Habitat utilization distribution of sika deer (Cervus nippon)

Habitat-specific and movement-related behavioral studies are essential for the development of sustainable biodiversity management practices. Although the number of studies on sika deer is increasing, habitat utilization distribution (UD)-related studies remain limited. In this study, we investigated the habitat UD behavior of sika deer (Cervus nippon) using a literature survey and an experimental study on Suncheon Bonghwasan Mountain, South Korea. We reviewed home range-related literature on sika deer published between 1982 and 2019 in order to assess their estimation methods, study region, and research background. We observed that the number of studies on sika deer has increased. The minimum convex polygon (MCP) has been utilized the most to estimate habitat UD, followed by the kernel density (KD), the Brownian bridge model, and a combination of these methods. The average home ranges (95 % utilization distribution) of sika deer from the literature survey were 236.99 ha and 1183.96 ha using the minimum convex polygon and kernel density approaches, respectively. The five female deer in our experimental study on Suncheon Bonghwasan Mountain had a mean home range of 66.831 ± 15.241 ha using the MCP approach and 78.324 ± 20.82 ha using the KD approach. The UD behavior of sika deer explored in this research is expected to benefit future scholars and policymakers when formulating deer management and wildlife conservation strategies.

Prediction of the visit and occupy of the sika deer (Cervus nippon) during the summer season using a virtual ecological approach

Prediction of the spaces used by animals is an important component of wildlife management, but requires detailed information such as animal visit and occupy in a short span of the target species. Computational simulation is often employed as an effective and economical approach. In this study, the visit and occupy of sika deer (Cervus nippon) during the plant growing season were predicted using a virtual ecological approach. A virtual ecological model was established to predict the visit and occupy of sika deer based on the indices of their food resources. The simulation results were validated against data collected from a camera trapping system. The study was conducted from May to November in 2018 in the northern Kanto region of Japan. The predictive performance of the model using the kernel normalized difference vegetation index (kNDVI) was relatively high in the earlier season, whereas that of the model using landscape structure was relatively low. The predictive performance of the model using combination of the kNDVI and landscape structure was relatively high in the later season. Unfortunately, visit and occupy of sika deer could not predict in November. The use of both models, depending on the month, achieved the best performance to predict the movements of sika deer.