Predicting Current and Future Habitat Suitability of Toxicodendron succedaneum in China Under Climate Change Using MaxEnt

Saer Fei

doi:10.54097/8eajdr78

Authors

Saer Fei School of Beijing Haidian Kaiwen academy, Beijing, China

DOI:

https://doi.org/10.54097/8eajdr78

Keywords:

Toxicodendron succedaneum, Climate change, Species distribution modeling.

Abstract

Climate change is expected to alter the geographic distributions of many tree species, posing substantial challenges to biodiversity conservation and the sustainable management of biological resources. Toxicodendron succedaneum (L.) Kuntze is an economically and medicinally important tree species widely distributed across East and Southeast Asia, but its potential response poor understood of future climate change in China. This study by using the MaxEnt algorithm to predict the current and future habitat suitability of T. succedaneum under the SSP370 for the future periods during 2011–2040, 2041–2070, and 2071–2100. The model was developed by 511 spatially filtered occurrence records and eight chosen environmental variables. Model have good performance, the area under the receiver operating characteristic curve (AUC) around 0.802 ± 0.004, indicating it's had a reliable predictive ability for our research. However, bio14 emerged as the dominant environmental driver under future climate scenarios, suggesting that dry-season water availability will increasingly constrain species distributions as climate change intensifies drought stress. Currently, the most suitable habitats are mainly concentrated in the southern and southeastern parts of China. Future predictions indicate that the habitats will undergo redistribution rather than significant loss. By the end of the 21st century, the highly suitable areas will expand slightly, but they will still mainly be concentrated in the southern coastal regions. The findings provide important scientific evidence for climate-adaptive conservation planning and highlight the importance of species distribution modelling in guiding the conservation of economically important tree species under future climate change.

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References

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