Species Status Assessment Research Articles

Genetic network analysis uncovers spatial variation in diversity and connectivity of a species presenting a continuous distribution

The conservation of genetic diversity and connectivity is essential for the long-term persistence and adaptive ability of a species. Recent calls have been made for the inclusion of genetic diversity and differentiation measures in the assessment, management, and conservation of species. However, the literature often lacks direction on how to do so for species with continuous distributions or no distinct breaks in genetic connectivity. There are many considerations to overcome when investigating genetic diversity and connectivity of such species. We combine multiple genetic network methodologies with more traditional population genetic analyses within a single framework to address the challenges of investigating population structure and quantifying variation in genetic diversity and connectivity of wide-ranging species with continuous distributions. We demonstrate the efficacy and applicability of our framework through a study on woodland caribou (Rangifer tarandus) occupying the boreal forest of Canada; a species of significant conservation concern. The dataset consisted of 4911 unique individuals genotyped at 9 microsatellite loci, which were subsequently partitioned into 103 spatial nodes to create a population-based genetic network. The Walktrap community detection algorithm was used to detect hierarchical population genetic structure within the study area and node-based network metrics such as mean inverse edge weight and clustering coefficient were used to quantify the variation in genetic connectivity across the range. Lastly, genetic diversity was assessed by calculating allelic richness and heterozygosity of the nodes making up the network. The community detection analysis identified two communities at the coarsest scale to nine communities at the optimal partition. A strong pattern of Isolation by Distance (IBD) was found across the range at multiple scales. Furthermore, signs of genetic erosion along the study area’s southern boundaries were depicted by nodes presenting low genetic diversity and low centrality values. These results are important to the species status assessments in providing previously unavailable information on connectivity and diversity within and beyond the current local population units used in management. Our approach to quantify the patterns and extent of connectivity across the boreal range is comprehensive and could easily be adapted to other species. The results are robust and provide a solid foundation for the continued monitoring and recovery of the species.

Modeling range dynamics through time to inform conservation planning: Canada lynx in the contiguous United States

Assessment of historical species range limits is rarely conducted. Yet, understanding where species were distributed in the past is fundamentally important for making informed policy decisions, including assessing species status and recovery in present day and in the context of future environmental change. Here, we provide a case study using a threatened species, Canada lynx, which is the subject of recent conservation policy debate and species recovery planning. We use species distribution models (SDM), combined with historic observations of lynx, to estimate historic southern range limits for the species at year 1900. We then forward project our SDM to estimate lynx vulnerability and likely spatial pattern of range retraction in the future. Our analysis reveals that substantial suitable lynx habitat existed in the past beyond their current range in the contiguous USA, and many extra-limital observations fell within this habitat suggesting relatively broad historic occupancy. This finding implies substantial lynx range contraction over the 20th century and is contrary to recent species status assessment. Moreover, some areas of the contiguous USA that may remain resilient to climate change for lynx in the future, fall outside current species range limits but potentially within historically occupied areas. Our results indicate that future recovery efforts for lynx should be informed by this new evidence regarding species range dynamics through time, including investigating suitability of sites outside current range limits. More broadly, our findings highlight the need for conservation planning and species recovery efforts to consider historical range limits whenever possible.

Indigenous knowledge and species assessment for the Alexander Archipelago wolf: successes, challenges, and lessons learned

AbstractThe United States Fish and Wildlife Service in Alaska, USA, conducted a species status assessment for a petition to list the Alexander Archipelago wolf (Canis lupus ligoni) under the Endangered Species Act in 2020‐2022. This federal undertaking could not be adequately prepared without including the knowledge of Indigenous People who have a deep cultural connection with the subspecies. Our objective is to communicate the authoritative expertise and voice of the Indigenous People who partnered on the project by demonstrating how their knowledge contributed to the species status assessment. The Indigenous knowledge applied in the assessment is the cultural and intellectual property of those who have shared it. We employed rapid appraisal research to expeditiously develop a preliminary and qualitative understanding of Indigenous People's cultural and ecological knowledge of Alexander Archipelago wolves. We used semi‐directed interviewing and inductive coding from grounded theory for text analysis. Indigenous knowledge contributed to the agency's understanding of the Alexander Archipelago wolf in Southeast Alaska and helped the agency with their classification decision. Indigenous research partners explained the rich cultural significance and position of wolves in Tlingit society and described human–wolf relationships and ecological interactions. The agency used a single‐species assessment approach based in species ecology and conservation biology, whereas the Indigenous wolf experts applied a multi‐species, community ecology approach based in a sociocultural context of balance and respect. The Indigenous wolf experts successfully addressed knowledge gaps identified by the agency. The partners were challenged by a short regulatory timeframe that did not allow for comprehensive study of Indigenous knowledge and constrained review and feedback by Indigenous experts. The United States Fish and Wildlife Service learned that its assessment framework was not designed to account for an Indigenous worldview. To level the playing field, the agency and Indigenous experts should discuss how to co‐develop an assessment framework that equitably applies both perspectives.

