Prediction of potential distribution of soybean in the frigid region in China with MaxEnt modeling |
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| Institution: | 1. Heilongjiang Province Institute of Meteorological Science, Harbin 150030, China;2. Innovation and Opening Laboratory of Regional Eco-Meteorology in Northeast, China Meteorological Administration, Harbin 150030, China;3. Heilongjiang Eco-meteorology Center, Harbin 150030, China;1. Jilin Provincial Laboratory of Grassland Farming/Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;1. Biodiversity Centre, Finnish Environment Institute, Latokartanonkaari 11, FI-00790 Helsinki, Finland;2. Finnish Meteorological Institute, Weather and climate change impact research, P.O. Box 503, FI-00101 Helsinki, Finland;3. Department of Geosciences and Geography, University of Helsinki, P.O. Box 64, Gustaf Hällströminkatu 2a, 00014 Helsinki, Finland;1. Department of Geographical Sciences, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China;2. Hubei Key Laboratory of Critical Zone Evolution, China University of Geosciences, Wuhan 430074, China;3. Guizhou Electric Power Design Research Institute, Power Construction Corporation of China, Guiyang 550002, Guizhou, China |
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| Abstract: | Soybean (Glycine max (L.) Merr.) is one of the most important grains and oil-producing plants grown in China. Understanding the potential suitable characteristics of areas where soybean is grown and predicting its potential habitat under different climate scenarios are a significant part of ensuring food security. This study compiled 65 occurrence locations of soybean and 32 environmental variables obtained from the WorldClim database. Nine environmental variables were selected for model training. We identified potential suitable distribution areas for soybean in the frigid region and predicted changes in its geographical distribution under four shared socioeconomic pathways, SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5, for the periods from 2021 to 2040, 2041 to 2060, 2061 to 2080, and 2081 to 2100 using the MaxEnt model. The results showed that annual mean temperature, elevation, and April solar radiation were the dominant factors affecting the distribution of soybean, contributing 48.8%, 17.9%, and 15.7% of the variability in the data, respectively. Highly suitable habitats (defined as having a suitability variable P of 0.66–1.0) for the current conditions included the Songnen and Sanjiang plains, covering about 2.36 × 105 km2. The total areas of highly (as defined above) and moderately suitable (0.33–0.66) habitats would be reduced under the four climate scenarios. However, the centroids of the highly suitable habitat had a small mobile range under different scenarios. These results along with previous research on the potential distribution of soybean offer useful information; ecological modeling approaches need to be considered in future crop planting management and land use. |
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