RESUMEN
Populations of soaring birds are often impacted by wind-power generation. Sex and age bias in turbine collisions can exacerbate these impacts through demographic changes that can lead to population decline or collapse. While several studies have reported sex and age differences in the number of soaring birds killed by turbines, it remains unclear if they result from different abundances or group-specific turbine avoidance behaviours, the latter having severer consequences. We investigated sex and age effects on turbine avoidance behaviour of black kites (Milvus migrans) during migration near the Strait of Gibraltar. We tracked the movements of 135 individuals with GPS data loggers in an area with high density of turbines and then modelled the effect of proximity of turbines on bird utilization distribution (UD). Both sexes and age classes showed similar patterns of displacement, with reduced UD values in the proximity of turbines and a clear peak at 700-850 m away, probably marking the distance at which most birds turn direction to avoid approaching the turbines further. The consistency of these patterns indicates that displacement range can be used as an accurate proxy for collision risk and habitat loss, and should be incorporated in environmental impact assessment studies.
RESUMEN
BACKGROUND: Animal movement expressed through home ranges or space-use can offer insights into spatial and habitat requirements. However, different classes of estimation methods are currently instinctively applied to answer home range, space-use or movement-based research questions regardless of their widely varying outputs, directly impacting conclusions. Recent technological advances in animal tracking (GPS and satellite tags), have enabled new methods to quantify animal space-use and movement pathways, but so far have primarily targeted mammal and avian species. METHODS: Most reptile spatial ecology studies only make use of two older home range estimation methods: Minimum Convex Polygons (MCP) and Kernel Density Estimators (KDE), particularly with the Least Squares Cross Validation (LSCV) and reference (h ref ) bandwidth selection algorithms. These methods are frequently applied to answer space-use and movement-based questions. Reptile movement patterns are unique (e.g., low movement frequency, long stop-over periods), prompting investigation into whether newer movement-based methods -such as dynamic Brownian Bridge Movement Models (dBBMMs)- apply to Very High Frequency (VHF) radio-telemetry tracking data. We simulated movement data for three archetypical reptile species: a highly mobile active hunter, an ambush predator with long-distance moves and long-term sheltering periods, and an ambush predator with short-distance moves and short-term sheltering periods. We compared traditionally used estimators, MCP and KDE, with dBBMMs, across eight feasible VHF field sampling regimes for reptiles, varying from one data point every four daylight hours, to once per month. RESULTS: Although originally designed for GPS tracking studies, dBBMMs outperformed MCPs and KDE h ref across all tracking regimes in accurately revealing movement pathways, with only KDE LSCV performing comparably at some higher frequency sampling regimes. However, the LSCV algorithm failed to converge with these high-frequency regimes due to high site fidelity, and was unstable across sampling regimes, making its use problematic for species exhibiting long-term sheltering behaviours. We found that dBBMMs minimized the effect of individual variation, maintained low error rates balanced between omission (false negative) and commission (false positive), and performed comparatively well even under low frequency sampling regimes (e.g., once a month). CONCLUSIONS: We recommend dBBMMs as a valuable alternative to MCP and KDE methods for reptile VHF telemetry data, for research questions associated with space-use and movement behaviours within the study period: they work under contemporary tracking protocols and provide more stable estimates. We demonstrate for the first time that dBBMMs can be applied confidently to low-resolution tracking data, while improving comparisons across regimes, individuals, and species. SUPPLEMENTARY INFORMATION: Supplementary information accompanies this paper at 10.1186/s40462-020-00229-3.
RESUMEN
BACKGROUND: Global positioning system (GPS) technology for monitoring home range and movements of wildlife has resulted in prohibitively large sample sizes of locations for traditional estimators of home range. We used area-under-the-curve to explore the fit of 8 estimators of home range to data collected with both GPS and concurrent very high frequency (VHF) technology on a terrestrial mammal, the Florida panther Puma concolor coryi, to evaluate recently developed and traditional estimators. RESULTS: Area-under-the-curve was the highest for Florida panthers equipped with Global Positioning System (GPS) technology compared to VHF technology. For our study animal, estimators of home range that incorporated a temporal component to estimation performed better than traditional first- and second-generation estimators. CONCLUSIONS: Comparisons of fit of home range contours with locations collected would suggest that use of VHF technology is not as accurate as GPS technology to estimate size of home range for large mammals. Estimators of home range collected with GPS technology performed better than those estimated with VHF technology regardless of estimator used. Furthermore, estimators that incorporate a temporal component (third-generation estimators) appeared to be the most reliable regardless of whether kernel-based or Brownian bridge-based algorithms were used and in comparison to first- and second-generation estimators. We defined third-generation estimators of home range as any estimator that incorporates time, space, animal-specific parameters, and habitat. Such estimators would include movement-based kernel density, Brownian bridge movement models, and dynamic Brownian bridge movement models among others that have yet to be evaluated.