ArticleEnvironmental science and pollution research international2022
Predicting the potential global distribution of Sapindus mukorossi under climate change based on MaxEnt modelling.
Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
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- Advancements in ecological niche models for forest adaptation to climate change: a comprehensive review.Biological reviews of the Cambridge Philosophical Society · 2025Review
- Changes in the Suitable Habitat of the Smoke Tree (Plants (Basel, Switzerland) · 2025Article
- Integrated approach to predicting habitat suitability and evaluating quality variations of Notopterygium franchetii under climate change.Scientific reports · 2024Article
- Predicting the Global Potential Suitable Areas of Sweet Osmanthus (Ecology and evolution · 2024Article
- Prediction of the potential distribution of a raspberry (Rubus idaeus) in China based on MaxEnt model.Scientific reports · 2024Article
- Xanthium strumarium L., an invasive species in the subtropics: prediction of potential distribution areas and climate adaptability in Pakistan.BMC ecology and evolution · 2024Article
- Response to Climate Change and GAP Analysis ofPlants (Basel, Switzerland) · 2024Article
- Potential planting regions ofEcology and evolution · 2024Article
- Prediction of the potential distribution ofBiodiversity data journal · 2024Article
- Prediction of global potential suitable habitats of Nicotiana alata Link et Otto based on MaxEnt model.Scientific reports · 2023Article
- Potentially suitable habitats ofFrontiers in plant science · 2023Article
- Prediction of the potentially suitable areas ofFrontiers in plant science · 2023Article
- Migration patterns ofEcology and evolution · 2022Article
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3 authors.
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Abstract
Sapindus mukorossi (S. mukorossi) is an important biological washing material and biomass energy tree species whose peel is rich in saponins, and its kernels have a high oil content. We used the maximum entropy model (MaxEnt) to predict the suitable habitats of S. mukorossi globally, screen the dominant environmental factors affecting its distribution and analyse the changes in its suitable habitats under climate change from prehistory to the future, and the results will provide a scientific basis for germplasm resource collection, protection, introduction and cultivation. Twenty-two environmental variables and global distribution data for S. mukorossi were used to construct the species distribution model, and the receiver operating characteristic (ROC) curve was used to verify the accuracy of the model. The dominant environmental factors were screened through the jackknife method, and then, the geographical information system (ArcGIS) was used to complete the grade of suitable habitat division and area calculation. The results showed that the MaxEnt model had an excellent predictive effect, and the area under the ROC curve (AUC) value was as high as 0.969. The precipitation of the warmest quarter (Bio18), the minimum temperature of the coldest month (Bio6), temperature seasonality (Bio4) and isothermality (Bio3) were the dominant environmental factors that affected the distribution of S. mukorossi. The largest area of the world's suitable habitats occurred during the last interglacial (LIG) (772.69 × 10
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