• Energy Research

AbstractIn its 40‐year history, the science of conservation has faced unprecedented challenges in terms of environmental damage and rapid global change, and environmental problems are only increasing as greater demands are placed on limited natural resources. Conservation science has been adapting to keep pace with these changes. Here, we highlight contemporary and emerging trends and innovations in conservation science that we believe represent the most effective responses to biodiversity threats. We focus on specific areas where conservation science has had to adjust its approach to address emerging threats to biodiversity, including habitat destruction and degradation, climate change, declining populations and invasive species. We also document changes in attitudes, norms and practices among conservation scientists. A key component to success is engaging and maintaining public support for conservation, which can be facilitated through the use of technology. These recent trends in conservation and management are innovative and will assist in optimizing conservation strategies, increasing our leverage with the general public and tackling our current environmental challenges.

Global agreements to reduce the extinction risk of migratory species depend critically on intersecting migratory connectivity-the linking of individuals between regions in different seasons-and spatial patterns of environmental change. Here we integrate movement data from >329,000 migratory birds of 112 species to develop a parameter representing exposure to global change: multispecies migratory connectivity. We then combine exposure with projected climate and land-cover changes as a measure of hazard and species conservation assessment scores as a metric of vulnerability to estimate the relative risk of migratory bird population declines across the Western Hemisphere. Multispecies migratory connectivity (exposure) is the strongest driver of risk relative to hazard and vulnerability, indicating the importance of synthesizing connectivity across species to comprehensively assess risk. Connections between breeding regions in Canada and non-breeding regions in South America are at the greatest risk, which underscores the particular susceptibility of long-distance migrants. Over half (54%) of the connections categorized as very high risk include breeding regions in the eastern United States. This three-part framework serves as an ecological risk assessment designed specifically for migratory species, providing both decision support for global biodiversity conservation and opportunities for intergovernmental collaboration to sustain migratory bird populations year-round.

AbstractOne of the most pressing questions in ecology and conservation centers on disentangling the relative impacts of concurrent global change drivers, climate and land‐use/land‐cover (LULC), on biodiversity. Yet studies that evaluate the effects of both drivers on species’ winter distributions remain scarce, hampering our ability to develop full‐annual‐cycle conservation strategies. Additionally, understanding how groups of species differentially respond to climate versus LULC change is vital for efforts to enhance bird community resilience to future environmental change. We analyzed long‐term changes in winter occurrence of 89 species across nine bird groups over a 90‐year period within the eastern United States using Audubon Christmas Bird Count (CBC) data. We estimated variation in occurrence probability of each group as a function of spatial and temporal variation in winter climate (minimum temperature, cumulative precipitation) and LULC (proportion of group‐specific and anthropogenic habitats within CBC circle). We reveal that spatial variation in bird occurrence probability was consistently explained by climate across all nine species groups. Conversely, LULC change explained more than twice the temporal variation (i.e., decadal changes) in bird occurrence probability than climate change on average across groups. This pattern was largely driven by habitat‐constrained species (e.g., grassland birds, waterbirds), whereas decadal changes in occurrence probabilities of habitat‐unconstrained species (e.g., forest passerines, mixed habitat birds) were equally explained by both climate and LULC changes over the last century. We conclude that climate has generally governed the winter occurrence of avifauna in space and time, while LULC change has played a pivotal role in driving distributional dynamics of species with limited and declining habitat availability. Effective land management will be critical for improving species’ resilience to climate change, especially during a season of relative resource scarcity and critical energetic trade‐offs.

AbstractClimate change alters ecological communities by affecting individual species and interactions between species. However, the impacts of climate change may be buffered by community diversity: diverse communities may be more resistant to climate-driven perturbations than simple communities. Here, we assess how diversity influences long-term thermal niche variation in communities under climate change. We use 50-year continental-scale data on bird communities during breeding and non-breeding seasons to quantify the communities’ thermal variability. Thermal variability is measured as the temporal change in the community’s average thermal niche and it indicates community’s response to climate change. Then, we study how the thermal variability varies as a function of taxonomic, functional, and evolutionary diversity using linear models. We find that communities with low thermal niche variation have higher functional diversity, with this pattern being measurable in the non-breeding but not in the breeding season. Given the expected increase in seasonal variation in the future climate, the differences in bird communities’ thermal variability between breeding and non-breeding seasons may grow wider. Importantly, our results suggest that functionally diverse wildlife communities can mitigate effects of climate change by hindering changes in thermal niche variability, which underscores the importance of addressing the climate and biodiversity crises together.

