Project Description

Since 1996, IPPC has been developing and maintaining a weather and climate driven decision support website for pest management and related agricultural needs. Beginning with a small number of insect models, this program has grown into a complex system of models, weather networks and advanced features. As of June 2017, there are over 140 pest and crop models (see details below) integrated with over 29,000 real-time weather stations from hundreds of weather networks across the United States. These searchable models integrate weather forecasts from several sources.

Project Aims

This program carries multiple aims:

  • To provide a free, comprehensive website for accessing weather and climate models of all types to support IPM decision-making;
  • To develop a nation-wide IPM resource that includes access for under-served regions and cropping systems;
  • To develop models that accurately predict key pest development points as an aid in management decision making;
  • To integrate both site-based and mapping-based tools for local and synoptic/region-wide services;
  • To integrate multiple models, tools, and features in one place, including:
    • multiple models with common inputs and outputs;
    • short and long-term forecasts;
    • climate data;
    • comparisons with recent and past predictions;
    • quality assurance;
    • graphical and tabular outputs;
    • and full transparency of the input weather data used to drive models.

Project Outcomes

Currently, we have 15 invasive insect models, 47 insect pest models, 32 crop models, 24 disease risk models, 5 weed models, 2 tree fruit dormancy (chilling requirement) models, 2 predator mite models, 1 endangered species (a butterfly) model, 3 pesticide drift model prediction aids, a soil solarization model (currently for 2 species of Phytophthora), a grass seed stem rust simulation model, and 1 mating disruption dispenser model in the system, along with generic degree-day and plant disease risk models for exploratory research needs. Weather data is obtained in real-time from 100’s of weather networks totaling over 29,000 weather stations.

Key Activities

Model BuildingBased upon requests made by growers, extension, researchers, and others, we select “best available” research and field monitoring data to build new models for the system, and independently validate the models whenever possible. The models are then readily added to the modular, open-source software system.

Weather Database: Most weather data is public and free for non-profit use as supplied by the Utah MesoWest system. We also custom-integrate several agricultural weather networks that are not part of Mesowest. There is no singular state-run agricultural weather network for the state of Oregon at this time, and IPPC has no actual weather station hardware maintenance to perform. This is undertaken by participating and cooperating networks, including:

AGRIMET (Bureau of Reclamation, US Dept. of the Interior)

AgWeatherNET (Washington State University)

ADCON (A private weather station hardware manufacturer)

CIMIS (California Irrigation Management Information System)

California PestCast (Univ. California crop disease management network)

ASOS/METAR (Automated Surface Observing System, using METAR formatted data)

RAWS (Remote Automated Weather Station, run by several US Federal Agencies)

APRSWXNET/CWOP (Automatic Position Reporting System Weather Network/Citizen Weather Observer Program)

“Added Value” Features: There are a number of innovative features such as:

  • Short and long-term forecasts, including 2 separate 7-day forecasts, a 3-month (CFSv2) extended forecast, and a 7-month (NMME) extended forecast;
  • Interactive charts that show a range of projected outcomes using 7 different methods to forecast weather data;
  • A system to fill in missing data with “virtual”, estimated data
  • A “Degree-Day Clock” tool that allows comparison of current season heat units to past years (e.g. reporting that we are for example “10 days behind last year and 10 days ahead of normal”);
  • Gridded map products: including interactive degree-day maps;

These features are built using funding from purpose-driven grants (largely from USDA NIFA, USDA SARE, and USDA-APHIS-PPQ), and priorities are determined through feedback from growers, researchers, extension agents, and other end-users who request models and features to support their pest management production, research or extension needs.

“MyPest Page”: programmed to be able to integrate new models and features, this prototype feature provides an entry point for IPM, whereby multiple insect pests, diseases, weeds, crops, and beneficial organisms can be modeled from a single web-based user interface.

Training and outreach: This system is regularly demonstrated to growers at events around the PNW region, and several “webinar” tutorials are on the website that demonstrate how the tools can be used. Trade publications often highlight the system as it applies to one or a few models. One-on-one training via the phone remains a good way to initiate a new user to use the website to meet their particular needs.

IPM Impacts

Coop, L. 2017. Web based decision tools for pest management: New and Used. Pesticide Recertification Course. Jan 24, 2017. Central Point, OR. 1 hr invited talk.

Coop, L and N. Andrews. 2016. Weather forecasting (long-term forecasts) and future capacity for the modeling system and user interface. In: Introducing and Using CROPTIME: Vegetable Crop Schedule with Degree-Days. 2.5 hr lecture and hands-on computer workshop. 2016 Small Farms Conference. Feb. 20, 2016. Corvallis, OR.

