Arthur G. Hornsby

Movement and degradation of aldicarb residues in the saturated zone under citrus groves on the Florida ridge

Abstract A 1.7-ha section of citrus grove near Lake Hamilton was the site of a three-year field study designed to monitor the movement and degradation of the nematicide and insecticide aldicarb in the central ridge area of Florida. Soil cores were used to monitor the fate of aldicarb residues in the unsaturated zone and over 2,000 groundwater samples were collected from 174 monitoring wells to measure horizontal and vertical transport of aldicarb residues in the saturated zone. A simple saturated zone model was used to estimate the degradation rate of aldicarb residues and extrapolate findings to other ridge areas. The results of the study suggest that in the saturated zone aldicarb residues degrade at a rate corresponding to a half-life of approximately eight months. The predominantly horizontal movement of groundwater at this site limits aldicarb residues to the upper three to five meters of the saturated zone. Field data from this site together with unsaturated and saturated zone simulations suggest that in this area of Florida current restrictions on aldicarb used near potable wells are adequate to protect drinking water supplies.

Distribution of rainfall and soil moisture content in the soil profile under citrus tree canopy and at the dripline

Abstract The plant canopy intercepts rain and thus can alter the distribution of water under the canopy as compared to that along the dripline. The effects of a citrus (Citrus sinensis L. Osbeck) tree (25-year-old, Valencia orange) canopy on the distribution of rainfall and soil moisture content within the soil profile either along the dripline (D) or under the canopy near the trunk (inner side; I), and midway between I and Dripline (M) were evaluated, on the east and west sides of trees planted along north-south rows. Results of eleven storm events in 1995 (mean of east and west sides) revealed that the amounts of precipitation at the D, M, and I positions were 97–140, 47–94, and 52–79% of the incident rainfall, respectively. Thus, canopy interception of incident rainfall was quite appreciable. The soil moisture content was greater along the dripline compared to that at the M and I positions, particularly in the deeper (≥60 cm) soil profile. The water flux was significantly greater at the dripline than under the canopy indicating a greater leaching potential of soil-applied fertilizers and other chemicals when placed along the dripline. A substantial reduction in the rainfall and water flux under the canopy as a result of canopy interception suggests that application of fertilizer and chemicals under the canopy could minimize leaching losses.

Sorption and Leaching Potential of Acidic Herbicides in Brazilian Soils

Abstract Leaching of acidic herbicides (2,4-D, flumetsulam, and sulfentrazone) in soils was estimated by comparing the original and modified AF (Attenuation Factor) models for multi-layered soils (AFi). The original AFi model was modified to include the concept of pH-dependence for K d (sorption coefficient) based on pesticide dissociation and changes in the accessibility of soil organic functional groups able to interact with the pesticide. The original and modified models, considering soil and herbicide properties, were applied to assess the leaching potential of selected herbicides in three Brazilian soils. The pH-dependent K d values estimated for all three herbicides were observed to be always higher than pH-independent K d values calculated using average K oc data, and therefore the original AFi model overestimated the overall leaching potential for the soils studied.Leaching of acidic herbicides (2,4-D, flumetsulam, and sulfentrazone) in soils was estimated by comparing the original and modified AF (Attenuation Factor) models for multi-layered soils (AFi). The original AFi model was modified to include the concept of pH-dependence for Kd (sorption coefficient) based on pesticide dissociation and changes in the accessibility of soil organic functional groups able to interact with the pesticide. The original and modified models, considering soil and herbicide properties, were applied to assess the leaching potential of selected herbicides in three Brazilian soils. The pH-dependent Kd values estimated for all three herbicides were observed to be always higher than pH-independent Kd values calculated using average Koc data, and therefore the original AFi model overestimated the overall leaching potential for the soils studied.

