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Conservation translocations, intentional movements of species to protect against extinction, have become widespread in recent decades and are projected to increase further as biodiversity loss continues worldwide. The literature abounds with analyses to inform translocations and assess whether they are successful, but the fundamental question of whether they should be initiated at all is rarely addressed formally. We used decision analysis to assess northern leopard frog reintroduction in northern Idaho, with success defined as a population that persists for at least 50 years. The Idaho Department of Fish and Game was the decision maker (i.e., the agency that will use this assessment to inform their decisions). Stakeholders from government, indigenous groups, academia, land management agencies, and conservation organizations also participated. We built an age-structured population model to predict how management alternatives would affect probability of success. In the model, we explicitly represented epistemic uncertainty around a success criterion (probability of persistence) characterized by aleatory uncertainty. For the leading alternative, the mean probability of persistence was 40%. The distribution of the modelling results was bimodal, with most parameter combinations resulting in either very low (<5%) or relatively high (>95%) probabilities of success. Along with other considerations, including cost, the Idaho Department of Fish and Game will use this assessment to inform a decision regarding reintroduction of northern leopard frogs. Conservation translocations may benefit greatly from more widespread use of decision analysis to counter the complexity and uncertainty inherent in these decisions. History: This paper has been accepted for the Decision Analysis Special Issue on Further Environmental Sustainability. Funding: This work was supported by the Wilder Institute/Calgary Zoo, the U.S. Fish and Wildlife Service [Grant F18AS00095], the NSF Idaho EPSCoR Program and the National Science Foundation [Grant OIA-1757324], and the Hunt Family Foundation. Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2023.0472 . 

Barriers such as hydroelectric dams inhibit migratory pathways essential to many aquatic species, resulting in significant losses of species, their unique life-history forms, and genetic diversity. Understanding the impacts of dam removal to species recovery at these different biological levels is crucial to fully understand the restoration response. We used the removal of two large dams on the Elwha River as an opportunity to characterize how restored connectivity impacts the reestablishment of two fish species, Chinook salmon (Oncorhynchus tshawytscha) and Steelhead/rainbow trout (Oncorhynchus mykiss), and their unique ocean migration return-timing life-history forms. In this study, we employed riverscape genetics to understand how restoration and the environment influence the distribution of neutral and return-timing genetic variation underlying the migratory life-history forms and species at- and between- sampling sites. We genotyped fish sampled over time and space in the Elwha River using Genotyping-in-Thousands by sequencing (GTseq) loci for both species at neutral and putatively adaptive loci in and near the major effect genic regionGREB1L/ROCK1putatively associated with migration timing. We observed little evidence of genetic structure for either species, but a statistically significant increase in early return-timing alleles in upriverO. mykisspopulation post-dam removal. ForO. tshawytscha, at-site genetic variation was shaped by river distance and a combination of environmental habitat differences, while between-site genetic variation was mainly shaped by river distance. For allO. mykiss, at- and between-site genetic variation is primarily explained by river distance. Genetic variation in juvenile and adult Steelhead, respectively, were influenced by at- and between-site environmental and habitat differences. Our study illustrates the power of using genetics to understand the implications of both demography and environment in facilitating the recovery of species and their diverse life-history forms following barrier removal. 

Abstract Despite growing interest in conservation and re‐establishment of ecological connectivity, few studies have explored its context‐specific social–ecological outcomes. We aimed to explore social and ecological outcomes to changing stream connectivity for both stakeholders and native fish species impacted by habitat fragmentation and nonnative species. We (1) investigated stakeholder perceptions of the drivers and outcomes of stream connectivity, and (2) evaluated the effects of stakeholder‐identified connectivity and nonnative species scenarios on Yellowstone cutthroat trout (YCT) populations. Our study was conducted in the Teton River, Idaho, USA. We integrated two modeling approaches, mental modeling and individual‐based ecological modeling, to explore social–ecological outcomes for stakeholders and YCT populations. Aggregation of mental models revealed an emergent pattern of increasing complexity as more types of stakeholders were considered, as well as gaps and linkages among different stakeholder knowledge areas. These results highlight the importance of knowledge sharing among stakeholders when making decisions about connectivity. Additionally, the results from the individual‐based models suggested that the potential for a large, migratory life history form of YCT, in addition to self‐preference mating where they overlap with rainbow trout, had the strongest effects on outcomes for YCT. Exploring social and ecological drivers and outcomes to changing connectivity is useful for anticipating and adapting to unintended outcomes, as well as making decisions for desirable outcomes. The results from this study can contribute to the management dialogue surrounding stream connectivity in the Teton River, as well as to our understanding of connectivity conservation and its outcomes more broadly. 

