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Abstract Global expansion in wind energy development is a notable achievement of the international community’s effort to reduce carbon emissions during energy production. However, the increasing number of wind turbines have unintended consequences for migratory birds and bats. Wind turbine curtailment and other mitigation strategies can reduce fatalities, but improved spatial and temporal data are needed to identify the most effective way for wind energy development and volant migratory species to coexist. Mexican free-tailed bats (Tadarida brasiliensis mexicana) account for a large proportion of known bat fatalities at wind facilities in the southwestern US. We examined the geographic concordance between existing wind energy generation facilities, areas of high wind potential amenable for future deployment of wind facilities, and seasonally suitable habitat for these bats. We used ecological niche modeling to determine species distribution during each of 4 seasons. We used a multi-criteria GIS-based approach to produce a wind turbine siting suitability map. We identified seasonal locations with highest and lowest potential for the species’ probability of occurrence, providing a potential explanation for the higher observed fatalities during fall migration. Thirty percent of 33,606 wind turbines within the southwestern US occurred in highly suitable areas for Mexican free-tailed bats, primarily in west Texas. There is also broad spatial overlap between areas of high wind potential and areas of suitable habitat for Mexican free-tailed bats. Because of this high degree of overlap, our results indicate that post-construction strategies, such as curtailing the timing of operations and deterrents, would be more effective for bat conservation than strategic siting of new wind energy installations.

Abstract The decline of the iconic monarch butterfly (Danaus plexippus) in North America has motivated research on the impacts of land use and land cover (LULC) change and climate variability on monarch habitat and population dynamics. We investigated spring and fall trends in LULC, milkweed and nectar resources over a 20-year period, and ~ 30 years of climate variables in Mexico and Texas, U.S. This region supports spring breeding, and spring and fall migration during the annual life cycle of the monarch. We estimated a − 2.9% decline in milkweed in Texas, but little to no change in Mexico. Fall and spring nectar resources declined

The global decline of pollinators, particularly insects, underscores the importance of enhanced monitoring of their populations and habitats. However, monitoring some pollinator habitat is challenging due to widespread species distributions and shifts in habitat requirements through seasons and life stages. The monarch butterfly (Danaus plexippus), a migratory insect pollinator that breeds widely throughout North America, presents a unique case study for testing a sampling framework to overcome these challenges. Monarchs exhibit discrete resource needs across life stages (e.g., larval requirement for milkweed, adult requirement for floral nectar), utilizing many land use types across their extensive geographic range during breeding and migration seasons. The Integrated Monarch Monitoring Program (IMMP) uses a standardized protocol with a generalized random tessellation stratified (GRTS) sampling design to gather spatially balanced and ecologically representative information on monarch habitats within the United States. The IMMP is applicable to various land use types and habitats used by breeding monarchs and may be extended to sites outside of the GRTS design to collect data on non-random sites of interest, such as legacy or conservation sites. Additionally, the IMMP’s modular design and publicly available training allows for broad participation, including involvement from community scientists. Here, we summarize habitat metrics (milkweed and floral resources) across 1,233 sites covering much of the monarch’s breeding range. We examine variation in milkweed density and floral resource availability on probabilistic (random) and non-probabilistic (convenience) samples and among land use types (site types). Additionally, we assess resource availability within core geographies for monarch breeding and migration, specifically within the U.S. Fish and Wildlife Service’s Monarch Conservation Units (western, northern, and southern United States). Milkweed density, floral frequency, and floral richness were higher on non-random sites and in the North region. Among site types, milkweed density was highest on Rights-of-Way and Unclassified Grassland, while floral frequency was lowest on Rights-of-Way. The IMMP represents the first field-based habitat monitoring program of this scale for monarchs, yielding a robust dataset on monarchs and their habitats across their breeding range and offering a framework for surveying the habitat of insect species with diverse habitat requirements or widespread distributions.

Returning monarch butterflies (Danaus plexippus) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company’s potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs.

Abstract Bats provide ecologically and agriculturally important ecosystem services but are currently experiencing population declines caused by multiple environmental stressors, including mortality from white-nose syndrome and wind energy development. Analyses of the current and future health and viability of these species may support conservation management decision making. Demographic modeling provides a quantitative tool for decision makers and conservation managers to make more informed decisions, but widespread adoption of these tools can be limited because of the complexity of the mathematical, statistical, and computational components involved in implementing these models. In this work, we provide an exposition of the BatTool R package, detailing the primary components of the matrix projection model, a publicly accessible graphical user interface ( https://rconnect.usgs.gov/battool ) facilitating user-defined scenario analyses, and its intended uses and limitations (Wiens et al., US Geol Surv Data Release 2022; Wiens et al., US Geol Surv Softw Release 2022). We present a case study involving wind energy permitting, weighing the effects of potential mortality caused by a hypothetical wind energy facility on the projected abundance of four imperiled bat species in the Midwestern United States.

