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未来气候情景下中国[具体物种未给出]的预测分布模式:来自优化的最大熵模型和生物多样性模型2的见解

Projected distribution patterns of in China under future climate scenarios: insights from optimized Maxent and Biomod2 models.

作者信息

Kang Yong, Lin Fei, Yin Junmei, Han Yongjie, Zhu Min, Guo Yuhua, Tang Fenling, Li Yamei

机构信息

National Key Laboratory for Tropical Crop Breeding, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China.

Haikou Experiment Station, Chinese Academy of Tropical Agricultural Sciences, Haikou, China.

出版信息

Front Plant Sci. 2025 Feb 10;16:1517060. doi: 10.3389/fpls.2025.1517060. eCollection 2025.

DOI:10.3389/fpls.2025.1517060
PMID:40017818
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11866951/
Abstract

, commonly known as Galangal, is not only widely used as a medicinal plant but also holds significant ornamental value in horticulture and landscape design due to its unique plant structure and floral aesthetics in China. This study evaluates the impact of current and future climate change scenarios (ssp126, ssp245, ssp370, and ssp585) on the suitable habitats for in China. A total of 73 reliable distribution points for were collected, and 11 key environmental variables were selected. The ENMeval package was used to optimize the Maxent model, and the potential suitable areas for were predicted in combination with Biomod2. The results show that the optimized Maxent model accurately predicted the potential distribution of in China. Under low emission scenarios (ssp126 and ssp245), the suitable habitat area increased and expanded towards higher latitudes. However, under high emission scenarios (ssp370 and ssp585), the suitable habitat area significantly decreased, with the species distribution range shrinking by approximately 3.7% and 19.8%, respectively. Through Multivariate environmental similarity surface (MESS) and most dissimilar variable (MoD) analyses revealed that increased climate variability under high emission scenarios, especially in ssp585, led to large-scale habitat contraction due to rising temperatures and unstable precipitation patterns. Changes in the center of suitability location showed that the current center of 's suitable habitat is located in Guangxi, China. Under low emission scenarios, the center of suitability gradually shifts northwest, while under high emission scenarios, this shift becomes more pronounced. These findings provide a scientific basis for the conservation of germplasm resources and the management strategies in response to climate change.

摘要

在中国,其通常被称为高良姜,不仅作为药用植物被广泛使用,还因其独特的植物结构和花卉美学在园艺和景观设计中具有重要的观赏价值。本研究评估了当前和未来气候变化情景(ssp126、ssp245、ssp370和ssp585)对中国高良姜适宜栖息地的影响。共收集了73个高良姜可靠分布点,并选择了11个关键环境变量。使用ENMeval软件包优化Maxent模型,并结合Biomod2预测高良姜的潜在适宜区域。结果表明,优化后的Maxent模型准确预测了高良姜在中国的潜在分布。在低排放情景(ssp126和ssp245)下,适宜栖息地面积增加并向更高纬度扩展。然而,在高排放情景(ssp370和ssp585)下,适宜栖息地面积显著减少,物种分布范围分别缩小了约3.7%和19.8%。通过多变量环境相似性表面(MESS)和最不相似变量(MoD)分析表明,高排放情景下尤其是ssp585中气候变异性增加,由于气温上升和降水模式不稳定导致大规模栖息地收缩。适宜性中心位置的变化表明,当前高良姜适宜栖息地中心位于中国广西。在低排放情景下,适宜性中心逐渐向西北转移,而在高排放情景下,这种转移更加明显。这些发现为高良姜种质资源保护和应对气候变化的管理策略提供了科学依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/d311cb199073/fpls-16-1517060-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/74f717e06850/fpls-16-1517060-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/260aa6cb7be1/fpls-16-1517060-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/de85b80268e0/fpls-16-1517060-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/1c58c74c24d8/fpls-16-1517060-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/888a16aa2a44/fpls-16-1517060-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/5768287e6066/fpls-16-1517060-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/b4814c5b023e/fpls-16-1517060-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/354730ea1288/fpls-16-1517060-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/d311cb199073/fpls-16-1517060-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/74f717e06850/fpls-16-1517060-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/260aa6cb7be1/fpls-16-1517060-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/de85b80268e0/fpls-16-1517060-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/1c58c74c24d8/fpls-16-1517060-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/888a16aa2a44/fpls-16-1517060-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/5768287e6066/fpls-16-1517060-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/b4814c5b023e/fpls-16-1517060-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/354730ea1288/fpls-16-1517060-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41b0/11866951/d311cb199073/fpls-16-1517060-g009.jpg

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Environ Evid. 2023 Apr 11;12(1):7. doi: 10.1186/s13750-023-00296-0.
3
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PLoS One. 2025 Apr 16;20(4):e0321167. doi: 10.1371/journal.pone.0321167. eCollection 2025.
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