RESUMO
Herbicide resistance is an evolutionary process that affects entire agricultural regions' yield and productivity. The high number of farms and the diversity of weed management can generate hot selection spots throughout the regions. Resistant biotypes can present a diversity of mechanisms of resistance and resistance factors depending on selective conditions inside the farm; this situation is similar to predictions by the geographic mosaic theory of coevolution. In Mexico, the agricultural region of the Bajio has been affected by herbicide resistance for 25 years. To date, Avena fatua L. is one of the most abundant and problematic weed species. The objective of this study was to determine the mechanism of resistance of biotypes with failures in weed control in 70 wheat and barley crop fields in the Bajio, Mexico. The results showed that 70% of farms have biotypes with target site resistance (TSR). The most common mutations were Trp-1999-Cys, Asp-2078-Gly, Ile-2041-Asn, and some of such mutations confer cross-resistance to ACCase-inhibiting herbicides. Metabolomic fingerprinting showed four different metabolic expression patterns. The results confirmed that in the Bajio, there exist multiple selection sites for both resistance mechanisms, which proves that this area can be considered as a geographic mosaic of resistance.
RESUMO
Perennial plants which propagate through both seeds and rhizomes are common in agricultural and nonagricultural systems. Due to their multifaceted life cycle, few population models are available for studying such species. We constructed a novel individual-based model to examine the effects of ecological, evolutionary, and anthropogenic factors on the population dynamics of perennial species. To exemplify the application of the model, we presented a case study of an important weed, Sorghum halepense (L.) Pers. (Johnsongrass), in soybean productions in Argentina. The model encompasses a full perennial weed life cycle with both sexual (seeds) and asexual (rhizomes) propagations. The evolution of herbicide resistance was modeled based on either single genes or quantitative effects. Field experiments were conducted in the species' native environment in Argentina to parameterize the model. Simulation results showed that resistance conferred by single-gene mutations was predominantly affected by the initial frequency of resistance alleles and the associated fitness cost. Population dynamics were influenced by evolved resistance, soil tillage, and rhizome fecundity. Despite the pivotal role of rhizomes in driving the population dynamics of Johnsongrass, most herbicides target the aboveground biomass, and chemical solutions to control rhizomes are still very limited. To maintain effective (short-term) and sustainable (long-term) weed management, it is recommended to combine soil tillage with herbicide applications for suppressing the rhizomes and delaying the evolution of resistance. This novel model of seed- and rhizome-propagated plants will also be a useful tool for studying the evolutionary processes of other perennial weeds, cash crops, and invasive species.