Abstract:

Forest ecosystems constitute the foundation of terrestrial carbon (C) sinks. Precise quantification of their sequestration capacity is an essential prerequisite for enhancing C storage in terrestrial ecosystems and mitigating climate change. Especially, it is of great value in predicting long-term C dynamics for optimizing forest management strategies and achieving China’s dual C strategic objectives. The currently widely used process models are mainly based on the prediction frameworks of forest ecosystem productivity, utilizing “light quantum transfer-large leaf model” to characterize C sink formation mechanisms. These models evaluate short-term ecological dynamics through key biometric indicators including gross primary production (GPP) and net primary production (NPP), thereby overcoming inherent limitations in traditional methods for predicting ecosystem C sequestration potential. Theoretically, community attributes significantly influence the variation in forest carbon sink functions. Under the dual regulation of climatic effects and interspecific competition, the dynamics of forest carbon sinks are primarily dictated by stand age and vegetation growth processes. Therefore, assessments of forest carbon sink dynamics should incorporate a full consideration of these regulatory mechanisms. However, current research on the formation mechanism of forest ecosystem carbon sinks is difficult to scientifically explain the forest community growth trajectories. Productivity-based predictive approaches demonstrate limited capacity to support process models in evaluating long-term growth trends and spatiotemporal heterogeneity of C sequestration, consequently constraining the effectiveness of scientific evidence available for policy formulation. To address these methodological constraints, this study systematically elaborates on a research framework for predicting the long-term forest C sequestration based on tree growth processes. This framework, based on growth equations, characterizes the long-term expansion of biomass C pools driven by stand age dynamics, integrates the response mechanisms of C sink to climatic and soil variables into the traditional vegetation growth hypotheses, and thus, achieves a process-based prediction model for forest C dynamics that incorporates both ecological and environmental determinants. The forest C sequestration model (FCS model) was developed using the logistic growth equation and key parameters to characterize long-term dynamic patterns of forest vegetation C sinks. This model builds upon a process-based C turnover approach to create a predictive framework for forest ecosystem C sequestration, wherein the dynamics of forest vegetation drive the stock growth of other major C pools, such as the dead organic matter C pool and soil organic C pool. The model was parameterized using systematic survey data from typical forest ecosystems in China. Studies have shown that the FCS model effectively quantifies the spatiotemporal covariation patterns of forest ecosystem C sinks. This predictive framework, grounded in tree growth processes, offers a novel theoretical paradigm for C sink projections. It significantly improves the simulation capability of long-term dynamic changes in forest ecosystem C sinks, thereby providing stronger support for China’s efforts to achieve its “C neutrality” strategic objectives.

Key words: forest carbon sequestration, ecosystem model, stand age, succession theory, carbon neutrality