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Weed management decision models: pitfalls, perceptions, and possibilities of the economic threshold approach

Published online by Cambridge University Press:  20 January 2017

Gail G. Wilkerson ,
Lori J. Wiles  and
Andrew C. Bennett
Lori J. Wiles
Affiliation:
USDA-ARS-WMU, AERC—Colorado State University, Fort Collins, CO 80523
Andrew C. Bennett
Affiliation:
Everglades Research and Education Center, 3200 East Palm Beach Road, Belle Glade, FL 33430-4702
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Abstract

The use of scouting and economic thresholds has not been accepted as readily for managing weeds as it has been for insects, but the economic threshold concept is the basis of most weed management decision models available to growers. A World Wide Web survey was conducted to investigate perceptions of weed science professionals regarding the value of these models. Over half of the 56 respondents were involved in model development or support, and 82% thought that decision models could be beneficial for managing weeds, although more as educational rather than as decision-making tools. Some respondents indicated that models are too simple because they do not include all factors that influence weed competition or all issues a grower considers when deciding how to manage weeds. Others stated that models are too complex because many users do not have time to obtain and enter the required information or are not necessary because growers use a zero threshold or because skilled decision makers can make better and quicker recommendations. Our view is that economic threshold–based models are, and will continue to be, valuable as a means of providing growers with the knowledge and experience of many experts for field-specific decisions. Weed management decision models must be evaluated from three perspectives: biological accuracy, quality of recommendations, and ease of use. Scientists developing and supporting decision models may have hindered wide-scale acceptance by overemphasizing the capacity to determine economic thresholds, and they need to explain more clearly to potential users the tasks for which models are and are not suitable. Future use depends on finding cost-effective methods to assess weed populations, demonstrating that models use results in better decision making, and finding stable, long-term funding for maintenance and support. New technologies, including herbicide-resistant crops, will likely increase rather than decrease the need for decision support.

Keywords

Bioeconomic modelsdecision support systemscomputer decision aids
Type
Research Article
Information
Weed Science , Volume 50 , Issue 4 , August 2002 , pp. 411 - 424
Copyright
Copyright © Weed Science Society of America 

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