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Distribution pattern of large old Ginkgo biloba in China under climate change scenarios.
- Source :
-
Ecology & Evolution (20457758) . May2024, Vol. 14 Issue 5, p1-15. 15p. - Publication Year :
- 2024
-
Abstract
- Large old Ginkgo biloba trees (LOGTs), with profound ecological and cultural significance in China, face increasing threats from climate change and human activities. We employed the BIOCLIM and DOMAIN species distribution models to predict their spatial patterns under the present climate and doubled‐CO2 climate change scenario in 2100. We collected 604 validated LOGT occurrence records and data on 19 bioclimate factors for the analysis. Our study yielded a LOGT geographic distribution pattern covering a wide latitudinal belt extending from south subtropical to temperate zones in central and eastern China, concentrating in low elevations and coastal regions. The principal component analysis identified the dominant bioclimatic factors shaping their distribution, namely annual precipitation and low winter temperatures. BIOCLIM and DOMAIN generated predicted suitable habitats that match the present distribution range well. However, under the future climate scenario, the models indicated habitat retentions mainly in the core distribution areas and habitat losses mainly in the southern edge of the present range and scattered pockets elsewhere. Some retained habitats, including excellent ones, will suffer from fragmentation. The predicted new habitats may permit some range expansion and migration but are beset by small patch size and large interpatch distance, bringing fragmentation and gene flow restrictions. The anticipated projected range decline highlights considerable threats climate change poses to the long‐term survival of the precious natural‐cum‐cultural resource. Understanding the distribution patterns and underlying drivers and distillation of practical conservation measures can foster sustainable management vis‐a‐vis the looming global change. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20457758
- Volume :
- 14
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Ecology & Evolution (20457758)
- Publication Type :
- Academic Journal
- Accession number :
- 177533051
- Full Text :
- https://doi.org/10.1002/ece3.11367