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Corrigendum
Environmental Toxicology and Chemistry ( IF 4.1 ) Pub Date : 2024-03-13 , DOI: 10.1002/etc.5837


Brix, K. V., Tear, L., Santore, R. C., Croteau, K., & DeForest, D. K. (2021). Comparative performance of multiple linear regression and biotic ligand models for estimating the bioavailability of copper in freshwater. Environmental Toxicology and Chemistry, 40, 1649–1661. https://doi.org/10.1002/etc.5012

The authors of the above noted paper hereby submit the following correction.

In this corrigendum, we provide one correction and one addition to the manuscript. First, it was noted that after page proofs were reviewed, an inadvertent column shift of some information presented in Table 2 occurred leading to errors in the table. A corrected version of Table 2 is provided. Second, the authors have been contacted by multiple readers of the manuscript that point out we failed to provide the multiple linear regression (MLR)-based water quality criteria (WQC) equations used to derive the plots in Figure 9. These equations are provided as follows:
Acute WQC : exp ( 0.700 * ln ( DOC ) + 0.579 * ln ( Hard ) + 0.778 * pH 6.738 ) $\mathrm{Acute\; WQC}:\exp (0.700* \mathrm{ln}(\text{DOC})+0.579* \mathrm{ln}(\text{Hard})\unicode{x02007}+0.778* \text{pH}-6.738)$
Chronic WQC : exp ( 0.855 * ln ( DOC ) + 0.221 * ln ( Hard ) + 0.216 * pH 1.402 ) $\mathrm{Chronic\; WQC}:\text{exp}(0.855* \mathrm{ln}(\text{DOC})+0.221* \mathrm{ln}(\text{Hard})\unicode{x02007}+0.216* \text{pH}-1.402)$
where, DOC = dissolved organic carbon (mg L−1) and Hard = water hardness (mg L−1 as CaCO3).
Table 2. Summary of species-specific and pooled Cu multiple linear regression models
Slope
Species Intercept ln(DOC) ln(Hard) pH pH2 ln(DOC) x pH ln(Hard) x pH n Adj. R2 Pred. R2
Acute
C. dubia −5.427 0.639 0.133 0.985 113 0.71 0.69
D. magna −4.991 0.746 0.544 0.774 408 0.78 0.78
D. obtusa −2.063 0.839 0.282 0.551 50 0.82 0.79
D. pulex 0.587 0.763 0.622 33 0.76 0.71
O. mykiss 0.481 0.511 0.758 89 0.58 0.55
P. promelas −6.654 0.670 0.986 0.962 206 0.77 0.76
Pooled Model 0.700 0.579 0.778 899
C. dubia −5.890 113 0.64
D. magna −5.148 408 0.78
D. obtusa −4.942 50 0.64
D. pulex −5.373 33 0.69
O. mykiss −4.650 89 0.48
P. promelas −3.605 206 0.70
Chronic
D. magna 0.372 0.851 0.198 0.175 74 0.87 0.86
O. mykiss −0.064 0.882 0.284 0.284 17 0.64 0.53
Pooled Model 0.855 0.221 0.215 91
D. magna −0.056 74 0.87
O. mykiss 0.685 17 0.62
  • DOC = dissolved organic carbon; Hard = water hardness.


中文翻译:

勘误表

Brix, KV、Tear, L.、Santore, RC、Croteau, K. 和 DeForest, DK (2021)。多元线性回归和生物配体模型用于估计淡水中铜的生物利用度的比较性能。环境毒理学和化学, 40,1649–1661。 https://doi.org/10.1002/etc.5012

上述论文的作者特此提出以下更正。

在本勘误中,我们对原稿进行了一项更正和一项补充。首先,有人指出,在审查校样后,表 2 中某些信息的列发生了无意的移位,导致了表格中的错误。提供了表 2 的更正版本。其次,手稿的多个读者联系了作者,指出我们未能提供用于推导图 9 中的图的基于多元线性回归 (MLR) 的水质标准 (WQC) 方程。这些方程提供为如下:
急性WQC 经验值 0.700 * 文档 + 0.579 * 难的 + 0.778 * 酸碱度 - 6.738 $\mathrm{急性\; WQC}:\exp (0.700* \mathrm{ln}(\text{DOC})+0.579* \mathrm{ln}(\text{Hard})\unicode{x02007}+0.778* \text{pH}-6.738 )$
慢性WQC 经验值 0.855 * 文档 + 0.221 * 难的 + 0.216 * 酸碱度 - 1.402 $\mathrm{慢性的\; WQC}:\text{exp}(0.855* \mathrm{ln}(\text{DOC})+0.221* \mathrm{ln}(\text{Hard})\unicode{x02007}+0.216* \text{pH }-1.402)$
其中,DOC = 溶解的有机碳 (mg L -1 ),Hard = 水硬度(mg L -1以 CaCO 3计)。
表 2.物种特异性和汇总铜多元线性回归模型总结
物种 截距 ln(DOC) ln(硬) 酸碱度 酸碱度2 ln(DOC) x pH ln(硬)x pH n 调整。 R 2 普雷德。 R 2
急性
疑似 C. dubia −5.427 0.639 0.133 0.985 113 0.71 0.69
麦格纳 −4.991 0.746 0.544 0.774 第408章 0.78 0.78
钝齿蠹 −2.063 0.839 0.282 0.551 50 0.82 0.79
D. pulex 0.587 0.763 0.622 33 0.76 0.71
O. 米基斯 0.481 0.511 0.758 89 0.58 0.55
普罗米拉斯 −6.654 0.670 0.986 0.962 206 0.77 0.76
混合模型 0.700 0.579 0.778 899
疑似 C. dubia −5.890 113 0.64
麦格纳 −5.148 第408章 0.78
钝齿蠹 −4.942 50 0.64
D. pulex −5.373 33 0.69
O. 米基斯 −4.650 89 0.48
普罗米拉斯 −3.605 206 0.70
慢性的
麦格纳 0.372 0.851 0.198 0.175 74 0.87 0.86
O. 米基斯 −0.064 0.882 0.284 0.284 17 号 0.64 0.53
混合模型 0.855 0.221 0.215 91
麦格纳 −0.056 74 0.87
O. 米基斯 0.685 17 号 0.62
  • DOC = 溶解有机碳;硬=水的硬度。
更新日期:2024-03-13
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