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

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 en...

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Autores principales:	Shuo Zhang, Xiaogang Liu, Rongmei Li, Xinle Wang, Jinhuan Cheng, Qiliang Yang, Hao Kong
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Climate change AHP-GIS MaxEnt model Potential geographical distribution Arabica coffee Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/a63a86b124d54301b28f85900ad029b4
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spelling	oai:doaj.org-article:a63a86b124d54301b28f85900ad029b42021-12-01T05:02:57ZAHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China1470-160X10.1016/j.ecolind.2021.108339https://doaj.org/article/a63a86b124d54301b28f85900ad029b42021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21010049https://doaj.org/toc/1470-160XCoffee, 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 × 104–4.42 × 104 km2 and 3.53 × 104–5.44 × 104 km2 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.Shuo ZhangXiaogang LiuRongmei LiXinle WangJinhuan ChengQiliang YangHao KongElsevierarticleClimate changeAHP-GISMaxEnt modelPotential geographical distributionArabica coffeeEcologyQH540-549.5ENEcological Indicators, Vol 132, Iss , Pp 108339- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Climate change AHP-GIS MaxEnt model Potential geographical distribution Arabica coffee Ecology QH540-549.5
spellingShingle	Climate change AHP-GIS MaxEnt model Potential geographical distribution Arabica coffee Ecology QH540-549.5 Shuo Zhang Xiaogang Liu Rongmei Li Xinle Wang Jinhuan Cheng Qiliang Yang Hao Kong AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China
description	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 × 104–4.42 × 104 km2 and 3.53 × 104–5.44 × 104 km2 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.
format	article
author	Shuo Zhang Xiaogang Liu Rongmei Li Xinle Wang Jinhuan Cheng Qiliang Yang Hao Kong
author_facet	Shuo Zhang Xiaogang Liu Rongmei Li Xinle Wang Jinhuan Cheng Qiliang Yang Hao Kong
author_sort	Shuo Zhang
title	AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China
title_short	AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China
title_full	AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China
title_fullStr	AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China
title_full_unstemmed	AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China
title_sort	ahp-gis and maxent for delineation of potential distribution of arabica coffee plantation under future climate in yunnan, china
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/a63a86b124d54301b28f85900ad029b4
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AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China

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