Regional data refine local predictions: modeling the distribution of plant species abundance on a portion of the central plains

Species distribution models are frequently used to predict species occurrences in novel conditions, yet few studies have examined the consequences of extrapolating locally collected data to regional landscapes. Similarly, the process of using regional data to inform local prediction for species distribution models has not been adequately evaluated. Using boosted regression trees, we examined errors associated with extrapolating models developed with locally collected abundance data to regional-scale spatial extents and associated with using regional data for predictions at a local extent for a native and non-native plant species across the northeastern central plains of Colorado. Our objectives were to compare model results and accuracy between those developed locally and extrapolated regionally, those developed regionally and extrapolated locally, and to evaluate extending species distribution modeling from predicting the probability of presence to predicting abundance. We developed models to predict the spatial distribution of plant species abundance using topographic, remotely sensed, land cover and soil taxonomic predictor variables. We compared model predicted mean and range abundance values to observed values between local and regional. We also evaluated model prediction performance based on Pearson's correlation coefficient. We show that: (1) extrapolating local models to regional extents may restrict predictions, (2) regional data can help refine and improve local predictions, and (3) boosted regression trees can be useful to model and predict plant species abundance. Regional sampling designed in concert with large sampling frameworks such as the National Ecological Observatory Network may improve our ability to monitor changes in local species abundance.     

Australian agriculture: coping with dangerous climate change

Australian agriculture has operated successfully in one of the world’s most hostile environments for two centuries. However, climate change is posing serious challenges to its ongoing success. Determining what might constitute dangerous climate change for Australian agriculture is not an easy task, as most climate-related risks are associated with changes in the highly uncertain hydrological cycle rather than directly to more predictable changes in temperature. In addition, the adaptive capacity of Australian producers is generally high, as they have had to cope with a highly variable climate in which periodic, severe droughts are the norm. As the underlying global trends in climate interact with the continent’s patterns of natural variability, producers can generally deal with gradual changes in climate but are most concerned about high rates of change in regional and local climates and with abrupt, unexpected shifts in climate patterns. Perhaps the best indicator of dangerous climate change for Australian agriculture is the persistence, or not, of the drying trends in many of the Country’s most productive regions and the strength of the linkage between these trends and global climate change.     

Gasification of refuse derived fuel in a fixed bed reactor for syngas production

Steam gasification of two different refuse derived fuels (RDFs), differing slightly in composition as well as thermal stability, was carried out in a fixed-bed reactor at atmospheric pressure. The proximate and ultimate analyses reveal that carbon and hydrogen are the major components in RDFs. The thermal analysis indicates the presence of cellulose and plastic based materials in RDFs. H2 and CO are found to be the major products, along with CO2 and hydrocarbons resulting from gasification of RDFs. The effect of gasification temperature on H2 and CO selectivities was studied, and the optimum temperature for better H2 and CO selectivity was determined to be 725 degrees C. The calorific value of product gas produced at lower gasification temperature is significantly higher than that of gas produced at higher process temperature. Also, the composition of RDF plays an important role in distribution of products gas. The RDF with more C and H content is found to produce more amounts of CO and H2 under similar experimental conditions. The steam/waste ratio showed a notable effect on the selectivity of syngas as well as calorific value of the resulting product gas. The flow rate of carrier gas did not show any significant effect on products yield or their distribution.     

Investigating differential binding of polychlorinated dibenzo-p-dioxins/dibenzofurans in soil and soil components using selective supercritical fluid extraction

