Prediction of potential suitable areas for Broussonetia papyrifera in China using the MaxEnt model and CIMP6 data

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Abstract

Broussonetia papyrifera is an important native tree species in China with strong adaptability, wide distribution and economic importance. Climate change is considered as the main threat to ecological processes and global biodiversity. Predicting the potential geographical distribution of B. papyrifera in future climate change scenarios will provide a scientific basis for ecological restoration in China. Principal component analysis and Pearson correlation analysis were conducted to select the environmental variables. The distribution and changes in the potential suitable area for B. papyrifera were predicted using the maximum entropy model and the CIMP6 dataset from 2041 to 2060. The current highly suitable areas for B. papyrifera were mainly located in Guangdong (5.60 × 104 km2), Guangxi (4.39 × 104 km2), Taiwan (2.54 × 104 km2) and Hainan (2.17 × 104 km2). The mean temperature of the coldest quarter (11.54-27.11 °C), precipitation of the driest quarter (51.48-818.40 mm) and precipitation of the wettest quarter (665.51-2302.60 mm) were the main factors limiting the suitable areas for B. papyrifera. The multi-modal average of the highly and the total suitable areas for B. papyrifera were 111.42 × 104 and 349.11 × 104 km2 in the SSP5-8.5 scenario, while those in the SSP1-2.6 scenario were 87.50 × 104 and 328.29 × 104 km2, respectively. The gained suitable areas for B. papyrifera will expand to the western and northern China in the future scenarios. The multi-model averaging results showed that the potential available planting area was 212.66 × 104 and 229.32 × 104 km2 in the SSP1-2.6 and SSP5-8.5 scenarios, respectively, when the suitable area within the farmland range was excluded.

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Wang, M., & Guan, Q. (2023). Prediction of potential suitable areas for Broussonetia papyrifera in China using the MaxEnt model and CIMP6 data. Journal of Plant Ecology, 16(4). https://doi.org/10.1093/jpe/rtad006

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