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At least 577 records · Page 32Linked to original sources
USGS2024

Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions

Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human-mediated changes to land use and water use. We created a transferable conceptual framework to enable multiscale assessments of state resilience and early warnings of state transitions that can inform strategic restorations and avoid ecosystem collapse. The conceptual framework integrated machine learning predictions with ecosystem state concepts (e.g., state classification, gradients of vulnerability, and recovery potential leading to state transitions) and was devised to investigate possible environmental drivers. As an application of the framework, we generated prediction probabilities of submersed aquatic vegetation (SAV) presence at nearly 10,000 sites in the Upper Mississippi River (United States). Then, we used an interpretability method to explain model predictions to gain insights into possible environmental drivers and thresholds or linear responses of SAV presence and absence. Model accuracy was 89% without spatial bias. Average water depth, suspended solids, substrate, and distance to nearest SAV were the best predictors and likely environmental drivers of SAV habitat suitability. These environmental drivers exhibited nonlinear, threshold-type responses for SAV. All the results are also presented in an online dashboard to explore results at many spatial scales. The habitat suitability model outputs and prediction explanations from many spatial scales (4 m to 400 km of river reach) can inform research and restoration planning.

Conservation Biology↗
USGS2024

Evaluating ecosystem protection and fragmentation of the world's major mountain regions

Conserving mountains is important for protecting biodiversity because they have high beta diversity and endemicity, facilitate species movement, and provide numerous ecosystem benefits for people. Mountains are often thought to have lower levels of human modification and contain more protected area than surrounding lowlands. To examine this, we compared biogeographic attributes of the largest, contiguous, mountainous region on each continent. In each region, we generated detailed ecosystems based on Köppen−Geiger climate regions, ecoregions, and detailed landforms. We quantified anthropogenic fragmentation of these ecosystems based on human modification classes of large wild areas, shared lands, and cities and farms. Human modification for half the mountainous regions approached the global average, and fragmentation reduced the ecological integrity of mountain ecosystems up to 40%. Only one-third of the major mountainous regions currently meet the Kunming-Montreal Global Biodiversity Framework target of 30% coverage for all protected areas; furthermore, the vast majority of ecosystem types present in mountains were underrepresented in protected areas. By measuring ecological integrity and human-caused fragmentation with a detailed representation of mountain ecosystems, our approach facilitates tracking progress toward achieving conservation goals and better informs mountain conservation.

Conservation Biology↗
USGS2024

The potential influence of genome-wide adaptive divergence on conservation translocation outcome in an isolated greater sage-grouse population

Conservation translocations are an important conservation tool commonly employed to augment declining or reestablish extirpated populations. One goal of augmentation is to increase genetic diversity and reduce the risk of inbreeding depression (i.e., genetic rescue). However, introducing individuals from significantly diverged populations risks disrupting coadapted traits and reducing local fitness (i.e., outbreeding depression). Genetic data are increasingly more accessible for wildlife species and can provide unique insight regarding the presence and retention of introduced genetic variation from augmentation as an indicator of effectiveness and adaptive similarity as an indicator of source and recipient population suitability. We used 2 genetic data sets to evaluate augmentation of isolated populations of greater sage-grouse ( Centrocercus urophasianus ) in the northwestern region of the species range (Washington, USA) and to retrospectively evaluate adaptive divergence among source and recipient populations. We developed 2 statistical models for microsatellite data to evaluate augmentation outcomes. We used one model to predict genetic diversity after augmentation and compared these predictions with observations of genetic change. We used the second model to quantify the amount of observed reproduction attributed to transplants (proof of population integration). We also characterized genome-wide adaptive divergence among source and recipient populations. Observed genetic diversity ( H O = 0.65) was higher in the recipient population than predicted had no augmentation occurred ( H O = 0.58) but less than what was predicted by our model ( H O = 0.75). The amount of shared genetic variation between the 2 geographically isolated resident populations increased, which is evidence of periodic gene flow previously assumed to be rare. Among candidate adaptive genes associated with elevated fixation index ( F ST ) (143 genes) or local environmental variables (97 and 157 genes for each genotype–environment association method, respectively), we found clusters of genes with related functions that may influence the ability of transplants to use local resources and navigate unfamiliar environments and their reproductive potential, all possible reasons for low genetic retention from augmentation.

