Development of Stream Water Chemistry during Spring Melt in a Northern Hardwood Forest

The role of snowmelt and subsurface hydrology in determiningthe chemistry of a small headwater stream in the TurkeyLakes Watershed (TLW) was evaluated for the spring meltperiods 1992 to 1996. Spring runoff is the dominanthydrological event at the TLW each year. Processesoccurring within the snowpack during snowmelt wereprincipally responsible for the above-ground changes inchemical fluxes relative to bulk deposition (the effect ofwinter throughfall was minimal). Large changes in chemicalfluxes occurred below ground. Organic matter decomposition,weathering, nitrification, and element cycling are some ofthe more important below-ground processes that operateduring the snow accumulation and ablation season and controlthe composition of the water ultimately appearing in thestream. Maximum stream discharge was accompanied byelevated concentrations of H⁺, NO₃ ^-, K⁺,NH₄ ⁺, DOC, Al and Mn, but reduced levels ofCa²⁺, Mg²⁺, SO₄ ^2- and SiO₂. Theconcentration-discharge relationships were consistent withwater movement through and above the forest floor duringpeak discharge, a flowpath facilitated by rapid infiltrationof meltwater and the existence of a relatively impermeablelayer in the mineral soil creating a perched water table. Averaged over the five periods of snow accumulation andablation, it was estimated that pre-melt stream flow, andwater routed through the forest floor and through the uppermineral soil contributed 9, 28 and 63%, respectively, ofthe discharge measured at the outlet of the catchment. Theforest floor contribution would be greater at peak dischargeand at higher elevations. An end-member mixing modelestimated concentrations of SO₄ ^2-, NO₃ ^-,Cl^-, Ca²⁺, Mg²⁺, Na⁺ and Al that werecomparable to average values measured in the stream. Othervariables (NH₄ ⁺, H⁺, K⁺ and DOC) wereover-estimated implying retention mechanisms operatingoutside the model assumptions.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

Biogeochemical consequences of a changing Arctic shelf seafloor ecosystem

Unprecedented and dramatic transformations are occurring in the Arctic in response to climate change, but academic, public, and political discourse has disproportionately focussed on the most visible and direct aspects of change, including sea ice melt, permafrost thaw, the fate of charismatic megafauna, and the expansion of fisheries. Such narratives disregard the importance of less visible and indirect processes and, in particular, miss the substantive contribution of the shelf seafloor in regulating nutrients and sequestering carbon. Here, we summarise the biogeochemical functioning of the Arctic shelf seafloor before considering how climate change and regional adjustments to human activities may alter its biogeochemical and ecological dynamics, including ecosystem function, carbon burial, or nutrient recycling. We highlight the importance of the Arctic benthic system in mitigating climatic and anthropogenic change and, with a focus on the Barents Sea, offer some observations and our perspectives on future management and policy.     

Microscale analytical methods for the quantitative detection of PCBs and PAHs in small tissue masses

Microscale methods (MM) were evaluated and compared to traditional methods (TM) for measuring polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) in spiked and standard reference fish and mussel tissues. MMs are advantageous because they use small tissue masses (ca. 100 mg), and maintain sensitivity through reducing final extract volume (traditionally 1 ml) by an order of magnitude or more (40 μl—PCBs; 100 μl—PAHs). Procedural losses occurred in the MMs’ combined cleanup/primary evaporation step (19% PAHs; 6% PCBs), and the final extract concentration (14% PAHs; 22% PCBs). The PAH MM performed comparably to the TM. Although most PCBs had recoveries >50%, the PCB MM generally yielded lower recoveries than the TM. Average method detection limits were 0.6 μg/kg (TM) and 1.0 μg/kg (MM) for PCBs and 25.7 μg/kg (TM) and 27.7 μg/kg (MM) for PAHs. MMs described for PCB and PAH tissue samples are potentially viable alternatives to TMs, and could lead to cost savings in bioaccumulation/toxicity tests.     

