Abstract
Biodiversity-related impacts at wind energy facilities have increasingly become a cause of conservation concern, central issue being the collision of birds. Utilizing spatial information of their carcass detections at wind turbines (WTs), we quantified the detections in relation to the metric distances of the respective turbines to different land-use types. We used ecological niche factor analysis (ENFA) to identify combinations of land-use distances with respect to the spatial allocation of WTs that led to higher proportions of collisions among the worst affected bird-groups: Buntings, Crows, Larks, Pigeons and Raptors. We also assessed their respective similarities to the collision phenomenon by checking for overlaps amongst their distance combinations. Crows and Larks showed the narrowest “collision sensitive niche”; a part of ecological niche under higher risk of collisions with turbines, followed by that of Buntings and Pigeons. Raptors had the broadest niche showing significant overlaps with the collision sensitive niches of the other groups. This can probably be attributed to their larger home range combined with their hunting affinities to open landscapes. Identification of collision sensitive niches could be a powerful tool for landscape planning; helping avoid regions with higher risks of collisions for turbine allocations and thus protecting sensitive bird populations.
Highlights
Global environmental change strongly impacts the structure of biological communities[1,2] leading to accelerated biodiversity loss
We evaluated the effects of distances between turbines and different land-use types on collision risks, for the worst hit taxon related groups of birds in our sample, using the multivariate approach of Ecological Niche Factor Analysis (ENFA), which is based on Hutchinson’s n-dimensional hypervolume[18,19,20]
We have investigated the group-wise significant differences between the distribution of the wind turbines (WTs) with fatalities and the WTs without fatalities against different Distance to edge based land-use variables (DELV) using the Kolmogorov-Smirnov test[36], using the maximum vertical deviation between their respective cumulative distributions as the statistic D and their respective P-values reporting the significance of difference
Summary
Global environmental change strongly impacts the structure of biological communities[1,2] leading to accelerated biodiversity loss. In order to resolve this contradiction and to correctly guide the installation of future wind farms several researchers have tried to assess the effects of wind farms on wildlife by monitoring collisions after the construction of wind turbines (WTs)[10,11,12] These long-term detections are based on carcass search operations conducted around the turbines. They underestimate the actual number of individuals being killed to a different degree due to a) spatial incompleteness related to non-uniformity in the searches, b) temporal incompleteness related to duration and periodicity of intervals between the searches, c) incomplete detection related to variability in carcass persistence time of birds of different sizes, and d) variation in detection probabilities related to the types of vegetation cover, substratum and the species involved in the searches[13]. We focused on assessing the similarities and dissimilarities between these collision sensitive niches of all the bird-groups under study, to enable the guidance of potential management interventions across multiple groups
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