Ecosystem classifications based on summer and winter conditions

Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.     

Regional data refine local predictions: modeling the distribution of plant species abundance on a portion of the central plains

Species distribution models are frequently used to predict species occurrences in novel conditions, yet few studies have examined the consequences of extrapolating locally collected data to regional landscapes. Similarly, the process of using regional data to inform local prediction for species distribution models has not been adequately evaluated. Using boosted regression trees, we examined errors associated with extrapolating models developed with locally collected abundance data to regional-scale spatial extents and associated with using regional data for predictions at a local extent for a native and non-native plant species across the northeastern central plains of Colorado. Our objectives were to compare model results and accuracy between those developed locally and extrapolated regionally, those developed regionally and extrapolated locally, and to evaluate extending species distribution modeling from predicting the probability of presence to predicting abundance. We developed models to predict the spatial distribution of plant species abundance using topographic, remotely sensed, land cover and soil taxonomic predictor variables. We compared model predicted mean and range abundance values to observed values between local and regional. We also evaluated model prediction performance based on Pearson's correlation coefficient. We show that: (1) extrapolating local models to regional extents may restrict predictions, (2) regional data can help refine and improve local predictions, and (3) boosted regression trees can be useful to model and predict plant species abundance. Regional sampling designed in concert with large sampling frameworks such as the National Ecological Observatory Network may improve our ability to monitor changes in local species abundance.     

Determination of contaminant levels and remediation efficacy in groundwater at a former in situ recovery uranium mine

There has been increasing interest in uranium mining in the United States via in situ recovery techniques. One of the main environmental concerns with in situ uranium mining is the potential for spreading groundwater contamination. There is a dearth of detailed analysis and information regarding the outcome of in situ uranium mine remediation to ascertain the environmental impacts. Regulatory measurements performed at a Wyoming in situ uranium mine were collected and analysed to ascertain the efficacy of remediation and potential long term environmental impact. Based on the measurements, groundwater sweeping followed by reverse osmosis (RO) treatment proved to be a highly efficient method of remediation. However, injection of a reductant in the form of H(2)S after groundwater sweeping and RO did not further reduce the aqueous concentration of U, Mn, or Fe. Low concentrations of target species at monitoring wells outside the mined area appear to indicate that in the long term, natural attenuation is likely to play a major role at reductively immobilizing residual (after remediation) concentrations of U(VI) thus preventing it from moving outside the mined area. Our analysis indicates the need for additional monitoring wells and sampling in conjunction with long term monitoring to better understand the impacts of the different remediation techniques.     

Environmental flows for rivers and economic compensation for irrigators

Securing flows for environmental purposes from an already fully utilized river is an impossible task--unless users are either coerced into freeing up water, or offered incentives to do so. One sensible strategy for motivating users to liberate volumes is to offer them economic compensation. The right amount for that compensation then becomes a key environmental management issue. This paper analyses a proposal to restore and maintain ecosystems on a stretch of the Río Conchos in northern Mexico, downstream from a large irrigation district that consumes nearly all local flows. We present here estimates of environmental flow requirements for these ecosystems and compute compensation figures for irrigators. These figures are derived from crop-specific irrigation water productivities we statistically estimate from a large set of historical production and irrigation data obtained from the district. This work has general implications for river ecosystem management in water-stressed basins, particularly in terms of the design of fair and effective water sharing mechanisms.     

Analysis of hazardous material releases due to natural hazards in the United States

Natural hazards were the cause of approximately 16,600 hazardous material (hazmat) releases reported to the National Response Center (NRC) between 1990 and 2008-three per cent of all reported hazmat releases. Rain-induced releases were most numerous (26 per cent of the total), followed by those associated with hurricanes (20 per cent), many of which resulted from major episodes in 2005 and 2008. Winds, storms or other weather-related phenomena were responsible for another 25 per cent of hazmat releases. Large releases were most frequently due to major natural disasters. For instance, hurricane-induced releases of petroleum from storage tanks account for a large fraction of the total volume of petroleum released during 'natechs' (understood here as a natural hazard and the hazardous materials release that results). Among the most commonly released chemicals were nitrogen oxides, benzene, and polychlorinated biphenyls. Three deaths, 52 injuries, and the evacuation of at least 5,000 persons were recorded as a consequence of natech events. Overall, results suggest that the number of natechs increased over the study period (1990-2008) with potential for serious human and environmental impacts.     

