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Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

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Abstract

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the “fluctuation threshold” which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981–2012. The results showed that extreme events were found to have the greatest impact on early rice yield (−2.59 to −15.89%). Followed by climatic fluctuations with a range of −2.60 to −4.46%, and then the climatic trend (4.91–2.12%). Furthermore, the influence of climatic trend on early rice yield presented “trade-offs” among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (−2.11 to −12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

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References

  • Aggarwal PK, Mall RK (2002) Climate change and rice yields in diverse agro-environments of India. II. Effect of uncertainties in scenarios and crop models on impact assessment. Clim Change 52(3):331–343

    Google Scholar 

  • Ågnström A (1924) Solar and terrestrial radiation. Q J R Meteorol Soc 52:121–125

    Google Scholar 

  • Akinbile CO (2011). Rice production and water use efficiency for self-sufficiency in Malaysia: a review. Trends Appl Sci Res 6(10):1127–1140

    Google Scholar 

  • Akinbile CO, Akinlade GM, Abolude AT (2015) Trend analysis in climatic variables and impacts on rice yield in Nigeria. J Water Clim Change 6(3):534–543

    Google Scholar 

  • Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank AMG, Haylock M, Collins D, Trewin B, Rahimzadeh F (2012) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res Atmos 111(D5):1042–1063

    Google Scholar 

  • Amiri E, Rezaei M, Bannayan M, Soufizadeh S (2013) Calibration and evaluation of CERES-Rice model under different nitrogen- and water-management options in Semi-Mediterranean climate condition. Commun Soil Sci Plant Anal 44(12):289–291

    Google Scholar 

  • Auffhammer M, Ramanathan V, Vincent JR (2012) Climate change, the monsoon, and rice yield in India. Clim Change 111(2):411–424

    Google Scholar 

  • Bai H, Tao F, Xiao D, Liu F, Zhang H (2016) Attribution of yield change for rice-wheat rotation system in China to climate change, cultivars and agronomic management in the past three decades. Clim Change 135(3):539–553

    Google Scholar 

  • Banerjee S, Mukherjee A, Das S, Mukherjee A, Saikia B (2016) Adaptation strategies to combat climate change effect on rice and mustard in Eastern India. Mitig Adapt Strateg Glob Change 21(2):1–13

    Google Scholar 

  • CMA (2012). Definition and classification of rainstorm. China Meteorological Administration, Beijing

    Google Scholar 

  • Conradt S, Bokusheva R, Finger R, Kussaiynov T (2012) Yield trend estimation in the presence of non-constant technological change and weather effects// 123rd Seminar, February 23-24, 2012, Dublin, Ireland. European Association of Agricultural Economists: 23–24

  • Daokuo GE, Jin ZQ, Lin SC, Zhi GL (2002) Gradual impacts of climate change on rice production and adaptation strategies in Southern China. Jiangsu J Agric Sci 18(1):1–8

    Google Scholar 

  • Deryng D, Conway D, Ramankutty N, Price J, Warren R (2014) Global crop yield response to extreme heat stress under multiple climate change futures. Environ Res Lett 9(3):2033–2053

    Google Scholar 

  • Dinse K (2009) Climate variability and climate change: what is the difference. Michigan Sea Grant. http://www.miseagrant.umich.edu/climate

  • Erda L, Wei X, Hui J, Yinlong X, Yue L, Liping B, Liyong X (2005) Climate change impacts on crop yield and quality with CO2 fertilization in China. Philos Trans R Soc Lond B Biol Sci 360(1463): 2149–2154

    Google Scholar 

  • FAOSTAT (2015) Crops download data: rice, paddy. FAO. http://www.fao.org/faostat/en/#data/QC. Accessed on 17 Feb 2017

  • GB/T 21985-2008 (2008) Temperature index of high temperature harm for main crop. China Standards Press, Beijing

    Google Scholar 

  • GB/T 27959-2011 (2012) Low temperature disaster of southern rice, rapeseed and orange. China Standards Press, Beijing

    Google Scholar 

  • Hansen J, Sato M, Ruedy R (2011) Climate variability and climate change: the new climate dice. NASA Goddard Institute for Space Studies, New York: 1–12

  • Hatfield JL, Prueger JH (2015) Temperature extremes: effect on plant growth and development. Weather Clim Extremes 10(PA):4–10

    Google Scholar 

  • Hess T (2012) Climate change impacts on crop productivity in Africa and South Asia. Environ Res Lett 7(3):34032–34039

    Google Scholar 

  • Hollinger SE, Angel JR (2009). Weather and crops. Illinois agronomy handbook. University of Illinois Extension, Urbana, pp 1–12

