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Chinese Agricultural Science Bulletin ›› 2024, Vol. 40 ›› Issue (31): 97-104.doi: 10.11924/j.issn.1000-6850.casb2024-0110

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Prediction of Potential Suitable Areas for Oenothera biennis Under Future Climate in Heilongjiang Province Based on MaxEnt Model

LIU Xu(), FU Shengjie, MU Liqiang()   

  1. College of Forestry, Northeast Forestry University, Harbin 150000
  • Received:2024-02-20 Revised:2024-08-26 Online:2024-11-05 Published:2024-11-04

Abstract:

This study predicts the potential suitable areas for Oenothera biennis in Heilongjiang Province and its changing patterns under future climate conditions, providing a basis for further monitoring and control efforts. This study focused on the invasive plant O. biennis and used software such as MaxEnt and ArcGIS to predict the changes in its distribution under three carbon emission scenarios (ssp126, ssp370, ssp585) for the present and two future periods (2021-2040, 2041-2060). The study also analyzed the dominant environmental factors and expansion trends that affected the distribution of O. biennis in Heilongjiang Province. The results showed that: (1) the MaxEnt model predicted an AUC value of 0.864, indicating accurate predictions. (2) The environmental factors with the greatest impact on the habitat of O. biennis were annual average precipitation (26.5%), coldest month minimum temperature (21.3%), and annual average temperature (16.9%). (3) The suitable area for O. biennis in Heilongjiang Province was 231600 km2, with high suitability accounting for 9.11% of the province. (4) Under the future climate change scenario of the 2040s, the suitable area for O. biennis increased by 5.78%, 5.16%, and 8.52% under the ssp126, ssp370, and ssp585 climate conditions, respectively. Under the 2060s scenario, the suitable area increased by 7.51%, 8.95%, and 8.66% under the three climate conditions. Under future climate change, the suitable area for the invasive plant O. biennis showed a trend of spreading from the center to the periphery, with average annual rainfall being the main influencing factors for its distribution.

Key words: Oenothera biennis, MaxEnt model, suitable area, distribution pattern, climate