The importance of seasonal variability and tactical responses to risk on estimating the economic benefits of integrated weed management

Abstract

Seasonal variability is an important source of risk faced by farmers and, regardless of an individual's attitude to risk, there are options to tactically adjust production strategies as the outcomes of risk become known. The objective of this article is to measure the economic benefits of alternative approaches to managing weeds, one of the most serious production problems in Australian cropping systems. A bioeconomic model that combines weed biology, crop growth and economics is developed to value the effects of seasonal variability and the role of tactical responses and sequential decision making in determining an optimal integrated weed management strategy. This shows that there are substantial differences in the measured long-term benefits from deterministic and stochastic simulations. It is concluded that, for research evaluation of technologies that involve complex biological and dynamic systems, ignoring the impacts of seasonal variability, responses to risk and sequential decision making can lead to an incorrect estimate of the economic benefits of a technology. In this case study of optimal weed management strategies in Australia, the size of the error is high. Copyright 2006 International Association of Agricultural Economists.

La gestione integrata delle malerbe: un approccio sostenibile per il contenimento delle perdite di produzione e la salvaguardia dell’ambiente

“…Questo punto di vista in realtà non è unanimemente condiviso. Secondo Jones et al (2006) in condizioni deterministiche, cioè ripetendo negli anni gli stessi interventi gestionali, l'IWM aumenta il beneficio economico del 6% rispetto ai sistemi convenzionali di gestione delle malerbe. Questo valore è considerato troppo basso per indurre gli agricoltori ad adottare il sistema.…”

Optimal weed population control using nonlinear programming

“…In these papers, dynamic programming techniques are used to find the optimal strategies. In Jones and Cacho (2000) and Jones et al (2006), the optimal level of weed control that maximized economic benefits was obtained in terms of a single herbicide dose sequence. The Pontryagin Maximum Principle and dynamic programming were used in solving the considered optimal control problem.…”

“…Optimization strategies are used in several weed management programs (Jones and Cacho 2000;Jones et al 2006;Kotani et al 2009Kotani et al , 2011. In these papers, dynamic programming techniques are used to find the optimal strategies.…”

Modeling producer responses with dynamic programming: a case for adaptive crop management

“…An exception to the lack of within‐season responses in DP is the work of Jones et al. (), which evaluated a single conditional herbicide application during the year. Here we extend the concept to multiple conditional responses triggered by multiple random events.…”