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Probabilistic analysis of phytoplankton biomass at the Frisian Inlet (NL)

机译：弗里斯兰湾（NL）浮游植物生物量的概率分析

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The BLOOM II model is applied in this study to interrogate the variation of phytoplankton biomass (in terms of chlorophyll a) at the Frisian Inlet (NL), located in the north of the Netherlands. The validation results of the model show that more than 90% of the comparisons between model results and observations have a good agreement, while only 3.1% are classified as poor. Chlorophyll a is significantly correlated with the ecological indicators of Si and NH4 by observational analysis. The modelled chlorophyll a is fitted well by a normal distribution function (mu = 3.95 mg m(-3), sigma = 2.96 mg m(-3)). Relationships between the modelled ecological indicators are investigated. Secchi depth as another important indicator is closely linked with chlorophyll a, PAR and K-d. Moreover, particular attention is paid to the phytoplankton biomass in response to nutrient availability. The decrease rate of chlorophyll a is from 16.8% to 19.2% for N-reduction, 17.4%-21.3% for P-reduction and 21.7%-28.0% for both N- and P-reduction. In the presence of uncertainty, the improved prediction of chlorophyll a is derived by Bayesian Markov Chain Monte Carlo (BMCMC) in this study. The improved prediction of chlorophyll a concentrations vary from 0.147 to 1534 mg m(-3) within the 95% confidence interval. This study emphasises the use of an ecological model to predict the variation of phytoplankton biomass, and improves the prediction with the integration of uncertainty analysis. (C) 2015 Elsevier Ltd. All rights reserved.
机译：在这项研究中，BLOOM II模型被用于询问位于荷兰北部弗里斯兰湾（NL）的浮游植物生物量（以叶绿素a的形式）的变化。模型的验证结果表明，模型结果与观测值之间的比较有90％以上具有良好的一致性，而只有3.1％的分类为差。通过观察分析，叶绿素a与Si和NH4的生态指标显着相关。通过正态分布函数（μ= 3.95 mg m（-3），sigma = 2.96 mg m（-3））很好地拟合了模型化的叶绿素a。研究了建模的生态指标之间的关系。 Secchi深度作为另一个重要指标与叶绿素a，PAR和K-d密切相关。此外，应特别注意响应养分利用率的浮游植物生物量。氮素还原的叶绿素a降低率从16.8％降至19.2％，磷还原剂的降低率为17.4％-21.3％，氮素和磷还原剂的降低率分别为21.7％-28.0％。在存在不确定性的情况下，本研究中的贝叶斯马尔可夫链蒙特卡洛（BMCMC）得出了叶绿素a的改进预测。在95％置信区间内，叶绿素a浓度的改进预测值从0.147到1534 mg m（-3）不等。这项研究强调使用生态模型来预测浮游植物生物量的变化，并通过不确定性分析的整合来改进预测。 （C）2015 Elsevier Ltd.保留所有权利。

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