Modeling forest ecosystems is a landmark challenge in science, due to the complexity of the processes involved and their importance in predicting future planetary conditions. While there are a number of open‐source forest biogeochemistry models, few papers exist detailing the software development approach used to develop these models. This has left many forest biogeochemistry models large, opaque and/or difficult to use, typically implemented in compiled languages for speed. Here, we present a forest biogeochemistry model from the SORTIE‐PPA class of models, PPA‐SiBGC. Our model is based on the perfect plasticity approximation with simple biogeochemistry compartments and uses empirical vegetation dynamics rather than detailed prognostic processes to drive the estimation of carbon and nitrogen fluxes. This allows our model to be used with traditional forest inventory data, making it widely applicable and simple to parameterize. We detail the conceptual design of the model as well as the software implementation in the R language for statistical computing. Our aim is to provide a useful tool for the biogeochemistry modeling community that demonstrates the importance of vegetation dynamics in biogeochemical models.

中文翻译：

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在 R 中使用生物地球化学室实现完美的可塑性近似

由于所涉及过程的复杂性及其在预测未来行星状况方面的重要性，森林生态系统建模是科学领域的一项里程碑式挑战。虽然有许多开源森林生物地球化学模型，但很少有论文详细说明用于开发这些模型的软件开发方法。这使得许多森林生物地球化学模型变得庞大、不透明和/或难以使用，通常以编译语言实现以提高速度。在这里，我们提出了一个来自 SORTIE-PPA 类模型 PPA-SiBGC 的森林生物地球化学模型。我们的模型基于具有简单生物地球化学隔间的完美可塑性近似，并使用经验植被动态而不是详细的预测过程来驱动碳和氮通量的估计。这允许我们的模型与传统的森林清单数据一起使用，使其广泛适用且易于参数化。我们详细介绍了模型的概念设计以及用于统计计算的 R 语言软件实现。我们的目标是为生物地球化学建模社区提供一个有用的工具，以证明植被动力学在生物地球化学模型中的重要性。