Behavior of potentially toxic elements from stoker-boiler fly ash in Interior Alaska: paired batch leaching and solid-phase characterization

Environmental Science and Pollution Research - Despite significant investigation of fly ash spills and mineralogical controls on the release of potentially toxic elements (PTEs) from fly ash,...     

Role of plant growth promoting rhizobacteria in the remediation of metal contaminated soils

Pollution of the biosphere by the toxic metals is a global threat that has accelerated dramatically since the beginning of industrial revolution. The primary source of this pollution includes the industrial operations such as mining, smelting, metal forging, combustion of fossil fuels and sewage sludge application in agronomic practices. The metals released from these sources accumulate in soil and in turn, adversely affect the microbial population density and physico-chemical properties of soils, leading to the loss of soil fertility and yield of crops. The heavy metals in general cannot be biologically degraded to more or less toxic products and hence, persist in the environment. Conventional methods used for metal detoxification produce large quantities of toxic products and are cost-effective. The advent of bioremediation technology has provided an alternative to conventional methods for remediating the metal-poisoned soils. In metal-contaminated soils, the natural role of metal-tolerant plant growth promoting rhizobacteria in maintaining soil fertility is more important than in conventional agriculture, where greater use of agrochemicals minimize their significance. Besides their role in metal detoxification/removal, rhizobacteria also promote the growth of plants by other mechanisms such as production of growth promoting substances and siderophores. Phytoremediation is another emerging low-cost in situ technology employed to remove pollutants from the contaminated soils. The efficiency of phytoremediation can be enhanced by the judicious and careful application of appropriate heavy-metal tolerant, plant growth promoting rhizobacteria including symbiotic nitrogen-fixing organisms. This review presents the results of studies on the recent developments in the utilization of plant growth promoting rhizobacteria for direct application in soils contaminated with heavy metals under a wide range of agro-ecological conditions with a view to restore contaminated soils and consequently, promote crop productivity in metal-polluted soils across the globe and their significance in phytoremediation.     

Effects of experimental protocol on global vegetation model accuracy: A comparison of simulated and observed vegetation patterns for Asia

Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO₂ concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO₂ concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO₂ concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.     

Managing plant population spread: prediction and analysis using a simple model

Models can be used to direct the management of population spread for the control of invasives or to encourage species of conservation value. Analytical models are attractive because of their theoretical basis and limited data requirements, but there is concern that their simplicity may limit their practical utility. We address the applied use of simple models in a study of a declining annual herb, Rhinanthus minor. We parameterized a population-spread model using field data on demography and dispersal for four management systems: grazed only (GR), hay-cut once (H1), hay-cut twice (H2), and hay-cut with autumn grazing (HG). Within a replicated experiment we measured spread rates of introduced R. minor populations over eight years. The modeled and measured spread rates were very similar in terms of both patterns of management effects and absolute values, so that in both cases HG > H2, H1 > GR. The treatments affected both dispersal and demography (establishment and survival) and so we used decomposition approaches to analyze the major causes of differences in population spread. Increased dispersal under hay-cutting was more important than demographic changes and accounted for approximately 70% of the differences in spread rate between the hay-cut and grazed-only treatments. Furthermore, management effects on the tail of the dispersal curve were by far the most critical in governing spread. This study suggests that simple models can be used to inform practical conservation management, and we demonstrate straightforward uses of our model to predict the impacts of different management strategies. While simple models can give accurate projections, we emphasize that they must be parameterized with high-quality data gathered at the appropriate spatial scale.     

Plant diversity, CO2, and N influence inorganic and organic N leaching in grasslands

In nitrogen (N)-limited systems, the potential to sequester carbon depends on the balance between N inputs and losses as well as on how efficiently N is used, yet little is known about responses of these processes to changes in plant species richness, atmospheric CO2 concentration ([CO2]), and N deposition. We examined how plant species richness (1 or 16 species), elevated [CO2] (ambient or 560 ppm), and inorganic N addition (0 or 4 g x m(-2) x yr(-1)) affected ecosystem N losses, specifically leaching of dissolved inorganic N (DIN) and organic N (DON) in a grassland field experiment in Minnesota, USA. We observed greater DIN leaching below 60 cm soil depth in the monoculture plots (on average 1.8 and 3.1 g N x m(-2) x yr(-1) for ambient N and N-fertilized plots respectively) than in the 16-species plots (0.2 g N x m(-2) x yr(-1) for both ambient N and N-fertilized plots), particularly when inorganic N was added. Most likely, loss of complementary resource use and reduced biological N demand in the monoculture plots caused the increase in DIN leaching relative to the high-diversity plots. Elevated [CO2] reduced DIN concentrations under conditions when DIN concentrations were high (i.e., in N-fertilized and monoculture plots). Contrary to the results for DIN, DON leaching was greater in the 16-species plots than in the monoculture plots (on average 0.4 g N x m(-2) x yr(-1) in 16-species plots and 0.2 g N x m(-2) x yr(-1) in monoculture plots). In fact, DON dominated N leaching in the 16-species plots (64% of total N leaching as DON), suggesting that, even with high biological demand for N, substantial amounts of N can be lost as DON. We found no significant main effects of elevated [CO2] on DIN or DON leaching; however, elevated [CO2] reduced the positive effect of inorganic N addition on DON leaching, especially during the second year of observation. Our results suggest that plant species richness, elevated [CO2], and N deposition alter DIN loss primarily through changes in biological N demand. DON losses can be as large as DIN loss but are more sensitive to organic matter production and turnover.     

