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Restoring gene flow among fragmented populations is discussed as a potentially powerful management strategy that could reduce inbreeding depression and cause genetic rescue. Yet, examples of assisted migration for genetic rescue remain sparse in conservation, prompting several outspoken calls for its increased use in genetic management of fragmented populations. We set out to evaluate the extent to which this strategy is underused and to determine how many imperiled species would realistically stand to benefit from genetic rescue, focusing on federally threatened or endangered vertebrate species in the United States. We developed a “genetic rescue suitability index (GR index)” based on concerns about small population problems relative to risks associated with outbreeding depression and surveyed the literature for 222 species. We found that two-thirds of these species were good candidates for consideration of assisted migration for the purpose of genetic rescue according to our suitability index. Good candidate species spanned all taxonomic groups and geographic regions, though species with more missing data tended to score lower on the suitability index. While we do not recommend a prescriptive interpretation of our GR index, we used it here to establish that assisted migration for genetic rescue is an underused strategy. For example, we found in total, “genetic rescue” was only mentioned in 11 recovery plans and has only been implemented in 3 of the species we surveyed. A potential way forward for implementation of this strategy is incorporating genetic rescue as a priority in USFWS recovery documentation. In general, our results suggest that although not appropriate for all imperiled species, many more species stand to benefit from a conservation strategy of assisted migration for genetic rescue than those for which it has previously been considered or implemented.

 

Abstract Adaptation within species to local environments is widespread in nature. Better understanding this local adaptation is critical to conserving biodiversity. However, conservation practices can rely on species’ trait averages or can broadly assume homogeneity across the range to inform management. Recent methodological advances for studying local adaptation provide the opportunity to fine-tune efforts for managing and conserving species. The implementation of these advances will allow us to better identify populations at greatest risk of decline because of climate change, as well as highlighting possible strategies for improving the likelihood of population persistence amid climate change. In the present article, we review recent advances in the study of local adaptation and highlight ways these tools can be applied in conservation efforts. Cutting-edge tools are available to help better identify and characterize local adaptation. Indeed, increased incorporation of local adaptation in management decisions may help meet the imminent demands of managing species amid a rapidly changing world. 

The unprecedented rate of extinction calls for efficient use of genetics to help conserve biodiversity. Several recent genomic and simulation-based studies have argued that the field of conservation biology has placed too much focus on conserving genome-wide genetic variation, and that the field should instead focus on managing the subset of functional genetic variation that is thought to affect fitness. Here, we critically evaluate the feasibility and likely benefits of this approach in conservation. We find that population genetics theory and empirical results show that conserving genome-wide genetic variation is generally the best approach to prevent inbreeding depression and loss of adaptive potential from driving populations toward extinction. Focusing conservation efforts on presumably functional genetic variation will only be feasible occasionally, often misleading, and counterproductive when prioritized over genome-wide genetic variation. Given the increasing rate of habitat loss and other environmental changes, failure to recognize the detrimental effects of lost genome-wide genetic variation on long-term population viability will only worsen the biodiversity crisis.

 

Adaptation to environmental change requires that populations harbor the necessary genetic variation to respond to selection. However, dispersal‐limited species with fragmented populations and reduced genetic diversity may lack this variation and are at an increased risk of local extinction. In freshwater fish species, environmental change in the form of increased stream temperatures places many cold‐water species at‐risk. We present a study of rainbow darters (Etheostoma caeruleum) in which we evaluated the importance of genetic variation on adaptive potential and determined responses to extreme thermal stress. We compared fine‐scale patterns of morphological and thermal tolerance differentiation across eight sites, including a unique lake habitat. We also inferred contemporary population structure using genomic data and characterized the relationship between individual genetic diversity and stress tolerance. We found site‐specific variation in thermal tolerance that generally matched local conditions and morphological differences associated with lake‐stream divergence. We detected patterns of population structure on a highly local spatial scale that could not be explained by isolation by distance or stream connectivity. Finally, we showed that individual thermal tolerance was positively correlated with genetic variation, suggesting that sites with increased genetic diversity may be better at tolerating novel stress. Our results highlight the importance of considering intraspecific variation in understanding population vulnerability and stress response.

 

Theory suggests that the evolution of dispersal is balanced by its fitness costs and benefits, yet empirical evidence is sparse due to the difficulties of measuring dispersal and fitness in natural populations. Here, we use spatially explicit data from a multi‐generational capture–mark–recapture study of two populations of Trinidadian guppies (Poecilia reticulata) along with pedigrees to test whether there are fitness benefits correlated with dispersal. Combining these ecological and molecular data sets allows us to directly measure the relationship between movement and reproduction. Individual dispersal was measured as the total distance moved by a fish during its lifetime. We analysed the effects of dispersal propensity and distance on a variety of reproductive metrics. We found that number of mates and number of offspring were positively correlated to dispersal, especially for males. Our results also reveal individual and environmental variation in dispersal, with sex, size, season, and stream acting as determining factors.

 

Structured demographic models are among the most common and useful tools in population biology. However, the introduction of integral projection models (IPMs) has caused a profound shift in the way many demographic models are conceptualized. Some researchers have argued that IPMs, by explicitly representing demographic processes as continuous functions of state variables such as size, are more statistically efficient, biologically realistic, and accurate than classic matrix projection models, calling into question the usefulness of the many studies based on matrix models. Here, we evaluate how IPMs and matrix models differ, as well as the extent to which these differences matter for estimation of key model outputs, including population growth rates, sensitivity patterns, and life spans. First, we detail the steps in constructing and using each type of model. Second, we present a review of published demographic models, concentrating on size‐based studies, which shows significant overlap in the way IPMs and matrix models are constructed and analyzed. Third, to assess the impact of various modeling decisions on demographic predictions, we ran a series of simulations based on size‐based demographic data sets for five biologically diverse species. We found little evidence that discrete vital rate estimation is less accurate than continuous functions across a wide range of sample sizes or size classes (equivalently bin numbers or mesh points). Most model outputs quickly converged with modest class numbers (≥10), regardless of most other modeling decisions. Another surprising result was that the most commonly used method to discretize growth rates for IPM analyses can introduce substantial error into model outputs. Finally, we show that empirical sample sizes generally matter more than modeling approach for the accuracy of demographic outputs. Based on these results, we provide specific recommendations to those constructing and evaluating structured population models. Both our literature review and simulations question the treatment of IPMs as a clearly distinct modeling approach or one that is inherently more accurate than classic matrix models. Importantly, this suggests that matrix models, representing the vast majority of past demographic analyses available for comparative and conservation work, continue to be useful and important sources of demographic information.