Software for pest‐management science: computer models and databases from the United States Department of Agriculture—Agricultural Research Service

Abstract

We present an overview of USDA Agricultural Research Service (ARS) computer models and databases related to pest-management science, emphasizing current developments in environmental risk assessment and management simulation models. The ARS has a unique national interdisciplinary team of researchers in surface and sub-surface hydrology, soil and plant science, systems analysis and pesticide science, who have networked to develop empirical and mechanistic computer models describing the behavior of pests, pest responses to controls and the environmental impact of pest-control methods. Historically, much of this work has been in support of production agriculture and in support of the conservation programs of our 'action agency' sister, the Natural Resources Conservation Service (formerly the Soil Conservation Service). Because we are a public agency, our software/database products are generally offered without cost, unless they are developed in cooperation with a private-sector cooperator. Because ARS is a basic and applied research organization, with development of new science as our highest priority, these products tend to be offered on an 'as-is' basis with limited user support except for cooperating R&D relationship with other scientists. However, rapid changes in the technology for information analysis and communication continually challenge our way of doing business.

Documenting the pesticide processes module of the ARS RZWQM agroecosystem model

“…It is likely that RZWQM will continue to receive some degree of user support from ARS for the near future 140. It has been selected as a test case for ‘modularization’ as part of the ARS Object Modeling System and it is currently being deconstructed into independent modules.…”

Modular structure of web-based decision support systems for integrated pest management. A review

“…The approach should be considered as typical, although the given examples are those followed by Damos and Karabatakis (2013). Actually, there are very few published works that provide a robust framework and opensource programs or algorithms that can be used ad hoc in decision support systems (Higley et al 1986;Bery 1995;Don Wauchope et al 2003).…”

Modelling pesticides transfer to surface water at the catchment scale: a multi-criteria analysis

“…For instance, the conceptual model SWAT includes 32 processes and appears as the most comprehensive model representing the water and pesticide cycles. It displays a significant degree of maturity by associating several models that had been separately validated in the various environmental compartments (Wauchope et al 2003): EPIC for the plant growth, CREAMS for the hydrology, GLEAMS for the fate of pesticides and SWRRB for the extension of the application field at the catchment scale. More simplified models such as Stream-pesticide, FLOWT and SACADEAU have been improved to enhance the applicability domain, and their authors have already identified the next processes to be integrated into future versions.…”

“…Though several review papers comparing modelling approach of pesticide fate in a general sense are available, they do not unequivocally integrate the catchment scale as an analysis criterion excepted in Borah and Bera (2004), Quilbe et al (2006) and Holvoet et al (2007). Review papers have been mostly focused on (a) a specific group of models, such as leaching models at the soil column or agricultural field scale (Vanclooster et al 2000;Siimes and Kämäri 2003;Jantunen et al 2004;Alvarez-Benedi et al 2004;Köhne et al 2009), (b) several types of models designed by a particular institution such as the Agricultural Research Service (Wauchope et al 2003), (c) indicators of risk exposure or pesticide contamination (Reus et al 2002;Devillers et al 2005) at the regional or farm scale (Halberg et al 2005), (d) regional and national spatialization of the simulation's results of the 1D leaching models MACRO, PEARL or PRZM such as GeoPearl or FitoMarche (Sood and Bhagat 2005;Tiktak et al 2006;Balderacchi et al 2008;Pavlis et al 2010) or (e) a cross-analysis of different models of pesticide fate and the environmental indicators to underscore their relative strengths, weaknesses, similarities and dissimilarities (Dubus and Surdyk 2006).…”