Abstract
Net primary productivity (NPP) is an important environmental indicator that provides information about vegetation productivity and carbon fluxes. Analyses of NPP time-series allow for understanding temporal patterns and changes in vegetation productivity. These are especially important in rapidly changing environments, such as China, the world’s third largest country. In this study, we use the model BETHY/DLR (Biosphere Energy Transfer Hydrology Model) for derivation of NPP time-series for China for 14 years from 1999–2012. We analyse spatial and temporal NPP distributions. These include mean annual NPP distribution and mean productivities for different land cover classes. Monthly data provide information about temporal patterns of vegetation productivity for different regions in China and different vegetation types. Analyses of interannual NPP variability revealed considerable differences in the development of annual vegetation productivity within the analysed time period for different provinces. The decrease in NPP for the district Shanghai shows the strong influence of one of Asia’s fastest growing megacities on the environment. The NPP time-series was additionally analysed for a forest region in North China, which has been affected by forest disturbances. Our results show that the NPP data are suitable for monitoring of forest disturbance and regrowth. The analyses and results presented in this study provide valuable information about spatial and temporal variation of vegetation productivity in the various regions within China.
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References
Bartholomé E, Belward AS (2005) GLC2000: a new approach to global land cover mapping from Earth observation data. Int J Remote Sens 26(9):1959–1977
Berrisford P, Dee D, Poli P, Brugge R, Fielding K, Fuentes M, Kallberg P, Kobayasha S, Uppala S, Simmons A (2011) The ERA-Interim archive. In: ERA report series, no. 1, version 2.0. ECMWF, Reading
Cao M, Prince SD, Li K, Tao B, Small J, Shao X (2003) Response of terrestrial carbon uptake to climate interannual variability in China. Glob Chang Biol 9:536–546
Collatz GJ, Ribas-Carbo M, Berry JA (1992) Coupled Photosynthesis–stomatal conductance model for leaves of C4 plants. Aust J Plant Physiol 19(5):519–538
Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thépaut JN, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(545):553–597
Eisfelder C, Kuenzer C, Dech S, Buchroithner MF (2013) Comparison of two remote sensing based models for regional net primary productivity estimation – a case study in semi-arid Central Kazakhstan. IEEE J Select Topics Appl Earth Obs Remote Sens 6(4):1843–1856
Eisfelder C, Klein I, Niklaus M, Kuenzer C (2014) Net primary productivity in Kazakhstan, its spatio-temporal patterns and relation to meteorological variables. J Arid Environ 103:17–30
FAO et al (2009) Harmonized world soil database (version 1.1). FAO/IIASA, Rome/Laxenburg
Farquhar GD, Caemmerer S, Berry JA (1980) A biochemical model of photosynthesis in leaves of C3 species. Planta 149(1):78–90
Feng X, Liu G, Chen JM, Chen M, Liu J, Ju WM, Sun R, Zhou W (2007) Net primary productivity of China’s terrestrial ecosystems from a process model driven by remote sensing. J Environ Manag 85(3):563–573
Fu Y, Yu X, Zhao Y, Zeng X, Xia L (2013) Assessment impacts of weather and LandUse/Land Cover (LULC) change on Urban Vegetation Primary Productivity (NPP): a case study in Guangzhou, China. Remote Sens 5:4125–4144
Gao Q, Yu M, Wang J, Jia H, Wang K (2004) Relationship between regional primary production and vegetation patterns. Ecol Model 172:1–12
Gao Y, Zhou X, Wang Y, Wang C, Zhan Z, Chen L, Yan J, Qu R (2013) Vegetation net primary productivity and its response to climate change during 2001–2008 in the Tibetan Plateau. Sci Total Environ 444:356–362
Gio-GL (2013) Gio global land component – Lot 1 “Operation of the global land component”, Product user manual, Leaf Area Index (LAI) – version 1. Issue I1.00. http://land.copernicus.eu/global/sites/default/files/products/GIO-GL1_PUM_LAIV1_I1.00.pdf. Accessed 18 Dec 2013