Conservation Biology↗
USGS2024

Reframing wildlife disease management problems with decision analysis

Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade-offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision-making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision-making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision-making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white-nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision-making, including competing objectives, risks, prediction uncertainty, and limited resources.

Conservation Biology↗
USGS2024

The dynamic feasibility of resisting (R), accepting (A), or directing (D) ecological change

Ecological transformations are occurring as a result of climate change, challenging traditional approaches to land management decision-making. The resist–accept–direct (RAD) framework helps managers consider how to respond to this challenge. We examined how the feasibility of the choices to resist, accept, and direct shifts in complex and dynamic ways through time. We considered 4 distinct types of social feasibility: regulatory, financial, public, and organizational. Our commentary is grounded in literature review and the examples that exist but necessarily has speculative elements because empirical evidence on this newly emerging management strategy is scarce. We expect that resist strategies will become less feasible over time as managers encounter situations where resisting is ecologically, by regulation, financially, or publicly not feasible. Similarly, we expect that as regulatory frameworks increasingly permit their use, if costs decrease, and if the public accepts them, managers will increasingly view accept and direct strategies as more viable options than they do at present. Exploring multiple types of feasibility over time allows consideration of both social and ecological trajectories of change in tandem. Our theorizing suggested that deepening the time horizon of decision-making allows one to think carefully about when one should adopt different approaches and how to combine them over time.

Conservation Biology↗
USGS2024

Quantitative support for the benefits of proactive management for wildlife disease control

Finding effective pathogen mitigation strategies is one of the biggest challenges humans face today. In the context of wildlife, emerging infectious diseases have repeatedly caused widespread host morbidity and population declines of numerous taxa. In areas yet unaffected by a pathogen, a proactive management approach has the potential to minimize or prevent host mortality. However, typically critical information on disease dynamics in a novel host system is lacking, empirical evidence on efficacy of management interventions is limited, and there is a lack of validated predictive models. As such, quantitative support for identifying effective management interventions is largely absent, and the opportunity for proactive management is often missed. We considered the potential invasion of the chytrid fungus, Batrachochytrium salamandrivorans (Bsal), whose expected emergence in North America poses a severe threat to hundreds of salamander species in this global salamander biodiversity hotspot. We developed and parameterized a dynamic multistate occupancy model to forecast host and pathogen occurrence, following expected emergence of the pathogen, and evaluated the response of salamander populations to different management scenarios. Our model forecasted that taking no action is expected to be catastrophic to salamander populations. Proactive action was predicted to maximize host occupancy outcomes relative to wait-and-see reactive management, thus providing quantitative support for proactive management opportunities. The eradication of Bsal was unlikely under all the evaluated management options. Contrary to our expectations, even early pathogen detection had little effect on Bsal or host occupancy outcomes. Our results provide quantitative support that proactive management is the optimal strategy for promoting persistence of disease-threatened salamander populations. Our approach fills a critical gap by defining a framework for evaluating management options prior to pathogen invasion and can thus serve as a template for addressing novel disease threats that jeopardize wildlife and human health.

Conservation Biology↗
USGS2024

Advancing at-risk species recovery planning in an era of rapid ecological change with a transparent, flexible, and expert-engaged approach

In the face of unprecedented ecological changes, the conservation community needs strategies to recover species at risk of extinction. On the Island of Maui, we collaborated with species experts and managers to assist with climate-resilient recovery planning for 36 at-risk native plant species by identifying priority areas for the management of recovery populations. To do this, we developed a tailored spatial conservation prioritization (SCP) approach distinguished by its emphasis on transparency, flexibility, and expert (TFE) engagement. Our TFE SCP approach consisted of 2 iterative steps: first, the generation of multiple candidate conservation footprints (i.e., prioritization solutions) with a flexible greedy algorithm that reflects conservation practitioners’ priorities and, second, the selection of an optimal conservation footprint based on the consideration of trade-offs in expert-agreed criteria among footprints. This process maximized buy-in by involving conservation practitioners and experts throughout, from setting goals to reviewing optimization data, defining optimization rules, and designating planning units meaningful to practitioners. We minimized the conservation footprint area necessary to meet recovery goals while incorporating species-specific measures of habitat suitability and climate resilience and retaining species-specific information for guiding recovery efforts. Our approach reduced the overall necessary conservation area by 36%, compared with selecting optimal recovery habitats for each species separately, and still identified high-quality habitat for individual species. Compared with prioritizr (an existing SCP tool), our approach identified a conservation area of equal size but with higher quality habitat. By integrating the strengths of existing techniques in a flexible and transparent design, our approach can address natural resource management constraints and provide outputs suitable for local recovery planning, consequently enhancing engagement and buy-in from conservation practitioners and experts. It demonstrates a step forward in making conservation planning more responsive to real-world complexities and helps reduce barriers to implementation for local conservation practitioners.

