Limitations, lack of standardization, and recommended best practices in studies of renewable energy effects on birds and bats

Predicting risk to bat species from wind turbine collision in Southeast Asia

Wind farms can pose significant risks to bat populations through collisions with turbines, habitat loss, and effects on behavior. With its rich bat diversity and expanding wind power industry, Southeast Asia lacks sufficient data to assess the risks posed to bat species from wind turbine collisions. We aimed to develop a predictive framework for assessing wind turbine risk to bats in Southeast Asia based on global bat fatality data and trait-based assessments. We conducted a review of the literature to compile data on global bat fatalities related to wind turbines. We developed a risk assessment framework comprising 3 components-potential fatality detection index (pDI), potential spatial exposure risk index (pSE), and conservation status-to assess species vulnerability to wind turbines and to generate a conservation prioritization score for Southeast Asian bat species. Our predictive models incorporated wing morphology traits to estimate fatality probabilities for bat species. Global wing morphology data provided some predictive power for bat collision risk. Our models correctly identified bat species with known fatality data but less successfully identified species with low risk of fatality. However, uncertainty arose from knowledge gaps and a lack of transferability of information to Southeast Asian species. Our framework offers a starting point for assessing bat collision risk in Southeast Asia, but it underscores the critical need for region-specific data and continued refinement of predictive models. Establishing comprehensive bat collision monitoring programs in the region is essential for informing evidence-based management decisions and ultimately minimizing the impacts of wind energy development on Southeast Asian bat populations.

Climate-Smart Siting for renewable energy expansion

A massive expansion of renewable energy (RE) is underway to meet the world's climate goals. Although RE serves to reduce threats from climate change, it can also pose threats to species whose current and future ranges intersect with RE installations. Here, we propose a "Climate-Smart Siting" framework for addressing potential conflicts between RE expansion and biodiversity conservation. The framework engenders authentic consultation with affected and disadvantaged communities throughout and uses overlay and optimization routines to identify focal areas now and in the future where RE development poses promise and peril as species' ranges shift in response to climate change. We use this framework to demonstrate methods, identify decision outcomes, and discuss market-based levers for aligning RE expansion with the United Nations Global Biodiversity Framework now and as climate change progresses. In the face of the climate crisis, a Climate-Smart Siting strategy could help create solutions without causing further harm to biodiversity and human communities..

The geographic extent of bird populations affected by renewable-energy development

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.

Numbers of wildlife fatalities at renewable energy facilities in a targeted development region

Increased interest in renewable energy has fostered development of wind and solar energy facilities globally. However, energy development sometimes has negative environmental impacts, such as wildlife fatalities. Efforts by regional land managers to balance energy potential while minimizing fatality risk currently rely on datasets that are aggregated at continental, but not regional scales, that focus on single species, or that implement meta-analyses that inappropriately use inferential statistics. We compiled and summarized fatality data from 87 reports for solar and wind facilities in the Mojave and Sonoran Deserts region of southern California within the Desert Renewable Energy Conservation Plan area. Our goal was to evaluate potential temporal and guild-specific patterns in fatalities, especially for priority species of conservation concern. We also aimed to provide a perspective on approaches interpreting these types of data, given inherent limitations in how they were collected. Mourning doves (Zenaida macroura), Chukar (Alectoris chukar) and California Quail (Callipepla californica), and passerines (Passeriformes), accounted for the most commonly reported fatalities. However, our aggregated count data were derived from raw, uncorrected totals, and thus reflect an absolute minimum number of fatalities for the monitored period. Additionally, patterns in the raw data suggested that many species commonly documented as fatalities (e.g., waterbirds and other nocturnal migrants, bats) are rarely counted during typical pre-construction use surveys. This may explain the more commonly observed mismatch between pre-construction risk assessment and actual fatalities. Our work may serve to guide design of future scientific research to address temporal and spatial patterns in fatalities and to apply rigorous guild-specific survey methodologies to estimate populations at risk from renewable energy development.

Understanding fatality patterns and sex ratios of Brazilian free-tailed bats (Tadarida brasiliensis) at wind energy facilities in western California and Texas

Background

Operation of wind turbines has resulted in collision fatalities for several bat species, and one proven method to reduce these fatalities is to limit wind turbine blade rotation (i.e., curtail turbines) when fatalities are expected to be highest. Implementation of curtailment can potentially be optimized by targeting times when females are most at risk, as the proportion of females limits the growth and stability of many bat populations. The Brazilian free-tailed bat (Tadarida brasiliensis) is the most common bat fatality at wind energy facilities in California and Texas, and yet there are few available data on the sex ratios of the carcasses that are found. Understanding the sex ratios of fatalities in California and Texas could aid in planning population conservation strategies such as informed curtailment.

Methods

We used PCR to determine the sex of bat carcasses collected from wind energy facilities during post-construction monitoring (PCM) studies in California and Texas. In California, we received samples from two locations within the Altamont Pass Wind Resource Area in Alameda County: Golden Hills (GH) (n = 212) and Golden Hills North (GHN) (n = 312). In Texas, we received samples from three wind energy facilities: Los Mirasoles (LM) (Hidalgo County and Starr County) (n = 252), Los Vientos (LV) (Starr County) (n = 568), and Wind Farm A (WFA) (San Patricio County and Bee County) (n = 393).

