A study of metal and metalloid contaminant availability in Antarctic marine sediments

Previous studies of impacted sites near Casey Station, Antarctica, have revealed elevated concentrations of metals and metalloids, particularly Cd, Cu, Fe, Pb, Sn and Zn in marine sediments. However, attempts to understand the availability and mobility of contaminant elements have not provided a true understanding of speciation. The current work shows, for the first time, that sediments in Brown Bay, an embayment adjacent to the Thala Valley waste disposal site, have elevated concentrations of sulfide, well in excess of that required to bind contaminant metals such as Cd, Cu, Pb and Zn. Furthermore, sediment characterisation using the BCR sequential extraction scheme has shown metal partitioning consistent with sulfides being the controlling factor in metal availability, thus explaining the low porewater concentrations of these metals. The speciation of Sn in Brown Bay, however, is still unclear with the BCR sequential extraction scheme partitioning Sn predominantly into the residual fraction despite Sn being readily extracted by dilute HCl.     

Forest Health Monitoring in the United States: First Four Years

To address the need for more effective methods for evaluating and assessing forest ecosystem health, the USDA-Forest Service and the US Environmental Protection Agency through its Environmental Monitoring and Assessment Program developed the Forest Health Monitoring program. The program was initiated in 1990 and by 1994 was present in the major areas of the United States. This paper presents an overview of the program, the indicators and methods developed for the program, and some of the results after four years of monitoring and research.     

Collaborative Modeling for Decision Support in Water Resources: Principles and Best Practices

Collaborative Modeling for Decision Support integrates collaborative modeling with participatory processes to inform natural resources decisions. Practitioners and advocates claim that the approach will lead to better water management, balancing interests more effectively and reducing the likelihood of costly legal delays. These claims are easy to make, but the benefits will only be realized if the process is conducted effectively. To provide guidance for how to conduct an effective collaborative modeling process, a task committee cosponsored by the Environmental Water Resources Institute (EWRI) of the American Society of Civil Engineers and by the U.S. Army Corps of Engineers' Institute for Water Resources developed a set of Principles and Best Practices for anyone who might convene or conduct collaborative modeling processes. The guidance is intended for both conflict resolution professionals and modelers, and our goal is to integrate these two fields in a way that will improve water resources planning and decision making. Here, the set of eight principles is presented along with a selection of associated best practices, illustrated by two different case examples. The complete document is available at: http://www.computeraideddisputeresolution.us/bestpractices/ .     

Functional and phylogenetic diversity as predictors of biodiversity--ecosystem-function relationships

How closely does variability in ecologically important traits reflect evolutionary divergence? The use of phylogenetic diversity (PD) to predict biodiversity effects on ecosystem functioning, and more generally the use of phylogenetic information in community ecology, depends in part on the answer to this question. However, comparisons of the predictive power of phylogenetic diversity and functional diversity (FD) have not been conducted across a range of experiments. To address how phylogenetic diversity and functional trait variation control biodiversity effects on biomass production, we summarized the results of 29 grassland plant experiments where both the phylogeny of plant species used in the experiments is well described and where extensive trait data are available. Functional trait variation was only partially related to phylogenetic distances between species, and the resulting FD values therefore correlate only partially with PD. Despite these differences, FD and PD predicted biodiversity effects across all experiments with similar strength, including in subsets that excluded plots with legumes and that focused on fertilization experiments. Two- and three-trait combinations of the five traits used here (leaf nitrogen percentage, height, specific root length, leaf mass per unit area, and nitrogen fixation) resulted in the FD values with the greatest predictive power. Both PD and FD can be valuable predictors of the effect of biodiversity on ecosystem functioning, which suggests that a focus on both community trait diversity and evolutionary history can improve understanding of the consequences of biodiversity loss.     

Assessing stream restoration effectiveness at reducing nitrogen export to downstream waters

The degradation of headwater streams is common in urbanized coastal areas, and the role these streams play in contributing to downstream pollution is a concern among natural resource managers and policy makers. Thus, many urban stream restoration efforts are increasingly focused on reducing the downstream flux of pollutants. In regions that suffer from coastal eutrophication, it is unclear whether stream restoration does in fact reduce nitrogen (N) flux to downstream waters and, if so, by how much and at what cost. In this paper, we evaluate whether stream restoration implemented to improve water quality of urban and suburban streams in the Chesapeake Bay region, USA, is effective at reducing the export of N in stream flow to downstream waters. We assessed the effectiveness of restored streams positioned in the upland vs. lowland regions of Coastal Plain watershed during both average and stormflow conditions. We found that, during periods of low discharge, lowland streams that receive minor N inputs from groundwater or bank seepage reduced in-stream N fluxes. Furthermore, lowland streams with the highest N concentrations and lowest discharge were the most effective. During periods of high flow, only those restoration projects that converted lowland streams to stream-wetland complexes seemed to be effective at reducing N fluxes, presumably because the design promoted the spillover of stream flow onto adjacent floodplains and wetlands. The observed N-removal rates were relatively high for stream ecosystems, and on the order of 5% of the inputs to the watershed. The dominant forms of N entering restored reaches varied during low and high flows, indicating that N uptake and retention were controlled by distinctive processes during different hydrological conditions. Therefore, in order for stream restoration to effectively reduce N fluxes exported to downstream waters, restoration design should include features that enhance the processing and retention of different forms of N, and for a wide range of flow conditions. The use of strategic designs that match the dominant attributes of a stream such as position in the watershed, influence of groundwater, dominant flow conditions, and N concentrations is crucial to assure the success of restoration.     

