Abstract
Vegetation phenology is one of the key agroclimatic indices that is sensitive to climate change. Analyzing the variation in plant phenology under a changing environment can provide reference information to assess the impact of climate change on ecosystems and agricultural management. In this study, we focused on the thermal growth season, an important phenology index. We defined four growing season indices based on the surface temperature to quantify the changes in thermal growth season and analyze their association with atmospheric circulation in China. The results showed that the start date of the growing season exhibited a significant advanced trend (P < 0.001), while the end date exhibited a significant delayed trend (P < 0.001). The length of growing season and the number of ≥ 10℃ days increased significantly in China (P < 0.001) from 1960 to 2018. The variation in thermal growth season differed in different regions. The Qinghai-Tibet Plateau and the Loess Plateau were the regions in which thermal growing season was the most sensitive to climate changes. Atmospheric circulation was one of the main factors affected the change in thermal growing season indices. The West Pacific Subtropical High Intensity Index and the Arctic Oscillation Index significantly negatively correlated with the start date of the growing season (P < 0.05), and significantly positively correlated with the length of growing season and the number of ≥ 10℃ days (P < 0.01). Atmospheric circulation affected the change in temperature and subsequently affected the thermal growth season. These findings will provide useful information to assess the risk assessment of climate change and take action to reduce in the impact of climate change on ecosystems and agricultural management.
Similar content being viewed by others
References
Beaubien EG, Freeland HJ (2000) Spring phenology trends in Alberta, Canada: links to ocean temperature. Int J Biometeorol 44(2):53–59. https://doi.org/10.1007/s004840000050
Bartier PM, Keller CP (1996) Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW). Computers & Geoscience 22(7):795–799. https://doi.org/10.1016/0098-3004(96)00021-0
Bradley NL, Leopold AC, Ross J, Huffaker W (1999) Phenological changes reflect climate change in Wisconsin. Proc Natl Acad Sci USA 96(17):9701–9704. https://doi.org/10.1073/pnas.96.17.9701
Cui LL, Shi J, Ma Y, Du HQ (2017) Distribution and trend in the thermal growing season in China during 1961–2015. Phys Geogr 38(6):506–523. https://doi.org/10.1080/02723646.2017.1344497
Chen XQ, Hu B, Yu R (2005) Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China. Glob Change Biol 11(7):1118–1130. https://doi.org/10.1111/j.1365-2486.2005.00974.x
Chen XN, Yang YP (2020) Observed earlier start of the growing season from middle to high latitudes across the Northern Hemisphere snow-covered landmass for the period 2001–2014. Environ Res Lett 15(3):034–042. https://doi.org/10.1088/1748-9326/ab6d39
Cui LL, Shi J (2021) Evaluation and comparison of growing season metrics in arid and semi-arid areas of northern China under climate change. Ecol Ind 121:107055. https://doi.org/10.1016/j.ecolind.2020.107055
Chmielewski FM, Müller A, Bruns E (2004) Climate changes and trends in phenology of fruit trees and field crops in Germany, 1961–2000. Agric for Meteorol 121(1–2):69–78. https://doi.org/10.1016/s0168-1923(03)00161-8
Dai JH, Wang HJ, Ge QS (2013) Multiple phenological responses to climate change among 42 plant species in Xi’an China. Int J Biometeorol 57(5):749–58. https://doi.org/10.1007/s00484-012-0602-2
