生物多样性 ›› 2019, Vol. 27 ›› Issue (6): 595-606. DOI: 10.17520/biods.2019085
张晓玲1,2,李亦超2,王芸芸2,蔡宏宇2,曾辉1,*(),王志恒2,*(
)
收稿日期:
2019-03-18
接受日期:
2019-05-06
出版日期:
2019-06-20
发布日期:
2019-06-20
通讯作者:
曾辉,王志恒
基金资助:
Zhang Xiaoling1,2,Li Yichao2,Wang Yunyun2,Cai Hongyu2,Zeng Hui1,*(),Wang Zhiheng2,*(
)
Received:
2019-03-18
Accepted:
2019-05-06
Online:
2019-06-20
Published:
2019-06-20
Contact:
Zeng Hui,Wang Zhiheng
摘要:
茶是对气候变化敏感的重要经济作物, 评价全球气候变化对茶分布和生产的影响对相关国家经济发展和茶农的生计至关重要。本研究基于全球858个茶分布点和6个气候因子数据, 利用物种分布模型预测全球茶的潜在适宜分布区及其在2070年的不同温室气体排放情景(RCP2.6和RCP8.5)下的变化。结果表明: 当前茶在五大洲均有适宜分布区, 主要集中在亚洲、非洲和南美洲, 并且最冷季平均温和最暖季降水量主导了茶的分布。预计2070年, 茶的适宜分布区变化在不同的大洲、国家和气候情景间将存在差异。具体来说, 茶的适宜分布区总面积将会减少, 减少的区域主要位于低纬度地区, 而中高纬度地区的适宜分布区将扩张, 由此可能导致茶的适宜分布区向北移动; 重要的产茶国中, 阿根廷、缅甸、越南等茶适宜分布区面积会减少57.8%-95.8%, 而中国和日本的适宜分布面积则会增加2.7%-31.5%。未来全球新增的适宜分布区中, 约有68%的地区土地覆盖类型为自然植被, 因此可能导致新茶树种植园的开垦和自然植被及生物多样性保护产生冲突。
张晓玲, 李亦超, 王芸芸, 蔡宏宇, 曾辉, 王志恒 (2019) 未来气候变化对不同国家茶适宜分布区的影响. 生物多样性, 27, 595-606. DOI: 10.17520/biods.2019085.
Zhang Xiaoling, Li Yichao, Wang Yunyun, Cai Hongyu, Zeng Hui, Wang Zhiheng (2019) Influence of future climate change in suitable habitats of tea in different countries. Biodiversity Science, 27, 595-606. DOI: 10.17520/biods.2019085.
环境变量 Environmental variables | 平均重要性 Mean importance |
---|---|
最冷季平均温 Mean temperature of coldest quarter | 0.36 |
最暖季降水量 Precipitation of warmest quarter | 0.27 |
降水季节性 Precipitation seasonality | 0.09 |
平均气温日较差 Mean diurnal temperature range | 0.06 |
最暖月最高温 Max temperature of warmest month | 0.04 |
最干月降水量 Precipitation of driest month | 0.03 |
土壤酸碱度 Soil pH | 0.00 |
表1 7个环境变量的平均重要性
Table 1 Mean importance of seven environmental variables
环境变量 Environmental variables | 平均重要性 Mean importance |
---|---|
最冷季平均温 Mean temperature of coldest quarter | 0.36 |
最暖季降水量 Precipitation of warmest quarter | 0.27 |
降水季节性 Precipitation seasonality | 0.09 |
平均气温日较差 Mean diurnal temperature range | 0.06 |
最暖月最高温 Max temperature of warmest month | 0.04 |
最干月降水量 Precipitation of driest month | 0.03 |
土壤酸碱度 Soil pH | 0.00 |
图2 用于物种分布模型构建的茶分布点和预测的现在茶潜在分布(世界地图来源于https://www.naturalearthdata.com/down loads/50m-physical-vectors/)
Fig. 2 Tea occurrence points used for constructing species distribution model and the predicted current potential distribution of tea
图3 预测的2070年不同气候情景下茶适宜分布区变化(世界地图来源于https://www.naturalearthdata.com/downloads/50m -physical-vectors/)
Fig. 3 Predicted suitable range shifts of tea by 2070s under different climate scenarios
气候情景 Scenarios | 新增的分布区 Gain | 丧失的分布区 Loss | 适宜分布面积的净变化 Net changes in suitable area |
---|---|---|---|
RCP2.6 | 9.1 | 18.6 | -9.5 |
RCP8.5 | 14.2 | 31.1 | -16.9 |
表2 预测2070年不同气候情景下茶适宜分布区的变化(%)
Table 2 Predicted suitable area changes of tea (%) for the 2070s
气候情景 Scenarios | 新增的分布区 Gain | 丧失的分布区 Loss | 适宜分布面积的净变化 Net changes in suitable area |
---|---|---|---|
RCP2.6 | 9.1 | 18.6 | -9.5 |
RCP8.5 | 14.2 | 31.1 | -16.9 |