A global community-sourced assessment of the state of conservation technology

Conservation technology holds the potential to vastly increase conservationists’ ability to understand and address critical environmental challenges, but systemic constraints appear to hamper its development and adoption. Understanding of these constraints and opportunities for advancement remains limited. We conducted a global online survey of 248 conservation technology users and developers to identify perceptions of existing tools’ current performance and potential impact, user and developer constraints, and key opportunities for growth. We also conducted focus groups with 45 leading experts to triangulate findings. The technologies with the highest perceived potential were machine learning and computer vision, eDNA and genomics, and networked sensors. A total of 95%, 94%, and 92% respondents, respectively, rated them as very helpful or game changers. The most pressing challenges affecting the field as a whole were competition for limited funding, duplication of efforts, and inadequate capacity building. A total of 76%, 67%, and 55% respondents, respectively, identified these as primary concerns. The key opportunities for growth identified in focus groups were increasing collaboration and information sharing, improving the interoperability of tools, and enhancing capacity for data analyses at scale. Some constraints appeared to disproportionately affect marginalized groups. Respondents in countries with developing economies were more likely to report being constrained by upfront costs, maintenance costs, and development funding (p = 0.048, odds ratio [OR] = 2.78; p = 0.005, OR = 4.23; p = 0.024, OR = 4.26), and female respondents were more likely to report being constrained by development funding and perceived technical skills (p = 0.027, OR = 3.98; p = 0.048, OR = 2.33). To our knowledge, this is the first attempt to formally capture the perspectives and needs of the global conservation technology community, providing foundational data that can serve as a benchmark to measure progress. We see tremendous potential for this community to further the vision they define, in which collaboration trumps competition; solutions are open, accessible, and interoperable; and user-friendly processing tools empower the rapid translation of data into conservation action. Article impact statement: Addressing financing, coordination, and capacity-building constraints is critical to the development and adoption of conservation technology.     

Physiological and Biochemical Effects of Atmospheric Oxidants on Plants

Photochemically produced oxidants in the atmosphere cause injury to plants primarily through inhibition of basic metabolic processes. Plants vary in their response to the oxidants and this variation must be dependent in part on the variation in metabolic activity with age or environmental conditions for growth, to a large degree not understood. Data are presented in this paper to show: (1) The changes in permeability of leaf tissue to exogenous substrate and in catabolic utilization of this substrate after exposure of plants to ozone but before visible symptoms appear; (2) The change in leaf carbohydrates as a result of exposure to ozone; (3) The protective effect of red light (700 mμ) during exposure of bean plants to peroxyacetyl nitrate (PAN); (4) The correlation of sulfhydryl (SH) content in bean leaf tissue with age of plants and light regime; and (5) Effect of light regime and age of plants on incorporation of C¹⁴ from C¹⁴-PAN by bean leaf tissue.     

Field verification of sound attenuation modeling and air emission testing in support of missile motor disposal activities

The U.S. Department of Defense-approved activities conducted at the Utah Test and Training Range (UTTR) include both operational readiness test firing of intercontinental ballistic missile (ICBM) motors, as well as the destruction of obsolete or otherwise unusable ICBM motors through open burn/open detonation (OB/OD). Within the Utah Division of Air Quality, these activities have been identified as having the potential to generate unacceptable noise levels, as well as significant amounts of volatile organic compounds (VOCs). Hill Air Force Base, UT, has completed a series of field tests at the UTTR in which sound-monitoring surveillance of OB/OD activities was conducted to validate the Sound Intensity Prediction System (SIPS) model. Using results generated by the SIPS model to support the decision to detonate, the UTTR successfully disposed of missile motors having an aggregate net explosive weight (NEW) of 81,374 lb without generating adverse noise levels within populated areas. In conjunction with collecting noise-monitoring data, air emissions were collected to support the development of air emission factors for both static missile motor firings and OB/OD activities. Through the installation of 15 ground-based air samplers, the generation of combustion-fixed gases, VOCs, and chlorides was monitored during the 81,374-lb NEW detonation event. Comparison of field measurements to predictions generated from the US Navy energetic combustion pollutant formation model, POLU4WN, indicated that, as the detonation fire ball expanded, organic compounds, as well as CO, continued to oxidize as the combustion gases mixed with ambient air. VOC analysis of air samplers confirmed the presence of chloromethane, vinyl chloride, benzene, toluene, and 2-methyl-1-propene. Qualitative chloride analysis indicated that gaseous HCl was generated at low concentrations, if at all.     

Use of noise attenuation modeling in managing missile motor detonation activities

The Sound Intensity Prediction System (SIPS) and Blast Operation Overpressure Model (BOOM) are semiempirical sound models that are employed by the Utah Test and Training Range (UTTR) to predict whether noise levels from the detonation of large missile motors will exceed regulatory thresholds. Field validation of SIPS confirmed that the model was effective in limiting the number of detonations of large missile motors that could potentially result in a regulatory noise exceedance. Although the SIPS accurately predicted the impact of weather on detonation noise propagation, regulators have required that the more conservative BOOM model be employed in conjunction with SIPS in evaluating peak noise levels in populated areas. By simultaneously considering the output of both models, in 2001, UTTR detonated 104 missile motors having net explosive weights (NEW) that ranged between 14,960 and 38,938 lb without a recorded public noise complaint. Based on the encouraging results, the U.S. Department of Defense is considering expanding the application of these noise models to support the detonation of missile motors having a NEW of 81,000 lb. Recent modeling results suggest that, under appropriate weather conditions, missile motors containing up to 96,000 lb NEW can be detonated at the UTTR without exceeding the regulatory noise limit of 134 decibels (dB).