DOI: 10.1016/j.watres.2018.06.058
Scopus记录号: 2-s2.0-85050124665
论文题名: The influence of land cover on the sensitivity of streams to metal pollution
作者: Tomczyk N.J. ; Parr T.B. ; Wenger S.J. ; Capps K.A.
刊名: Water Research
ISSN: 431354
出版年: 2018
卷: 144 起始页码: 55
结束页码: 63
语种: 英语
英文关键词: Biotic ligand model
; Copper
; Land cover
; Land use
; Landscape
; Landscape ecotoxicology
; Nickel
; Watershed
; Zinc
Scopus关键词: Copper
; Land use
; Ligands
; Metals
; Nickel
; Organic carbon
; Watersheds
; Wetlands
; Zinc
; Anthropogenic stressors
; Biotic Ligand Model
; Dissolved organic carbon
; Eco-toxicology
; Land cover
; Landscape
; Mean annual precipitation
; Mean annual temperatures
; River pollution
; copper
; dissolved organic matter
; nickel
; organic carbon
; zinc
; anthropogenic effect
; concentration (composition)
; detection method
; dissolved organic carbon
; ecotoxicology
; heavy metal
; land cover
; land use
; landscape change
; nickel
; numerical model
; physicochemical property
; sensitivity analysis
; stream
; water chemistry
; water pollution
; watershed
; wetland
; zinc
; Article
; biotic ligand model
; chemical parameters
; crop
; data base
; ecotoxicology
; forest
; land use
; landscape
; precipitation
; predictor variable
; priority journal
; risk
; stream (river)
; temperature
; United States
; urban area
; water pollution
; watershed
; wetland
; United States
英文摘要: Identifying freshwater systems that are at risk from anthropogenic stressors is a pressing management problem. In particular, the detection of metal pollution is often constrained by data availability and resources. To address this challenge and develop a tool to identify susceptible systems, we tested whether land cover could be predictive of stream sensitivity to metal pollution, as determined by the biotic ligand model (BLM). We used water chemistry data from the conterminous United States to estimate metal sensitivity in streams using two BLMs (i.e., HydoQual, Bio-Met). Subsequently, we combined the sensitivity estimates with land cover and physiochemical data from the GAGES-II database to build predictive models of sensitivity to metals in streams. When combined, our predictor variables (e.g., land cover, mean annual temperature, mean annual precipitation) generally explained about half of the variation in our dataset. In each model, the percent of wetlands in a watershed was strongly correlated with reduced sensitivity to metals, likely due to increased concentrations of dissolved organic carbon associated with wetlands. To validate the utility of the models, we used them to predict metal sensitivity in sites where metal concentrations had been collected, but where the full suite of BLM parameters were unknown. We were able to classify several hundred sites which are likely at risk to metal pollution. Our work highlights the value in considering metal toxicity at the landscape-scale and describes a new approach to estimate metal sensitivity when site-specific chemical parameters are unknown. © 2018 Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/112529
Appears in Collections: 气候减缓与适应
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作者单位: Odum School of Ecology, University of Georgia, Athens, GA, United States; Savannah River Ecology Lab, University of Georgia, Aiken, SC, United States; Department of Biology, University of Oklahoma, Norman, OK, United States
Recommended Citation:
Tomczyk N.J.,Parr T.B.,Wenger S.J.,et al. The influence of land cover on the sensitivity of streams to metal pollution[J]. Water Research,2018-01-01,144