It may be possible to avert threatened species declines by protecting refuges that promote species persistence during times of stress. To do this, we need to know where refuges are located, and when and which management actions are required to preserve, enhance or replicate them. Here we use a niche-based perspective to characterise refuges that are either fixed or shifting in location over ecological time scales (hours to centuries). We synthesise current knowledge of the role of fixed and shifting refuges, using threatened species examples where possible, and examine their relationships with stressors including drought, fire, introduced species, disease, and their interactions. Refuges often provide greater cover, water, food availability or protection from predators than other areas within the same landscapes. In many cases, landscape features provide refuge, but refuges can also arise through dynamic and shifting species interactions (e.g., mesopredator suppression). Elucidating the mechanisms by which species benefit from refuges can help guide the creation of new or artificial refuges. Importantly, we also need to recognise when refuges alone are insufficient to halt the decline of species, and where more intensive conservation intervention may be required. We argue that understanding the role of ecological refuges is an important part of strategies to stem further global biodiversity loss.

Persistence through tough times: fixed and shifting refuges in threatened species conservation

Biological invasions have emerged as an eminent feature of global change, with substantial impacts on the environment and human livelihoods. Current research demonstrates that the numbers and impacts of alien species are rising unabatedly. At the same time, we lack a thorough understanding of potential future trajectories for the decades to come. With the recent establishment of comprehensive global databases, it is, for the first time, feasible to develop and quantify future scenarios of biological invasions. Therefore, we propose a conceptual framework for how to develop alien species scenarios for the twenty-first century and how to identify relevant steps and challenges along the way. The concept will be important to inform research, policy, stakeholders, and the general public. Furthermore, we call for the scientific community to join forces and to operationalize the framework for scenarios and models of biological invasions to develop an important baseline for understanding and managing future biological invasions.

/pdf/a-framework-for-global-twenty-first-century-scenarios-and-57p8g3l5xj.pdf

A Framework for Global Twenty-First Century Scenarios and Models of Biological Invasions.

Climate change is a major threat to global biodiversity, and its impacts can act synergistically to heighten the severity of other threats. Most research on projecting species range shifts under climate change has not been translated to informing priority management strategies on the ground. We develop a prioritization framework to assess strategies for managing threats to biodiversity under climate change and apply it to the management of invasive animal species across one-sixth of the Australian continent, the Lake Eyre Basin. We collected information from key stakeholders and experts on the impacts of invasive animals on 148 of the region's most threatened species and 11 potential strategies. Assisted by models of current distributions of threatened species and their projected distributions, experts estimated the cost, feasibility, and potential benefits of each strategy for improving the persistence of threatened species with and without climate change. We discover that the relative cost-effectiveness of invasive animal control strategies is robust to climate change, with the management of feral pigs being the highest priority for conserving threatened species overall. Complementary sets of strategies to protect as many threatened species as possible under limited budgets change when climate change is considered, with additional strategies required to avoid impending extinctions from the region. Overall, we find that the ranking of strategies by cost-effectiveness was relatively unaffected by including climate change into decision-making, even though the benefits of the strategies were lower. Future climate conditions and impacts on range shifts become most important to consider when designing comprehensive management plans for the control of invasive animals under limited budgets to maximize the number of threatened species that can be protected.

Priority threat management of invasive animals to protect biodiversity under climate change

Paeonia (Paeoniaceae), a culturally and economically important plant genus, has an isolated taxonomy while the evolution of this genus is unclear. A plant species endemic to southwest China, Paeonia mairei is precious germplasm for evolution-related research and cultivar improvement, and its conservation is urgent. However, little is known about its patterns of habitat distribution and responses to climate change. Using 98 occurrence sites and data of 19 bioclimatic variables, we conducted principal component analysis and hierarchical cluster analysis to delineate different climatic populations. Maximum entropy algorithm (MaxEnt) was applied to each population to evaluate the importance of environmental variables in shaping their distribution, and to identify distribution shifts under different climate change scenarios. We also applied MaxEnt to all of the P. mairei presence sites (P_Whole) to evaluate the need to construct separate species distribution models for separate populations rather than a common approach by treating them as a whole. Our results show that local adaptation exists within the distribution range of P. mairei and that all presence sites were clustered into a western population (P_West) and an eastern population (P_East). Two variables (precipitation of the driest month and temperature seasonality) are important when shaping the distribution of P_West, and another two variables (mean diurnal range and mean temperature of the wettest quarter) are important for P_East. Both populations are likely to shift upward under climate change, while P_East may lose most current suitable areas while P_West may not. P_Whole produced a narrower area compared to the combination of P_West and P_East but a suitable area (south Chongqing) may have been missed in the prediction. Accordingly, a population-based approach in constructing a species distribution model is needed to provide a detailed appreciation of the distribution of P. mairei, allowing for a population-based conservation strategy. In this case, it could include assisted migration to new and suitable distribution areas for P_West and in situ conservation in high elevation regions for P_East. The results of our study could be a useful reference for implementing the long-term conservation and further research of P. mairei.

