Shanley James B, Kamman Neil C, Clair Thomas A, Chalmers Ann
U.S. Geological Survey, P.O. Box 628, Montpelier, VT 05602, USA.
Ecotoxicology. 2005 Mar;14(1-2):125-34. doi: 10.1007/s10646-004-6264-z.
The physical factors controlling total mercury (HgT) and methylmercury (MeHg) concentrations in lakes and streams of northeastern USA were assessed in a regional data set containing 693 HgT and 385 corresponding MeHg concentrations in surface waters. Multiple regression models using watershed characteristics and climatic variables explained 38% or less of the variance in HgT and MeHg. Land cover percentages and soil permeability generally provided modest predictive power. Percent wetlands alone explained 19% of the variance in MeHg in streams at low-flow, and it was the only significant (p < 0.02) predictor for MeHg in lakes, albeit explaining only 7% of the variance. When stream discharge was added as a variable it became the dominant predictor for HgT in streams, improving the model r2 from 0.19 to 0.38. Stream discharge improved the MeHg model more modestly, from r2 of 0.25 to 0.33. Methylation efficiency (MeHg/HgT) was modeled well (r2 of 0.78) when a seasonal term was incorporated (sine wave with annual period). Physical models explained 18% of the variance in fish Hg concentrations in 134 lakes and 55% in 20 reservoirs. Our results highlight the important role of seasonality and short-term hydrologic changes to the delivery of Hg to water bodies.
在美国东北部一个包含693个总汞(HgT)和385个相应地表水中甲基汞(MeHg)浓度的区域数据集中,评估了控制湖泊和溪流中总汞和甲基汞浓度的物理因素。使用流域特征和气候变量的多元回归模型解释了HgT和MeHg中38%或更低的方差。土地覆盖百分比和土壤渗透率通常具有一定的预测能力。仅湿地百分比就解释了低流量溪流中MeHg方差的19%,并且它是湖泊中MeHg唯一显著(p < 0.02)的预测因子,尽管仅解释了7%的方差。当将溪流流量作为变量添加时,它成为溪流中HgT的主要预测因子,将模型r2从0.19提高到0.38。溪流流量对MeHg模型的改善较为适度,从r2为0.25提高到0.33。当纳入季节性项(年周期正弦波)时,甲基化效率(MeHg/HgT)的建模效果良好(r2为0.78)。物理模型解释了134个湖泊中鱼类汞浓度方差的18%以及20个水库中55%的方差。我们的结果突出了季节性和短期水文变化对汞输送到水体的重要作用。