Developing national-level policies related to climate change induced expansions of invasive species requires predictive modelling at a regional scale level. This study aimed to predict future changes in the habitat distributions of two major invasive alien fish species, Micropterus salmoides and Lepomis macrochirus, in South Korea. An ensemble system with multiple species distribution models was used for the prediction, and gridded water portion data from the linear-structure information on river channels inputted as habitat characteristics of freshwater ecosystem into the models. Bioclimatic variables at 20-year intervals from 2001 to 2100 were generated from predicted temperature and precipitation data under the representative concentration pathway 4.5 and 8.5 scenarios. The overall distribution probabilities of the potential habitats increased with time in both climate change scenarios, and the potential habitats were predicted to expand to upstream areas. Combined with regional ecological value information, such as biodiversity in freshwater ecosystems, these results can be an important basis for deriving regional priority information for managing alien species in climate change. Additionally, the modelling approach is highly applicable to various national-level policies for ecosystem conservation since it is not greatly restricted by spatial scales.

Severe declines in the population of Abies koreana, a conifer native to the subalpine regions of South Korea, are likely a consequence of climate change. However, local-scale modeling of the species’ spatial distribution has seen limited application to in situ conservation policies. Therefore, we intended for this study to examine the applicability of fine-scale species distribution modeling of A. koreana in the Mt. Jiri National Park area in S. Korea in order to explore candidate areas for its in situ conservation. We simulated the potential habitat of the species in the area with four separate models using different dominance patterns, then created an index based on habitability probabilities and residual durations to determine priority conservation areas. Under the highest sensitivity of potential habitats to temperature (spatially downscaled based on geomorphological characteristics), rapid habitat reduction occurred under climate warming in all experiments. At the regional scale, hydrological characteristics such as precipitation and slope characterized different secondary habitat distributional patterns among the experiments. Final conservation priority sites were identified based on specified criteria for the designed index. Our results suggest that a fine-scale modeling system with adequate spatial resolution of environmental inputs is advantageous in representing local habitat characteristics of A. koreana and can be applied to in situ conservation strategies.

Yeonsook Choung, Kyu Song Lee, Hyun Kyung Oh, Soyeon Cho, Youngjin Kim, Kyungeun Lee, Jaeyeon Lee and Sangyeop Jung. J Ecol Environ 2024;48:. https://doi.org/10.5141/jee.24.089

As the impacts of climate change on ecosystems and human society become increasingly severe, the need for national-level policy responses is growing. However, biodiversity survey data collected by various government agencies in South Korea lack spatial and temporal representativeness at the national scale. This limits the ability to accurately assess the current state of biodiversity and to identify the mechanisms of biodiversity change due to climate change. To address these challenges, this study proposes a strategy for integrating various biodiversity survey datasets to obtain data suitable for analyzing the current state of biodiversity and time-series changes in the context of climate change impacts. The approach involves identifying common elements (such as species names, location, and survey period) and examining standardization methodologies. The key recommendations of this study are as follows: First, standardize species names based on the National Species List to ensure consistency in survey data. Second, improve the precision of location information and correct errors to enhance data reliability. Third, develop a method to derive analysis unit periods for time-series analysis from datasets with irregular survey frequencies. These strategies are expected to strengthen the scientific foundation for ecosystem change research and provide critical baseline data for policy development in response to climate change.

Many endemic and rare species live in Korea’s subalpine zone, but there have been many research results showing that alpine creatures are disappearing due to recent climate change. Therefore, in this study, bioclimatic variables with 100 m resolution were created for Mt. Jirisan and Mt. Hallasan, representative mountainous regions in Korea. Nineteen high-resolution bioclimatic variables were created for the current and 4 future periods, and the generated data is believed to represent topographical characteristics well. This data is expected to be useful to predict potential habitats through species distribution modeling and the impact of climate change on organisms limited to alpine regions.