CITRATE 1.0: Phytoplankton continuous trait-distribution model with one-dimensional physical transport applied to the North Pacific
CITRATE 1.0: Phytoplankton continuous trait-distribution model with one-dimensional physical transport applied to the North Pacific
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DOI：
10.5194/gmd-11-467-2018
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发表时间：
2018-02-01
影响因子：
5.1
通讯作者：
Smith, Sherwood Lan
中科院分区：
文献类型：
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作者：
Chen, Bingzhang;Smith, Sherwood Lan
多样性在生态系统功能中发挥着关键作用，但为了更好地了解这些作用并重现海洋中一致观察到的多样性模式，对浮游植物多样性进行建模仍然具有挑战性。与解决不同物种或功能组的典型方法相反，我们提出了一个连续TRAiT-based浮游植物模型（CITRATE），专注于宏观系统属性，如总生物量，平均性状值和性状方差。这个浮游植物组件是嵌入在一个氮-浮游植物-浮游动物tonderitus-铁模型，本身是一个简化的一维海洋模型耦合。大小被用作浮游植物的主要特征。柠檬酸盐还结合了“性状扩散”，以维持多样性和生理适应的简单表示，即，灵活的叶绿素碳和氮碳比。我们在北太平洋两个对比鲜明的观测站实施了CITRATE，那里有几年的观测数据。该模式是由物理强迫，包括垂直涡动扩散进口的三维一般海洋环流模式（GCMs）。一个共同的一组模型参数的两个站进行了优化，使用延迟拒绝自适应大都会-哈希蒙特卡罗（DRAM）算法。该模型忠实地再现了大多数观察到的模式，并给出了强大的预测浮游植物的平均大小和大小多样性。CITRATE适用于GCM中的应用，并构成了一个原型，可以在此基础上开发更复杂的基于连续特质的模型。
Diversity plays critical roles in ecosystem functioning, but it remains challenging to model phytoplankton diversity in order to better understand those roles and reproduce consistently observed diversity patterns in the ocean. In contrast to the typical approach of resolving distinct species or functional groups, we present a ContInuous TRAiT-basEd phytoplankton model (CITRATE) that focuses on macroscopic system properties such as total biomass, mean trait values, and trait variance. This phytoplankton component is embedded within a nitrogen-phytoplankton-zooplanktondetritus- iron model that itself is coupled with a simplified one-dimensional ocean model. Size is used as the master trait for phytoplankton. CITRATE also incorporates "trait diffusion" for sustaining diversity and simple representations of physiological acclimation, i.e., flexible chlorophyllto- carbon and nitrogen-to-carbon ratios. We have implemented CITRATE at two contrasting stations in the North Pacific where several years of observational data are available. The model is driven by physical forcing including vertical eddy diffusivity imported from three-dimensional general ocean circulation models (GCMs). One common set of model parameters for the two stations is optimized using the Delayed-Rejection Adaptive Metropolis-Hasting Monte Carlo (DRAM) algorithm. The model faithfully reproduces most of the observed patterns and gives robust predictions on phytoplankton mean size and size diversity. CITRATE is suitable for applications in GCMs and constitutes a prototype upon which more sophisticated continuous trait-based models can be developed.