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基于回归模型的淡水鱼铯浓度比预测模型的建立与评估。

Development and evaluation of a regression-based model to predict cesium concentration ratios for freshwater fish.

机构信息

Department of Environmental and Radiological Health Sciences, Colorado State University, 305 W. Magnolia PMB 231, Fort Collins, CO 80521, USA.

Atomic Energy of Canada Limited (AECL), Environmental Technologies Branch, Chalk River Laboratories, Chalk River Ontario K0J 1J0, Canada.

出版信息

J Environ Radioact. 2014 Aug;134:89-98. doi: 10.1016/j.jenvrad.2014.03.003. Epub 2014 Apr 1.

DOI:10.1016/j.jenvrad.2014.03.003
PMID:24699402
Abstract

Data from published studies and World Wide Web sources were combined to produce and test a regression model to predict Cs concentration ratios for freshwater fish species. The accuracies of predicted concentration ratios, which were computed using 1) species trophic levels obtained from random resampling of known food items and 2) K concentrations in the water for 207 fish from 44 species and 43 locations, were tested against independent observations of ratios for 57 fish from 17 species from 25 locations. Accuracy was assessed as the percent of observed to predicted ratios within factors of 2 or 3. Conservatism, expressed as the lack of under prediction, was assessed as the percent of observed to predicted ratios that were less than 2 or less than 3. The model's median observed to predicted ratio was 1.26, which was not significantly different from 1, and 50% of the ratios were between 0.73 and 1.85. The percentages of ratios within factors of 2 or 3 were 67 and 82%, respectively. The percentages of ratios that were <2 or <3 were 79 and 88%, respectively. An example for Perca fluviatilis demonstrated that increased prediction accuracy could be obtained when more detailed knowledge of diet was available to estimate trophic level.

摘要

综合已发表的研究数据和万维网资源,建立并检验了一个回归模型,用于预测淡水鱼类的 Cs 浓度比。使用以下两种方法计算预测的浓度比的准确度:1)随机抽取已知食物物种的营养级来获得物种的营养级;2)利用 43 个地点 44 个物种的 207 条鱼的水中 K 浓度。对来自 25 个地点 17 个物种的 57 条鱼的独立观察比值进行了测试。准确度评估为观察比值与预测比值的比值在 2 或 3 倍以内的百分比。保守性(表现为预测值低于 2 或低于 3 的比例)评估为观察比值与预测比值小于 2 或小于 3 的比例。模型的中位数观察到的预测比值为 1.26,与 1 无显著差异,50%的比值在 0.73 至 1.85 之间。比值在 2 或 3 倍以内的比例分别为 67%和 82%。比值小于 2 或小于 3 的比例分别为 79%和 88%。以 Perca fluviatilis 为例,当有更详细的饮食知识可用于估计营养级时,预测准确度可以提高。

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