Department of Forestry and Environmental Conservation, 261 Lehotsky Hall, Clemson University, Clemson SC 29634, USA.
Department of Forestry and Environmental Conservation, 261 Lehotsky Hall, Clemson University, Clemson SC 29634, USA.
Ecotoxicol Environ Saf. 2017 Nov;145:591-596. doi: 10.1016/j.ecoenv.2017.08.010. Epub 2017 Aug 9.
Along with mechanistic models, predictions of exposure-response relationships for copper are often derived from laboratory toxicity experiments with standardized experimental exposures and conditions. For predictions of copper toxicity to algae, cell density is a critical factor often overlooked. For pulse exposures of copper-based algaecides in aquatic systems, cell density can significantly influence copper sorbed by the algal population, and consequent responses. A cyanobacterium, Microcystis aeruginosa, was exposed to a copper-based algaecide over a range of cell densities to model the density-dependence of exposures, and effects on microcystin-LR (MC-LR) release. Copper exposure concentrations were arrayed to result in a gradient of MC-LR release, and masses of copper sorbed to algal populations were measured following exposures. While copper exposure concentrations eliciting comparable MC-LR release ranged an order of magnitude (24-h EC50s 0.03-0.3mg Cu/L) among cell densities of 10 through 10 cells/mL, copper doses (mg Cu/mg algae) were similar (24-h EC50s 0.005-0.006mg Cu/mg algae). Comparisons of MC-LR release as a function of copper exposure concentrations and doses provided a metric of the density dependence of algal responses in the context of copper-based algaecide applications. Combined with estimates of other site-specific factors (e.g. water characteristics) and fate processes (e.g. dilution and dispersion, sorption to organic matter and sediments), measuring exposure-response relationships for specific cell densities can refine predictions for in situ exposures and algal responses. These measurements can in turn decrease the likelihood of amending unnecessary copper concentrations to aquatic systems, and minimize risks for non-target aquatic organisms.
除了机械模型外,通常还可以通过具有标准化实验暴露和条件的实验室毒性实验来预测铜的暴露-反应关系。对于藻类的铜毒性预测,细胞密度是一个经常被忽视的关键因素。对于水生系统中基于铜的杀藻剂的脉冲暴露,细胞密度会显著影响藻类种群吸附的铜量,以及随之而来的反应。为了模拟暴露的密度依赖性以及对微囊藻毒素-LR(MC-LR)释放的影响,将一种蓝藻,铜绿微囊藻,暴露于一系列细胞密度的铜基杀藻剂中。将铜暴露浓度排列成微囊藻毒素释放的梯度,并在暴露后测量藻类群体吸附的铜量。虽然在细胞密度为 10 到 10 个细胞/mL 之间,引起可比 MC-LR 释放的铜暴露浓度范围为一个数量级(24-h EC50s 为 0.03-0.3mg Cu/L),但铜剂量(mg Cu/mg 藻类)相似(24-h EC50s 为 0.005-0.006mg Cu/mg 藻类)。将 MC-LR 释放作为铜暴露浓度和剂量的函数进行比较,提供了在基于铜的杀藻剂应用背景下藻类反应的密度依赖性的度量。将其与其他特定地点因素(例如水质)和命运过程(例如稀释和分散、与有机物和沉积物的吸附)的估计相结合,测量特定细胞密度的暴露-反应关系可以改善对原位暴露和藻类反应的预测。这些测量反过来可以减少向水生系统中添加不必要的铜浓度的可能性,并最大程度地降低对非目标水生生物的风险。