Gastrodia elata has been a valuable medicinal resource in the East for approximately 3000 years. In South Korea, G. elata is cultivated in open-fields or greenhouses near residential areas. However, due to severe continuous damage, cultivation sites need to be frequently relocated, leading to a shortage of available cultivation areas. Alternatively, farmers are focusing on mountain cultivation. This study analyzed suitable cultivation sites for G. elata in mountainous areas using a geographic information system (GIS) and applied various classification methods to identify their characteristics and similarities. The analysis showed that the Natural Breaks (Jenks) classification method maximized the differences between grades, whereas the Quantile method reclassified the area of suitable sites to a relatively high proportion. In contrast, the Equal Interval method reclassified the areas of suitable and unsuitable sites to a lower proportion, whereas the Geometric Interval method best demonstrated extreme-temperature regions as unsuitable sites. Among the classification methods, the Natural Breaks (Jenks) and Geometric Interval methods yielded the most similar results. These findings provide critical methodological outcomes for G. elata cultivation and sustainable agriculture and forestry. Future empirical research and the application of climate change scenarios are necessary to enhance the sustainability of the G. elata cultivation industry.

Pine wilt disease (PWD), caused by the invasive nematode Bursaphelenchus xylophilus, poses a growing threat to East Asian coniferous forests, which is further exacerbated by climate change. While studies have successfully applied Maximum Entropy (MaxEnt) models to map the potential spread of PWD, they have primarily focused on broad spatial scales and climatic factors. This highlights the need for fine-scale, integrative modeling approaches that also account for environmental and anthropogenic factors. Therefore, we applied the MaxEnt model combined with change vector analysis to evaluate the spatial risk and potential future spread of PWD in Andong-si, Republic of Korea, under the SSP1-2.6 climate scenario. We integrated forest structure, soil conditions, topography, climate variables, and anthropogenic factors to generate high-resolution risk maps and identify the most influential environmental drivers. Notably, we demonstrated that historical infection proximity and isothermality strongly influence habitat suitability. We also, for the first time, projected an eastward shift of high-risk areas in Andong-si under future climate conditions. These findings provide timely insights for designing proactive surveillance networks, implementing risk-based monitoring, and developing climate-resilient management strategies. Our integrative modeling framework offers decision-support tools that can enhance early detection and targeted interventions against invasive forest pests under environmental change.

Control measures for pine wilt disease (PWD) are widely implemented, yet multi-year field comparisons that track biodiversity trajectories across contrasting management regimes remain limited. We conducted a 3-year (2023–2025) replicated study across nine pine-forest sites in Gyeongsangnam-do, Republic of Korea, comparing three management regimes (Clear-cut, Fumigation/Aerial, Unmanaged) to evaluate regime-associated patterns in ground-active beetle diversity, activity density, and community composition while considering understory vegetation cover. Regime-associated differences were consistent but dynamic: Unmanaged stands generally supported higher richness and Shannon diversity (H′), Clear-cut stands showed the lowest diversity immediately after harvest, and Fumigation/Aerial stands maintained the highest activity density. Assemblage composition separated strongly among regimes within each year, and indicator taxa highlighted regime-associated assemblage states, notably Pheropsophus jessoensis (Fumigation/Aerial), Carabus tuberculosus (Clear-cut), and Blindus strigosus (Unmanaged). Because regimes were assigned at the site level and were partially confounded by geographic region, we interpreted these outcomes as region-structured, regime-associated patterns rather than strictly causal effects. We recommend integrating PWD management with retention forestry (e.g., partial canopy and deadwood retention) and routine biodiversity monitoring to reconcile effective disease suppression with the long-term conservation of forest biodiversity.