ANALYSIS OF LAND USE, DIVERSITY, BIOMASS, C AND NUTRIENT STORAGE OF A DRY TROPICAL FOREST ECOSYSTEM OF INDIA USING SATELLITE REMOTE SENSING AND GIS TECHNIQUES

Abstract

Tropical forests are recognised as rich, diverse and highly productive ecosystems of the world. More than half of the global annual NPP occurs in the tropics. In India, the tropical forests covers about 75%. The present study was carried out to characterize the land use, vegetation structure, diversity, biomass production, C and nutrient storage of a dry tropical forest ecosystem in Barnawpara Sanctuary, Raipur district of Chhattisgarh through satellite remote sensing techniques and GIS. Results revealed that density of different forest types varied from 324 to 733 trees ha-1, basal area from 8.13 to 28.87 m2 ha-1 and number of species from 9 to 26. Similarly, the diversity ranged from 1.36 to 2.98, concentration of dominance from 0.07 to 0.49, species richness from 3.88 to 6.86 and beta diversity from 1.29 to 2.21. Sal mixed forest type recorded highest basal area and diversity was highest in Dense mixed forest, while Teak forest recorded maximum density. It was poor in Degraded mixed forests. Results revealed that the highest biomass was found in Dense mixed forest (321464.28 Mg), while net production was highest in Teak forests. Both were lowest in Degraded mixed forests (42996.08 Mg) in different forest types. The total storage of nutrients in vegetation (OS+US+GS) varied from 105.1 to 560.69 kg ha-1 in N, 4.09 kg ha-1 to 49.59 kg ha-1 in P, 24.59 kg ha-1 to 255.58 kg ha-1for K and 7310 to 4836 kg ha-1 for C in different forest types. They were highest in Dense mixed forest and lowest in Degraded mixed forest.

The study also showed that NDVI and carbon storage was strongly correlated to Shannon Index and species richness thus it indicates that the diversity of forest type play a vital role in carbon accumulation. The study also developed reliable regression model for the estimation of LAI, biomass, NPP, C & N storage in dry tropical forests by using NDVI and different vegetation indices, which can be derived from fine resolution satellite data.

Both quantitative and qualitative information derived in the study helped in evolving key strategies for maintaining existing C pools and also improving the C sequestration in different forest types. The study explores the scope and potential of dry tropical forests of Chhattisgarh for improving C sequestration and mitigating the global warming and climatic change.