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.

Collaborative monitoring over broad scales and levels of ecological organization can inform conservation efforts necessary to address the contemporary biodiversity crisis. An important challenge to collaborative monitoring is motivating local engagement with enough buy-in from stakeholders while providing adequate top-down direction for scientific rigor, quality control, and coordination. Collaborative monitoring must reconcile this inherent tension between top-down control and bottom-up engagement. Highly mobile and cryptic taxa, such as bats, present a particularly acute challenge. Given their scale of movement, complex life histories, and rapidly expanding threats, understanding population trends of bats requires coordinated broad-scale collaborative monitoring. The North American Bat Monitoring Program (NABat) reconciles top-down, bottom-up tension with a hierarchical master sample survey design, integrated data analysis, dynamic data curation, regional monitoring hubs, and knowledge delivery through web-based infrastructure. NABat supports collaborative monitoring across spatial and organizational scales and the full annual lifecycle of bats.

Abstract Migratory waterfowl are an important resource for consumptive and non‐consumptive users alike and provide tremendous economic value in North America. These birds rely on a complex matrix of public and private land for forage and roosting during migration and wintering periods, and substantial conservation effort focuses on increasing the amount and quality of target habitat. Yet, the value of habitat is a function not only of a site's resources but also of its geographic position and weather. To quantify this value, we used a continental‐scale energetics‐based model of daily dabbling duck movement to assess the marginal value of lands across the contiguous United States during the non‐breeding period (September to May). We examined effects of eliminating each habitat node (32 × 32 km) in both a particularly cold and a particularly warm winter, asking which nodes had the largest effect on survival. The marginal value of habitat nodes for migrating dabbling ducks was a function of forage and roosting habitat but, more importantly, of geography (especially latitude and region). Irrespective of weather, nodes in the Southeast, central East Coast, and California made the largest positive contributions to survival. Conversely, nodes in the Midwest, Northeast, Florida, and the Pacific Northwest had consistent negative effects. Effects (positive and negative) of more northerly nodes occurred in late fall or early spring when climate was often severe and was most variable. Importance and effects of many nodes varied considerably between a cold and a warm winter. Much of the Midwest and central Great Plains benefited duck survival in a warm winter, and projected future warming may improve the value of lands in these regions, including many National Wildlife Refuges, for migrating dabbling ducks. Our results highlight the geographic variability in habitat value, as well as shifts that may occur in these values due to climate change.

Many pressing conservation issues are complex problems caused by multiple social and environmental drivers; their resolution is aided by interdisciplinary teams of scientists, decision makers, and stakeholders working together. In these situations, how do we generate science to effectively guide conservation (resource management and policy) decisions? This paper describes elements of successful big-team science in conservation, as well as shortcomings and lessons learned, based on our work with the monarch butterfly (Danaus plexippus) in North America. We summarize literature on effective science teams, extracting information about elements of success, effective implementation approaches, and barriers or pitfalls. We then describe recent and ongoing conservation science for the monarch butterfly in North America. We focus primarily on the activities of the Monarch Conservation Science Partnership–an international collaboration of interdisciplinary scientists, policy experts and natural resource managers spanning government, non-governmental and academic institutions—which developed science to inform imperilment status, recovery options, and monitoring strategies. We couch these science efforts in the adaptative management framework of Strategic Habitat Conservation, the business model for conservation employed by the US Fish and Wildlife Service to inform decision-making needs identified by stakeholders from Canada, the United States, and Mexico. We conclude with elements critical to effective big-team conservation science, discuss why science teams focused on applied conservation problems are unique relative to science teams focusing on traditional or theoretical research, and list benefits of big team science in conservation.

Abstract Migratory species often provide ecosystem service benefits to people in one country while receiving habitat support in other countries. The multinational cooperation that could help ensure continued provisioning of these benefits by migration may be informed by understanding the economic values people in different countries place on the benefits they derive from migratory wildlife. We conducted contingent valuation surveys to estimate the willingness of 3733 respondents from Canada, the United States and México to invest in conservation for two disparate migratory species, the northern pintail duck Anas acuta and the Mexican free‐tailed bat Tadarida brasiliensis mexicana. With zero‐inflated mixed‐effects negative binomial regression (explaining 87% of the variation in willingness to pay for conservation), we found that respondents from each nation, after controlling for both household income and per capita national Gross Domestic Product, were willing to invest in conservation in other countries. This willingness to pay for conservation, even when respondents knew that funds would be used to support benefits accruing primarily in other countries, demonstrates the potential for support of multinational conservation policies and programmes that direct resources to locations where the most critical habitat is located, rather than where the funding is generated. These findings could be used to support the development or expansion of new and existing international conservation programmes for migratory species. Read the free Plain Language Summary for this article on the Journal blog.

