The energy landscape predicts flight height and wind turbine collision hazard in large soaring raptors

PERON, GUILLAUME; FLEMING, CHRISTEN; DURIEZ, OLIVIER; FLUHR, JULIE; ITTY, CHRISTIAN; LAMBERTUCCI, SERGIO; SAFI, KAMRAN; SHEPARD, EMILY; CALABRESE, JUSTIN

JOURNAL OF APPLIED ECOLOGY

WILEY-BLACKWELL PUBLISHING, INC

Lugar: Londres; Año: 2017 vol. 54 p. 1895 - 1906

0021-8901

1.Collisions of large soaring raptors with wind turbines and other structures are an increasing source of concern for the conservation of these iconic species that provide recognized ecosystem services. Soaring raptors are theoretically expected to select energy sources (uplift) optimally. We can use this behavior to model their flight height and predict the probability that raptors fly in zones that can be dangerous since they overlap with human infrastructure. However, empirical investigations of the factors influencing flight height have been hindered by observation error. 2.We propose a two-pronged approach. First, state-space models are fitted to z-axis GPS tracking data to filter observation error and estimate the relationship between vertical movement parameters and variables describing the energy landscape (thermal and orographic uplift potential). Second, we fit a mechanistic model of flight height above ground based on aerodynamics and resource selection theories. The approach is replicated for five GPS-tracked Andean condors (Vultur gryphus), eight griffon vultures (Gyps fulvus), and six golden eagles (Aquila chrysaetos). 3.In all individuals, movement parameters correlated with thermal uplift potential in the expected direction. In all species, collision hazard was lowest for high thermal uplift potential values. Species-specificities in the presence of a peak in collision hazard for medium values of thermal uplift potential could be explained by differences in wing loading and aspect ratio. 4.Synthesis and applications: These new insights highlight how GPS tracking data, combined with an understanding of the mechanisms underlying vertical movement, can make it possible to leverage behavioral knowledge for conservation purposes. Our model of collision hazard can be used for pre-construction wind farm project planning. However, it should be combined with post-construction monitoring to systematically document and eventually account for turbine avoidance behaviors in collision rate predictions.