Understanding hunters’ spatial strategies and the factors influencing hunting success is crucial for sustainable wildlife management. This study analyzed 6,338 roe deer (Capreolus capreolus) harvest events in the Piedmont Region (northwestern Italy), assessing environmental and anthropogenic factors associated with hunting site selection and hunting effort, measured as the number of hunting outings required per successful harvest. Spatial selection was modeled using matched case–control Resource Selection Functions (RSFs), whereas hunting effort was analyzed using generalized linear mixed models (GLMMs) with a Poisson distribution, as confirmed by the analyses performed. Results revealed partial overlap of key spatial predictors: open habitats, moderate slopes, and proximity to human settlements were significant drivers of both site selection and hunting success. However, distance to trails showed contrasting effects, with hunters selecting areas near trails but achieving higher hunting efficiency in more remote locations. This suggests that more experienced hunters operate in less accessible, less disturbed habitats with higher prey presence and success. Integrating RSF and hunting effort models provides a more comprehensive understanding of hunting dynamics, highlighting the interplay between human behavior, landscape features, and prey adaptive strategies. These findings offer valuable insights for developing targeted management strategies and mitigating human-wildlife conflicts in ecologically and agriculturally sensitive areas.
Spatial strategies and harvest dynamics in roe deer hunting
Gaydou, FrancescaFirst
;Marucco, Francesca
Last
2026-01-01
Abstract
Understanding hunters’ spatial strategies and the factors influencing hunting success is crucial for sustainable wildlife management. This study analyzed 6,338 roe deer (Capreolus capreolus) harvest events in the Piedmont Region (northwestern Italy), assessing environmental and anthropogenic factors associated with hunting site selection and hunting effort, measured as the number of hunting outings required per successful harvest. Spatial selection was modeled using matched case–control Resource Selection Functions (RSFs), whereas hunting effort was analyzed using generalized linear mixed models (GLMMs) with a Poisson distribution, as confirmed by the analyses performed. Results revealed partial overlap of key spatial predictors: open habitats, moderate slopes, and proximity to human settlements were significant drivers of both site selection and hunting success. However, distance to trails showed contrasting effects, with hunters selecting areas near trails but achieving higher hunting efficiency in more remote locations. This suggests that more experienced hunters operate in less accessible, less disturbed habitats with higher prey presence and success. Integrating RSF and hunting effort models provides a more comprehensive understanding of hunting dynamics, highlighting the interplay between human behavior, landscape features, and prey adaptive strategies. These findings offer valuable insights for developing targeted management strategies and mitigating human-wildlife conflicts in ecologically and agriculturally sensitive areas.| File | Dimensione | Formato | |
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Gaydou_Airaudo_Marucco_2026_EJWM_s10344-026-02091-x.pdf
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Descrizione: Gaydou_Airaudo_Marucco_2026_EJWM
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