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The increasing number of wind energy sites developed globally, has consequently resulted in a green-on-green predicament, due to an increase in avian mortality caused by collisions with wind turbines. The proportion of collision-related fatalities is not evenly distributed across species, indicating that some species groups are more prone to turbine collision. Such differences between species have been proposed to be affiliated with species-specific foraging and flight behavior. The aim of this study is to investigate how the flight behavioral traits; head position, active flight, track symmetry, and track tortuosity can be used to model collision risk along with other influencing factors i.e., weather variables (temperature, wind speed, and cloud coverage) and temporal variables (time of day and time of year). The study also sought to investigate the species-specificity of the four traits in relation to the phylogenetic relatedness of the study species. This was achieved through a case study at a wind farm on the Swedish island of Gotland in which the behavior of birds from 11 different genera was studied. The flight behavior of these species was assessed using data collected by the IdentiFlight system, e.g., flight trajectories and images of the birds throughout their flight track. The results confirm the species-specificity of the four flight behaviors and indicated that all four traits can be used to predict collision risk along with species as a categorical factor. The framework provided in this study along with the results of the case study can be used to identify risk-prone species based on phylogenetic relatedness and flight behavior.

Some wind farms have implemented automated camera-based monitoring systems, e.g., IdentiFlight to mitigate the impact of wind turbines on protected birds. These systems have promoted the collection of large amounts of unique data that can be used to describe flight behavior in a novel way. The aim of this study was to evaluate how this unique data can be used to create a robust quantitative behavioral analysis, that can be used to identify risk-prone flight behavior and avoidance behavior and thereby used to assess collision risk in the future. This was achieved through a case study at a wind farm on the Swedish island Gotland, where golden eagles (Aquila chrysaetos), white-tailed eagles (Haliaeetus albicilla), and red kites (Milvus milvus), were chosen as the bird species. These three species are generally rare breeds in Europe and have also been shown to be particularly vulnerable to collisions with wind turbines. The results demonstrate that data from the IdentiFlight system can be used to identify risk-prone flight behaviors, e.g., tortuous flight and foraging behavior. Moreover, it was found that these flight behaviors were affected by both weather conditions, but also their distance to the nearest wind turbine. This data can, thus, be used to evaluate collision risk and avoidance behavior. This study presents a promising framework for future research, demonstrating how data from camera-based monitoring systems can be utilized to quantitatively describe risk-prone behavior and thereby assess collision risk and avoidance behavior.

Behavioral instability is a concept used for indicating environmental stress based on behavioral traits. This study investigates the possibility of using behavioral instability as a tool for assessing behavioral reaction norms in captive animals. The understanding of personality in captive animals can be a useful tool in the development of enrichment programs in order to improve animal welfare. In this study, a case study examined how olfactory stimuli affected the behavior of two polar bears Ursus maritimus in captivity. Using continuous focal sampling throughout the day, it was found that for many behaviors, the individuals responded differently to stimuli, indicating that there was a difference in behavioral reaction norms. This is shown using multiple approaches. One approach used traditional methods for behavioral analyses, and the other approach used the concept of behavioral instability as a new quantitative method. This study demonstrates the utility of behavioral instability as a new quantitative method for investigating behavioral reaction norms, expanding the possibility of comparing behavioral responses between species. Moreover, it is shown that outliers—that cause asymmetric distributions—should not be removed in behavioral analysis, without careful consideration. In conclusion, the theoretical implications and future perspectives of behavioral instability are discussed.