Positive vs. false detection: A comparison of analytical methods and performance for analysis of cyclic volatile methylsiloxanes (cVMS) in environmental samples from remote regions

Contamination and analytical variation can significantly hinder trace analysis of cyclic methyl volatile siloxanes (cVMS); potentially resulting in the report of false positives at concentrations approaching detection limits. To assess detection and variation associated with trace cVMS analysis in environmental matrices, a co-operative laboratory comparison for the analysis of octametylcyclotetrasiloxane (D4), decamethylcylcopentasiloxane (D5), and dodecametylcyclohexasiloxane (D6) in sediment and biota from the Svalbard Archipelago was conducted. Two definitions of detection limits were evaluated in this study; method detection limits (MDL, matrix defined) and limits of detection (LOD, solvent defined). D5 was the only cVMS detected above both LOD (0.08–0.81 ng g⁻¹ ww) and MDL (0.47–2.36 ng g⁻¹ ww) within sediment by all laboratories where concentrations ranged from 0.55 to 3.91 ng g⁻¹ ww. The percentage of positive detects for D5 decreased by 80% when MDL was defined as the detection limit. D5 was also detected at the highest frequency among all laboratories in fish liver with concentrations ranging from 0.72 to 345 ng g⁻¹ ww. Similar to sediment, percentage of positive detects for D5 decreased by 60% across all laboratories for fish livers when using MDL (0.68–3.49 ng g⁻¹ ww). Similar observations were seen with both D4 and D6, indicating that sample matrix significantly contributes to analytical response variation. Despite differences in analytical methods used between laboratories, good agreement was obtained when using MDL to define detection limits. This study shows the importance of incorporating variation introduced by sample matrices into detection limit calculations to insure data accuracy of cVMS at low concentrations.     

Is the Water Footprint an Appropriate Tool for Forestry and Forest Products: The Fennoscandian Case

The water footprint by the Water Footprint Network (WF) is an ambitious tool for measuring human appropriation and promoting sustainable use of fresh water. Using recent case studies and examples from water-abundant Fennoscandia, we consider whether it is an appropriate tool for evaluating the water use of forestry and forest-based products. We show that aggregating catchment level water consumption over a product life cycle does not consider fresh water as a renewable resource and is inconsistent with the principles of the hydrologic cycle. Currently, the WF assumes that all evapotranspiration (ET) from forests is a human appropriation of water although ET from managed forests in Fennoscandia is indistinguishable from that of unmanaged forests. We suggest that ET should not be included in the water footprint of rain-fed forestry and forest-based products. Tools for sustainable water management should always contextualize water use and water impacts with local water availability and environmental sensitivity.     

Co-treatment of acid mine drainage with municipal wastewater: performance evaluation

Co-treatment of acid mine drainage (AMD) with municipal wastewater (MWW) using the activated sludge process is a novel treatment technology offering potential savings over alternative systems in materials, proprietary chemicals and energy inputs. The impacts of AMD on laboratory-scale activated sludge units (plug-flow and sequencing batch reactors) treating synthetic MWW were investigated. Synthetic AMD containing Al, Cu, Fe, Mn, Pb, Zn and SO₄ at a range of concentrations and pH values was formulated to simulate three possible co-treatment processes, i.e., (1) adding raw AMD to the activated sludge aeration tank, (2) pre-treating AMD prior to adding to the aeration tank by mixing with digested sludge and (3) pre-treating AMD by mixing with screened MWW. Continuous AMD loading to the activated sludge reactors during co-treatment did not cause a significant decrease in chemical oxygen demand (COD), 5-day biochemical oxygen demand, or total organic carbon removal; average COD removal rates ranged from 87–93 %. Enhanced phosphate removal was observed in reactors loaded with Fe- and Al-rich AMD, with final effluent TP concentrations <2 mg/L. Removal rates for dissolved Al, Cu, Fe and Pb were 52–84 %, 47–61 %, 74–86 % and 100 %, respectively, in both systems. Manganese and Zn removal were strongly linked to acidity; removal from net-acidic AMD was <10 % for both metals, whereas removal from circum-neutral AMD averaged 93–95 % for Mn and 58–90 % for Zn. Pre-mixing with screened MWW was the best process option in terms of AMD neutralization and metal removal. However, significant MWW alkalinity was consumed, suggesting an alkali supplement may be necessary.     

Eukaryotic diversity in premise drinking water using 18S rDNA sequencing: implications for health risks

The goal of this study was to characterize microbial eukaryotes over a 12-month period to provide insight into the occurrence of potential bacterial predators and hosts in premise plumbing. Nearly 6,300 partial 18S rRNA gene sequences from 24 hot (36.9–39.0 °C) and cold (6.8–29.1 °C) drinking water samples were analyzed and classified into major eukaryotic groups. Each major group, consisting of free-living amoebae (FLA)/protozoa, algae, copepods, dinoflagellates, fungi, nematodes, and unique uncultured eukaryotic sequences, showed limited diversity dominated by a few distinct populations, which may be characteristic of oligotrophic environments. Changes in the relative abundance of predators such as nematodes, copepods, and FLA appear to be related to temperature and seasonal changes in water quality. Sequences nearly identical to FLA such as Hartmannella vermiformis, Echinamoeba thermarmum, Pseudoparamoeba pagei, Protacanthamoeba bohemica, Platyamoeba sp., and Vannella sp. were obtained. In addition to FLA, various copepods, rotifers, and nematodes have been reported to internalize viral and bacterial pathogens within drinking water systems thus potentially serving as transport hosts; implications of which are discussed further. Increasing the knowledge of eukaryotic occurrence and their relationship with potential pathogens should aid in assessing microbial risk associated with various eukaryotic organisms in drinking water.