Abstract
The monitoring of terrestrial carbon dynamics is important in studies related with global climate change. This paper presents results of the inter-annual variability of Net Primary Productivity (NPP) from 1981 to 2000 derived using observations from NOAA-AVHRR data using Global Production Efficiency Model (GloPEM). The GloPEM model is based on physiological principles and uses the production efficiency concept, in which the canopy absorption of photosynthetically active radiation (APAR) is used with a conversion “efficiency” to estimate Gross Primary Production (GPP). NPP derived from GloPEM model over India showed maximum NPP about 3,000 gCm−2year−1 in west Bengal and lowest up to 500 gCm−2year−1 in Rajasthan. The India averaged NPP varied from 1,084.7 gCm−2year−1 to 1,390.8 gCm−2year−1 in the corresponding years of 1983 and 1998 respectively. The regression analysis of the 20 year NPP variability showed significant increase in NPP over India (r = 0.7, F = 17.53, p < 0.001). The mean rate of increase was observed as 10.43 gCm−2year−1. Carbon fixation ability of terrestrial ecosystem of India is increasing with rate of 34.3 TgC annually (t = 4.18, p < 0.001). The estimated net carbon fixation over Indian landmass ranged from 3.56 PgC (in 1983) to 4.57 PgC (in 1998). Grid level temporal correlation analysis showed that agricultural regions are the source of increase in terrestrial NPP of India. Parts of forest regions (Himalayan in Nepal, north east India) are relatively less influenced over the study period and showed lower or negative correlation (trend). Finding of the study would provide valuable input in understanding the global change associated with vegetation activities as a sink for atmospheric carbon dioxide.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bonan, G. B. (2008). Forest and climate change: Forcings, feedbacks, and the climate benefits of forest. Science, 320, 1444.
Chhabra, A., & Dadhwal, V. K. (2004). Estimating terrestrial net primary productivity over India using satellite data. Current Science, 86(2), 269.
Goetz, S. J., Prince, S. P., Smell, J., & Gleason. (2000). Inter annual variability of global terrestrial primary production: Results of a model driven with global satellite observations. Journal of Geophysical Research, 105(D15), 20077–20091.
Jingyun, F., Piao, S., Tang, Z., Peng, C., & Ji, W. (2001). Inter annual variability in net primary production and precipitation. Science, 293, 1723.
Knapp, K., & Smith, M. D. (2001). Variation among biomes in temporal dynamics of aboveground primary production. Science, 291, 481.
Kumar, M., & Monteith, J. L. (1981). Remote sensing of crop growth. In H. Smith (Ed.), Plants and the daylight spectrum (pp. 133–144). London: Academic Press.
Nemani, R. R., Keeling, C. D., Hashimoto, H., Jolly, W. M., Piper, S. C., & Tucker, C. J. (2003). Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 300, 1560.
Nemani, R., Running, S. W., Band, L. E., & Peterson, D. L. (1993). Regional hydroecological simulation system: an illustration of the integration of ecosystem models in a GIS. In M. F. Goodchild, B. O. Parks, & L. T. Steyaert (Eds.), Environmental modeling with GIS (pp. 296–304). New York: Oxford University Press.
Panigrahy, R. K., Panigrahy, S., Parihar, J. S. (2004). Spatio-temporal pattern of agro ecosystem net primary productivity of India: A preliminary analysis using spot Vgt data. Int. Symp. on Geospatial Databases for Sustainable Development, Goa 36(4): 724–729
Pinker R. T., Zhao, M., Wang, H., & Wood, E. F. (2010). Impact of satellite based PAR on estimates of terrestrial net primary productivity. International Journal of Remote Sensing, 31(19), 5221–5237.
Prince, S. D. (1991). A model of regional primary production to use with coarse resolution satellite data. International Journal of Remote Sensing, 12(6), 1313–1330.
Prince, S. D., & Goward, S. J. (1995). Global primary production: A remote sensing approach. Journal of Biogeography, 22, 316–336.
Running, S. W., & Coughlan, J. C. (1988). A general model of forest ecosystem processes for regional applications. I. Hydrological balance, canopy gas exchange and primary production processes. Ecological Modelling, 42, 125–154.
Running, S. W., & Gower, S. T. (1991). FOREST BGC, A general model of forest ecosystem processes for regional applications. II. Dynamic carbon allocation and nitrogen budgets. Tree Physiology, 9, 147–160.
Sabbe, H., & Veroustraete, F. (2000) Estimation of net primary and net ecosystem productivity of European terrestrial ecosystems by means of the C-Fix model and NOAA/AVHRR data VEGETATION 2000 conference, 2 years of operation to prepare the future, pp. 95–99. Space Application Institute, Joint Research Center, 21020 Ispra, Varese-Italy
Del Grosso, S., Parton, W., Stohlgren, T., Zheng, D., Bachelet, D., Prince, S., Hibbard, K., & Olson, R. (2008). Global potential net primary production predicted from vegetation class, precipitation and temperature. Ecology, 89(8), 2117–2126.
Thornton, P. E. (1998). Description of a numerical simulation model for predicting the dynamics of energy, water, carbon, and nitrogen in a terrestrial ecosystem. Missoula, MT: University of Montana.
VEMAP. (1995). Vegetation/Ecosystem Modelling and Analysis Project (VEMAP): Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochemical Cycles, 9, 407–437.
Zhao, M., & Running, S. W. (2010). Drought-induced reduction in global terrestrial net primary production from 2000 to 2009. Science, 329, 940–943.
ZhiQiang, G., & JiYuan, L. (2008). Simulation study of China’s net primary production. Chinese Science Bulletin, 53(3), 434–443.
Acknowledgment
Authors gratefully acknowledge Dr. Ranganath R. Navalgund, Director, SAC, and Dr. S.S. Ray, Head, AED/SAC for the suggestions and encouragement. One of the Author (RPS) thankfully acknowledges Dr. Markand P. Oza for discussions and help in analysis. Authors thank University of Maryland (http://glcf.umiacs.umd.edu/data/glopem) for providing the NPP data for analysis.
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Singh, R.P., Rovshan, S., Goroshi, S.K. et al. Spatial and Temporal Variability of Net Primary Productivity (NPP) over Terrestrial Biosphere of India Using NOAA-AVHRR Based GloPEM Model. J Indian Soc Remote Sens 39, 345–353 (2011). https://doi.org/10.1007/s12524-011-0123-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12524-011-0123-1