Plant competition varies with community composition in an edaphically complex landscape

There is currently no consensus on how physical and biological factors affect competitive intensity. Tests of whether competitive intensity varies along axes of environmental change have commonly been conducted in systems with a single strong environmental gradient, such as productivity, a soil resource, or an environmental stress. Frequently, these same axes are associated with changes in species composition, yet few studies have asked whether shifts in the identity of competitors affect competitive intensity. We ask whether resources (nutrients, water), stressors (heavy metals, Ca:Mg ratio), productivity (aboveground biomass), or species identity (an ordination axis of plant community composition) were the best predictors of the intensity of competition in a heterogeneous grassland landscape that included multiple independent environmental gradients. The reproductive fitness of six annual plant species was measured in the presence and absence of competitors and used to calculate relative interaction intensity (RII). We found that RII was best predicted by community composition. Nutrient availability was also important, and a post hoc test showed that competitive intensity was best explained by the combined effects of community composition and nutrient availability. We argue that community composition may be the most effective metric for predicting competitive intensity in many ecosystems because it includes both the competitive effects of the local community and information about covarying environmental characteristics.     

Five lessons to guide more effective biodiversity conservation message framing

Communication and advocacy approaches that influence attitudes and behaviors are key to addressing conservation problems, and the way an issue is framed can affect how people view, judge, and respond to an issue. Responses to conservation interventions can also be influenced by subtle wording changes in statements that may appeal to different values, activate social norms, influence a person's affect or mood, or trigger certain biases, each of which can differently influence the resulting engagement, attitudes, and behavior. We contend that by strategically considering how conservation communications are framed, they can be made more effective with little or no additional cost. Key framing considerations include, emphasizing things that matter to the audience, evoking helpful social norms, reducing psychological distance, leveraging useful biases, and, where practicable, testing messages. These lessons will help communicators think strategically about how to frame messages for greater effect.     

Bridging information domains to improve ecological understanding of biological invasions in a marine ecosystem

We devised a practical method for integrating information on 2 marine invasive species using 3 different approaches: standardized ecological monitoring, online-reporting databases, and surveys of anglers and crabbers. Focusing on 2 recently introduced species with different characteristics, the Asian shore crab (Hemigrapsus sanguineus) and Chinese mitten crab (Eriocheir sinensis), in the Hudson-Raritan watershed of New York and New Jersey, we used sensitivity analyses to explore the relative contribution of each information source to knowledge of species abundance and distribution. All 3 information sources contributed something unique to understanding abundance and distribution of the introduced crabs. Online and survey data on Asian shore crabs significantly affected predictions of abundance, whereas monitoring data did not. When survey data were omitted, abundance estimates were unchanged over time, but when they were included, the model predicted an increased abundance in 2012. All 3 data sets for the Asian shore crab significantly affected estimates of species coverage; surveys had the biggest influence, increasing range size by 4097.25 km². For the catadromous Chinese mitten crab, ecological monitoring data collected in freshwater shortly after the original sighting significantly shaped model estimates for abundance and documented the establishment phase of the mitten crab in an area outside the spatial scope of the surveyed resource users. However, the survey data significantly enlarged mitten crab range-size estimates by 6498.01 km². By demonstrating that data integration produced an image of the invasion process that would not have emerged had we used any 1 method individually, model results provide evidence for the advantages of an interdisciplinary approach.     

A comprehensive evaluation of two sample treatment procedures for the determination of emerging and historical halogenated flame retardants in biota

Environmental Science and Pollution Research - Two different sample preparation protocols for the determination of 37 emerging and historical halogenated flame retardants (HFRs) in marine tissues...     

Future Climate in the Yellowstone National Park Region and Its Potential Impact on Vegetation

Biotic responses to future changes in global climate are difficult to project for a particular region because the responses involve processes that operate at many spatial scales. This difficulty is exacerbated in mountainous regions, where future vegetation changes are often portrayed as simple upward displacements of vegetation zones in response to warming. We examine the scope of future responses that may occur in a mountainous area by illustrating the potential distributions of selected tree taxa in the region of Yellowstone National Park. The output of a coarse-resolution climate model that incorporated a doubling of carbon dioxide concentration in the atmosphere was interpolated onto a 5-minute grid of topographically adjusted climate data. The output was also used as input into statistical relationships between the occurrence of individual taxa and climate. The simulated vegetation changes include a combination of elevational and directional range adjustments. The range of high-elevation species decreases, and some species become regionally extirpated. The new communities have no analogue in the present-day vegetation because they mix low-elevation montane species currently in the region with extralocal species from the northern and central Rocky Mountains and Pacific Northwest. The projected climate changes within the Yellowstone region and the individualism displayed by species in their potential range adjustments are equal or greater than the changes seen in the paleoecologic record during previous warming intervals. Although the results support conservation strategies that include habitat connectivity, the magnitude of the changes may exceed the ability of species to adjust their ranges. The predicted patterns call into question the adequacy of current management objectives to cope with the scope of future changes.