U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment, 26 Martin Luther King Dr. W, Cincinnati, OH 45268, USA.
Tetra Tech, 10711 Red Run Blvd., Suite 105, Owings Mills, MD 21117, USA.
Sci Total Environ. 2018 Aug 15;633:1629-1636. doi: 10.1016/j.scitotenv.2018.02.044. Epub 2018 Feb 22.
Field-collected measures of dissolved salts and occurrences of aquatic invertebrates have been used to develop protective levels. However, sufficiently large field data sets of exposures and biota are often not available. Therefore, a model was developed to predict the exposure extirpating 5% of benthic invertebrate genera using only measures of specific conductivity (SC) as the independent variable. The model is based on 3 assumptions: (1) a genus will rarely occur where the background exceeds its upper physiological limit; (2) the lowest possible tolerance limit of a genus in a region is defined by the natural background; and (3) as a result, there will be a regular association between natural background SC and the SC at which salt-intolerant genera are present. Three steps were used to develop the model. First, background SC was characterized as the 25th centile of sampled sites for each of 24 areas in the United States with streams dominated by bicarbonate and sulfate ions. Second, the extirpation concentration (XC), an estimate of the upper tolerance limit with respect to SC, was calculated for genera in 24 data sets. Next, the lower 5th centile of each set of XC values (XCD) was identified for the most salt-intolerant members in each data set. Finally, the relationship between the 24 background SC and the 24 XCD values was empirically modeled to develop a background-to-criterion model. The least squares regression of XCD values on log background SC (log Y = 0.658logX + 1.071) yields a strong linear relationship (r = 0.93). The regression model makes it possible to use SC background to predict the SC likely to extirpate the most salt-intolerant genera in an area. The results also suggest that species distribute along natural background gradients of SC and that this relationship can be used to develop criteria for ionic concentration.
已采集现场的溶解盐和水生无脊椎动物的出现数据来制定保护水平。然而，通常无法获得足够大的暴露和生物区系的现场数据集。因此，开发了一种模型，该模型仅使用特定电导率 (SC) 作为自变量来预测暴露会消灭 5%的底栖无脊椎动物属的情况。该模型基于以下 3 个假设：(1) 一个属很少会在背景超过其上限生理极限的地方出现；(2) 一个属在一个区域内的最低可能耐受极限由自然背景定义；(3) 因此，自然背景 SC 与不耐盐属存在的 SC 之间将存在有规律的关联。该模型的开发使用了三个步骤。首先，将背景 SC 描述为美国 24 个地区中受碳酸氢盐和硫酸盐离子主导的溪流中每个采样点的第 25 百分位数。其次，计算了 24 个数据集的属的灭绝浓度 (XC)，这是对 SC 的上限耐受极限的估计。接下来，确定了每个数据集的最不耐盐属的 XC 值的下 5 个百分位数 (XCD)。最后，通过经验对 24 个背景 SC 和 24 个 XCD 值之间的关系进行了建模，以开发背景到标准模型。XCD 值对背景 SC 的最小二乘回归 (log Y = 0.658logX + 1.071) 得出了很强的线性关系 (r = 0.93)。回归模型使得可以使用 SC 背景来预测可能消灭一个地区最不耐盐属的 SC。结果还表明，物种沿着 SC 的自然背景梯度分布，并且可以利用这种关系来制定离子浓度标准。
