State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A & F University, Yangling 712100, China.
Key Laboratory of Virtual Geographical Environment of Ministry of Education, Nanjing Normal University, Nanjing 210023, China; Jiangsu Centre for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China; School of Geographical Sciences, Nanjing Normal University, Nanjing 210023, China.
Sci Total Environ. 2022 May 20;822:153343. doi: 10.1016/j.scitotenv.2022.153343. Epub 2022 Jan 29.
Many models were established to estimate gross primary production (GPP) of terrestrial ecosystems based on vegetation light use efficiency (LUE). Analysing the spatial-temporal variations of global terrestrial GPP became capable with the increasing length of satellite data. Previous studies mainly focused on evaluating the model performance or investigating the mean, the temporal trend or the interannual variability (IAV) of global terrestrial GPP based on one single or multiple models, which is difficult to identify common merits of a same cluster of GPP models. This study compared eight satellite-based LEU-type GPP models in capturing the mean, temporal trend and IAV of global GPP concurrently. Our results showed that current common-used models based on LUE methodology estimated global mean GPP ranging from 128.5 to 158.3 Pg C year, and global mean IAV ranging from 0.1 to 0.35, but the trends ranging from -0.22 to 0.51 Pg C year. In the context of plant functional types (PFTs) and climate classifications, no consistent feature for either of the mean, trend or IAV of GPP are identified among eight models. Future studies should integrate the latest advances on the mechanisms and associated environmental factors into models and consolidate performance of models to better understand the evolutions of terrestrial ecosystem functioning.
许多模型被建立起来，基于植被的光能利用效率（LUE）来估算陆地生态系统的总初级生产力（GPP）。随着卫星数据的不断延长，全球陆地 GPP 的时空变化分析成为可能。以前的研究主要集中在评估模型的性能或基于一个或多个模型来研究全球陆地 GPP 的平均值、时间趋势或年际变异性（IAV），这很难确定同一组 GPP 模型的共同优点。本研究比较了八种基于卫星的 LUE 型 GPP 模型，以同时捕捉全球 GPP 的平均值、时间趋势和 IAV。我们的结果表明，目前基于 LUE 方法学的常用模型估计全球平均 GPP 范围为 128.5 到 158.3Pg C 年，全球平均 IAV 范围为 0.1 到 0.35，但趋势范围为-0.22 到 0.51Pg C 年。在植物功能类型（PFTs）和气候分类的背景下，八种模型中都没有确定 GPP 的平均值、趋势或 IAV 的一致特征。未来的研究应该将最新的关于机制和相关环境因素的进展整合到模型中，并整合模型的性能，以更好地了解陆地生态系统功能的演变。