Dai JH, Wang HJ, Ge QS (2014) The spatial pattern of leaf phenology and its response to climate change in China. Int J Biometeorol 58(4):521–528. https://doi.org/10.1007/s00484-013-0679-2
Ding YH, Ren GY, Shi GY, Gong P, Zheng XH, Zhai PM, Zhang DR, Zhao ZC, Wang SW, Wang HJ, Luo Y, Chen DL, Gao XJ, Dai XS (2006) National Assessment Report of Climate change (I)Climate change in China and its future trend. Clim Change Res 2(1):3–8. https://doi.org/10.3969/j.issn.1673-1719.2007.z1.001
Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Klein Tank AMG, Peterson T (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Climate Res 19:193–212. https://doi.org/10.3354/cr019193
Ford KR, Harrington CA, Clair JBS (2017) Photoperiod cues and patterns of genetic variation limit phenological responses to climate change in warm parts of species’ range: modeling diameter-growth cessation in coast Douglas-fir. Glob Chang Biol 23(8):3348–3362. https://doi.org/10.1111/gcb.13690
Guo LH, Wu SH, Zhao DS, Leng GY, Zhang QY (2013) Change trends of growing season over inner Mongolia in the past 50 years. Scientia Geographica Sinica 33(4):505–512. https://doi.org/10.13249/j.cnki.sgs.2013.04.014
Guan YH, Zhang XC, Zheng FL, Wang B (2015) Trends and variability of daily temperature extremes during 1960–2012 in the Yangtze River Basin, China. Glob Planet Change 124:79–94. https://doi.org/10.1016/j.gloplacha.2014.11.008
Gong DY, Wang SW, Zhu JH (2001) East Asian winter monsoon and Arctic oscillation. Geophys Res Lett 28(10):2073–2076. https://doi.org/10.1029/2000gl012311
He SP, Wang HJ (2016) Linkage between the East Asian January temperature extremes and the preceding Arctic Oscillation. Int J Climatol 36(2):1026–1032. https://doi.org/10.1002/joc.4399
IPCC. Climate Change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press: 25
Jeong SJ, Ho CH, Gim HJ, Brown M (2011) Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008. Glob Chang Biol 17(7):2385–2399. https://doi.org/10.1111/j.1365-2486.2011.02397.x
Justice CO, Townshend JRG, Holben BN, Tucker CJ (2007) Analysis of the phenology of global vegetation using meteorological satellite data. Int J Remote Sens 6(8):1271–1318. https://doi.org/10.1080/01431168508948281
Jiang FQ, Hu RJ, Zhang YW, Li XM, Tong L (2011) Variations and trends of onset, cessation and length of climatic growing season over Xinjiang, NW China. Theor Appl Climatol 106(3–4):449–458. https://doi.org/10.1007/s00704-011-0445-5
Kendall MG (1948) Rank correlation methods. London: Charles Griffin 44:298.
Lin E (1997) Modeling Chinese agriculture impact under globe climate change. Chinese Agricultural Science and Tchnology Press, Beijing, pp 61–68
Li XF, Li DL, Duan XF, Liu Y (2019) Variations and effects of climate in growth period of Lycium barbarum L. in Ningxia. Chin J Eco-Agric 27(12):1789–1798. https://doi.org/10.13930/j.cnki.cjea.190477
Li Y, Yang XQ, Xie Q (2010) Selective Interaction between interannual variability of North Pacific Subtropical High and ENSO cycle. Chinese J Geophys 53(7):1543–1553. https://doi.org/10.3969/j.issn.0001-5733.2010.07.005
Liu BH, Henderson M, Zhang YD, Xu M (2009) Spatiotemporal change in China’s climatic growing season: 1955–2000. Clim Change 99(1–2):93–118. https://doi.org/10.1007/s10584-009-9662-7
Linderholm HW (2006) Growing season changes in the last century. Agric for Meteorol 137(1–2):1–14. https://doi.org/10.1016/j.agrformet.2006.03.006
Liu Q, Fu YH, Zeng ZZ, Huang MT, Li XR, Piao SL (2016) Temperature, precipitation, and insolation effects on autumn vegetation phenology in temperate China. Glob Chang Biol 22(2):644–655. https://doi.org/10.1111/gcb.13081
