Data on the predictions of plant redistribution under interplays among climate change, land-use change, and dispersal capacity
The future distribution data of Pittosporum tobira, Raphiolepis indica var. umbellata, Neolitsea sericea, Ilex integra, and Eurya emarginata were acquired from the MigClim, a GIS-based (hybrid) cellular automation model, modeling and the traditional SDM modeling using BioMod2. The current SDM projec...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922008721 |
| _version_ | 1811190711207329792 |
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| author | Kyung Ah Koo Seon Uk Park |
| author_facet | Kyung Ah Koo Seon Uk Park |
| author_sort | Kyung Ah Koo |
| collection | DOAJ |
| description | The future distribution data of Pittosporum tobira, Raphiolepis indica var. umbellata, Neolitsea sericea, Ilex integra, and Eurya emarginata were acquired from the MigClim, a GIS-based (hybrid) cellular automation model, modeling and the traditional SDM modeling using BioMod2. The current SDM projections, the traditional SDM predictions, which were assumed the climate-change-only, and model validation were performed using BioMod2 with 686 presence/absence data for each plant species. The MigClim predictions were performed under the combination of two climate change scenarios (RCP 4.5 and RCP 8.5), two land-use change scenarios (SSP1 and SSP3), and four dispersal scenarios (no dispersal, short-distance dispersal, long-distance dispersal, and full dispersal). For the MigClim predictions, the initial distribution map was produced by coupling the current land-use map with the ensemble SDM predictions for each plant. The future habitat suitability map was predicted by coupling the land-use prediction with the SDM predictions under RCP 4.5 and RCP 8.5. For the land-use map, the future land-use maps were predicted under SSP1 and SSP3 using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Scenario Generator tool, and the land-use categories were classified into two classes, namely barrier and non-barrier. The degree of dispersal for each species was calculated using a negative exponential function, where the coefficients were 0.005 (∼1 km) and 0.0005 (∼10 km). The future expansion of range was predicted through dispersal simulations of 80 times from 1990 to 2070. The prediction and analyzed data provide essential information and insight for understanding the climate change effects on the warm-adapted plants in interactions with land-use change and the dispersal process. These data can be used for detecting restoration areas for increasing connectivity among habitats, establishing protected areas, and developing environmental policies related to restoration and conservation. |
| first_indexed | 2024-04-11T14:53:46Z |
| format | Article |
| id | doaj.art-3ce7071bacc2498786280ce414b7c49b |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-11T14:53:46Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-3ce7071bacc2498786280ce414b7c49b2022-12-22T04:17:19ZengElsevierData in Brief2352-34092022-12-0145108667Data on the predictions of plant redistribution under interplays among climate change, land-use change, and dispersal capacityKyung Ah Koo0Seon Uk Park1Korea Environment Institute, 370 Sicheong-daero, Sejong-si 30147, Republic of Korea; Corresponding author.Div. of Restoration Strategy, National Institute of Ecology, Yeongyang 36531, Republic of KoreaThe future distribution data of Pittosporum tobira, Raphiolepis indica var. umbellata, Neolitsea sericea, Ilex integra, and Eurya emarginata were acquired from the MigClim, a GIS-based (hybrid) cellular automation model, modeling and the traditional SDM modeling using BioMod2. The current SDM projections, the traditional SDM predictions, which were assumed the climate-change-only, and model validation were performed using BioMod2 with 686 presence/absence data for each plant species. The MigClim predictions were performed under the combination of two climate change scenarios (RCP 4.5 and RCP 8.5), two land-use change scenarios (SSP1 and SSP3), and four dispersal scenarios (no dispersal, short-distance dispersal, long-distance dispersal, and full dispersal). For the MigClim predictions, the initial distribution map was produced by coupling the current land-use map with the ensemble SDM predictions for each plant. The future habitat suitability map was predicted by coupling the land-use prediction with the SDM predictions under RCP 4.5 and RCP 8.5. For the land-use map, the future land-use maps were predicted under SSP1 and SSP3 using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Scenario Generator tool, and the land-use categories were classified into two classes, namely barrier and non-barrier. The degree of dispersal for each species was calculated using a negative exponential function, where the coefficients were 0.005 (∼1 km) and 0.0005 (∼10 km). The future expansion of range was predicted through dispersal simulations of 80 times from 1990 to 2070. The prediction and analyzed data provide essential information and insight for understanding the climate change effects on the warm-adapted plants in interactions with land-use change and the dispersal process. These data can be used for detecting restoration areas for increasing connectivity among habitats, establishing protected areas, and developing environmental policies related to restoration and conservation.http://www.sciencedirect.com/science/article/pii/S2352340922008721Plant redistributionClimate changeLand-use changeSpecies distribution model (SDM)-Dispersal-Land-use change modeling |
| spellingShingle | Kyung Ah Koo Seon Uk Park Data on the predictions of plant redistribution under interplays among climate change, land-use change, and dispersal capacity Data in Brief Plant redistribution Climate change Land-use change Species distribution model (SDM)-Dispersal-Land-use change modeling |
| title | Data on the predictions of plant redistribution under interplays among climate change, land-use change, and dispersal capacity |
| title_full | Data on the predictions of plant redistribution under interplays among climate change, land-use change, and dispersal capacity |
| title_fullStr | Data on the predictions of plant redistribution under interplays among climate change, land-use change, and dispersal capacity |
| title_full_unstemmed | Data on the predictions of plant redistribution under interplays among climate change, land-use change, and dispersal capacity |
| title_short | Data on the predictions of plant redistribution under interplays among climate change, land-use change, and dispersal capacity |
| title_sort | data on the predictions of plant redistribution under interplays among climate change land use change and dispersal capacity |
| topic | Plant redistribution Climate change Land-use change Species distribution model (SDM)-Dispersal-Land-use change modeling |
| url | http://www.sciencedirect.com/science/article/pii/S2352340922008721 |
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