The determinants of Grassland-woodland mosaics in the Terai ecosystems of the Indian subcontinent

Banerjee, Subham (2022) The determinants of Grassland-woodland mosaics in the Terai ecosystems of the Indian subcontinent. PhD thesis, Indian Institute of Science Education and Research Kolkata.

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The Terai-Duar Savanna and Grassland ecoregion (hereafter terai), located at the base of the Himalayas in the Indian subcontinent, support diverse ecosystems with pure grasslands, savanna, and forests in varying proportions. There are indications that grasslands and savanna are being lost to woody encroachment across the ecoregion. A significant fraction of plant and animal taxa are endemic to grasslands, so the decline of grasslands is likely to impact biodiversity and ecosystem function. We assessed large-scale vegetation changes to terai habitats over three decades (1989-2019) and then quantified the role of environmental factors in driving the observed changes. Selecting eight large protected areas (four each from India and Nepal), we performed supervised vegetation classification for three time points in the 30-year period. We then quantified grassland-woodland transitions and used Bayesian Conditional Autoregressive spatial models to test the influence of several climatic, environmental, and anthropogenic factors on these changes. Despite considering all the protected sites with substantial grassland areas, we found that the total extent of grasslands was only 1417 km2 in 1988-1989, which declined to 923 km² (34.4%) in three decades, while woodland area increased from 3235 km² to 3516 km² (8.7%). To a lesser extent, grasslands were also converted to cropland or inundated by flooding. Dry season grass fire had the strongest influence on grassland persistence, followed by anthropogenic impacts. Terai ecosystems also experience significant threats from climatic changes and increasing human footprint, particularly in India, and the loss of grasslands due to anthropogenic impacts needs to be urgently addressed. The use of fires to maintain vegetation and wildlife habitat in the Terai protected areas is an integral part of forest management. Although fires are initiated by forest managers or local people, their eventual spread and behaviour are not controlled. We hypothesize that distributions of fires are determined by several direct and indirect drivers like fuel load, fuel moisture content, presence of natural or artificial fire breaks, and climatic attributes of precipitation and temperature. Using the moderate-resolution (375-m) satellite sensor-based data we studied the environmental influence on the spatial-temporal patterns of fire events over 18 years (2000-2018) in Manas National Park of India. Like the rest of the Terai, the park has a mosaic of vegetation formations – including dry and swampy alluvial grassland, early successional woodland, and moist tropical forest. Despite high rainfall, there is an intense dry season that renders the herbaceous vegetation susceptible to fires. Using spatial and spatial-temporal Poisson regression models in a rigorous conditional autoregressive Bayesian framework, we found that net primary productivity (a proxy of vegetation type and fuel load), distance to roads (a measure of human influence), elevation (through its influence on floods and vegetation type), and river area extent (by determining the area under vegetation) had a significant influence on the spatial distributions of fires. The climatic signal on interannual variation in fires was weak, but dry season rainfall reduced fire incidence. The disproportionate distribution of fires adjacent to roads compared to the interior, and the repeated burning of some grassland patches need to be addressed in fire management. In recent times, globally, invasive plant species have wreaked havoc on maintaining protected areas for threatened species. The terai protected areas also experiencing the alien plant invasion. To study the distribution and impact of the major invasive plants in Manas National Park, we conducted a vegetation survey in 107 plots of size 30-m × 30-m, during November 2019 to March 2020. Mikania micrantha (climber) and Chromolaena odorata (shrub) were found to be the most prevalent invasive species of the park. We evaluated the change in invasive abundance in 83 plots with the present data and our previously (2011) surveyed data. We used decision tree-based regression to assess the influence of environmental variables on the distribution and abundance of the two species and create invasion risk maps. The impacts of the two invasives on plant communities were also analyzed by comparing non-invaded and invaded quadrats. Chromolaena odorata and Mikania micrantha have increased their density in majority of the plots, sometimes by more than twofold. The regression models had explained the abundance of Chromolaena odorata (R² = 0.47) and Mikania micrantha (R2 = 0.82) with significant predictive power. Road proximity and Fire frequency had the strongest influence on Chromolaena odorata and Mikania micrantha, respectively. Chromolaena odorata has shown negative impact on plant community structure. The rapid growth in number and range of these two invasive species over the last eight years is concerning. Predicted invasion risk maps can be used as an early detection tool for invasive species control, thereby reducing invasions' ecological and economic impact. The findings of this study will assist forest authorities in managing, taking the appropriate actions in the designated region, and developing a complete plan for invasive species control.

Item Type: Thesis (PhD)
Additional Information: Supervisor: Dr. Robert John Chandran
Uncontrolled Keywords: Chromolaena odorata; Grassland-woodland Transitions; Indian Subcontinent; Manas National Park; Mikania micrantha; Terai-Duars; Terai Ecosystems; Vegetation Changes
Subjects: Q Science > QH Natural history > QH301 Biology
Q Science > QK Botany
Divisions: Department of Biological Sciences
Depositing User: IISER Kolkata Librarian
Date Deposited: 22 Aug 2022 05:37
Last Modified: 22 Aug 2022 05:37

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