Influence of Landscape Variability on Atmospheric Dispersion

Using idealized distributions of surface moisture, it is shown that with a significant synoptic prevailing flow over these regions of surface variability, dispersion is generally enhanced over heterogeneous surfaces as compared to horizontally homogeneous conditions. The importance of the heterogeneity becomes less, however, as the large scale wind speed increases and/or the spatial scale of the heterogeneities become less. This work also clearly demonstrates that the use of Gaussian regulatory models in areas of landscape variability is inappropriate.     

A Framework for Responding to Coral Disease Outbreaks that Facilitates Adaptive Management

Predicted increases in coral disease outbreaks associated with climate change have implications for coral reef ecosystems and the people and industries that depend on them. It is critical that coral reef managers understand these implications and have the ability to assess and reduce risk, detect and contain outbreaks, and monitor and minimise impacts. Here, we present a coral disease response framework that has four core components: (1) an early warning system, (2) a tiered impact assessment program, (3) scaled management actions and (4) a communication plan. The early warning system combines predictive tools that monitor the risk of outbreaks of temperature-dependent coral diseases with in situ observations provided by a network of observers who regularly report on coral health and reef state. Verified reports of an increase in disease prevalence trigger a tiered response of more detailed impact assessment, targeted research and/or management actions. The response is scaled to the risk posed by the outbreak, which is a function of the severity and spatial extent of the impacts. We review potential management actions to mitigate coral disease impacts and facilitate recovery, considering emerging strategies unique to coral disease and more established strategies to support reef resilience. We also describe approaches to communicating about coral disease outbreaks that will address common misperceptions and raise awareness of the coral disease threat. By adopting this framework, managers and researchers can establish a community of practice and can develop response plans for the management of coral disease outbreaks based on local needs. The collaborations between managers and researchers we suggest will enable adaptive management of disease impacts following evaluating the cost-effectiveness of emerging response actions and incrementally improving our understanding of outbreak causation.     

Effects of economic growth on biodiversity in the United States

For many citizens and policymakers, the empirical relationship between economic growth and biodiversity conservation has not been sufficiently established for purposes of identifying the types of economic policies amenable to biodiversity conservation. Some think economic growth conflicts with biodiversity conservation; others think economic growth conduces biodiversity conservation. With panel data from 1997‐2011, encompassing US continental states, we developed a series of statistical models to investigate the relationships among species endangerment, human population, and economic growth as indicated by GDP and per capita GDP. Species endangerment is highly correlated with population and GDP, and per capita GDP is a significant regressor of species endangerment. Across US continental states, competitive exclusion of non‐human species occurs via human economic growth and population growth.     

Assessment of heterogeneity of metal composition of fine particulate matter collected from eight U.S. counties using principal component analysis

The main objectives of this study are to (1) characterize chemical constituents of particulate matter (PM) and (2) compare overall differences in PM collected from eight US. counties. This project was undertaken as a part of a larger research program conducted by the Johns Hopkins Particulate Matter Research Center (JHPMRC). The goal of the JHPMRC is to explore the relationship between health effects and exposure to ambient PM of differing composition. The JHPMRC collected weekly filter-based ambient fine particle samples from eight US. counties between January 2008 and January 2010. Each sampling effort consisted of a 5-6-week sampling period. Filters were analyzed for 25 metals using inductively coupled plasma mass spectrometry (ICP-MS). Overall compositional differences were ranked by principal component analysis (PCA). The results showed that weekly concentrations of each element varied 3-40 times between the eight counties. PCA showed that the first five principal components explained 85% of the total variance. The authors found significant overall compositional differences in PM as the average of standardized principal component scores differed between the counties. These findings demonstrate PCA is a useful tool to identify the differences in PM compositional mixtures by county. These differences will be helpful for epidemiological and toxicological studies to help explain why health risks associated with PM exposure are different in locations with similar mass concentrations of PM.     

An ecological perspective on nanomaterial impacts in the environment

Growing concerns over the potential for unintended, adverse consequences of engineered nanoparticles (ENPs) in the environment have generated new research initiatives focused on understanding the ecological effects of ENPs. Almost nothing is currently known about the fate and transport of ENPs in environmental waters, soils, and sediments or about the biological impacts of ENPs in natural environments, and the bulk of modern nanotoxicogical research is focused on highly controlled laboratory studies with single species in simple media. In this paper, we provide an ecological perspective on the current state of knowledge regarding the likely environmental impacts of nanomaterials and propose a strategy for making rapid progress in new research in ecological nanoscience.     

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

Earthworm ecotoxicological assessments of pesticides used to treat seeds under tropical conditions

Ecotoxicological laboratory tests (lower-tier tests) are fundamental tools for assessing the toxicity of pesticides to soil organisms. In this study, using these tests under tropical conditions, we quantified the impact of the insecticides imidacloprid, fipronil, and thiametoxam, and the fungicides captan and carboxin + thiram, all of which are used in the chemical treatment of crop seeds, on the survival, reproduction, and behavior of Eisenia andrei (Oligochaeta). With the exception of imidacloprid, none of the pesticides tested caused mortality in E. andrei in artificial soils. The LC₅₀ of imidacloprid was estimated as 25.53 mg active ingredient kg^?1 of dry soil. Earthworm reproduction rates were reduced by imidacloprid (EC₅₀ = 4.07 mg kg^?1), fipronil (EC₂₀ = 23.16 mg kg^?1), carboxin + thiram (EC₅₀ = 56.38 mg kg^?1), captan (EC₅₀ = 334.84 mg kg^?1), and thiametoxam (EC₅₀ = 791.99 mg kg^?1). Avoidance behavior was observed in the presence of imidacloprid (AC₅₀ = 0.11 mg kg^?1), captan (AC₅₀ = 33.54 mg kg^?1), carboxin + thiram (AC₅₀ = 60.32 mg kg^?1), and thiametoxam (AC₅₀ = >20 mg kg^?1). Earthworms showed a preference for soils with the insecticide fipronil. Imidacloprid was the most toxic of the substances tested for E. andrei. The avoidance test was the most sensitive test for most pesticides studied, but results varied between pesticides. These results offer new insights on the toxicity of pesticides used to treat seeds in tropical regions. However, they should be complemented with higher-tier tests in order to reduce the uncertainties in risk assessment.     

The Analysis of Airborne Sulfate

This report reviews the current state of analytical methodology for sulfate in airborne particles. Methods for determination of total aerosol sulfate and total soluble sulfate are assessed. A more detailed review of the relatively new techniques for quantitative speciation of airborne sulfate then follows. Size distribution methodology and filter sampling difficulties relating to the collection of airborne sulfate-containing particles are enumerated. Experiments are suggested which use new, improved, and potentially applicable sulfate speciation techniques to obtain a better understanding of the generation, transport, transformation and removal processes that, in turn, determine the identity and concentrations of sulfate species in ambient air.     

Characterization of Particulates from Power Plants

The emphasis on participate control from industrial processes has been shifted recently towards fine particulates, having diameters less than 3 microns. There exists an urgent need for more scientific information of fine particle characterization.^1,2 Coal and oil fired power plants are among the largest anthropogenic point sources of particulate matter.³ Limited knowledge is available on particle size distribution and trace metal composition in power plant emissions.^4-7 The morphological properties of particle emissions have been largely neglected. In this report we present some information on particle characteristics for an oil-fired and coal-fired power plant.