Nutrias (Myocastor coypus) were imported to South Korea for farming in 1985; individuals escaped captivity and established wild populations in natural ecosystems in the late 1990s. Numerous studies have focused on their monitoring and management; however, information on the continuous movement of individuals is not available. In this study, telemetry data from field conditions were used to identify the nearest-neighbor distances of individuals in association with environmental factors, including plant type, land cover, and biological parameters. The minimum nearest-neighbor distances for the different sexes were, overall, according to the minimum distances for the same sex. Local co-occurrences of individuals, either of the same or different sex, were seasonal. Tall grasslands, followed by herbaceous vegetation, were associated with the co-occurrence of different sexes. Conversely, floating-leaved hydrophytes, followed by xeric herbaceous vegetation, were correlated with the co-occurrence of the same sex. Local female-male co-occurrences were negatively associated with male-male co-occurrences but not with female-female co-occurrences, suggesting male dominance in group formations. Movement and co-occurrence information extracted using Geo-self-organizing maps furthers our understanding of population dispersal and helps formulate management strategies for nutria populations.
Keywords: Myocastor coypus; machine learning; movement behavior; nearest-neighbor distance; sexual difference; small mammal.