Results

In California, the sex ratios of fatalities did not differ from 50:50, and the sex ratio remained stable over the survey years, but the seasonal timing of peak fatalities was inconsistent. In 2017 and 2018, fatalities peaked between September and October, whereas in 2019 and 2020 fatalities peaked between May and June. In Texas, sex ratios of fatalities varied between locations, with Los Vientos being female-skewed and Wind Farm A being male-skewed. The sex ratio of fatalities was also inconsistent over time. Lastly, for each location in Texas with multiple years studied, we observed a decrease in the proportion of female fatalities over time.

Discussion

We observed unexpected variation in the seasonal timing of peak fatalities in California and differences in the sex ratio of fatalities across time and facility location in Texas. In Texas, proximity to different roost types (bridge or cave) likely influenced the sex ratio of fatalities at wind energy facilities. Due to the inconsistencies in the timing of peak female fatalities, we were unable to determine an optimum curtailment period; however, there may be location-specific trends that warrant future investigation. More research should be done over the entirety of the bat active season to better understand these trends in Texas. In addition, standardization of PCM studies could assist future research efforts, enhance current monitoring efforts, and facilitate research on post-construction monitoring studies.

EolPop, a R-shiny tool for quantifying the demographic impact of species exposed to fatalities: Application to bird collisions with wind turbines

Quantifying the demographic impact of anthropogenic fatalities on animal populations is a key component of wildlife conservation. However, such quantification remains rare in environmental impact assessments (EIA) of large-infrastructure projects, partly because of the complexity of implementing demographic models. Providing user-friendly demographic tools is thus an important step to fill this gap. We developed an application called EolPop to run demographic simulations and assess population-level impacts of fatalities. This tool, freely available online, is easy to use and requires minimal input data from the user. As an output, it provides an estimate, with associated uncertainty, of the relative deficit in population size at a given time horizon. Because this impact metric is relative to a baseline scenario without fatalities, it is robust to uncertainties. We showcase the tool using examples on two species that are affected by collisions with wind turbines: Lesser kestrel (Falco naumanni) and Eurasian skylark (Alauda arvensis). After 30 years, the kestrel's population is expected to suffer a deficit of ca. 48%. In contrast, the impact on skylarks, which are already declining in France, is estimated to be fairly low (ca. 7%). EolPop aims at providing a robust quantification of the relative impact of fatalities. This tool was originally built for windfarm EIA, with a focus on birds, but it can be used to assess the demographic consequences of any type of fatalities on any species.

Genetic identification of avian samples recovered from solar energy installations

Renewable energy production and development will drastically affect how we meet global energy demands, while simultaneously reducing the impact of climate change. Although the possible effects of renewable energy production (mainly from solar- and wind-energy facilities) on wildlife have been explored, knowledge gaps still exist, and collecting data from wildlife remains (when negative interactions occur) at energy installations can act as a first step regarding the study of species and communities interacting with facilities. In the case of avian species, samples can be collected relatively easily (as compared to other sampling methods), but may only be able to be identified when morphological characteristics are diagnostic for a species. Therefore, many samples that appear as partial remains, or "feather spots"-known to be of avian origin but not readily assignable to species via morphology-may remain unidentified, reducing the efficiency of sample collection and the accuracy of patterns observed. To obtain data from these samples and ensure their identification and inclusion in subsequent analyses, we applied, for the first time, a DNA barcoding approach that uses mitochondrial genetic data to identify unknown avian samples collected at solar facilities to species. We also verified and compared identifications obtained by our genetic method to traditional morphological identifications using a blind test, and discuss discrepancies observed. Our results suggest that this genetic tool can be used to verify, correct, and supplement identifications made in the field and can produce data that allow accurate comparisons of avian interactions across facilities, locations, or technology types. We recommend implementing this genetic approach to ensure that unknown samples collected are efficiently identified and contribute to a better understanding of wildlife impacts at renewable energy projects.

Vulnerability of avian populations to renewable energy production

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.

Estimation of spatiotemporal trends in bat abundance from mortality data collected at wind turbines

Renewable energy sources, such as wind energy, are essential tools for reducing the causes of climate change, but wind turbines can pose a collision risk for bats. To date, the population-level effects of wind-related mortality have been estimated for only 1 bat species. To estimate temporal trends in bat abundance, we considered wind turbines as opportunistic sampling tools for flying bats (analogous to fishing nets), where catch per unit effort (carcass abundance per monitored turbine) is a proxy for aerial abundance of bats, after accounting for seasonal variation in activity. We used a large, standardized data set of records of bat carcasses from 594 turbines in southern Ontario, Canada, and corrected these data to account for surveyor efficiency and scavenger removal. We used Bayesian hierarchical models to estimate temporal trends in aerial abundance of bats and to explore the effect of spatial factors, including landscape features associated with bat habitat (e.g., wetlands, croplands, and forested lands), on the number of mortalities for each species. The models showed a rapid decline in the abundance of 4 species in our study area; declines in capture of carcasses over 7 years ranged from 65% (big brown bat [Eptesicus fuscus]) to 91% (silver-haired bat [Lasionycteris noctivagans]). Estimated declines were independent of the effects of mitigation (increasing wind speed at which turbines begin to generate electricity from 3.5 to 5.5 m/s), which significantly reduced but did not eliminate bat mortality. Late-summer mortality of hoary (Lasiurus cinereus), eastern red (Lasiurus borealis), and silver-haired bats was predicted by woodlot cover, and mortality of big brown bats decreased with increasing elevation. These landscape predictors of bat mortality can inform the siting of future wind energy operations. Our most important result is the apparent decline in abundance of four common species of bat in the airspace, which requires further investigation.