    Google Scholar 

  • Hossain MJ, Kuri SK, Islam MS, Mondal U, Hossain MJ, Islam MS, Mondal U (2014) Estimating the effect of climate change on rice yield: a study from Mymensingh district of Bangladesh using quantile regression method. Int J Sustain Crop Prod 9(1):1–7

    Google Scholar 

  • IPCC (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of working groups I and II of the Intergovernmental Panel on Climate Change. CU Press, Cambridge

    Google Scholar 

  • IPCC (2013) Climate change 2013: The physical science basis. Contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. CU Press, Cambridge

    Google Scholar 

  • IPCC (2014) Climate change 2014: Impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of working group II to the fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt L, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT (2003) The DSSAT cropping system model. Eur J Agron 18(3):235–265

    Google Scholar 

  • Kim M-K, Pang A (2009) Climate change impact on rice yield and production risk. J Rural Dev 32(2):17–29

    Google Scholar 

  • Kim HY, Ko J, Kang S, Tenhunen J (2013). Impacts of climate change on paddy rice yield in a temperate climate. Glob Change Biol 19(2):548–562

    Google Scholar 

  • Kuwagata T, Yoshimoto M, Ishigooka Y, Hasegawa T, Utsumi M, Nishimori M, Masaki Y, Saito O (2011) MeteoCrop DB: an agro-meteorological database coupled with crop models for studying climate change impacts on rice in Japan. J Agric Meteorol 67(4):297–306

    Google Scholar 

  • Larson R, Farber B (2006) Elementary statistics. Pearson Custom Pub

  • Lenton TM (2011) Early warning of climate tipping points. Nat Clim Change 1(4):201–209

    Google Scholar 

  • Lesk C, Rowhani P, Ramankutty N (2016) Influence of extreme weather disasters on global crop production. Nature 529(7584):84–87

    Google Scholar 

  • Li Y, Wenxiang WU, Ge Q, Zhou Y, Chenchen XU (2016) Simulating climate change impacts and adaptive measures for rice cultivation in Hunan province, China. J Appl Meteorol Climatol 55(6):1359–1376

    Google Scholar 

  • Lilliefors HW (1967) On the Kolmogorov–Smirnov test for normality with mean and variance unknown. J Am Stat Assoc 62(318):399–402

    Google Scholar 

  • Liu Y, Yu D, Su Y, Hao R (2014) Quantifying the effect of trend, fluctuation, and extreme event of climate change on ecosystem productivity. Environ Monit Assess 186(12):8473–8486

    Google Scholar 

  • Liu S, Xue J, Zhang R, Chen Z, Chen F, Hu S, Zhang H (2015) Sensitivity analysis of double-rice yield under climate change in Hunan Province. Trans Chin Soc Agric Eng 31(6):246–252

    Google Scholar 

  • Loague K, Green RE (1991) Statistical and graphical methods for evaluating solute transport models: overview and application. J Contam Hydrol 7(1–2):51–73

    Google Scholar 

  • Lobell DB (2007a) Changes in diurnal temperature range and national cereal yields. Agric For Meteorol 145(3):229–238

    Google Scholar 

  • Lobell DB, Asseng S (2017) Comparing estimates of climate change impacts from process-based and statistical crop models. Environ Res Lett 12(1):1–12

    Google Scholar 

  • Lobell DB, Field CB (2007b) Global scale climate–crop yield relationships and the impacts of recent warming. Environ Res Lett 2(1):625–630

    Google Scholar 

  • Lobell DB, Gourdji SM (2012) The influence of climate change on global crop productivity. Plant Physiol 160(4):1686–1697

    Google Scholar 

  • Lobell DB, Tebaldi C (2014) Getting caught with our plants down: the risks of a global crop yield slowdown from climate trends in the next two decades. Environ Res Lett 9(7):1–8

    Google Scholar 

  • Lobell DB, Schlenker W, Costa-Roberts J (2011) Climate trends and global crop production since 1980. Science 333(6042):616–620

    Google Scholar 

  • Lu Y, Jin J, Kueppers LM (2015) Crop growth and irrigation interact to influence surface fluxes in a regional climate-cropland model (WRF3.3-CLM4crop). Clim Dyn 45(11–12):3347–3363

    Google Scholar 

  • Luterbacher J, Dietrich D, Xoplaki E, Grosjean M, Wanner H (2004) European seasonal and annual temperature variability, trends, and extremes since 1500. Science 303(5663):1499–1503

    Google Scholar 

  • Mann ME (2008) Smoothing of climate time series revisited. Geophys Res Lett 35(16):134–143

