Predicting the biological condition of streams: use of geospatial indicators of natural and anthropogenic characteristics of watersheds

We developed and evaluated empirical models to predict biological condition of wadeable streams in a large portion of the eastern USA, with the ultimate goal of prediction for unsampled basins. Previous work had classified (i.e., altered vs. unaltered) the biological condition of 920 streams based on a biological assessment of macroinvertebrate assemblages. Predictor variables were limited to widely available geospatial data, which included land cover, topography, climate, soils, societal infrastructure, and potential hydrologic modification. We compared the accuracy of predictions of biological condition class based on models with continuous and binary responses. We also evaluated the relative importance of specific groups and individual predictor variables, as well as the relationships between the most important predictors and biological condition. Prediction accuracy and the relative importance of predictor variables were different for two subregions for which models were created. Predictive accuracy in the highlands region improved by including predictors that represented both natural and human activities. Riparian land cover and road-stream intersections were the most important predictors. In contrast, predictive accuracy in the lowlands region was best for models limited to predictors representing natural factors, including basin topography and soil properties. Partial dependence plots revealed complex and nonlinear relationships between specific predictors and the probability of biological alteration. We demonstrate a potential application of the model by predicting biological condition in 552 unsampled basins across an ecoregion in southeastern Wisconsin (USA). Estimates of the likelihood of biological condition of unsampled streams could be a valuable tool for screening large numbers of basins to focus targeted monitoring of potentially unaltered or altered stream segments.     

Selection and application of a rainbow trout toxicity testing procedure for screening Sacramento River Watershed, California samples

A number of procedures have been developed to assess toxic effects on the early life stages of salmonid fish. In this study 13 rainbow trout embryo development relatively short-term (7 to 90 day) procedures were reviewed. Three 7-day methods from the published literature and three modifications developed at AQUA-Science (A-S) were evaluated in the laboratory. Based on that evaluation, A-S methods were selected for screening surface water samples (A-S 1) collected in the Sacramento River watershed (California) and for conducting toxicity identification evaluations (TIE) to identify cause(s) of toxicity. Test control performance, test sensitivity, and reference toxicant response variability in the A-S 1 were superior to those in commonly used freshwater toxicity testing methods. The incidence of Sacramento River watershed samples resulting in a notable decrease in embryo development was very low. Of 260 samples screened only 16 (6%) resulted in statistically significant inhibition of embryo development. Of the 16 toxic samples, nine caused minimal (less than 20% abnormal development) and four marginal (less than 30%) toxicity. Samples collected from the agriculture-dominated Colusa Basin Drain and rangeland/forest-dominated Battle Creek on June 16, 2005 caused significant toxicity. TIE procedures indicated that cationic chemicals were the primary cause of toxicity. Metals analysis did not reveal concentrations sufficient to inhibit embryo development, so the most probable cause of toxicity in the two samples was cationic chemicals (perhaps surfactants?) or metals that were not included in the analytical screening.     

Comparison of arsenic, cadmium, chromium, lead, manganese, mercury and selenium in feathers in bald eagle (Haliaeetus leucocephalus), and comparison with common eider (Somateria mollissima), glaucous-winged gull (Larus glaucescens), pigeon guillemot (Cepphus columba), and tufted puffin (Fratercula cirrhata) from the Aleutian Chain of Alaska

There is an abundance of field data for levels of metals from a range of places, but relatively few from the North Pacific Ocean and Bering Sea. In this paper we examine the levels of arsenic, cadmium, chromium, lead, manganese, mercury and selenium in feathers from common eiders (Somateria mollissima), glaucous-winged gulls (Larus glaucescens), pigeon guillemots (Cepphus columba), tufted puffins (Fratercula cirrhata) and bald eagles (Haliaeetus leucocephalus) from the Aleutian Chain of Alaska. Our primary objective was to test the hypothesis that there are no trophic levels relationships for arsenic, cadmium, chromium, lead, manganese, mercury and selenium among these five species of birds breeding in the marine environment of the Aleutians. There were significant interspecific differences in all metal levels. As predicted bald eagles had the highest levels of arsenic, chromium, lead, and manganese, but puffins had the highest levels of selenium, and pigeon guillemot had higher levels of mercury than eagles (although the differences were not significant). Common eiders, at the lowest trophic level had the lowest levels of some metals (chromium, mercury and selenium). However, eiders had higher levels than all other species (except eagles) for arsenic, cadmium, lead, and manganese. Levels of lead were higher in breast than in wing feathers of bald eagles. Except for lead, there were no significant differences in metal levels in feathers of bald eagles nesting on Adak and Amchitka Island; lead was higher on Adak than Amchitka. Eagle chicks tended to have lower levels of manganese than older eagles.     

