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

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.

Practical solutions for making models indispensable in conservation decision‐making

“…(ii)'Grower decisions include too many judgment factors and life situation variables for the models to be useful' (Wilkerson et al, 2002). 4.…”

“…Models focus on environmental considerations of the decision context, but fail to capture the social, economic and political factors which influence conservation management options (i) 'I still think the human mind is better at processing this information if you have all the information' (a statement made by decision-maker in Hajkowicz, 2007). (ii) 'Currently available models are too simple because they do not consider the effects of cultural practices… on weed competitiveness when making recommendations' (Wilkerson et al, 2002). 5.…”

“…Models are either too complicated or too simple (i)'Although scientific models are simplifications of reality, many remain so complex that they are seen as black boxes instead of transparent analytical tools ' (De Smedt, 2010). (ii) 'From a biological standpoint… currently available models are too simple' (Wilkerson et al, 2002). 6.…”

“…7. Inadequate data quantity/quality leads to inaccurate model predictions (i)'Models themselves are currently too inaccurate to be of value in real-time decision making because insufficient data have been used in model development for them to accurately predict competitive effects and yield losses in most situations' (Wilkerson et al, 2002). (ii) Decision-makers are 'not convinced that seasonal climate forecasts can be very accurate…' and that there is 'not much point in a seasonal forecast that is vague' (a common perception of graziers (decision-makers) cited in Marshall et al, 2010).…”

Using Light Attenuation to Estimate Leafy Spurge Impacts on Forage Production

“…The user interface would present weed impact estimates in charts, tables, or other kinds of diagrams. Technology similar to this is already used in estimating some rangeland weed (Sheley et al 1997) and cropland weed (Wilkerson et al 2002) impacts. .…”