David Thornby

Herbicide resistance modelling: past, present and future.

Computer simulation modelling is an essential aid in building an integrated understanding of how different factors interact to affect the evolutionary and population dynamics of herbicide resistance, and thus in helping to predict and manage how agricultural systems will be affected. In this review, we first discuss why computer simulation modelling is such an important tool and framework for dealing with herbicide resistance. We then explain what questions related to herbicide resistance have been addressed to date using simulation modelling, and discuss the modelling approaches that have been used, focusing first on the earlier, more general approaches, and then on some newer, more innovative approaches. We then consider how these approaches could be further developed in the future, by drawing on modelling techniques that are already employed in other areas, such as individual-based and spatially explicit modelling approaches, as well as the possibility of better representing genetics, competition and economics, and finally the questions and issues of importance to herbicide resistance research and management that could be addressed using these new approaches are discussed. We conclude that it is necessary to proceed with caution when increasing the complexity of models by adding new details, but, with appropriate care, more detailed models will make it possible to integrate more current knowledge in order better to understand, predict and ultimately manage the evolution of herbicide resistance.

Changes in weed species since the introduction of glyphosate-resistant cotton

Abstract. Weed management practices in cotton systems that were based on frequent cultivation, residual herbicides, and some post-emergent herbicides have changed. The ability to use glyphosate as a knockdown before planting, in shielded sprayers, and now over-the-top in glyphosate-tolerant cotton has seen a significant reduction in the use of residual herbicides and cultivation. Glyphosate is now the dominant herbicide in both crop and fallow. This reliance increases the risk of shifts to glyphosate-tolerant species and the evolution of glyphosate-resistant weeds. Four surveys were undertaken in the 2008–09 and 2010–11 seasons. Surveys were conducted at the start of the summer cropping season (November–December) and at the end of the same season (March–April). Fifty fields previously surveyed in irrigated and non-irrigated cotton systems were re-surveyed. A major species shift towards Conyza bonariensis was observed. There was also a minor increase in the prevalence of Sonchus oleraceus. Several species were still present at the end of the season, indicating either poor control and/or late-season germinations. These included C. bonariensis, S. oleraceus, Hibiscus verdcourtii and Hibiscus tridactylites, Echinochloa colona, Convolvulus sp., Ipomea lonchophylla, Chamaesyce drummondii, Cullen sp., Amaranthus macrocarpus, and Chloris virgata. These species, with the exception of E. colona, H. verdcourtii, and H. tridactylites, have tolerance to glyphosate and therefore are likely candidates to either remain or increase in dominance in a glyphosate-based system.

Using computational plant science tools to investigate morphological aspects of compensatory growth

Models of cotton plant architecture expressing several physiological hypotheses about plant resource use and responses to damage are incorporated in the traditional research cycle to investigate the phenomena of compensation for defoliation. Two separate approaches to modelling the uptake and allocation of carbon are used: a detailed bottom-up physiology model expressing ideas about local control, and a top-down, canonical approach where qualitative knowledge about plant responses to defoliation are modelled as yows between plant physiological compartments. The two models provide contrasting methods for developing explanations for the underlying pattern of responses observed in the plants.

Assessing weeds at risk of evolving glyphosate resistance in Australian sub-tropical glyphosate-resistant cotton systems

Glyphosate resistance will have a major impact on current cropping practices in glyphosate-resistant cotton systems. A framework for a risk assessment for weed species and management practices used in cropping systems with glyphosate-resistant cotton will aid decision making for resistance management. We developed this framework and then assessed the biological characteristics of 65 species and management practices from 50 cotton growers. This enabled us to predict the species most likely to evolve resistance, and the situations in which resistance is most likely to occur. Species with the highest resistance risk were Brachiaria eruciformis, Conyza bonariensis, Urochloa panicoides, Chloris virgata, Sonchus oleraceus and Echinochloa colona. The summer fallow and non-irrigated glyphosate-resistant cotton were the highest risk phases in the cropping system. When weed species and management practices were combined, C. bonariensis in summer fallow and other winter crops were at very high risk. S. oleraceus had very high risk in summer and winter fallow, as did C. virgata and E. colona in summer fallow. This study enables growers to identify potential resistance risks in the species present and management practices used on their farm, which will to facilitate a more targeted weed management approach to prevent development of glyphosate resistance.

Non-Destructive Assessment of Arundo donax (Poaceae) Leaf Quality

ABSTRACT Leaf carbon (C) content, leaf nitrogen (N) content, and C:N ratio are especially useful for understanding plant-herbivore interactions and may be important in developing control methods for the invasive riparian plant Arundo donax L. We measured C content, N content, C:N ratio, and chlorophyll index (SPAD 502 reading) for 768 leaves from A. donax collected over a five year period at several locations in California, Nevada, and Texas. Leaf N was more variable than leaf C, and thus we developed a linear regression equation for estimating A. donax leaf N from the leaf chlorophyll index (SPAD reading). When applied to two independent data sets, the equation (leaf N content % = −0.63 + 0.08 x SPAD) produced realistic estimates that matched seasonal and spatial trends reported from a natural A. donax population. Used in conjunction with the handheld SPAD 502 meter, the equation provides a rapid, non-destructive method for estimating A. donax leaf quality.

