Successful implementation of evolutionary management programs to rescue climatically threatened species requires identification of adaptive genetic variation. Although current genotype-environment association methods have been successful in identifying adaptive variation, they can be improved in two important aspects. First, most existing methods do not account for genotype uncertainty in widely available low-coverage whole-genome sequencing data. Researchers often restrict analysis to loci for which genotypes can be inferred reliably or call the most probable genotype, allowing the use of traditional genotype-based methods, such as BayeScEnv and Bayenv. However, discarding data and false genotype calls increases the uncertainty in estimates of genetic variation and introduces systematic biases. Second, most methods use phenomenological approaches, such as logistic regression, to partition estimated genetic variation into adaptive and non-adaptive components. Consequently, current approaches may inadvertently fail to account for evolutionary processes, such as migration-selection balance. Structured migration between climatically disparate locations can produce deviations from a smooth S-shape response curve, which can be difficult to accommodate using generalized linear regression models. To overcome these challenges, we developed a method that accounts for genotype uncertainty in sequencing data and propagates this uncertainty to inform the parameters of a model of evolution. A key feature of this evolutionary model is that it mechanistically describes how genetic variation arises from joint interactions between local adaptation, structured migration, mutation, and drift. We apply our approach to analyze multiple synthetic datasets and a real dataset of North American rosy-finches (3.7 million SNPs), a high-alpine, climatically threatened clade of bird species. ### Competing Interest Statement The authors have declared no competing interest. U.S. National Science Foundation, 2222525, 1927177, 2222524, 2222526 U.S. National Science Foundation, 2138259, 2138286, 2138307, 2137603, 2138296

1. Identifying genomic adaptation is key to understanding species' evolutionary responses to environmental changes. However, current methods to identify adaptive variation have two major limitations. First, when estimating genetic variation, most methods do not account for observational uncertainty in genetic data because of finite sampling and missing genotypes. Second, many current methods use phenomenological models to partition genetic variation into adaptive and non-adaptive components. 2. We address these limitations by developing a hierarchical Bayesian model that explicitly accounts for observational uncertainty and underlying evolutionary processes. The first layer of the hierarchy is the data model that captures observational uncertainty by probabilistically linking RAD sequence data to genetic variation. The second layer is a process model that represents how evolutionary forces, such as local adaptation, mutation, migration and drift, maintain genetic variation. The third layer is the parameter model, which incorporates our knowledge about biological processes. For example, because most loci in the genome are expected to be neutral, the environmental sensitivity coefficients are assigned a regularized prior centred at zero. Together, the three models provide a rigorous probabilistic framework to identify local adaptation in wild organisms. 3. Analysis of simulated RAD-seq data shows that our statistical model can reliably infer adaptive genetic variation. To show the real-world applicability of our method, we re-analysed RAD-Seq data (similar to 105 k SNPs) from Willow Flycatchers (Empidonax traillii) in the United States. We found 30 genes close to 47 loci that showed a statistically significant association with temperature seasonality. Gene ontology suggests that several of these genes play a crucial role in egg mineralization, feather development and the ability to withstand extreme temperatures. 4. Moreover, the data and process models can be modified to accommodate a wide range of genetic datasets (e.g. pool and low coverage genome sequencing) and demographic histories (e.g. range shifts) to study climatic adaptation in a wide range of natural systems.

The frequency and severity of drought in the Western United States have significantly increased. California endemic blue oaks ( Quercus douglasii ) are predicted to be negatively impacted by extreme drought and are already experiencing dieback in the driest areas of their distribution. To explore whether there is drought‐adaptive variation among blue oak populations, we conducted a greenhouse common garden drought experiment with seedlings from five sites along a range‐wide precipitation gradient. We investigated seedling performance under experimental drought (fluorescence/maximum fluorescence [Fv/Fm], stomatal conductance, and leaf desiccation). We measured physiological and morphological traits, including average leaf area, specific leaf area (SLA), leaf margin morphology, C:N, and carbon isotope discrimination (δ 13 C, a proxy for water use efficiency). We used generalized linear mixed models to understand the relationship between seedling performance and traits, and the mean annual precipitation (MAP) of the seedling source site. We found significant relationships between source site MAP and Fv/Fm, percent of green leaves, and plant stomatal conductance, with plants from drier source sites performing better under the experimental drought. Seedlings from drier sites also had a lower C:N ratio, consistent with adaptation to more arid environments. Our study points to population‐level variation in seedling drought adaptation. Climate‐forward conservation strategies that conserve or leverage drought‐adaptive genetic resources from the species' threatened dry range edge could support climate change resilience in a future drier environment.

