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Projections for deep decarbonization require large amounts of solar energy, which may compete with other land uses such as agriculture, urbanization, and conservation of natural lands. Existing capacity expansion models do not integrate land use land cover change (LULC) dynamics into projections. We explored the interaction between projected LULC, solar photovoltaic (PV) deployment, and solar impacts on natural lands and croplands by integrating projections of LULC with a model that can project future deployment of solar PV with high spatial resolution for the conterminous United States. We used scenarios of LULC projections from the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios from 2010 to 2050 and two electricity grid scenarios to model future PV deployment and compared those results against a baseline that held 2010 land cover constant through 2050. Though solar PV's overall technical potential was minimally impacted by LULC scenarios, deployed PV varied by -16.5 to 11.6 % in 2050 from the baseline scenario. Total land requirements for projected PV were similar to other studies, but measures of PV impacts on natural systems depended on the underlying land change dynamics occurring in a scenario. The solar PV deployed through 2050 resulted in 1.1 %-2.4 % of croplands and 0.3 %-0.7 % of natural lands being converted to PV. However, the deepest understanding of PV impacts and interactions with land cover emerged when the complete net gains and losses from all land cover change dynamics, including PV, were integrated. For example, one of the four LULC projections allows for high solar development and a net gain in natural lands, even though PV drives a larger percentage of natural land conversion. This paper shows that integrating land cover change dynamics with energy expansion models generates new insights into trade offs between decarbonization, impacts of renewables, and ongoing land cover change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The US Geological Survey, The Author(s). Published by Elsevier B.V. All rights reserved.)

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., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Bird populations are declining globally. Wind and solar energy can reduce emissions of fossil fuels that drive anthropogenic climate change, yet renewable-energy production represents a potential threat to bird species. Surveys to assess potential effects at renewable-energy facilities are exclusively local, and the geographic extent encompassed by birds killed at these facilities is largely unknown, which creates challenges for minimizing and mitigating the population-level and cumulative effects of these fatalities. We performed geospatial analyses of stable hydrogen isotope data obtained from feathers of 871 individuals of 24 bird species found dead at solar- and wind-energy facilities in California (USA). Most species had individuals with a mix of origins, ranging from 23% to 98% nonlocal. Mean minimum distances to areas of likely origin for nonlocal individuals were as close as 97 to >1250 km, and these minimum distances were larger for species found at solar-energy facilities in deserts than at wind-energy facilities in grasslands (Cohen's d = 6.5). Fatalities were drawn from an estimated 30-100% of species' desingated ranges, and this percentage was significantly smaller for species with large ranges found at wind facilities (Pearson's r = -0.67). Temporal patterns in the geographic origin of fatalities suggested that migratory movements and nonmigratory movements, such as dispersal and nomadism, influence exposure to fatality risk for these birds. Our results illustrate the power of using stable isotope data to assess the geographic extent of renewable-energy fatalities on birds. As the buildout of renewable-energy facilities continues, accurate assessment of the geographic footprint of wildlife fatalities can be used to inform compensatory mitigation for their population-level and cumulative effects., (© 2024 Society for Conservation Biology. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

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 < 1% in both study extents. Vegetation greenness increased in the fall and spring in Mexico while the other climate variables did not change in both Mexico and Texas. Monarch habitat in Mexico and Texas appears relatively more intact than in the midwestern, agricultural landscapes of the U.S. Given the relatively modest observed changes in nectar and milkweed, the relatively stable climate conditions, and increased vegetation greenness in Mexico, it seems unlikely that habitat loss (quantity or quality) in Mexico and Texas has caused large declines in population size or survival during migration., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Over 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 megawatt direct current (MW dc ) or more. Ground-mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. The United States Large-Scale Solar Photovoltaic Database (USPVDB) was developed to fill this gap. Using US Energy Information Administration (EIA) data, locations of 3,699 LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available via an interactive web application and multiple downloadable formats, including: comma-separated value (CSV), application programming interface (API), and GIS shapefile and GeoJSON., (© 2023. The Author(s).)

