Simulation Models on the Ecology and Management of Arable Weeds: Structure, Quantitative Insights, and Applications

BAGAVATHIANNAN, MUTHUKUMAR V.; BECKIE, HUGH J.; CHANTRE, GUILLERMO R.; GONZALEZ-ANDUJAR, JOSE L.; LEON, RAMON G.; NEVE, PAUL; POGGIO, SANTIAGO L.; SCHUTTE, BRIAN J.; SOMERVILLE, GAYLE J.; WERLE, RODRIGO; ACKER, RENE VAN

Agronomy

MDPI

Lugar: Basilea; Año: 2020 vol. 10 p. 1 - 24

In weed science and management, models are important and can be used to better understand what has occurred in management scenarios, to predict what will happen and to evaluate the outcomes of control methods. To-date, perspectives on and the understanding of weed models have been disjointed, especially in terms of how they have been applied to advance weed science and management. This paper presents a general overview of the nature and application of a full range of simulation models on the ecology, biology, and management of arable weeds, and how they have been used to provide insights and directions for decision making when long-term weed population trajectories are impractical to be determined using field experimentation. While research on weed biology and ecology has gained momentum over the past four decades, especially for species with high risk for herbicide resistance evolution, knowledge gaps still exist for several life cycle parameters for many agriculturally important weed species. More research efforts should be invested in filling these knowledge gaps, which will lead to better models and ultimately better inform weed management decision making.