ALBERT

Description: IJERPH, Vol. 14, Pages 947: Surface Sampling Collection and Culture Methods for Escherichia coli in Household Environments with High Fecal Contamination International Journal of Environmental Research and Public Health doi: 10.3390/ijerph14080947 Authors: Natalie Exum Margaret Kosek Meghan Davis Kellogg Schwab Empiric quantification of environmental fecal contamination is an important step toward understanding the impact that water, sanitation, and hygiene interventions have on reducing enteric infections. There is a need to standardize the methods used for surface sampling in field studies that examine fecal contamination in low-income settings. The dry cloth method presented in this manuscript improves upon the more commonly used swabbing technique that has been shown in the literature to have a low sampling efficiency. The recovery efficiency of a dry electrostatic cloth sampling method was evaluated using Escherichia coli and then applied to household surfaces in Iquitos, Peru, where there is high fecal contamination and enteric infection. Side-by-side measurements were taken from various floor locations within a household at the same time over a three-month period to compare for consistency of quantification of E. coli bacteria. The dry cloth sampling method in the laboratory setting showed 105% (95% Confidence Interval: 98%, 113%) E. coli recovery efficiency off of the cloths. The field application demonstrated strong agreement of side-by-side results (Pearson correlation coefficient for dirt surfaces was 0.83 (p < 0.0001) and 0.91 (p < 0.0001) for cement surfaces) and moderate agreement for results between entrance and kitchen samples (Pearson (0.53, p < 0.0001) and weighted Kappa statistic (0.54, p < 0.0001)). Our findings suggest that this method can be utilized in households with high bacterial loads using either continuous (quantitative) or categorical (semi-quantitative) data. The standardization of this low-cost, dry electrostatic cloth sampling method can be used to measure differences between households in intervention and non-intervention arms of randomized trials.

Description: Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs ( Lithobates sylvaticus ) in North America. Using long-term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long-term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species-interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate. Demographic processes and climate interact and vary across a species’ range to determine how species’ distributions will respond to climate change. We predicted that populations at the extremes of a species’ climate envelope are most sensitive to climate shifts. We tested this using a dynamic species distribution model linking demographic rates to variation in climate for wood frogs ( Lithobates sylvaticus ) in North America. Sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope.

Description: Human activity has significantly increased the deposition of nitrogen (N) on terrestrial ecosystems over pre-industrial levels leading to a multitude of effects including losses of biodiversity, changes in ecosystem functioning, and impacts on human well-being. It is challenging to explicitly link the level of deposition on an ecosystem to the cascade of ecological effects triggered and ecosystem services affected, because of the multitude of possible pathways in the N cascade. To address this challenge, we report on the activities of an expert workshop to synthesize information on N-induced terrestrial eutrophication from the published literature and to link critical load exceedances with human beneficiaries by using the STressor–Ecological Production function–final ecosystem Services Framework and the Final Ecosystem Goods and Services Classification System (FEGS-CS). We found 21 N critical loads were triggered by N deposition (ranging from 2 to 39 kg N·ha −1 ·yr −1 ), which cascaded to distinct beneficiary types through 582 individual pathways in the five ecoregions examined (Eastern Temperate Forests, Marine West Coast Forests, Northwestern Forested Mountains, North American Deserts, Mediterranean California). These exceedances ultimately affected 66 FEGS across a range of final ecosystem service categories (21 categories, e.g., changes in timber production, fire regimes, and native plant and animal communities) and 198 regional human beneficiaries of different types. Several different biological indicators were triggered in different ecosystems, including grasses and/or forbs (33% of all pathways), mycorrhizal communities (22%), tree species (21%), and lichen biodiversity (11%). Ecoregions with higher deposition rates for longer periods tended to have more numerous and varied ecological impacts (e.g., Eastern Temperate Forests, eight biological indicators) as opposed to other ecoregions (e.g., North American Deserts and Marine West Coast Forests each with one biological indicator). Nonetheless, although ecoregions differed by ecological effects from terrestrial eutrophication, the number of FEGS and beneficiaries impacted was similar across ecoregions. We found that terrestrial eutrophication affected all ecosystems examined, demonstrating the widespread nature of terrestrial eutrophication nationally. These results highlight which people and ecosystems are most affected according to present knowledge, and identify key uncertainties and knowledge gaps to be filled by future research.

Description: Climate, Vol. 5, Pages 76: The Relationship between Atmospheric Carbon Dioxide Concentration and Global Temperature for the Last 425 Million Years Climate doi: 10.3390/cli5040076 Authors: W. Davis Assessing human impacts on climate and biodiversity requires an understanding of the relationship between the concentration of carbon dioxide (CO2) in the Earth’s atmosphere and global temperature (T). Here I explore this relationship empirically using comprehensive, recently-compiled databases of stable-isotope proxies from the Phanerozoic Eon (~540 to 0 years before the present) and through complementary modeling using the atmospheric absorption/transmittance code MODTRAN. Atmospheric CO2 concentration is correlated weakly but negatively with linearly-detrended T proxies over the last 425 million years. Of 68 correlation coefficients (half non-parametric) between CO2 and T proxies encompassing all known major Phanerozoic climate transitions, 77.9% are non-discernible (p > 0.05) and 60.0% of discernible correlations are negative. Marginal radiative forcing (ΔRFCO2), the change in forcing at the top of the troposphere associated with a unit increase in atmospheric CO2 concentration, was computed using MODTRAN. The correlation between ΔRFCO2 and linearly-detrended T across the Phanerozoic Eon is positive and discernible, but only 2.6% of variance in T is attributable to variance in ΔRFCO2. Of 68 correlation coefficients (half non-parametric) between ΔRFCO2 and T proxies encompassing all known major Phanerozoic climate transitions, 75.0% are non-discernible and 41.2% of discernible correlations are negative. Spectral analysis, auto- and cross-correlation show that proxies for T, atmospheric CO2 concentration and ΔRFCO2 oscillate across the Phanerozoic, and cycles of CO2 and ΔRFCO2 are antiphasic. A prominent 15 million-year CO2 cycle coincides closely with identified mass extinctions of the past, suggesting a pressing need for research on the relationship between CO2, biodiversity extinction, and related carbon policies. This study demonstrates that changes in atmospheric CO2 concentration did not cause temperature change in the ancient climate.