Supercritical fluid extraction (SFE) with pure carbon dioxide was performed at increasingly strong conditions to investigate differential binding of polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) in two impacted soils, in their sieved size fractions, and in small (a few mg) samples of industry-related waste products separated from impacted soil. The binding strengths of PCDD/Fs were shown to be different in the two soils, and in their different soil particle size fractions. As might be expected based on surface area considerations, one soil showed the strongest binding in the smallest (<5 μm) sieved fraction. However, the other soil showed the strongest binding in the larger sized fractions, possibly indicating that process-related particles could be controlling PCDD/F binding. Selective SFE of various types of particles including black carbon and charcoal (separated from soil), and from a suspected process anode residue did show different PCDD/F binding behavior ranging from quite weak binding (charcoal) to very strong binding (anode particles). Shifts to the stronger SFE fractions in the soils after activated carbon treatment agreed well with the decreases previously found in the uptake of PCDD/Fs by earthworms, as well as decreases in their freely-dissolved aqueous concentrations in soil/water slurries. These results show that, as previously demonstrated for PAHs and PCBs, selective SFE can be a useful tool to investigate differences in PCDD/F binding behaviors in impacted soils and sediments and their component parts, as well as a rapid tool for estimating the effectiveness of activated carbon treatments on decreasing the bioavailability of PCDD/Fs in soils and sediments.     

Statistical modelling of district-level residential electricity use in NSW, Australia

Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of ?1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the ‘most’ appropriate system when a review or upgrade of the network infrastructure is required.     

Numerical investigation of the flow profiles in the electrically enhanced cyclone

A numerical model for simulation of the electrohydrodynamic flow in an electrically enhanced cyclone is presented. A finite element approach was applied to solve the coupled equations for the positive corona-induced electric field. Three-dimensional simulations of gas flow were carried using Reynolds-Averaged Navier-Stokes equations including the Reynolds stress model and the electrohydrodynamic effect. Numerical results show that the change in the flow profile because of the influence of the corona-induced electric field is apparent when the inlet flow rate is low but is negligible at higher flow rates.     

Estimating the effectiveness of ergonomics interventions through case studies: implications for predictive cost-benefit analysis

PROBLEM: Cost-benefit analysis (CBA) can help to justify an investment in ergonomics interventions. A predictive CBA model would allow practitioners to present a cost justification to management during the planning stages, but such a model requires reliable estimates of the benefits of ergonomics interventions. METHOD: Through literature reviews and Internet searches, 250 case studies that reported the benefits of ergonomics programs and control measures were collected and summarized. RESULTS: Commonly reported benefits included reductions in the number of work-related musculoskeletal disorders (WMSDs) or their incidence rate, as well as related lost workdays, restricted workdays, and workers' compensation costs. Additional benefits reported were related to productivity, quality, turnover and absenteeism. DISCUSSION: Benefits reported were largely positive, and payback periods for ergonomics interventions were typically less than one year. SUMMARY: The results of this review could be used to develop predictive CBA models for ergonomics programs and individual control measures. IMPACT ON INDUSTRY: Cost-justifying ergonomics interventions prior to implementation may help to secure management support for proposed changes. Numbers used for the benefits side of a cost-benefit analysis (CBA) need to be based on "real world" data in order to be credible. The data presented in this paper may help in the development of simple cost-benefit models for ergonomics programs and control measures.     

Effects of urbanization on the population structure of freshwater turtles across the United States

Landscape‐scale alterations that accompany urbanization may negatively affect the population structure of wildlife species such as freshwater turtles. Changes to nesting sites and higher mortality rates due to vehicular collisions and increased predator populations may particularly affect immature turtles and mature female turtles. We hypothesized that the proportions of adult female and immature turtles in a population will negatively correlate with landscape urbanization. As a collaborative effort of the Ecological Research as Education Network (EREN), we sampled freshwater turtle populations in 11 states across the central and eastern United States. Contrary to expectations, we found a significant positive relationship between proportions of mature female painted turtles (Chrysemys picta) and urbanization. We did not detect a relationship between urbanization and proportions of immature turtles. Urbanization may alter the thermal environment of nesting sites such that more females are produced as urbanization increases. Our approach of creating a collaborative network of scientists and students at undergraduate institutions proved valuable in terms of testing our hypothesis over a large spatial scale while also allowing students to gain hands‐on experience in conservation science.     

Advancing “Autonomous” sensing and prediction of the subsurface environment: a review and exploration of the challenges for soil and groundwater contamination

Environmental Science and Pollution Research - Can we hope for autonomous (self-contained in situ) sensing of subsurface soil and groundwater pollutants to satisfy relevant regulatory criteria?...