Comparing Spatial Analysis Methods for Habitat Selection: GPS Telemetry Reveals Methodological Bias in Raccoon Dog (Nyctereutes procyonoides) Ecology
Year: 2025
Type: article
Abstract: Recent issues that have emerged in regard to raccoon dog (Nyctereutes procyonoides) include interaction with humans and disease transmission. Therefore, understanding their habitat characteristics and preferences is crucial in the effort to limit conflicts with humans. A total of thirteen raccoon dogs were captured from three regions in South Korea, each with distinct habitat characteristics. GPS trackers were attached for tracking the raccoon dogs’ movements. Utilizing GPS tracking data, Kernel Density Estimation (KDE), Minimum Convex Polygon (MCP), and Jacobs Index were applied to learn more about the habitat preferences of the raccoon dogs. According to the results, the habitat composition ratios for KDE and MCP showed that forests had the largest proportion. However, a habitat composition ratio similar to the land proportion of the area that they inhabit indicated that raccoon dogs had the ability to adapt to various habitats. Jacobs Index analysis revealed different habitat selection patterns compared to KDE and MCP, with forests showing neutral to negative selection despite comprising large proportions of home ranges. Our results highlight important methodological considerations when inferring habitat preferences from spatial data, suggesting that multiple analytical approaches provide complementary insights into animal space use.
Source: Forests
DOI: 10.3390/f16101588
Authors: Sumin Jeon, Soo Kyeong Hwang, Yeon Woo Lee, Jihye Son, Hyeok Jae Lee, Chae Won Yoon, Ju Yeong Lee, Ju Yeong Lee, Dong Kyun Yoo, Ok-Sik Chung, Jong Koo Lee, Jong Koo Lee
Institutions: Incheon National University, ChungNam Institute
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: gold
Estimated APC paid: $3,137
Funder: Korea Forest Service
Award: G1018793497
OpenAlex ID: W4415263871