Critical technical elements of state bioassessment programs: a process to evaluate program rigor and comparability

We developed a systematic process to evaluate state/tribal bioassessment programs to provide information about the rigor of the technical approach. This is accomplished via on-site interviews to produce an evaluation that assigns one of four levels of rigor as an outcome. Level 4 is the most rigorous and reflects a technical capacity to accurately determine incremental condition and support management programs. The remaining three levels are less able to assess incremental condition and are appropriate for only some management support needs. Accurately determining impairment and diagnosing pollution-specific stressors are fundamental tasks that states/tribes must accomplish to provide management support. This goal is fulfilled to varying degrees by most states/tribes. The evaluation employs a checklist and a sliding scale of rigor for 13 technical elements. Feedback is provided to each state/tribe via a technical memorandum that describes the technical components of the monitoring program, highlights strengths, and recommends improvements for specific technical issues. This can be used to refine the bioassessment and monitoring programs to better support management programs. The results of 14 state/tribal evaluations are included here. The majority (nine states, one tribe) revealed that most operate at level 2 with developmental activities that will elevate the level of program rigor already underway. Two states operate level 4 programs and each have numeric biocriteria and refined designated uses in their water quality standards. This is the ultimate goal of the process of engaging states in the development of bioassessment programs in the U.S.     

Assessment and significance of phytoplankton species composition within Chesapeake Bay and Virginia tributaries through a long-term monitoring program

Phytoplankton and water quality long term trends are presented from a 20-year monitoring program of Chesapeake Bay and several of its major tributaries. Increasing phytoplankton biomass and abundance are ongoing within this estuarine complex, with diatoms the dominant component, along with chlorophytes and cyanobacteria as sub-dominant contributors in the tidal freshwater and oligohaline regions. Diatoms, dinoflagellates, and cryptomonads are among the major flora downstream in the tributaries and within the Chesapeake Bay. Water quality conditions within the three tributaries have remained rather stable over this time period; while there are long term trends of reduced nutrients, increasing bottom oxygen, and decreasing water clarity for the lower Chesapeake Bay. Of note is an increasing trend of cyanobacteria biomass at 12 of the 13 stations monitored at tributary and Chesapeake Bay stations, plus the presence of 37 potentially harmful taxa reported for these waters. However, the overall status of the phytoplankton populations is presently favorable, in that it is mainly represented and dominated by taxa suitable as a major food and oxygen source within this ecosystem. Although potentially harmful taxa are present, they have not at this time exerted profound impact to the region, or replaced the diatom populations in overall dominance.     

Advantages of Geographically Weighted Regression for Modeling Benthic Substrate in Two Greater Yellowstone Ecosystem Streams

Stream habitat assessments are commonplace in fish management, and often involve nonspatial analysis methods for quantifying or predicting habitat, such as ordinary least squares regression (OLS). Spatial relationships, however, often exist among stream habitat variables. For example, water depth, water velocity, and benthic substrate sizes within streams are often spatially correlated and may exhibit spatial nonstationarity or inconsistency in geographic space. Thus, analysis methods should address spatial relationships within habitat datasets. In this study, OLS and a recently developed method, geographically weighted regression (GWR), were used to model benthic substrate from water depth and water velocity data at two stream sites within the Greater Yellowstone Ecosystem. For data collection, each site was represented by a grid of 0.1 m² cells, where actual values of water depth, water velocity, and benthic substrate class were measured for each cell. Accuracies of regressed substrate class data by OLS and GWR methods were calculated by comparing maps, parameter estimates, and determination coefficient r ². For analysis of data from both sites, Akaike’s Information Criterion corrected for sample size indicated the best approximating model for the data resulted from GWR and not from OLS. Adjusted r ² values also supported GWR as a better approach than OLS for prediction of substrate. This study supports GWR (a spatial analysis approach) over nonspatial OLS methods for prediction of habitat for stream habitat assessments.     