Li CL, Wang J, Hu RC, Yin S, Bao YH, Ayal DY (2018) Relationship between vegetation change and extreme climate indices on the Inner Mongolia Plateau, China, from 1982 to 2013. Ecol Ind 89:101–109. https://doi.org/10.1016/j.ecolind.2018.01.066
Menzel A, Jakobi G, Ahas R, Scheifinger H, Estrella N (2003) Variations of the climatological growing season (1951–2000) in Germany compared with other countries. Int J Climatol 23(7):793–812. https://doi.org/10.1002/joc.915
Menzel A (2003) Plant phenological anomalies in Germany and their relation to air temperature and NAO. Clim Change 57:243–263
Manton MJ, Nicholls N (1999) Monitoring trends in extreme climate events. Asia Pacific Network for Global Change Research, Tokyo. APN Newsletter 5(1):1–3. https://doi.org/10.1002/eej.23306
Neilson RP (1995) A model for predicting continental-scale vegetation distribution and water balance. Ecol Appl 5(2):362–385. https://doi.org/10.2307/1942028
Pingale SM, Khare D, Jat MK, Adamowski J (2014) Spatial and temporal trends of mean and extreme rainfall and temperature for the 33 urban centers of the arid and semi-arid state of Rajasthan, India. Atmos Res 138:73–90. https://doi.org/10.1016/j.atmosres.2013.10.024
Piao SL, Friedlingstein P, Ciais P, Viovy N, Demarty J (2007) Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades. Global Biogeochemical Cycles 21(3):n/a-n/a. https://doi.org/10.1029/2006gb002888
Piao SL, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang JY, Barr A, Chen AP, Grelle A, Hollinger DY, Laurila T, Lindroth A, Richardson AD, Vesala T (2008) Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451(7174):49–52. https://doi.org/10.1038/nature06444
Piao SL, Wang XH, Ciais P, Zhu B, Wang T, Liu J (2011) Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Glob Change Biol 17(10):3228–3239. https://doi.org/10.1111/j.1365-2486.2011.02419.x
Ren GY, Xu MZ, Chu ZY, Guo J, Li QX, Liu XN, Wang Y (2005) Changes of surface air temperature in China during 1951–2004. Climatic and Environmental Research 10(4):717–727. https://doi.org/10.3969/j.issn.1006-9585.2005.04.002
Ren SL, Qin QM, Ren HZ, Sui J, Zhang Y (2019) New model for simulating autumn phenology of herbaceous plants in the Inner Mongolian Grassland. Agric for Meteorol 275:136–145. https://doi.org/10.1016/j.agrformet.2019.05.011
Studer S, Stockli R, Appenzeller C, Vidale PL (2007) A comparative study of satellite and ground-based phenology. Int J Biometeorol 51(5):405–414. https://doi.org/10.1007/s00484-006-0080-5
Shen BZ, Lian Y, Zhang SX, Li SF (2012) Impacts of Arctic oscillation and polar vortex anomalies on winter temperature over Eurasian continent. Clim Change Res 8(6):434–439. https://doi.org/10.3969/j.issn.1673-1719.2012.06.007
Sun WY, Mu XM, Song XY, Wu D, Cheng AF, Qiu B (2016) Changes in extreme temperature and precipitation events in the Loess Plateau (China) during 1960–2013 under global warming. Atmos Res 168:33–48. https://doi.org/10.1016/j.atmosres.2015.09.001
Shi N, Zhu QG, Wu BG (1996) The East Asian summer monsoon in relation to summer large scale weather—climate anomaly in China. Chin J Atmos Sci 20(5):575–583. https://doi.org/10.3878/j.issn.1006-9895.1996.05.08
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63:1379–1389. https://doi.org/10.1080/01621459.1968.10480934
Sun SQ, Ying M (1999) Subtropical high anomalies over the western Pacific and its relations to the Asian monsoon and SST anomaly. Adv Atmos Sci 16(4):559–568. https://doi.org/10.1007/s00376-999-0031-2
Schwartz MD, Reiter BE (2000) Changes in north American spring. Int J Climatol 20(8):929–932. https://doi.org/10.1002/1097-0088(20000630)20:8%3C929::aid-joc557%3E3.0.co;2-5
