference reliability, highlighting the importance of intensive monitoring efforts. Further development of best practices for evaluating genetic rescue attempts will be crucial for a responsible transition to increased use of translocations to decrease extinction risk.

Evaluación de los Resultados de los Intentos de Rescate Genético Resumen El aumento del flujo génico es una herramienta poderosa para la conservación de poblaciones pequeñas y aisladas. Sin embargo, los intentos de rescate genético en su mayoría se han limitado a las poblaciones que se encuentran al borde de la extinción, en parte debido a la preocupación que existe por los resultados negativos (es decir, la depresión exogámica). La creciente fragmentación del hábitat puede requerir un manejo genético más proactivo. La aplicación más extensa del flujo génico aumentado requerirá a su vez una evaluación rigurosa para incrementar la confianza e identificar las dificultades de esta estrategia. A la fecha, no ha habido una evaluación de las mejores prácticas de monitoreo para los intentos de rescate genético. Usamos simulaciones explícitas basadas en individuos para examinar la efectividad de las estrategias comunes (es decir, análisis del incremento en adaptabilidad, ascendencia migratoria, heterocigosidad y abundancia) para determinar si ocurrió el rescate genético o la depresión exogámica. El poder estadístico para detectar los efectos del flujo génico sobre la adaptabilidad fue elevado (≥0.8) cuando el tamaño de los efectos fue grande, un hallazgo consistente con aquellos realizados en estudios previos sobre poblaciones con una endogamia severa. Sin embargo, los efectos menores del flujo génico sobre la adaptabilidad pueden afectar de manera apreciable la probabilidad de persistencia, pero las estrategias actuales de evaluación no proporcionan resultados de los cuales se puedan hacer inferencias confiables. El poder de las medidas que examinamos para evaluar los intentos de rescate genético dependió del tiempo desde que inició el flujo génico y de si el flujo génico fue benéfico o perjudicial. De manera alentadora, el uso de múltiples medidas proporcionó información no redundante y mejoró la confiabilidad de la inferencia, resaltando así la importancia de los esfuerzos intensivos de monitoreo. El futuro desarrollo de mejores prácticas para la evaluación de los intentos de rescate genético será de suma importancia para la transición responsable hacia el mayor uso de reubicaciones para reducir el riesgo de extinción.

Genomic population structure of Striped Bass (Morone saxatilis) from the Gulf of St. Lawrence to Cape Fear River.

Striped Bass, Morone saxatilis (Walbaum, 1792), is an anadromous fish species that supports fisheries throughout North America and is native to the North American Atlantic Coast. Due to long coastal migrations that span multiple jurisdictions, a detailed understanding of population genomics is required to untangle demographic patterns, understand local adaptation, and characterize population movements. This study used 1,256 single nucleotide polymorphism (SNP) loci to investigate genetic structure of 477 Striped Bass sampled from 15 locations spanning the North American Atlantic coast from the Gulf of St. Lawrence, Canada, to the Cape Fear River, United States. We found striking differences in neutral divergence among Canadian sites, which were isolated from each other and US populations, compared with US populations that were much less isolated. Our SNP dataset was able to assign 99% of Striped Bass back to six reporting groups, a 39% improvement over previous genetic markers. Using this method, we found (a) evidence of admixture within Saint John River, indicating that migrants from the United States and from Shubenacadie River occasionally spawn in the Saint John River; (b) Striped Bass collected in the Mira River, Cape Breton, Canada, were found to be of both Miramichi River and US origin; (c) juveniles in the newly restored Kennebec River population had small and nonsignificant differences from the Hudson River; and (d) tributaries within the Chesapeake Bay showed a mixture of homogeny and small differences among each other. This study introduces new hypotheses about the dynamic zoogeography of Striped Bass at its northern range and has important implications for the local and international management of this species.

The Laboratory Domestication of Zebrafish: From Diverse Populations to Inbred Substrains.

We know from human genetic studies that practically all aspects of biology are strongly influenced by the genetic background, as reflected in the advent of "personalized medicine." Yet, with few exceptions, this is not taken into account when using laboratory populations as animal model systems for research in these fields. Laboratory strains of zebrafish (Danio rerio) are widely used for research in vertebrate developmental biology, behavior, and physiology, for modeling diseases, and for testing pharmaceutic compounds in vivo. However, all of these strains are derived from artificial bottleneck events and therefore are likely to represent only a fraction of the genetic diversity present within the species. Here, we use restriction site-associated DNA sequencing to genetically characterize wild populations of zebrafish from India, Nepal, and Bangladesh, and to compare them to previously published data on four common laboratory strains. We measured nucleotide diversity, heterozygosity, and allele frequency spectra, and find that wild zebrafish are much more diverse than laboratory strains. Further, in wild zebrafish, there is a clear signal of GC-biased gene conversion that is missing in laboratory strains. We also find that zebrafish populations in Nepal and Bangladesh are most distinct from all other strains studied, making them an attractive subject for future studies of zebrafish population genetics and molecular ecology. Finally, isolates of the same strains kept in different laboratories show a pattern of ongoing differentiation into genetically distinct substrains. Together, our findings broaden the basis for future genetic, physiological, pharmaceutic, and evolutionary studies in Danio rerio.