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978
Hou Y, Wang S, Zhou Y, Yan F, Zhu J (2013) Analysis of the carbon dioxide concentration in the lowest atmospheric layers and the factors affecting China based on satellite observations. Int J Remote Sens 34(6):1981–1994
Knorr W (1997) Satellite remote sensing and modelling of the global CO2 exchange of land vegetation: a synthesis study. PhD dissertation. Max-Planck-Institute for Meteorology, Hamburg
Kottek M, Grieser J, Beck C, Rudolf B, Rubel F (2006) World map of the Köppen-Geiger climate classification updated. Meteorol Z 15:259–263
Lu L, Li X, Veroustraete F, Dong QH (2004) Estimation of NPP in Western China using remote sensing and the C-Fix model. In Proceedings of IEEE international geoscience and remote sensing symposium, IGARSS 2004, 20–24 September, pp 12–15
Lu L, Li X, Veroustraete F, Kang E, Wang J (2013) Analysing the forcing mechanisms for net primary productivity changes in the Heihe River Basin, north-west China. Int J Remote Sens 30(3):793–816
Matsushita B, Tamura M (2002) Integrating remotely sensed data with an ecosystem model to estimate net primary productivity in East Asia. Remote Sens Environ 18(1):58–66
Niemeijer C (2002) Developing indicators for environmental policy: data-driven and theory-driven approaches examined by example. Environ Sci Policy 5(2):91–103
PRB (2013) 2013 world population data sheet. http://www.prb.org/pdf13/2013-population-data-sheet_eng.pdf. Accessed 29 Jan 2014
PRC (2012) The People’s Republic of China national report on sustainable development, 100 pp. http://www.china-un.org/eng/zt/sdreng/P020120608816288649663.pdf. Accessed 27 Nov 2013
Prentice IC, Farquhar GD, Fasham MJR, Goulden ML, Heimann M, Jaramillo VJ, Kheshgi HS, Le Quéré C, Scholes RJ, Wallace DWR (2001) The carbon cycle and atmospheric carbon dioxide. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (eds) Climate change 2001: the scientific basis. Contribution of working group I to the third assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge/New York
Schimel DS (1995) Terrestrial biogeochemical cycles: global estimates with remote sensing. Remote Sens Environ 51(1):49–56
Tao J, Zhang Y, Yuan X, Wang J, Zhang X (2013) Analysis of forest fires in Northeast China from 2003 to 2011. Int J Remote Sens 34(22):8235–8251
UNDP (2013) China national human development report 2013. Sustainable and liveable cities: towards ecological civilization, p 200. http://www.undp.org/content/dam/china/docs/Publications/UNDP-CH-HD-Publication-NHDR_2013_EN_final.pdf. Accessed 26 Nov 2013
USGS (1996) GTOPO30, Global 30-Arc-Second Elevation Data Set. U.S. Geological Survey, EROS Data Center, Sioux Falls, South Dakota. http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/GTOPO30. Accessed 9 Dec 2013
Wang Y, Zhao P, Ren H, Kakubar Y (2008) Spatiotemporal dynamics of forest net primary production in China over the past two decades. Glob Planet Chang 61(3–4):267–274
Wißkirchen K, Tum M, Günther KP, Niklaus M, Eisfelder C, Knorr W (2013) Quantifying the carbon uptake by vegetation for Europe on a 1 km2 resolution using a remote sensing driven vegetation model. Geosci Model Dev Dis 6:2457–2489
Yan J, Wang Y, Zhou G, Zhang D (2006) Estimates of soil respiration and net primary production of three forests at different succession stages in South China. Glob Chang Biol 12(5):810–821
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We thank ECMWF, VITO, and IIASA for providing input data for NPP modelling.
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Eisfelder, C., Kuenzer, C. (2015). Investigating Fourteen Years of Net Primary Productivity Based on Remote Sensing Data for China. In: Kuenzer, C., Dech, S., Wagner, W. (eds) Remote Sensing Time Series. Remote Sensing and Digital Image Processing, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-15967-6_13
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DOI: https://doi.org/10.1007/978-3-319-15967-6_13
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