Pesticide Impact Rating Index – A Pesticide Risk Indicator for Water Quality

Pesticide users, natural resource managers, regulators, government agencies and many others are concerned about the off-site impact of pesticides on the environment. Systematic methods of the assessment of potential risk of pesticides to environmental components can serve as valuable tools in decision making and policy formulation. Simple risk indicators have been developed which cover a range of scenarios such as toxicity to organisms, health of farm workers, consumer health, and residues in harvested produce. The authors have developed a software package named Pesticide Impact Rating Index (PIRI) that outputs an improved pesticide risk indicator for water quality. PIRI is a standalone, user-friendly, platform-independent program. It can be used to (i) rank pesticides in terms of their relative pollution potential to groundwater or surface water, and (ii) to compare different land uses in a catchment or at a regional scale in terms of their relative impact on water quality. It is based on pesticides use; the pathway through which the pesticides are released to the water resources (drift, runoff, erosion, leaching) and the value of the water resources threatened. Each component is quantified using pesticide characteristics (including toxicity to organisms at different trophic levels, i.e. fish, daphnia, algae, etc.), environmental and site conditions (e.g. organic carbon content of soil, water input, slope of land, soil loss, recharge rate, depth of water table, etc.). This paper describes two case studies of the application of PIRI in Australia. The comparison of the risk assessment by PIRI on these revealed that PIRI correctly estimated the pollution potential of pesticides in greater than 80% of cases. A GIS version of PIRI is described in a companion paper in this volume. An erratum to this article is available at .     

Linking field experiments to long-term simulation of impacts of nitrogen deposition on heathlands and moorlands

The results from three long-term field manipulation studies of the impacts of increased nitrogen deposition (0–120 kg N ha^?1 yr^?1) on lowland and upland heathlands in the UK were compared, to test if common responses are observed. Consistent increases in Calluna foliar N content and decreases in litter C:N ratios were found across all sites, while increases in N leaching were not observed at any site over the range 0–80 kg ha^?1 yr^?1. However, the response of Calluna biomass did vary between sites, possibly reflecting site differences in nutrient status and management histories. Five versions of a simulation model of heathland responses to N were developed, each reflecting different assumptions about the fate and turnover of soil N. Model outputs supported the deduction from mass balance calculations at two of the field sites that N additions have resulted in an increase in immobilisation; the latter was needed to prevent the model overestimating measured N leaching. However, this version of the model significantly underestimated Calluna biomass. Model versions, which included uptake of organic N by Callunaand re-mobilisation of N from the soil organic store provided some improvement in the fit between modelled and field biomass data, but re-mobilisation also led to an overestimation of N leaching. Quantification of these processes and their response to increased N deposition are therefore critical to interpreting experimental data and predicting the long-term impacts of atmospheric deposition on heathlands and moorlands.     

Job level risk assessment using task level strain index scores: a pilot study.

This paper explores 2 methods of modifying the Strain Index (SI) to assess the ergonomic risk of multi-task jobs. Twenty-eight automotive jobs (15 cases and 13 controls) were studied. The first method is based on the maximum task SI score, and the second method is modeled on the NIOSH Composite Lifting Index (CLI) algorithm, named cumulative assessment of risk to the distal upper extremity (CARD). Significant odds ratios of 11 (CI 1.7-69) and 24 (CI 2.4-240) were obtained using the modified maximum task and CARD, respectively. This indicates that modification of the SI may be useful in determining the risk of distal upper extremity injury associated with a multi-task job.     

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.     

Long-term effects of sustained beef feedlot manure application on soil nutrients, corn silage yield, and nutrient uptake

A field study was initiated in 1992 to investigate the long-term impacts of beef feedlot manure application (composted and uncomposted) on nutrient accumulation and movement in soil, corn silage yield, and nutrient uptake. Two application strategies were compared: providing the annual crop nitrogen (N) requirement (N-based rate) or crop phosphorus (P) removal (P-based rate), as well as a comparison to inorganic fertilizer. Additionally, effects of a winter cover crop were evaluated. Irrigated corn (Zea mays L.) was produced annually from 1993 through 2002. Average silage yield and crop nutrient removal were highest with N-based manure treatments, intermediate with P-based manure treatments, and least with inorganic N fertilizer. Use of a winter cover crop resulted in silage yield reductions in four of ten years, most likely due to soil moisture depletion in the spring by the cover crop. However, the cover crop did significantly reduce NO3-N accumulation in the shallow vadose zone, particularly in latter years of the study. The composted manure N-based treatment resulted in significantly greater soil profile NO3-N concentration and higher soil P concentration near the soil surface. The accounting procedure used to calculate N-based treatment application rates resulted in acceptable soil profile NO3-N concentrations over the short term. While repeated annual manure application to supply the total crop N requirement may be acceptable for this soil for several years, sustained application over many years carries the risk of unacceptable soil P concentrations.     

MODELING THE DISTRIBUTION OF DIFFUSE NITROGEN SOURCES AND SINKS IN THE NEUSE RIVER BASIN OF NORTH CAROLINA,USA1

This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km² Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).     

PREDICTING FECAL COLIFORM BACTERIA LEVELS IN THE CHARLES RIVER,MASSACHUSETTS, USA1

In Massachusetts, the Charles River Watershed Association conducts a regular water quality monitoring and public notification program in the Charles River Basin during the recreational season to inform users of the river's health. This program has relied on laboratory analyses of river samples for fecal coliform bacteria levels, however, results are not available until at least 24 hours after sampling. To avoid the need for laboratory analyses, ordinary least squares (OLS) and logistic regression models were developed to predict fecal coliform bacteria concentrations and the probabilities of exceeding the Massachusetts secondary contact recreation standard for bacteria based on meteorological conditions and streamflow. The OLS models resulted in adjusted R²s ranging from 50 to 60 percent. An uncertainty analysis reveals that of the total variability of fecal coliform bacteria concentrations, 45 percent is explained by the OLS regression model, 15 percent is explained by both measurement and space sampling error, and 40 percent is explained by time sampling error. Higher accuracy in future bacteria forecasting models would likely result from reductions in laboratory measurement errors and improved sampling designs.