Mon, Aug 15, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/MethodsProtected areas (PAs) are one of the most important strategies for biodiversity conservation, and worldwide efforts are being made to expand them. In order to designate PAs effectively, spatial conservation priorities can be evaluated for target regions. However, many regions have problems with the consistency and reliability of species survey data for biodiversity assessment. Climate is a key determinant of biodiversity patterns and can be mapped in space. The spatial distribution of climate variables of interest can be identified through analyzing climate space that represents the multi-dimensional climatic conditions of the region.In this study, we proposed a new method for evaluating potential PAs using climate space analysis. We analyzed the frequency of the two-dimensional climate space of the annual average temperature and annual precipitation in South Korea and created scenarios for selecting potential PAs. Using MARXAN, which is one of the conservation decision-support tool, we simulated potential PAs under four conservation scenarios: (i) randomly irrespective of climate space (ii) areas with rare climates first, (iii) various climate spaces in equal proportions, (iv) areas with frequent climates first. We analyzed the most effective strategies for biodiversity conservation by calculating the average species richness for the derived four PAs cases.
Results/ConclusionsAs a result of climate spatial analysis, the most frequent climatic conditions in South Korea were found to be 11-12 °C and 1100-1200 mm. From the PAs simulation results using the MARXAN, the PAs with the highest species richness, which was 738 species per square kilometer, were derived from the scenario that gives priority to the areas with rare climates. This is consistent with the location tendency of existing PAs, which are mainly located in areas with rare climates. The PAs with the lowest species richness were resulted from the scenario selecting various climate spaces in equal proportions. These results imply that the areas with rare climates have greater biodiversity when the spatial extents are limited to South Korea. Prioritizing areas with rare climates when designating additional PAs will enable PA systems more effective for biodiversity conservation. Since the climate rarity can vary depending on how the spatial extents are defined, additional studies in various spatial ranges are required. Future studies need to evaluate species diversity including the distribution of endangered species as well as species richness, and climate space strategies that can maintain the effectiveness of PAs in the future under climate change are also needed.
Results/ConclusionsAs a result of climate spatial analysis, the most frequent climatic conditions in South Korea were found to be 11-12 °C and 1100-1200 mm. From the PAs simulation results using the MARXAN, the PAs with the highest species richness, which was 738 species per square kilometer, were derived from the scenario that gives priority to the areas with rare climates. This is consistent with the location tendency of existing PAs, which are mainly located in areas with rare climates. The PAs with the lowest species richness were resulted from the scenario selecting various climate spaces in equal proportions. These results imply that the areas with rare climates have greater biodiversity when the spatial extents are limited to South Korea. Prioritizing areas with rare climates when designating additional PAs will enable PA systems more effective for biodiversity conservation. Since the climate rarity can vary depending on how the spatial extents are defined, additional studies in various spatial ranges are required. Future studies need to evaluate species diversity including the distribution of endangered species as well as species richness, and climate space strategies that can maintain the effectiveness of PAs in the future under climate change are also needed.