出 处:《Journal of Environmental Protection》2021年第7期490-507,共18页环境保护(英文)
摘 要:Estimation of NEE of Grasslands ecosystems becomes mandatory as these grasslands with their wide spread (almost 40% of land of the earth) and high plant diversity play a major role in global carbon balances and NEE at both local and global scale. The present study has been focused on understanding the role of different plant species responsible for variation in NEE of the Banni Grasslands of India. These grasslands form a belt of arid grassland having low growing forbs, graminoids and scattered tree cover. Due to its wide spread and inaccessibility of Banni, this study utilized spatial approach for evaluating carbon emissions and NEE. Landsat data was utilized for vegetation type classification and SMAP data for extraction of NEE values proved their potential for categorising vegetation type and generating NEE values precisely. Three major plant types were identified from the study area <i>viz.</i>, Grasslands, Land with <i>Acacia</i> and Land with <i>Prosopis</i>. Grasses were dominant covering 77% and the rest of the area was occupied by the other two classes, <i>i.e. Acacia</i> and <i>Prosopis</i>. The NEE values were higher for the grasses when compared to the other two plant species proving to be the active sinks when compared to other plants. The differential contribution of NEE by species has been depicted in the present work.Estimation of NEE of Grasslands ecosystems becomes mandatory as these grasslands with their wide spread (almost 40% of land of the earth) and high plant diversity play a major role in global carbon balances and NEE at both local and global scale. The present study has been focused on understanding the role of different plant species responsible for variation in NEE of the Banni Grasslands of India. These grasslands form a belt of arid grassland having low growing forbs, graminoids and scattered tree cover. Due to its wide spread and inaccessibility of Banni, this study utilized spatial approach for evaluating carbon emissions and NEE. Landsat data was utilized for vegetation type classification and SMAP data for extraction of NEE values proved their potential for categorising vegetation type and generating NEE values precisely. Three major plant types were identified from the study area <i>viz.</i>, Grasslands, Land with <i>Acacia</i> and Land with <i>Prosopis</i>. Grasses were dominant covering 77% and the rest of the area was occupied by the other two classes, <i>i.e. Acacia</i> and <i>Prosopis</i>. The NEE values were higher for the grasses when compared to the other two plant species proving to be the active sinks when compared to other plants. The differential contribution of NEE by species has been depicted in the present work.
关 键 词:Normalized Difference Vegetation Index (NDVI) Fractional Vegetation Coverage (FVC) CO2 Flux Prosopis Grasses Acacia
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