The Capacity to Detect Change Stream Fish Communities Characteristics at the Site-Level in the Lake Ontario Basin

We investigate natural inter-annual variability of fish community measures within streams of the Lake Ontario basin. Given this variability, we examined coefficients of variation (CV) among the community measures and three scenarios pertaining to the capacity of biologists to detect changes in the fish community at the stream site level. Results indicate that Ontario's stream fish communities are highly variable in time. Young-of-the-year rainbow trout growth was the least variable whereas biomass density scored the highest CV of 0.50 among streams (range 0.22-0.99). Given the CVs and relatively equal sample sizes, our measures of the fish community can be ranked from least to most powerful: biomass, density, richness, diversity, and growth of young-of-the-year rainbow trout. Only large changes in measures can typically be detected. For instance, it would take 4-6 years of monitoring before and after a pulse perturbation to detect a 50 % change in species richness or diversity. We suggest that monitoring abundance is unlikely to result in the detection of small impacts within a short period of time and that large effects can be masked by low statistical power. This evidence voices the need for more research into better sampling methods, experimental designs, and choice of indicators to support monitoring programs for flowing waters.     

Taking a ‘Big Data’ approach to data quality in a citizen science project

Data from well-designed experiments provide the strongest evidence of causation in biodiversity studies. However, for many species the collection of these data is not scalable to the spatial and temporal extents required to understand patterns at the population level. Only data collected from citizen science projects can gather sufficient quantities of data, but data collected from volunteers are inherently noisy and heterogeneous. Here we describe a ‘Big Data’ approach to improve the data quality in eBird, a global citizen science project that gathers bird observations. First, eBird’s data submission design ensures that all data meet high standards of completeness and accuracy. Second, we take a ‘sensor calibration’ approach to measure individual variation in eBird participant’s ability to detect and identify birds. Third, we use species distribution models to fill in data gaps. Finally, we provide examples of novel analyses exploring population-level patterns in bird distributions.     

An Index of Air Pollution and its Relation to Health

Atmospheric pollution by sulfur oxides is discussed in terms of the sources of the pollutant and the possible methods of control. Possible approaches to control are classified in general categories, including fuel desulfurization, process modifications, and flue-gas desulfurization. Some of the more promising specific possibilities are discussed in relation to the organizations developing them.     

Maintenance Guidelines

As utility use of flue gas desulfurization (FGD) technology has increased, so has an awareness of the importance of maintenance to system economy and availability. These guidelines provide a comprehensive source of information on overall FGD system maintenance.     

Errors in coarse particulate matter mass concentrations and spatiotemporal characteristics when using subtraction estimation methods

In studies of coarse particulate matter (PM_10-2.5), mass concentrations are often estimated through the subtraction of PM_2.5 from collocated PM₁₀ tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM_10-2.5 estimation when using the possible combinations of PM₁₀ and PM_2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural–Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM_10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM_10-2.5 mass and spatial characteristics due to the very low semivolatile PM_10-2.5 concentrations in Colorado. Estimation using either a PM_2.5 or PM₁₀ monitor without FDMS introduced absolute biases of 2.4 µg/m³ (25%) to –2.3 µg/m³ (–24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM_10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM_2.5 TEOM and PM₁₀ TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM_2.5 from total PM_2.5 concentrations. By estimating nonvolatile PM_2.5 concentrations from this relationship, PM_10-2.5 was calculated as the difference between nonvolatile PM₁₀ and PM_2.5 concentrations.

Implications: Errors in the estimation of PM_10-2.5 concentrations using subtraction methods were shown to be related to the unmeasured semivolatile mass when using certain combinations of TEOM instruments. For the northeastern Colorado region, the absolute bias associated with this error significantly affects mean and 95th percentile values, which would affect assessment of compliance if PM_10-2.5 is regulated in the future. Estimating PM_10-2.5 mass concentrations using nonvolatile mass concentrations from collocated PM₁₀ and PM_2.5 TEOM monitors closely estimates the total PM_10-2.5 mass concentrations. A corrective model that removes the described error was developed and applied to data from two sites in Denver.

Supplemental Materials: Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association.     

