Identifying Potential OECM Sites for Endangered Birds to Achieve the '30 by 30' Target in South Korea: Integrating Ecological Value and Socio-Economic Costs

The Kunming-Montreal Global Biodiversity Framework (GBF) has established a global target to conserve 30% of the planet's land and seas by 2030. Nations worldwide, including South Korea, are actively committed to achieving this target. However, achieving this goal in South Korea is complicated by specific geographical and socio-economic constraints. While the nation is a critical stopover in the East Asian–Australasian Flyway (EAAF), its current Protected Area (PA) network is disproportionately skewed toward mountainous regions due to topographical characteristics. Consequently, critical habitats for threatened bird species—specifically in coasts, lowlands, farmlands, and islands—remain severely underrepresented, creating distinct conservation gaps. However, these biodiversity-rich areas are often privately owned and subject to high development pressure, making the designation of strict PAs legally and economically difficult. Therefore, identifying Other Effective area-based Conservation Measures (OECMs) that balance ecological needs with socio-economic realities is essential.

To systematically bridge the aforementioned conservation gaps, this study aims to identify feasible potential OECMs. To model nationwide habitat suitability, we employed the ensemble modeling framework of the biomod2 R package, utilizing machine learning algorithms such as Random Forest (RF), Generalized Boosting Model (GBM), and Artificial Neural Networks (ANN). For this analysis, we utilized occurrence data from the Global Biodiversity Information Facility (GBIF) for avian species classified as Critically Endangered (CR), Endangered (EN), and Vulnerable (VU) as input variables to accurately quantify the ecological value of unprotected areas. Crucially, unlike previous studies that focused solely on ecological metrics, this research integrated "Human Pressure Index (HPI)" and "proportion of private land" as explicit cost layers in a spatial optimization framework. This approach allows for the identification of areas offering high conservation value with manageable socio-economic trade-offs.

The analysis reveals that existing PAs fail to cover key lowland habitats essential for threatened birds. By incorporating cost variables, the optimization model derived potential OECMs that minimize land-use conflicts and acquisition costs while maximizing species protection. These findings suggest that a multi-criteria approach, considering both biological suitability and anthropogenic pressure, is vital for realistic conservation planning. The proposed potential OECMs provide a scientific basis for policy decisions and are expected to offer a practical pathway for South Korea to achieve the national 30 by 30 target by securing vulnerable avian habitats outside the traditional protected area network.