Dataset Information

Geographic context affects the landscape change and fragmentation caused by wind energy facilities.

ABSTRACT: 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.

SUBMITTER: Diffendorfer JE

PROVIDER: S-EPMC6640624 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Geographic context affects the landscape change and fragmentation caused by wind energy facilities.

Diffendorfer Jay E JE Dorning Monica A MA Keen Jolene R JR Kramer Louisa A LA Taylor Robert V RV

PeerJ 20190716

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 land ...[more]

PMID: 31341727

Similar Datasets

Project description:Researchers typically conduct fatality monitoring to determine a wind energy facility's direct impacts on wildlife. In the United States, wind energy impacts on eagles have received increased attention in recent years because eagle incidental take permits became available. Permit holders are required to conduct fatality monitoring to evaluate compliance with permitted eagle take. Our objective was to develop an efficient eagle fatality monitoring protocol with a quantifiable detection probability based on a stationary scanning search method. We conducted scanning searches for eagle carcasses at four wind energy facilities. We estimated searcher efficiency of the scanning search method using feathered turkey decoys as eagle carcass surrogates, used publicly available data on large raptor carcass distances from turbines to evaluate the proportion of carcasses expected to occur in searched areas, and estimated carcass persistence rates for game birds and raptors. These three bias adjustments were combined to estimate the overall probability of detection for the scanning search method. We found generally high searcher efficiency for the scanning search method, with 76% of decoys detected; however, detection decreased with distance and difficulty of visibility class. Mean carcass persistence time varied between 28 and 76 days for raptors and between three and nine days for game birds, showing that game birds do not persist as long as raptors. We estimated that 95% of large avian carcasses fall within 100 m of turbine bases, and 99% fall within 150 m. Using these estimates and assuming a 30-day search interval for all facility turbines, we estimated that the probability of detecting a large raptor carcass using the scanning search method at a wind facility ranged from 0.50 to 0.69. Our research suggests a monitoring program that uses scanning searches can be a cost-effective approach for gathering data necessary to meet incidental eagle take permit requirements.

Project description:Risk of birds colliding with wind turbines, especially protected species like bald eagle and golden eagle in the U.S., is a fundamental wildlife challenge the wind industry faces when developing and operating projects. The U.S. Fish and Wildlife Service requires wind energy facilities that obtain eagle take permits document permit compliance through fatality monitoring. If trained Operations and Maintenance (O&M) staff can reliably detect and report carcasses during their normal routines, and their detection probability can be estimated, then their 'incidental detections' could contribute substantially towards demonstrating permit compliance. Our primary objective was to quantify incidental detection of eagle carcasses by O&M staff under a variety of landscape contexts and environmental conditions throughout a single year. We used the incidental detection probabilities, along with raptor carcass persistence data and area adjustments, to calculate overall probability of incidental detection (i.e., incidental g). We used feathered decoys as eagle-carcass surrogates for monthly detection trials at 6 study sites throughout the U.S. We evaluated the primary drivers of incidental detection using logit regression models including season, viewshed complexity, and a derived variable called the "density quartile" as covariates. We used an Evidence of Absence-based approach to estimate the overall probability of incidental detection. The incidental detection probabilities ranged from 0.28 to 0.78 (mean = 0.48). Detection probabilities decreased as viewshed complexity increased and as distance from the turbine increased. The resulting overall probability of incidental detection ranged from 0.07 to 0.47 (mean = 0.31). The primary drivers of variability in incidental g were detection probability and the area adjustment. Results of our research show that O&M staff were effective at detecting trial carcasses incidentally. Incorporating incidental detection in eagle fatality monitoring efforts is a reliable means of improving estimates of a facility's direct impacts on eagles.

Project description:Small passerines, sometimes referred to as perching birds or songbirds, are the most abundant bird group in the United States (US) and Canada, and the most common among bird fatalities caused by collision with turbines at wind energy facilities. We used data compiled from 116 studies conducted in the US and Canada to estimate the annual rate of small-bird fatalities. It was necessary for us to calculate estimates of small-bird fatality rates from reported all-bird rates for 30% of studies. The remaining 70% of studies provided data on small-bird fatalities. We then adjusted estimates to account for detection bias and loss of carcasses from scavenging. These studies represented about 15% of current operating capacity (megawatts [MW]) for all wind energy facilities in the US and Canada and provided information on 4,975 bird fatalities, of which we estimated 62.5% were small passerines comprising 156 species. For all wind energy facilities currently in operation, we estimated that about 134,000 to 230,000 small-passerine fatalities from collision with wind turbines occur annually, or 2.10 to 3.35 small birds/MW of installed capacity. When adjusted for species composition, this indicates that about 368,000 fatalities for all bird species are caused annually by collisions with wind turbines. Other human-related sources of bird deaths, (e.g., communication towers, buildings [including windows]), and domestic cats) have been estimated to kill millions to billions of birds each year. Compared to continent-wide population estimates, the cumulative mortality rate per year by species was highest for black-throated blue warbler and tree swallow; 0.043% of the entire population of each species was estimated to annually suffer mortality from collisions with turbines. For the eighteen species with the next highest values, this estimate ranged from 0.008% to 0.038%, much lower than rates attributed to collisions with communication towers (1.2% to 9.0% for top twenty species).

Dataset Information

Geographic context affects the landscape change and fragmentation caused by wind energy facilities.

Publications

Geographic context affects the landscape change and fragmentation caused by wind energy facilities.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets