Linear infrastructure and associated wildlife accidents create an ecological trap for an apex predator and scavenger

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Abstract

Animals can be caught in an “ecological trap” when they select for seemingly attractive habitats at the expense of their fitness. Such maladaptive behaviour is often a consequence of human induced rapid changes in animals’ natal environment such as building of energy and transportation infrastructure. We tested the ecological trap hypotheses for human created linear infrastructure on a widely distributed apex predator and a scavenger – the Golden eagle ( Aquila chrysaetos ), whose range spans across the entire northern hemisphere. Roads and railways create novel and attractive feeding subsidies through traffic induced mortality of other species, while powerline areas provide perching or nesting sites and scavenging opportunities from electrocuted or collision-killed birds. These conditions lead to negative demographic consequences for eagles. We used integrated step selection functions for habitat selection and movement behaviour with ten years of data from 74 GPS-tracked Golden Eagles (36 adult and 38 immature) in Fennoscandia. To measure habitat attractiveness, we use wildlife traffic accident statistics on major wildlife species including the eagles, and mortality of five GPS- tracked eagles to show demographic consequences. Eagles selected for linear features all year round and across entire study region. Individuals also searched and sat alongside roads and railway lines more frequently. Immature eagles selected roads and railway sites more consistently compared to adults and showed learning behaviour with age. We discuss implications of these findings for conservation and population ecology of apex predators and scavengers and their potential evolutionary implications. We suggest that rapid removal of carcasses from roads and tracks is urgently needed to avoid this trap for many raptor and scavenger species throughout the world and develop methods and approaches to reduce wildlife traffic accidents all together.

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