Development of a Prototype Weed Management Model

Institution: University of Maine
Sponsor: Senator George J. Mitchell Center for Sustainability Solutions

A decision-aid to improve weed management on Maine organic farms

hairy galinsogaThis project is developing a decision-aid tool to improve the economic sustainability of Maine organic farmers through improved weed management. Stakeholders will be included in the development of this tool and will also help publicize the finished product. Project researchers will synthesize results from the model underpinning this decision-aid to gain insight that will help identify priorities for future research.

A growing sector with a major production challenge
Farming is a growing sector of the Maine economy, with substantial increases over the past 10 years in the number of farms (17 percent), value of agricultural products (65 percent), and number of farmers under the age of 34 (46 percent). Many Maine farmers choose to grow organically, motivated by deeply held commitments to environmental sustainability. Organic farming practices are typically more environmentally sustainable than conventional practices. However, economic sustainability is a challenge.

Agricultural weeds are a foremost production challenge on organic farms in the Northeast. There is clear need and support in the organic farming community for tools to help farmers effectively target specific weed issues.

This project will leverage existing datasets to create a model that will simulate the impacts of multiple weed control tactics, incorporated into realistic farm management rotations, on the population dynamics of weed species problematic to Maine organic vegetable farmers. This weed management model is novel; we are aware of no other efforts to implement such a model for organic vegetable systems.  Models of this kind are useful in that they offer relatively low-cost means of utilizing existing data to greatly expand existing knowledge.

The model will form the basis of a web-based decision-aid that will assist farmer decision making by allowing farmers to virtually experiment with farm management rotations and see the impacts on the populations and seedbanks of target weed problems.

Team Leader

Eric Gallandt
, School of Food and Agriculture, UMaine

Team Members

David Hiebeler
, Department of Mathematics and Statistics, UMaine

Aaron Hoshide
, School of Economics, UMaine & Farmer at EIEIO Farm (Bangor, ME)

Sonja Birthisel
, PhD Student in Ecology and Environmental Sciences