Abstract Increasing anthropogenic emissions of nitrogen (N) and carbon (C) are major threats to ecosystems globally. Although atmospheric N deposition is likely affecting N cycling and community composition in California's serpentine ecosystems, a historical record of N inputs to vegetation has yet to be reconstructed for these nutrient‐limited biodiversity hotspots. For leather oak (Quercus durata var. durata), a foundational, serpentine‐endemic species, we investigated leaf N and C isotopic composition (δ15N and δ13C) and leaf %N of herbarium and modern leaf samples collected from 1899 to 2009 from serpentine ecosystems in two study areas in California: Santa Clara County, and Lake and Napa Counties combined. We also evaluated tree ring growth over a similar time period in long‐lived leather oak individuals. Leaf δ15N and δ13C values decreased over time in both study areas, likely reflecting changes in the regional and local atmospheric N and C pools caused by human perturbation. However, leaf %N values and stem growth did not change over time with increasing N deposition, indicating that increasing atmospheric N deposition and CO2 concentration may not translate to increased N uptake or productivity in plants with conservative growth strategies, even in ecosystems thought to be N‐limited. In serpentine systems, this could competitively advantage nitrophilic invasive annual grasses and accelerate trends toward native species loss. While the rates of decline in leaf δ15N values were similar between study areas, rates of decline in leaf δ13C values were steeper in Santa Clara County, possibly reflecting its more urban environment. Herbarium samples combined with tree ring data can provide a valuable opportunity to explore the historical record of human‐induced changes in N and C cycling and their biotic impacts.

Fieldwork is crucial for science but poses heightened risks of gender-based harassment and assault. Current practices prioritize post-incident reporting, despite the demonstrated potential of preventive approaches. We recommend proactive practices, training strategies, and systemic policy changes to build safe and inclusive fieldwork settings from the outset.

Over the past three decades, climate change adaptation has become a central focus in conservation. To inform these efforts, the scientific community has provided a growing body of recommendations on biodiversity management with climate change. A previously published study reviewed the first wave of such recommendations in the peer-reviewed literature as they occurred between 1985 and 2007. Here we build on that work, reviewing the literature from the subsequent time period, 2007–2017. We report on the development of the field between the two time periods, and review in depth three highly ranked, climate change-specific conservation strategies from the more recent time period. Overall, recommended strategies for ecological management have remained remarkably consistent over the last three decades, and the field continues to draw mainly on conventional, long-standing conservation approaches. However, the actionability and specificity of recommendations have increased, and certain novel, climate change-specific strategies have become more prominent, pointing the way toward increasing options for practitioner response.

Aim Species persistence in the face of climate change depends on both ecological and evolutionary factors. Here, we integrate ecological and whole-genome sequencing data to describe how populations of an alpine specialist, the Brown-capped Rosy-Finch (Leucosticte australis) may be impacted by climate change. Location Southern Rocky Mountains in North America. Methods We sampled 116 Brown-capped Rosy-Finches from 11 sampling locations across the breeding range. Using 429,442 genetic markers from whole-genome sequencing, we described population genetic structure and identified a subset of 436 genomic variants associated with environmental data. We modelled future climate change impacts on habitat suitability using ecological niche models (ENMs) and impacts on putative local adaptation using gradient forest models (a genetic-environment association analysis; GEA). We used the metric of niche margin index (NMI) to determine regions of forecasting uncertainty due to climate shifts to novel conditions. Results Population genetic structure was characterized by weak genetic differentiation, indicating potential ongoing gene flow among populations. Precipitation as snow had high importance for both habitat suitability and changes in genetic variation across the landscape. Comparing ENM and gradient forest models with future climate predicted suitable habitat contracting at high elevations and population allele frequencies across the breeding range needing to shift to keep pace with climate change. NMI revealed large portions of the breeding range shifting to novel climate conditions. Main conclusions Our study demonstrates that forecasting climate vulnerability from ecological and evolutionary factors reveals insights into population-level vulnerability to climate change that are obfuscated when either approach is considered independently. For the Brown-capped Rosy-Finch, our results suggest that persistence may depend on rapid adaptation to novel climate conditions in a contracted breeding range. Importantly, we demonstrate the need to characterize novel climate conditions that influence uncertainty in forecasting methods.

Globally, cold-limited trees and forests are expected to experience growth acceleration as a direct response to warming temperatures. However, thresholds of temperature limitation may vary substantially with local environmental conditions, leading to heterogeneous responses in tree ecophysiology. We used dendroecological and isotopic methods to quantify shifting tree growth and resource use over the past 143 years across topographic aspects in a high-elevation forest of central Mexico. Trees on south-facing slopes (SFS) grew faster than those on north-facing slopes (NFS) until the mid-20th century, when this pattern reversed notably with marked growth rate declines on SFS and increases on NFS. Stable isotopes of carbon, oxygen, and carbon-to-nitrogen ratios suggest that this reversal is linked to interactions between CO2 stimulation of photosynthesis and water or nitrogen limitation. Our findings highlight the importance of incorporating landscape processes and habitat heterogeneity in predictions of tree growth responses to global environmental change.

