Biodiversity Science ›› 2019, Vol. 27 ›› Issue (6): 595-606.doi: 10.17520/biods.2019085

• Original Papers • Previous Article     Next Article

Influence of future climate change in suitable habitats of tea in different countries

Zhang Xiaoling1, 2, Li Yichao2, Wang Yunyun2, Cai Hongyu2, Zeng Hui1, *(), Wang Zhiheng2, *()   

  1. 1 School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, Guangdong 518055
    2 Institute of Ecology and Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871
  • Received:2019-03-18 Accepted:2019-05-06 Online:2019-06-20
  • Zeng Hui,Wang Zhiheng E-mail:zengh@pkusz.edu.cn;zhiheng.wang@pku.edu.cn

Tea (Camellia sinensis) is an important crop and is sensitive to climate change. Evaluating the impact of climate change on tea distribution and production is not only important for the global economy but also the livelihoods of farmers in many countries. Here we compiled data from 858 global occurrences of C. sinensis and six climatic variables, and used species distribution model (SDM) to predict the current potential distribution and possible range shifts in response to climate change in 2070 under Representative Concentration Pathway 2.6 and 8.5 (RCP2.6 and RCP8.5). The results indicate that the current potential distribution of tea is mainly confined to Asia, Africa and South America, and distribution is limited by mean temperature of coldest quarter (MTCQ) and precipitation of warmest quarter (PWQ). Under future climate change scenarios, by 2070 suitable habitat for tea could significantly shrink at low latitudes, but expand at middle latitudes, leading to a northward shift of the distribution. However, the influence of future climate change on tea distribution differed across regions. The climatically suitable areas in Argentina, Myanmar, and Vietnam are projected to decrease by 57.8%-95.8%, whereas those in China and Japan are projected to increase by 2.7%-31.5%. Moreover, 68% of the new suitable habitat for tea cultivation under future climate change are predicted to lie within areas of natural vegetation cover. Therefore, the establishment of new tea gardens in these areas may lead to conflicts between tea cultivation and conservation of natural vegetation and biodiversity.

Key words: climate change, tea plantation, species distribution model, biodiversity conservation, land cover

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

Fig. 1

Response curves of six climate variables"

Fig. 2

Tea occurrence points used for constructing species distribution model and the predicted current potential distribution of tea"

Fig. 3

Predicted suitable range shifts of tea by 2070s under different climate scenarios"

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

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

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."