Estimating the abundance of unmarked animal populations from acoustic data is challenging due to the inability to identify individuals and the need to adjust for observation biases including detectability (false negatives), species misclassification (false positives), and sampling exposure. Acoustic surveys conducted along mobile transects were designed to avoid counting individuals more than once, where raw counts are commonly treated as an index of abundance. More recently, false‐positive abundance models have been developed to estimate abundance while accounting for imperfect detection and misclassification. We adapted these methods to model summertime abundance and trends of three species of bats at multiple spatial scales using acoustic recordings collected along mobile transects by partners of the North American Bat Monitoring Program (NABat) from 2012 to 2020. This multiscale modeling spanned individual transect routes, larger NABat grid cells (10 km × 10 km), and across the entire extent of modeled species ranges. We estimated relationships between species abundances and a suite of abiotic and biotic predictors (landcover types, climatological variables, physiographic diversity, building density, and the impacts of white‐nose syndrome [WNS]) and found varying levels of support between species. We present clear evidence of substantial declines in populations of tricolored bats (Perimyotis subflavus) and little brown bats (Myotis lucifugus), declines that corresponded in space and time with the progression of WNS, a devastating disease of hibernating bats. In contrast, our analysis revealed that similar population‐wide declines probably have not occurred in big brown bats (Eptesicus fuscus), a species known to be less affected by WNS. This study provides the first abundance‐based species distribution predictions and population trends for bats in their summer ranges in North America. These models will probably be applicable to assessing wildlife populations in other monitoring programs where acoustic data are used or where false‐negative and false‐positive detections are present. Finally, our abundance framework (as a spatial point pattern process) can serve as a foundation from which more sophisticated integrated species distribution models that incorporate additional streams of monitoring data (e.g., stationary acoustics, captures) can be developed for North American bats. [ABSTRACT FROM AUTHOR]

Abstract Biodiversity conservation efforts have been criticized for generating inequitable socio‐economic outcomes. These equity challenges are largely analyzed as place‐based problems affecting local communities directly impacted by conservation programs. The conservation of migratory species extends this problem geographically since people in one place may benefit while those in another bear the costs of conservation. The spatial subsidies approach offers an effective tool for analyzing such relationships between places connected by migratory species. Designed to quantify ecosystem services provided and received in specific locations across a migratory species’ range—and the disparities between them—the spatial subsidies approach highlights three axes of inequity: between indigenous and settler colonial societies, between urban and rural populations, and between the Global North and Global South. Recognizing these relationships is critical to achieving two mutually reinforcing policy goals: avoiding inequitable conservation outcomes in efforts to conserve migratory species, and ensuring effective long‐term conservation of migratory species. In demonstrating how the spatial subsidies approach enables the identification and quantification of inequities involving three migratory species (northern pintail ducks, monarch butterflies, and Mexican free‐tailed bats), we argue that a spatial subsidies approach could apply to migratory species conservation efforts worldwide under the context of “payments for ecosystem services.”

Abstract White‐nose syndrome has been decimating populations of several bat species since its first occurrence in the Northeastern United States in the winter 2006–2007. The spread of the disease has been monitored across the continent through the collaboration of many organizations. Inferring the rate of spread of the disease and predicting its arrival at new locations is critical when assessing the current and predicting the future status and trends of bat species. We developed a model of disease spread that simultaneously achieves high‐predictive performance, computational efficiency, and interpretability. We modeled white‐nose syndrome spread using Gaussian process variations to infer the spread rate of the disease front, identify areas of anomalous time of arrival, and provide future forecasts of the expected time of arrival throughout North America. Cross‐validation of model predictive performance identified a stationary Gaussian process without an additional residual error process as the best‐supported model. Results indicated that white‐nose syndrome is likely to spread throughout the entire continental United States by 2030. These annually updatable model predictions will be useful in determining the horizon over which disease management actions must take place as well as in status and trend assessments of disease‐affected bats.

Recovering species are not returning to the same environments or communities from which they disappeared. Conservation researchers and practitioners are thus faced with additional challenges in ensuring species resilience in these rapidly changing ecosystems. Assessing the resilience of species in these novel systems can still be guided by species’ ecology, including knowledge of their population size, life history traits, and behavioral adaptations, as well as the type, strength, and number of ways that they interact with other species in the community. We summarized broad trends of Common Loons (Gavia immer) breeding at Voyageurs National Park from 1973 to 2009, and evaluated the effects of increased risk from recovering Bald Eagles (Haliaeetus leucocephalus) on chick survival from 2004 to 2006. Adult Common Loons appear to have increased over time. Using Bayesian survival models that accounted for imperfect detection of unmarked individuals, we determined that chick survival of Common Loons was high from year to year and was unrelated to predation risk from Bald Eagles because chicks in territories closer to active nests did not experience greater mortality than those farther away. We suggest that Common Loon chicks were unaffected by the recovery of this top predator during the three years of sampling. Previous research indicates that Bald Eagles and other predators are an important source of egg losses, but Common Loons can compensate by re-nesting. Despite current uncertainties from anthropogenic threats, knowledge of a species’ ecology remains instrumental in determining its resilience during recovery.