A code to simulate nuclear reactor inventories and associated gamma-ray spectra

A computer code has been developed to simulate the gamma-ray spectra that would be measured by airborne gamma spectrometry (AGS) systems from sources containing short-lived fission products. The code uses simple numerical methods to simulate the production and decay of fission products and generates spectra for sodium iodide (NaI) detectors using Monte Carlo codes. A new Monte Carlo code using a virtual array of detectors to reduce simulation times for airborne geometries is described. Spectra generated for a short irradiation and laboratory geometry have been compared with an experimental data set. The agreement is good. Spectra have also been generated for airborne geometries and longer irradiation periods. The application of this code to generate AGS spectra for accident scenarios and their uses in the development and evaluation of spectral analysis methods for such situations are discussed.     

Performance of Manufacturer Cleaning Recommendations Applied to 3D Food Ink Capsules for the Control of a Human Norovirus Surrogate

With the widespread availability of 3D food printing systems for purchase, users can customize their food in new ways. Manufacturer recommendations for cleaning these machines remain untested with regard to the prevention of foodborne pathogen transmission. This study aimed to determine if manufacturer cleaning recommendations for food ink capsules utilized in 3D food printers are adequate to control human norovirus (HuNoV). A HuNoV surrogate, Tulane virus (TuV; ~?6 log₁₀ PFU/mL), was inoculated onto the interior surface of stainless steel food ink capsules. Capsules were either unsoiled or soiled with one of the following: butter, protein powder solution, powdered sugar solution, or a mixture containing all three food components. The capsules were allowed to dry and then one of three hygienic protocols was applied: manual washing (MW), a dishwasher speed cycle (DSC), or a dishwasher heavy cycle (DHC). The interaction effect between DSC and pure butter was a significant predictor of log reduction (P?=?0.0067), with the pure butter and DSC combination achieving an estimated mean log reduction of 4.83 (95% CI 4.13, 5.59). The DSC was the least effective method of cleaning when compared with MW and the DHC. The 3-way interaction effects between wash type, soil, and capsule position were a significant predictor of log reduction (P?=?0.00341). Capsules with butter in the DSC achieved an estimated mean log reduction of 2.81 (95% CI 2.80, 2.83) for the front-most position versus 6.35 (95% CI 6.33, 6.37) for the back-most position. Soil matrix, cleaning protocol, and capsule position all significantly impact capsule cleanability and potential food safety risk. The DHC is recommended for all capsules, and the corners should be avoided when placing capsules into the dishwasher. The current study seeks to provide recommendations for users of additive manufacturing and 3D food printing including consumers, restaurants, industry, and regulatory industries.

     

Temporal Trends in Water Chemistry in the Turkey Lakes Watershed Ontario,Canada, 1982-1999

The Turkey Lakes Watershed (TLW) was established in 1980 as asite for study of the ecosystem effects of acidic deposition, andsince then there has been 40% reduction in North AmericanSO₂ emissions. Monitoring records for bulk deposition,shallow and deep ground water, two headwater streams and two lakeoutflows have been tested to identify statistically significantmonotonic trends. The TLW appears to be responding to decliningacidifying emissions because the most prevalent chemical trendacross sample types/stations was decreasing SO₄ ^2-. Increasing pH was detected in four of the seven data sets, butonly the H⁺ decrease in bulk deposition was of a magnitudeto be an important ionic compensation for the SO₄ ^2-decline. There is little evidence of acidification recovery inTLW waters however. Increasing alkalinity was found only in theoutflow of the penultimate lake of the basin, and in fact, deepground water and the other lake outflow had decreasing alkalinitytrends (i.e., continuing acidification). For the surface waterstations, the greater part of the ionic compensation fordeclining SO₄ ^2- was decreasing base cations, and as aresult, these waters are probably becoming more dilute with time,although only the headwater streams exhibited decliningconductivity. Five of seven data sets had increasing dissolvedorganic carbon concentrations. Increasing NO₃ ^- wasimportant in ground waters. Drought has strongly influencedtrends and delayed recovery by mobilizing S stored in catchmentwetlands and/or soils.     

Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Great Plains

Crop simulation models are frequently used to estimate the impact of climate change on crop production. However, few studies have evaluated the model performance in ways that most researchers practiced in climate impact studies. In this article, we examined the reliability of the EPIC model in simulating grain sorghum (Sorghum bicolor (L.) Moench) yields in the U.S. Great Plains under different climate scenarios, namely in years with normal or extreme temperature and precipitation. We also investigated model uncertainties introduced by input data that are not site-specific but commonly used or available for climate change studies. Historical field trial data of sorghum at the Mead Experimental Center, NE, were used for model evaluations. The results showed that overall model reliability was about 56%. The mean absolute relative error (absRE) was about 29%. The degree of accuracy and reliability varied with climate-classes and nitrogen (N)-treatments. The largest bias occurred in drought years (RE = ?25%) and the most unreliable results were found in N-0 treatment (reliability = 32%). There was more than 69% probability that input-data-induced uncertainties were limited to less than 20% of absRE. Our results support the application of the EPIC model to climate change impact studies in the U.S. Great Plains. However, efforts are needed to improve the accuracy in simulating crop responses to extreme water- and nitrogen-stressed conditions.     

Relationships among nutrients, chlorophyll-a, and dissolved oxygen in agricultural streams in Illinois

A better understanding of the controls on algae and dissolved O2 in agricultural streams of Illinois is needed to aid in development of nutrient standards. We investigated the relationships between dissolved nutrients, algal abundance, and dissolved O2 in five streams in east-central Illinois from March through November 2004. The streams drained watersheds from 25 to 777 km2 that were dominated by row crop agriculture. Three sites had open canopies and two were bordered by a narrow forest of deciduous trees. Algal abundance was measured as chlorophyll-a (chl-a) concentration in the water column (sestonic) and on the streambed (periphytic). Mean NO3-N concentrations ranged from 5.5 to 8.8 mg N L(-1) and did not relate to algal abundance. Sestonic chl-a values ranged from nearly zero to >15 mg m(-3) with no differences between open and shaded streams and only a weak correlation with dissolved reactive P (mean concentrations were 44-479 microg L(-1)). The results suggest that sestonic chl-a is a poor criterion for assessing nutrient-related problems in these streams. Greatest periphytic chl-a occurred during low flow from August through October, but periphyton occurred consistently in only two of the five streams. The abundance of filamentous algae explained 64% of the variation in diel O2 saturation, but was not correlated with nutrients. Currently it appears that hydrology and light, rather than nutrients, control algal abundance in these streams, and in the agricultural landscape of east-central Illinois, it may not be possible to reduce nutrient concentrations sufficiently to limit filamentous algal blooms.     

Polychlorinated biphenyls in freshwater salmonids from the Kerguelen Islands in the Southern Ocean

The Subantarctic Kerguelen Islands (49°S, 70°E) contain freshwater ecosystems among the most isolated in the world. Concentrations of polychlorinated biphenyls (PCBs) were assessed in the muscle of 48 brook trout and 38 brown trout caught during summer and spring 2006 in the rivers, lakes and ponds of Kerguelen. The sum of 29 PCBs averaged 404 and 358 ng g⁻¹ lipid, and dioxin-like PCB was 19 and 69 ng g⁻¹ lipid, in brook and brown trout, respectively. The values showed a high variability and some fish accumulated PCBs at levels similar to those of fish from impacted areas. While inter-sex differences were limited, the season and the morphotype appeared to have the most influence. Fish captured in summer had muscle PCB concentrations about three times higher than those caught in spring and the ‘river’ morphotype of brook trout showed the highest PCB levels.