Author
Listed:
- Yiannis G. Zevgolis
(Biodiversity Conservation Laboratory, Department of Environment, University of the Aegean, 81132 Mytilene, Greece)
- Alexandros D. Kouris
(Department of Sustainable Agriculture, University of Patras, 30131 Agrinio, Greece)
- Apostolos Christopoulos
(Department of Zoology and Marine Biology, Faculty of Biology, National and Kapodistrian University of Athens, 15772 Athens, Greece)
- Marios Leros
(Biodiversity Conservation Laboratory, Department of Environment, University of the Aegean, 81132 Mytilene, Greece)
- Maria Loupou
(Biodiversity Conservation Laboratory, Department of Environment, University of the Aegean, 81132 Mytilene, Greece)
- Dimitra-Lida Rammou
(Laboratory of Marine and Terrestrial Animal Diversity, Department of Zoology, School of Biology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)
- Dionisios Youlatos
(Laboratory of Marine and Terrestrial Animal Diversity, Department of Zoology, School of Biology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
International Center for Biodiversity and Primate Conservation, Dali University, Dali 671003, China)
- Andreas Y. Troumbis
(Biodiversity Conservation Laboratory, Department of Environment, University of the Aegean, 81132 Mytilene, Greece)
Abstract
Understanding fine-scale spatial ecology is essential for defining effective conservation priorities, particularly at the range margins of vulnerable species. Here, we investigate the spatial ecology and habitat associations of the Persian squirrel ( Sciurus anomalus ) on Lesvos Island, Greece, representing the species’ westernmost distribution. Using a randomized grid-based survey, we recorded 424 presence records across the island and applied a suite of spatial analyses, including Kernel Density Estimation, Getis-Ord Gi*, and Anselin Local Moran’s I, to detect hotspots, coldspots, and spatial outliers. Binomial Logistic Regression, supported by Principal Component Analysis, identified key ecological drivers of habitat use, while spatial regression models (Spatial Lag and Spatial Error Models) quantified the influence of land-use characteristics and spatial dependencies on hotspot intensity and clustering dynamics. Our results showed that hotspots were primarily associated with olive-dominated and broadleaved landscapes, while coldspots and Low–Low clusters were concentrated in fragmented or degraded habitats, often outside protected areas. Spatial outliers revealed fine-scale deviations from broader patterns, indicating local habitat disruptions and emerging conservation risks not captured by existing Natura 2000 boundaries. Spatial regression confirmed that both hotspot intensity and clustering patterns were shaped by specific land-use features and spatially structured processes. Collectively, our findings underscore the fragmented nature of suitable habitats and the absence of cohesive population cores, reinforcing the need for connectivity-focused, landscape-scale conservation.
Suggested Citation
Yiannis G. Zevgolis & Alexandros D. Kouris & Apostolos Christopoulos & Marios Leros & Maria Loupou & Dimitra-Lida Rammou & Dionisios Youlatos & Andreas Y. Troumbis, 2025.
"Where to Protect? Spatial Ecology and Conservation Prioritization of the Persian Squirrel at the Westernmost Edge of Its Distribution,"
Land, MDPI, vol. 14(4), pages 1-27, April.
Handle:
RePEc:gam:jlands:v:14:y:2025:i:4:p:876-:d:1635923
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