Semi-arid urban environments are undergoing an increase in both average air temperatures and in the frequency and intensity of extreme heat events. Within cities, different composition and densities of urban landcovers (ULC) influence local air temperatures, either mitigating or increasing heat. Currently, understanding how combinations of ULC influence air temperature at the block to neighborhood scale is necessary for heat mitigation plans, and yet limited due to the complexities integrating high-resolution ULC with spatial and temporally high-resolution microclimate data. We quantify how ULC influences air temperature at 60 m resolution for day and nighttime climate normals and extreme heat conditions by integrating microclimate sensor data sensor and high-resolution (1 m 2 ) ULC for Denver, Colorado's urban core. We derive ULC drivers of air temperature using a structural equation model, then use a random forest algorithm to predict air temperatures for 30-year climate normals and an extreme heat condition. We find that, in conjunction with other ULC, urban tree canopy reduces daytime air temperatures (-0.026 °C per % cover), and the combination of impervious surfaces and buildings increases daytime air temperature (0.021 °C per % cover). Compared to daytime hours, nighttime irrigated turf temperature cooling effects are increased from being non-significant to -0.022 °C per % cover, while tree canopy effects are reduced from -0.026 °C during the day to -0.016 °C at night. Overall, ULC drives ~17% and 25% of local air temperature during the day and night, respectively. ULC influence on daytime air temperatures is altered in extreme heat events, both depending on the ULC type and time of day. Our findings inform urban planners seeking to identify potential hot and cool spots within a semi-arid city and mitigate high urban air temperatures through using ULC within larger urban climate mitigation strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier B.V.)

Renewable energy production can kill individual birds, but little is known about how it affects avian populations. We assessed the vulnerability of populations for 23 priority bird species killed at wind and solar facilities in California, USA. Bayesian hierarchical models suggested that 48% of these species were vulnerable to population-level effects from added fatalities caused by renewables and other sources. Effects of renewables extended far beyond the location of energy production to impact bird populations in distant regions across continental migration networks. Populations of species associated with grasslands where turbines were located were most vulnerable to wind. Populations of nocturnal migrant species were most vulnerable to solar, despite not typically being associated with deserts where the solar facilities we evaluated were located. Our findings indicate that addressing declines of North American bird populations requires consideration of the effects of renewables and other anthropogenic threats on both nearby and distant populations of vulnerable species., Competing Interests: The authors declare the following competing interests: T.J.C. is serving as a member of the Alameda County (California) Wind Repowering / Avian Protection Technical Advisory Committee. T.V.D. and P.M.S. also serve on Technical Advisory Groups for several solar facilities. T.D.A. is Director of Research with the Renewable Energy Wildlife Institute. D.M.N. is a science advisor to the Renewable Energy Wildlife Institute. All other authors declare they have no competing interests., (© 2022 The Authors.)

Increasing global energy demand is fostering the development of renewable energy as an alternative to fossil fuels. However, renewable energy facilities may adversely affect wildlife. Facility siting guidelines recommend or require project developers complete pre- and postconstruction wildlife surveys to predict risk and estimate effects of proposed projects. Despite this, there are no published studies that have quantified the types of surveys used or how survey types are standardized within and across facilities. We evaluated 628 peer-reviewed publications, unpublished reports, and citations, and we analyzed data from 525 of these sources (203 facilities: 193 wind and 10 solar) in the United States and Canada to determine the frequency of pre- and postconstruction surveys and whether that frequency changed over time; frequency of studies explicitly designed to allow before-after or impact-control analyses; and what types of survey data were collected during pre- and postconstruction periods and how those data types were standardized across periods and among facilities. Within our data set, postconstruction monitoring for wildlife fatalities and habitat use was a standard practice (n = 446 reports), but preconstruction estimation of baseline wildlife habitat use and mortality was less frequently reported (n = 84). Only 22% (n = 45) of the 203 facilities provided data from both pre- and postconstruction, and 29% (n = 59) had experimental study designs. Of 108 facilities at which habitat-use surveys were conducted, only 3% estimated of detection probability. Thus, the available data generally preclude comparison of biological data across construction periods and among facilities. Use of experimental study designs and following similar field protocols would improve the knowledge of how renewable energy affects wildlife. Article Impact Statement Many surveys at wind and solar facilities provide limited information on wildlife use and fatality rates., (© 2020 Society for Conservation Biology.)

