A Dataset for Species Distribution Modelling of Mangroves in Vietnam: Based on the National Forest Inventory Monitoring
| Title: | A Dataset for Species Distribution Modelling of Mangroves in Vietnam: Based on the National Forest Inventory Monitoring |
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| Authors: | Sungsoo Yoon, Nguyen Duy Liem, Le Hoang Tu, Nguyen Kim Loi |
| Source: | Geo Data, Vol 6, Iss 3, Pp 150-158 (2024) |
| Publisher Information: | GeoAI Data Society, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Environmental sciences LCC:Geology |
| Subject Terms: | mangroves, national forest inventory monitoring, climate change, species distribution model, Environmental sciences, GE1-350, Geology, QE1-996.5 |
| More Details: | 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. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English Korean |
| ISSN: | 2713-5004 |
| Relation: | http://geodata.kr/upload/pdf/GD-2024-0022.pdf; https://doaj.org/toc/2713-5004 |
| DOI: | 10.22761/GD.2024.0022 |
| Access URL: | https://doaj.org/article/6aefdde68ea04cfabe417d4bfd581dd2 |
| Accession Number: | edsdoj.6aefdde68ea04cfabe417d4bfd581dd2 |
| Database: | Directory of Open Access Journals |
| ISSN: | 27135004 |
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| DOI: | 10.22761/GD.2024.0022 |
| Published in: | Geo Data |
| Language: | English Korean |