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5 March 2019 A Modification of CIM for Prediction of Net Primary Productivity of the Three-River Headwaters, China
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Abstract

The Three-River Headwaters (TRH) region is covered dominantly with alpine meadow, a large part of which is confronting severe degradation as a result of climate change and human-induced influences. The estimation of net primary productivity (NPP) is essential to provide support for scientific management of TRH grassland resources to prevent further degradation. The classification indices-based model (CIM) has been applied in the estimation of NPP and its response to global warming because of its simple structure and easily obtained indices. However, CIM is considered to estimate the potential NPP rather than the actual value. Thus, its application has been restricted. In this study, the normalized difference vegetation index (NDVI) was applied to modify the CIM. Then, CIM and modified CIM were compared with the other three models. The assessment of NPP estimates indicated that the modified CIM had a fair performance among the NPP models (R2= 0.42, RMSE = 178.08). All the NPP estimation models revealed that NPP increased from the northwest to the southeast. According to the modified CIM, the mean NPP of TRH grassland was 135.44 gC·m-2·yr-1and the total NPP was 3.22 × 1013gC·yr-1. Among the classes of the grassland of TRH in the comprehensive and sequential classification system( CSCS), the frigid perhumid rain tundra and alpine meadow occupied most of the grassland NPP, which was 3.06× 1013gC·yr-1. With the help of the NDVI, the modified CIM performed better than the CIM; however, there is still much room for the improvement of CIM in future research.

© 2018 The Society for Range Management. Published by Elsevier Inc. All rights reserved.
Chong Wang, Huilong Lin, and Yuting Zhao "A Modification of CIM for Prediction of Net Primary Productivity of the Three-River Headwaters, China," Rangeland Ecology and Management 72(2), 327-335, (5 March 2019). https://doi.org/10.1016/j.rama.2018.11.003
Received: 16 November 2017; Accepted: 6 November 2018; Published: 5 March 2019
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