We developed a bioaccumulation model from an extensive set of monitoring data to predict selenium (Se) concentrations in biota within a terrestrial system (Kesterson Reservoir, CA). The model uses water-extractable Se and total Se concentrations in soil to estimate the expected mean and ranges of Se concentrations in biota at Kesterson for future scenarios. Biological monitoring data collected at Kesterson from 1989 to 1994 were used to parameterize the initial model. The model was tested and updated with additional sample results from 1995 through 2001 biological monitoring and validated and calibrated using Se concentrations from sampling conducted in 2004 and 2006. Minor adjustments were made to the model based on each additional year’s results, and the model was used in 2014 to assess whether there were continuing threats to wildlife at Kesterson. The model predicts Se concentrations in small mammals, bird blood, and bird eggs in common species found at Kesterson. This model was used for the final assessment of Kesterson in 2014 and performed well, but there was variability in results, probably due to differences in individual diets and feeding ranges of animals. The model has been further refined since 2014, as we describe here. The model performs well for predicting central tendency and is conservative as the predicted upper limits of the biotic exposure distributions were mostly similar or higher than the measured. The trophic and tissue transfer factors and regression equations should be applicable to other Se-contaminated sites; adjusting weighting factors based on diet and range allows the model to be adapted and used at other sites.

我们根据大量监测数据开发了一个生物积累模型，以预测陆地系统（加利福尼亚州凯斯特森水库）内生物群中的硒 (Se) 浓度。该模型使用水可提取的硒和土壤中的总硒浓度来估计未来情景中凯斯特森生物群中硒浓度的预期平均值和范围。1989 年至 1994 年在 Kesterson 收集的生物监测数据用于参数化初始模型。使用 1995 年至 2001 年生物监测的额外样本结果对该模型进行了测试和更新，并使用 2004 年和 2006 年进行的采样中的硒浓度进行了验证和校准。根据每一年的结果对模型进行了微调，该模型于 2014 年用于评估 Kesterson 的野生动物是否持续受到威胁。该模型预测了在 Kesterson 发现的常见物种中小型哺乳动物、鸟类血液和鸟蛋中的硒浓度。该模型用于 2014 年对 Kesterson 的最终评估，表现良好，但结果存在差异，可能是由于个体饮食和动物饲养范围的差异。正如我们在这里所描述的，该模型自 2014 年以来得到了进一步完善。该模型在预测集中趋势方面表现良好并且是保守的，因为生物暴露分布的预测上限大多类似于或高于测量值。营养和组织转移因子和回归方程应适用于其他硒污染部位；