Hawaii↗
USGS2025

Integrating data to assess occupancy patterns of an endangered bumble bee

There is growing interest in integrating community science data with structured monitoring data to estimate changes in distribution patterns of imperiled species, including pollinators. However, significant challenges remain in determining how unstructured community science data should be incorporated into formal analyses of species distributions. We developed a dynamic framework for combining community science and structured monitoring data of bumble bees to estimate changes in occupancy of rusty-patched bumble bees ( Bombus affinis ), a federally endangered species in the United States. We applied traditional metapopulation theory and accounted for imperfect detection to estimate site-specific extirpation risk and colonization rates across the known distribution of B. affinis in the Upper Midwest (USA). Despite a 144% increase in presence-only detections from 2017 to 2022, occupancy probabilities and the estimated number of occupied sites remained static or declined slightly across a 4-state region during this period. Our results provide preliminary evidence that the probability of local extirpation risk of B. affinis increased in response to drought, but that effect was tempered with a high number of neighboring patches occupied by B. affinis (i.e., rescue effect). Our framework can be used by managers to track population recovery goals for B. affinis and other bumble bees of conservation concern. In addition, our study highlights the importance of accounting for imperfect detection and addressing spatial sampling biases in bumble bee monitoring efforts, particularly those for which a portion of the monitoring data are generated from community science projects.

Illinois, Iowa, Minnesota, Wisconsin↗
USGS2025

Bright spots for advancing ecological understanding and conservation decision-making

A lot can be learned by studying bright spots—defined as unexpected positive outcomes. In fields like public health, education, and oncology, identifying factors behind bright spots reveals previously unknown drivers of success that can be replicated elsewhere. This concept is being applied in conservation but is hampered by variations in definitions of bright spots and confusion with hotspots—sites with high absolute values of a metric. We developed a framework to clearly define and distinguish between hotspots (e.g., a wetland with high plant diversity) and bright spots (e.g., a biodiverse wetland in a housing development), which outperform conservation expectations. The framework is an iterative cycle, consisting of setting expectations for relative comparisons, classifying systems into bright, dark, hot, and cold categories, and digging deeper to reveal hidden mechanisms and opportunities for intervention. We drew on examples from diverse fields to demonstrate how our framework can generate new knowledge, identify potential interventions, and inform management priorities. Defining conservation and management expectations, often through predictive models, is essential to understanding drivers of success and fosters hypotheses about overlooked factors. Our framework can enhance ecological understanding, guide interventions, and help prioritize actions in conservation and natural resource management.

Conservation Biology↗
USGS2025

Success of restoration strategies in preventing extirpation of 2 critically endangered coral species

An unprecedented marine heatwave in 2023 caused widespread coral bleaching and mortality throughout the Caribbean. In the Florida Keys (USA), 2 foundation species, elkhorn coral ( Acropora palmata ) and staghorn coral ( Acropora cervicornis ), were severely affected. These species have been the primary focus of reef restoration in Florida for decades. Substantial losses of these species occurred in outplanted populations, in ocean-based nurseries, and among remnant wild colonies, leading to uncertainty over their future in the Florida Keys, given recent observed trends in climate conditions. However, the past 2 decades of restoration activity created a community of experts, a network of ocean-based and land-based coral-rearing infrastructure, and 2 independent land-based coral gene banks that prevented regional extirpation and preserved much of the genetic richness of these critically endangered coral species. Without the past decades of effort and the emergency response associated with the 2023 bleaching event, Florida acroporids would largely have been lost. This outcome afforded by the restoration network in Florida demonstrates the value of proactively establishing resources prior to major disturbances. We identified several critical strategies that, in the context of existing climate change, are preventing the extirpation of coral species in Florida, including extending collaborative restoration efforts to solidify a network of trained experts; establishing trust-focused relationships among management agencies and restoration groups; testing direct interventions to reduce light and temperature stress early during thermal anomalies; developing redundant ocean-based and land-based nurseries; and establishing living coral gene banks prior to major threats to prevent the extirpation of coral species.

