AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China. (December 2021)

• Record Type: Journal Article
• Authors: Zhang, Shuo; Liu, Xiaogang; Li, Rongmei; Wang, Xinle; Cheng, Jinhuan; Yang, Qiliang; Kong, Hao
• Is Part Of: Ecological indicators. Volume 132(2021)
• Publication Date: 2021-12
• Subjects: Climate change -- AHP-GIS -- MaxEnt model -- Potential geographical distribution -- Arabica coffee; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2021.108339
• Languages: English
• ISSNs: 1470-160X

Abstract

Graphical abstract: Highlights: MaxEnt and AHP-GIS were used to predict potential distribution. Bio5, Bio6, Bio12, altitude, slope, sand and silt were the most key factors. Under SSPs370, the most suitable area of Arabica coffee has increased. Arabica coffee showed range expansions towards higher elevation and latitude. Abstract: Coffee, as one of three major beverages all over the world, is featured by many functions mainly including refreshment, diuresis, invigorating stomach and stimulating appetite. However, there still lack of studies regarding the potential distribution of suitable planting regions and the important environmental factors that affect the growth and development of Arabica coffee . Based on climate, terrain and soil data, MaxEnt model and AHP-GIS technology were used to evaluate and analyze the increase and decrease range of Arabica coffee ecological suitability planting areas and most suitable areas in different periods, determine the most significant environmental factors affecting ecological suitability, and determine the distribution transformation under climate change scenario (SSPs370). Results showed that the ecological suitability of Arabica coffee plantation was mainly subjected to the climate factors, among which the maximum temperature in the warmest month, minimum temperature in the coldest month and the annual precipitation were particularly important, followed by terrain and soil factors. The model accuracies of MaxEnt and AHP-GIS were 0.925 and 0.833 respectively, indicating that the two methods were reliable in the ecological suitability evaluation of Arabica coffee . MaxEnt predicted that the most and moderately suitable area accounted for 16.26% and 22.59%, and AHP-GIS predicted that they accounted for 13.35% and 41.32% of the total area respectively. The most and moderately suitable areas were mainly concentrated in west, southeast, south and southwest Yunnan. Under the future climate scenario model, MaxEnt and AHP-GIS predicted that the area of the most suitable area would increase by 2.62 × 10 4 –4.42 × 10 4 km 2 and 3.53 × 10 4 –5.44 × 10 4 km 2 respectively from 2021 to 2100, which were mainly concentrated in west, southwest and southeast Yunnan. At the same time, the distribution of the most suitable area migrated northward generally to higher altitude and higher latitude, and the migration distance was 27.44–92.22 km. The predicted potential distribution of Arabica coffee based on MaxEnt model and AHP-GIS model could provide reference for the implementation of long-term planning and development programs so as to alleviate the effects of climate change on the distribution of Arabica coffee .