Skip to main content

Advertisement

Log in

Influences of Climate Extremes on NDVI (Normalized Difference Vegetation Index) in the Poyang Lake Basin, China

  • Original Research
  • Published:
Wetlands Aims and scope Submit manuscript

Abstract

Based on long-term NDVI (Normalized Difference Vegetation Index) derived from Global Inventory Modeling and Mapping Study (GIMMS) and daily meteorological observations from 14 stations in the Poyang Lake Basin, this study investigated the relationship between vegetation variation and climatic extremes during 1982–2006. Ten typical indices were adopted to describe climatic extreme, including two precipitation-related and eight temperature-related indices. Correlation analysis shows that monthly averaged NDVI variations are generally determined by temperature but not precipitation extremes. Positive correlations appear between NDVI and temperature indices, and the correlations are more significant in spring and autumn. Significant negative correlations are found in summer and winter between NDVI and precipitation-related indices. In addition, spatial heterogeneity analysis shows that NDVI is more vulnerable to climate change for the middle basin than other regions. Finally, we demonstrate that NDVI can currently responds to temperature extremes or with a lag of 1 month. With respect to precipitation extremes, the strongest response may occur 2 months later. Our study highlights the role of climate extremes to the NDVI, and is helpful to improve the understanding of vegetation vulnerability to climate fluctuations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Beer C, Reichstein M, Tomelleri E, Ciais P, Jung M, Carvalhais N, Papale D (2010) Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329(5993):834–838

    Article  CAS  PubMed  Google Scholar 

  • Breda N, Huc R, Granier A, Dreyer E (2006) Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences. Annals of Forest Science 63(6):625–644

    Article  Google Scholar 

  • Cavender-Bares J, Bazzaz F (2000) Changes in drought response strategies with ontogeny in quercus rubra: implications for scaling from seedlings to mature trees. Oecologia 124(1):8–18

    Article  Google Scholar 

  • Chen P, Yu S, Zhan Y, Kang X (2006) A review on plant heat stress physiology. Chinese Agricultural Science Bulletin 22(5):223–227

    Google Scholar 

  • Crippen R (1990) Calculating the vegetation index faster. Remote Sensing of Environment 34(1):71–73

    Article  Google Scholar 

  • Frank D, Reichstein M, Bahn M, Thonicke K, Frank D, Mahecha MD, et al. (2015) Effects of climate extremes on the terrestrial carbon cycle: concepts, processes and potential future impacts. Global Change Biology. doi:10.1111/gcb.12916

    Google Scholar 

  • Frost G, Epstein H, Walker D (2014) Regional and landscape-scale variability of landsat-observed vegetation dynamics in northwest siberian tundra. Environmental Research Letters 9(2). doi:10.1088/1748-9326/9/2/025004

  • Gu T, Zhou S, Shao B, Li Q (2009) Interactions between vegetation cover change and precipitation in poyang lake region. Chinese Journal of Ecology 28(6):1060–1066

    Google Scholar 

  • Guo H, Hu Q, Jiang T (2008) Annual and seasonal streamflow responses to climate and land-cover changes in the poyang lake basin, China. Journal of Hydrology 355(1–4):106–122

    Article  Google Scholar 

  • Gurgel H, Ferreira N (2003) Annual and interannual variability of NDVI in Brazil and its connections with climate. International Journal of Remote Sensing 24(18):3595–3609

    Article  Google Scholar 

  • Hasson A, Mills G, Timbal B, Walsh K (2009) Assessing the impact of climate change on extreme fire weather events over southeastern Australia. Climate Research 39(2):159–172

    Article  Google Scholar 

  • Holmgren M, Stapp P, Dickman C, Gracia C, Graham S, Gutiérrez J, Hice C, Jaksic F, Kelt D, Letnic M (2006) Extreme climatic events shape arid and semiarid ecosystems. Frontiers in Ecology and the Environment 4(2):87–95

    Article  Google Scholar 

  • Hui F, Xu B, Huang H, Yu Q, Gong P (2008) Modelling spatial-temporal change of poyang lake using multitemporal landsat imagery. International Journal of Remote Sensing 29(20):5767–5784

    Article  Google Scholar 

  • Hyndman R, Fan Y (1996) Sample quantiles in statistical packages. The American Statistician 50:361–367

    Google Scholar 

  • John R, Chen J, Ou-Yang Z, Xiao J, Becker R, Samanta A, Ganguly S, Yuan W, Batkhishig O (2013) Vegetation response to extreme climate events on the Mongolian plateau from 2000 to 2010. Environmental Research Letters 8(3). doi:10.1088/1748-9326/8/3/035033

  • Kanai Y, Ueta M, Germogenov N, Nagendran M, Mita N, Higuchi H (2002) Migration routes and important resting areas of siberian cranes between northeastern siberia and China as revealed by satellite tracking. Biological Conservation 106(3):339–346

    Article  Google Scholar 

  • Kerr R (2003) Climate change: a perfect ocean for four years of globe-girdling drought. Science 299(5607):636

