Modeling net primary productivity of tropical deciduous forests in North India using bio-geochemical model

Abstract

The present work investigates the applicability of a widespread bio-geochemical model (Biome BGC) to simulate monthly net primary productivity (NPP) and leaf area index (LAI) of Indian tropical deciduous forests. We simulated the monthly NPP and LAI of three plant functional types (PFTs) [dry mixed (DM), sal mixed (SM) and teak plantation (TP)] having distinct tree species compositions, canopy structure, different carbon assimilation rates and microclimate within a broad tropical deciduous forest during 2011–2012. The parameterization of 11 major eco-physiological parameters of Biome BGC was performed from in-situ physiological measurements gathered from 9 long-term ecological research plots in above three PFTs and PFT specific indices were developed. Bimodal trends, with highest peak in September during autumn and second peak in January during winter were observed for simulated monthly NPP in all three PFTs. Simulated NPP (gC/m2/year) values were 408.8 and 414.6; 376.8 and 392.9; and 327.5 and 338.2 during 2011 and 2012 in DM, SM and TP PFTs respectively. Observed NPP (gC/m2/year) values ranged between 463.4 and 493.1; 498.0 and 529.5; and 542.1 and 677.9 in 2012 in DM, SM and TP PFTs respectively. Biome BGC simulated NPP were in positive agreement with observed NPP in all PFTs (R2 = 0.92, 0.83 and 0.72 in DM, SM and TP respectively). In all PFTs Biome BGC led to an underestimation of LAI. The current investigation evaluated the operational application of Biome BGC in Indian tropical deciduous forest and opens scope for further improvement for LAI algorithms for better in-situ LAI simulation.