Abstract We developed a continental energetics‐based model of daily mallard (Anas platyrhynchos) movement during the non‐breeding period (September to May) to predict year‐specific migration and overwinter occurrence. The model approximates movements and stopovers as functions of metabolism and weather, in terms of temperature and frozen precipitation (i.e., snow). The model is a Markov process operating at the population level and is parameterized through a review of literature. We applied the model to 62 years of daily weather data for the non‐breeding period. The average proportion of available habitat decreased as weather severity increased, with mortality decreasing as the proportion of available habitat increased. The most commonly used locations during the course of the non‐breeding period were generally consistent across years, with the most inter‐annual variation present in the overwintering area. Our model revealed that the distribution of mallards on the landscape changed more dramatically when the variation in daily available habitat was greater. The main routes for avian migration in North America were predicted by our simulations: the Atlantic, Mississippi, Central, and Pacific flyways. Our model predicted an average of 77.4% survivorship for the non‐breeding period across all years (range = 76.4%–78.4%), with lowest survivorship during autumn (90.5 ± 1.4%), intermediate survivorship in winter (91.8 ± 0.7%), and greatest survivorship in spring (93.6 ± 1.1%). We provide the parameters necessary for exploration within and among other taxa to leverage the generalizability of this migration model to a broader expanse of bird species, and across a range of climate change and land use/land cover change scenarios.

As youth development programs established in the United States expand globally, researchers must evaluate their impacts in diverse contexts. The work described in this article established a baseline for assessing the impact of a 4-S youth program at professional technical high schools in Costa Rica. The 4-S program is equivalent to 4-H in English-speaking countries. Results indicate that members of the 4-S program exhibited significantly higher levels of positive youth development than youths in the comparison group (p < 0.001). We consider how these findings speak to the importance of promoting programs such as 4-S, and we conclude by discussing the implications of this work for practitioners.

Abstract A simulation‐based power analysis can be used to estimate the sample sizes needed for a successful monitoring program, but requires technical expertise and sometimes extensive computing resources. We developed a web‐based lookup app, called TrendPowerTool (https://www.usgs.gov/apps/TrendPowerTool/), to provide guidance for ecological monitoring programs when resources are not available for a simulation‐based power analysis. TrendPowerTool is implemented through the shiny package in R, but is accessible through a webpage without the need for users to install any software. By drawing on results of 1.4 million scenarios that we simulated on a supercomputer, TrendPowerTool quickly and easily provides an estimate of the statistical power to detect a population trend of a particular magnitude with a planned monitoring program, based on user‐specified parameters for the monitoring design and population of interest. TrendPowerTool provides a user‐friendly interface that retrieves results instantaneously, facilitating the important step of conducting a power analysis when designing monitoring programs.

Abstract A central challenge in applied ecology is understanding the effect of anthropogenic fatalities on wildlife populations and predicting which populations may be particularly vulnerable and in greatest need of management attention. We used three approaches to investigate the potential effects of fatalities from collisions with wind turbines on 14 raptor species for both current (106 GW) and anticipated future (241 GW) levels of installed wind energy capacity in the United States. Our goals were to identify species at relatively high vs low risk of experiencing population declines from turbine collisions and to also compare results generated from these approaches. Two of the approaches used a calculated turbine‐caused mortality rate to decrement population growth, where population trends were derived either from the North American Breeding Bird Survey or from a matrix model parameterized from literature‐derived demographic values. The third approach was potential biological removal, which estimates the number of fatalities that allow a population to reach and maintain its optimal sustainable population set by management objectives. Different results among the methods reveal substantial gaps in knowledge and uncertainty in both demographic parameters and species‐specific estimates of fatalities from wind turbines. Our results suggest that, of the 14 species studied, those with relatively higher potential of population‐level impacts from wind turbine collisions included barn owl, ferruginous hawk, golden eagle, American kestrel, and red‐tailed hawk. Burrowing owl, Cooper’s hawk, great horned owl, northern harrier, turkey vulture, and osprey had a relatively lower potential for population impacts, and results were not easily interpretable for merlin, prairie falcon, and Swainson’s hawk. Projections of current levels of fatalities to future wind energy scenarios at 241 GW of installed capacity suggest some species could experience population declines because of turbine collisions. Populations of those species may benefit from research to identify tools to prevent or reduce raptor collisions with wind turbines.

Returning monarch butterflies (Danaus plexippus) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company's potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs. [ABSTRACT FROM AUTHOR]