GEO DATA

Data Articles

Species Distribution Model-based Habitat Change Projections of the Kelp Species, Ecklonia cava under SSP Scenarios: Sun Kyeong Choi, Seonggil Go, Sang Rul Park; Received April 8, 2025 Accepted May 8, 2025 Published online May 21, 2025; DOI: https://doi.org/10.22761/GD.2025.0009 [Epub ahead of print]

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Abstract PDF: The main kelp forest-forming alga Ecklonia cava (E. cava), plays an important role in coastal ecosystems of South Korea. Despite this coastal ecological importance, there is a lack of research on the prediction of macroalgal distribution. In this study, we examined the distribution of E. cava recorded since 1955 and predicted distribution changes starting from 2000, under different climate change scenarios (SSP1-1.9 and SSP5-8.5) using the species distribution model (MAXENT). It reported that E. cava has expanded its range to 38°N latitude since 2000. We found seawater temperature, primary productivity and seawater velocity were controlling factors that determine the habitat of E. cava. Under the low emissions scenario (SSP1-1.9), the habitat suitability and distribution of suitable habitats did not show significant changes. While, under the high emissions scenario (SSP5-8.5), a decline in the southern distribution and an expansion of the northern distribution was predicted. In particular, most of the current habitats of E. cava were found to have decreased habitat suitability, thus the existing population of the species in South Korea may experience a sharp decline. The results of this study can be used as a basis for developing sustainable conservation measures to maintain coastal ecosystems of rocky shore in South Korea.

Climate Change Impacts on the Potential Distribution of Camellia japonica in South Korea under SSP Scenarios: Jaeho Lee, Sungsoo Yoon, Jaeseok Lee, Changwan Seo; GEO DATA. 2024;6(4):400-410. Published online December 31, 2024; DOI: https://doi.org/10.22761/GD.2024.0058

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Abstract PDF: Climate change presents significant challenges to the habitat suitability of Camellia japonica, a key species in East Asian ecosystems. This study evaluated the potential impacts of climate change on the distribution of Camellia japonica in South Korea using species distribution models (SDMs) and shared socioeconomic pathways (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). Eleven SDMs, including an ensemble model weighted mean (EMW), were applied to predict habitat suitability from 2010 to 2070. Model performance was assessed using receiver operating characteristics curve (ROC), true skill statistics (TSS), and Kappa statistics, with EMW achieving the highest accuracy (ROC mean, 0.941), validating its reliability for integrated predictions. Bioclimatic variables, specifically mean diurnal range (BIO2) and annual precipitation (BIO12), were identified as the most influential factors driving habitat suitability. Under low-emission scenarios (SSP1-2.6 and SSP2-4.5), Camellia japonica habitats remained stable or showed slight expansion, maintaining suitability across coastline and central inland regions. Under high-emission scenarios (SSP3-7.0 and SSP5-8.5), Its habitat is expected to expand more rapidly and extensively across the eastern coastline and inland regions. Habitat shifts towards higher altitudes were observed across all scenarios, suggesting potential refugia in mountainous regions. This study highlights the vulnerability of Camellia japonica to climate change and the critical need for emission reduction policies to mitigate habitat loss. The findings provide actionable insights for conservation planning, emphasizing adaptive management strategies, such as preserving high-altitude refuges and restoring lowland habitats. Future research should incorporate additional ecological factors and higher-resolution datasets to refine predictions and guide sustainable biodiversity conservation efforts.

Predicting Habitat Changes and Vulnerability of Climate-sensitive Insects under SSP Scenarios: Jaeho Lee, Jin Lee, Sungsoo Yoon, Jaeseok Lee, Changwan Seo; GEO DATA. 2024;6(4):365-376. Published online December 31, 2024; DOI: https://doi.org/10.22761/GD.2024.0057

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Abstract PDF: Climate change significantly impacts the distribution and habitat suitability of insects, particularly those highly sensitive to environmental fluctuations. This study evaluated the habitat changes of 12 climate-sensitive insect species in South Korea under shared socioeconomic pathways (SSP) scenarios, SSP2-4.5 and SSP5-8.5, using random forest (RF) models. Bioclimatic variables, including annual mean temperature (BIO1) and annual precipitation (BIO12), were identified as key contributors to habitat suitability changes. The model demonstrated high predictive accuracy, with receiver operating characteristic (ROC) values exceeding 0.8 for five species, such as Papilio helenus and Argynnis hyperbius, while six species, including Sympetrum pedemontanum elatum, exhibited lower predictability due to data distribution challenges. The results revealed that SSP2-4.5 allowed more stable or expanding habitats for certain species, such as Argynnis hyperbius and Lampides boeticus, where habitat areas significantly increased by 2070. In contrast, SSP5-8.5 showed drastic habitat reductions for most species, including Camponotus kiusiuensis and Sympetrum pedemontanum elatum, with some habitats shrinking by over 90% by 2090. The study underscores the importance of climate variables, with temperature and precipitation consistently influencing habitat changes across species. This research provides critical insights into the ecological risks posed by climate change and emphasizes the necessity of mitigation strategies. While some species demonstrate adaptive potential under moderate scenarios, others face severe vulnerabilities under extreme climate conditions. These findings offer valuable guidance for biodiversity conservation and policy-making, highlighting the need for integrated approaches that account for non-climatic factors such as land-use changes.

