You cannot fight fire with fire: a demographic model suggests alternative approaches to manage multiple herbicide‐resistant Avena fatua

Abstract

Multiple herbicide-resistant (MHR) weed populations pose significant agronomic and economic threats and demand the development and implementation of ecologically based tactics for sustainable management. We investigated the influence of nitrogen fertiliser rate (56, 112, 168, or 224 kg N ha À1 ) and spring wheat seeding density (67.3 kg ha À1 or 101 kg ha À1 ) on the demography of one herbicide susceptible and two MHR Avena fatua populations under two cropping systems (continuous cropping and crop-fallow rotation). To represent a wide range of environmental conditions, data were obtained in field conditions over 3 years (2013)(2014)(2015). A stochastic density-dependent population dynamics model was constructed using the demographic data to project A. fatua populations. Elasticity analysis was used to identify demographic processes with negative impacts on population growth. In both cropping systems, MHR seedbank densities were negatively impacted by increasing nitrogen fertilisation rate and wheat density. Overall, MHR seedbank densities were larger in the wheat-fallow compared with the continuous wheat cropping system and seedbank densities stabilised near zero in the high nitrogen and high spring wheat seeding rate treatment. In both cropping systems, density-dependent seed production was the most influential parameter impacting population growth rate. This study demonstrated that while the short-term impact of weed management tactics can be investigated by field experiments, evaluation of long-term consequences requires the use of population dynamics models. Demographic models, such as the one constructed here, will aid in selecting ecologically based weed management tactics, such as appropriate resource availability and modification to crop competitive ability to reduce the impact of MHR.

Mitigating agricultural intensification in the Western Cape with landscape elements: a synopsis of applicable ecological weed management strategies

“…Perennial row crops lends themselves to intra-row application of biomass mulches in the form of wood chips or straw bales with modified manure spreaders. In approach that will enhance sustainable production (Burns et al, 2018). Bunchek et al (2020) suggested the application IWM principles that include complementary herbicidal and non-chemical weed management decisions based on an ecological foundation.…”

“…Diversity in tactics and strategy are based on both IWM and sustainable agro-ecosystems. Furthermore, practices that decrease seed production coupled with those that increase greater weed mortality are deemed as alternatives to herbicide applications, since they reduce the risk of selection pressure (Burns et al, 2018).…”

Estimations and projections of Avena fatua dynamics under multiple management scenarios in crop fields using simplified longitudinal monitoring

“…Several strategies have already been examined [ 17 ] such as crop rotation [ 18 – 21 ], changing sowing times [ 22 , 23 ], using competitive crops or cultivars [ 24 , 25 ], and increasing seeding densities [ 26 ], increasing soil water content to reduce the A . fatua seed bank [ 27 , 28 ], and combination of them in management cycles [ 18 – 20 , 29 ]. However, there is a limit to the number of experimental treatments that can be examined simultaneously or repetitively.…”

Seed predation is key to preventing population growth of the weed Alopecurus myosuroides

“…Plant population modelling makes it possible to link seed predation with weed species‐specific population growth. Weed population models are often used as tools in weed management decision making, to forecast weed species abundance and associated crop losses under different management strategies (Burns et al., 2018; Davis et al., 2004; Liebman & Nichols, 2020). However, predicting plant population dynamics is challenging, due to the unpredictability of environmental conditions, the natural variation in plant fitness, reproduction and mortality induced by genetic variability and epigenetics, and uncertainties associated with parameter estimates (Holst et al., 2007).…”