An investigation of the kinetic processes influencing mercury emissions from sand and soil samples of varying thickness

Mercury flux from HgCl2-treated sand and untreated soil samples of varying thickness (0.5-15 mm) were measured in dark and light under a Teflon dynamic flux chamber. Mean emissions over a 5.5-d sampling period showed an increase with depth for sand samples between 0.5 and 2 mm, but increasing depth above 2 mm had no effect. First-order kinetic models showed strong goodness of fit to the data and explained a high degree ofvariability in the emissions profile of all sand samples (R = 0.70-0.98). Soil samples showed an initial emissions peak that was not correlated with depth, suggesting a very shallow process at work. However, longer-term "baseline" emissions, measured as mean emissions between days 4.5 and 5.5, did show a relationship with depth. First-order kinetic models showed good fit for soil samples up to 4 mm thick (R2 = 0.66-0.91); however, thicker samples did not show a consistent fit to first- or second-order kinetic models (1 degree R2 = 0.00-0.46; 2 degree R2 = 0.00-0.54). The data suggest that mercury emissions from soil samples may follow a multicomponent model for which more     

Alternative poultry litter storage for improved transportation and use as a soil amendment

Transportation of poultry litter out of nutrient limited watersheds such as the Illinois River basin (eastern Oklahoma) is a logical solution for minimizing phosphorus (P) losses from soils to surface waters. Transportation costs are basedon mass of load and distance transported. This study investigated an alternative litter storage technique designed to promote carbon (C) degradation, thereby concentrating nutrients for the purpose of decreasing transportation costs through decreased mass. Poultry litter was stored in 0.90-Mg conical piles under semipermeable tarps and adjusted to 40% moisture content, tested with and without addition of alum (aluminum sulfate). additional study was conducted using 3.6-Mg piles under the same conditions, except tested with and without use of aeration pipes. Samples were analyzed before and after (8 wk) storage. Litter mass degradation (i.e., loss in mass due to organic matter decomposition) was estimated on the basis of changes in litter total P contents. Additional characterization included pH, total nutrients, moisture content, total C, and degree of humification. Litter storage significantly decreased litter mass (16 to 27%), concentrated nutrients such as P and potassium (K) and increased proportion of fulvic and humic acids. The addition of aeration pipes increased mass degradationrelative to piles without aeration pipes. Nitrogen volatilization losses were minimized with alum additions. Increases in P and K concentrations resulted in greater monetary value per unit mass compared with fresh litter. Such increases translate to increased litter shipping distance and cost savings of $17.2 million over 25 yr for litter movement out of eastern Oklahoma.     

Estimation of Mussel Population Response to Hydrologic Alteration in a Southeastern U.S. Stream

The southeastern United States has experienced severe, recurrent drought, rapid human population growth, and increasing agricultural irrigation during recent decades, resulting in greater demand for the water resources. During the same time period, freshwater mussels (Unioniformes) in the region have experienced substantial population declines. Consequently, there is growing interest in determining how mussel population declines are related to activities associated with water resource development. Determining the causes of mussel population declines requires, in part, an understanding of the factors influencing mussel population dynamics. We developed Pradel reverse-time, tag-recapture models to estimate survival, recruitment, and population growth rates for three federally endangered mussel species in the Apalachicola–Chattahoochee–Flint River Basin, Georgia. The models were parameterized using mussel tag-recapture data collected over five consecutive years from Sawhatchee Creek, located in southwestern Georgia. Model estimates indicated that mussel survival was strongly and negatively related to high flows during the summer, whereas recruitment was strongly and positively related to flows during the spring and summer. Using these models, we simulated mussel population dynamics under historic (1940–1969) and current (1980–2008) flow regimes and under increasing levels of water use to evaluate the relative effectiveness of alternative minimum flow regulations. The simulations indicated that the probability of simulated mussel population extinction was at least 8 times greater under current hydrologic regimes. In addition, simulations of mussel extinction under varying levels of water use indicated that the relative risk of extinction increased with increased water use across a range of minimum flow regulations. The simulation results also indicated that our estimates of the effects of water use on mussel extinction were influenced by the assumptions about the dynamics of the system, highlighting the need for further study of mussel population dynamics.     

Generalized functional responses for species distributions

Researchers employing resource selection functions (RSFs) and other related methods aim to detect correlates of space-use and mitigate against detrimental environmental change. However, an empirical model fit to data from one place or time is unlikely to capture species responses under different conditions because organisms respond nonlinearly to changes in habitat availability. This phenomenon, known as a functional response in resource selection, has been debated extensively in the RSF literature but continues to be ignored by practitioners for lack of a practical treatment. We therefore extend the RSF approach to enable it to estimate generalized functional responses (GFRs) from spatial data. GFRs employ data from several sampling instances characterized by diverse profiles of habitat availability. By modeling the regression coefficients of the underlying RSF as functions of availability, GFRs can account for environmental change and thus predict population distributions in new environments. We formulate the approach as a mixed-effects model so that it is estimable by readily available statistical software. We illustrate its application using (1) simulation and (2) wolf home-range telemetry. Our results indicate that GFRs can offer considerable improvements in estimation speed and predictive ability over existing mixed-effects approaches.     