Effects of drought, invasive species, and habitat loss on future extinction risk of two species of imperiled freshwater turtle

While predicting species status into the future is inherently uncertain, it is necessary to properly inform conservation decision-making. Using a triple loop stochastic simulation model with a population viability analysis, we projected populations of the northwestern and southwestern pond turtle (Actinemys marmorata and Actinemys pallida, respectively) to the end of the century. We integrated the future trajectories and demographic or population-level effects of three primary threats (drought, invasive bullfrogs, and habitat loss) into the predictive model. Extinction risk of both species increased into the future, with projected widespread declines in abundance and a consistent, negative population growth. By the end of the century, mean probability of extinction was 50 % for the northwestern pond turtle and 75 % for the southwestern pond turtle. The northwestern pond turtle exhibited a latitudinal trend, with southern population units at greater risk of extinction. The population growth rate of the northwestern pond turtle was sensitive to the threat of invasive bullfrogs, whereas drought most strongly influenced southwestern pond turtle growth rates. Future drought conditions will likely be more stochastic than modeled here, where projection methods were limited by the scale and congruency of drought information in pond turtle studies. The habitat loss threat was negligible for both species, although it is likely underestimated due to lack of relevant information on both its future trajectory and effect on vital rates. This work served as decision support science for the Species Status Assessment of the two species, and ultimately, the listing decision under the U.S. Endangered Species Act.

A field-validated ensemble species distribution model of Eriogonum pelinophilum, an endangered subshrub in Colorado, USA.

Understanding the suitable habitat of endangered species is crucial for agencies such as the Bureau of Land Management to plan management and conservation. However, few species distribution models are directly validated, potentially limiting their application in management. In preparation for a Species Status Assessment of clay-loving wild buckwheat (Eriogonum pelinophilum), an endangered subshrub found in southwest Colorado, we ran a series of species distribution models to estimate the species' potential occupied habitat and validated these models in the field. A 1-meter resolution digital elevation model derived from LiDAR and a high-resolution geology mapping helped identify biologically relevant characteristics of the species' habitat. We employed a weighted ensemble model based on two Random Forest and one Boosted Regression Tree model, and discrimination performance of the ensemble model was high (AUC-PR = 0.793). We then conducted a systematic field survey of model habitat suitability predictions, during which we discovered 55 new subpopulations of the species and demonstrated that new species observations were strongly associated with model predictions (p < .0001, Cliff's delta = 0.575). We further refined our original models by incorporating the additional species occurrences collected in the field survey, a new explanatory variable, and a more diverse set of models. These iterative changes marginally improved performance of the ensemble model (AUC-PR = 0.825). Direct validation of species distribution models is extremely rare, and our field survey provides strong validation of our model results. This helps increase confidence to utilize predictions in planning. The final model predictions greatly improve the Bureau of Land Management's understanding of the species' habitat and increase our ability to consider potential habitat in planning land use activities such as road development and travel management.

Prioritization of Species Status Assessments for Decision Support

Species status assessments are used to inform U.S. Fish and Wildlife Service (USFWS) decision making for Endangered Species Act (ESA) classification decisions, recovery planning, and more. The large number of species that require assessment and uncertainty in the data available impede the process of assigning and completing the assessments, which makes creating a multiyear work plan extremely difficult. An optimized triaging system that maximizes the use of the best available information while managing the complex ESA workload and meeting deadlines is necessary. We used a structured decision-making framework to approach the problem with the goal of creating a prioritization tool that would be effective at scheduling assessments, given the best information available and priorities of the USFWS. We collected data on the species awaiting assessment and developed a value function that incorporates existing deadlines, taxonomic uncertainty, controversy of the species, and population and habitat data availability and quality. We used a constrained linear optimization algorithm to maximize the value function and ensure that workload capacity was not exceeded. A comparison of model scenarios indicates that imposed deadlines impact the model more than capacity constraints. Additionally, differential weighting of the metrics significantly affected the outcome of the model. In the future, elicitation of metric weights should be done routinely before the model is run for use in official planning to ensure alignment with current USFWS priorities. Output from this optimization can be used to inform a five-year work plan, allocate resources, and discuss workforce decisions. History: This paper has been accepted for the Decision Analysis Special Issue on Decision Analysis to Advance Environmental Sustainability. Funding: This work was funded via an inter-agency agreement between the USFWS and the USGS and subsequently by a Research Work Order contract between the USGS and the University of Florida [Grant G21AC00016].