    Google Scholar 

  • Mann ME (2013) On smoothing potentially non-stationary climate time series. Geophys Res Lett 31(7):10–1029

    Google Scholar 

  • Mastrandrea MD, Tebaldi C, Snyder CW, Schneider SH (2011) Current and future impacts of extreme events in California. Clim Change 109(109):43–70

    Google Scholar 

  • Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT, Gregory JM, Kitoh A, Knutti R, Murphy JM, Noda A (2007) Climate change 2007: mitigation. Contribution of Working Group III to the fourth assessment report of the Intergovernmental Panel on Climate Change 2007:533–535

  • Müller C, Bondeau A, Popp A, Waha K, Fader M (2010) Climate change impacts on agricultural yields: background note to the World Development Report 2010. Woshington DC: World Bank 11:1996–2005

  • Nachtergaele F, van Velthuizen H, Verelst L, Batjes N, Dijkshoorn K, van Engelen V, Fischer G, Jones A, Montanarella L, Petri M (2008) Harmonized world soil database. Food and Agriculture Organization of the United Nations

  • Nelson GC, Rosegrant MW, Koo J, Robertson R, Sulser T, Zhu T, Ringler C, Msangi S, Palazzo A, Batka M (2009) Climate change: impact on agriculture and costs of adaptation, vol 21. International Food Policy Research Institute, Washington, DC, pp 1–19

    Google Scholar 

  • Pachauri RK, Allen MR, Barros V, Broome J, Cramer W, Christ R, Church J, Clarke L, Dahe Q, Dasgupta P (2014) Climate change 2014: synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. J Roman Stud 4(2):85–88

  • Peng S, Huang J, Sheehy JE, Laza RC, Visperas RM, Zhong X, Centeno GS, Khush GS, Cassman KG (2004) Rice yields decline with higher night temperature from global warming. Proc Natl Acad Sci USA 101(27):9971–9975

    Google Scholar 

  • Potts R, Faith JT (2015) Alternating high and low climate variability: the context of natural selection and speciation in Plio-Pleistocene hominin evolution. J Hum Evol 87:5–20

    Google Scholar 

  • Prescott J (1940) Evaporation from a water surface in relation to solar radiation. Trans R Soc S Aust 64(1):114–118

    Google Scholar 

  • Qin D, Zhang J, Shan C, Song L (2015) China national assessment report on risk management and adaptation of climate extremes and disasters. S Press, Beijing

    Google Scholar 

  • Ray DK, Gerber JS, MacDonald GK, West PC (2015) Climate variation explains a third of global crop yield variability. Nat Commun 6(5989):5989

    Google Scholar 

  • Rinaldi M, Losavio N, Flagella Z (2003) Evaluation and application of the OILCROP–SUN model for sunflower in southern Italy. Agric Syst 78(1):17–30

    Google Scholar 

  • Rosenzweig C, Parry ML (1994) Potential impact of climate change on world food supply. Nature 367(6459):133–138

    Google Scholar 

  • Roudier P, Sultan B, Quirion P, Berg A (2011) The impact of future climate change on West African crop yields: what does the recent literature say? Glob Environ Change 21(3):1073–1083

    Google Scholar 

  • Russill C, Nyssa Z (2009) The tipping point trend in climate change communication. Glob Environ Change 19(3):336–344

    Google Scholar 

  • Sapkota S, Paudel MN, Thakur NS, Nepali MB, Neupane R (2011) Effect of climate change on rice production: a case of six VDCs in Jumla District. R Nepal Acad Sci Technol 11(2010):57–62

    Google Scholar 

  • Sarker MAR, Alam K, Gow J (2012) Exploring the relationship between climate change and rice yield in Bangladesh: an analysis of time series data. Agric Syst 112(13):11–16

    Google Scholar 

  • Schellnhuber HJ, Hare B, Serdeczny O, Schaeffer M, Adams S, Baarsch F, Schwan S, Coumou D, Robinson A, Vieweg M (2013) Turn down the heat: climate extremes, regional impacts, and the case for resilience. World Bank Publications 31(2):346–347

    Google Scholar 

  • Shi PJ, Shao S, Ming W, Ning LI, Wang JA, Jin YY, Xiaotian GU, Yin WX (2014) Climate change regionalization in China (1961–2010). Sci China Earth Sci 57(11):2676–2689

    Google Scholar 

  • Shuai J, Zhang Z, Liu X, Chen Y, Wang P, Shi P (2013) Increasing concentrations of aerosols offset the benefits of climate warming on rice yields during 1980–2008 in Jiangsu Province, China. Reg Environ Change 13(2):287–297