Florida↗
USGS2026

The collective application of shorebird tracking data to conservation

Addressing urgent conservation issues, such as the drastic declines of North American migratory birds, requires creative, evidence-based, efficient, and collaborative approaches. The abundance of over 50% of monitored North American shorebird populations has declined by over 50% since 1980. To address these declines, we developed a partnership of scientists and practitioners called the Shorebird Science and Conservation Collective (hereafter the collective ). The collective was founded to translate the combined findings of shorebird tracking data into on-the-ground conservation action. With advice from an advisory group, the collective acts as an intermediary whereby dedicated staff collate and analyze data contributions from scientists to support knowledge requests from conservation practitioners. In its first three years, data contributions from 75 organizations include over 7.1 million shorebird observations forming movement paths of 3420 individuals representing 36 species tracked across the Americas and have informed 18 conservation projects spanning education, land and species management, land conservation, and policy requests. Others engaged in translational science from big data could consider similar knowledge-sharing models that prioritize usable data products, foster collaborative engagement between science experts and practitioners, build focused communities around topics or taxonomic groups, and employ a proof-of-concept phase to develop scalable solutions while making progress toward long-term funding to sustain impact. As the volume of scientific data continues to grow, intermediaries, such as the collective, can be vital liaisons to rapidly integrate and interpret research to support conservation action. Dedicated to the memory of Shiloh Schulte and his conservation achievements for shorebirds.

Conservation Biology↗
USGS2025

Effects of ungulate browsing on forest assisted migration strategies to conserve ecosystem function

Forest managers recognize that proactive management strategies, such as forest assisted migration (FAM) of tree species, intended to accelerate the pace of forest adaptation, may be necessary to maintain resilient forests and combat the stressors of climate change. However, the impact of interactions between climate change and ungulate browsers of trees, both of which have profound effects on the landscape, on the success of FAM efforts is unknown. We used a forest landscape model (LANDIS-II) to simulate assisted migration and browsing by ungulate (white-tailed deer [ Odocoileus virginianus ]) populations on a northern Wisconsin (USA) landscape under alternate climate futures. After accounting for effects of FAM strategy and climate change scenario, simulated ungulate browsing reduced species richness and the proportion of the landscape with tree species preferred by browsers and resulted in more of the landscape developing into novel forest communities that supported fewer ecosystem goods and services. Our results suggest that managers may need to select FAM species less preferred by ungulates or use seedling protection measures to mitigate the negative effects of chronically high ungulate populations in efforts to transition future forests to sustain ecosystem goods and services.

Wisconsin↗
USGS2026

Synthesizing beaver coexistence messaging with the capability, opportunity, and motivation behavior model

In the western United States, conservation practitioners are increasingly working with private landowners to restore habitat for North American beavers ( Castor canadensis ) and to use nonlethal mitigation techniques when beavers damage crops and infrastructure. Effective communication is critical for promoting coexistence, yet on-the-ground conservation messaging seldom links to behavior change theories. We conducted 23 semistructured interviews with practitioners to examine the approaches they used to communicate with private landowners about beaver coexistence in Oregon (USA). Although we did not set out to interview practitioners about their messages targeting capability, opportunity, and motivation (elements of the COM-B model of behavior), we used the COM-B model to synthesize the primary dimensions of practitioners’ complex, real-world communication about human–wildlife coexistence. We found that practitioners used multiple communication channels to listen for and respond to landowners’ capability, opportunity, and motivation. They tailored messages to affirm and enhance knowledge and skills, identify and address site-specific and social contexts, and align beaver impacts with landowner goals. Our findings suggest the COM-B model can go beyond guiding audience analysis and behavioral intervention design to help practitioners tailor real-time communication with landowners about coexistence behavior. The model, based on our use of COM-B to analyze existing communication, could be used to provide practitioners with techniques for making sense of their existing communication efforts, for identifying gaps, and for dynamically tailoring their communication.