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
[1] Ahmed S, Stepp JR, Orians C, Griffin T, Matyas C, Robbat A, Cash S, Xue D, Long C, Unachukwu U, Buckley S, Small D, Kennelly E ( 2014) Effects of extreme climate events on tea (Camellia sinensis) functional quality validate indigenous farmer knowledge and sensory preferences in tropical China. PLoS ONE, 9, e109126.
doi: 10.1371/journal.pone.0109126
[2] Allouche O, Tsoar A, Kadmon R ( 2006) Assessing the accuracy of species distribution models: Prevalence, Kappa and the true skill statistic (TSS). Journal of Applied Ecology, 43, 1223-1232.
doi: 10.1111/jpe.2006.43.issue-6
[3] Araújo MB, Peterson AT ( 2012) Uses and misuses of bioclimatic envelope modeling. Ecology, 93, 1527-1539.
doi: 10.1890/11-1930.1
[4] Barbet-Massin M, Jiguet F, Albert CH, Thuiller W ( 2012) Selecting pseudo-absences for species distribution models: How, where and how many? Methods in Ecology and Evolution, 3, 327-338.
doi: 10.1111/j.2041-210X.2011.00172.x
[5] Bartholome E, Belward AS ( 2005) GLC2000: A new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing, 26, 1959-1977.
doi: 10.1080/01431160412331291297
[6] Campbell BM, Vermeulen SJ, Aggarwal PK, Corner-Dolloff C, Girvetz E, Loboguerrero AM, Ramirez-Villegas J, Rosenstock T, Sebastian L, Thornton PK, Wollenberg E ( 2016) Reducing risks to food security from climate change. Global Food Security, 11, 34-43.
doi: 10.1016/j.gfs.2016.06.002
[7] Carr M ( 1972) The climatic requirements of the tea plant: A review. Experimental Agriculture, 8, 1-14.
doi: 10.1017/S0014479700023449
[8] Chang K, Brattlof M ( 2015) Socio-Economic Implications of Climate Change for Tea Producing Countries. Rome, FAO.
[9] Chen L, Zhou ZX ( 2005) Variations of main quality components of tea genetic resources [Camellia sinensis (l.) O. Kuntze] preserved in the China National Germplasm Tea Repository. Plant Foods for Human Nutrition, 60, 31-35.
doi: 10.1007/s11130-005-2540-1
[10] Chen ZM, Chen L ( 2012) Delicious and healthy tea: An overview. In: Global Tea Breeding. Advanced Topics in Science and Technology in China (eds Chen L, Apostolides Z, Chen ZM), pp. 1-11. Springer, Berlin, Heidelberg.
[11] Cobos ME, Peterson AT, Barve N, Osorio-Olvera L ( 2019) kuenm: An R package for detailed development of ecological niche models using Maxent. PeerJ, 7, e6281.
doi: 10.7717/peerj.6281
[12] Davis AP, Gole TW, Baena S, Moat J ( 2012) The impact of climate change on indigenous Arabica coffee (Coffea arabica): Predicting future trends and identifying priorities. PLoS ONE, 7, e47981.
doi: 10.1371/journal.pone.0047981
[13] De Costa W, Mohotti AJ, Wijeratne MA ( 2007) Ecophysiology of tea. Brazilian Journal of Plant Physiology, 19, 299-332.
doi: 10.1590/S1677-04202007000400005
[14] Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carré G, Marquéz JRG, Gruber B, Lafourcade B, Leitão PJ, Münkemüller T, McClean C, Osborne PE, Reineking B, Schröder B, Skidmore AK, Zurell D, Lautenbach S ( 2013) Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36, 27-46.
doi: 10.1111/j.1600-0587.2012.07348.x
[15] Duncan J, Saikia S, Gupta N, Biggs E ( 2016) Observing climate impacts on tea yield in Assam, India. Applied Geography, 77, 64-71.
doi: 10.1016/j.apgeog.2016.10.004
[16] Eden T ( 1965) Tea Tropical Agriculture Series. Longman, London.
[17] Eitzinger A, Läderach P, Quiroga A, Pantoja A, Gordon J ( 2011 a) Future Climate Scenarios for Kenya’s Tea Growing Areas. International Center for Tropical Agriculture (CIAT), Cali, Colombia.
[18] Eitzinger A, Läderach P, Quiroga A, Pantoja A, Gordon J ( 2011 b) Future Climate Scenarios for Uganda’s Tea Growing Areas. International Center for Tropical Agriculture (CIAT), Cali, Colombia.