Coop, L. 2016. Integrated Pest Management as it Relates to Climate. Blue Mountain Horticulture Society Annual Meeting. Feb. 10, 2016. Milton Freewater, OR.

Coop, L. and G. Cook. 2015. DDRP Mapping: Degree-day, Risk, and Pest Event Maps. Invited talk. USDA-APHIS-PPQ-CPHST. Dec. 9, 2015. Ft. Collins, CO.

Andrews, N., L. Coop, and H. Noordijk. 2015. Scheduling vegetables using degree-days. New crop planning, planting model from Oregon State University. Tilth Producers Quarterly 25:4:1-6.

Andrews, N., L. B. Coop, H. E. Noordijk, and J. R. Myers. 2015. Crop Time: Degree-day Models and an Online Decision Tool for the Vegetable Industry. HortScience Supplement. 50:S138.

Coop, L. 2015. Pest Phenology Model Development & Online Tools. Oregon Agric. Extension Assoc. invited presentation. Apr 28, 2015, Medford, OR.

Coop, L. 2015. NW Pest Prediction Models Using Weather Data. IR-4 State Commodity Liaison Meeting. Invited presentation. Apr 22, 2015, Portland, OR.

Coop, L., P. Jepson, and C. Landgren. 2015. Tools for sprayers and IPM innovators – with focus on aphids and midges. Oregon Christmas Tree Assoc. Meeting. Mar 6, 2015. Wilsonville, OR.

Coop, L. 2015. Crops and Climate – Has it been getting warmer in the Pacific Northwest and how will that affect plant/crop phenology. FRED Talk (Food and Farming Research Extension and Development). Small Farms Conference. Corvallis OR Feb. 28th 2015.

Andrews, N., D. Andrews, L. Coop. Croptime: Crop Phenology Models Interface Usability Tests. NWREC Aurora, OR. Jan 27, 2015.

Andrews, N., C. Bubl, L. Coop, A. Garrett, S. Kawai, J. Myers, H. Noordijk, E. Peachey, and D. Sullivan. Croptime: Vegetable degree-days. NW Horticultural Soc. Ann. Mtg. Jan 13, 2015, Canby, OR.

Coop, L. and A. Dreves. 2014. Using a phenology model for spotted wing Drosophila. SWD Tool Conversations - Extension Worksop. NWREC Aurora, OR Dec 11, 2014.

Coop, L. 2014. Phenology model for the omnivorous leaftier, Cnephasia longana: reviving intensive research from a bygone ear. Presentation at ESA National Meeting, Portland, OR, Nov. 23, 2014.

Coop, L. 2014. The Best/Worst Time for Pathogens. New, weather-driven risk models indicate when box blight and apple scab are more likely to spread. Growing Knowledge Article in Digger Magazine Pub. by The Ore. Assoc. of Nurseries. Oct. 2014.

Kaiser, C., Christensen, J.M., Coop, L. and Masterson, K., 2014. Collaboration and Grant Writing in County Extension. OSUEA Annual Conference, Corvallis, OR – Sept 2014. (Invited Presentation)

Kaiser, C., Coop, L. and Meland, M., 2014. Developing a robust, predictive model for sweet cherry (Prunus avium L.) flowering, comparing eastern Oregon and mesic Nordic climates. ASHS Annual Conference. July 22-29, 2014. Orlando, FL.

Kaiser, C. and Coop, L., 2014. Camp program in the Walla Walla Valley. NACAA Annual Conference, July 19-24, 2014. Mobile, AL. (Invited presentation for National Award – Search for Excellence).

Coop, L. 2014. Spotted Wing Drosophila: Predict Spring Activity and Generation Increase: Degree Day Model. NWREC Spotted Wing Drosophila Extension Workshop May 22, 2014. Aurora, OR.

Coop, L. 2014. Boxwood Blight: Epidemiology and Monitoring. Developing a Predictive Model for the United States. 2014 Boxwood Summit. May 13, 2014. Beltsville, Maryland.

Coop, L. 2014. Tree fruit decision support – phenology and plant disease risk models. Presentation at N. Willamette Tree Fruit Growers Meeting. Feb. 15, 2014. Salem, Oregon.

Coop, L. 2014. Weather data and weed control: degree-day models and pesticide drift forecasts. Presentation at Douglas County Weed Day 2014. Feb. 5, 2014. Roseburg, Oregon.

Coop, L. 2014. Using phenology models and pheromone traps. Presentation at IPPC Chemical Applicators Short Course, Jan. 7, 2014. Wilsonville, Oregon.

Coop, L., F. Grevstadt, and G. Cook. 2014. Pest event mapping: a new tool to aid in prediction of insect phenology. Presentation and paper presented at: Pacific Northwest insect management conference. Jan. 6, 2014, Portland, Oregon.