Abstract
Urban landscape networks of connected habitat nodes are expanding and play an important role in shaping the biosphere. Within these networks, humans and wildlife coexist, living and moving in close proximity with the potential for conflict. Remotely sensed data provides accurate knowledge of landscape cover. Circuit-based ecological connectivity models can simulate the movement of wildlife across complex urban landscapes. The resistance surfaces needed to perform this modelling were derived using random forest machine learning land cover classification, on combined Planet SkySat multispectral satellite imagery, and light detection and ranging-derived digital surface model datasets with 78.2% overall accuracy. By comparing movement models for wildlife species and humans, sites of overlapping movement were identified primarily along roads and between forested patches in the south of campus. Areas of particular interest were located at intersections where vehicle and pedestrian traffic is high, and at active construction sites both near the Museum of Anthropology and in Wesbrook Village. These findings are consistent with previous projects studying ecological connectivity on campus. Recommendations involve monitoring construction projects, roads, and neighbourhoods. These results support Campus Vision 2050 initiatives to increase green space to improve ecological connectivity in the centre of campus, design protected connectivity corridors, and discourage unnecessary single-passenger vehicle traffic. Future research may incorporate object-based classification, or consider timing in human and animal movement patterns.
MGEM Student: Aidan V. Rankin
Key words: Coexistence of species
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Rankin, A.V., 2025, “Promoting human-wildlife coexistence through ecological connectivity modelling on the University of British Columbia Vancouver campus“, https://doi.org/10.5683/SP3/LCXQ8W, Borealis, V1