Under climate change, species unable to track their niche via range shifts are largely reliant on genetic variation to adapt and persist. Genomic vulnerability predictions are used to identify populations that lack the necessary variation, particularly at climate-relevant genes. However, hybridization as a source of novel adaptive variation is typically ignored in genomic vulnerability studies. We estimated environmental niche models and genomic vulnerability for closely related species of rainbowfish (Melanotaeniaspp.) across an elevational gradient in the Australian Wet Tropics. Hybrid populations between a widespread generalist and several narrow range endemic species exhibited reduced vulnerability to projected climates compared to pure narrow endemics. Overlaps between introgressed and adaptive genomic regions were consistent with a signal of adaptive introgression. Our findings highlight the often-underappreciated conservation value of hybrid populations and indicate that adaptive introgression may contribute to evolutionary rescue of species with narrow environmental ranges.

Significance: Adaptation to climate change is expected to be influenced by thermal conditions experienced by species during their evolutionary history. We studied plastic capacity as a target of climatic selection, hypothesizing that populations that evolved under warmer climates have greater plastic adaptive resilience to climate change. This was tested experimentally by comparing upper thermal tolerance and gene expression in fish populations from desert, temperate, and subtropical regions of Australia. Divergent adaptive plastic responses to future climates were found across different bioregions, including in key heat stress genes. The greatest adaptive resilience was shown by the subtropical ecotype, followed by the desert and temperate ecotypes. These results have implications for large-scale assessments of climate impacts and for predictions of species distribution changes.

To conserve the high functional and genetic variation in hotspots such as tropical rainforests, it is essential to understand the forces driving and maintaining biodiversity. We asked to what extent environmental gradients and terrain structure affect morphological and genomic variation across the wet tropical distribution of an Australian rainbowfish,Melanotaenia splendida splendida. We used an integrative riverscape genomics and morphometrics framework to assess the influence of these factors on both putative adaptive and non-adaptive spatial divergence. We found that neutral genetic population structure was largely explainable by restricted gene flow among drainages. However, environmental associations revealed that ecological variables had a similar power to explain overall genetic variation, and greater power to explain body shape variation, than the included neutral covariables. Hydrological and thermal variables were the strongest environmental predictors and were correlated with traits previously linked to heritable habitat-associated dimorphism in rainbowfishes. In addition, climate-associated genetic variation was significantly associated with morphology, supporting heritability of shape variation. These results support the inference of evolved functional differences among localities, and the importance of hydroclimate in early stages of diversification. We expect that substantial evolutionary responses will be required in tropical rainforest endemics to mitigate local fitness losses due to changing climates.

Genetic rescue is a conservation management strategy that reduces the negative effects of genetic drift and inbreeding in small and isolated populations. However, such populations might already be vulnerable to random fluctuations in growth rates (demographic stochasticity). Therefore, the success of genetic rescue depends not only on the genetic composition of the source and target populations but also on the emergent outcome of interacting demographic processes and other stochastic events. Developing predictive models that account for feedback between demographic and genetic processes (‘demo‐genetic feedback’) is therefore necessary to guide the implementation of genetic rescue to minimize the risk of extinction of threatened populations. Here, we explain how the mutual reinforcement of genetic drift, inbreeding, and demographic stochasticity increases extinction risk in small populations. We then describe how these processes can be modelled by parameterizing underlying mechanisms, including deleterious mutations with partial dominance and demographic rates with variances that increase as abundance declines. We combine our suggestions of model parameterization with a comparison of the relevant capability and flexibility of five open‐source programs designed for building genetically explicit, individual‐based simulations. Using one of the programs, we provide a heuristic model to demonstrate that simulated genetic rescue can delay extinction of small virtual populations that would otherwise be exposed to greater extinction risk due to demo‐genetic feedback. We then use a case study of threatened Australian marsupials to demonstrate that published genetic data can be used in one or all stages of model development and application, including parameterization, calibration, and validation. We highlight that genetic rescue can be simulated with either virtual or empirical sequence variation (or a hybrid approach) and suggest that model‐based decision‐making should be informed by ranking the sensitivity of predicted probability/time to extinction to variation in model parameters (e.g., translocation size, frequency, source populations) among different genetic‐rescue scenarios.

Genetic rescue is now a serious management consideration for protecting small and isolated populations from the negative effects of inbreeding and genetic drift on genetic diversity and population viability. However, such populations might be already vulnerable to random fluctuations in growth rates (demographic stochasticity). Therefore, the success of genetic rescue depends not only on the genetic composition of the source and target populations, but also on the emergent outcome of interacting demographic processes and other stochastic events. Developing predictive models that account for feedback between demographic and genetic processes ('demo-genetic feedback') is therefore necessary to guide genetic-rescue interventions that potentially minimise the risk of extinction of threatened populations. We review the available software and explore how they could be used to develop practical simulations that incorporate demo-genetic feedback to plan and implement scenarios of genetic rescue. We then present a summary of a literature search of available genetic data using Australian threatened marsupials as a case study. We conclude with a guided approach for making model-based decisions on implementing genetic rescue.