Architectural modelling of maize under water stress

Two field experiments using maize (Pioneer 31H50) and three watering regimes [(i) irrigated for the whole crop cycle, until anthesis, (ii) not at all (experiment 1) and (iii) fully irrigated and rain grown for the whole crop cycle (experiment 2)] were conducted at Gatton, Australia, during the 2003–04 season. Data on crop ontogeny, leaf, sheath and internode lengths and leaf width, and senescence were collected at 1- to 3-day intervals. A glasshouse experiment during 2003 quantified the responses of leaf shape and leaf presentation to various levels of water stress. Data from experiment 1 were used to modify and parameterise an architectural model of maize (ADEL-Maize) to incorporate the impact of water stress on maize canopy characteristics. The modified model produced accurate fitted values for experiment 1 for final leaf area and plant height, but values during development for leaf area were lower than observed data. Crop duration was reasonably well fitted and differences between the fully irrigated and rain-grown crops were accurately predicted. Final representations of maize crop canopies were realistic. Possible explanations for low values of leaf area are provided. The model requires further development using data from the glasshouse study and before being validated using data from experiment 2 and other independent data. It will then be used to extend functionality in architectural models of maize. With further research and development, the model should be particularly useful in examining the response of maize production to water stress including improved prediction of total biomass and grain yield. This will facilitate improved simulation of plant growth and development processes allowing investigation of genotype by environment interactions under conditions of suboptimal water supply.

Managing glyphosate resistance in Australian cotton farming: modelling shows how to delay evolution and maintain long-term population control

Abstract. Glyphosate resistance is a rapidly developing threat to profitability in Australian cotton farming. Resistance causes an immediate reduction in the effectiveness of in-crop weed control in glyphosate-resistant transgenic cotton and summer fallows. Although strategies for delaying glyphosate resistance and those for managing resistant populations are qualitatively similar, the longer resistance can be delayed, the longer cotton growers will have choice over which tactics to apply and when to apply them. Effective strategies to avoid, delay, and manage resistance are thus of substantial value. We used a model of glyphosate resistance dynamics to perform simulations of resistance evolution in Sonchus oleraceus (common sowthistle) and Echinochloa colona (awnless barnyard grass) under a range of resistance prevention, delaying, and management strategies. From these simulations, we identified several elements that could contribute to effective glyphosate resistance prevention and management strategies. (i) Controlling glyphosate survivors is the most robust approach to delaying or preventing resistance. High-efficacy, high-frequency survivor control almost doubled the useful lifespan of glyphosate from 13 to 25 years even with glyphosate alone used in summer fallows. (ii) Two non-glyphosate tactics in-crop plus two in-summer fallows is the minimum intervention required for long-term delays in resistance evolution. (iii) Pre-emergence herbicides are important, but should be backed up with non-glyphosate knockdowns and strategic tillage; replacing a late-season, pre-emergence herbicide with inter-row tillage was predicted to delay glyphosate resistance by 4 years in awnless barnyard grass. (iv) Weed species’ ecological characteristics, particularly seed bank dynamics, have an impact on the effectiveness of resistance strategies; S. oleraceus, because of its propensity to emerge year-round, was less exposed to selection with glyphosate than E. colona, resulting in an extra 5 years of glyphosate usefulness (18 v. 13 years) even in the most rapid cases of resistance evolution. Delaying tactics are thus available that can provide some or many years of continued glyphosate efficacy. If glyphosate-resistant cotton cropping is to remain profitable in Australian farming systems in the long-term, however, growers must adapt to the probability that they will have to deal with summer weeds that are no longer susceptible to glyphosate. Robust resistance management systems will need to include a diversity of weed control options, used appropriately.

Gene expression in response to glyphosate treatment in fleabane (Conyza bonariensis) - glyphosate death response and candidate resistance genes

BACKGROUND This study takes a whole-transcriptome approach to assess gene expression changes in response to glyphosate treatment in glyphosate-resistant fleabane. We assessed gene expression changes in both susceptible and resistant lines so that the glyphosate death response could be quantified, and constitutively expressed candidate resistance genes identified. There are three copies of the glyphosate target site (5-enolpyruvylshikimate-3-phosphate; EPSPS) gene in Conyza and because Conyza bonariensis is allohexaploid, there is a baseline nine copies of the gene in any individual. RESULTS Many genes were differentially expressed in response to glyphosate treatment. Known resistance mutations are present in EPSPS2 but they are present in a glyphosate-susceptible line as well as resistant lines and therefore not sufficient to confer resistance. EPSPS1 is expressed four times more than EPSPS2, further reducing the overall contribution of these mutations. CONCLUSION We demonstrate that glyphosate resistance in C. bonariensis is not the result of EPSPS mutations or overexpression, but due to a non-target-site mechanism. A large number of genes are affected by glyphosate treatment. We present a list of candidate non-target-site-resistance (NTSR) genes in fleabane for future studies into these mechanisms.

Complete chloroplast genome of glyphosate resistant Conyza bonariensis (L.) Cronquist from Australia

Abstract Conyza bonariensis, flaxleaf fleabane, is a serious weed in Australian agricultural systems, particularly the north-east cropping system. We present the complete chloroplast sequence of C. bonariensis reconstructed from Illumina whole genome shotgun sequencing. This is the first complete chloroplast genome available for genus Conyza. The complete chloroplast sequence is 153,014 bp long, and has the same gene content and structure as other members of the tribe Astereae. A Bayesian phylogeny of the chloroplast coding regions of 18 representatives of Astereae is presented. The C. bonariensis chloroplast genome is deposited at GenBank under accession number MF276802.

Complete chloroplast genome of glyphosate resistant Sonchus oleraceus L. from Australia, with notes on the small single copy (SSC) region orientation

Abstract Sonchus oleraceus, common sowthistle, is an asteraceous weed in Australian agricultural systems and has recently developed resistance to glyphosate. We present the complete chloroplast sequence of S. oleracueus reconstructed from Illumina whole genome shotgun sequencing. This is the first complete chloroplast genome available for the genus Sonchus. The complete chloroplast sequence is 151,808 bp long. A Bayesian phylogeny of the chloroplast coding regions of the tribe Cichorieae (Asteraceae) is presented. The S. oleraceus chloroplast genome is deposited at GenBank under accession number MG878405.