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S.S. Qian

Publications and source records attributed to S.S. Qian.

2 recordsLinked to original sources

Multilevel regression models describing regional patterns of invertebrate and algal responses to urbanization across the USA

Multilevel hierarchical regression was used to examine regional patterns in the responses of benthic macroinvertebrates and algae to urbanization across 9 metropolitan areas of the conterminous USA. Linear regressions established that responses (intercepts and slopes) to urbanization of invertebrates and algae varied among metropolitan areas. Multilevel hierarchical regression models were able to explain these differences on the basis of region-scale predictors. Regional differences in the type of land cover (agriculture or forest) being converted to urban and climatic factors (precipitation and air temperature) accounted for the differences in the response of macroinvertebrates to urbanization based on ordination scores, total richness, Ephemeroptera, Plecoptera, Trichoptera richness, and average tolerance. Regional differences in climate and antecedent agriculture also accounted for differences in the responses of salt-tolerant diatoms, but differences in the responses of other diatom metrics (% eutraphenic, % sensitive, and % silt tolerant) were best explained by regional differences in soils (mean % clay soils). The effects of urbanization were most readily detected in regions where forest lands were being converted to urban land because agricultural development significantly degraded assemblages before urbanization and made detection of urban effects difficult. The effects of climatic factors (temperature, precipitation) on background conditions (biogeographic differences) and rates of response to urbanization were most apparent after accounting for the effects of agricultural development. The effects of climate and land cover on responses to urbanization provide strong evidence that monitoring, mitigation, and restoration efforts must be tailored for specific regions and that attainment goals (background conditions) may not be possible in regions with high levels of prior disturbance (e.g., agricultural development).

Journal of the North American Benthological Societ

Exploring factors controlling the variability of pesticide concentrations in the Willamette River Basin using tree-based models

We analyzed available concentration data of five commonly used herbicides and three pesticides collected from small streams in the Willamette River Basin in Oregon to identify factors that affect the variation of their concentrations in the area. The emphasis of this paper is the innovative use of classification and regression tree models for exploratory data analysis as well as analyzing data with a substantial amount of left-censored values. Among variables included in this analysis, land-use pattern in the watershed is the most important for all but one (simazine) of the eight pesticides studied, followed by geographic location, intensity of agriculture activities in the watershed (represented by nutrient concentrations in the stream), and the size of the watershed. The significant difference between urban sites and agriculture sites is the variability of stream concentrations. While all 16 nonurban watersheds have significantly higher variation than urban sites, the same is not necessarily true for the mean concentrations. Seasonal variation accounts for only a small fraction of the total variance in all eight pesticides.We analyzed available concentration data of five commonly used herbicides and three pesticides collected from small streams in the Willamette River Basin in Oregon to identify factors that affect the variation of their concentrations in the area. The emphasis of this paper is the innovative use of classification and regression tree models for exploratory data analysis as well as analyzing data with a substantial amount of left-censored values. Among variables included in this analysis, land-use pattern in the watershed is the most important for all but one (simazine) of the eight pesticides studied, followed by geographic location, intensity of agriculture activities in the watershed (represented by nutrient concentrations in the stream), and the size of the watershed. The significant difference between urban sites and agriculture sites is the variability of stream concentrations. While all 16 nonurban watersheds have significantly higher variation than urban sites, the same is not necessarily true for the mean concentrations. Seasonal variation accounts for only a small fraction of the total variance in all eight pesticides.

Environmental Science & Technology