Tracking Ideal Varieties and Cropping Techniques for Agroecological Weed Management: A Simulation-Based Study on Pea

Pea or Pisum sativum L. is a key diversification crop, but current varieties are not very competitive against weeds. The objective was to identify, depending on the type of cropping system and weed flora, (1) the key pea parameters that drive crop production, weed control and weed contribution to biodiversity, (2) optimal combinations of pea-parameter values and crop-management techniques to maximize these goals. For this, virtual experiments were run, using FLORSYS, a mechanistic simulation model. This individual-based 3D model simulates daily crop-weed seed and plant dynamics over the years, from the cropping system and pedoclimate. Here, this model was parameterized for seven pea varieties, from experiments and literature. Moreover, ten virtual varieties were created by randomly combining variety-parameter values according to a Latin Hypercube Sampling (LHS) plan, respecting parameter ranges and correlations observed in the actual varieties. A global sensitivity analysis was run, using another LHS plan to combine pea varieties, crop rotations and management techniques in nine contrasting situations (e.g., conventional vs. organic, no-till, type of weed flora). Simulated data were analyzed with classification and regression trees (CART). We highlighted (1) Parameters that drive potential yield and competitivity against weeds (notably the ability to increase plant height and leaf area in shaded situations), depending on variety type (spring vs. winter) and cropping system. These are pointers for breeding varieties to regulate weeds by biological interactions; (2) Rules to guide farmers to choose the best pea variety, depending on the production goal and the cropping system; (3) The trade-off between increasing yield potential and minimizing yield losses due to weeds when choosing pea variety and management, especially in winter peas. The main pea-variety rules were the same for all performance goals, management strategies, and analyses scales, but further rules were useful for individual goals, strategies, and scales. Some variety features only fitted to particular systems (e.g., delayed pea emergence is only beneficial in case of herbicide-spraying and disastrous in unsprayed systems). Fewer variety rules should be compensated by more management rules. If one of the two main weed-control levers, herbicide or tillage, was eliminated, further pea-variety and/or management rules were needed.

Populations of arable weed species show intra-specific variability in germination base temperature but not in early growth rate

Key plant traits affecting growth performance can differ among and within species, influencing competitive plant community dynamics. We determined the intra-specific variability of germination base temperature among 13 arable weed species and the seedlings' early post-emergence relative growth rate among 21 species in climate chamber and green house experiments. Intra-specific variability was quantified with two seed populations (originating from contrasting climate in Germany & France) for the germination base temperature of 6 species and for the early growth rate of 16 species. Inter-specific variability for both traits was always higher than intra-specific variability. Within a given species, we found that germination base temperatures were higher in seeds stemming from colder climate populations. Seedling relative growth rates did not differ between seed populations. Models simulating weed growth should reflect these differences in germination traits among populations, especially when they are used for weed community assembly studies in a local to regional extent.

Relationship between weed dormancy and herbicide rotations: implications in resistance evolution

It is suggested that selection for late germinating seed cohorts is significantly associated with herbicide resistance in some cropping systems. In turn, it is conceivable that rotating herbicide modes of action selects for populations with mutations for increased secondary dormancy, thus partially overcoming the delaying effect of rotation on resistance evolution. Modified seed dormancy could affect management strategies - like herbicide rotation - that are used to prevent or control herbicide resistance. Here, we review the literature for data on seed dormancy and germination dynamics of herbicide-resistant versus susceptible plants. Few studies use plant material with similar genetic backgrounds, so there are few really comparative data. Increased dormancy and delayed germination may co-occur with resistance to ACCase inhibitors, but there is no clear-cut link with resistance to other herbicide classes. Population shifts are due in part to pleiotropic effects of the resistance genes, but interaction with the cropping system is also possible. We provide an example of a model simulation that accounts for genetic diversity in the dormancy trait, and subsequent consequences for various cropping systems. We strongly recommend adding more accurate and detailed mechanistic modelling to the current tools used today to predict the efficiency of prevention and management of herbicide resistance. These models should be validated through long-term experimental designs including mono-herbicide versus chemical rotation in the field. © 2017 Society of Chemical Industry.

