Reference carbon cycle dataset for typical Chinese forests via colocated observations and data assimilation

Chinese forests cover most of the representative forest types in the Northern Hemisphere and function as a large carbon (C) sink in the global C cycle. The availability of long-term C dynamics observations is key to evaluating and understanding C sequestration of these forests. The Chinese Ecosystem Research Network has conducted normalized and systematic monitoring of the soil-biology-atmosphere-water cycle in Chinese forests since 2000. For the first time, a reference dataset of the decadal C cycle dynamics was produced for 10 typical Chinese forests after strict quality control, including biomass, leaf area index, litterfall, soil organic C, and the corresponding meteorological data. Based on these basic but time-discrete C-cycle elements, an assimilated dataset of key C cycle parameters and time-continuous C sequestration functions was generated via model-data fusion, including C allocation, turnover, and soil, vegetation, and ecosystem C storage. These reference data could be used as a benchmark for model development, evaluation and C cycle research under global climate change for typical forests in the Northern Hemisphere.

中国森林涵盖北半球绝大多数典型森林类型，在全球碳循环（Carbon cycle）中发挥着大型碳汇（Carbon sink）的功能。长期碳动态观测数据的获取，是评估与明晰该类森林固碳（Carbon sequestration）能力的核心前提。中国生态系统研究网络（Chinese Ecosystem Research Network）自2000年起，对中国森林的土壤-生物-大气-水循环开展了规范化、系统化的监测工作。本研究首次针对10处典型中国森林，经严格质量控制后构建了年代际碳循环动态参考数据集，涵盖生物量、叶面积指数（Leaf area index）、凋落物产量、土壤有机碳及配套气象数据。基于这些基础但时间离散的碳循环核心要素，通过模型数据融合（Model-data fusion）方法，生成了包含关键碳循环参数与时间连续固碳功能的同化数据集，内容涉及碳分配、周转过程以及土壤、植被与生态系统碳储量。该参考数据集可作为北半球典型森林在全球气候变化背景下开展模型研发、模型评估及碳循环研究的基准参照。