PnET-CN模型对东亚森林生态系统碳通量模拟的适用性和不确定性分析

Application of the PnET-CN Model to Different Forest Ecosystems in East Asia

东亚地区森林类型多样,开展区域生态系统碳循环模拟时应考虑森林类型的差异。论文利用基于叶氮浓度-最大净光合作用速率关系的PnET-CN模型,对东亚地区8个森林生态系统通量观测站点的总生态系统碳交换(GEE)和生态系统呼吸(RE)进行模拟,以探讨模型的适用性并对不确定性来源进行分析。研究结果表明:1PnET-CN模型能较为准确地模拟东亚地区大部分森林生态系统站点的GEE和RE;2模型的适用性排序依次为温带、寒温带、亚热带、热带,模型未能很好地模拟热带湿地森林GEE和RE的季节与年际变异;3在同一气候区中,PnET-CN模型更加适用于针叶林碳交换的模拟;4PnET-CN模型比较准确地反映了东亚森林生态系统GEE、RE对气候因子(例如,温度或辐射)的响应,但在低温、较弱辐射条件下模型低估了GEE,在高温或较强辐射条件下高估了GEE;在低温条件下模型低估了RE,在高温条件下模型高估了RE。针对东亚多个森林通量站点的模拟情况,论文提出模型应在以下方面进行改进:1PnET-CN模型计算物候时除了考虑温度之外还应加入土壤湿度的影响,并对不同气候区森林生态系统赋予不同叶片凋落时长;2PnET-CN模型中温度对GEE的限制以及光合最适温度应该根据不同站点设置;3PnET-CN模型应该考虑森林生态系统对环境胁迫的适应性,加强对干旱等干扰的模拟;4同时对于拥有复杂水文条件的森林生态系统应该改进土壤含水量的算法,以准确反映该类型森林生态系统GEE和RE的季节变化。

Great spatial diversity exists in forest ecosystems in East Asia, thus it is necessary to take the difference among forest biomes into account in regional carbon cycle modelling. This study applied an Amax–N% relationship based model, the PnET-CN model, to eight flux sites to comprehensively evaluating its performance and uncertainty. The biomes at these eight sites include deciduous needle-leaved forest, deciduous broad-leaved forest, evergreen needle-leaved forest and evergreen broad-leaved forest. The climate ranges from cold temperate to tropical.The PnET-CN model was applied to these eight sites to model the monthly carbon flux variation. The overall PnET-CN model performance was comprehensively evaluated using three indicators: correlation coefficient(r), root mean square error(RMSE) and standard error(SD). Results showed that: 1) at monthly scale, the PnET-CN model could model the gross ecosystem exchange(GEE) and the ecosystem respiration(RE) quite well(GEE: 0.85 ≤ r ≤ 0.98; RE:0.51 ≤||r ≤ 0.98) except in a tropical swamp forest(GEE: r = 0.16; RE: r =-0.21); 2) but the applicability in different climate regimes was not the same; it had the best performance in temperate zone, then cold temperate zone, subtropical zone and last tropical zone; 3) the PnETCN model could model needle leaved forests better than broad-leaved forests; and 4) the PnETCN model underestimated GEE at low temperature and low radiation and vice versa; the same phenomena occurred to RE responding to temperature. Finally, this study analysed reasons for the gaps between simulated and observed data and gave suggestions on improving the model:1) effects of soil moisture should be accounted for in estimating phenology and the process of leaf senescence should be assigned different values depending on the climate zone; 2) the regulation of temperature and the optimal temperature for photosynthesis should be set differently in different ecosystems; 3) it is necessary to take the resilience and adaptation capacity of forest ecosystems into account in response to disturbance such as drought and high temperature; 4)the PnET-CN model should improve its bucket model to simulate the seasonal dynamics of carbon fluxes in forest ecosystems with complex hydrological conditions. Our results and conclusions are helpful for understanding the spatial heterogeneity in forest ecosystem carbon cycle in East Asian region and for filling gaps between the modelling and observation.