Multiscale resistant kernel surfaces derived from inferred gene flow: An application with vernal pool breeding salamanders.

The importance of assessing spatial data at multiple scales when modelling species-environment relationships has been highlighted by several empirical studies. However, no landscape genetics studies have optimized landscape resistance surfaces by evaluating relevant spatial predictors at multiple spatial scales. Here, we model multiscale/layer landscape resistance surfaces to estimate resistance to inferred gene flow for two vernal pool breeding salamander species, spotted (Ambystoma maculatum) and marbled (A. opacum) salamanders. Multiscale resistance surface models outperformed spatial layers modelled at their original spatial scale. A resistance surface with forest land cover at a 500-m Gaussian kernel bandwidth and normalized vegetation index at a 100-m Gaussian kernel bandwidth was the top optimized resistance surface for A. maculatum, while a resistance surface with traffic rate and topographic curvature, both at a 500-m Gaussian kernel bandwidth, was the top optimized resistance surface for A. opacum. Species-specific resistant kernels were fit at all vernal pools in our study area with the optimized multiscale/layer resistance surface controlling kernel spread. Vernal pools were then evaluated and scored based on surrounding upland habitat (local score) and connectivity with other vernal pools on the landscape, with resistant kernels driving vernal pool connectivity scores. As expected, vernal pools that scored highest were in areas within forested habitats and with high vernal pool densities and low species-specific landscape resistance. Our findings highlight the success of using a novel analytical approach in a multiscale framework with applications beyond vernal pool amphibian conservation.

The Exciting Potential and Remaining Uncertainties of Genetic Rescue.

Restoring gene flow into small, isolated populations can alleviate genetic load and decrease extinction risk (i.e., genetic rescue), yet gene flow is rarely augmented as a conservation strategy. Due to this discrepancy between opportunity and action, a recent call was made for widespread genetic rescue attempts. However, several aspects of augmenting gene flow are poorly understood, including the magnitude and duration of beneficial effects and when deleterious effects are likely to occur. We discuss the remaining uncertainties of genetic rescue in order to promote and direct future research and to hasten progress toward implementing this potentially powerful conservation strategy on a broader scale.

Experimental test of genetic rescue in isolated populations of brook trout.

Genetic rescue is an increasingly considered conservation measure to address genetic erosion associated with habitat loss and fragmentation. The resulting gene flow from facilitating migration may improve fitness and adaptive potential, but is not without risks (e.g., outbreeding depression). Here, we conducted a test of genetic rescue by translocating ten (five of each sex) brook trout (Salvelinus fontinalis) from a single source to four nearby and isolated stream populations. To control for the demographic contribution of translocated individuals, ten resident individuals (five of each sex) were removed from each recipient population. Prior to the introduction of translocated individuals, the two smallest above-barrier populations had substantially lower genetic diversity, and all populations had reduced effective number of breeders relative to adjacent below-barrier populations. In the first reproductive bout following translocation, 31 of 40 (78%) translocated individuals reproduced successfully. Translocated individuals contributed to more families than expected under random mating and generally produced larger full-sibling families. We observed relatively high (>20%) introgression in three of the four recipient populations. The translocations increased genetic diversity of recipient populations by 45% in allelic richness and 25% in expected heterozygosity. Additionally, strong evidence of hybrid vigour was observed through significantly larger body sizes of hybrid offspring relative to resident offspring in all recipient populations. Continued monitoring of these populations will test for negative fitness effects beyond the first generation. However, these results provide much-needed experimental data to inform the potential effectiveness of genetic rescue-motivated translocations.

Keeping things local: Subpopulation Nb and Ne in a stream network with partial barriers to fish migration.

For organisms with overlapping generations that occur in metapopulations, uncertainty remains regarding the spatiotemporal scale of inference of estimates of the effective number of breeders (N^b) and whether these estimates can be used to predict generational Ne. We conducted a series of tests of the spatiotemporal scale of inference of estimates of Nb in nine consecutive cohorts within a long-term study of brook trout (Salvelinus fontinalis). We also tested a recently developed approach to estimate generational Ne from N^b and compared this to an alternative approach for estimating N^e that also accounts for age structure. Multiple lines of evidence were consistent with N^b corresponding to the local (subpopulation) spatial scale and the cohort-specific temporal scale. We found that at least four consecutive cohort-specific estimates of N^b were necessary to obtain reliable estimates of harmonic mean N^b for a subpopulation. Generational N^e derived from cohort-specific N^b was within 7%-50% of an alternative approach to obtain N^e, suggesting some population specificity for concordance between approaches. Our results regarding the spatiotemporal scale of inference for Nb should apply broadly to many taxa that exhibit overlapping generations and metapopulation structure and point to promising avenues for using cohort-specific N^b for local-scale genetic monitoring.

