Football Game Program 3 1965

Football Game Program 3 196

Interaction of riparian wetlands and average March runoff (mm) on RichTOL for N.E Highlands BRT model.

<p>Boosted regression tree partial dependency plot shows the response form of average taxa tolerance (y-axis  =  fitted function of RichTOL) based on the effect of the interaction of two individual explanatory variables along the response variable (all other variable responses removed). There is a relatively large interaction at high values of average March runoff when there are also high values of percent riparian wetland thus resulting in higher values of tolerant taxa (RichTOL) than would be expected. We believe that high values of riparian wetland are acting as a surrogate for high values of percent urban land use.</p

Partial dependency plots for variables in BRT model for RichTOL for North Central Appalachian Region.

<p>Boosted regression tree partial dependency plots show the response form of average taxa tolerance (y-axis  =  fitted function of RichTOL) based on the effect of individual explanatory variables with the response of all other variables removed (development data set). Shown in order of model importance: (A) percent riparian forest, (B) riparian population density (#/km²), (C) percent riparian agriculture and (D) population density (#/km²). The relative contribution of each explanatory variable is reported in parentheses. Refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090944#pone-0090944-t001" target="_blank">Table 1</a> for variable definitions. Three of the four variables can be interpreted as disturbance variables, two directly assessing urban land use (population density) and the third, riparian forest, which measures the amount of disturbance in the riparian zone was the top variable modeled. However, this region had the shortest disturbance gradient and the lowest modeled R² (0.67), though still relatively strong.</p

Interaction of manmade streams and mean elevation on RichTOL for Northern Piedmont BRT model.

<p>Boosted regression tree partial dependency plot shows the response form of average taxa tolerance (y-axis  =  fitted function of RichTOL) based on the effect of the interaction of two individual explanatory variables along the response variable (all other variable responses removed). There is a relatively strong interaction acting on RichTOL at low values of mean elevation and high values of percent manmade streams that cause high values of tolerant taxa to occur. This is a common pattern, higher urbanization occurring in the lower elevation valleys.</p

Description, variable code and definition of explanatory environmental (landscape, riparian and habitat) and response (invertebrate metrics) variables used for model development.

<p>All variables listed were initially considered for inclusion in boosted regression tree (BRT) models. NLCD–National Land Cover Dataset, NRCS–National Resource Conservation Service, STATSGO–State Soil Geographic data base.</p

Partial dependency plots for variables in BRT model for RichTOL for Ridge and Valley Region.

<p>Boosted regression tree partial dependency plots show the response form of average taxa tolerance (y-axis  =  fitted function of RichTOL) based on the effect of individual explanatory variables with the response of all other variables removed (development data set). Shown in order of model importance: (A) percent manmade channels, (B) percent riparian forests, (C) maximum November runoff (mm) and (D) population density (#/km²), model R² = 0.81. The relative contribution of each explanatory variable is reported in parentheses. Refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090944#pone-0090944-t001" target="_blank">Table 1</a> for variable definitions. Three of the four variables measure the effects of disturbance, two measure the response to urban land use and the other disturbance in the riparian zone due to either agriculture or urbanization. The fourth variable shows the response due to maximum November runoff.</p

Observed versus predicted plots for BRT models for development (left) and validation (right) data sets.

<p>The observed versus predicted plots are based on the boosted regression models developed for average taxa tolerance (RichTOL) for five models: Full Region and four individual ecoregions (NC Appalachian, Ridge and Valley, NE Highlands, and N. Piedmont). The Full Region and N. Piedmont region plot relatively tight to the 1∶1 line for both the development and validation models indicating a good predictive fit with only slight bias at high and low values of RichTOL. The other regions in general showed more scatter and the N.C. Appalachian region which had the lowest modeled R², had had the shortest disturbance gradient (narrow range of RichTOL values) compared to the other regions.</p

Comparison of model evaluation statistics for boosted regression tree models (BRT) for four macroinvertebrate metrics for development (develop) and validation (valid) data sets at two spatial scales (full region and four ecoregions), number of variables in final model in parentheses.

<p>Validation models run with the same variables as the final development model.*</p><p>*R²–adjusted R-squared, CV R²-Cross validation R²; EPTR–Total taxa richness of Ephemeroptera (mayflies), Plecoptera (stoneflies) and Trichoptera (caddisflies); RichTOL-Average tolerance of all taxa; INTOL_RICH-Richness of intolerant taxa; NonInsectR-Noninsect taxa richness.</p

Expanded Target-Chemical Analysis Reveals Extensive Mixed-Organic-Contaminant Exposure in U.S. Streams

Surface water from 38 streams nationwide was assessed using 14 target-organic methods (719 compounds). Designed-bioactive anthropogenic contaminants (biocides, pharmaceuticals) comprised 57% of 406 organics detected at least once. The 10 most-frequently detected anthropogenic-organics included eight pesticides (desulfinylfipronil, AMPA, chlorpyrifos, dieldrin, metolachlor, atrazine, CIAT, glyphosate) and two pharmaceuticals (caffeine, metformin) with detection frequencies ranging 66–84% of all sites. Detected contaminant concentrations varied from less than 1 ng L^–1 to greater than 10 μg L^–1, with 77 and 278 having median detected concentrations greater than 100 ng L^–1 and 10 ng L^–1, respectively. Cumulative detections and concentrations ranged 4–161 compounds (median 70) and 8.5–102 847 ng L^–1, respectively, and correlated significantly with wastewater discharge, watershed development, and toxic release inventory metrics. Log₁₀ concentrations of widely monitored HHCB, triclosan, and carbamazepine explained 71–82% of the variability in the total number of compounds detected (linear regression; <i>p</i>-values: < 0.001–0.012), providing a statistical inference tool for unmonitored contaminants. Due to multiple modes of action, high bioactivity, biorecalcitrance, and direct environment application (pesticides), designed-bioactive organics (median 41 per site at μg L^–1 cumulative concentrations) in developed watersheds present aquatic health concerns, given their acknowledged potential for sublethal effects to sensitive species and lifecycle stages at low ng L^–1