    Google Scholar 

  • SL424-2008 (2009) Standard of classification for drought severity. Ministry of Water Resources of the People’s Republic of China, Beijing

    Google Scholar 

  • Tao F, Yokozawa M, Liu JY, Zhang Z (2008) Climate–crop yield relationships at provincial scales in China and the impacts of recent climate trends. Clim Res 38(1):83–94

    Google Scholar 

  • Tao F, Zhang Z, Shi W, Liu Y, Xiao D, Zhang S, Zhu Z, Wang M, Liu F (2013) Single rice growth period was prolonged by cultivars shifts, but yield was damaged by climate change during 1981–2009 in China, and late rice was just opposite. Glob Change Biol 19(10):3200–3209

    Google Scholar 

  • Teixeira EI, Fischer G, Velthuizen HV, Walter C, Ewert F (2013) Global hot-spots of heat stress on agricultural crops due to climate change. Agric For Meteorol 170(2):206–215

    Google Scholar 

  • Tiamiyu SA, Eze JN, Yusuf TM, Maji AT, Bakare SO (2015) Rainfall variability and its effect on yield of rice in Nigeria. Int Lett Nat Sci 49:63–68

    Google Scholar 

  • Tian JR, Li XK (1994) Managing diseases and insect pests of hybrid rice in China. International Rice Research Conference, Los Banos, Laguna (Philippines), pp 115–122

  • Timsina J, Humphreys E (2006a) Applications of CERES-rice and CERES-wheat in research, policy and climate change studies in Asia: a review. Int J Agric Res 1(3):202–225

    Google Scholar 

  • Timsina J, Humphreys E (2006b) Performance of CERES-rice and CERES-wheat models in rice–wheat systems: a review. Agric Syst 90(1–3):5–31

    Google Scholar 

  • Vijayalakshmi C, Radhakrishnan R, Nagarajan M, Rajendran C (1991) Effect of solar radiation deficit on rice productivity. J Agron Crop Sci 167(3):184–187

    Google Scholar 

  • Wang P, Zhao Z, Xiao S, Yi C, Xing W, Shi P, Tao F (2014) Temperature variations and rice yields in China: historical contributions and future trends. Clim Change 124(4):777–789

    Google Scholar 

  • Wang Z, Ye T, Wang J, Cheng Z, Shi P (2016) Contribution of climatic and technological factors to crop yield: empirical evidence from late paddy rice in Hunan Province, China. Stoch Environ Res Risk Assess 30(7):2019–2030

    Google Scholar 

  • Wassmann R, Jagadish SVK, Sumfleth K, Pathak H, Howell G, Ismail A, Serraj R, Redona E, Singh RK, Heuer S (2009) Regional vulnerability of climate change impacts on Asian rice production and scope for adaptation. Adv Agron 102(09):91–133

    Google Scholar 

  • Wheeler TR, Craufurd PQ, Ellis RH, Porter JR, Prasad PV (2000) Temperature variability and the yield of annual crops. Agric Ecosyst Environ 82(1):159–167

    Google Scholar 

  • Wu W, Fang Q, Ge Q, Zhou M, Lin Y (2014) CERES-rice model-based simulations of climate change impacts on rice yields and efficacy of adaptive options in Northeast China. Crop Pasture Sci 65(12):1267–1277

    Google Scholar 

  • Xiao F, Song L (2011) Analysis of extreme low-temperature events during the warm season in Northeast China. Nat Hazards 58(3):1333–1344

    Google Scholar 

  • Xiong W, Tao F, Xu Y, Lin E (2001). Simulation of rice yield under climatic changes in future in China. Agric Meteorol 22(3):1–5

    Google Scholar 

  • Xu CC, Wu WX, Ge QS, Zhou Y, Lin YM, Li YM (2017) Simulating climate change impacts and potential adaptations on rice yields in the Sichuan Basin, China. Mitig Adapt Strateg Glob Change 22(4):565–594

    Google Scholar 

  • Yao F, Xu Y, Lin E, Yokozawa M, Zhang J (2007) Assessing the impacts of climate change on rice yields in the main rice areas of China. Clim Change 80(3):395–409

    Google Scholar 

  • Yearbook (2015) China Statistical Yearbook. China Statistics Press, Beijing

    Google Scholar 

  • Yi W, Ren Z (1995) Yield-increasing capacity and developing measures of early rice in Hunan. Hybrid Rice 3:1–4

    Google Scholar 

  • Yin X, Kropff MJ, Goudriaan J (1996) Differential effects of day and night temperature on development to flowering in rice. Ann Bot (Lond) 77(3):203–213

