Purpose

The quantitative study for the allocation of photosynthetically fixed carbon to plant tissues, soil, and respiratory losses is essential for understanding the key process of carbon (C) cycle. In this study, the measured C flux data was used to validate a process-based denitrification-decomposition (DNDC) model, and the C budget components were simulated and quantitatively separated in the Qinghai-Tibet Plateau alpine wetland ecosystem.

Materials and methods

The field observation and 50-year climate data in this site were used as input to simulate soil environment change, plant growth, and C allocation for DNDC. The local parameterization, optimization, calibration, and evaluation of the process-based DNDC model were conducted to improve the simulation accuracy of the model and to separate the C budget components of the Zoige alpine wetland ecosystem on the basis of measured C flux data.

Results and discussion

The results show that the modeled and measured values have good consistency on multiple time scales, and the system shows obvious C sink (− 169.16 g C m⁻² yr⁻¹). The plant net primary productivity (NPP) accounted for 53% of gross primary productivity (GPP); the plant autotrophic respiration (R_a) accounts for 61% of ecosystem respiration (R_e); and the soil heterotrophic respiration (R_h) accounts for 51% of soil respiration (R_s). Vegetation has the strongest photosynthesis and net C sequestration capacity during the peak growth stage, while the system appears as a C source in the senescence stage. Moreover, R_a dominated during the first four periods of plant growth, while R_h was dominant in the plant senescence stage. There was a negative correlation between environmental factors and NEE and a significant positive relationship with other C budget variables (P < 0.001). Precipitation and temperature regulate the C budgets and C distribution. When soil temperature and monthly precipitation exceeded 7 °C and 18 mm mon⁻¹, the ecosystem switched from C source to C sink.

Conclusions

The optimized DNDC model can capture the dynamics of C budget in Zoige alpine wetland, and there are large differences in the function of C source and sink, C allocation, and relative contribution during different plant growth stages. Our work will provide support to predict the changes in C cycle components at regional scales in future climate change scenarios and to formulate measures to mitigate greenhouse effects.

中文翻译：

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降水和温度调节高山湿地的碳分配过程：定量模拟

目的

将光合固定碳分配至植物组织，土壤和呼吸系统损失的定量研究对于理解碳（C）循环的关键过程至关重要。在这项研究中，使用测得的碳通量数据来验证基于过程的反硝化分解（DNDC）模型，并在青藏高原高山湿地生态系统中模拟并定量分离了碳预算组成。

材料和方法

该站点的现场观测和50年气候数据被用作模拟土壤环境变化，植物生长和DNDC碳分配的输入。对基于过程的DNDC模型进行了局部参数化，优化，校准和评估，以提高模型的仿真精度，并根据测得的C通量数据分离Zoige高山湿地生态系统的C预算组成部分。

结果和讨论

结果表明，模型值和测量值在多个时间尺度上具有良好的一致性，并且系统显示出明显的C吸收（-169.16 g C m ^-2  yr ^-1）。工厂的净初级生产力（NPP）占总初级生产力（GPP）的53％；植物自养呼吸（R _a）占生态系统呼吸（R _e）的61％；土壤异养呼吸（R _h）占土壤呼吸（R _s）的51％。在峰值生长阶段，植被具有最强的光合作用和净碳固存能力，而该系统在衰老阶段表现为碳源。而且，R_一个在植物生长的前四个周期为主，而[R _ħ是在植物衰老阶段占主导地位。环境因素与NEE之间呈负相关，与其他C预算变量之间呈显着正相关（P  <0.001）。降水和温度调节碳预算和碳分布。当土壤温度和每月降水量超过7°C和18 mm mon ^-1时，生态系统从C源转变为C汇。

结论

优化的DNDC模型可以捕获Zoige高山湿地的碳平衡动态，并且在不同植物生长阶段，碳源和碳汇的功能，碳分配和相对贡献存在很大差异。我们的工作将为预测未来气候变化情景中区域尺度C循环成分的变化提供支持，并制定减轻温室效应的措施。