Decoupling residents and dispersers from detection data improve habitat selection modelling: the case study of the wolf in a natural corridor

Abstract

Resource selection analyses based on detection data are widely used to parametrize resistance surfaces used to identify ecological corridors. To successfully parametrize resistance, it is crucial to decouple resident and disperser behaviours yet to date connectivity studies using detection data have not addressed this issue. Here, we decoupled data of resident and dispersing wolves by analysing detection data collected within a natural corridor crossing a human dominated plain in Italy. To decouple residents and dispersers, we ran a Kernel Density analysis to investigate whether clusters of wolf detection points characterized by sharply higher points’ density exist and checked whether the areas outlined by these clusters (core areas) hold specific characteristics. Habitat selection analysis was then performed to compare the intensity of habitat selection carried out by putative residents and dispersers. We identified a high-density cluster of 30 detection points outlining a small core area stably located in the central part of the park. The dramatic differences of the R² and the AUC of the habitat selection models performed inside (R² = 0.506; AUC = 0.952) and outside (R² = 0.037; AUC = 0.643) the core area corroborated the hypothesis that the core area effectively encloses detection points belonging to residents. Our results show that through simple space use analyses it is possible to roughly discriminate between detection points belonging to resident-behaving and disperser-behaving individuals and that habitat selection models separately performed on these data have extremely different results with strong possible effects on resistance surfaces parametrized from these models.

Highlights

• We decoupled data of resident and dispersing wolves by analyzing detection data collected within a natural ecological corridor.

• Through space use analyses on detection data, it is possible to roughly discriminate between resident-behaving and disperser-behaving individuals.

• Habitat selection carried out by resident-behaving and disperser-behaving individuals is dramatically different.

KEY WORDS:

• Canis lupus italicus
• dispersal
• kernel density estimation
• resource selection functions
• space use analyses

ACKNOWLEDGEMENTS

This study was carried out as part of a collaboration project between the University of Milano-Bicocca, (Department of Earth and Environmental Sciences), University of Pavia (Department of Earth and Environmental Sciences), the Parco Lombardo della Valle del Ticino and the Ente di Gestione delle Aree Protette del Ticino e del Lago Maggiore. We thank the staff of the Parco Lombardo della Valle del Ticino (B. Badino, M. Balocco, D. Cameroni, O. Cortesi, C. Poma, I. Provini) and the Ente di Gestione delle Aree Protette del Ticino e del Lago Maggiore (P. Trovò) and the students of the University of Milano-Bicocca (G. Balan, V. Brambilla, M. Verrecchia) and the University of Pavia (I. Piacentini) for their help in data collection.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

AUTHOR CONTRIBUTION

Conceptualization: O. Dondina, A. Meriggi, L. Bani and V. Orioli; Data collection: O. Dondina and A. Meriggi; Data analysis: O. Dondina and V. Orioli; Writing – original draft preparation: O. Dondina; Writing – review and editing: A. Meriggi, L. Bani and V. Orioli; Supervision: A. Meriggi and L. Bani. All authors read and approved the final manuscript.

SUPPLEMENTAL DATA

Supplemental data for this article can be accessed at https://doi.org/10.1080/03949370.2021.1988724

DATA ACCESSIBILITY

All data analysed during this study are included in this published article [and its Supplemental Data].