Simulating changes in cropping practices in conventional and glyphosate-resistant maize. II. Weed impacts on crop production and biodiversity

Overreliance on the same herbicide mode of action leads to the spread of resistant weeds, which cancels the advantages of herbicide-tolerant (HT) crops. Here, the objective was to quantify, with simulations, the impact of glyphosate-resistant (GR) weeds on crop production and weed-related wild biodiversity in HT maize-based cropping systems differing in terms of management practices. We (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, with the weed dynamics model FLORSYS; (2) quantified how much the presence of GR weeds contributed to weed impacts on crop production and biodiversity; (3) determined the effect of cultural practices on the impact of GR weeds and (4) identified which species traits most influence weed-impact indicators. The simulation study showed that during the analysed 28 years, the advent of glyphosate resistance had little effect on plant biodiversity. Glyphosate-susceptible populations and species were replaced by GR ones. Including GR weeds only affected functional biodiversity (food offer for birds, bees and carabids) and weed harmfulness when weed effect was initially low; when weed effect was initially high, including GR weeds had little effect. The GR effect also depended on cultural practices, e.g. GR weeds were most detrimental for species equitability when maize was sown late. Species traits most harmful for crop production and most beneficial for biodiversity were identified, using RLQ analyses. None of the species presenting these traits belonged to a family for which glyphosate resistance was reported. An advice table was built; the effects of cultural practices on crop production and biodiversity were synthesized, explained, quantified and ranked, and the optimal choices for each management technique were identified.

Simulating changes in cropping practises in conventional and glyphosate-tolerant maize. I. Effects on weeds

Herbicide-tolerant (HT) crops such as those tolerant to glyphosate simplify weed management and make it more efficient, at least at short-term. Overreliance on the same herbicide though leads to the spread of resistant weeds. Here, the objective was to evaluate, with simulations, the impact on the advent of glyphosate resistance in weeds of modifications in agricultural practises resulting from introducing HT maize into cropping systems. First, we included a single-gene herbicide resistance submodel in the existing multispecific FLORSYS model. Then, we (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, (2) compared these systems in terms of glyphosate resistance, (3) identified pertinent cultural practises influencing glyphosate resistance, and (4) investigated correlations between cultural practises and species traits, using RLQ analyses. The simulation study showed that, during the analysed 28 years, (1) glyphosate spraying only results in glyphosate resistance in weeds when combined with other cultural factors favouring weed infestation, particularly no till; (2) pre-sowing glyphosate applications select more for herbicide resistance than post-sowing applications on HT crops; and (3) glyphosate spraying selects more for species traits avoiding exposure to the herbicide (e.g. delayed early growth, small leaf area) or compensating for fitness costs (e.g. high harvest index) than for actual resistance to glyphosate, (4) actual resistance is most frequent in species that do not avoid glyphosate, either via plant size or timing, and/or in less competitive species, (5) in case of efficient weed control measures, actual resistance proliferates best in outcrossing species. An advice table was built, with the quantitative, synthetic ranking of the crop management effects in terms of glyphosate-resistance management, identifying the optimal choices for each management technique.

Choosing the best cropping systems to target pleiotropic effects when managing single-gene herbicide resistance in grass weeds. A blackgrass simulation study

BACKGROUND

Managing herbicide-resistant weeds is becoming increasingly difficult. Here we adapted the weed dynamics model AlomySys to account for experimentally measured fitness costs linked to mutants of target-site resistance to acetyl-coenzyme A carboxylase (ACCase)-inhibiting herbicides in Alopecurus myosuroides. We ran simulations to test how effectively cultural practices manage resistance.

RESULTS

Simulations of an oilseed rape/winter wheat/winter barley rotation showed that, when replacing one of the seven applied herbicides with an ACCase-inhibiting one, resistant mutants exceeded 1 plant m(-2) , with a probability of 40%, after an average of 18 years. This threshold was always exceeded when three or four ACCase-inhibiting herbicides were used, after an average of 8 and 6 years respectively. With reduced herbicide rates or suboptimal spraying conditions, resistance occurred 1-3 years earlier in 50% of simulations. Adding spring pea to the rotation or yearly mouldboard ploughing delayed resistance indefinitely in 90 and 60% of simulations respectively. Ploughing also modified the genetic composition of the resistant population by selecting a previously rare mutant that presented improved pre-emergent growth. The prevalence of the mutations was influenced more by their associated fitness cost or benefit than by the number of ACCase-inhibiting herbicides to which they conferred resistance.

CONCLUSION

Simulations allowed us to rank weed management practices and suggest that pleiotropic effects are extremely important for understanding the frequency of herbicide resistance in the population. © 2016 Society of Chemical Industry.

