Predicting habitat suitability for the soybean pod borer <i>Leguminivora glycinivorella</i> (Matsumura) using optimized MaxEnt models with multiple variables

The soybean pod borer Leguminivora glycinivorella (Matsumura) is one of the most important soybean pests and often causes serious damage to Glycine max (L.) Merr., a leading source of dietary protein and oil in animal feed. However, the potential distribution patterns of this economically important pest and its driving factors require further investigation. Here, we used the optimized MaxEnt model to predict the potential distribution of this pest with multiple variables associated with climate, land use, and host plant, at its recorded range and a globe scale. Based on 4 variable combinations, the results show that the current suitable habitats of L. glycinivorella are primarily distributed in most of China, the Korean Peninsula, and Japan. Whereas no suitable area is present in other continents. In future projections, the suitable region shows a slight northward expansion compared with the result predicted with current climatic conditions, and the suitable areas of almost all future projections were stable in size. Among the 9 bioclimatic factors, BIO03 (isothermality) consistently highly contributes to the predictions, indicating that temperature may be a key factor influencing the habitat distribution of L. glycinivorella. Comparative analyses of projections further show that non-climatic factors are informative in the modeling as routinely used bioclimate variables. The spatio-temporal distribution patterns of suitable habitats and the regulatory factors predicted in this study could provide important guidance for L. glycinivorella management.

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Publication Details

Journal
Journal of Economic Entomology
Published
2024-08-09
DOI
https://doi.org/10.1093/jee/toae167
Citations
4
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
3.68

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article

Predicting habitat suitability for the soybean pod borer Leguminivora glycinivorella (Matsumura) using optimized MaxEnt models with multiple variables

Houhun Li, Weili Ding, Mingsheng Yang, Ying Wang et al.
4 citations
Journal of Economic Entomology
Species Distribution and Climate Change
3.68
article

Predicting habitat suitability for the soybean pod borer Leguminivora glycinivorella (Matsumura) using optimized MaxEnt models with multiple variables

Houhun Li, Weili Ding, Mingsheng Yang, Ying Wang, Ai‐bing Zhang
article en
4 citations

Abstract

The soybean pod borer Leguminivora glycinivorella (Matsumura) is one of the most important soybean pests and often causes serious damage to Glycine max (L.) Merr., a leading source of dietary protein and oil in animal feed. However, the potential distribution patterns of this economically important pest and its driving factors require further investigation. Here, we used the optimized MaxEnt model to predict the potential distribution of this pest with multiple variables associated with climate, land use, and host plant, at its recorded range and a globe scale. Based on 4 variable combinations, the results show that the current suitable habitats of L. glycinivorella are primarily distributed in most of China, the Korean Peninsula, and Japan. Whereas no suitable area is present in other continents. In future projections, the suitable region shows a slight northward expansion compared with the result predicted with current climatic conditions, and the suitable areas of almost all future projections were stable in size. Among the 9 bioclimatic factors, BIO03 (isothermality) consistently highly contributes to the predictions, indicating that temperature may be a key factor influencing the habitat distribution of L. glycinivorella. Comparative analyses of projections further show that non-climatic factors are informative in the modeling as routinely used bioclimate variables. The spatio-temporal distribution patterns of suitable habitats and the regulatory factors predicted in this study could provide important guidance for L. glycinivorella management.

Journal of Economic EntomologyVol. 117(5)
Nankai University (CN), Zhoukou Normal University (CN), Zhoukou City Academy of Agricultural Sciences (CN), Capital Normal University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Climate action
Openalex Percentile: Top 8%
Species Distribution and Climate Change
3.68
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