AbstractClimate change poses an intensifying threat to many bird species and projections of future climate suitability provide insight into how species may shift their distributions in response. Climate suitability is characterized using ecological niche models (ENMs), which correlate species occurrence data with current environmental covariates and project future distributions using the modeled relationships together with climate predictions. Despite their widespread adoption, ENMs rely on several assumptions that are rarely validated in situ and can be highly sensitive to modeling decisions, precluding their reliability in conservation decision‐making. Using data from a novel, large‐scale community science program, we developed dynamic occupancy models to validate near‐term climate suitability projections for bluebirds and nuthatches in summer and winter. We estimated occupancy, colonization, and extinction dynamics across species’ ranges in the United States in relation to projected climate suitability in the 2020s, and used a Gibbs variable selection approach to quantify evidence of species–climate relationships. We also included a Bird Conservation Region strata‐level random effect to examine among‐strata variation in occupancy that may be attributable to land‐use and ecoregional differences. Across species and seasons, we found strong evidence that initial occupancy and colonization were positively related to 2020 climate suitability, illustrating an independent validation of projections from ENMs across a large geographic area. Random strata effects revealed that occupancy probabilities were generally higher than average in core areas and lower than average in peripheral areas of species’ ranges, and served as a first step in identifying spatial patterns of occupancy from these community science data. Our findings lend much‐needed support to the use of ENM projections for addressing questions about potential climate‐induced changes in species’ occupancy dynamics. More broadly, our work highlights the value of community scientist observations for ground‐truthing projections from statistical models and for refining our understanding of the processes shaping species’ distributions under a changing climate.

Abstract Global climate change is driving species' distributions towards the poles and mountain tops during both non‐breeding and breeding seasons, leading to changes in the composition of natural communities. However, the degree of season differences in climate‐driven community shifts has not been thoroughly investigated at large spatial scales. We compared the rates of change in the community composition during both winter (non‐breeding season) and summer (breeding) and their relation to temperature changes. Based on continental‐scale data from Europe and North America, we examined changes in bird community composition using the community temperature index (CTI) approach and compared the changes with observed regional temperature changes during 1980–2016. CTI increased faster in winter than in summer. This seasonal discrepancy is probably because individuals are less site‐faithful in winter, and can more readily shift their wintering sites in response to weather in comparison to the breeding season. Regional long‐term changes in community composition were positively associated with regional temperature changes during both seasons, but the pattern was only significant during summer due to high annual variability in winter communities. Annual changes in community composition were positively associated with the annual temperature changes during both seasons. Our results were broadly consistent across continents, suggesting some climate‐driven restructuring in both European and North American avian communities. Because community composition has changed much faster during the winter than during the breeding season, it is important to increase our knowledge about climate‐driven impacts during the less‐studied non‐breeding season.

Abstract Together climate and land‐use change play a crucial role in determining species distribution and abundance, but measuring the simultaneous impacts of these processes on current and future population trajectories is challenging due to time lags, interactive effects and data limitations. Most approaches that relate multiple global change drivers to population changes have been based on occurrence or count data alone. We leveraged three long‐term (1995–2019) datasets to develop a coupled integrated population model‐Bayesian population viability analysis (IPM‐BPVA) to project future survival and reproductive success for common loons Gavia immer in northern Wisconsin, USA, by explicitly linking vital rates to changes in climate and land use. The winter North Atlantic Oscillation (NAO), a broad‐scale climate index, immediately preceding the breeding season and annual changes in developed land cover within breeding areas both had strongly negative influences on adult survival. Local summer rainfall was negatively related to fecundity, though this relationship was mediated by a lagged interaction with the winter NAO, suggesting a compensatory population‐level response to climate variability. We compared population viability under 12 future scenarios of annual land‐use change, precipitation and NAO conditions. Under all scenarios, the loon population was expected to decline, yet the steepest declines were projected under positive NAO trends, as anticipated with ongoing climate change. Thus, loons breeding in the northern United States are likely to remain affected by climatic processes occurring thousands of miles away in the North Atlantic during the non‐breeding period of the annual cycle. Our results reveal that climate and land‐use changes are differentially contributing to loon population declines along the southern edge of their breeding range and will continue to do so despite natural compensatory responses. We also demonstrate that concurrent analysis of multiple data types facilitates deeper understanding of the ecological implications of anthropogenic‐induced change occurring at multiple spatial scales. Our modelling approach can be used to project demographic responses of populations to varying environmental conditions while accounting for multiple sources of uncertainty, an increasingly pressing need in the face of unprecedented global change.