Predicting the Potential Distribution of Rare and Endangered <i>Emmenopterys henryi</i> in China Under Climate Change

Climate change has a pivotal impact on the potential distribution of endangered and relic tree species. Probably due to unrepresentative sampling and single algorithm, at present, there are different views on the potential range of the endangered tree <i>Emmenopterys henryi,</i> endemic to China. Here, we first collated 612 occurrence records and 22 environmental variables including climate, topography, and soil. Combined the Biomod2 with MaxEnt, we then predicted its past, current, and future potential suitable area in China, and determined the key factors influencing its distribution. The ensemble model results showed that the main environmental variables affecting this species were the minimum temperature of the coldest month (BIO6), precipitation of warmest quarter (BIO18), and temperature seasonality (BIO4). Its current potential distribution area was 176.53 × 10<sup>4</sup> km<sup>2</sup>, mainly concentrated in eastern, central, and southwestern China. Collectively, the suitable area of <i>E. henryi</i> would averagely decrease by 3.90% in all 16 future scenarios, with its centroid largely migrating northeastward. Our findings indicate that the endangered <i>E. henryi</i> covered 18 provinces in China, having a larger area than known. Moreover, climate change may have an adverse effect on its potential distribution. In addition, the ensemble model can produce more effective prediction outcomes than MaxEnt for such endemic tree species with large environmental range. We recommend increasing sample representativeness by analyzing the completeness properties of sample coverage, and simultaneously selecting appropriate algorithms to ensure the reliability of distribution prediction for endangered and relict tree species.

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Publication Details

Journal
Ecology and Evolution
Published
2024-10-01
DOI
https://doi.org/10.1002/ece3.70403
Citations
9
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
8.28
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article

Predicting the Potential Distribution of Rare and Endangered Emmenopterys henryi in China Under Climate Change

Guangfu Zhang, Hanwei Cai
9 citations
Ecology and Evolution
Species Distribution and Climate Change
8.28
article

Predicting the Potential Distribution of Rare and Endangered Emmenopterys henryi in China Under Climate Change

Guangfu Zhang, Hanwei Cai
article en
9 citations

Abstract

Climate change has a pivotal impact on the potential distribution of endangered and relic tree species. Probably due to unrepresentative sampling and single algorithm, at present, there are different views on the potential range of the endangered tree <i>Emmenopterys henryi,</i> endemic to China. Here, we first collated 612 occurrence records and 22 environmental variables including climate, topography, and soil. Combined the Biomod2 with MaxEnt, we then predicted its past, current, and future potential suitable area in China, and determined the key factors influencing its distribution. The ensemble model results showed that the main environmental variables affecting this species were the minimum temperature of the coldest month (BIO6), precipitation of warmest quarter (BIO18), and temperature seasonality (BIO4). Its current potential distribution area was 176.53 × 10<sup>4</sup> km<sup>2</sup>, mainly concentrated in eastern, central, and southwestern China. Collectively, the suitable area of <i>E. henryi</i> would averagely decrease by 3.90% in all 16 future scenarios, with its centroid largely migrating northeastward. Our findings indicate that the endangered <i>E. henryi</i> covered 18 provinces in China, having a larger area than known. Moreover, climate change may have an adverse effect on its potential distribution. In addition, the ensemble model can produce more effective prediction outcomes than MaxEnt for such endemic tree species with large environmental range. We recommend increasing sample representativeness by analyzing the completeness properties of sample coverage, and simultaneously selecting appropriate algorithms to ensure the reliability of distribution prediction for endangered and relict tree species.

Ecology and EvolutionVol. 14(10)
Nanjing Normal University (CN)
Climate action
Openalex Percentile: Top 3%
Species Distribution and Climate Change
8.28
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