Description: Understanding the responses of biodiversity to different land use regimes is critical for managing biodiversity in the face of future land use change. However, there is still significant uncertainty around how consistent the responses of different taxonomic groups to land use change are. Here, we use a combination of high-throughput environmental DNA sequencing and traditional field-based survey methods to examine how patterns of richness and community composition correlate among four domains/kingdoms (bacteria, fungi, plants, and metazoans) and the four most-abundant animal taxonomic groups (arachnids, Collembola, insects, and nematodes) across five different land use types (natural forest, planted forest, unimproved grassland, improved grassland, and vineyards). Richness for each taxonomic group varied between land use types, yet different taxa showed inconsistent responses to land use, and their richness was rarely correlated. This contrasted with community composition of taxonomic groups, for which there was relatively good discrimination of land use types and there was strong correlation between group responses. We found little evidence for consistent drivers of taxonomic richness, yet identified several significant drivers of community composition that were shared across many groups. Drivers of composition were not the same as the drivers of diversity, suggesting diversity and composition are independently controlled. While land use intensification has been viewed as having generally negative effects on biodiversity, our results provide evidence that different taxa respond divergently across different land uses. Further, our study demonstrates the power of high-throughput sequencing of environmental DNA as a tool for addressing broad ecological patterns relating to landscape biodiversity.

Description: Increases in atmospheric CO 2 levels and associated ocean changes are expected to have dramatic impacts on marine ecosystems. Although the Southern Ocean is experiencing some of the fastest rates of change, few studies have explored how Antarctic fishes may be affected by co-occurring ocean changes, and even fewer have examined early life stages. To date, no studies have characterized potential trade-offs in physiology and behavior in response to projected multiple climate change stressors (ocean acidification and warming) on Antarctic fishes. We exposed juvenile emerald rockcod Trematomus bernacchii to three P CO 2 treatments (~450, ~850 and ~1200 μatm P CO 2 ) at two temperatures (-1º or 2°C). After 2, 7, 14, and 28 days, metrics of physiological performance including cardiorespiratory function (heart rate [ f H ] and ventilation rate [ f V ]), metabolic rate (ṀO 2 ), and cellular enzyme activity were measured. Behavioral responses, including scototaxis, activity, exploration and escape response were assessed after 7 and 14 days. Elevated P CO 2 independently had little impact on either physiology or behavior in juvenile rockcod, whereas warming resulted in significant changes across acclimation time. After 14 days, f H , f V and ṀO 2 significantly increased with warming, but not with elevated P CO 2 . Increased physiological costs were accompanied by behavioral alterations including increased dark zone preference up to 14%, reduced activity by 12%, as well as reduced escape time suggesting potential trade-offs in energetics. After 28 days, juvenile rockcod demonstrated a degree of temperature compensation as f V , ṀO 2 , and cellular metabolism significantly decreased following the peak at 14 days; however, temperature compensation was only evident in the absence of elevated P CO 2 . Sustained increases in f V and ṀO 2 after 28 days exposure to elevated P CO 2 indicate additive ( f V ) and synergistic (ṀO 2 ) interactions occurred in combination with warming. Stressor-induced energetic trade-offs in physiology and behavior may be an important mechanism leading to vulnerability of Antarctic fishes to future ocean change. This article is protected by copyright. All rights reserved.

Description: Coal seam gas production involves generation and management of large amounts of co-produced water. One of the most suitable methods of management is injection into deep aquifers. Field injection trials may be used to support the predictions of anticipated hydrological and geochemical impacts of injection. The present work employs reactive transport modeling (RTM) for a comprehensive analysis of data collected from a trial where arsenic mobilization was observed. Arsenic sorption behavior was studied through laboratory experiments, accompanied by the development of a surface complexation model (SCM). A field-scale RTM that incorporated the laboratory-derived SCM was used to simulate the data collected during the field injection trial and then to predict the long-term fate of arsenic. We propose a new practical procedure which integrates laboratory and field-scale models using a Monte Carlo type uncertainty analysis and alleviates a significant proportion of the computational effort required for predictive uncertainty quantification. The results illustrate that both arsenic desorption under alkaline conditions and pyrite oxidation have likely contributed to the arsenic mobilization that was observed during the field trial. The predictive simulations show that arsenic concentrations would likely remain very low if the potential for pyrite oxidation is minimized through complete deoxygenation of the injectant. The proposed modeling and predictive uncertainty quantification method can be implemented for a wide range of groundwater studies that investigate the risks of metal(loid) or radionuclide contamination.