Schwartz MD, Ahas R, Aasa A (2006) Onset of spring starting earlier across the Northern Hemisphere. Glob Change Biol 12(2):343–351. https://doi.org/10.1111/j.1365-2486.2005.01097.x
Thompson DWJ, Wallace JM (1998) The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys Res Lett 25(9):1297–1300. https://doi.org/10.1029/98gl00950
White MA, Hoffman F, Hargrove WW, Nemani RR (2005) A global framework for monitoring phenological responses to climate change. Geophysical Research Letters 32(4):n/a-n/a. https://doi.org/10.1029/2004gl021961
Walther A, Linderholm HW (2006) A comparison of growing season indices for the Greater Baltic Area. Int J Biometeorol 51(2):107–118. https://doi.org/10.1007/s00484-006-0048-5
Yuan MX, Zhao L, Lin AW, Li QJ, She DX, Qu S (2020) How do climatic and non-climatic factors contribute to the dynamics of vegetation autumn phenology in the Yellow River Basin, China? Ecol Ind 112:106–112. https://doi.org/10.1016/j.ecolind.2020.106112
Yin YH, Deng HY, Wu SH (2019) Spatial-temporal variations in the thermal growing degree-days and season under climate warming in China during 1960–2011. Int J Biometeorol 63(5):649–658. https://doi.org/10.1007/s00484-017-1417-y
Yu DD, Zhang R, Zhao CY, Wan L, Guo XX (2014) Correlation between the subtropical high abnormal longitudinal position and the East Asian summer monsoon system. Transactions of Atmospheric Sciences 37(3):304–312. https://doi.org/10.13878/j.cnki.dqkxxb.2014.03.005
Zhu WQ, Tian HQ, Xu XF, Pan YZ, Chen GS, Lin WP (2012) Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982–2006. Glob Ecol Biogeogr 21(2):260–271. https://doi.org/10.1111/j.1466-8238.2011.00675.x
Zhong KY, Zheng FL, Wu HY, Qin C, Xu XM (2017) Dynamic changes in temperature extremes and their association with atmospheric circulation patterns in the Songhua River Basin, China. Atmos Res 190:77–88. https://doi.org/10.1016/j.atmosres.2017.02.012
Zhong KY, Zheng FL, Zhang XC, Qin C, Xu XM, Lalic B, Ćupina B (2020) Dynamic changes in snowfall extremes in the Songhua River Basin, Northeastern China. Int J Climatol 41(1):423–438. https://doi.org/10.1002/joc.6628
Zheng ZT, Zhu WQ, Chen GS, Jiang N, Fan DQ, Zhang DH (2016) Continuous but diverse advancement of spring-summer phenology in response to climate warming across the Qinghai-Tibetan Plateau. Agric for Meteorol 223:194–202. https://doi.org/10.1016/j.agrformet.2016.04.012
Acknowledgements
Acknowledgement for the data support from “the National Meteorological Information Center of the China Meteorological Administration (http://data.cma.cn/), the Chinese Phenological Observation Network (http://www.cpon.ac.cn/), and the National Earth System Science Data Center, National Science and Technology Infrastructure of China (http://www.geodata.cn).”
Funding
This study was supported by the Science and Technology Foundation of the Education Department of Jiangxi Province, China (GJJ180784), Ganzhou key research and development project ([2020]60), Gannan Normal University Research Base project (2020bmy01), University Student Innovation and Entrepreneurship Training Program Project of Gannan Normal University CX200001 and National Natural Science Foundation of China (41601600).
Author information
Authors and Affiliations
Corresponding author
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Shang, L., Liao, J., Xie, S. et al. Dynamic changes in the thermal growing season and their association with atmospheric circulation in China. Int J Biometeorol 66, 545–558 (2022). https://doi.org/10.1007/s00484-021-02215-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00484-021-02215-9