Trophic Relationships between the Parasitic Plant Species Phelipanche ramosa (L.) and Different Hosts Depending on Host Phenological Stage and Host Growth Rate

Phelipanche ramosa (L.) Pomel (branched broomrape) is a holoparasitic plant that reproduces on crops and also on weeds, which contributes to increase the parasite seed bank in fields. This parasite extracts all its nutrients at the host's expense so that host-parasite trophic relationships are crucial to determine host and parasite growth. This study quantified the intensity with which P. ramosa draws assimilates from its host and analyzed whether it varied with host species, host phenological stage and host growth rate. A greenhouse experiment was conducted on three host species: the crop species Brassica napus (L.) (oilseed rape) and two weed species, Capsella bursa-pastoris (L.) Medik. and Geranium dissectum (L.). Plants were grown with or without P. ramosa and under three light levels to modulate host growth rate. The proportion of host biomass loss due to parasitism by P. ramosa differed between host species (at host fructification, biomass loss ranged from 34 to 84%). B. napus and C. bursa-pastoris displayed a similar response to P. ramosa, probably because they belong to the same botanical family. The sensitivity to P. ramosa in each host species could be related to the precocity of P. ramosa development on them. Host compartments could be ranked as a function of their sensitivity to parasitism, with the reproductive compartment being the most severely affected, followed by stems and roots. The proportion of biomass allocated to leaves was not reduced by parasitism. The proportion of pathosystem biomass allocated to the parasite depended on host species. It generally increased with host stage progression but was constant across light induced-host growth rate, showing that P. ramosa adapts its growth to host biomass production. The rank order of host species in terms of sink strength differed from that in terms of host sensitivity. Finally, for B. napus, the biomass of individual parasite shoots decreased with increasing their number per host plant, regardless of host growth rate. Results will be incorporated into a mechanistic model in order to analyze the effect of parasitic plant species on weed community assembly and to design new cropping systems for controlling P. ramosa.

Ecological Intensification Through Pesticide Reduction: Weed Control, Weed Biodiversity and Sustainability in Arable Farming

Amongst the biodiversity components of agriculture, weeds are an interesting model for exploring management options relying on the principle of ecological intensification in arable farming. Weeds can cause severe crop yield losses, contribute to farmland functional biodiversity and are strongly associated with the generic issue of pesticide use. In this paper, we address the impacts of herbicide reduction following a causal framework starting with herbicide reduction and triggering changes in (i) the management options required to control weeds, (ii) the weed communities and functions they provide and (iii) the overall performance and sustainability of the implemented land management options. The three components of this framework were analysed in a multidisciplinary project that was conducted on 55 experimental and farmer's fields that included conventional, integrated and organic cropping systems. Our results indicate that the reduction of herbicide use is not antagonistic with crop production, provided that alternative practices are put into place. Herbicide reduction and associated land management modified the composition of in-field weed communities and thus the functions of weeds related to biodiversity and production. Through a long-term simulation of weed communities based on alternative (?) cropping systems, some specific management pathways were identified that delivered high biodiversity gains and limited the negative impacts of weeds on crop production. Finally, the multi-criteria assessment of the environmental, economic and societal sustainability of the 55 systems suggests that integrated weed management systems fared better than their conventional and organic counterparts. These outcomes suggest that sustainable management could possibly be achieved through changes in weed management, along a pathway starting with herbicide reduction.

Combining a weed traits database with a population dynamics model predicts shifts in weed communities

A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated 'fitness contours' (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

Injury profile SIMulator, a Qualitative aggregative modelling framework to predict injury profile as a function of cropping practices, and abiotic and biotic environment. II. Proof of concept: design of IPSIM-wheat-eyespot

IPSIM (Injury Profile SIMulator) is a generic modelling framework presented in a companion paper. It aims at predicting a crop injury profile as a function of cropping practices and abiotic and biotic environment. IPSIM's modelling approach consists of designing a model with an aggregative hierarchical tree of attributes. In order to provide a proof of concept, a model, named IPSIM-Wheat-Eyespot, has been developed with the software DEXi according to the conceptual framework of IPSIM to represent final incidence of eyespot on wheat. This paper briefly presents the pathosystem, the method used to develop IPSIM-Wheat-Eyespot using IPSIM's modelling framework, simulation examples, an evaluation of the predictive quality of the model with a large dataset (526 observed site-years) and a discussion on the benefits and limitations of the approach. IPSIM-Wheat-Eyespot proved to successfully represent the annual variability of the disease, as well as the effects of cropping practices (Efficiency = 0.51, Root Mean Square Error of Prediction = 24%; bias = 5.0%). IPSIM-Wheat-Eyespot does not aim to precisely predict the incidence of eyespot on wheat. It rather aims to rank cropping systems with regard to the risk of eyespot on wheat in a given production situation through ex ante evaluations. IPSIM-Wheat-Eyespot can also help perform diagnoses of commercial fields. Its structure is simple and permits to combine available knowledge in the scientific literature (data, models) and expertise. IPSIM-Wheat-Eyespot is now available to help design cropping systems with a low risk of eyespot on wheat in a wide range of production situations, and can help perform diagnoses of commercial fields. In addition, it provides a proof of concept with regard to the modelling approach of IPSIM. IPSIM-Wheat-Eyespot will be a sub-model of IPSIM-Wheat, a model that will predict injury profile on wheat as a function of cropping practices and the production situation.