[19] Food and Agriculture Organization of the United Nations ( FAO) ( 2016) FAOSTAT Database. http://www.fao.org/ faostat/en/#data. (accessed on 2018-12-24)
[20] Gallien L, Münkemüller T, Albert CH, Boulangeat I, Thuiller W ( 2010) Predicting potential distributions of invasive species: Where to go from here? Diversity and Distributions, 16, 331-342.
doi: 10.1111/j.1472-4642.2010.00652.x
[21] Han W, Li X, Yan P, Zhang L, Ahammed GJ ( 2018) Tea cultivation under changing climatic conditions. In: Global Tea Science (eds Sharma VS, Kumudini GMT), pp. 455-472. Burleigh Dodds Science Publishing Limited, Cambridge.
[22] Hannah L, Roehrdanz PR, Ikegami M, Shepard AV, Shaw MR, Tabor G, Zhi L, Marquet PA, Hijmans RJ ( 2013) Climate change, wine, and conservation. Proceedings of the National Academy of Sciences, USA, 110, 6907-6912.
doi: 10.1073/pnas.1210127110
[23] Huang SB ( 1981) Agrometeorological index for tea growth. Chinese Journal of Agrometeorology, 2(3), 54-58. (in Chinese)
[ 黄寿波 ( 1981) 茶树生长的农业气象指标. 农业气象, 2(3), 54-58.]
[24] Huang SB, Fan XH, Yao GK ( 1993) Microclimate in tea tree crown and its effect on growth, development and biochemical composition of new shoots. Chinese Journal of Applied Ecology, 4, 99-101. (in Chinese with English abstract)
[ 黄寿波, 范兴海, 姚国坤 ( 1993) 丛栽茶树树冠小气候及其对新梢生育和生化成分的影响. 应用生态学报, 4, 99-101.]
[25] Imbach P, Fung E, Hannah L, Navarro-Racines CE, Roubik DW, Ricketts TH, Harvey CA, Donatti CI, Laderach P, Locatelli B, Roehrdanz PR ( 2017) Coupling of pollination services and coffee suitability under climate change. Proceedings of the National Academy of Sciences, USA, 114, 10438-10442.
doi: 10.1073/pnas.1617940114
[26] IPCC( 2013) Climate change 2013: The physical science basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge.
[27] Jin ZF, Yang D, Yao YP, Li RZ, Wang ZH ( 2016) Assessment on climatic potential productivity of tea in Zhejiang Province. Chinese Journal of Ecology, 35, 1791-1798. (in Chinese with English abstract)
[ 金志凤, 杨栋, 姚益平, 李仁忠, 王治海 ( 2016) 浙江省茶叶气候生产潜力评估. 生态学杂志, 35, 1791-1798.]
[28] Jin ZF, Ye JG, Yang ZQ, Sun R, Hu B, Li RZ ( 2014) Climate suitability for tea growing in Zhejiang Province. Chinese Journal of Applied Ecology, 25, 967-973. (in Chinese with English abstract)
[ 金志凤, 叶建刚, 杨再强, 孙睿, 胡波, 李仁忠 ( 2014) 浙江省茶叶生长的气候适宜性. 应用生态学报, 25, 967-973.]
[29] Larson C ( 2015) Reading the tea leaves for effects of climate change. Science, 348, 953-954.
doi: 10.1126/science.348.6238.953
[30] Li HM, Ma YX, Liu WJ, Liu WJ ( 2012) Soil changes induced by rubber and tea plantation establishment: Comparison with tropical rain forest soil in Xishuangbanna, SW China. Environmental Management, 50, 837-848.
doi: 10.1007/s00267-012-9942-2
[31] Liaw A, Wiener M ( 2002) Classification and regression by randomForest. R News, 2, 18-22.
[32] Lobell DB, Schlenker W, Costa-Roberts J ( 2011) Climate trends and global crop production since 1980. Science, 333, 616-620.
doi: 10.1126/science.1204531
[33] McCullagh P, Nelder JA ( 1989) Generalized Linear Models. CRC Press, Boca Raton, USA.
[34] Mondal TK, Bhattacharya A, Laxmikumaran M, Ahuja PS ( 2004) Recent advances of tea (Camellia sinensis) biotechnology. Plant Cell, Tissue and Organ Culture, 76, 195-254.
doi: 10.1023/B:TICU.0000009254.87882.71
[35] Mukhopadhyay M, Mondal TK ( 2017) Cultivation, Improvement, and Environmental Impacts of Tea. Oxford University Press, Oxford.
[36] Nemec-Boehm RL, Cash SB, Anderson BT, Ahmed S, Griffin TS, Orians CM, Robbat AJ, Stepp RA, Han WY ( 2014) Climate change, the monsoon, and tea yields in China. Agricultural and Applied Economics Association’s 2014 AAEA Annual Meeting, Minnesota.