Simulation of nitrogen in agro-ecosystems: Criteria for model selection and use

Available simulation models for describing nitrogen behavior in agro-ecosystems vary in two characteristics:(i) conceptual completeness in terms of the number of processes considered, and(ii) thelevel of detail at which each process is modeled. These model characteristics are determined by both the objectives that the model is designed to meet and the current state-of-the-art understanding of the various processes included in the model. The levels of conceptual completeness and detail in a model govern the potential applications for which the model may be used. Applications of models may be research-oriented, management-oriented, or planning-oriented. A model suitable for a given application should have an appropriate level of completeness and detail to accomplish the stated objective.Criteria to aid in the selection and evaluation of nitrogen simulation models for a particular application include: i) the availability of computational facilities, ii) the spatial and temporal scales of application, iii) the intended use of the simulations, iv) the availability of model input data, and v) the confidence regions associated with the model output.ResumenLos modelos de simulación del comportamiento en agro-ecosistemas difieren en dos características: (i)entereza o minuciosidad conceptual, en términos del número de procesos que considera, y (ii)el nivel de detalle en el cual cada proceso es modelado. Estas características del modelo son determinadas por los objetivos para los cuales el modelo es diseñado y por el grado acutal del conocimiento de los procesos incluídos en el modelo. Los niveles de entereza conceptual y de detalle en un modelo determinan las aplicaciones potenciales para las cuales dicho modelo puede ser utilizado. Las aplicationes pueden ser orientadas a la investigación, manejo o planificación. Un modelo adecuado para una aplicación determinada debería tener un nivel apropiado de entereza y detalle para lograr el objetivo establecido.Los criterios de ayuda en la selección y evaluación de los modelos de simulación del nitrógeno para una aplicación particular incluyen: (i) la disponibilidad de facilidades computacionales, (ii) las escalas espacial y temporal de aplicación, (iii) el uso deseado de las simulaciones, (iv) la disponibilidad de datos de entrada al modelo, y (v) los ámbitos de confianza asociadas con las salidas del modelo.

Simulation of nitrogen in agro-ecosystems: Criteria for model selection and use@@@Simulación de nitrógeno en agro-ecosistemas: Criterios para selección y uso del modelo

Available simulation models for describing nitrogen behavior in agro-ecosystems vary in two characteristics:(i) conceptual completeness in terms of the number of processes considered, and(ii) thelevel of detail at which each process is modeled. These model characteristics are determined by both the objectives that the model is designed to meet and the current state-of-the-art understanding of the various processes included in the model. The levels of conceptual completeness and detail in a model govern the potential applications for which the model may be used. Applications of models may be research-oriented, management-oriented, or planning-oriented. A model suitable for a given application should have an appropriate level of completeness and detail to accomplish the stated objective.Criteria to aid in the selection and evaluation of nitrogen simulation models for a particular application include: i) the availability of computational facilities, ii) the spatial and temporal scales of application, iii) the intended use of the simulations, iv) the availability of model input data, and v) the confidence regions associated with the model output.ResumenLos modelos de simulación del comportamiento en agro-ecosistemas difieren en dos características: (i)entereza o minuciosidad conceptual, en términos del número de procesos que considera, y (ii)el nivel de detalle en el cual cada proceso es modelado. Estas características del modelo son determinadas por los objetivos para los cuales el modelo es diseñado y por el grado acutal del conocimiento de los procesos incluídos en el modelo. Los niveles de entereza conceptual y de detalle en un modelo determinan las aplicaciones potenciales para las cuales dicho modelo puede ser utilizado. Las aplicationes pueden ser orientadas a la investigación, manejo o planificación. Un modelo adecuado para una aplicación determinada debería tener un nivel apropiado de entereza y detalle para lograr el objetivo establecido.Los criterios de ayuda en la selección y evaluación de los modelos de simulación del nitrógeno para una aplicación particular incluyen: (i) la disponibilidad de facilidades computacionales, (ii) las escalas espacial y temporal de aplicación, (iii) el uso deseado de las simulaciones, (iv) la disponibilidad de datos de entrada al modelo, y (v) los ámbitos de confianza asociadas con las salidas del modelo.

Managing pesticides for crop production and water quality protection: practical grower guides