The consequences of environmental disturbance and management are difficult to quantify for spatially structured populations because changes in one location carry through to other areas as a result of species movement. We develop a metric, G , for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different from other contribution metrics, as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences the ordering of node contribution. We find that habitats within which all individuals reside during one season are the most important to short-term network growth under complete removal scenarios, whereas the central breeding region contributes most to population growth over all but the strongest disturbances. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations.

Over 60,000 utility-scale wind turbines are installed in the United States as of October, 2019, representing over 97 gigawatts of electric power capacity; US wind turbine installations continue to grow at a rapid pace. Yet, until April 2018, no publicly-available, regularly updated data source existed to describe those turbines and their locations. Under a cooperative research and development agreement, analysts from three organizations collaborated to develop and release the United States Wind Turbine Database (USWTDB) - a publicly available, continuously updated, spatially rectified data source of locations and attributes of utility-scale wind turbines in the United States. Technical specifications and wind facility data, incorporated from five sources, undergo rigorous quality control. The location of each turbine is visually verified using high-resolution aerial imagery. The quarterly-updated data are available in a variety of formats, including an interactive web application, comma-separated values (CSV), shapefile, and application programming interface (API). The data are used widely by academic researchers, engineers and developers from wind energy companies, government agencies, planners, educators, and the general public.

Wind energy generation affects landscapes as new roads, pads, and transmission lines are constructed. Limiting the landscape change from these facilities likely minimizes impacts to biodiversity and sensitive wildlife species. We examined the effects of wind energy facilities' geographic context on changes in landscape patterns using three metrics: portion of undeveloped land, core area index, and connectance index. We digitized 39 wind facilities and the surrounding land cover and measured landscape pattern before and after facility construction using the amount, core area, and connectivity of undeveloped land within one km around newly constructed turbines and roads. New facilities decreased the amount of undeveloped land by 1.8% while changes in metrics of landscape pattern ranged from 50 to 140%. Statistical models indicated pre-construction development was a key factor explaining the impact of new wind facilities on landscape metrics, with pre-construction road networks, turbine spacing, and topography having smaller influences. As the proportion of developed land around facilities increased, a higher proportion of the facility utilized pre-construction developed land and a lower density of new roads were built, resulting in smaller impacts to undeveloped landscapes. Building of new road networks was also a predictor of landscape fragmentation. Utilizing existing development and carefully placing turbines may provide opportunities to minimize the impacts of new wind energy facilities., Competing Interests: The authors declare there are no competing interests.

Migratory species provide important benefits to society, but their cross-border conservation poses serious challenges. By quantifying the economic value of ecosystem services (ESs) provided across a species' range and ecological data on a species' habitat dependence, we estimate spatial subsidies-how different regions support ESs provided by a species across its range. We illustrate this method for migratory northern pintail ducks in North America. Pintails support over $101 million USD annually in recreational hunting and viewing and subsistence hunting in the U.S. and Canada. Pintail breeding regions provide nearly $30 million in subsidies to wintering regions, with the "Prairie Pothole" region supplying over $24 million in annual benefits to other regions. This information can be used to inform conservation funding allocation among migratory regions and nations on which the pintail depends. We thus illustrate a transferrable method to quantify migratory species-derived ESs and provide information to aid in their transboundary conservation.

In many parts of the world, the combined effects of habitat fragmentation and altered disturbance regimes pose a significant threat to biodiversity. This is particularly true in Mediterranean-type ecosystems (MTEs), which tend to be fire-prone, species rich, and heavily impacted by human land use. Given the spatial complexity of overlapping threats and species' vulnerability along with limited conservation budgets, methods are needed for prioritizing areas for monitoring and management in these regions. We developed a multi-criteria Pareto ranking methodology for prioritizing spatial units for conservation and applied it to fire threat, habitat fragmentation threat, species richness, and genetic biodiversity criteria in San Diego County, California, USA. We summarized the criteria and Pareto ranking results (from west to east) within the maritime, coastal, transitional, inland climate zones within San Diego County. Fire threat increased from the maritime zone eastward to the transitional zone, then decreased in the mountainous inland climate zone. Number of fires and fire return interval departure were strongly negatively correlated. Fragmentation threats, particularly road density and development density, were highest in the maritime climate zone, declined towards the east, and were positively correlated. Species richness criteria showed distributions among climate zones similar to those of the fire threat variables. When using species richness and fire threat criteria, most lower-ranked (higher conservation priority) units occurred in the coastal and transitional zones. When considering genetic biodiversity, lower-ranked units occurred more often in the mountainous inland zone. With Pareto ranking, there is no need to select criteria weights as part of the decision-making process. However, negative correlations and larger numbers of criteria can result in more units assigned to the same rank. Pareto ranking is broadly applicable and can be used as a standalone decision analysis method or in conjunction with other methods., Competing Interests: TAO was an employee of the consulting company AECOM while he collected plant data used by The Nature Conservancy in constructing the plant species distribution models. AECOM had no input or influence on the planning, execution, or reporting of the work described in this manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