    Article  PubMed  Google Scholar 

  • Kim C, Park M, Lee J (2014) Analysis of climate change impacts on the spatial and frequency patterns of drought using a potential drought hazard mapping approach. International Journal of Climatology 34(1):61–80

    Article  Google Scholar 

  • Koepke D, Kolb T, Adams H (2010) Variation in woody plant mortality and dieback from severe drought among soils, plant groups, and species within a northern Arizona ecotone. Oecologia 163(4):1079–1090

    Article  PubMed  Google Scholar 

  • Li B, Tao S (2000) Correlation between AVHRR NDVI and climate factors. Acta Ecologica Sinica 20(5):898–902

    Google Scholar 

  • Liao J, Shen G, Dong L (2013) Biomass estimation of wetland vegetation in poyang lake area using ENVISAT advanced synthetic aperture radar data. Journal of Applied Remote Sensing 7(1):073579–073579

    Article  Google Scholar 

  • Liu Y, Song P, Peng J, Ye C (2012) A physical explanation of the variation in threshold for delineating terrestrial water surfaces from multi-temporal images: effects of radiometric correction. International Journal of Remote Sensing 33(18):5862–5875

    Article  Google Scholar 

  • Liu G, Liu H, Yin Y (2013) Global patterns of NDVI-indicated vegetation extremes and their sensitivity to climate extremes. Environmental Research Letters 8(2):025009

    Article  Google Scholar 

  • Lloret F, Escudero A, Iriondo J, et al. (2012) Extreme climatic events and vegetation: the role of stabilizing processes. Global Change Biology 18(3):797–805

    Article  Google Scholar 

  • Min Q, Shi J, Min D (2011) Characteristics of sediment into and out of poyanghu lake from 1956 to 2005. Journal of China Hydrology 31(1):54–58

    Google Scholar 

  • Miriti M, Rodríguez-Buriticá S, Wright S, Howe H (2007) Episodic death across species of desert shrubs. Ecology 88(1):32–36

    Article  PubMed  Google Scholar 

  • Piao S., Fang J., Zhou L., Guo Q., Henderson M., Ji W., & Tao S (2003) Interannual variations of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999. Journal of Geophysical Research: Atmospheres (1984–2012), 108(D14)

  • Piao S, Nan H, Huntingford C, Ciais P, Friedlingstein P, Sitch S, Chen A (2014) Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity. Nature Communications 5. doi:10.1038/ncomms6018

  • Potter C, Brooks V (1998) Global analysis of empirical relations between annual climate and seasonality of NDVI. International Journal of Remote Sensing 19(15):2921–2948

    Article  Google Scholar 

  • Reichstein M, Bahn M, Ciais P, Frank D, Mahecha M, Seneviratne S, Zscheischler J, Beer C, Buchmann N, Frank DC, Papale D, Rammig A, Smith P, Thonicke K, van der Velde M, Vicca S, Walz A, Wattenbach M (2013) Climate extremes and the carbon cycle. Nature 500(7462):287–295

    Article  CAS  PubMed  Google Scholar 

  • Rocklov J. and Forsberg B. (2009) The attributed effect of climate extremes, climate related epidemics or outbreaks on health is largely dependent on the choice of approach-a case study comparing four approaches for estimating excess hospital admissions during a record warm summer in south Sweden. Epidemiology 20(6):S68-S68

  • Schuster Z, Potter K, Liebl D (2012) Assessing the effects of climate change on precipitation and flood damage in Wisconsin. Journal of Hydrologic Engineering 17(8):888–894

    Article  Google Scholar 

  • Seneviratne S., Nicholls N., Easterling D., Goodess C., Kanae S., Kossin J., Luo Y., Marengo J., McInnes K., Rahimi M. (2012) Changes in climate extremes and their impacts on the natural physical environment: An overview of the IPCC SREX report. In, EGU General Assembly Conference Abstracts (p. 12566)

  • Shankman D, Liang Q (2003) Landscape changes and increasing flood frequency in China’s Poyang lake region∗. The Professional Geographer 55(4):434–445

    Article  Google Scholar 

  • Shankman D, Keim B, Song J (2006) Flood frequency in China’s Poyang lake region: trends and teleconnections. International Journal of Climatology 26(9):1255–1266

    Article  Google Scholar 

  • Shevyrnogov A, Chernetskiy M, Vysotskaya G (2013) Multiyear trends of normalized difference vegetation index and temperature in the south of Krasnoyarsk krai. Izvestiya Atmospheric and Oceanic Physics 49(9):1047–1056

    Article  Google Scholar 

  • Tao H, Fraedrich K, Menz C (2014) Trends in extreme temperature indices in the poyang lake basin, China. Stochastic Environmental Research and Risk Assessment 28(6):1543–1553

    Article  Google Scholar 

  • Tourre Y, Jarlan L, Lacaux J, Rotela C, Lafaye M (2008) Spatio-temporal variability of NDVI-precipitation over southernmost south America: possible linkages between climate signals and epidemics. Environmental Research Letters 3(4):044008. doi:10.1088/1748-9326/3/4/044008