A decision aid has been developed for use by farmers and other pesticide users that permits the selection of pesticides on the basis of water quality impact in addition to efficacy and cost as is traditionally done. This ‘kitchen table’ decision aid uses information on environmental fate and toxicity of pesticides, soil leaching potential or run-off ratings in combination with pest management guidelines to make site-specific selections that minimize the potential impacts of pesticide use on water quality. Pesticide properties used include the sorption coefficient ( K oc ), degradation half-life, lifetime health advisory level (HAL), and aquatic toxicity. The first two properties are used to derive a relative leaching potential index, RLPI, and a relative run-off potential index, RRPI, for each pesticide. Site-specific soil ratings for pesticide leaching and run-off, provided by the US Department of Agriculture Soil Conservation Service, are matched with these indices and toxicity values via a table of selection criteria. A pesticide selection worksheet is provided to organize the necessary information to make an informed decision. This decision aid assists the pesticide user in understanding the water quality impacts of alternative pesticide selections. These grower guides are customized to individual crops. They include a table of pesticides registered for use on the crop, organized by major use category (herbicides, insecticides, nematicides, fungicides, and soil fumigants). Within categories, trade names, common names, application type (soil vs. foliar), K oc , RLPI, RRPI, HAL, and aquatic toxicity are listed. These grower guides can easily be adapted for use in other states or countries. This technology will not only help agricultural and urban pesticide users select pesticides with less water quality impact, but will also aid regulatory agencies in developing meaningful groundwater protection plans, and hopefully will result in more equitable public policy decisions.

A simulation model for fate and transport of methyl bromide during fumigation in plastic-mulched vegetable soil beds†

A coupled water-heat and chemical transport model was used to describe the fate and transport of methyl bromide fumigant in low-density polyethylene plastic-mulched soil beds used for vegetable production. Methyl bromide transport was described by convective-dispersive processes including transformations through hydrolysis. Effects of non-isothermal conditions on chemical transport were considered through inclusion of temperature effects on transport parameters. An energy-balance approach was used to describe the plastic-mulched boundary condition that controls the thermal regime within the soil bed. Simulations were made for variable water-saturation regimes within the bed and for different depths of fumigant injection. Simulations for various scenarios revealed that large amounts (20-44% over a 7-day period) of applied methyl bromide are lost from the un-mulched furrows between the beds. Plastic mulching of the bed was found to be only partially effective (11-29% emission losses over a 7-day period) in reducing atmospheric emissions. Deep injection of fumigant and saturating the soil with water both led to increased retention of methyl bromide within the soil and less emission to the atmosphere. However, deep injection was unfavorable for effective sterilization of the crop root zone.

Sources of the Data

The original “ARS pesticide database” was compiled by ARS Soil Scientist Ralph Nash for research purposes but was never published. The data were compiled on paper forms by Nash and, after conversion to electronic records, became the nucleus of this database. Hornsby and Rao and their colleagues of the University of Florida have collected a large amount of data [129,223,234–237]. In addition to the primary literature, excellent compilations of some of the parameters are available, and these publications remain the only source of some values. The Weed Science Society of America Herbicide Handbook [325–327], a result of voluntary industry submissions of information on herbicides, has data on solubilities, vapor pressures, and, in some cases, persistences. The Royal Society of Chemistry Agrochemicals Handbook [245,246], and the British Crop Protection Council Pesticide Manual [32–34] continue the British tradition of pesticide science with a physical-chemical emphasis, giving high-quality solubilities, vapor pressures, Chemical Abstract Service Reference Numbers, molecular weights, and formulas for most pesticides. Trademark, formulation, and detailed use information are available from the Crop Protection Chemicals Reference [47], which is a collection of product labels. However, all manufacturers are not included. The Farm Chemicals Handbook [195,196] is the most complete cross-referenced listing of pesticides new and old and their uses and properties. These handbooks also contain much toxicological, chemical, and other information not covered here.

Database Limitations: Other Information Needs

It must be said that the “screening” procedures that are being used with these data are trustworthy only if they determine that the pollution potential for a specific pesticide site use situation is extremely high or extremely low. More accurate predictions can be made using computer simulation modeling to integrate a much more detailed process description, which includes more information about the properties of the chemical and the use and site situation of concern. Considerable progress is being made in this area [49,61], and it is clear that the adequate characterization of a pesticide’s behavior in the environment (not to mention its toxicology) requires more than six parameters. The Beltsville ARS database [116], which contains the six parameters compiled here plus heats of vaporization, phase transition temperatures, hydrolysis and photolysis rate constants, and specific soil sorption coefficients, is a step in the right direction. Although many of those data are missing, much of that will become available as part of the reregistration process, and the quality and completeness of reporting of that data should be improved as a result of Good Laboratory Practice (GLP) compliance.

Notes on the Database Fields

Generic names have been developed by the pesticide science societies to refer to active ingredient compounds without naming specific products or trade names. Generally we used the International Union of Pure and Applied Chemistry (IUPAC) common name if more than one existed.