Flight Type and Seasonal Movements Are Important Predictors for Avian Collisions in Wind Farms

Abstract

Wind farms are an alternative energy source mitigating environmental pollution. However, they can have adverse effects, causing an increase in mortality for wildlife through collision with wind turbines. The aim of this study was to investigate the risks of bird collisions with wind turbines linked to species-specific variables. For this purpose, we have analysed the dead birds involved in wind farm collisions that were admitted to two rescue centres in Spain over a period of 16 years (2001–2016; full dataset: n = 3130). All the birds analysed in this study were killed by turbines in wind farms. We performed two linear models using all species and a reduced dataset (bird of prey and passerine having more than four collisions) that included group, seasonal movements, flight type, length, and the number of pairs for the Spanish and European populations. The coefficients and the percent of variance explained by each relevant variable were determined in the models and the real values were compared with predicted values to visualise the goodness of fit. We found that the flight type was the most important variable explaining 35% of the total variability for the model including all species and 29% for the reduced dataset respectively, followed by seasonal movement type (4%/17% respectively) and the Spanish population (4%/6%). Subsequent analyses suggested that species with hovering, song-flights and active soaring flights are more susceptible to collisions with wind farms, and that species showing partial migration have a significant peak of collisions across spring and autumn. The estimated species-specific collision index can help in modelling the theoretical risk of collision with wind turbines, depending on the species existing in the area and their predicted values of vulnerability, which is linked to flight types and seasonal movements.