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Spatial ecology of conflicts: unravelling patterns of wildlife damage at multiple scales
Author(s) -
Carlos Bautista,
Eloy Revilla,
Teresa BerezowskaCnota,
Néstor Fernández,
Javier Naves,
Nuria Selva
Publication year - 2021
Publication title -
proceedings - royal society. biological sciences/proceedings - royal society. biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.342
H-Index - 253
eISSN - 1471-2954
pISSN - 0962-8452
DOI - 10.1098/rspb.2021.1394
Subject(s) - wildlife , context (archaeology) , human–wildlife conflict , environmental resource management , habitat , ursus , geography , scale (ratio) , spatial ecology , ecology , resource (disambiguation) , temporal scales , landscape epidemiology , wildlife management , environmental science , cartography , computer science , landscape ecology , biology , population , computer network , demography , archaeology , sociology
Human encroachment into natural habitats is typically followed by conflicts derived from wildlife damage to agriculture and livestock. Spatial risk modelling is a useful tool to gain the understanding of wildlife damage and mitigate conflicts. Although resource selection is a hierarchical process operating at multiple scales, risk models usually fail to address more than one scale, which can result in the misidentification of the underlying processes. Here, we addressed the multi-scale nature of wildlife damage occurrence by considering ecological and management correlates interacting from household to landscape scales. We studied brown bear ( Ursus arctos ) damage to apiaries in the North-eastern Carpathians as our model system. Using generalized additive models, we found that brown bear tendency to avoid humans and the habitat preferences of bears and beekeepers determine the risk of bear damage at multiple scales. Damage risk at fine scales increased when the broad landscape context also favoured damage. Furthermore, integrated-scale risk maps resulted in more accurate predictions than single-scale models. Our results suggest that principles of resource selection by animals can be used to understand the occurrence of damage and help mitigate conflicts in a proactive and preventive manner.

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