Most earth system models fail to capture the seasonality of carbon fluxes in radiation-limited tropical evergreen forests (TEF) in the Amazon. Kim et al. (2012, https://doi.org/10.1111/j.1365-2486.2011.02629.x) first statistically incorporated a light-controlled phenology module into an ecosystem model to improve carbon flux simulations at one TEF site. However, it is not clear how their approach can be extended to other TEF sites with different climatic conditions. Here we evaluated temporal variability in plant functional traits at three different TEF sites using a data-conditioned stochastic parameterization method. We showed that previously studied links—between seasonal photosynthetically active radiation (PAR) and the traits V_cmax25 and leaf longevity—occur across sites. We further determined that seasonal PAR could similarly drive variations in the stomatal conductance slope parameter. Differences found in temporal trait estimates among sites indicate that dynamic trait parameters cannot be applied uniformly over space, but it may be possible to extrapolate them based on climatic factors. Motivated by recent observations that physiological capacity develops as leaves mature, we built new regression models for predicting traits that not only include PAR but also an autoregressive lag term to capture observed physiological delays behind PAR-driven phenology shifts. With our stochastic parameterization, we predicted the three sites to be carbon neutral or carbon sinks under the RCP 8.5 future climate scenario. In contrast, projections using standard static trait parameters show most of the Amazonian TEF region becoming a carbon source. We further approximated that variable traits may allow at least a third of the radiation-limited TEF region in the Amazon to serve as a future net carbon sink.

中文翻译：

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评估多个亚马逊常绿林地的叶功能性状及其驱动因素的时空变异性：一种具有陆表建模的随机参数化方法

大多数地球系统模型未能捕捉到亚马逊辐射受限热带常绿森林 (TEF) 中碳通量的季节性。金等人。（2012，https://doi.org/10.1111/j.1365-2486.2011.02629.x）首先在统计上将光控物候模块纳入生态系统模型，以改善一个 TEF 站点的碳通量模拟。但是，尚不清楚如何将他们的方法扩展到具有不同气候条件的其他 TEF 站点。在这里，我们使用数据条件随机参数化方法评估了三个不同 TEF 站点植物功能性状的时间变异性。我们展示了先前研究的联系——季节性光合有效辐射 (PAR) 与性状V _{c max25}和叶子寿命——跨站点发生。我们进一步确定季节性 PAR 可以类似地驱动气孔导度斜率参数的变化。在站点之间的时间特征估计中发现的差异表明动态特征参数不能在空间上均匀应用，但可以根据气候因素对其进行推断。最近观察到生理能力随着叶子成熟而发展，受此启发，我们建立了新的回归模型，用于预测不仅包括 PAR 还包括自回归滞后项的特征，以捕捉观察到的 PAR 驱动物候变化背后的生理延迟。通过我们的随机参数化，我们预测这三个地点在 RCP 8.5 未来气候情景下是碳中和或碳汇。相比之下，使用标准静态特征参数的预测显示，亚马逊 TEF 地区的大部分地区成为碳源。我们进一步估计，可变性状可能允许亚马逊中至少三分之一的辐射受限 TEF 区域作为未来的净碳汇。