The distribution and extent of heavy metal accumulation in song sparrows along Arizona’s upper Santa Cruz River

Heavy metals are persistent environmental contaminants, and transport of metals into the environment poses a threat to ecosystems, as plants and wildlife are susceptible to long-term exposure, bioaccumulation, and potential toxicity. We investigated the distribution and cascading extent of heavy metal accumulation in southwestern song sparrows (Melospiza melodia fallax), a resident riparian bird species that occurs along the US/Mexico border in Arizona’s upper Santa Cruz River watershed. This study had three goals: (1) quantify the degree of heavy metal accumulation in sparrows and determine the distributional patterns among study sites, (2) compare concentrations of metals found in this study to those found in studies performed prior to a 2009 international wastewater facility upgrade, and (3) assess the condition of song sparrows among sites with differing potential levels of exposure. We examined five study sites along with a reference site that reflect different potential sources of contamination. Body mass residuals and leukocyte counts were used to assess sparrow condition. Birds at our study sites typically had higher metal concentrations than birds at the reference site. Copper, mercury, nickel, and selenium in song sparrows did exceed background levels, although most metals were below background concentrations determined from previous studies. Song sparrows generally showed lower heavy metal concentrations compared to studies conducted prior to the 2009 wastewater facility upgrade. We found no cascading effects as a result of metal exposure.     

Assessment of long-term wastewater irrigation impacts on the soil geochemical properties and the bioaccumulation of heavy metals to the agricultural products

An extensive field survey was employed for assessing the impacts of long-term wastewater irrigation of forage crops and orange orchards in three suburban agricultural areas in Cyprus (areas I, II, and III), as compared to rainfed agriculture, on the soil geochemical properties and the bioaccumulation of heavy metals (Zn, Ni, Mn, Cu, Co) to the agricultural products. Both ryegrass fields and orange orchards in areas I and II were continuously wastewater irrigated for 10 years, whereas clover fields in area III for 0.5, 4, and 8 years. The results revealed that wastewater reuse for irrigation caused a slight increase in soil salinity and Cl^? content in areas I and II, and a remarkable increase, having strong correlation with the period in which wastewater irrigation was practiced, in area III. Soil salinization in area III was due to the high electrical conductivity (EC) of the wastewater applied for irrigation, attributed to the influx of seawater to the sewage collection network in area III. In addition, the wastewater irrigation practice resulted in a slight decrease of the soil pH values in area III, while a subtle impact was identified regarding the CaCO₃, Fe, and heavy metal content in the three areas surveyed. The heavy metal content quantified in the forage plants’ above-ground parts was below the critical levels of phytotoxicity and the maximum acceptable concentration in dairy feed, whereas heavy metals quantified in orange fruit pulp were below the maximum permissible levels (MPLs). Heavy metal phytoavailability was confined due to soil properties (high pH and clay content), as evidenced by the calculated low transfer factor (TF).     

Life cycle cost evaluation of the digital opacity compliance system

The US Environmental Protection Agency (EPA) has established EPA Reference Method 9 (Method 9) as the preferred enforcement approach for verifying compliance with federal visible opacity standards. While Method 9 has an extensive history of successful employment, reliance on human observers to quantify visible emissions is inherently subjective, a characteristic that exposes Method 9 results to claims of inaccuracy, bias and, in some cases, outright fraud.The Digital Opacity Compliance System (DOCS), which employs commercial-off-the-shelf digital photography coupled with simple computer processing, is a new approach for quantifying visible opacity. The DOCS technology has been previously demonstrated to meet and, in many cases, surpass the Method 9 accuracy and reliability standards (McFarland et al., 2006). Beyond its performance relative to Method 9, DOCS provides a permanent visual record of opacity, a vital feature in legal compliance challenges.In recent DOCS field testing, the opacity analysis of two hundred and forty one (241) regulated air emissions from the following industrial processes: 1) industrial scrubbers, 2) emergency generators, 3) asphalt paving, 4) steel production and 5) incineration indicated that Method 9 and DOCS were statistically equivalent at the 99% confidence level. However, a life cycle cost analysis demonstrated that implementation of DOCS could potentially save a facility $15,732 per trained opacity observer compared to utilization of Method 9.     

Models for waste life cycle assessment: Review of technical assumptions

A number of waste life cycle assessment (LCA) models have been gradually developed since the early 1990s, in a number of countries, usually independently from each other. Large discrepancies in results have been observed among different waste LCA models, although it has also been shown that results from different LCA studies can be consistent. This paper is an attempt to identify, review and analyse methodologies and technical assumptions used in various parts of selected waste LCA models. Several criteria were identified, which could have significant impacts on the results, such as the functional unit, system boundaries, waste composition and energy modelling. The modelling assumptions of waste management processes, ranging from collection, transportation, intermediate facilities, recycling, thermal treatment, biological treatment, and landfilling, are obviously critical when comparing waste LCA models.This review infers that some of the differences in waste LCA models are inherent to the time they were developed. It is expected that models developed later, benefit from past modelling assumptions and knowledge and issues. Models developed in different countries furthermore rely on geographic specificities that have an impact on the results of waste LCA models. The review concludes that more effort should be employed to harmonise and validate non-geographic assumptions to strengthen waste LCA modelling.