Skip to main content
SpringerLink
Log in

Preliminary Estimation of the Realistic Optimum Temperature for Vegetation Growth in China

  • Published:
Environmental Management Aims and scope Submit manuscript

Abstract

The estimation of optimum temperature of vegetation growth is very useful for a wide range of applications such as agriculture and climate change studies. Thermal conditions substantially affect vegetation growth. In this study, the normalized difference vegetation index (NDVI) and daily temperature data set from 1982 to 2006 for China were used to examine optimum temperature of vegetation growth. Based on a simple analysis of ecological amplitude and Shelford’s law of tolerance, a scientific framework for calculating the optimum temperature was constructed. The optimum temperature range and referenced optimum temperature (ROT) of terrestrial vegetation were obtained and explored over different eco-geographical regions of China. The results showed that the relationship between NDVI and air temperature was significant over almost all of China, indicating that terrestrial vegetation growth was closely related to thermal conditions. ROTs were different in various regions. The lowest ROT, about 7.0 °C, occurred in the Qinghai-Tibet Plateau, while the highest ROT, more than 22.0 °C, occurred in the middle and lower reaches of the Yangtze River and the Southern China region.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Alcaraz-Segura D, Cabello J, Paruelo JM, Delibes M (2009) Use of descriptors of ecosystem functioning for monitoring a national park network: a remote sensing approach. Environ Manage 43(38):48

    Google Scholar 

  • Berry J, Bjorkman O (1980) Photosynthetic response and adaptation to temperature in higher plants. Annu Rev Plant Phys 31(1):491–543

    Article  Google Scholar 

  • Cao MK, Prince SD, Small J, Goetz S (2004) Remotely sensed interannual variations and trends in terrestrial net primary productivity 1981–2000. Ecosystems 7:233–242

    Article  Google Scholar 

  • Chapin FSI (1983) Direct and indirect effects of temperature on Arctic plants. Polar Biol 2:47–52

    Article  Google Scholar 

  • Chen XQ, Hu B, Yu R (2005) Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China. Global Change Biol 11:1118–1130

    Article  Google Scholar 

  • Cui YP, Wang RH, Liu T, Zhang HF (2010) Extraction of vegetation information in arid desert ares based on spectral mixture analysis: a case in the western Gurbantunggut desert. J Desert Res 30(2):334–341

    Google Scholar 

  • Dong JW, Liu JY, Tao FL, Xu XL, Wang JB (2009) Spatio-temporal changes in annual accumulated temperature in China and the effects on cropping systems, 1980s to 2000. Clim Res 40(1):37–48

    Article  CAS  Google Scholar 

  • Dong J, Liu J, Yan H, Tao F, Kuang W (2010) Spatio-temporal pattern and rationality of land reclamation and cropland abandonment in mid-eastern Inner Mongolia of China in 1990–2005. Environ Monit Assess 179:137–153. doi:10.1007/s10661-010-1724-9

    Article  Google Scholar 

  • Fitter A, Fitter R (2002) Rapid changes in flowering time in British plants. Science 296(5573):1689

    Article  CAS  Google Scholar 

  • Fontana F, Trishchenko AP, Khlopenkov KV, Luo Y, Wunderle S (2009) Impact of orthorectification and spatial sampling on maximum NDVI composite data in mountain regions. Remote Sens Environ 113(12):2701–2712

    Article  Google Scholar 

  • Gu Z, Chen J, Shi P, Xu M (2005) Correlation analysis of NDVI difference series and climate variables in Xinlingole steppe from 1983 to 1999. Acta Ecologica Sinica 29(5):753–765

    Google Scholar 

  • Häninnen H (1994) Effects of climatic change on trees from cool and temperate regions: an ecophysiological approach to modeling of budburst phenology. Can J Bot 73:183–199

    Article  Google Scholar 

  • Hunt ER, Kelly RD, Smith WK, Fahnestock JT, Welker JM, Reiners WA (2004) Estimation of carbon sequestration by combining remote sensing and net ecosystem exchange data for northern mixed-grass prairie and sagebrush-steppe ecosystems. Environ Manage 33:432–441

    Article  Google Scholar 

  • Hutchinson M (1989) New objective method for spatial interpolation of meteorological variables from irregular networks applied to the estimation of monthly mean solar radiation, temperature, precipitation and windrun. Techn Memo 89(5):95–104

    Google Scholar 

  • Jobbágy EG, Sala OE, Paruelo JM (2002) Patterns and controls of primary production in the Patagonian steppe: a remote sensing approach. Ecology 83(2):307–319

    Google Scholar 

  • Jönsson P, Eklundh L (2004) TIMESAT–a program for analyzing time-series of satellite sensor data. Comput Geosci 30(8):833–845

    Article  Google Scholar 

  • Julien Y, Sobrino JA (2009) Global land surface phenology trends form GIMMS database. Int J Remote Sens 30(13):3495–3513

    Article  Google Scholar 

  • Lacaze R, Balsamob G, Baretc F, Bradleyd A, et al (2009) Geoland2-Towards an operational GMES land monitoring core service. First results of the biogeophysical parameter core mapping service. http://www.isprs.org/proceedings/XXXVIII/part7/b/pdf/354_XXXVIII-part7B.pdf