How to model and simulate the effects of cropping systems on population dynamics and gene flow at the landscape level: example of oilseed rape volunteers and their role for co-existence of GM and non-GM crops

BACKGROUND, AIM AND SCOPE

Agricultural landscapes comprise cultivated fields and semi-natural areas. Biological components of these compartments such as weeds, insect pests and pathogenic fungi can disperse sometimes over very large distances, colonise new habitats via insect flight, spores, pollen or seeds and are responsible for losses in crop yield (e.g. weeds, pathogens) and biodiversity (e.g. invasive weeds). The spatiotemporal dynamics of these biological components interact with crop locations, successions and management as well as the location and management of semi-natural areas such as roadverges. The objective of this investigation was to establish a modelling and simulation methodology for describing, analysing and predicting spatiotemporal dynamics and genetics of biological components of agricultural landscapes. The ultimate aim of the models was to evaluate and propose innovative cropping systems adapted to particular agricultural concerns. The method was applied to oilseed rape (OSR) volunteers playing a key role for the coexistence of genetically modified (GM) and non-GM oilseed rape crops, where the adventitious presence of GM seeds in non-GM harvests (AGMP) could result in financial losses for farmers and cooperatives.

MATERIAL AND METHODS

A multi-year, spatially explicit model was built, using field patterns, climate, cropping systems and OSR varieties as input variables, focusing on processes and cultivation techniques crucial for plant densities and pollen flow. The sensitivity of the model to input variables was analysed to identify the major cropping factors. These should be modified first when searching for solutions limiting gene flow. The sensitivity to model processes and species life-traits were analysed to facilitate the future adaptation of the model to other species. The model was evaluated by comparing its simulations to independent field observations to determine its domain of validity and prediction error.

RESULTS

The cropping system study determined contrasted farm types, simulated the current situation and tested a large range of modifications compatible with each farm to identify solutions for reducing the AGMP. The landscape study simulated gene flow in a large number of actual and virtual field patterns, four combinations of regional OSR and GM proportions and three contrasted cropping systems. The analysis of the AGMP rate at the landscape level determined a maximum acceptable GM OSR area for the different cropping systems, depending on the regional OSR volunteer infestation. The analysis at the field level determined minimum distances between GM and non-GM crops, again for different cropping systems and volunteer infestations.

DISCUSSION

The main challenge in building spatially explicit models of the effects of cropping systems and landscape patterns on species dynamics and gene flow is to determine the spatial extent, the time scale, the major processes and the degree of mechanistic description to include in the model, depending on the species characteristics and the model objective.

CONCLUSIONS

These models can be used to study the effects of cropping systems and landscape patterns over a large range of situations. The interactions between the two aspects make it impossible to extrapolate conclusions from individual studies to other cases. The advantage of the present method was to produce conclusions for several contrasted farm types and to establish recommendations valid for a large range of situations by testing numerous landscapes with contrasted cropping systems. Depending on the level of investigation (region or field), these recommendations concern different decision-makers, either farmers and technical advisors or cooperatives and public decision-makers.

RECOMMENDATIONS AND PERSPECTIVES

The present simulation study showed that gene flow between coexisting GM and non-GM varieties is inevitable. The management of OSR volunteers is crucial for containing gene flow, and the cropping system study identified solutions for reducing these volunteers and ferals in and outside fields. Only if these are controlled can additional measures such as isolation distances between GM and non-GM crops or limiting the proportion of the region grown with GM OSR be efficient. In addition, particular OSR varieties contribute to limit gene flow. The technical, organisational and financial feasibility of the proposed measures remains to be evaluated by a multi-disciplinary team.

Influence of crop management on take-all development and disease cycles on winter wheat

ABSTRACT Wheat was assessed at four crop growth stages for take-all (Gaeumannomyces graminis var. tritici) in a series of field trials that studied the effects of five wheat management practices: sowing date, plant density, nitrogen fertilizer dose and form, and removal/burial of cereal straw. An equation expressing disease level as a function of degree days was fitted to the observed disease levels. This equation was based on take-all epidemiology and depended on two parameters reflecting the importance of the primary and secondary infection cycles, respectively. Early sowing always increased disease frequency via primary infection cycle; its influence on the secondary cycle was variable. Primary infection and earliness of disease onset were increased by high density; however, at mid-season take-all was positively correlated to the root number per plant, which was itself negatively correlated to plant density. At late stages of development, neither plant density nor root number per plant had any influence on disease. A high nitrogen dose increased both take-all on seminal roots and severity of primary infection cycle but decreased take-all on nodal roots and secondary infection cycle. Ammonium (versus ammonium nitrate) fertilizer always decreased disease levels and infection cycles, whereas straw treatment (burial versus removal of straw from the previous cereal crop) had no influence.