Comparison of Population Level and Individual Level Endpoints To Evaluate Ecological Risk of Chemicals
Comparison of Population Level and Individual Level Endpoints To Evaluate Ecological Risk of Chemicals
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DOI：
10.1021/es3008968
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发表时间：
2012-05-15
影响因子：
11.4
通讯作者：
Stark, John D.
中科院分区：
文献类型：
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作者：
Hanson, Niklas;Stark, John D.
化学品的生态风险评估通常以个体的死亡率和繁殖率为基础。为了保护人群，对数据应用了固定的安全系数。然而，个体和群体之间的关系不能轻易地用预先确定的数字来描述。使用总体模型可以减少不确定性，从而减少错误评估的风险。然而，引入模型也引入了额外的复杂性。因此，希望保持模型尽可能简单。本研究的目的是确定简单的风险方程或矩阵模型是否可以改善ERA相比，传统的终点。为了检验这一点，复杂的模型，包括环境随机性和密度依赖性被用来模拟人口水平的风险的基础上五种化学品的剂量反应数据。风险，衡量的概率为伪灭绝和恢复时间，然后进行比较的风险估计的基础上个人水平的数据（急性和慢性），风险方程，和简单的矩阵模型。结果表明，与急性和慢性数据相比，简单矩阵模型分别将不确定性降低了88%和76%以上。此外，简单的风险方程大大降低了不确定性（与急性和慢性数据相比，分别为80%和61%）。
Ecological risk assessments (ERA) of chemicals are often based on mortality and reproduction of individuals., To protect populations, fixed safety factors are applied to the data. However, the relationship between individuals and populations cannot easily be described by predefined numbers. The use of population models may reduce uncertainty and, hence, the risk for erroneous assessments. However, introducing models also introduces additional complexity. Therefore, it is desirable to keep the models as simple as possible. The objective of the present study was to determine whether simple risk equations or matrix models can improve ERA compared to traditional endpoints. To examine this, complex models that included environmental stochasticity and density dependence were used to simulate population level risk based on dose-response data for five chemicals. The risk, measured as probability for pseudo extinction and recovery time, was then compared to risk estimates based on individual level data (acute and chronic), risk equations, and simple matrix models. The results showed that the simple matrix models reduced uncertainty by more than 88% and 76% compared to acute and chronic data, respectively. Also the simple risk equation reduced uncertainty considerably (80% and 61% compared to acute and chronic data, respectively).