Diversity and Assembly of a Sub-Tropical Grassland Community in Eastern Himalaya: Open defense of PhD thesis by Dhritiman Das

Abstract: The Terai ecosystem at the base of the Himalayas has some of the most extraordinary grasslands in the world. The vegetation at large scales appears as a mosaic of woodland and grassland, and the environment is typically characterized by a high water table, annual flooding, and dry season grassland fires. Research has shown that the grassland and forest spatial patchiness and successional dynamics may be driven by complex interactions between climate, hydrology, herbivore pressure, and disturbance dynamics. 

I chose to study the Terai ecosystem in Manas National Park (MNP), Assam, a highly diverse grassland and forest mosaic with an area of 519 sq. km, situated in the north bank landscape of the Brahmaputra River in Assam. My study focused on three aspects. In the first, I examined the dynamics of vegetation during the last 3 decades (1988-2016) in MNP using satellite images to describe and understand forest-grassland transitions. The time sequence maps show a highly dynamic landscape of forest and grassland distributions, where the dynamism appears strongly correlated with hydrological action, and fire and other factors to a smaller extent. In the second part of the thesis, I assess the relative contributions of environmental and spatial factors to the variation in species abundances of trees and grasses across the MNP landscape. We found that soil nutrients, including N, P, and K, climatic variables including dry and wet season precipitation, and habitat factors including recent history of fire and moisture stress, could collectively explain only about 20% of the variation in species abundances. Spatial connectivity models that linked sites through dispersal up to about 15 km had best support in our data. However, a large amount of variation (~79%) in species abundances remain unexplained indicating that the contributions of unmeasured environmental factors, biotic interactions, and stochasticity induced by disturbance and history needs to be investigated with greater rigor. 

It is feared that recent disturbance may have promoted the spread of alien invasive plant species in this region, with attendant threats to native biodiversity. I studied invasive species abundance as a function of several environmental variables. I found that Mikania micrantha, an herbaceous climber, and Chromolaena odorata, a non-woody shrub, were the most prevalent and abundant species. Using a decision-tree based regression-prediction algorithm (Random Forests) I attempted to map the distributions of these two species for MNP at the landscape level. However, the statistical power of environmental variables to predict invasive species distributions was very poor for Mikania and insignificant for Chromolaena. 

Overall, my study shows that while environmental factors such as climate, soils, and habitat factors influence the tree-grass mixtures, most of this variation in species abundances remains to be investigated and understood.