Maximum Entropy Modeling for the Prediction of Potential Plantation Distribution of Arabica coffee under the CMIP6 Mode in Yunnan, Southwest China

Abstract

As one of three major beverages in the world, coffee ranks first in terms of production, consumption, and economic output. However, little is known about the habitat of Arabica coffee and the key environmental factors that influence its ecological distribution. Based on climatic, topographic, and soil data, the Arabica coffee planting regions with different levels of ecological suitability in different periods, and environmental factors that have the largest impact on ecological suitability were simulated using the MaxEnt model. The results showed that the ecologically suitable regions were mainly determined by climatic (max temperature of warmest month and annual precipitation) factors, followed by terrain (slope, altitude, and aspect) and soil (silt) factors. Under the current scenario, the most suitable and suitable regions accounted for 4.68% and 14.29% of the entire area, respectively, mainly in the western, southeastern, southern, and southwestern parts of Yunnan. The highly suitable regions shrank by 0.59 × 104–2.16 × 104 km2 under SSPs245 in 2061–2080 and SSPs585 in 2021–2040 and 2041–2060. By contrast, the highly suitable regions increased by 0.33 × 104–9.65 × 104 km2 under other scenarios. The suitable regions migrated towards higher-altitude and higher-latitude regions. Predicting the potential distribution of Arabica coffee based on a species distribution model (MaxEnt) can inform the implementation of long-term plantation development plans to mitigate the effects of climate change on the distribution of Arabica coffee.