ArticleScientific reports2026
Predicting the potential distribution of Euryale ferox in China under future climate scenarios using MaxEnt modeling.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
- Spatiotemporal transferability of multi-temporal random forest model for mappingFrontiers in plant science · 2026Article
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7 authors.
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Abstract
Climate change poses a threat to both the natural habitat and the sustainable production of Euryale ferox, a valuable aquatic crop. To address this issue, our study employed an optimized Maximum Entropy (MaxEnt) model to project the climatic suitability of E. ferox distribution in China for the 2030-2070 s under four climate scenarios. Utilizing 130 occurrence records of E. ferox and 20 ecological factors, we identified four primary factors influencing the distribution of E. ferox. The optimal conditions for E. ferox include elevations below 184.8 m, the temperature of the warmest season exceeds 25.7°C, the precipitation of the wettest month ranging between 167 and 718 mm, and precipitation over 9.5 mm in the driest month. The accuracy of the MaxEnt model predictions was comprehensively evaluated by the area under the ROC curve (AUC = 0.942) and the true skill statistic (TSS = 0.783), indicating its effectiveness in forecasting suitable environments. We also found that the current areas of highly and moderately suitable habitats are 0.909 × 10
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