The empirical relationship between total phosphorus and chlorophyll has guided lake management decisions for decades, but imprecision in this relationship in individual lakes limits the utility of these models. Many environmental factors that potentially affect the total phosphorus-chlorophyll relationship have been studied, but here we hypothesize that imprecision can be reduced by considering differences in the proportions of phosphorus bound to three different "compartments" in the water column: phosphorus bound in phytoplankton, phosphorus bound to suspended sediment that is not associated with phytoplankton, and dissolved phosphorus. We specify a hierarchical Bayesian network model that estimates phosphorus associated with each compartment using field measurements of chlorophyll, total suspended solids, and total phosphorus collected from reservoirs in Missouri, USA. We then demonstrate that accounting for these different compartments yields accurate predictions of total phosphorus in individual lakes. Results from this model also yield insights into the mechanisms by which lake morphometric and watershed characteristics affect observed relationships between total phosphorus and chlorophyll.

中文翻译：

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重新思考湖泊中磷-叶绿素的关系

几十年来，总磷和叶绿素之间的经验关系一直在指导湖泊管理决策，但这种关系在个别湖泊中的不精确性限制了这些模型的实用性。已经研究了许多可能影响总磷 - 叶绿素关系的环境因素，但在这里我们假设可以通过考虑与水体中三个不同“隔间”结合的磷比例的差异来减少不精确性：浮游植物中的磷，与浮游植物无关的悬浮沉积物中的磷和溶解的磷。我们指定了一个分层贝叶斯网络模型，该模型使用叶绿素、总悬浮固体、和从美国密苏里州的水库收集的总磷。然后我们证明，考虑到这些不同的隔间，可以准确预测单个湖泊中的总磷。该模型的结果还有助于深入了解湖泊形态测量和流域特征影响观察到的总磷和叶绿素之间关系的机制。