Energy profiles of an agricultural frontier: the American Great Plains, 1860–2000

Regional Environmental Change - Agro-ecosystem energy profiles reveal energy flows into, within, and out of US Great Plains farm communities across 140 years. This study evaluates external...     

Ambient Air Quality Monitoring Network Design for Assessing Human Health Impacts from Exposures to Airborne Contaminants

Existing methods of establishing ambientair quality monitoring networks typically evaluateonly parameters related to ambient concentrations ofthe contaminant(s) of interest such as emissionsource characteristics, atmospheric transport anddispersion, secondary reactions, depositioncharacteristics, and local topography. However,adverse health risks from exposures to airbornecontaminants are a function of the contaminant andthe anatomic and physiologic characteristics of theexposed population. Thus, ambient air qualitymonitoring networks designed for the protection ofpublic health or for epidemiological studiesevaluating adverse health impacts from exposures toambient air contaminants should account for bothcontaminant characteristics and human healthparameters. A methodology has been establishedwhich optimizes ambient air quality monitoringnetworks for assessments of adverse human healthimpacts from exposures to airborne contaminants byincorporating human health risk assessmenttechniques. The use of risk assessment techniquesas the basis for designing ambient air qualitymonitoring networks will help to target limitedfinancial and human resources to evaluate humanhealth risks from exposures to airbornecontaminants.     

Spatial prioritization of revegetation sites for dryland salinity management: an analytical framework using GIS

To address the limited application of analytical and modelling techniques in prioritizing revegetation sites for dryland salinity (saline land) management, a case study of the Hodgson Creek catchment in Queensland, Australia, was conducted. An analytical framework was developed, incorporating the use of spatial datasets (Landsat 7 image, DEM, soil map, and salinity map), which were processed using digital image processing techniques and a geographic information system (GIS). Revegetation sites were mapped and their priority determined based on recharge area, land use/cover and sub‐catchment salinity. The analytical framework presented here enhances the systematic use of land information, widens the scope for scenario testing, and improves the testing of alternative revegetation options. The spatial patterns of revegetation sites could provide an additional set of information relevant in the design of revegetation strategies.     

Community-based Environmental Planning: Operational Dilemmas,Planning Principles and Possible Remedies

The operational dilemmas and challenges associated with the practice of community-based environmental planning (CBEP) are examined. The paper examines the frequently invoked ‘bottom-up’ versus ‘top-down’ dichotomy and argues that environmental governance is more complex, dynamic and multi-scalar than this simple dichotomy implies. The paper identifies six key problems with the CBEP approach: (i) the conceptualization of ‘community’ which poorly accounts for difference; (ii) problems of inequality; (iii) the organizational capacity and efficacy of community groups; (iv) the scale of CBEP; (v) the types of knowledge utilized by communities in environmental management; and (vi) the potential for parochial concerns to dominate the priorities and agenda of community organizations. The paper analyses each of these issues, identifies planning principles that may aid resolution, and suggests possible remedies.     

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base‐flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite‐nitrate (NO₂‐NO₃), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO₂‐NO₃ concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed‐use and heavily impacted watersheds.     

Energy-Based Land Use Predictors of Proximal Factors and Benthic Diatom Composition in Florida Freshwater Marshes

The Landscape Development Intensity index (LDI), which is based on non-renewable energy use and integrates diverse land use activities, was compared to other measures of LU (e.g., %agriculture, %urban) to determine its ability for predicting benthic diatom composition in freshwater marshes of peninsular Florida. In this study, 70 small, isolated herbaceous marshes located along a human disturbance gradient (generally agricultural) throughout peninsular Florida were sampled for benthic diatoms and soil and water physical/chemical parameters (i.e., TP, TKN, pH, specific conductance, etc.). Landscape measures of percent agriculture, percent urban, percent natural, and LDI index values were calculated for a 100 m buffer around each site. The strongest relationships using Mantel's r statistic, which ranges from −1 to 1, were found between benthic diatom composition, the combined soil and water variables, and LDI scores (r=0.51, P<0.0001). Although similar, soil and water variables alone (r=0.45, P<0.0001) or with percent agriculture or percent natural were not as strongly correlated (both Mantel's r=0.46, P<0.0001). Little urban land use was found in the areas surrounding the study wetlands. Diatom data were clustered using flexible beta into 2 groups, and stepwise discriminant analysis identified specific conductance, followed by LDI score, soil pH, water total phosphorus, and ammonia, as cluster-separating variables. The LDI explained slightly more of the variation in species composition than either percent agriculture or percent natural, perhaps because the LDI can combine disparate land uses into a single quantitative value. However, the ecological significance of the difference between land use metrics and diatom composition is controvertible, and additional tests including more varied land uses appear warranted.     

A free-enzyme catalyst for the bioremediation of environmental atrazine contamination

Herbicide contamination from agriculture is a major issue worldwide, and has been identified as a threat to freshwater and marine environments in the Great Barrier Reef World Heritage Area in Australia. The triazine herbicides are of particular concern because of potential adverse effects, both on photosynthetic organisms and upon vertebrate development. To date a number of bioremediation strategies have been proposed for triazine herbicides, but are unlikely to be implemented due to their reliance upon the release of genetically modified organisms. We propose an alternative strategy using a free-enzyme bioremediant, which is unconstrained by the issues surrounding the use of live organisms. Here we report an initial field trial with an enzyme-based product, demonstrating that the technology is technically capable of remediating water bodies contaminated with the most common triazine herbicide, atrazine.     

Accumulation and partitioning of heavy metals in mangroves: a synthesis of field-based studies

We report the findings of a comparative analysis examining patterns of accumulation and partitioning of the heavy metals copper (Cu), lead (Pb) and zinc (Zn) in mangroves from available field-based studies to date, employing both species level analyses and a phylogenetic approach. Despite mangroves being a taxonomically diverse group, metal accumulation and partitioning for all metals examined were broadly similar across genera and families. Patterns of metal accumulation were also similar regardless of whether species were classified as salt secreting or non-secreting. Metals were accumulated in roots to concentrations similar to those of adjacent sediments with root bio-concentration factors (BCF; ratio of root metal to sediment metal concentration) of 1< or =. Root BCFs were constant across the exposure range for all metals. Metal concentrations in leaves were half that of roots or lower. Essential metals (Cu and Zn; translocation factors (TF; ratio of leaf metal to root metal concentration) of 0.52 and 0.53, and leaf BCFs of 0.47 and 0.51, respectively) showed greater mobility than non-essential metals (Pb; TF of 0.31 and leaf BCF of 0.11). Leaf BCFs for the essential metals Cu and Zn decreased as environmental concentrations increased. The non-essential metal Pb was excluded from leaf tissue regardless of environmental concentrations. Thus mangroves as a group tend to operate as excluder species for non-essential metals and regulators of essential metals. For phytoremediation initiatives, mangrove ecosystems are perhaps best employed as phytostabilisers, potentially aiding in the retention of toxic metals and thereby reducing transport to adjacent estuarine and marine systems.