Abstract
In this study, we proposed climate use efficiency (CUE), a new index in monitoring grassland ecosystem function, to mitigate the disturbance of climate fluctuation. A comprehensive evaluation index (EI), combining with actual vegetation net primary productivity (NPP), CUE, vegetation coverage, and surface bareness, was constructed for the dynamic remote sensing monitoring of grassland degradation/restoration on a regional scale. By using this index, the grassland degradation/restoration in the Three-River Source Region (TRSR) was quantitatively evaluated during 2001–2016, which has been an important ecological barrier area in China. Results showed the following: During the study period, the grassland of Yellow River source (SRYe) had high vegetation coverage, NPP, CUE, and low bareness, whereas Yangtze River source (SRYa) had low vegetation coverage, NPP, CUE, and high bareness. The vegetation coverage and CUE of the grassland showed upward trends, with annual change rates of 0.75% and 0.45% year −1. The surface bareness and NPP showed downward trends, with annual change rates of −0.37% year−1 and −0.24 g C m−2 yr−2, respectively. Assessment of EI revealed that 67.18% of the grassland of TRSR showed a recovery trend during the study period. The overall restoration of the SRYe was the best, followed by SRYa. However, the status of Lancang River source (SRLa) was poor.
Highlights
The area of grassland degradation reached 14 × 106 km2 in 2010, accounting for nearly 49.3% of the world’s grassland area [1]
We proposed climate use efficiency (CUE) as a new index in monitoring grassland ecosystem function to mitigate the disturbance of climate fluctuation
Ij represents the respective contribution rates of vegetation coverage, surface bareness, net primary productivity (NPP), and CUE; aj is the corresponding values of their first principal component of the eigenvector
Summary
The area of grassland degradation reached 14 × 106 km in 2010, accounting for nearly 49.3% of the world’s grassland area [1]. Remote sensing has played an unprecedented role in land degeneration mapping, assessment, and monitoring at multiple spatial and temporal scales [5], offering broadly automated and repeatable methods for indicators of vegetation condition [6]. Grassland vegetation index, such as net primary productivity (NPP), vegetation coverage, or biomass is the direct manifestation of grassland degeneration [7]. Inter-annual grass growth fluctuates with climatic condition when monitoring temporal dynamic change; it is hard to distinguish grassland degradation from the influence of climate It leads to overestimating of the severity of degradation in a poor harvest year and underestimating in bumper harvest year. This study could serve as a theoretical reference for the treatment and rational utilization of grassland resources, offering demonstration and reference for similar research
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