Abstract The need to ensure that rising investment in nature‐based climate solutions delivers expected outcomes hinges on incorporating current and future climate into design and implementation. Technical guidelines and formal planning processes serve a purpose in ensuring the quality of climate‐informed strategies for local projects. The inherent complexity, cost, and time required to use these tools, however, can make them inaccessible or daunting. Taking lessons learned from a decade of funding over 100 adaptation initiatives in conservation—some of which also provide mitigation benefits—we describe a simple rapid assessment framework for use by practitioners and funders. This framework, which we refer to as the 5Ws (what, when, where, why, and who) of climate‐informed action, serves as a guide to make projects more robust to future climate.

Understanding how gene flow affects population divergence and speciation remains challenging. Differentiating one evolutionary process from another can be difficult because multiple processes can produce similar patterns, and more than one process can occur simultaneously. Although simple population models produce predictable results, how these processes balance in taxa with patchy distributions and complicated natural histories is less certain. These types of populations might be highly connected through migration (gene flow), but can experience stronger effects of genetic drift and inbreeding, or localized selection. Although different signals can be difficult to separate, the application of high-throughput sequence data can provide the resolution necessary to distinguish many of these processes. We present whole-genome sequence data for an avian species group with an alpine and arctic tundra distribution to examine the role that different population genetic processes have played in their evolutionary history. Rosy-finches inhabit high elevation mountaintop sky islands and high-latitude island and continental tundra. They exhibit extensive plumage variation coupled with low levels of genetic variation. Additionally, the number of species within the complex is debated, making them excellent for studying the forces involved in the process of diversification, as well as an important species group in which to investigate species boundaries. Total genomic variation suggests a broadly continuous pattern of allele frequency changes across the mainland taxa of this group in North America. However, phylogenomic analyses recover multiple distinct, well supported, groups that coincide with previously described morphological variation and current species-level taxonomy. Tests of introgression using D-statistics and approximate Bayesian computation reveal significant levels of introgression between multiple North American taxa. These results provide insight into the balance between divergent and homogenizing population genetic processes and highlight remaining challenges in interpreting conflict between different types of analytical approaches with whole-genome sequence data. [ABBA-BABA; approximate Bayesian computation; gene flow; phylogenomics; speciation; whole-genome sequencing.].

Biodiversity losses are a major driver of global changes in ecosystem functioning. While most studies of the relationship between biodiversity and ecosystem functioning have examined randomized species losses, trait-based filtering associated with species-specific vulnerability to drivers of diversity loss can strongly influence how ecosystem functioning responds to declining biodiversity. Moreover, the responses of ecosystem functioning to diversity loss may be mediated by environmental variability interacting with the suite of traits remaining in depauperate communities. We do not yet understand how communities resulting from realistic diversity losses (filtered by response traits) influence ecosystem functioning (via effect traits of the remaining community), especially under variable environmental conditions. Here, we directly test how realistic and randomized plant diversity losses influence productivity and invasion resistance across multiple years in a California grassland. Compared with communities based on randomized diversity losses, communities resulting from realistic (drought-driven) species losses had higher invasion resistance under climatic conditions that matched the trait-based filtering they experienced. However, productivity declined more with realistic than with randomized species losses across all years, regardless of climatic conditions. Functional response traits aligned with effect traits for productivity but not for invasion resistance. Our findings illustrate that the effects of biodiversity losses depend not only on the identities of lost species but also on how the traits of remaining species interact with varying environmental conditions. Understanding the consequences of biodiversity change requires studies that evaluate trait-mediated effects of species losses and incorporate the increasingly variable climatic conditions that future communities are expected to experience.

Field courses have been identified as powerful tools for student success in science, but the potential for field courses to address demographic disparities and the mechanisms behind these benefits are not well understood. To address these knowledge gaps, we studied students in a nonmajors Ecology and Evolutionary Biology course, Introduction to Field Research and Conservation, at the University of California Santa Cruz, a large Hispanic-Serving Institution. We examined (a) the effects of participation on students' perception of their scientific competencies and (b) how the field course shaped student experiences and built their sense of community, confidence and belonging in science. Our mixed-methods approach included the Persistence in the Sciences (PITS) survey with field course students and a control group; interviews, focus groups, and prompted student journal entries with a subset of field course students; and participant-observation. We found that field course participants scored higher on all science identity items of the PITS instrument than students in the control (lecture course) group. Field course students from underrepresented minority groups also scored similarly to or higher than their well-represented peers on each of the six PITS survey components. From our qualitative data, themes of growth in peer community, relationships with mentors, confidence living and working outdoors, team-based science experiences, and a sense of contributing to knowledge and discovery interacted throughout the course-especially from the initial overnight field trip to the final one-to assist these gains and strengthen interest in science and support persistence. These findings highlight the importance of holistic support and community building as necessary driving factors in inclusive course design, especially as a way to begin to dismantle structures of exclusion in the sciences.