Utilizing herbarium specimens to assist with the listing of rare plants

Funding for rare plant conservation is limited. In addition, many aspects of the biology and ecology of rare plants are unknown. Therefore, low-cost data generation approaches to fill these gaps should be pursued. Herbarium specimens can be used as a low-cost alternative to learn about the basic biology and ecology of rare plant species. The information provided on herbarium labels has dramatically increased in recent decades to include precise locality (i.e., latitude/longitude), exact dates, habitat, associated species, and substrate. In addition, herbarium specimens are being digitized and the resulting images and data are available via clearinghouses such as GBIF and SEINet. Already, herbarium specimens of rare plants have been used to develop habitat suitability models, predict range shifts, and assess changes in flower phenology due to climate change. Herbarium specimens can also provide a wealth of information about the reproductive biology and biotic interactions of rare plants. In this paper, we will demonstrate how this information can be accessed and present a practical application for using this information to populate an important federal listing document in the USA, Species Status Assessments (SSA). We will provide examples from the literature, as well as case studies from our own research, to demonstrate how this information can be collected from herbarium specimens and how and where to incorporate this information into SSAs. More generally, data gleaned from herbarium specimens can become part of a conservationist’s tool kit to further our knowledge of past, present, and future trends for rare plants. Additional knowledge of a species’ biology and ecology allows land managers and conservationists to make more informed decisions and allows for greater protection of listed species.

User Engagement Testing with a Pilot Decision Support Tool Aimed to Support Species Managers

Abstract Species status assessments (SSAs) are required for endangered species by the U.S. Fish and Wildlife Service and focus on the resiliency, redundancy, and representation of endangered species. SSAs must include climate information, because climate is a factor that will impact species in the future. To aid in the inclusion of climate information, a decision support system (DSS) entitled Climate Analysis and Visualization for the Assessment of Species Status (CAnVAS) was developed by the State Climate Office of North Carolina using a coproduction approach. In this study, users viewed a mock-up version of the CAnVAS interface displaying a sample layout of future projections for three key climate variables (average precipitation, average maximum temperature, and occurrence of maximum temperature) at a location of interest. This assessment of the pilot version of the CAnVAS DSS was the first step in refining CAnVAS for species-manager use. This research analyzed the differences in usability between two pilot versions of the CAnVAS DSS through eye tracking and subsequent interviews with novice users. The two pilot versions of CAnVAS differed in the way data were displayed on graphs and the color ramps used on regional maps. We found that graphically displaying temporal climate information through box-and-whisker plots and spatially through a sequential color ramp from white to purple were more effective than alternative displays at communicating climate information on endangered species. The results of this research will be used to further develop the CAnVAS DSS tool for future implementation. Significance Statement A decision support system was developed for U.S. Fish and Wildlife Service biologists to incorporate more climate information in species status assessments for endangered species. This tool was tested through eye tracking and interviews with a novice undergraduate student sample to best refine the tool for stakeholder use. This work was able to discover that graphically displaying data in box-and-whisker format and spatially displaying data with a sequential color scheme of white to purple was best for usability purposes. The authors provide these recommendations for those who are producing usable products.

