The roles of soft technologies and cooperative extension in solving wicked integrated pest management problems.

Abstract

Notwithstanding the many failures and shortcomings attributed to implementations of integrated pest management (IPM), IPM inclusive of the transdisciplinary needs of its stakeholders is the only rational strategy for addressing 'wicked' as well as 'tame' pest management problems. Examples that support this hypothesis are provided throughout this chapter. The chapter aims to provide a balanced perspective of IPM, focusing on how it is practised in the US. Because it suggests that IPM works best when soft (handled by people) and hard (do not require human oversight) technologies are utilized in concert, examples are given of complications where soft technologies were not developed or not optimally deployed to complement hard technologies for IPM. These examples focus on the shortcomings of soft technologies primarily because it is more common for these to be deficient rather than the hard technologies. Towards this effort, discussion focuses on two themes: (i) industry-wide adoption of single tactic leading to overdependence, and (ii) behaviours of consumers and producers. The chapter also provides two contrasting examples of IPM successes that support the position that IPM functions best when hard and soft technologies are harmonized. The first is an example of a nascent IPM programme for Aphis glycines in Midwestern US soyabean, while the second is an example of a mature IPM system in Arizona cotton.

Developing a decision‐making framework for insect pest management: a case study using Aphis glycines (Hemiptera: Aphididae)

“…In systems where crops are economically injured by few pests, such as the Midwest United States, pest management budgets could help farmers comprehend the impact of decision‐making on revenue and guide adoption of IPM principles. Financial models and budgeting techniques for pest management options are most useful if designed to be easily adjusted for different environments or crop–pest systems 9 . Probability models explicitly address uncertainty associated with decision‐making and allow for inputs to be changed as new information becomes available, which is imperative to the success of a model that accounts for sporadic pests 10 .…”