| 英文摘要： |
Plant functional traits are considered a potential approach to explain the spatial variation of ecosystem productivity on a large scale, but how to involve traits in models to predict productivity is still a challenge. Here, we propose a novel trait-based productivity (TBP) framework, as a core of plant community traits in land areas, to interpret the variation in productivity. We assumed that productivity in TBP is determined by a threedimensional combination of efficiency x quantity x growth length and tested it using data regarding leaf chlorophyll traits (scaling-up community weighted mean) in three grassland transects of the Tibetan, Mongolian, and Loess Plateaus in China. The results showed that 52%, 54%, and 67% of the variations in gross primary productivity, net primary productivity, and aboveground net primary productivity, respectively, were captured by the TBP framework in all grassland transects, indicating that it was applicable for the three environmentally distinct plateaus. Furthermore, it was more fitted to the environmentally stressful Tibetan plateau, with an explanatory power of up to 83%. Compared with chlorophyll efficiency, the chlorophyll quantity which is regulated by climate or regional limiting factors, has dominant roles in influencing the spatial variation of grassland productivity. The TBP framework emphasises the connotation of traits behind community functions and seemed as a potential in ecological estimations and predictions; however, multiple traits should be considered for further improvement in the future. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
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