磷影响陆地生态系统碳循环过程及模型表达方法

全球气候变暖已大大改变了陆地植物碳吸收能力, 提高了全球植被净初级生产力。随着气候变暖的加剧, 磷对植物生长的限制作用逐渐显现且不断增强, 磷影响陆地生态系统碳循环的机理和模型研究已成为研究热点。该文系统分析了磷影响陆地生态系统碳循环的相关机理以及模型对相关过程的定量化表达方法。综合对比分析了国际上的Carnegie- Ames-Stanford Approach-CNP (CASA-CNP)、Community Land Model-CNP (CLM-CNP)和Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg-CNP (JSBACH-CNP)等碳、氮、磷耦合模型中磷影响植物光合作用与同化物分配过程、植物对磷的吸收过程、土壤中磷的转化过程以及生态系统磷输入与输出等过程的相关数学表达方法, 指出了模型算法的局限与不确定性以及未来模型发展与改进的方向。同时综合对比分析了CASA-CNP、CLM-CNP、JSBACH-CNP模型的基本特征, 总结了磷循环模型的建模方法, 为未来开展磷影响陆地生态系统碳循环的模型模拟研究提供了借鉴方法与参考思路。

Modeling phosphorus effects on the carbon cycle in terrestrial ecosystems

Climate warming has significantly alerted the terrestrial carbon dynamics, resulting in enhanced vegetation productivity, especially in the northern hemisphere. However, most of the prior modeling studies have neglected the effects of nutrient availability, such as the phosphorus limitation, on carbon processes, which potentially leads to an overestimation of the capacity of terrestrial ecosystems to sequester additional carbon. Here, we reviewed recent progress in phosphorus limitation and its interactions with carbon dynamics in the context of climate change, with a focus on the process-based modeling approach. We comparatively analyzed quantitative representations of phosphorus-associated biological processes in some models (i.e., Carnegie-Ames-Stanford Approach (CASA), Community Land Model (CLM), and Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg (JSBACH)), such as photosynthesis and distribution of assimilates, phosphorus uptake by plants, the transformation of phosphorus pools in soil, phosphorus inputs and outputs, etc. We also discussed the key characteristics of these models and summarized the mathematical representations of the terrestrial phosphorus cycle. In addition, we identified and discussed the limitations, uncertainties and future needs in process-based modeling in terms of nutrient and carbon dynamics. Our study highlighted the importance of including phosphorus limitation in regional carbon estimation and provided deep insights related to biogeochemical modeling at broad scales.