Field courses have been identified as powerful tools for inclusion and student success in science. However, not all students are equally likely to take field courses. How do we remove barriers to equity in field courses, to make them engines for inclusion, diversity, and collective excellence in ecology and evolution?

Conservation and restoration of riparian vegetation in agricultural landscapes has had mixed success at protecting in‐stream habitat, potentially due to the mismatch between watershed‐scale impacts and reach‐scale restoration. Prioritizing contiguous placement of small‐scale restoration interventions may effectively create larger‐scale restoration projects and improve ecological outcomes. We performed a multi‐site field study to evaluate whether greater linear length of narrow riparian tree corridors resulted in measurable benefits to in‐stream condition. We collected data at 41 sites with varying upstream tree cover nested within 13 groups in rangeland streams in coastal northern California, United States. We evaluated the effect of riparian tree corridor length on benthic macroinvertebrate communities, as well as food resources, water temperature, and substrate size. Sites with longer riparian corridors had higher percentages of invertebrates sensitive to disturbance (including clingers and EPT taxa) as well as lower water temperatures and less fine sediment, two of the most important aquatic stressors. Despite marked improvement, we found no evidence that macroinvertebrate communities fully recovered, suggesting that land use continued to constrain conditions. The restoration of long riparian corridors may be an economically viable and rapidly implementable technique to improve habitat, control sediment, and counter increasing water temperatures expected with climate change within the context of ongoing land use.

Helping the world's coastal communities adapt to climate change impacts requires evaluating the vulnerability of coastal communities and assessing adaptation options. This includes understanding the potential for 'natural' infrastructure (ecosystems and the biodiversity that underpins them) to reduce communities' vulnerability, alongside more traditional 'hard' infrastructure approaches. Here we present a spatially explicit global evaluation of the vulnerability of coastal-dwelling human populations to key climate change exposures and explore the potential for coastal ecosystems to help people adapt to climate change (ecosystem-based adaptation (EbA)). We find that mangroves and coral reefs are particularly well situated to help people cope with current weather extremes, a function that will only increase in importance as people adapt to climate change now and in coming decades. We find that around 30.9 million people living within 2km of the coast are highly vulnerable to tropical storms and sea-level rise (SLR). Mangroves and coral reefs overlap these threats to at least 5.3 and 3.4 million people, respectively, with substantial potential to dissipate storm surges and improve resilience against SLR effects. Significant co-benefits from mangroves also accrue, with 896 million metric tons of carbon stored in their soils and above- and below-ground biomass. Our framework offers a tool for prioritizing 'hotspots' of coastal EbA potential for further, national and local analyses to quantify risk reduction and, thereby, guide investment in coastal ecosystems to help people adapt to climate change. In doing so, it underscores the global role that conserving and restoring ecosystems can play in protecting human lives and livelihoods, as well as biodiversity, in the face of climate change.

Conservation translocations - the intentional movement of individuals from one area to another for conservation purposes - provide a potential response to climate change, but can be costly and risky. To help improve translocation outcomes and assess their feasibility as a climate adaptation tool, we analyzed past conservation translocations (176 bird species at 680 sites globally) as a proxy for future efforts. To determine predictors of annual survival of released birds, we used generalized linear mixed models. Species with larger bodies and relative brain size had higher survival. Survival was also higher in protected areas, with subsequent releases at a site, for more recent years, and where the initial cause of decline was removed (n = 435 releases). Of particular relevance to climate-motivated translocations, longer distance translocations decreased survival; there was no evidence that greater climate differences between source and release sites (n = 117 releases), or releases beyond the indigenous range ("managed relocation", n = 435 releases), reduced survival. We also assessed how reproduction varied with release rates (birds/year) and species' generation lengths. Species with long generation lengths released at high rates had similar reproductive success to species with short generation lengths released at low rates. These findings can improve conservation translocation decisions by informing expected outcomes for target species, and identifying site features and management practices that maximize the likelihood of success. We also provide an empirical assessment of potential challenges of using conservation translocations in response to climate change, including evidence that longer distance translocations may be less feasible than shorter distance translocations.