    Article  Google Scholar 

  • Tucker C (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 8(2):127–150

    Article  Google Scholar 

  • Tucker C, Pinzon J, Brown M, Slayback D, Pak E, Mahoney R, Vermote E, El Saleous N (2005) An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing 26(20):4485–4498

    Article  Google Scholar 

  • Valladares F, Gianoli E, Gómez J (2007) Ecological limits to plant phenotypic plasticity. The New Phytologist 176(4):749–763

    Article  PubMed  Google Scholar 

  • Van Asch N, Hoek W (2012) The impact of summer temperature changes on vegetation development in Ireland during the weichselian lateglacial interstadial. Journal of Quaternary Science 27(5):441–450

    Article  Google Scholar 

  • Verbesselt J, Hyndman R, Newnham G, Culvenor D (2010) Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment 114(1):106–115

    Article  Google Scholar 

  • Verbesselt J, Zeileis A, Herold M (2012) Near real-time disturbance detection using satellite image time series. Remote Sensing of Environment 123:98–108

    Article  Google Scholar 

  • Vicente-Serrano S, Gouveia C, Camarero J, Begueria S, Trigo R, Lopez-Moreno J, Azorin-Molina C, Pasho E, Lorenzo-Lacruz J, Revuelto J, Moran-Tejeda E, Sanchez-Lorenzo A (2013) Response of vegetation to drought time-scales across global land biomes. Proceedings of the National Academy of Sciences of the United States of America 110(1):52–57

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Von Liebig J (1842) Die organische chemie in ihrer anwendung auf physiologie und pathologie. Verlag von Friedrich Vieweg und Sohn

  • Wallace J, Held I, Thompson D, Trenberth K, Walsh J (2014) Global warming and winter weather. Science 343(6172):729–730

    Article  CAS  PubMed  Google Scholar 

  • Wang F, Wu D, Li R (2008) Analysis on flood disaster characteristic in lake Poyang region. Journal of Lake Science 20(4):500–506

    Google Scholar 

  • Wang T, Kou X, Xiong Y, Mou P, Wu J, Ge J (2010) Temporal and spatial patterns of NDVI and their relationship to precipitation in the loess plateau of China. International Journal of Remote Sensing 31(7):1943–1958

    Article  CAS  Google Scholar 

  • Wang L, Dronova I, Gong P, Yang W, Li Y, Liu Q (2012) A new time series vegetation-water index of phenological-hydrological trait across species and functional types for Poyang lake wetland ecosystem. Remote Sensing of Environment 125:49–63

    Article  Google Scholar 

  • Woodward M, Kapelan Z, Gouldby B (2014) Adaptive flood risk management under climate change uncertainty using real options and optimization. Risk Analysis 34(1):75–92

    Article  Google Scholar 

  • Yang L, Wylie B, Tieszen L, Reed B (1998) An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the US northern and central great plains. Remote Sensing of Environment 65(1):25–37

    Article  Google Scholar 

  • Zhang X, Hegerl G, Zwiers F, et al. (2005) Avoiding inhomogeneity in percentile-based indices of temperature extremes. Journal of Climate 18(11):1641–1651

    Article  Google Scholar 

  • Zhang L, Chen X, Cai X, Habib A (2010) Spatial-temporal changes of NDVI and their relations with precipitation and temperature in Yangtze river basin from 1981 to 2001. Geo-Spatial Information Science 13(3):186–190

    Article  Google Scholar 

  • Zhang G, Xu X, Zhou C, Zhang H, Ouyang H (2011) Responses of vegetation changes to climatic variations in hulun buir grassland in past 30 years. Journal of Geographical Sciences 66(1):47–58

    Google Scholar 

  • Zhang L, Yin J, Jiang Y, Wang H (2012) Relationship between the hydrological conditions and the distribution of vegetation communities within the Poyang lake national nature reserve, China. Ecological Informatics 11:65–75

    Article  CAS  Google Scholar 

  • Zhang Y, Gao J, Liu L, Wang Z, Ding M, Yang X (2013) NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: a case study in the koshi river basin in the middle Himalayas. Global and Planetary Change 108:139–148

    Article  Google Scholar 

Download references

Acknowledgments

We are thankful to Thomas Fischer (Eberhard Karls University) for the assistance of preparing the manuscript. This study is financially supported by the National Basic Research Program of China (No.2012CB417005 and No.2013CB430205) and the National Nature Sciences Foundation (No.41375099, No.91337108, No.41371121 and No.41271034). The authors express their gratitude to the National Climate Center (NCC) of China Meteorological Administration (CMA) for providing the data. The authors also are very thankful to the three anonymous reviewers for their constructive suggestions and comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hui Tao.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tan, Z., Tao, H., Jiang, J. et al. Influences of Climate Extremes on NDVI (Normalized Difference Vegetation Index) in the Poyang Lake Basin, China. Wetlands 35, 1033–1042 (2015). https://doi.org/10.1007/s13157-015-0692-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13157-015-0692-9

Keywords

Navigation