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Movement is a key means by which animals cope with variable environments. As they move, animals construct individual niches composed of the environmental conditions they experience. Niche axes may vary over time and covary with one another as animals make tradeoffs between competing needs. Seasonal migration is expected to produce substantial niche variation as animals move to keep pace with major life history phases and fluctuations in environmental conditions. Here, we apply a time-ordered principal component analysis to examine dynamic niche variance and covariance across the annual cycle for four species of migratory crane: common crane ( Grus grus , n = 20), demoiselle crane ( Anthropoides virgo , n = 66), black-necked crane ( Grus nigricollis , n = 9), and white-naped crane ( Grus vipio , n = 9). We consider four key niche components known to be important to aspects of crane natural history: enhanced vegetation index (resources availability), temperature (thermoregulation), crop proportion (preferred foraging habitat), and proximity to water (predator avoidance). All species showed a primary seasonal niche "rhythm" that dominated variance in niche components across the annual cycle. Secondary rhythms were linked to major species-specific life history phases (migration, breeding, and nonbreeding) as well as seasonal environmental patterns. Furthermore, we found that cranes' experiences of the environment emerge from time-dynamic tradeoffs among niche components. We suggest that our approach to estimating the environmental niche as a multidimensional and time-dynamical system of tradeoffs improves mechanistic understanding of organism-environment interactions., Competing Interests: Competing interests statement:The authors declare no competing interest.

Monitoring of bird migration at marine wind farms has a short history, and unsurprisingly most studies have focused on the potential for collisions. Risk for population impacts may exist to soaring migrants such as raptors with K-strategic life-history characteristics. Soaring migrants display strong dependence on thermals and updrafts and an affinity to land areas and islands during their migration, a behaviour that creates corridors where raptors move across narrow straits and sounds and are attracted to islands. Several migration corridors for soaring birds overlap with the development regions for marine wind farms in NW Europe. However, no empirical data have yet been available on avoidance or attraction rates and behavioural reactions of soaring migrants to marine wind farms. Based on a post-construction monitoring study, we show that all raptor species displayed a significant attraction behaviour towards a wind farm. The modified migratory behaviour was also significantly different from the behaviour at nearby reference sites. The attraction was inversely related to distance to the wind farm and was primarily recorded during periods of adverse wind conditions. The attraction behaviour suggests that migrating raptor species are far more at risk of colliding with wind turbines at sea than hitherto assessed., (© 2016 The Author(s).)

Advances in technology and engineering, along with European Union renewable energy targets, have stimulated a rapid growth of the wind power sector. Wind farms contribute to carbon emission reductions, but there is a need to ensure that these structures do not adversely impact the populations that interact with them, particularly birds. We developed movement models based on observed avoidance responses of common eider Somateria mollissima to wind farms to predict, and identify potential measures to reduce, impacts. Flight trajectory data that were collected post-construction of the Danish Nysted offshore wind farm were used to parameterize competing models of bird movements around turbines. The model most closely fitting the observed data incorporated individual variation in the minimum distance at which birds responded to the turbines. We show how such models can contribute to the spatial planning of wind farms by assessing their extent, turbine spacing and configurations on the probability of birds passing between the turbines. Avian movement models can make new contributions to environmental assessments of wind farm developments, and provide insights into how to reduce impacts that can be identified at the planning stage.

An increased focus on renewable energy has led to the planning and construction of marine wind farms in Europe. Since several terrestrial studies indicate that raptors are especially susceptible to wind turbine related mortality, a Spatial Planning Tool is needed so that wind farms can be sited, in an optimal way, to minimize risk of collisions. Here we use measurements of body mass, wingspan and wing area of eight European raptor species, to calculate their Best Glide Ratio (BGR). The BGR was used to construct a linear equation, which, by the use of initial take-off altitude, could be used to calculate a Theoretical Maximum Distance (TMD) from the coast, attained by these soaring-gliding raptor species. If the nearest turbine, of future marine wind farms, is placed farther away from the coast than the estimated TMD, the collision risk between the turbine blades and these gliding raptors will be minimized. The tool was demonstrated in a case study at the Rødsand II wind farm in Denmark. Data on raptor migration altitude were gathered by radar. From the TMD attained by registered soaring-gliding raptors in the area, we concluded that the Rødsand II wind farm is not sited ideally, from an ornithological point of view, as potentially all three registered species are at risk of gliding through the area swept by the turbine rotor blades, and thereby at risk of colliding with the wind turbines.

Wind power generation is likely to constitute one of the most extensive human physical exploitation activities of European marine areas in the near future. The many millions of migrating birds that pass these man-made obstacles are protected by international obligations and the subject of public concerns. Yet some bird species are more sensitive to bird-wind turbine mortality than others. This study developed a simple and logical framework for ranking bird species with regard to their relative sensitivity to bird-wind turbine-collisions, and applied it to a data set comprising 38 avian migrant species at the Nysted offshore wind farm in Denmark. Two indicators were selected to characterize the sensitivity of each individual species: 1) relative abundance and 2) demographic sensitivity (elasticity of population growth rate to changes in adult survival). In the case-study from the Nysted offshore wind farm, birds of prey and waterbirds dominated the group of high priority species and only passerines showed a low risk of being impacted by the wind farm. Even where passerines might be present in very high numbers, they often represent insignificant segments of huge reference populations that, from a demographic point of view, are relatively insensitive to wind farm-related adult mortality. It will always be important to focus attention and direct the resources towards the most sensitive species to ensure cost-effective environmental assessments in the future, and in general, this novel index seems capable of identifying the species that are at high risk of being adversely affected by wind farms.

We have been the first to investigate whether long-lived geese and ducks can detect and avoid a large offshore wind farm by tracking their diurnal migration patterns with radar. We found that the percentage of flocks entering the wind farm area decreased significantly (by a factor 4.5) from pre-construction to initial operation. At night, migrating flocks were more prone to enter the wind farm but counteracted the higher risk of collision in the dark by increasing their distance from individual turbines and flying in the corridors between turbines. Overall, less than 1% of the ducks and geese migrated close enough to the turbines to be at any risk of collision.