国家 Countries | 当前适宜分布区 Current suitable area (km2) | 适宜分布面积变化 Changes in suitable area (km2) | 适宜分布面积变化比例 Changes in suitable area (%) | 产量 (2016年) Production (t) | ||
---|---|---|---|---|---|---|
RCP2.6 | RCP8.5 | RCP2.6 | RCP8.5 | |||
中国 China | 2,607,924 | 69,384 | 135,088 | 2.7 | 5.2 | 2,414,802 |
印度 India | 315,323 | -9,241 | -25,162 | -2.9 | -8.0 | 1,252,174 |
肯尼亚 Kenya | 17,994 | -4,470 | -5,834 | -24.8 | -32.4 | 473,000 |
斯里兰卡 Sri Lanka | 9,356 | -232 | -3,323 | -2.5 | -35.5 | 349,308 |
土耳其 Turkey | 2,765 | 654 | -1,619 | 23.7 | -58.6 | 243,000 |
越南 Vietnam | 75,599 | -43,657 | -55,005 | -57.8 | -72.8 | 240,000 |
印度尼西亚 Indonesia | 260,214 | -31,551 | -94,931 | -12.1 | -36.5 | 144,015 |
缅甸 Myanmar | 38,221 | -28,938 | -35,895 | -75.7 | -93.9 | 102,404 |
阿根廷 Argentina | 32,876 | -31,085 | -31,503 | -94.6 | -95.8 | 89,609 |
日本 Japan | 279,395 | 27,910 | 87,979 | 10.0 | 31.5 | 80,200 |
表3 未来不同气候情景下主要产茶国家的适宜分布区面积变化
Table 3 Changes of suitable area in major tea-producing countries under different future climate scenarios
国家 Countries | 当前适宜分布区 Current suitable area (km2) | 适宜分布面积变化 Changes in suitable area (km2) | 适宜分布面积变化比例 Changes in suitable area (%) | 产量 (2016年) Production (t) | ||
---|---|---|---|---|---|---|
RCP2.6 | RCP8.5 | RCP2.6 | RCP8.5 | |||
中国 China | 2,607,924 | 69,384 | 135,088 | 2.7 | 5.2 | 2,414,802 |
印度 India | 315,323 | -9,241 | -25,162 | -2.9 | -8.0 | 1,252,174 |
肯尼亚 Kenya | 17,994 | -4,470 | -5,834 | -24.8 | -32.4 | 473,000 |
斯里兰卡 Sri Lanka | 9,356 | -232 | -3,323 | -2.5 | -35.5 | 349,308 |
土耳其 Turkey | 2,765 | 654 | -1,619 | 23.7 | -58.6 | 243,000 |
越南 Vietnam | 75,599 | -43,657 | -55,005 | -57.8 | -72.8 | 240,000 |
印度尼西亚 Indonesia | 260,214 | -31,551 | -94,931 | -12.1 | -36.5 | 144,015 |
缅甸 Myanmar | 38,221 | -28,938 | -35,895 | -75.7 | -93.9 | 102,404 |
阿根廷 Argentina | 32,876 | -31,085 | -31,503 | -94.6 | -95.8 | 89,609 |
日本 Japan | 279,395 | 27,910 | 87,979 | 10.0 | 31.5 | 80,200 |
图4 未来气候变化下, 茶适宜分布区面积变化最多的前10个国家。(a)适宜分布区面积减少; (b)适宜分布区面积增加。
Fig. 4 Top ten countries with the largest changes in suitable area for tea under different future climate scenarios. (a) Loss suitable area; (b) Gain suitable area.
土地覆盖类型 Land cover | 新增适宜分布区的来源 Source of newly suitable areas (%) | |
---|---|---|
RCP2.6 | RCP8.5 | |
森林 Forest | 46.9 | 41.5 |
灌木 Shrub | 5.4 | 8.0 |
草地 Grassland | 15.9 | 19.4 |
耕地 Farmland | 20.0 | 16.4 |
建设用地 Urban | 0.5 | 0.3 |
其他 Others | 11.2 | 14.4 |
表4 不同未来气候情景下新增茶适宜分布区的来源
Table 4 The source of newly suitable areas for tea cultivation under different future climate scenarios
土地覆盖类型 Land cover | 新增适宜分布区的来源 Source of newly suitable areas (%) | |
---|---|---|
RCP2.6 | RCP8.5 | |
森林 Forest | 46.9 | 41.5 |
灌木 Shrub | 5.4 | 8.0 |
草地 Grassland | 15.9 | 19.4 |
耕地 Farmland | 20.0 | 16.4 |
建设用地 Urban | 0.5 | 0.3 |
其他 Others | 11.2 | 14.4 |
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