MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenario
IntroductionCoffea arabica (Arabica coffee) is an important cash crop in Yunnan, China. Ongoing climate change has made coffee production more difficult to sustain, posing challenges for the region’s coffee industry. Predictions of the distribution of potentially suitable habitats for Arabica coffee...
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2024.1471653/full |
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| author | Xia Li Xia Li Zihao Wang Shaoqiang Wang Shaoqiang Wang Zhaohui Qian Zhaohui Qian |
| author_facet | Xia Li Xia Li Zihao Wang Shaoqiang Wang Shaoqiang Wang Zhaohui Qian Zhaohui Qian |
| author_sort | Xia Li |
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| description | IntroductionCoffea arabica (Arabica coffee) is an important cash crop in Yunnan, China. Ongoing climate change has made coffee production more difficult to sustain, posing challenges for the region’s coffee industry. Predictions of the distribution of potentially suitable habitats for Arabica coffee in Yunnan could provide a theoretical basis for the cultivation and rational management of this species.MethodsIn this study, the MaxEnt model was used to predict the potential distribution of suitable habitat for Arabica coffee in Yunnan under current and future (2021-2100) climate scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) using 56 distributional records and 17 environmental variables and to analyze the important environmental factors. Marxan model was used to plan the priority planting areas for this species at last.ResultsThe predicted suitable and sub-suitable areas were about 4.21×104 km2 and 13.87×104 km2, respectively, accounting for 47.15% of the total area of the province. The suitable areas were mainly concentrated in western and southern Yunnan. The minimum temperature of the coldest month, altitude, mean temperature of the wettest quarter, slope, and aluminum saturation were the main environmental variables affecting the distribution of Arabica coffee in Yunnan Province. Changes in habitat suitability for Arabica coffee were most significant and contracted under the SSP3-7.0 climate scenario, while expansion was highest under the SSP5-8.5 climate scenario. Priority areas for Arabica coffee cultivation in Yunnan Province under the 30% and 50% targets were Pu’er, Xishuangbanna, Honghe, Dehong, and Kunming.DiscussionClimate, soil, and topography combine to influence the potential geographic distribution of Arabica coffee. Future changes in suitable habitat areas under different climate scenarios should lead to the delineation of coffee-growing areas based on appropriate environmental conditions and active policy measures to address climate change. |
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| institution | OA Journals |
| issn | 1664-462X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Plant Science |
| spelling | doaj-art-a426d7e0a3ce470cb39e059a2eb478032025-08-20T02:07:23ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2024-11-011510.3389/fpls.2024.14716531471653MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenarioXia Li0Xia Li1Zihao Wang2Shaoqiang Wang3Shaoqiang Wang4Zhaohui Qian5Zhaohui Qian6College of Environmental Science and Engineering, Tongji University, Shanghai, ChinaForeign Environmental Cooperation Center, Ministry of Ecology and Environment, Beijing, ChinaHubei Key Laboratory of Regional Ecology and Environmental Change, China University of Geosciences, Wuhan, ChinaHubei Key Laboratory of Regional Ecology and Environmental Change, China University of Geosciences, Wuhan, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, ChinaForeign Environmental Cooperation Center, Ministry of Ecology and Environment, Beijing, ChinaInstitute of Advanced Studies, China University of Geosciences, Wuhan, ChinaIntroductionCoffea arabica (Arabica coffee) is an important cash crop in Yunnan, China. Ongoing climate change has made coffee production more difficult to sustain, posing challenges for the region’s coffee industry. Predictions of the distribution of potentially suitable habitats for Arabica coffee in Yunnan could provide a theoretical basis for the cultivation and rational management of this species.MethodsIn this study, the MaxEnt model was used to predict the potential distribution of suitable habitat for Arabica coffee in Yunnan under current and future (2021-2100) climate scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) using 56 distributional records and 17 environmental variables and to analyze the important environmental factors. Marxan model was used to plan the priority planting areas for this species at last.ResultsThe predicted suitable and sub-suitable areas were about 4.21×104 km2 and 13.87×104 km2, respectively, accounting for 47.15% of the total area of the province. The suitable areas were mainly concentrated in western and southern Yunnan. The minimum temperature of the coldest month, altitude, mean temperature of the wettest quarter, slope, and aluminum saturation were the main environmental variables affecting the distribution of Arabica coffee in Yunnan Province. Changes in habitat suitability for Arabica coffee were most significant and contracted under the SSP3-7.0 climate scenario, while expansion was highest under the SSP5-8.5 climate scenario. Priority areas for Arabica coffee cultivation in Yunnan Province under the 30% and 50% targets were Pu’er, Xishuangbanna, Honghe, Dehong, and Kunming.DiscussionClimate, soil, and topography combine to influence the potential geographic distribution of Arabica coffee. Future changes in suitable habitat areas under different climate scenarios should lead to the delineation of coffee-growing areas based on appropriate environmental conditions and active policy measures to address climate change.https://www.frontiersin.org/articles/10.3389/fpls.2024.1471653/fullArabica coffeeMAXENT modelMarxan modelmain environmental variablepotential habitatpriority planting area |
| spellingShingle | Xia Li Xia Li Zihao Wang Shaoqiang Wang Shaoqiang Wang Zhaohui Qian Zhaohui Qian MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenario Frontiers in Plant Science Arabica coffee MAXENT model Marxan model main environmental variable potential habitat priority planting area |
| title | MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenario |
| title_full | MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenario |
| title_fullStr | MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenario |
| title_full_unstemmed | MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenario |
| title_short | MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenario |
| title_sort | maxent and marxan modeling to predict the potential habitat and priority planting areas of coffea arabica in yunnan china under climate change scenario |
| topic | Arabica coffee MAXENT model Marxan model main environmental variable potential habitat priority planting area |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2024.1471653/full |
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