We estimated U.S. and Mexican citizens' willingness to pay (WTP) for protecting habitat for a transborder migratory species, the Mexican free-tailed bat (Tadarida brasiliensis mexicana), using the contingent valuation method. Few contingent valuation surveys have evaluated whether households in one country would pay to protect habitat in another country. This study addresses that gap. In our study, Mexican respondents were asked about their WTP for conservation of Mexican free-tailed bat habitat in Mexico and in the United States. Similarly, U.S. respondents were asked about their WTP for conservation in the United States and in Mexico. U.S. households would pay $30 annually to protect habitat in the United States and $24 annually to protect habitat in Mexico. Mexican households would pay $8 annually to protect habitat in Mexico and $5 annually to protect habitat in the United States. In both countries, these WTP amounts rose significantly for increasing the size of the bat population rather than simply stabilizing the current bat population. The ratio of Mexican household WTP relative to U.S. household WTP is nearly identical to that of Mexican household income relative to U.S. household income. This suggests that the perceived economic benefits received from the bats is similar in Mexico and the United States, and that scaling WTP by relative income in international benefit transfer may be plausible.

In 2014, the Fish and Wildlife Service (FWS) and National Marine Fisheries Service announced a new policy interpretation for the U.S. Endangered Species Act (ESA). According to the act, a species must be listed as threatened or endangered if it is determined to be threatened or endangered in a significant portion of its range (SPR). The 2014 policy seeks to provide consistency by establishing that a portion of the range should be considered significant if the associated individuals' "removal would cause the entire species to become endangered or threatened." We reviewed 20 quantitative techniques used to assess whether a portion of a species' range is significant according to the new guidance. Our assessments are based on the 3R criteria-redundancy (i.e., buffering from catastrophe), resiliency (i.e., ability to withstand stochasticity), and representation (i.e., ability to evolve)-that the FWS uses to determine if a species merits listing. We identified data needs for each quantitative technique and considered which methods could be implemented given the data limitations typical of rare species. We also identified proxies for the 3Rs that may be used with limited data. To assess potential data availability, we evaluated 7 example species by accessing data in their species status assessments, which document all the information used during a listing decision. In all species, an SPR could be evaluated with at least one metric for each of the 3Rs robustly or with substantial assumptions. Resiliency assessments appeared most constrained by limited data, and many species lacked information on connectivity between subpopulations, genetic variation, and spatial variability in vital rates. These data gaps will likely make SPR assessments for species with complex life histories or that cross national boundaries difficult. Although we reviewed techniques for the ESA, other countries require identification of significant areas and could benefit from this research., (© 2017 Society for Conservation Biology.)

Quantification of the economic value provided by migratory species can aid in targeting management efforts and funding to locations yielding the greatest benefits to society and species conservation. Here we illustrate a key step in this process by estimating hunting and birding values of the northern pintail (Anas acuta) within primary breeding and wintering habitats used during the species' annual migratory cycle in North America. We used published information on user expenditures and net economic values (consumer surplus) for recreational viewing and hunting to determine the economic value of pintail-based recreation in three primary breeding areas and two primary wintering areas. Summed expenditures and consumer surplus for northern pintail viewing were annually valued at $70M, and annual sport hunting totaled $31M (2014 USD). Expenditures for viewing ($42M) were more than twice as high than those for hunting ($18M). Estimates of consumer surplus, defined as the amount consumers are willing to pay above their current expenditures, were $15M greater for viewing ($28M) than for hunting ($13M). We discovered substantial annual consumer surplus ($41M) available for pintail conservation from birders and hunters. We also found spatial differences in economic value among the primary regions used by pintails, with viewing generally valued more in breeding regions than in wintering regions and the reverse being true for hunting. The economic value of pintail-based recreation in the Western wintering region ($26M) exceeded that in any other region by at least a factor of three. Our approach of developing regionally explicit economic values can be extended to other taxonomic groups, and is particularly suitable for migratory game birds because of the availability of large amounts of data. When combined with habitat-linked population models, regionally explicit values could inform development of more effective conservation finance and policy mechanisms to enhance environmental management and societal benefits across the geographically dispersed areas used by migratory species., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles.

