Paul John F, Comeleo Randy L, Copeland Jane
USEPA, Narragansett, RI 02882, USA.
J Environ Qual. 2002 May-Jun;31(3):836-45. doi: 10.2134/jeq2002.8360.
In a previously published study, quantitative relationships were developed between landscape metrics and sediment contamination for 25 small estuarine systems within Chesapeake Bay. These analyses have been extended to include 75 small estuarine systems across the mid-Atlantic and southern New England regions of the USA. Because of the different characteristics and dynamics of the estuaries across these regions, adjustment for differing hydrology, sediment characteristics, and sediment origins were included in the analysis. Multiple linear regression with stepwise selection was used to develop statistical models for sediment metals, organics, and total polycyclic aromatic hydrocarbons (PAHs). The landscape metrics important for explaining the variation in sediment metals levels (R2 = 0.72) were the percent area of nonforested wetlands (negative contribution), percent area of urban land, and point source effluent volume and metals input (positive contributions). The metrics important for sediment organics levels (R2 = 0.5) and total PAHs (R2 = 0.46) were percent area of urban land (positive contribution) and percent area of nonforested wetlands (negative contribution). These models included silt-clay content (metals) or total organic C (organics, total PAHs) of sediments and grouping by estuarine hydrology, suggesting the importance of sediment characteristics and hydrology in mitigating the influence of the landscape metrics on sediment contamination levels. The overall results from this study are indicative of how statistical models can be developed relating landscape metrics to estuarine sediment contamination for distributions of land cover and point source discharges.
在之前发表的一项研究中，针对切萨皮克湾内的25个小型河口系统，建立了景观指标与沉积物污染之间的定量关系。这些分析已扩展至包括美国中大西洋地区和新英格兰南部地区的75个小型河口系统。由于这些地区河口的特征和动态各异，分析中纳入了针对不同水文、沉积物特征和沉积物来源的调整。采用逐步选择的多元线性回归来建立沉积物金属、有机物和总多环芳烃（PAHs）的统计模型。对于解释沉积物金属含量变化（R2 = 0.72）重要的景观指标是非森林湿地面积百分比（负贡献）、城市土地面积百分比、点源污水排放量和金属输入量（正贡献）。对于沉积物有机物含量（R2 = 0.5）和总PAHs（R2 = 0.46）重要的指标是城市土地面积百分比（正贡献）和非森林湿地面积百分比（负贡献）。这些模型包括沉积物的粉砂 - 粘土含量（金属）或总有机碳（有机物、总PAHs），并按河口水文进行分组，这表明沉积物特征和水文在减轻景观指标对沉积物污染水平影响方面的重要性。这项研究的总体结果表明了如何针对土地覆盖和点源排放分布，建立将景观指标与河口沉积物污染相关联的统计模型。