Using predictions from multiple anthropogenic threats to estimate future population persistence of an imperiled species

Imperiled species face numerous and diverse anthropogenic threats to their persistence, and wildlife managers charged with making conservation decisions benefit from a sound understanding of how populations, species, and ecosystems will respond to future changes in threats to biodiversity. In southeastern North America, the gopher tortoise ( Gopherus polyphemus ) is a keystone species in upland ecosystems; however, tortoise populations have declined strongly over the last century, and the species is a candidate for increased protection by the United States federal government under the Endangered Species Act (ESA). Here, we sought to support conservation decision making for G. polyphemus by developing a spatially-explicit predictive population model that linked four anthropogenic threats (climate warming, sea-level rise, urbanization, habitat degradation) to demographic vital rates and used the model to estimate future changes in the number of individuals, populations, and metapopulations across the species’ range. Using recent survey data, we projected 457 populations for 80 years into the future under scenarios varying in threat magnitude, management magnitude, and demographic uncertainty. Population projections predicted that the number of individuals, populations, and metapopulations would decline among all simulated scenarios in the next 80 years. Model predictions were more sensitive to variation in adult survival and immigration rates than to variation in threat magnitude. A scenario with decreased habitat management and threat effects from climate warming, sea-level rise, and urbanization predicted geographic variation in persistence probabilities for populations that might result in decreased genetic representation across the species' range. Our results can be used to support conservation listing decisions for the gopher tortoise as part of its federal Species Status Assessment and provide an analytical framework for how to link diverse threats to geographically-varying demographic rates during population viability analyses for wide-ranging imperiled species around the world.

A Review of Recovery Plan Criteria for Threatened and Endangered Fish Taxa Managed by the U.S. Fish and Wildlife Service

Endangered Species Act recovery plans must meet legal requirements (1) to provide recovery time and cost estimates, (2) to set objective and measurable delisting criteria, and (3) to address the five factors that are considered when listing or delisting a species. These five factors include: threats to habitat or range, whether or not a species is subject to overutilization, presence of disease, existence of regulatory mechanisms outside of federal protection (i.e., the states), and if there are other natural or anthropogenic factors impacting continued existence. We reviewed recovery plans for fish listed under the Endangered Species Act and managed by the Fish and Wildlife Service (USFWS) to determine how many meet these requirements. Of 105 recovery plans for fish taxa managed by the USFWS, 52% of plans estimated time to recovery, 44% plans estimated cost of recovery, and 61% plans provided quantitative recovery criteria. Only one‐third of these recovery plans specifically addressed the five delisting factors, which include taxa‐specific threats to species persistence. The USFWS is using the species status assessment (SSA) framework to inform species management, with 15 listed species that have a completed SSA. As SSAs are completed to inform objective and measurable criteria, recovery plans could be revised or amended at the time of 5‐year reviews, especially for taxa whose time and cost estimates for recovery have been surpassed.

Demographic Modeling Refines Assessment of Three Populations of a Long-Lived Threatened Plant

Structured demographic models can be valuable for assessing the status of at-risk plant species and for guiding efforts to protect and manage them, but they may be infrequently employed in assessments of species of conservation concern because they require data that are not often available to those charged with management. We constructed and analyzed matrix projection models for three populations of the threatened perennial plant species Euphorbia telephioides to reevaluate a prior assessment of stable status and to compare the conclusions of models based on different amounts of data. In contrast to the prior assessment, all of our models predicted population decline for all three populations. Projected growth rates were similar for models based on sparse sampling and those based on a larger more representative sample of individuals, but the models supported contrasting patterns of the sensitivity of population growth rate to individual demographic transitions. Models based on more complete data supported greater elasticity of growth rate to the demographic fates of small non-flowering plants, which had among the lowest elasticity values for models based on more sparse data. We conclude that even models based on limited data can be useful to species status assessments, but that more complete data may be necessary to identify targets for effective management.

Evaluating the effect of expert elicitation techniques on population status assessment in the face of large uncertainty

Population projection models are important tools for conservation and management. They are often used for population status assessments, for threat analyses, and to predict the consequences of conservation actions. Although conservation decisions should be informed by science, critical decisions are often made with very little information to support decision-making. Conversely, postponing decisions until better information is available may reduce the benefit of a conservation decision. When empirical data are limited or lacking, expert elicitation can be used to supplement existing data and inform model parameter estimates. The use of rigorous techniques for expert elicitation that account for uncertainty can improve the quality of the expert elicited values and therefore the accuracy of the projection models. One recurring challenge for summarizing expert elicited values is how to aggregate them. Here, we illustrate a process for population status assessment using a combination of expert elicitation and data from the ecological literature. We discuss the importance of considering various aggregation techniques, and illustrate this process using matrix population models for the wood turtle (Glyptemys insculpta) to assist U.S. Fish and Wildlife Service decision-makers with their Species Status Assessment. We compare estimates of population growth using data from the ecological literature and four alternative aggregation techniques for the expert-elicited values. The estimate of population growth rate based on estimates from the literature (λmean = 0.952, 95% CI: 0.87–1.01) could not be used to unequivocally reject the hypotheses of a rapidly declining population nor the hypothesis of a stable, or even slightly growing population, whereas our results for the expert-elicited estimates supported the hypothesis that the wood turtle population will decline over time. Our results showed that the aggregation techniques used had an impact on model estimates, suggesting that the choice of techniques should be carefully considered. We discuss the benefits and limitations associated with each method and their relevance to the population status assessment. We note a difference in the temporal scope or inference between the literature-based estimates that provided insights about historical changes, whereas the expert-based estimates were forward looking. Therefore, conducting an expert-elicitation in addition to using parameter estimates from the literature improved our understanding of our species of interest.