The monarch butterfly ( Danaus plexippus ) population in North America has sharply declined over the last two decades. Despite rising concern over the monarch butterfly's status, no comprehensive study of the factors driving this decline has been conducted. Using partial least-squares regressions and time-series analysis, we investigated climatic and habitat-related factors influencing monarch population size from 1993 to 2014. Potential threats included climatic factors, habitat loss (milkweed and overwinter forest), disease and agricultural insecticide use (neonicotinoids). While climatic factors, principally breeding season temperature, were important determinants of annual variation in abundance, our results indicated strong negative relationships between population size and habitat loss variables, principally glyphosate use, but also weaker negative effects from the loss of overwinter forest and breeding season use of neonicotinoids. Further declines in population size because of glyphosate application are not expected. Thus, if remaining threats to habitat are mitigated we expect climate-induced stochastic variation of the eastern migratory population of monarch butterfly around a relatively stationary population size., Competing Interests: The authors declare no conflicts of interest.

Given the rapid population decline and recent petition for listing of the monarch butterfly ( Danaus plexippus L.) under the Endangered Species Act, an accurate estimate of the Eastern, migratory population size is needed. Because of difficulty in counting individual monarchs, the number of hectares occupied by monarchs in the overwintering area is commonly used as a proxy for population size, which is then multiplied by the density of individuals per hectare to estimate population size. There is, however, considerable variation in published estimates of overwintering density, ranging from 6.9-60.9 million ha -1 . We develop a probability distribution for overwinter density of monarch butterflies from six published density estimates. The mean density among the mixture of the six published estimates was ∼27.9 million butterflies ha -1 (95% CI [2.4-80.7] million ha -1 ); the mixture distribution is approximately log-normal, and as such is better represented by the median (21.1 million butterflies ha -1 ). Based upon assumptions regarding the number of milkweed needed to support monarchs, the amount of milkweed ( Asclepias spp.) lost (0.86 billion stems) in the northern US plus the amount of milkweed remaining (1.34 billion stems), we estimate >1.8 billion stems is needed to return monarchs to an average population size of 6 ha. Considerable uncertainty exists in this required amount of milkweed because of the considerable uncertainty occurring in overwinter density estimates. Nevertheless, the estimate is on the same order as other published estimates. The studies included in our synthesis differ substantially by year, location, method, and measures of precision. A better understanding of the factors influencing overwintering density across space and time would be valuable for increasing the precision of conservation recommendations., Competing Interests: The authors declare there are no competing interests.

Hundreds of thousands of bats are killed annually by colliding with wind turbines in the U.S., yet little is known about factors causing variation in mortality across wind energy facilities. We conducted a quantitative synthesis of bat collision mortality with wind turbines by reviewing 218 North American studies representing 100 wind energy facilities. This data set, the largest compiled for bats to date, provides further support that collision mortality is greatest for migratory tree-roosting species (Hoary Bat [ Lasiurus cinereus ], Eastern Red Bat [ Lasiurus borealis ], Silver-haired Bat [ Lasionycteris noctivagans ]) and from July to October. Based on 40 U.S. studies meeting inclusion criteria and analyzed under a common statistical framework to account for methodological variation, we found support for an inverse relationship between bat mortality and percent grassland cover surrounding wind energy facilities. At a national scale, grassland cover may best reflect openness of the landscape, a factor generally associated with reduced bat activity and abundance that may also reduce turbine collisions. Further representative sampling of wind energy facilities is required to validate this broad pattern. Ecologically informed decisions regarding placement of wind energy facilities involves multiple considerations, including not only factors associated with bat mortality, but also factors associated with bird collision mortality, indirect habitat-related impacts to all species, and overall ecosystem impacts.