Abstract Adaptive capacity can present challenges for modelling as it encompasses multiple ecological and evolutionary processes such as natural selection, genetic drift, gene flow and phenotypic plasticity. Spatially explicit, individual‐based models provide an outlet for simulating these complex interacting eco‐evolutionary processes. We expanded the existing Cost‐Distance Meta‐POPulation (CDMetaPOP) framework with inducible plasticity modelled as a habitat selection behaviour, using temperature or habitat quality variables, with a genetically based selection threshold conditioned on past individual experience. To demonstrate expected results in the new module, we simulated hypothetical populations and then evaluated model performance in populations of redband trout (Oncorhynchus mykiss gairdneri) across three watersheds where temperatures induce physiological stress in parts of the stream network. We ran simulations using projected warming stream temperature data under four scenarios for alleles that: (1) confer thermal tolerance, (2) bestow plastic habitat selection, (3) give both thermal tolerance and habitat selection preference and (4) do not provide either thermal tolerance or habitat selection. Inclusion of an adaptive allele decreased declines in population sizes, but this impact was greatly reduced in the relatively cool stream networks. As anticipated with the new module, high‐temperature patches remained unoccupied by individuals with the allele operating plastically after exposure to warm temperatures. Using complete habitat avoidance above the stressful temperature threshold, habitat selection reduced the overall population size due to the opportunity cost of avoiding areas with increased, but not guaranteed, mortality. Inclusion of plasticity within CDMetaPOP will provide the potential for genetic or plastic traits and ‘rescue’ to affect eco‐evolutionary dynamics for research questions and conservation applications. 

Abstract Adaptive capacity is a topic at the forefront of environmental change research with roots in both social, ecological, and evolutionary science. It is closely related to the evolutionary biology concept of adaptive potential. In this systematic literature review, we: (1) summarize the history of these topics and related fields; (2) assess relationship(s) between the concepts among disciplines and the use of the terms in climate change research, and evaluate methodologies, metrics, taxa biases, and the geographic scale of studies; and (3) provide a synthetic conceptual framework to clarify concepts. Bibliometric analyses revealed the terms have been used most frequently in conservation and evolutionary biology journals, respectively. There has been a greater growth in studies of adaptive potential than adaptive capacity since 2001, but a greater geographical extent of adaptive capacity studies. Few studies include both, and use is often superficial. Our synthesis considers adaptive potential as one process contributing to adaptive capacity of complex systems, notes “sociological” adaptive capacity definitions include actions aimed at desired outcome (i.e., policies) as a system driver whereas “biological” definitions exclude such drivers, and suggests models of adaptive capacity require integration of evolutionary and social–ecological system components. 

Whole‐genome sequencing is revolutionizing our understanding of organismal biology, including adaptations likely to influence demographic performance in different environments. Excitement over the potential of genomics to inform population dynamics has prompted multiple conservation applications, including genomics‐based decision‐making for translocation efforts. Despite interest in applying genomics to improve translocations, there is a critical research gap: we lack an understanding of how genomic differences translate into population dynamics in the real world. We review how genomics and genetics data could be used to inform organismal performance, including examples of how adaptive and neutral loci have been quantified in a translocation context, and future applications. Next, we discuss three main drivers of population dynamics: demographic structure, spatial barriers to movement, and introgression, and their consequences for translocations informed by genomic data. Finally, we provide a practical guide to different types of models, including size‐structured and spatial models, that could be modified to include genomics data. We then propose a framework to improve translocation success by repeatedly developing, selecting, and validating forecasting models. By integrating lab‐based and field‐collected data with model‐driven research, our iterative framework could address long‐standing challenges in restoration ecology, such as when selecting locally adapted genotypes will aid translocation of plants and animals. 

Abstract Many species that undergo long breeding migrations, such as anadromous fishes, face highly heterogeneous environments along their migration corridors and at their spawning sites. These environmental challenges encountered at different life stages may act as strong selective pressures and drive local adaptation. However, the relative influence of environmental conditions along the migration corridor compared with the conditions at spawning sites on driving selection is still unknown. In this study, we performed genome–environment associations (GEA) to understand the relationship between landscape and environmental conditions driving selection in seven populations of the anadromous Chinook salmon (Oncorhynchus tshawytscha)—a species of important economic, social, cultural, and ecological value—in the Columbia River basin. We extracted environmental variables for the shared migration corridors and at distinct spawning sites for each population, and used a Pool‐seq approach to perform whole genome resequencing. Bayesian and univariate GEA tests with migration‐specific and spawning site‐specific environmental variables indicated many more candidate SNPs associated with environmental conditions at the migration corridor compared with spawning sites. Specifically, temperature, precipitation, terrain roughness, and elevation variables of the migration corridor were the most significant drivers of environmental selection. Additional analyses of neutral loci revealed two distinct clusters representing populations from different geographic regions of the drainage that also exhibit differences in adult migration timing (summer vs. fall). Tests for genomic regions under selection revealed a strong peak on chromosome 28, corresponding to the GREB1L/ROCK1 region that has been identified previously in salmonids as a region associated with adult migration timing. Our results show that environmental variation experienced throughout migration corridors imposed a greater selective pressure on Chinook salmon than environmental conditions at spawning sites.