| For 2020 and newer grants, please go to https://grants.ipmcenters.org/ |
|---|
|
|
| Home Current RFAs PD User Guide Projects Login |
|
Funded Project |
|
Funding Program:
Regional IPM Competitive Grants - Northeastern |
|
Project Title:
Verification of Web-based Real-time High-resolution Weed and Insect Predictive Models for Northeast IPM Programs |
Project Directors (PDs):
|
|
Lead State: PA Lead Organization: Pennsylvania State University |
| Extension Funding: $22,692 |
| Research Funding: $37,308 |
|
Start Date: Jul-01-2004 End Date: Jun-30-2006 |
|
Pests Involved: weeds, insects |
|
Area of Emphasis: modeling, forecasting, phenology |
|
Summary:
Many mathematical models of insect and weed development are available to help predict pest management activities. The use of these models, however, has been limited by the need for high quality weather data inputs and software to run them. In 2003, the first high-resolution real-time prediction models that use up-to-date spatially interpolated (10 km2 resolution) temperature data were made available through the Penn State Departments of Entomology and Crop and Soil Sciences websites. The underlying models were site verified at specific locations, but have not had wide-scale verification. Therefore, this project proposes to collect verification data from multiple climatic/crop production regions in Pennsylvania to assure the models are adequately tracking pest development at an accuracy required for pest management. The systems are designed as an early warning system to alert farmers and pest management professional to impending pest populations. Although the verification process is currently limited to Pennsylvania, the climatic zones represented are common across most of the field crop production region of the Northeast and Mid-Atlantic. If the models track properly across Pennsylvania, they are likely to be on target in other areas of the region. The maps are currently being provided to other cooperating states in the region.
Problem, Justification, and Background Integrated Pest Management is defined as the use of multiple management tactics to maintain pest populations below economic levels in an environmentally and socially acceptable manner (Stern et al. 1959). Historically, however, synthetic pesticides have been the dominant tactic of choice, both to prevent and rescue crops from injury. Their relatively low cost has lead growers to use them as cheap insurance rather than when needed. The overuse of pesticides has lead to increased risk of adverse affects on the environment and human health and lower farm profits. Farmers have used this approach because of the profit risk they perceived, their lack of understanding of pest biology, and lack of reliable tools to predict timing of pest occurrence. In order for farmers to move away from over reliance on pesticides, reliable economic thresholds, sampling methods, management tools, and tools to time pest management activities are needed. Although all these tactics are important for an IPM program, timing of key events is probably the most difficult yet also the most important component. Without accurate straightforward methods to time critical events, such as scouting and pest management intervention, significant inefficiencies develop that result in failure and reduced profit to growers. Properly timing management tactics requires an understanding of environmental factors that drive development of key pest species. Insect and weed development increases as the temperature rises and slows as the temperature declines (poikilothermic). Weeds can also have moisture and light requirements for germination and growth. Arnold (1959) was the first to develop an index of temperature to drive crop and pest development. This was the heat unit or degree-day concept, which is a measure of the amount of heat available within a 24-hour period to drive an organism's development. The degree-day requirements of a specific organism are estimated by relating the rate of development, expressed as 1/days, at constant temperatures in a linear regression equation. Extrapolation of the linear line to the temperature where development is predicted to be zero provides the threshold of development (TD) for the species and for individual life stages of the species. These TDs typically vary from around 9 oC for cool temperature adapted species to 15 oC for warm temperature adapted species. Non-linear models can also be used, but degree-day accumulations remain the most widely used approach because of their simplicity. Once quantified, these mathematical models can be used to predict when an organism's population will reach key life stages that are important in pest management. Because development of crops, insects and weeds are temperature dependent, their temporal occurrence during the season is greatly influenced by physical features of the region. (Appendix Ia). Appendix Ia illustrates the great topographic relief differences that exist in the Northeast and Mid-Atlantic regions. The seasonal degree-day accumulations in this region are greatly affected by this variation in relief and the latitudinal gradient (Appendix Ib). It can be seen in Appendix Ib for Pennsylvania that the accumulation of degree days for European corn borer development varies spatially from 700 to 1400. This indicates that in the warmest areas of the state, there are twice the heat units for the pest population to development than in the cooler more northern region. In fact, the pest typically completes two to three generations in the southeast and south central regions of the state and only one in the north central region. Model simulation for the European corn borer have indicated that the second generation egg laying period can vary by up to five weeks between locations in the state and up to five weeks between years at the same location. Similar differences are seen for other insect pests. This variation can also have a major impact on spring and summer weed emergence periods. In the warmer southern areas, weed emergence occurs earlier on average and may occur over a longer or shorter time period depending on species than in cooler northern areas. These differences can greatly influence the timing and effectiveness of weed management tactics. A farmer trying to optimize the timing of pest management activities would have a difficult time knowing when to begin and stop scouting and when to implement a control tactic (chemical, mechanical, or biological). Uncertainty surrounding when to implement pest management activity greatly increases the time for scouting and adds inefficiency into control efforts, which increases the cost of IPM programs and reduces the effectiveness of management tactics. Objectives: 1. Verify and demonstrate each phenology model's reliability for timing key weed emergence periods and insect life stages across climatic regions of Pennsylvania. 2. Conduct educational training sessions with farmers, consultants, and agricultural professionals to demonstrate the use of the phenology model tools. USDA CRIS data Progress Report 2005 Final Report 2006 |
| Close Window |
|
Northeastern IPM Center 340 Tower Road Cornell University Ithaca, NY 14853 NortheastIPM.org |
 |
Developed by the Center for IPM © Copyright CIPM 2004-2026 |
|