    Google Scholar 

  • Zahid M, Rasul G (2011) Frequency of extreme temperature and precipitation events in Pakistan 1965–2009. Sci Int 23(4):313–319

    Google Scholar 

  • Zhang Z, Song X, Fulu T, Zhang S, Wenjiao S (2016a) Climate trends and crop production in China at county scale, 1980 to 2008. Theor Appl Climatol 123(1–2): 291–302

    Google Scholar 

  • Zhang H, Tao F, Xiao D, Shi W, Liu F, Zhang S, Liu Y (2016b) Contributions of climate, varieties, and agronomic management to rice yield change in the past three decades in China. Front Earth Sci 10(2):315–327

    Google Scholar 

  • Zhao C, Piao S, Wang X, Huang Y, Ciais P, Elliott J, Huang M, Janssens IA, Li T, Lian X (2016). Plausible rice yield losses under future climate warming. Nat Plants 3:16202

    Google Scholar 

  • Zhou M, Wang H, Yang S, Fan K (2012) Influence of springtime North Atlantic Oscillation on crops yields in Northeast China. Clim Dyn 41(11–12):3317–3324

    Google Scholar 

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Acknowledgements

We are thankful for the comments of anonymous reviewers and the editors. This study was financially supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 41321001), the State Key Laboratory of Earth Surface Processes and Resource Ecology and the Faculty of Geographical Science of Beijing Normal University.

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Corresponding author

Correspondence to Peijun Shi.

Additional information

This paper is a contribution to the special issue on East Asian Climate under Global Warming: Understanding and Projection, consisting of papers from the East Asian Climate (EAC) community and the 13th EAC International Workshop in Beijing, China on 24–25 March 2016, and coordinated by Jianping Li, Huang-Hsiung Hsu, Wei-Chyung Wang, Kyung-Ja Ha, Tim Li, and Akio Kitoh.

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Appendices

Appendix 1: Description of genetic coefficients for rice cultivar in the CERES-Rice model

Index

Description

Unit

P1

Growing degree days in the basic vegetative phase

°C days

P2R

Extent to which phasic development leading to panicle initiation is delayed for each hour increase in photoperiod above P2O

°C days

P5

Growing degree days in the grain filling duration

°C days

P2O

the longest day length (in hours) at which the development occurs at a maximum rate

h

G1

Potential spikelet number coefficient

G2

Single grain weight under ideal growing conditions

g

G3

Tillering coefficient under ideal conditions

G4

Temperature tolerance coefficient

Appendix 2: 1 SD for each climate variable in different early rice-growth stage

Climate variable

Station

Sowing stage

Emergence stage

Transplanting stage

Green stage

Tillering stage

Booting stage

Heading stage

Maturity stage

Temperature (℃)

Nanxian

2.5

1.5

2.9

1.6

1.5

1.3

1.6

1.6

Wuling

3.1

1.6

2.6

1.5

1.6

1.3

1.8

1.7

Changsha

2.2

1.4

3.2

2

1.5

1.2

1.7

1.2

Wugang

3.5

1.1

2.6

1.8

1.6

1.1

1.5

1.0

Hengnan

1.9

1.4

3.3

1.6

1.7

1.2

1.5

1.3

Zixing

4.5

1.3

2.9

1.7

1.6

1.1

1.3

0.9

Precipitation (mm)

Nanxian

21.1

79.4

17.2

61.7

47.6

57.6

75.4

65.2

Wuling

25.9

101.1

36.1

51.8

47.9

74.7

76.1

48.4

Changsha

22.3

75.4

22.4

52.7

94.5

89.2

82.2

66.7

Wugang

20.2

43.5

32.5

45.3

48.2

64.7

49.7

79

Hengnan

29.8

64.1

25.1

51.3

54.5

57.6

57.4

54

Zixing

28.1

82.8

21.6

45.9

79.3

57.6

51.7

77.7

Sunshine duration (h)

Nanxian

11.1

28.4

15.7

34

26.5

35.5

27

29.2

Wuling

12.6

37.1

14.4

21.3

26.4

24.2

26.4

33.2

Changsha

12.7

30.7

12.7

20.9

28.4

27.7

23.2

41.5

Wugang

9.7

30.2

14.5

22.1

23.4

38.8

22.4

33.6

Hengnan

7.9

31.8

12.7

25.3

28.5

27.6

28.1

29.4

Zixing

6.2

22.5

8.0

19.2

23.4

29.9

21.4

29.3

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Wang, Z., Shi, P., Zhang, Z. et al. Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China. Clim Dyn 51, 4469–4487 (2018). https://doi.org/10.1007/s00382-017-3831-6

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