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Scientia Silvae Sinicae ›› 2025, Vol. 61 ›› Issue (4): 104-116.doi: 10.11707/j.1001-7488.LYKX20230618

• Research papers • Previous Articles    

Prediction of the Distribution of Robinia pseudoacacia in China under Future Climate Change Using an Optimized MaxEnt Model

Gao Wanting1,2,3, Hu Xiaochuang1,2,3, Sun Shoujia1,2,3, Zhang Jinsong1,2,3, Meng Ping1,2,3, Cai Jinfeng2   

  1. 1. Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration　Research Instituteof Forestry, Chinese Academy of Forestry　Beijing 100091;
    2. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forest University　Nanjing 210037;
    3. Henan Xiaolangdi Forest Ecosystem National Observation and Research Station　Jiyuan 454650
  • Received:2023-12-15 Revised:2024-05-28 Published:2025-04-21

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Abstract: Objective This study aims to explore the relationship between Robinia pseudoacacia (black locust) distribution and environmental variables at the national scale as well as the changes of future adaptation areas, so as to provide data support for afforestation planning and management of R. pseudoacacia.Method The MaxEnt model optimized by the Kuenm package in R language and ArcGIS software were applied to explore the main environmental factors affecting its geographical distribution. With the selected 181 distribution point records of black locust in China and 12 environmental factors, this optimized MaxEnt model was used to predict the potential habitat area and centroid changes of black locust in China under three different climate change scenarios (ssp126, ssp245, ssp585) in four periods, namely contemporary, future 2030s, 2050s, and 2070s. Result The results showed that when the feature combination (FC) = linear + product and the modulation frequency was 0.5 (RM = 0.5), the model had the lowest complexity and higher prediction accuracy. The area under curve (AUC) was 0.880, which was able to be used to predict the suitable growth range of black locust. The mean air temperature in the coldest quarter, precipitation in the warmest quarter, and the altitude were the main environmental factors affecting the potential geographical distribution of black locust, and their adaptation ranges were from –5 to 6.5 ℃, from 335 to 1 825 mm, and from –155 to 1 725 m, respectively. Under contemporary climate conditions, the total suitable area for black locust in China is 262.51 × 104 km2, and the highly suitable area is 37.86×104 km2. The total suitable area for black locust in all three future climate change scenarios would generally consistent compared with current situation, while the highly suitable area would decrease. However, the highly suitable area in the ssp126 scenario would decrease in 2070s. The centroid analysis results indicated that under future climate change scenarios, the potential total suitable area for black locust in China would shift towards the northeast, and the highly suitable area would shift towards the southwest.Conclusion The optimized MaxEnt model can accurately predict the potential suitable habitats of black locust in China. Temperature, precipitation, and altitude are identified as the dominant environmental variables influencing its distribution. Climate change is expected to reduce the highly suitable habitat area for black locust in the future and cause shifts in its potential distribution.

Key words: climate change, Robinia pseudoacacia, MaxEnt model, potential suitable areas

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