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Investigating the contribution of climate variables to estimates of net primary productivity in a tropical deciduous forest in India

pmid: 31989264
Investigating the contribution of climate variables to estimates of net primary productivity in a tropical deciduous forest in India
Investigating the impact of climate variables on net primary productivity is crucial to evaluate the ecosystem health and the status of forest type response to climate change. The objective of this paper is (1) to estimate spatio-temporal patterns of net primary productivity (NPP) during 2001 to 2010 in a tropical deciduous forest based on the input variable dataset (i.e.meteorological and biophysical) derived from the remote sensing and other sources and (2) to investigate the effects of climate variables on NPP during 2001 to 2010. The study was carried out in Katerniaghat Wildlife Sanctuary that forms a part of a tropical forest and is situated in Uttar Pradesh, India, along the Indo-Nepal border. Mean annual NPP was observed to be highest during 2007 with a value of 878 g C m-2 year-1 and 781.25 g C m-2 year-1 for sal and teak respectively. A decline in mean NPP during 2002-2003, 2005 and 2008-2010 could be attributed to drought, increased temperature and vapour pressure deficit (VPD). The time lag correlation analysis revealed precipitation as the major variables affecting NPP, whereas combination of temperature and VPD showed dominant effect on NPP as revealed by generalized linear modelling. The carbon gain in NPP in sal forest was observed to be marginal higher than that of teak plantation throughout the study period. The decrease in NPP was observed during 2010, pertaining to increased VPD. Contribution of different climatic variables through some link process was revealed in statistical analysis and clearly indicated the co-dominance of all the variables in explaining NPP.
China, Climate Change, India, Forests, Trees, Nepal, Ecosystem, Environmental Monitoring
China, Climate Change, India, Forests, Trees, Nepal, Ecosystem, Environmental Monitoring
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