首页> 外文期刊>Environmental Science & Technology >Application of Biotic Ligand and Toxic Unit Modeling Approaches to Predict Improvements in Zooplankton Species Richness in Smelter- Damaged Lakes near Sudbury, Ontario
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Application of Biotic Ligand and Toxic Unit Modeling Approaches to Predict Improvements in Zooplankton Species Richness in Smelter- Damaged Lakes near Sudbury, Ontario

机译:应用生物配体和有毒单位建模方法预测安大略省萨德伯里附近冶炼厂受损的湖泊浮游动物物种丰富度的提高

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摘要

Using a 30-year record of biological and water chemistry data collected from seven lakes near smelters in Sudbury (Ontario, Canada) we examined the link between reductions of Cu, Ni, and Zn concentrations and zooplankton species richness. The toxicity of the metal mixtures was assessed using an additive Toxic Unit (TU) approach. Four TU models were developed based on total metal concentrations (TM-TU); free ion concentrations (FI-TU); acute LC50s calculated from the Biotic Ligand Model (BLM-TU); and chronic LC50s (acute LC50s adjusted by metal-specific acute-to-chronic ratios, cBLM-TU). All models significantly correlated reductions in metal concentrations to increased zooplankton species richness over time (p < 0.01) with a rank based on r~2 values of cBLM-TU > BLM-TU = FI-TU > TM-TU. Lake-wise comparisons within each model showed that the BLM-TU and cBLM-TU models provided the best description of recovery across all seven lakes. These two models were used to calculate thresholds for chemical and biological recovery using data from reference lakes in the same region. A threshold value of TU = 1 derived from the cBLM-TU provided the most accurate description of recovery. Overall, BLM-based TU models that integrate site-specific water chemistry-derived estimates of toxicity offer a useful predictor of biological recovery.
机译:利用从萨德伯里(加拿大安大略省)冶炼厂附近七个湖收集的30年生物和水化学数据记录,我们研究了铜,镍和锌浓度降低与浮游动物物种丰富度之间的联系。使用添加的毒性单位(TU)方法评估了金属混合物的毒性。根据总金属浓度(TM-TU)开发了四个TU模型;自由离子浓度(FI-TU);根据生物配体模型(BLM-TU)计算的急性LC50;和慢性LC50(通过金属特异性急性与慢性比率cBLM-TU调整的急性LC50)。所有模型均基于cBLM-TU> BLM-TU = FI-TU> TM-TU的r〜2值,将金属浓度的降低与浮游动物物种丰富度随时间的增加显着相关(p <0.01)。每个模型中按湖计算的比较表明,BLM-TU和cBLM-TU模型提供了对所有七个湖的恢复的最佳描述。这两个模型用于使用来自同一地区参考湖的数据来计算化学和生物恢复的阈值。从cBLM-TU得出的TU = 1阈值提供了最准确的恢复描述。总体而言,基于BLM的TU模型集成了特定于地点的水化学衍生的毒性估计值,可提供有用的生物恢复预测指标。

著录项

  • 来源
    《Environmental Science & Technology》 |2012年第3期|p.1641-1649|共9页
  • 作者单位

    Department of Biology, Wilfrid Laurier University, 75 University Avenue W, Waterloo, Ontario N2L 3C5, Canada,Department of Zoology, Natural History Museum, Cromwell Road, London SW7 5BD;

    Cooperative Freshwater Ecology Unit, Laurentian University, Sudbury, Ontario P3E 2C6, Canada;

    Department of Biology, York University, Toronto, Ontario M3J 1P3, Canada;

    Ontario Ministry of the Environment, Toronto, Ontario M4 V 1M2, Canada;

    Department of Biology, McMaster University, 1280 Main Street, Hamilton, Ontario, L8S 4K1, Canada;

    Department of Biology, Wilfrid Laurier University, 75 University Avenue W, Waterloo, Ontario N2L 3C5, Canada;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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