Protection from wintertime rainfall reduces nutrient losses and greenhouse gas emissions during the decomposition of poultry and horse manure-based amendments

Manure-based soil amendments (herein “amendments”) are important fertility sources, but differences among amendment types and management can significantly affect their nutrient value and environmental impacts. A 6-month in situ decomposition experiment was conducted to determine how protection from wintertime rainfall affected nutrient losses and greenhouse gas (GHG) emissions in poultry (broiler chicken and turkey) and horse amendments. Changes in total nutrient concentration were measured every 3 months, changes in ammonium (NH₄⁺) and nitrate (NO₃^?) concentrations every month, and GHG emissions of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) every 7–14 days. Poultry amendments maintained higher nutrient concentrations (except for K), higher emissions of CO₂ and N₂O, and lower CH₄ emissions than horse amendments. Exposing amendments to rainfall increased total N and NH₄⁺ losses in poultry amendments, P losses in turkey and horse amendments, and K losses and cumulative N₂O emissions for all amendments. However, it did not affect CO₂ or CH₄ emissions. Overall, rainfall exposure would decrease total N inputs by 37% (horse), 59% (broiler chicken), or 74% (turkey) for a given application rate (wet weight basis) after 6 months of decomposition, with similar losses for NH₄⁺ (69–96%), P (41–73%), and K (91–97%). This study confirms the benefits of facilities protected from rainfall to reduce nutrient losses and GHG emissions during amendment decomposition.

Implications: The impact of rainfall protection on nutrient losses and GHG emissions was monitored during the decomposition of broiler chicken, turkey, and horse manure-based soil amendments. Amendments exposed to rainfall had large ammonium and potassium losses, resulting in a 37–74% decrease in N inputs when compared with amendments protected from rainfall. Nitrous oxide emissions were also higher with rainfall exposure, although it had no effect on carbon dioxide and methane emissions. Overall, this work highlights the benefits of rainfall protection during amendment decomposition to reduce nutrient losses and GHG emissions.     

Elevated in-home sediment contaminant concentrations - the consequence of a particle settling-winnowing process from Hurricane Katrina floodwaters

Sediment samples were collected from two homes which were flooded in the wake of Hurricane Katrina in August 2005. The samples were analyzed for trace metals and semi-volatile organic compounds using techniques based on established EPA methods. The data showed higher concentrations of some metals and semi-volatile organic pollutants than reported in previous outdoor sampling events of soils and sediments. The Lake Pontchartrain sediments became resuspended during the hurricane, and this material subsequently was found in the residential areas of New Orleans following levee breaches. The clay and silt particles appear to be selectively deposited inside homes, and sediment contaminant concentrations are usually greatest within this fraction. Re-entry advisories based on outdoor sample concentration results may have under-predicted the exposure levels to homeowners and first responders. All contaminants found in the sediment sampled in this study have their origin in the sediments of Lake Pontchartrain and other localized sources.     

Towards an ecologically meaningful classification of the flow biotope for river inventory, rehabilitation, design and appraisal purposes

Recent research into the physical and ecological status of rivers has focused upon rapid field-based assessments of mesoscale habitat features in order to satisfy international regulatory requirements for habitat inventory and appraisal. Despite the low cost and time efficient nature of rapid field surveys, the robustness of such techniques remains uncertain. This paper uses data from over 4000 surveyed UK river reaches in the UK River Habitat Survey (RHS) database in order to seek linkages between surface flow conditions (flow biotopes), local channel morphology (physical biotopes) and biologically distinct vegetative and minerogenic habitat units (functional habitats). Attempts to identify one-to-one connections between surface flow types, units of channel morphology and functional habitats oversimplify a complex and dynamic hydraulic environment. Instead, a nested hierarchy of reach-scale physical and ecological habitat structures exists, characterised by transferable assemblages of habitat units. Five flow biotopes show strong correlations with functional habitats, and differing combinations of three of these account for over 60% of the distribution for all functional habitats. On this basis, a classification of environments for ecological purposes is proposed. Principal components analysis and agglomerative hierarchical clustering analysis are employed to objectively validate the proposed classification. Flow biotope assemblages may also represent reach-scale channel morphologies (step-pool, riffle-pool and glide-pool), although functional habitats exhibit differing 'preferences' for rougher or more tranquil environments within these. While the data and analysis are specific to the UK RHS, the methods and findings have wider application in situations, where rapid field appraisal methods and associated databases are deployed in water resource inventory and river rehabilitation design.