Using structural equation modeling to investigate relationships among ecological variables

Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude –0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0.1258. Natural variability had a positive direct effect on biodiversity of magnitude 0.5347 and a negative indirect effect mediated through growth potential of magnitude –0.1105 yielding a positive total effects of magnitude 0.4242. Sediment contamination had a negative direct effect on biodiversity of magnitude –0.1956 and a negative indirect effect on growth potential via biodiversity of magnitude –0.067. Biodiversity had a positive effect on growth potential of magnitude 0.8432, and growth potential had a positive effect on biodiversity of magnitude 0.3398. The correlation between biodiversity and growth potential was estimated at 0.7658 and that between sediment contamination and natural variability at –0.3769.     

Evaluating Change in Rangeland Condition using Multitemporal AVHRR Data and Geographic Information System Analysis

Coarse-scale, multitemporal satellite image data were evaluated as a tool for detecting variation in vegetation productivity, as a potential indicator of change in rangeland condition in the western U.S. The conterminous U.S. Advanced Very High Resolution Radiometer (AVHRR) biweekly composite data set was employed using the six-year time series 1989–1994. Normalized Difference Vegetation Index (NDVI) image bands for the state of New Mexico were imported into a Geographic Information System (GIS) for analysis with other spatial data sets. Averaged NDVI was calculated for each year, and a series of regression analyses were performed using one year as the baseline. Residuals from the regression line indicated 14 significant areas of NDVI change: two with lower NDVI, and 11 with higher NDVI. Rangeland management changes, cross-country military training activities, and increases in irrigated cropland were among the identified causes of change.     

Source apportionment of particulate matter (PM2.5) in an urban area using dispersion,receptor and inverse modelling

Air pollution emission inventories are the basis for air quality assessment and management strategies. The quality of the inventories is of great importance since these data are essential for air pollution impact assessments using dispersion models. In this study, the quality of the emission inventory for fine particulates (PM_2.5) is assessed: first, using the calculated source contributions from a receptor model; second, using source apportionment from a dispersion model; and third, by applying a simple inverse modelling technique which utilises multiple linear regression of the dispersion model source contributions together with the observed PM_2.5 concentrations. For the receptor modelling the chemical composition of PM_2.5 filter samples from a measurement campaign performed between January 2004 and April 2005 are analysed. Positive matrix factorisation is applied as the receptor model to detect and quantify the various source contributions. For the same observational period and site, dispersion model calculations using the Air Quality Management system, AirQUIS, are performed. The results identify significant differences between the dispersion and receptor model source apportionment, particularly for wood burning and traffic induced suspension. For wood burning the receptor model calculations are lower, by a factor of 0.54, but for the traffic induced suspension they are higher, by a factor of 7.1. Inverse modelling, based on regression of the dispersion model source contributions and the PM_2.5 concentrations, indicates similar discrepancies in the emissions inventory. In order to assess if the differences found at the one site are generally applicable throughout Oslo, the individual source category emissions are rescaled according to the receptor modelling results. These adjusted PM_2.5 concentrations are compared with measurements at four independent stations to evaluate the updated inventory. Statistical analysis shows improvement in the estimated concentrations for PM_2.5 at all sites. Similarly, inverse modelling is applied at these independent sites and this confirms the validity of the receptor model results.     

Chromosomal genes conferring tolerance to heavy metal (Ag) toxicity

Bacterial strains were isolated from sediment samples from the Thames River. Successive transfer growth of the various strains on nutrient agar containing increasing concentrations of AgNO₃ revealed that three of the bacterial isolates were found to be capable of tolerating high concentrations of AgNO₃ ranging from 20 to 80 mM on a solid medium and up to 10 mM AgNO₃ in liquid medium. Molecular characterization and identification based on 16S rDNA gene sequencing of three strains of bacteria that are tolerant to silver nitrate showed that the major tolerant strains include the superbug, Shewanella oneidensis, Pseudomonas sp. and Bacillus sp. Protein extraction and two-dimensional (2D) sodium dodecyl sulfate SDS-polyacrylamide gel electrophoresis (PAGE) of the protein extracts in bacteria exposed to very high concentrations of AgNO₃ revealed a general reduction in the number of expressed proteins, although two protein spots were conspicuously over expressed in the exposed bacteria compared to control. The N-terminal amino acid sequence analysis of the protein spots identified the major up-regulated proteins as the outer membrane protein To1C (45.2 kDa) and the structural protein of the flagellar filament, flagellin (28.34 kDa), encoded for by the to1C and fliC genes, respectively. The roles of these genes in a number of multi-drug resistant pathogen and potentials for biotechnological applications in toxic metal control for treatment of contaminated ecosystems and biomining were discussed.     

The network imaginary: coherence and creativity within a multiscalar collaborative effort to reform US fire management

In response to the ongoing crisis in fire management, the US Fire Learning Network (FLN) engages partners in collaborative, landscape-scale ecological fire restoration. The paper contends that the FLN employs technologies, planning guidelines and media to articulate an FLN imaginary that co-ordinates independent efforts to engage in ecological fire restoration work without need of either hierarchal authority or collective social capital. This imaginary may allow the FLN to draw on the creativity and adaptive innovation of collaboration to reform fire management institutions and fire-adapted ecosystems.     

