Standards for Modeling Plant Pests Roger Magarey Mid-West Weather Working Group August 3, iPIPE

Example standards Salamis stone

Information Technology (IT) Platform Hierarchy of Information Flow

Information Technology (IT) Platform Stakeholder Participation Training Government University Industry Public Education Policy Research Modeling Management Monitoring News, Programs

Publications, brochures, online info, press releases, program lists Educational Webinars Onsite seminars Public outings Meetings, speakers Public outings K-12 school projects Stimulus programs Food security Subsidies Incentives Clean Water Act Clean Air Act Section 109 State 303D CRP CREP Nutrient management plans Subsurfer manure injection Stormwater ordinances Septic system permits Volunteer conservation Severe weather alerts Best management practices Resource allocation Impaired watersheds Resource allocation Nutrient credit trading Carbon credit trading Green economics WIPs, TMDLs CAPS pest listNon-ag water pollutants Reanalysis products Management scenarios Climate manage zones Agricultural statistics Suitability indicesBackstop measuresResearch on ensemble practices Conservation systems Weather models RUSLE2, WEPS 1.0, APEX models CEAP models Step-L, WASP modelsAVGWLF, PreDICT models Chesapeake Bay (Phase 5) model Stormwater models Weather data SSURGO soil data Crop data Phenology data Stream gage data Topography data Land use and cover Watershed data Stream surveys Farm surveys Social surveys Student scientists Citizen scientists Tri-County Assoc. Londonberry Twshp. Local Municipalities Individuals PA-Universities PA-Penn Dept. Agric. PA- Chesapeake Bay PA-Conserv. Districts PA-NRCS PA-DEP PA-ARS PA-EPA NOAA-NWS USDA-NRCS USDA-NASS USDA-ARS USDA-For. Serv. USGS-NPN USGS-NSIP US-EPA Information Technology (IT) Platform Sources of U.S. Data and Information for Watershed Applications

Consequences of lack of standards It is difficult to compare models, even those constructed for the same pests, because the models have different inputs and outputs. The knowledge base for a model can easily be lost when the author retires or moves on Models are developed in many different computer languages, adding another obstacle to researchers who wish to compare, evaluate, validate or adapt existing models.

Challenges to developing standards There is great variability in the design and construction of prediction models for plant pests, weeds, and diseases due to: Biological diversity e.g., pests (weeds, fungi, arthropods, bacteria, etc.) and hosts Diversity in modeling approaches, including the choice of algorithm and the associated biological and weather inputs and outputs.

Who would standards help? Researchers (modelers) wishing to share, build, or evaluate new models or adapt existing models to new pests/hosts Extension specialists wishing to build, evaluate or archive models Public and private service providers wishing to deploy new models

Identify Agricultural Components Requiring Standards Compose a Glossary of Standard Agricultural Terms Develop a Standard API for Distribution to Industry Develop a XML Schema for Data/Information Sharing Address Security Issues of Information Ownership Create a Level Playing Field to Foster Innovation Fit Regulatory Concerns into Standards Identify Members to Lead Standards Movement AgGateway Organization and Activities

Database Structures Data Formats and Field Names Data Ownership, Privacy, and User Rights Variable Names, Definitions, and Units Model Structures and Configurations of Input and Output Application Programming Interface (API) Standard Web Services Description Language (WSDL ) Standard Security Levels for Information Equipment and Telematics Specification Guidelines and Standards Quality Control Procedures Including Objective Benchmarks Customer Service Center for Resolving Product Issues Agricultural Components Requiring Standards

Our Job is to Identify Standards for Models Potential areas for standards include Model definitions Model documentation Model inputs, outputs and parameters Model evaluation with observations Model metadata Model integration Sharing of models and/or exchange of model outputs and executables through web services (i.e. XML) Model applications especially for decision making in the field

Conclusion The advent of webservices and the AgGateway initiative provides a unique opportunity to standardize and harmonize agricultural modeling, with plant pest models leading the way.