Assessing Climate Change Impacts on Subalpine Plant Habitat Suitability in South Korea Using SSP Scenarios: Jaeho Lee, Sungsoo Yoon, Jaeseok Lee, Changwan Seo; GEO DATA. 2024;6(4):354-364. Published online December 31, 2024; DOI: https://doi.org/10.22761/GD.2024.0055

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Abstract PDF: This study evaluates the impacts of climate change on the habitat suitability of eight subalpine plant species in South Korea under four shared socioeconomic pathways (SSP) scenarios, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. Using high-resolution climate data and random forest-based species distribution models (SDMs), we predicted habitat changes between 2010 and 2090s. Key bioclimatic variables, including annual mean temperature (BIO1) and annual precipitation (BIO12), were identified as primary drivers of habitat shifts. SSP5-8.5 scenarios resulted in significant habitat losses and upward altitudinal shifts, with species such as Pinus pumila and Abies nephrolepis losing all suitable habitats by 2090s. In contrast, SSP1-2.6 indicated more stable conditions, preserving habitats for species like Abies holophylla and Taxus cuspidata, highlighting the potential benefits of emission reduction efforts. This study underscores the urgent need for adaptive conservation strategies and robust emission mitigation policies to protect high-risk species and regions, safeguarding subalpine biodiversity. These findings provide a scientific foundation for policymakers to design sustainable biodiversity conservation strategies and foster climate resilience in subalpine ecosystems.

Expanded Bioclimatic Variables Extracted from Monthly Climate Predictions under the SSP Climate Scenarios over South Korea: Jieun Oh, Ah Reum Han, Yeong-cheol Kim, Seungbum Hong; GEO DATA. 2024;6(4):235-247. Published online December 3, 2024; DOI: https://doi.org/10.22761/GD.2024.0018

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Abstract PDF: Numerous studies, including the Intergovernmental Panel on Climate Change (IPCC) sixth assessment report, have documented species habitat shifts caused by climate change. These shifts lead to transformations in ecosystem structure, components, and functions. Exploring the connections between species and climate change is essential for developing adaptation strategies. Many studies use species distribution models (SDMs), which are based on the correlation between species habitats and climatic surroundings, to predict ecological shifts under climate change. The primary climate variables for these models are the only 19 variables whose concepts are based on monthly average temperature and precipitation from the BIOCLIM package developed in 1984. These 19 bioclimatic variables usually are obtained from WorldClim data set and other datasets. However, they have limitations in reflecting local climate characteristics and their association with ecology. Firstly, future projection data from global dataset including WorldClim dataset is derived directly from global climate models rather than regional climate models. Secondly, the 19 variables based on monthly temperature and precipitation do not adequately express hydrological characteristics of terrestrial ecosystem which are crucial for species habitats. Lastly, although there are various biogeographical indices excepts the 19 bioclimatic variables, there have been just a few cases that they were applied to SDMs for Korea. To overcome these limitations, this study expands the various bioclimatic variables, using regionally specialized climate data from Korea Meteorology Administration (KMA). The newly extended indices, which can reflect water availability, are expected to improve the prediction of SDMs, enabling more precise assessment of ecological risks due to climate change and effective adaptation strategies to mitigate the impacts of climate change on ecosystems.

A Dataset for Species Distribution Modelling of Mangroves in Vietnam: Based on the National Forest Inventory Monitoring: Sungsoo Yoon, Nguyen Duy Liem, Le Hoang Tu, Nguyen Kim Loi; GEO DATA. 2024;6(3):150-158. Published online September 30, 2024; DOI: https://doi.org/10.22761/GD.2024.0022

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Abstract PDF: Mangroves provides essential ecosystem services such as protection of coastal areas, carbon sequestration, and habitat provision for diverse species in coastal ecosystems. Species distribution models (SDMs) are powerful tools for predicting the potential distribution of mangrove species, which support impact assessments of climate changes on biodiversity and ecological functions of mangrove ecosystems. A comprehensive dataset for mangrove occurrence information derived from the Forest Inventory Map of Vietnam was designed to facilitate the building and projection of SDMs. The prediction data designed for training SDMs integrates ecological information including 701 field survey-based mangrove occurrences at the genus level and 21 environmental variables such as bioclimatic variables, digital elevation model and soil properties with 1 km spatial resolution. The projection data for provide sets of predictors aligned with four shared socioeconomic pathways scenarios representing two future periods to support the projection of SDM results under future climate conditions in Vietnam. This dataset serves as a valuable ecological information resource, enabling the modeling and predicting of potential mangrove habitats and distributions for the protection and restoration of mangroves in Vietnam under changing environmental conditions.

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