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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 We evaluated 628 peer‐reviewed publications, unpublished reports, and citations, and we analyzed data from 525 of these sources (203 facilities: 193 wind and 10 solar) in the United States and Canada to determine the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.

Nest predation is a major limiting factor for songbird productivity, including the federally endangered black‐capped vireo (Vireo atricapilla). However, nest predator information is limited across the range of the black‐capped vireo in central and southwest Texas. We monitored nests in 3 counties within the breeding range of black‐capped vireos in Texas in 2008 and 2009 and used continuous recording digital video cameras to record predation events. We video‐monitored 115 nests and documented 39 predation events by at least 9 predator species. Overall, we observed avian species (51%, n = 39), specifically brown‐headed cowbirds (Molothrus ater; n = 12), and snakes (26%, n = 39) as the most frequent nest predators. The estimated daily nest survival rate during the laying and incubation stage was 0.985 (95% CI = 0.967–0.993) and 0.944 (95% CI = 0.921–0.961) during the nestling stage. In addition, we analyzed models of predator‐specific nest predation using multinomial logistic regression. Effect of nest height on predation rate was significant for snakes; nest stage was significant for nests depredated by avian predators. By identifying and increasing our knowledge of nest predators and vegetation characteristics associated with greater risk of predation in multiple locations within the black‐capped vireo's range, we can effectively manage habitat to benefit recovery efforts of the species. © 2012 The Wildlife Society.

Human activity influences wildlife. However, the ecological and conservation significances of these influences are difficult to predict and depend on their population-level consequences. This difficulty arises partly because of information gaps, and partly because the data on stressors are usually collected in a count-based manner (e.g., number of dead animals) that is difficult to translate into rate-based estimates important to infer population-level consequences (e.g., changes in mortality or population growth rates). However, ongoing methodological developments can provide information to make this transition. Here, we synthesize tools from multiple fields of study to propose an overarching, spatially explicit framework to assess population-level consequences of anthropogenic stressors on terrestrial wildlife. A key component of this process is using ecological information from affected animals to upscale from count-based field data on individuals to rate-based demographic inference. The five steps to this framework are (1) framing the problem to identify species, populations, and assessment parameters; (2) field-based measurement of the effect of the stressor on individuals; (3) characterizing the location and size of the populations of interest; (4) demographic modeling for those populations; and (5) assessing the significance of stressor-induced changes in demographic rates. The tools required for each of these steps are well developed, and some have been used in conjunction with each other, but the entire group has not previously been unified together as we do in this framework. We detail these steps and then illustrate their application for two species affected by different anthropogenic stressors. In our examples, we use stable hydrogen isotope data to infer a catchment area describing the geographic origins of affected individuals, as the basis to estimate population size for that area. These examples reveal unexpectedly greater potential risks from stressors for the more common and widely distributed species. This work illustrates key strengths of the framework but also important areas for subsequent theoretical and technical development to make it still more broadly applicable.