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首页> 外文期刊>Ecological Modelling >Predicting aquaculture-derived benthic organic enrichment: Model validation
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Predicting aquaculture-derived benthic organic enrichment: Model validation

机译：预测水产养殖底栖生物富集：模型验证

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A sediment trap validation study was conducted near the commercial sea bass and sea bream fish farm in order to assess the predictive capability of a particle tracking deposition model. The validation procedure consisted of two distinct phases. First, the deposition of particulate waste (i.e. fecal pellets and excess feed) was measured near a single net pen containing 19 tons of sea bass. Afterwards, the model quality was determined by statistical comparison of predicted and observed values. Goodness of fit analysis indicates that the model successfully accounts for more than 75% of variance in the observed deposition. At 5% significance level, predictions do not underestimate or overestimate observations and there is no bias. Mean absolute relative error of +/- 48.9% compares favorably to other published deposition models. Obtained results affirm the reliability of particle tracking techniques in modeling the aquaculture-derived benthic organic enrichment.
机译：在商业鲈鱼和鲷鱼养殖场附近进行了沉积物捕集器验证研究，以评估颗粒追踪沉积模型的预测能力。验证程序包括两个不同的阶段。首先，在包含19吨鲈鱼的单个网围附近测量颗粒废物（即粪便和过量饲料）的沉积。之后，通过对预测值和观察值进行统计比较来确定模型质量。拟合优度分析表明，该模型成功解决了观测沉积物中75％以上的方差。在显着性水平为5％的情况下，预测不会低估或高估观察值，并且没有偏差。平均绝对相对误差为+/- 48.9％，与其他已发表的沉积模型相比更为有利。获得的结果证实了颗粒追踪技术在水产养殖底栖生物富集建模中的可靠性。

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