Incorporating Local Adaptation Into Species Distribution Modeling of Paeonia mairei, an Endemic Plant to China

Biodiversity is being lost at an alarming rate across the globe, with extinction rates up to a hundred times greater than historical norms. Climate change will only exacerbate this crisis. The rapid pace of projected climate change is set to push birds to seek new locations, drastically reshuffling the avian communities of North America. In an emerging climate crisis, effective conservation requires both adaptation and mitigation to improve the resilience of species. However, the pledged reductions in greenhouse gas emissions outlined in the Paris Agreement framework would still lead to a 3.2°C or greater increase in global mean temperature by the end of this century. In this study, we use big data analytics to develop species distribution models and assess the vulnerability of 604 North American birds to multiple climate change scenarios. We assess how climate change mitigation can affect the number of species vulnerable to climate change, as well as the species and locations at risk if emissions continue unchecked. Our results indicate that over two-thirds of North American birds are moderately or highly vulnerable to climate change under a 3.0°C global warming scenario. Of these climate-vulnerable species, 76% would have reduced vulnerability and 38% of those would be considered non-vulnerable if warming were stabilized at 1.5°C. Thus, the current pledge in greenhouse gas reductions set by the Paris Agreement is inadequate to reduce vulnerability to birds. Additionally, if climate change proceeds on its current trajectory, arctic birds, waterbirds and boreal and western forest birds will be highly vulnerable to climate change; groups that are currently not considered of high conservation concern. Thus, there is an urgent need for both aggressive policies to mitigate emissions and focused conservation adaptation actions to protect birds and the places they need in a changing climate.

North American birds require mitigation and adaptation to reduce vulnerability to climate change

The need to proactively manage landscapes and species to aid their adaptation to climate change is widely acknowledged. Current approaches to prioritizing investment in species conservation generally rely on correlative models, which predict the likely fate of species under different climate change scenarios. Yet, while model statistics can be improved by refining modeling techniques, gaps remain in understanding the relationship between model performance and ecological reality. To investigate this, we compared standard correlative species distribution models to highly accurate, fine-scale, distribution models. We critically assessed the ecological realism of each species' model, using expert knowledge of the geography and habitat in the study area and the biology of the study species. Using interactive software and an iterative vetting with experts, we identified seven general principles that explain why the distribution modeling under- or overestimated habitat suitability, under both current and predicted future climates. Importantly, we found that, while temperature estimates can be dramatically improved through better climate downscaling, many models still inaccurately reflected moisture availability. Furthermore, the correlative models did not account for biotic factors, such as disease or competitor species, and were unable to account for the likely presence of micro refugia. Under-performing current models resulted in widely divergent future projections of species' distributions. Expert vetting identified regions that were likely to contain micro refugia, even where the fine-scale future projections of species distributions predicted population losses. Based on the results, we identify four priority conservation actions required for more effective climate change adaptation responses. This approach to improving the ecological realism of correlative models to understand climate change impacts on species can be applied broadly to improve the evidence base underpinning management responses.

https://espace.library.uq.edu.au/view/UQ:c1072c8/UQc1072c8_OA.pdf

Beyond the model: expert knowledge improves predictions of species' fates under climate change.

https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/bes2.1522

Travis Sydes

Papers

Beyond the model: expert knowledge improves predictions of species' fates under climate change.

Beyond the Model: Expert Knowledge Improves Predictions of Species’ Fates under Climate Change