Wind energy generation holds the potential to adversely affect wildlife populations. Species-wide effects are difficult to study and few, if any, studies examine effects of wind energy generation on any species across its entire range. One species that may be affected by wind energy generation is the endangered Indiana bat ( Myotis sodalis ), which is found in the eastern and midwestern United States. In addition to mortality from wind energy generation, the species also faces range-wide threats from the emerging infectious fungal disease, white-nose syndrome (WNS). White-nose syndrome, caused by Pseudogymnoascus destructans , disturbs hibernating bats leading to high levels of mortality. We used a spatially explicit full-annual-cycle model to investigate how wind turbine mortality and WNS may singly and then together affect population dynamics of this species. In the simulation, wind turbine mortality impacted the metapopulation dynamics of the species by causing extirpation of some of the smaller winter colonies. In general, effects of wind turbines were localized and focused on specific spatial subpopulations. Conversely, WNS had a depressive effect on the species across its range. Wind turbine mortality interacted with WNS and together these stressors had a larger impact than would be expected from either alone, principally because these stressors together act to reduce species abundance across the spectrum of population sizes. Our findings illustrate the importance of not only prioritizing the protection of large winter colonies as is currently done, but also of protecting metapopulation dynamics and migratory connectivity., Competing Interests: The authors declare there are no competing interests.

The Eastern, migratory population of monarch butterflies (Danaus plexippus), an iconic North American insect, has declined by ~80% over the last decade. The monarch's multi-generational migration between overwintering grounds in central Mexico and the summer breeding grounds in the northern U.S. and southern Canada is celebrated in all three countries and creates shared management responsibilities across North America. Here we present a novel Bayesian multivariate auto-regressive state-space model to assess quasi-extinction risk and aid in the establishment of a target population size for monarch conservation planning. We find that, given a range of plausible quasi-extinction thresholds, the population has a substantial probability of quasi-extinction, from 11-57% over 20 years, although uncertainty in these estimates is large. Exceptionally high population stochasticity, declining numbers, and a small current population size act in concert to drive this risk. An approximately 5-fold increase of the monarch population size (relative to the winter of 2014-15) is necessary to halve the current risk of quasi-extinction across all thresholds considered. Conserving the monarch migration thus requires active management to reverse population declines, and the establishment of an ambitious target population size goal to buffer against future environmentally driven variability.

Recent growth in the wind energy industry has increased concerns about its impacts on wildlife populations. Direct impacts of wind energy include bird and bat collisions with turbines whereas indirect impacts include changes in wildlife habitat and behavior. Although many species may withstand these effects, species that are long-lived with low rates of reproduction, have specialized habitat preferences, or are attracted to turbines may be more prone to declines in population abundance. We developed a prioritization system to identify the avian species most likely to experience population declines from wind facilities based on their current conservation status and their expected risk from turbines. We developed 3 metrics of turbine risk that incorporate data on collision fatalities at wind facilities, population size, life history, species' distributions relative to turbine locations, number of suitable habitat types, and species' conservation status. We calculated at least 1 measure of turbine risk for 428 avian species that breed in the United States. We then simulated 100,000 random sets of cutoff criteria (i.e., the metric values used to assign species to different priority categories) for each turbine risk metric and for conservation status. For each set of criteria, we assigned each species a priority score and calculated the average priority score across all sets of criteria. Our prioritization system highlights both species that could potentially experience population decline caused by wind energy and species at low risk of population decline. For instance, several birds of prey, such as the long-eared owl, ferruginous hawk, Swainson's hawk, and golden eagle, were at relatively high risk of population decline across a wide variety of cutoff values, whereas many passerines were at relatively low risk of decline. This prioritization system is a first step that will help researchers, conservationists, managers, and industry target future study and management activity.

Wind energy is a rapidly growing form of renewable energy in the United States. While summary information on the total amounts of installed capacity are available by state, a free, centralized, national, turbine-level, geospatial dataset useful for scientific research, land and resource management, and other uses did not exist. Available in multiple formats and in a web application, these public domain data provide industrial-scale onshore wind turbine locations in the United States up to March 2014, corresponding facility information, and turbine technical specifications. Wind turbine records have been collected and compiled from various public sources, digitized or position verified from aerial imagery, and quality assured and quality controlled. Technical specifications for turbines were assigned based on the wind turbine make and model as described in public literature. In some cases, turbines were not seen in imagery or turbine information did not exist or was difficult to obtain. Uncertainty associated with these is recorded in a confidence rating.