An opilioacarid mite in Cretaceous Burmese amber

A fossil opilioacarid mite (Parasitiformes: Opilioacarida) in Burmese amber is described as ?Opilioacarus groehni sp. nov. This ca. 99 Ma record (Upper Cretaceous: Cenomanian) represents only the third fossil example of this putatively basal mite lineage, the others originating from Eocene Baltic amber (ca. 44–49 Ma). Our new record is not only the oldest record of Opilioacarida, but it is also one of the oldest examples of the entire Parasitiformes clade. The presence of Opilioacarida—potentially Opiloacarus—in the Cretaceous of SE Asia suggests that some modern genus groups were formerly more widely distributed across the northern hemisphere, raising questions about previously suggested Gondwanan origins for these mites.     

Exploring the influence of outdoor recreation participation on pro-environmental behaviour in a demographically diverse population

This study used structural equation modelling to examine the effects of socio-demographic variables and outdoor recreation participation on pro-environmental behaviour (PEB) among an ethnically diverse population of adult state-park visitors near Atlanta, Georgia, USA (N?=?319). Data collected through intercept surveys at three state parks were used to examine interactions among potential predictors of PEB, including socio-demographics (ethnicity, gender, education, and income), outdoor recreation participation (during childhood and adulthood), and environmental value orientations (biocentric and anthropocentric). The best fitting model accounted for 40% of the variance in self-reported PEB and indicated the strongest positive relationship between adult outdoor recreation participation and PEB (β?=?0.54, t?=?5.70). Biocentric and anthropocentric value orientation scores were also significant antecedents of PEB (β?=?0.17, t?=?1.99, and β?=?0.19, t?=?2.56, respectively), and both were influenced by socio-demographic variables. Overall, results suggest that a diverse public's environmental ethos and propensity to engage in PEBs could be influenced by outdoor recreation opportunities.     

A Systems-Based Conceptual Framework for Assessing the Determinants of a Social License to Operate in the Mining Industry

The concept of a “social license to operate” (SLO) was coined in the 1990s and gained popularity as one way in which “social” considerations can be addressed in mineral development decision making. The need for a SLO implies that developers require the widespread approval of local community members for their projects to avoid exposure to potentially costly conflict and business risks. Only a limited amount of scholarship exists on the topic, and there is a need for research that specifically addresses the complex and changeable nature of SLO outcomes. In response to these challenges, this paper advances a novel, systems-based conceptual framework for assessing SLO determinants and outcomes in the mining industry. Two strands of systems theory are specifically highlighted—complex adaptive systems and resilience—and the roles of context, key system variables, emergence, change, uncertainty, feedbacks, cross-scale effects, multiple stable states, thresholds, and resilience are discussed. The framework was developed from the results of a multi-year research project which involved international mining case study investigations, a comprehensive literature review, and interviews conducted with mining stakeholders and observers. The framework can help guide SLO analysis and management efforts, by encouraging users to account for important contextual and complexity-oriented elements present in SLO settings. We apply the framework to a case study in Alaska, USA before discussing its merits and challenges. We also illustrate knowledge gaps associated with applications of complex adaptive systems and resilience theories to the study of SLO dynamics, and discuss opportunities for future research.     

The problem and promise of scale dependency in community phylogenetics

The problem of scale dependency is widespread in investigations of ecological communities. Null model investigations of community assembly exemplify the challenges involved because they typically include subjectively defined "regional species pools." The burgeoning field of community phylogenetics appears poised to face similar challenges. Our objective is to quantify the scope of the problem of scale dependency by comparing the phylogenetic structure of assemblages across contrasting geographic and taxonomic scales. We conduct phylogenetic analyses on communities within three tropical forests, and perform a sensitivity analysis with respect to two scaleable inputs: taxonomy and species pool size. We show that (1) estimates of phylogenetic overdispersion within local assemblages depend strongly on the taxonomic makeup of the local assemblage and (2) comparing the phylogenetic structure of a local assemblage to a species pool drawn from increasingly larger geographic scales results in an increased signal of phylogenetic clustering. We argue that, rather than posing a problem, "scale sensitivities" are likely to reveal general patterns of diversity that could help identify critical scales at which local or regional influences gain primacy for the structuring of communities. In this way, community phylogenetics promises to fill an important gap in community ecology and biogeography research.     

Air quality modeling of hazardous pollutants: current status and future directions

The current requirements and status of air quality modeling of hazardous pollutants are reviewed. Many applications require the ability to predict the local impacts from industrial sources or large roadways as needed for community health characterization and evaluating environmental justice concerns. Such local-scale modeling assessments can be performed by using Gaussian dispersion models. However, these models have a limited ability to handle chemical transformations. A new generation of Eulerian grid-based models is now capable of comprehensively treating transport and chemical transformations of air toxics. However, they typically have coarse spatial resolution, and their computational requirements increase dramatically with finer spatial resolution. The authors present and discuss possible advanced approaches that can combine the grid-based models with local-scale information.