  • Li B (2000) Ecology. Higher Education Press, Beijing

    Google Scholar 

  • Li L, Lu H, Campbell D, Ren H (2011) Methods for estimating the uncertainty in energy table-form models. Ecol Model 222:2615–2622

    Article  Google Scholar 

  • Liu M (2008) Study on estimation and uncertainty of terrestrial ecosystem productivity based on RS and GIS—take the grassland transect in Tibetan Plateau for example. Nanjing Normal University, Nanjing

    Google Scholar 

  • Liu JY, Zhang ZX, Luo D, Xiao X (2003) Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data. Int J Remote Sens 24(12):2485–2500

    Article  Google Scholar 

  • Liu J, Liu M, Tian H, Zhuang D, Zhang Z, Zhang W, Tang X, Deng X (2005) Spatial and temporal patterns of China’s cropland during 1990–2000: an analysis based on Landsat TM data. Remote Sens Environ 98(4):442–456

    Article  Google Scholar 

  • Los SO, O JC, Tucker CJ (1994) A global 11 by 11 NDVI data set for climate studies derived from the GIMMS continental NDVI data. Int J Remote Sens 15:3493–3518

    Article  Google Scholar 

  • Myneni RB, Keeling CD, Tucker CJ et al (1997) Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386:698–702

    Article  CAS  Google Scholar 

  • Nagai S, Nasahara KN, Muraoka H, Akiyama T, Tsuchida S (2010) Field experiments to test the use of the normalized-difference vegetation index for phenology detection. Agric Forest Meteorol 150(2):152–160

    Article  Google Scholar 

  • Pianka E (1978) Evolutionary ecology. Harper and Row, New York

    Google Scholar 

  • Piao SL, Fang JY, Zhou LM et al (2006) Variations in satellite-derived phenology in China’s temperate vegetation. Global Change Biol 12(4):672–685

    Article  Google Scholar 

  • Rea R, Eccel E (2006) Phenological models for blooming of apple in a mountainous region. Int J Biometeorol 51:1–16

    Article  Google Scholar 

  • Schwartz MD, Chen XQ (2002) Examining the onset of spring in China. Clim Res 12:157–164

    Article  Google Scholar 

  • Scott D (1970) Relative growth rates under controlled temperatures of some New Zealand indigenous and introduced grasses. N Z J Bot 8:76–81

    Article  Google Scholar 

  • Tucker CJ, Slayback DA, Pinzon JE et al (2001) Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999. Int J Biometeorol 45:184–190

    Article  CAS  Google Scholar 

  • Wang Q, Ni J, Tenhunen J (2005) Application of geographically-weighted regression analysis to estimate net primary production of Chinese forest ecosystem. Global Ecol Biogeogr 14:379–393

    Article  Google Scholar 

  • White MA, Thornton PE, Running SW (1997) A continental phenology model for monitoring vegetation responses to interannual climatic variability. Global Biogeochem Cycles 11(2):217–234

    Article  CAS  Google Scholar 

  • Xu H, Li Y (2006) Water-use strategy of three central Asian desert shrubs and their responses to rain pulse events. Plant Soil 285(1):5–17

    Article  CAS  Google Scholar 

  • Zhang LY, Chen CD (2002) On the general characteristics of plant diversity of Gurbantunggut sandy Desert. Acta Ecologica Sinica 22(11):1923–1932

    Google Scholar 

  • Zhang X, Friedl MA, Schaaf CB, Strahler AH (2004) Climate controls on vegetation phenological patterns in northern mid-and high latitudes inferred from MODIS data. Global Change Biol 10(7):1133–1145

    Article  Google Scholar 

  • Zheng D, Li BY (2005) Chinese eco-geographic map. Beijing Commercial Press, Beijing

    Google Scholar 

  • Zhou L, Kaufmann RK, Tian Y et al (2003) Relation between interannual variations in satellite measures of vegetation greenness and climate between 1982 and 1999. J Geophys Res 108(D1):4004. doi:10.1029/2002JD002510

    Article  Google Scholar 

  • Zhu W (2005) Estimation of net primary productivity of Chinese terrestrial vegetation based on remote sensing and its relationship with global climate change. Beijing Normal University, Beijing

    Google Scholar 

  • Zhu WQ, Tian HQ, Xu XF, Pan YZ, Chen GS, Lin WP (2011) Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982–2006. Global Ecol Biogeogr 21(2):260–271

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Basic Research Program (2010CB950901 and 2012CB955800), National Natural Science Foundation of China (41171438), and Major Program of Humanities and Social Sciences Key Research Base of Ministry of Education of China (10JJDZONGHE015).

Author information

Authors and Affiliations

  1. Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, College of Environment and Planning, Henan University, Kaifeng, 475001, China

    Yaoping Cui

Authors
  1. Yaoping Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yaoping Cui.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cui, Y. Preliminary Estimation of the Realistic Optimum Temperature for Vegetation Growth in China. Environmental Management 52, 151–162 (2013). https://doi.org/10.1007/s00267-013-0065-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00267-013-0065-1

Keywords

Search

Navigation