Work

Impact of Climate Change on Oriental Migratory Locust Suitability: A Multi-Source Data and MaxEnt-Based Analysis in Hainan Island

Year: 2025

Type: article

Abstract: This study employed an integrated approach combining multi-source remote sensing data and the MaxEnt model to systematically assess the ecological niche characteristics of the oriental migratory locust (Locusta migratoria manilensis) in Hainan Island, while projecting the evolution of its suitable habitats under both historical and future climate scenarios (up to 2040). Firstly, we synthesized traditional climate, soil, and topography data with remote sensing data to characterize the suitable areas of the oriental migratory locust based on MaxEnt model (with high accuracy of AUC = 0.935 and TSS = 0.76). Subsequently, six dominant environmental variables—precipitation in April (PRE04), precipitation in September (PRE09), maximum temperature in August (TMAX08), minimum temperature in December (TMIN12), NDVI in February (NDVI02), and NDVI in May (NDVI02)—were identified as key predictors. Their threshold values were determined, with PRE04, PRE09, TMAX08, and TMIN12 ranging from 39 to 44 mm, 196 to 223 mm, 31.1 to 32.2 °C, and 17.7 to 18.0 °C in high-suitability zones, respectively. Finally, these six predictors were used to assess habitat suitability across Hainan Island for both the 2001–2020 and 2021–2040 periods. Under historical climate conditions, highly suitable areas (505 km2, 1.41% of total land area) were concentrated in the western and northeastern regions, particularly in Dongfang City (46.27%), Ledong Li Autonomous County (32.91%), and Changjiang Li Autonomous County (18.39%). Future projections indicate significant habitat expansion, with total suitable areas increasing by 13.4–42.0% and highly suitable areas reaching 571–831 km2 by 2040. The study highlights the critical Dongfang–Danzhou–Ledong region for targeted locust control, providing scientific support for pest management in tropical island ecosystems under climate change.

Source: Remote Sensing

DOI: 10.3390/rs17081329

Authors: Zhongxiang Sun, Huichun Ye, Weiping Kong, Chaojia Nie, Huiqing Bai

Institutions: China Agricultural Museum, Aerospace Information Research Institute, Chinese Academy of Sciences, Chinese Academy of Agricultural Sciences, Institute of Environment and Sustainable Development in Agriculture

Language: English

Topic: Species Distribution and Climate Change

Subfield: Ecological Modeling

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Life on land, Sustainable cities and communities, Zero hunger

Open Access status: gold

Estimated APC paid: $3,258