High dietary and habitat diversity indicate generalist behaviors of northern bog lemmings Synaptomys borealis in Alaska, USA

The northern bog lemming Synaptomys borealis (NBL) is a rare small mammal that is undergoing a federal Species Status Assessment (SSA) under the US Endangered Species Act. Despite a wide North American distribution, very little is known about NBL dietary or habitat needs, both of which are germane to the resiliency of this species to climate change. To quantify diet composition of NBL in Alaska, we used DNA metabarcoding from 59 archived specimens to describe the taxonomic richness and relative abundance of foods in recent diets. DNA analyses revealed a broad diet composed of at least 110 families and 92 genera of bryophytes (mosses and liverworts), graminoids, fungi, forbs, and woody shrubs. Nine bryophyte genera and Carex sedges composed the largest portions of NBL diets. To quantify habitat preference, we intersected 467 georeferenced occurrence records of NBL in Alaska with remotely sensed land cover classes and used a compositional analysis framework that accounts for the relative abundance of land cover types. We did not detect significant habitat preferences for specific land cover types, although NBL frequently occurred in evergreen forest, woody wetlands, and adjacent to water. Our research highlights the importance of bryophytes, among a high diversity of dietary components, and describes NBL as boreal habitat generalists. Results will inform the current federal SSA by quantifying the extent to which ecological constraints are likely to affect NBL in a rapidly changing boreal environment.

A Phylogeographic Contact Zone for Arctic Grayling in Alberta, Canada

AbstractArctic Grayling Thymallus arcticus are a salmonid with a Holarctic distribution, extending from northeastern Eurasia through northwestern North America. Throughout their range, Arctic Grayling face a number of threats, including angling mortality, habitat fragmentation and loss, and climate change. Thus, there is a need to protect the species through targeted management actions. Genetic information can assist in determining the appropriate scale for these actions through the description of designatable units. Here we use newly collected mitochondrial DNA sequence data to assess the phylogeographic structure of Arctic Grayling in Alberta, Canada, and link these with previously collected mitochondrial and microsatellite data to determine how many designatable units may exist across Canada. Our assessment of 831 base pairs of sequence data in 96 individuals found two deeply divergent lineages in Alberta. When combined with 22 previously collected sequences, our results highlight that Alberta is a contact zone for the observed lineages of Arctic Grayling in North America. A reassessment of nine microsatellites that were genotyped in 1,116 individuals further highlighted interbasin divergence, likely the result of historical processes. Given the divergence and geographic distribution of the genetic diversity, Arctic Grayling in Canada merit consideration for separate designatable units in future species status assessments and management plans. Continuing research should attempt to expand sampling geographically (e.g., regions east of Great Slave Lake and along the Arctic coastline) to clarify possible colonization routes and add to or synthesize the work on Arctic Grayling behavior, morphology, and life history to address the limited understanding of local adaptions within this species.

Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide

Despite its successes, the U.S. Endangered Species Act (ESA) has proven challenging to implement due to funding limitations, workload backlog, and other problems. As threats to species survival intensify and as more species come under threat, the need for the ESA and similar conservation laws and policies in other countries to function efficiently has grown. Attempts by the U.S. Fish and Wildlife Service (USFWS) to streamline ESA decisions include multispecies recovery plans and habitat conservation plans. We address species status assessment (SSA), a USFWS process to inform ESA decisions from listing to recovery, within the context of multispecies and ecosystem planning. Although existing SSAs have a single‐species focus, ecosystem‐based research can efficiently inform multiple SSAs within a region and provide a foundation for transition to multispecies SSAs in the future. We considered at‐risk grassland species and ecosystems within the southeastern United States, where a disproportionate number of rare and endemic species are associated with grasslands. To initiate our ecosystem‐based approach, we used a combined literature‐based and structured World Café workshop format to identify science needs for SSAs. Discussions concentrated on 5 categories of threats to grassland species and ecosystems, consistent with recommendations to make shared threats a focus of planning under the ESA: (1) habitat loss, fragmentation, and disruption of functional connectivity; (2) climate change; (3) altered disturbance regimes; (4) invasive species; and (5) localized impacts. For each threat, workshop participants identified science and information needs, including database availability, research priorities, and modeling and mapping needs. Grouping species by habitat and shared threats can make the SSA process and other planning processes for conservation of at‐risk species worldwide more efficient and useful. We found a combination of literature review and structured discussion effective for identifying the scientific information and analysis needed to support the development of multiple SSAs. Article impact statement: Species status assessments can be improved by an ecosystem‐based approach that groups imperiled species by shared habitats and threats.

The scope and severity of white-nose syndrome on hibernating bats in North America.

Assessing the scope and severity of threats is necessary for evaluating impacts on populations to inform conservation planning. Quantitative threat assessment often requires monitoring programs that provide reliable data over relevant spatial and temporal scales, yet such programs can be difficult to justify until there is an apparent stressor. Leveraging efforts of wildlife management agencies to record winter counts of hibernating bats, we collated data for 5 species from over 200 sites across 27 U.S. states and 2 Canadian provinces from 1995 to 2018 to determine the impact of white‐nose syndrome (WNS), a deadly disease of hibernating bats. We estimated declines of winter counts of bat colonies at sites where the invasive fungus that causes WNS (Pseudogymnoascus destructans) had been detected to assess the threat impact of WNS. Three species undergoing species status assessment by the U.S. Fish and Wildlife Service (Myotis septentrionalis, Myotis lucifugus, and Perimyotis subflavus) declined by more than 90%, which warrants classifying the severity of the WNS threat as extreme based on criteria used by NatureServe. The scope of the WNS threat as defined by NatureServe criteria was large (36% of Myotis lucifugus range) to pervasive (79% of Myotis septentrionalis range) for these species. Declines for 2 other species (Myotis sodalis and Eptesicus fuscus) were less severe but still qualified as moderate to serious based on NatureServe criteria. Data‐sharing across jurisdictions provided a comprehensive evaluation of scope and severity of the threat of WNS and indicated regional differences that can inform response efforts at international, national, and state or provincial jurisdictions. We assessed the threat impact of an emerging infectious disease by uniting monitoring efforts across jurisdictional boundaries and demonstrated the importance of coordinated monitoring programs, such as the North American Bat Monitoring Program (NABat), for data‐driven conservation assessments and planning.

Genetic data disagree with described subspecies ranges for Seaside Sparrows on the Atlantic coast

AbstractSeaside Sparrows (Ammospiza maritima) are tidal salt marsh endemic passerines found along the Atlantic and Gulf coasts of North America. Currently, there are 7 described subspecies, and “MacGillivray’s” Seaside Sparrow (A. m. macgillivraii) is the name given to the Atlantic coast subspecies breeding from North Carolina to northern Florida. In 2019 the US Fish and Wildlife Service received a petition to list this subspecies under the Endangered Species Act due to shrinking populations and loss of marsh habitat, which necessitated a Species Status Assessment. As part of the Species Status Assessment, we analyzed genetic (microsatellite and mitochondria) data from 464 Seaside Sparrows from Connecticut to Florida, USA, to infer population connectivity (gene flow) among Atlantic coast populations, and to assess the concordance of population genetic data with the putative ranges of the subspecies. Bayesian cluster analysis (program Structure) indicates three genetically distinct population segments: (1) Florida + Georgia, (2) Charleston, South Carolina, and (3) North Carolina to Connecticut. The population in Charleston, South Carolina was the most strongly differentiated based on microsatellite data, and harbored a unique mitochondrial haplotype not shared by other sampling locations, possibly reflecting long-standing isolation. Our results indicate population genetic discordance with currently described ranges of the subspecies of Seaside Sparrow and provide grounds for the consideration of separate management plans for the three populations.