State of the Arctic Conference 2010: International Perspectives on Progress of Research Responsive to Decision-Makers’ Information Needs

The SoA conference emphasized that urgent questions posed by society and decision-makers in response to rapid Arctic change require that Arctic research address the broader concepts of sustainability as well as adaptation to and mitigation of interrelated environmental and socioeconomic change. Murray et al. (submitted) explore progress made in this context. The SoA meeting demonstrated significant progress by the Arctic community of scientists and stakeholders in meeting this challenge, as well as the need to better engage the private sector and find more effective ways to partner with relevant research activities outside of the polar regions.     

Methods of characterizing the distribution of exhaust emissions from light-duty, gasoline-powered motor vehicles in the U.S. fleet

Mobile sources significantly contribute to ambient concentrations of airborne particulate matter (PM). Source apportionment studies for PM10 (PM < or = 10 microm in aerodynamic diameter) and PM2.5 (PM < or = 2.5 microm in aerodynamic diameter) indicate that mobile sources can be responsible for over half of the ambient PM measured in an urban area. Recent source apportionment studies attempted to differentiate between contributions from gasoline and diesel motor vehicle combustion. Several source apportionment studies conducted in the United States suggested that gasoline combustion from mobile sources contributed more to ambient PM than diesel combustion. However, existing emission inventories for the United States indicated that diesels contribute more than gasoline vehicles to ambient PM concentrations. A comprehensive testing program was initiated in the Kansas City metropolitan area to measure PM emissions in the light-duty, gasoline-powered, on-road mobile source fleet to provide data for PM inventory and emissions modeling. The vehicle recruitment design produced a sample that could represent the regional fleet, and by extension, the national fleet. All vehicles were recruited from a stratified sample on the basis of vehicle class (car, truck) and model-year group. The pool of available vehicles was drawn primarily from a sample of vehicle owners designed to represent the selected demographic and geographic characteristics of the Kansas City population. Emissions testing utilized a portable, light-duty chassis dynamometer with vehicles tested using the LA-92 driving cycle, on-board emissions measurement systems, and remote sensing devices. Particulate mass emissions were the focus of the study, with continuous and integrated samples collected. In addition, sample analyses included criteria gases (carbon monoxide, carbon dioxide, nitric oxide/nitrogen dioxide, hydrocarbons), air toxics (speciated volatile organic compounds), and PM constituents (elemental/organic carbon, metals, semi-volatile organic compounds). Results indicated that PM emissions from the in-use fleet varied by up to 3 orders of magnitude, with emissions generally increasing for older model-year vehicles. The study also identified a strong influence of ambient temperature on vehicle PM mass emissions, with rates increasing with decreasing temperatures.     

Comparison of a two-dimensional numerical dust transport model with experimental dust emissions from soil surfaces in a wind tunnel

Near-surface wind-tunnel fugitive dust concentration profiles arising from soil surfaces beds were compared to a finite difference numerical dust transport model. Comparisons of the type shown in this study were previously non-existent in the literature due to the lack of experimental wind-tunnel data for near-surface concentrations over a soil bed. However, in a previous study by the authors, near-surface steady-state concentration profiles were measured in order to obtain fugitive dust emission rates, thus allowing the comparison to models shown in this paper. The novel aspects of the current study include: comparison of concentration profiles of dust obtained experimentally in the wind tunnel with those calculated numerically; comparison of the calculated numerical fetch effect on dust emissions with that obtained in the wind tunnel; and comparison of the emission rates calculated numerically with those obtained experimentally in the wind tunnel. Initial comparisons with the model indicate good agreement implying that the physical mechanism of advection–diffusion is reasonably modeled with the choice of equations for the simple “steady-state” process near the surface. Furthermore, the numerical solutions presented in this paper provide a means to systematically explore the relative impact of varied surface boundary conditions upon the emission process and provide a potential link between wind-tunnel simulations and field scale models.     

Forest Vegetation Monitoring and Foliar Chemistry of Red Spruce and Red Maple at Acadia National Park in Maine

The USDA Forest Service Forest Health Monitoring (FHM) program indicators, including forest mensuration, crown condition classification, and damage and mortality indicators were used in the Cadillac Brook and Hadlock Brook watershed forests at Acadia National Park (ANP) along coastal Maine. Cadillac Brook watershed burned in a wildfire in 1947. Hadlock Brook watershed, undisturbed for several centuries, serves as the reference site. These two small watersheds have been gauged and monitored at ANP since 1998 as part of the Park Research and Intensive Monitoring of Ecosystems Network (PRIMENet). Forest vegetation at Hadlock Brook was dominated by late successional species such as Acer saccharum, Fagus grandifolia, Betula alleghaniensis, Acer rubrum and Picea rubens. Forest vegetation at Cadillac Brook, on the other hand, was younger and more diverse and included those species found in Hadlock as well as early successional species such as Betula papyrifera and Populus grandidentata. Differences in forest species composition and stand structure were attributed to the severe wildfire that affected the Cadillac Brook watershed. Overall, the forests at these ANP watersheds were healthy with a low percentage (相似文献   

Environmental and Distributional Impacts of Conservation Targeting Strategies

Resource purchasing funds have become a major tool for environmental protection and resource conservation. These funds use various strategies to target resources for conservation, the choice of which may lead to striking differences in environmental performance. This paper develops an analytical framework to analyze the impact of alternative targeting strategies on different interest groups, including consumers, producers, labor, and environmentalists. We show that ignoring the output price effect of purchasing funds reduces environmental gain and in some cases may make a purchasing fund counterproductive, and we argue that the optimal design of targeting criteria must consider the price feedback effect.