数字农科院2.0

Comparative analysis between ecological niche and biological models to project climate-driven habitat shifts of the oriental migratory locust in China

文献类型： 外文期刊

作者： Shiqian Feng;Siyan Dong;Xiao Chang;Shaodan Wang;Sultanova Nadira;Niyazbekov Zhan;Fozilbek Nurjonov;Farman Ullah;Shuai Shi;Zehua Zhang;Xiongbing Tu

关键词： Oriental migratory locust;statistical downscaling;degree-day model;MaxEnt model;projection;habitat expansion

期刊名称： ENTOMOLOGIA GENERALIS

ISSN： 0171-8177

年卷期： 2025 年

页码：

收录情况： SCIE（2025版）

摘要： The oriental migratory locust, Locusta migratoria manilensis, a major agricultural pest in China, faces shifting habitat suitability under climate change. Integrating a biological model (MDD, modified degree-day model) and an ecological niche model (MaxEnt) with six downscaled CMIP6 climate datasets, we quantified temperature-driven distribution changes from 1961–2100. Provincial analyses identified March temperatures as critical periods, which is an important month for diapause egg hatching, emphasizing the pivotal role of population baselines to locust outbreaks. The results from both models (MDD and MaxEnt) and six climate datasets revealed an overall accelerated northward habitat expansion, with northeastern China as a hotspot. The suitable habitat increased by 19.71% (0.61 million km2, MDD) and 4.41% (0.11 million km2, MaxEnt) during 1961-2020. MIROC6, the best-fitting climate dataset to real observation data, projected 10.42% (MDD) and 1.78% (MaxEnt) expansion during 1961-2020, rising to 21.92% (MDD) and 6.21% (MaxEnt) from 2020-2100. This shift transforms marginal regions (e.g., Heilongjiang, Jilin provinces) into year-round breeding zones, exemplified by the 2017–2018 outbreak in Jilin province after decades of thermal accumulation. The MDD model, sensitive to thermal thresholds, projects larger suitable areas than MaxEnt, reflecting its focus on physiological limits versus MaxEnt’s biotic constraints. Our dual-model framework resolves key limitations of single-model approaches, offering actionable insights for monitoring and management.

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