[37] Nowogrodzki A ( 2019) How climate change might affect tea. Nature, 566, S10.
doi: 10.1038/d41586-019-00399-0
[38] Ochieng J, Kirimi L, Mathenge M ( 2016) Effects of climate variability and change on agricultural production: The case of small scale farmers in Kenya. NJAS-Wageningen Journal of Life Sciences, 77, 71-78.
doi: 10.1016/j.njas.2016.03.005
[39] Ovalle-Rivera O, Laderach P, Bunn C, Obersteiner M, Schroth G ( 2015) Projected shifts in Coffea arabica suitability among major global producing regions due to climate change. PLoS ONE, 10, e0124155.
doi: 10.1371/journal.pone.0124155
[40] Owuor PO, Wachira FN, Ng’etich WK ( 2010) Influence of region of production on relative clonal plain tea quality parameters in Kenya. Food Chemistry, 119, 1168-1174.
doi: 10.1016/j.foodchem.2009.08.032
[41] Parry M, Canziani O, Palutikof J, van der Linden PJ, Hanson CE ( 2007) Climate Change 2007: Impacts, Adaptation and Vulnerability. Cambridge University Press, Cambridge.
[42] Pearson RG, Dawson TP ( 2003) Predicting the impacts of climate change on the distribution of species: Are bioclimate envelope models useful? Global Ecology and Biogeography, 12, 361-371.
doi: 10.1046/j.1466-822X.2003.00042.x
[43] Peterson AT, Papeş M, Soberón J ( 2008) Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecological Modelling, 213, 63-72.
doi: 10.1016/j.ecolmodel.2007.11.008
[44] Phillips SJ, Anderson RP, Schapire RE ( 2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-259.
doi: 10.1016/j.ecolmodel.2005.03.026
[45] Pineda E, Lobo JM ( 2009) Assessing the accuracy of species distribution models to predict amphibian species richness patterns. Journal of Animal Ecology, 78, 182-190.
doi: 10.1111/jae.2009.78.issue-1
[46] R Core Team ( 2017) R: A Language and Environment for Statistical Computing. https://www.R-project.org/. ( accessed on 2019-01-13)
[47] Schmidhuber J, Tubiello FN ( 2007) Global food security under climate change. Proceedings of the National Academy of Sciences, USA, 104, 19703-19708.
doi: 10.1073/pnas.0701976104
[48] Schroth G, Läderach P, Martinez-Valle AI, Bunn C, Jassogne L ( 2016) Vulnerability to climate change of cocoa in West Africa: Patterns, opportunities and limits to adaptation. Science of the Total Environment, 556, 231-241.
doi: 10.1016/j.scitotenv.2016.03.024
[49] Thuiller W, Lafourcade B, Engler R, Araújo MB ( 2009) BIOMOD—A platform for ensemble forecasting of species distributions. Ecography, 32, 369-373.
doi: 10.1111/eco.2009.32.issue-3
[50] Wijeratne M, Anandacoomaraswamy A, Amarathunga M, Ratnasiri J, Basnayake B, Kalra N ( 2007) Assessment of impact of climate change on productivity of tea (Camellia sinensis L.) plantations in Sri Lanka. Journal of the National Science Foundation of Sri Lanka, 35, 119-126.
doi: 10.4038/jnsfsr.v35i2.3676
[51] Wu TW, Song LC, Li WP, Wang ZZ, Zhang H, Xin XG, Zhang YW, Zhang L, Li JL, Wu FH ( 2014) An overview of BCC climate system model development and application for climate change studies. Journal of Meteorological Research, 28, 34-56.
[52] Yan YJ, Li Y, Wang WJ, He JS, Yang RH, Wu HJ, Wang XL, Jiao L, Tang ZY, Yao YJ ( 2017) Range shifts in response to climate change of Ophiocordyceps sinensis, a fungus endemic to the Tibetan Plateau. Biological Conservation, 206, 143-150.
doi: 10.1016/j.biocon.2016.12.023
[53] Zhu GP, Fan JY, Wang ML, Chen M, Qiao HJ ( 2017) The importance of the shape of receiver operating characteristic (ROC) curve in ecological model evaluation—Case study of Hlyphantria cunea. Journal of Biosafety, 26, 184-190. (in Chinese with English abstract)
[ 朱耿平, 范靖宇, 王梦琳, 陈敏, 乔慧捷 ( 2017) ROC曲线形状在生态位模型评价中的重要性——以美国白蛾为例. 生物安全学报, 26, 184-190.]
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