We compared the number of avian species detected and the sampling effort during fatality monitoring at 50 North American wind facilities. Facilities with short intervals between sampling events and high effort detected more species, but many facilities appeared undersampled. Species accumulation curves for 2 wind facilities studied for more than 1 year had yet to reach an asymptote. The monitoring effort that is typically invested is likely inadequate to identify all of the species killed by wind turbines. This may understate impacts for rare species of conservation concern that collide infrequently with turbines but suffer disproportionate consequences from those fatalities. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.

Critics of the market-based, ecosystem services approach to biodiversity conservation worry that volatile market conditions and technological substitutes will diminish the value of ecosystem services and obviate the "economic benefits" arguments for conservation. To explore the effects of market forces and substitutes on service values, we assessed how the value of the pest-control services provided by Mexican free-tailed bats (Tadarida brasiliensis mexicana) to cotton production in the southwestern U.S. has changed over time. We calculated service values each year from 1990 through 2008 by estimating the value of avoided crop damage and the reduced social and private costs of insecticide use in the presence of bats. Over this period, the ecosystem service value declined by 79% ($19.09 million U.S. dollars) due to the introduction and widespread adoption of Bt (Bacillus thuringiensis) cotton transgenically modified to express its own pesticide, falling global cotton prices and the reduction in the number of hectares in the U.S. planted with cotton. Our results demonstrate that fluctuations in market conditions can cause temporal variation in ecosystem service values even when ecosystem function--in this case bat population numbers--is held constant. Evidence is accumulating, however, of the evolution of pest resistance to Bt cotton, suggesting that the value of bat pest-control services may increase again. This gives rise to an economic option value argument for conserving Mexican free-tailed bat populations. We anticipate that these results will spur discussion about the role of ecosystem services in biodiversity conservation in general, and bat conservation in particular.

Many ecosystems of conservation concern require some level of disturbance to sustain their species composition and ecological function. However, inappropriate disturbance regimes could favor invasion or expansion of exotic species. In southern California coastal sage scrub (CSS) fire is a natural disturbance, but because of human influence, frequencies may now be unnaturally high. Other anthropogenic disturbances such as grazing also occur in reserve areas. Managers charged with imposing or tolerating fire or other disturbance within their reserves are concerned that habitat quality may be degraded by an increasing abundance of exotic plants. We used vegetation monitoring data from Camp Pendleton, California, USA, to assess the correlation between past disturbances (frequent fire, agriculture, or grazing and mechanical disturbances) and current exotic species abundance in CSS. We found that disturbance history was only modestly related to exotic abundance overall, but fire frequency showed the strongest association. We also examined whether cover and richness of various native plant life forms (woody species, perennial herbs, and annual herbs) were more strongly influenced by disturbance history or by exotic-plant abundance. Native plant responses varied among life forms, but woody species and annual herbs were generally more strongly and negatively associated with exotic abundance than with disturbance. Effective CSS conservation will require developing means to curb the negative impacts of exotic plants, which may abound with or without severe or recent disturbance. Additionally, more focus should be given to understory herbs showing sensitivity to invasion. Though understudied, native herbs comprise the greatest portion of plant diversity in CSS and are critical to preservation of the community as a whole.

We present five case studies highlighting the effects of habitat fragmentation on the genetic structure of small mammal populations. The studies reflect different spatial scales and components of genetic variation. In marginal and central populations of Sigmodon hispidus we found less allozymic variation within the marginal population, whereas patterns of morphological variability were the converse. In the rice rat (Oryzomys spp.), nucleotide diversity in mtDNA was similar in an island population in the Florida Keys to mainland populations in the Everglades. This observation contrasts with insular vole populations (Microtus spp.), where isolation on islands results in genetic structuring. Temporal changes in abundance in mainland populations had no effects on genetic differentiation (FST values) because subpopulations did not experience bottlenecks. In an experimentally fragmented landscape, fragmentation influenced demographic processes but not genetic structure. We conclude that (1) with extreme fragmentation, small mammal populations become depauperate of genetic variation and differentiate genetically; (2) different components of genetic variation lead to different genetic structuring; (3) spatial and temporal scales should both be considered when examining genetic structure of populations; (4) demographic and ecological processes are more likely influenced by fragmentation than genetic structure; and (5) there is an interaction between demographic processes and genetic structure.