Modeling the Population Dynamics and Management of Italian Ryegrass under Two Climatic Scenarios in Brazil

Abstract

Italian ryegrass (Lolium multiflorum L.) is an annual grass widely distributed in cultivated crops around the world. This weed causes significant yield reduction in many crops and has developed herbicide resistance. The aim of this study was to develop a cohort-based stochastic population dynamics model that integrates both emergence (thermal time) and dynamic population models as a tool to simulate the population dynamics of susceptible and resistant populations of L. multiflorum under the effects of climate change. The current climate scenario and the increase in the average air temperature by 2.5 °C were considered. Chemical and cultural management strategies commonly used in the South Region of Brazil during the winter and summer seasons were incorporated into the model. In the absence of control and under the current climate conditions, the seed bank population grew until reaching an equilibrium density of 19,121 ± 371 seeds m−2 for the susceptible and 20463 ± 363 seeds m−2 for the resistant populations. Considering the second climate scenario, the seed bank reaches an equilibrium density of 24,182 ± 253 seeds m−2 (+26% in relation to the current scenario) for the susceptible population and 24,299 ± 254 seeds m−2 (+18% in relation to the current scenario) for the resistant one. The results showed that the effect of the rise in temperature implies an increase in population in all the management strategies in relation to the current climate scenario. In both climate scenarios, the strategies based on herbicides application controlling cohorts 1 and 2 were the most efficient, and cropping systems including winter oat-soybeans rotation had a smaller impact on the L. multiflorum seed bank than crop rotations including winter wheat or summer corn. Crop rotations including wheat and corn for L. multiflorum management as an adaptive strategy under the future climate change are suggested.

Keywords

• <i>lolium multiflorum</i>
• stochastic model
• climate change
• seed bank
• management strategies