Oregon↗
USGS2026

Constructed value of information with iterative scoring and parametric uncertainty to identify management-relevant research priorities for a declining raptor species

Constructed value of information (CVoI) is an expert elicitation decision-analytic tool used to prioritize sources of uncertainty based on their potential to improve decision outcomes if resolved. Despite increased application of CVoI, the robustness of CVoI prioritization of sources of uncertainty relative to differences in expert elicitation and scoring methods has not been evaluated. We engaged a group of species experts in a decision-analytic process to elicit uncertainties, framed as alternative hypotheses, about current population declines of the American kestrel ( Falco sparverius ) in the United States. Participants scored 13 hypotheses across 3 CVoI criteria, which are defined as constructed scales. Rather than experts selecting a single score per criterion, we used a likelihood point method to incorporate parametric uncertainty in the scoring process, in which experts were given 100 points to distribute across possible score categories within the criterion-specific constructed scale. Experts provided scores over 2 scoring rounds, with an opportunity to review and discuss initial scores between rounds. We used a Shannon entropy calculation to quantify how evenly participants allotted their points. We used simulation to evaluate the robustness of our prioritization results relative to a scoring method in which participants selected a single score category for each criterion. Participants often spread their points across 2 adjacent scores, reflecting parametric uncertainty. For one third of the hypothesis-scoring round combinations, the prioritization results differed in approximately 50% of simulations. The highest scoring hypotheses related to how the use of artificial versus natural nest cavities affects fecundity or survival, whether winter roosting sites are a limiting factor for population growth, and whether gamebird habitat management may benefit kestrel populations. Our CVoI prioritization framework can be used to develop collaborative research that is directly relevant to a management decision and is an advance in eliciting more representative expert beliefs.

Conservation Biology↗
USGS2026

Scenarios and strategies for future-proofing ecosystem management under climatic novelty

Climate change is driving unprecedented declines in dominant, habitat-forming foundation species across marine and terrestrial ecosystems globally. As climatic novelty becomes the norm, ecosystem reassembly will become increasingly common. Predicting and understanding these transitions, and their implications for future ecosystem functioning, is essential for designing effective forward-looking management strategies. We explored 3 scenarios that describe a range of ecosystem reassembly trajectories following declines in previously dominant habitat-forming taxa: compensation, in which functionally similar subdominant or immigrating taxa maintain ecosystem structure and function; decline, in which no compensation occurs leading to loss of ecosystem structure and function; and transformation, in which the ecosystem present historically can no longer persist and shifts into a fundamentally different ecosystem type with distinct structure and function. This range of potential outcomes highlights the urgent need to assess the ecological feasibility and functional implications of potential management actions. Scientists and managers can work together to quantify local-scale climatic novelty and ecosystem resilience to better predict the most likely reassembly trajectories and identify management interventions that will optimize ecosystem function. This approach would allow for more proactive planning to support persistence of ecosystem structure and function, helping to future-proof ecosystem management in a rapidly changing world.

Conservation Biology↗
USGS2020

Identifying research needs to inform white-nose syndrome management decisions

Ecological understanding of host–pathogen dynamics is the basis for managing wildlife diseases. Since 2008, federal, state, and provincial agencies and tribal and private organizations have collaborated on bat and white‐nose syndrome (WNS) surveillance and monitoring, research, and management programs. Accordingly, scientists and managers have learned a lot about the hosts, pathogen, and dynamics of WNS. However, effective mitigation measures to combat WNS remain elusive. Host–pathogen systems are complex, and identifying ecological research priorities to improve management, choosing among various actions, and deciding when to implement those actions can be challenging. Through a cross‐disciplinary approach, a group of diverse subject matter experts created an influence diagram used to identify uncertainties and prioritize research needs for WNS management. Critical knowledge gaps were identified, particularly with respect to how WNS dynamics and impacts may differ among bat species. We highlight critical uncertainties and identify targets for WNS research. This tool can be used to maximize the likelihood of achieving bat conservation goals within the context and limitations of specific real‐world scenarios.

Conservation Biology↗