Embracing Ensemble Species Distribution Models to Inform At-Risk Species Status Assessments

AbstractConservation planning depends on reliable information regarding the geographic distribution of species. However, our knowledge of species' distributions is often incomplete, especially when species are cryptic, difficult to survey, or rare. The use of species distribution models has increased in recent years and proven a valuable tool to evaluate habitat suitability for species. However, practitioners have yet to fully adopt the potential of species distribution models to inform conservation efforts for information-limited species. Here, we describe a species distribution modeling approach for at-risk species that could better inform U.S. Fish and Wildlife Service's species status assessments and help facilitate conservation decisions. We applied four modeling techniques (generalized additive, maximum entropy, generalized boosted, and weighted ensemble) to occurrence data for four at-risk species proposed for listing under the U.S. Endangered Species Act (Papaipema eryngii, Macbridea caroliniana, Scutellaria ocmulgee, and Balduina atropurpurea) in the Southeastern United States. The use of ensemble models reduced uncertainty caused by differences among modeling techniques, with a consequent improvement of predictive accuracy of fitted models. Incorporating an ensemble modeling approach into species status assessments and similar frameworks is likely to benefit survey efforts, inform recovery activities, and provide more robust status assessments for at-risk species. We emphasize that co-producing species distribution models in close collaboration with species experts has the potential to provide better calibration data and model refinements, which could ultimately improve reliance and use of model outputs.

Mapping shifts in spatial synchrony in grassland birds to inform conservation planning.

Spatial synchrony, defined as the correlated fluctuations in abundance of spatially separated populations, can be caused by regional fluctuations in natural and anthropogenic environmental population drivers. Investigations into the geography of synchrony can provide useful insight to inform conservation planning efforts by revealing regions of common population drivers and metapopulation extinction vulnerability. We examined the geography of spatial synchrony and decadal changes in these patterns for grassland birds in the United States and Canada, which are experiencing widespread and persistent population declines. We used Bayesian hierarchical models and over 50 years of abundance data from the North American Breeding Bird Survey to generate population indices within a 2° latitude by 2° longitude grid. We computed and mapped mean local spatial synchrony for each cell (mean detrended correlation of the index among neighboring cells), along with associated uncertainty, for 19 species in 2, 26-year periods, 1968-1993 and 1994-2019. Grassland birds were predicted to increase in spatial synchrony where agricultural intensification, climate change, or interactions between the 2 increased. We found no evidence of an overall increase in synchrony among grassland bird species. However, based on the geography of these changes, there was considerable spatial heterogeneity within species. Averaging across species, we identified clusters of increasing spatial synchrony in the Prairie Pothole and Shortgrass Prairie regions and a region of decreasing spatial synchrony in the eastern United States. Our approach has the potential to inform continental-scale conservation planning by adding an additional layer of relevant information to species status assessments and spatial prioritization of policy and management actions. Our work adds to a growing literature suggesting that global change may result in shifting patterns of spatial synchrony in population dynamics across taxa with broad implications for biodiversity conservation.

Linking monitoring and data analysis to predictions and decisions for the range-wide eastern black rail status assessment

The US Fish and Wildlife Service (USFWS) has initiated a re-envisioned approach for providing decision makers with the best available science and synthesis of that information, called the Species Status Assessment (SSA), for endangered species decision making. The SSA report is a descriptive document that provides decision makers with an assessment of the current and predicted future status of a species. These analyses support all manner of decisions under the US Endangered Species Act, such as listing, reclassification, and recovery planning. Novel scientific analysis and predictive modeling in SSAs could be an important part of rooting conservation decisions in current data and cutting edge analytical and modeling techniques. Here, we describe a novel analysis of available data to assess the current condition of eastern black rail Laterallus jamaicensis jamaicensis across its range in a dynamic occupancy analysis. We used the results of the analysis to develop a site occupancy projection model where the model parameters (initial occupancy, site persistence, colonization) were linked to environmental covariates, such as land management and land cover change (sea-level rise, development, etc.). We used the projection model to predict future status under multiple sea-level rise and habitat management scenarios. Occupancy probability and site colonization were low in all analysis units, and site persistence was also low, suggesting low resiliency and redundancy currently. Extinction probability was high for all analysis units in all simulated scenarios except one with significant effort to preserve existing habitat, suggesting low future resiliency and redundancy. With the results of these data analyses and predictive models, the USFWS concluded that protections of the Endangered Species Act were warranted for this subspecies.