A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags.

Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade(-1)) and a widening of the synchronized period (29 d decade(-1)). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.

Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout.

Understanding how multiple extrinsic (density-independent) factors and intrinsic (density-dependent) mechanisms influence population dynamics has become increasingly urgent in the face of rapidly changing climates. It is particularly unclear how multiple extrinsic factors with contrasting effects among seasons are related to declines in population numbers and changes in mean body size and whether there is a strong role for density-dependence. The primary goal of this study was to identify the roles of seasonal variation in climate driven environmental direct effects (mean stream flow and temperature) vs. density-dependence on population size and mean body size in eastern brook trout (Salvelinus fontinalis). We use data from a 10-year capture-mark-recapture study of eastern brook trout in four streams in Western Massachusetts, USA to parameterize a discrete-time population projection model. The model integrates matrix modeling techniques used to characterize discrete population structures (age, habitat type, and season) with integral projection models (IPMs) that characterize demographic rates as continuous functions of organismal traits (in this case body size). Using both stochastic and deterministic analyses we show that decreases in population size are due to changes in stream flow and temperature and that these changes are larger than what can be compensated for through density-dependent responses. We also show that the declines are due mostly to increasing mean stream temperatures decreasing the survival of the youngest age class. In contrast, increases in mean body size over the same period are the result of indirect changes in density with a lesser direct role of climate-driven environmental change.

The evolutionary legacy of size-selective harvesting extends from genes to populations.

Size-selective harvesting is assumed to alter life histories of exploited fish populations, thereby negatively affecting population productivity, recovery, and yield. However, demonstrating that fisheries-induced phenotypic changes in the wild are at least partly genetically determined has proved notoriously difficult. Moreover, the population-level consequences of fisheries-induced evolution are still being controversially discussed. Using an experimental approach, we found that five generations of size-selective harvesting altered the life histories and behavior, but not the metabolic rate, of wild-origin zebrafish (Danio rerio). Fish adapted to high positively size selective fishing pressure invested more in reproduction, reached a smaller adult body size, and were less explorative and bold. Phenotypic changes seemed subtle but were accompanied by genetic changes in functional loci. Thus, our results provided unambiguous evidence for rapid, harvest-induced phenotypic and evolutionary change when harvesting is intensive and size selective. According to a life-history model, the observed life-history changes elevated population growth rate in harvested conditions, but slowed population recovery under a simulated moratorium. Hence, the evolutionary legacy of size-selective harvesting includes populations that are productive under exploited conditions, but selectively disadvantaged to cope with natural selection pressures that often favor large body size.

Effective number of breeders provides a link between interannual variation in stream flow and individual reproductive contribution in a stream salmonid.

The effective number of breeders that give rise to a cohort (N(b)) is a promising metric for genetic monitoring of species with overlapping generations; however, more work is needed to understand factors that contribute to variation in this measure in natural populations. We tested hypotheses related to interannual variation in N(b) in two long-term studies of brook trout populations. We found no supporting evidence for our initial hypothesis that N^(b) reflects N^(c) (defined as the number of adults in a population at the time of reproduction). N^(b) was stable relative to N^(C) and did not follow trends in abundance (one stream negative, the other positive). We used stream flow estimates to test the alternative hypothesis that environmental factors constrain N(b). We observed an intermediate optimum autumn stream flow for both N^(b) (R(2) = 0.73, P = 0.02) and full-sibling family evenness (R(2) = 0.77, P = 0.01) in one population and a negative correlation between autumn stream flow and full-sib family evenness in the other population (r = -0.95, P = 0.02). Evidence for greater reproductive skew at the lowest and highest autumn flow was consistent with suboptimal conditions at flow extremes. A series of additional tests provided no supporting evidence for a related hypothesis that density-dependent reproductive success was responsible for the lack of relationship between N(b) and N(C) (so-called genetic compensation). This work provides evidence that N(b) is a useful metric of population-specific individual reproductive contribution for genetic monitoring across populations and the link we provide between stream flow and N(b) could be used to help predict population resilience to environmental change.

Robust estimates of environmental effects on population vital rates: an integrated capture-recapture model of seasonal brook trout growth, survival and movement in a stream network.

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses. We developed an integrated capture-recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival. We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature. Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall. These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful.