French low-input winegrowing demonstration farms: A dataset of their operations traceability and sustainability performances.

This article presents data on farming operations traceability and associated performances, for winegrowing systems with low phytosanitary inputs. 343 farms were sampled from the DEPHY network: a governmental initiative to produce references on phytosanitary-efficient cropping systems under real conditions of production. Data were collected every campaign between 2017 and 2020, by multiple extensionists who provide support to the voluntarily enlisted growers, in exchange for traceability of their practices and their commitment to reducing pesticide use. The dataset includes raw data of farming operations (date, machinery, inputs, products and doses, etc.), and performance indicators computed at farm level (Treatment Frequency Index, workload, expenses, greenhouse gas emissions, etc.). This information could be useful to researchers, policymakers and agricultural consultants. It provides leads to understand how winegrowers manage to successfully reduce their pesticide consumption, as well as assessing the triggers and entailments of such transitions.

How the Green Architecture of the 2023-2027 Common Agricultural Policy could have been greener.

A new 5-year Common Agricultural Policy has been in place since January 2023. Like its predecessors, this new policy will fail to deliver significant climatic and environmental benefits. We show how the Green Architecture of the policy relying on the three instruments of conditionality, eco-schemes, and agri-environment and climate measures could have been used more consistently and effectively. Our proposals are based on core principles of public economics and fiscal federalism as well as on research results in agronomy and ecology. Conditionality criteria are the minimal requirements that every agricultural producer must meet. Farmers should be rewarded for efforts that go beyond these basic requirements through eco-schemes for global public goods complemented by agri-environment and climate measures centred on local public goods. Eco-schemes should cover the whole agricultural area by targeting permanent grasslands, crop diversification, and green cover and non-productive agro-ecological infrastructures. We discuss trade-offs that our proposals could generate.

A research agenda for scaling up agroecology in European countries.

A profound transformation of agricultural production methods has become unavoidable due to the increase in the world's population, and environmental and climatic challenges. Agroecology is now recognized as a challenging model for agricultural systems, promoting their diversification and adaptation to environmental and socio-economic contexts, with consequences for the entire agri-food system and the development of rural and urban areas. Through a prospective exercise performed at a large interdisciplinary institute, INRAE, a research agenda for agroecology was built that filled a gap through its ambition and interdisciplinarity. It concerned six topics. For genetics, there is a need to study genetic aspects of complex systems (e.g., mixtures of genotypes) and to develop breeding methods for them. For landscapes, challenges lie in effects of heterogeneity at multiple scales, in multifunctionality and in the design of agroecological landscapes. Agricultural equipment and digital technologies show high potential for monitoring dynamics of agroecosystems. For modeling, challenges include approaches to complexity, consideration of spatial and temporal dimensions and representation of the cascade from cropping practices to ecosystem services. The agroecological transition of farms calls for modeling and observational approaches as well as for creating new design methods. Integration of agroecology into food systems raises the issues of product specificity, consumer behavior and organization of markets, standards and public policies. In addition, transversal priorities were identified: (i) generating sets of biological data, through research and participatory mechanisms, that are appropriate for designing agroecological systems and (ii) collecting and using coherent sets of data to enable assessment of vulnerability, resilience and risk in order to evaluate the performance of agroecological systems and to contribute to scaling up. The main lessons learned from this collective exercise can be useful for the entire scientific community engaged in research into agroecology.

Improving pest monitoring networks using a simulation-based approach to contribute to pesticide reduction.

Conventional pest management mainly relies on the use of pesticides. However, the negative externalities of pesticides are now well known. More sustainable practices, such as Integrated Pest Management, are necessary to limit crop damage from pathogens, pests and weeds in agroecosystems. Reducing pesticide use requires information to determine whether chemical treatments are really needed. Pest monitoring networks (PMNs) are key contributors to this information. However, the effectiveness of a PMN in delivering relevant information about pests depends on its spatial sampling resolution and its memory length. The trade-off between the monitoring efforts and the usefulness of the information provided is highly dependent on pest ecological traits, the damage they can cause (in terms of crop losses), and economic drivers (production costs, agriculture product prices and incentives). Due to the high complexity of optimising PMNs, we have developed a theoretical model that belongs to the family of Dynamic Bayesian Networks in order to compare several PMNs performances. This model links the characteristics of a PMN to treatment decisions and the resulting pest dynamics. Using simulation and inference tools for graphical models, we derived the proportion of impacted fields, the number of pesticide treatments and the overall gross margins for three types of pest with contrasting levels of endocyclism. The term "endocyclic" refers to an organism whose development is mostly restricted to a field and highly depends on the inoculum present in the considered field. The presence of purely endocyclic pests at a given time increases the probability of reoccurrence. Conversely, slightly endocyclic pests have a low persistence. The simulation analysis considered ten scenarios: an expected margin-based strategy with a spatial resolution of four PMNs and two memory lengths (one year or eight years), as well as two extreme crop protection strategies (systematic treatments on all fields and systematic no treatment). For purely and mainly endocyclic pests (e.g. soil-borne pathogens and most weeds, respectively), we found that increasing the spatial resolution of PMNs made it possible to significantly decrease the number of treatments required for pest control. Taking past observations into account was also effective, but to a lesser extent. PMN information had virtually no influence on the control of non-endocyclic pests (such as flying insects or airborne plant pathogens) which may be due to the spatial coverage addressed in our study. The next step is to extend the analysis of PMNs and to integrate the information generated by PMNs into sustainable pest management strategies, both at the field and the landscape level.

Which Traits Make Weeds More Successful in Maize Crops? Insights from a Three-Decade Monitoring in France.

A major aim in invasion biology is identifying traits distinguishing alien invasive and alien non-invasive plants. Surprisingly, this approach has been, so far, poorly used to understand why some arable weeds are abundant and widespread while others are rare and narrowly distributed. In the present study, we focused on the characteristics of successful weeds occurring in maize fields, one of the most important crops worldwide. Two national weed surveys conducted in France were used to identify increasing and decreasing species based on 175 and 484 surveyed fields in the 1970s and the 2000s, respectively. Weed trait values related to regional frequency, local abundance, and specialization to maize were identified with phylogenetic generalized least-squares (PGLS). We found a positive relationship between regional frequency and local abundance, i.e., the most widespread weeds were also locally more abundant. We highlighted that weeds with the C4 photosynthetic pathway and summer emergence were more abundant, more frequent, and more specialized to maize crops. More generally, we highlighted two successful strategies: On the one hand, traits related to a general weediness syndrome with rapid resource acquisition (high SLA and Ellenberg-N) and high colonization capacity (seed longevity, fecundity, and wind dispersal); on the other hand, traits related to specific adaptation to spring cultivation (thermophilous species with summer emergence, late flowering, and C4 photosynthetic pathway). Deviations from the abundancy-frequency relationships also indicated that species of the Panicoideae sub-family, species with Triazine-resistant populations, and neophyte species were more abundant than expected by their regional frequency. To some extent, it is therefore possible to predict which species can be troublesome in maize crops and use this information in weed risk assessment tools to prevent new introductions or favor early detection and eradication. This study showed how tools developed in functional and macro-ecology can be used to improve our understanding of weed ecology and to develop more preventive management strategies.

Investigation of Amino Acids As Herbicides for Control of Orobanche minor Parasitism in Red Clover.

Certain amino acids induce inhibitory effects in plant growth due to feedback inhibition of metabolic pathways. The inhibition patterns depend on plant species and the plant developmental stage. Those amino acids with inhibitory action on specific weeds could be utilized as herbicides, however, their use for weed control has not been put into practice. Orobanche minor is a weed that parasitizes red clover. O. minor germination is stimulated by clover root exudates. The subsequent seedling is an obligated parasite that must attach quickly to the clover root to withdraw its nutrients. Early development of O. minor is vulnerable to amino acid inhibition and therefore, a series of in vitro, rhizotron, and field experiments were conducted to investigate the potential of amino acids to inhibit O. minor parasitism. In in vitro experiments it was found that among a collection of 20 protein amino acids, lysine, methionine and tryptophan strongly interfere with O. minor early development. Field research confirmed their inhibitory effect but revealed that methionine was more effective than lysine and tryptophan, and that two successive methionine applications at 308 and 543 growing degree days inhibited O. minor emergence in red clover up to 67%. We investigated additional effects with potential to influence the practical use of amino acids against broomrape weeds, whether the herbicidal effect may be reversible by other amino acids exuded by host plants or may be amplified by inducing host resistance barriers against O. minor penetration. This paper suggests that amino acids may have the potential to be integrated into biorational programs of broomrape management.

Broomrape Weeds. Underground Mechanisms of Parasitism and Associated Strategies for their Control: A Review.

Broomrapes are plant-parasitic weeds which constitute one of the most difficult-to-control of all biotic constraints that affect crops in Mediterranean, central and eastern Europe, and Asia. Due to their physical and metabolic overlap with the crop, their underground parasitism, their achlorophyllous nature, and hardly destructible seed bank, broomrape weeds are usually not controlled by management strategies designed for non-parasitic weeds. Instead, broomrapes are in current state of intensification and spread due to lack of broomrape-specific control programs, unconscious introduction to new areas and may be decline of herbicide use and global warming to a lesser degree. We reviewed relevant facts about the biology and physiology of broomrape weeds and the major feasible control strategies. The points of vulnerability of some underground events, key for their parasitism such as crop-induced germination or haustorial development are reviewed as inhibition targets of the broomrape-crop association. Among the reviewed strategies are those aimed (1) to reduce broomrape seed bank viability, such as fumigation, herbigation, solarization and use of broomrape-specific pathogens; (2) diversion strategies to reduce the broomrape ability to timely detect the host such as those based on promotion of suicidal germination, on introduction of allelochemical interference, or on down-regulating host exudation of germination-inducing factors; (3) strategies to inhibit the capacity of the broomrape seedling to penetrate the crop and connect with the vascular system, such as biotic or abiotic inhibition of broomrape radicle growth and crop resistance to broomrape penetration either natural, genetically engineered or elicited by biotic- or abiotic-resistance-inducing agents; and (4) strategies acting once broomrape seedling has bridged its vascular system with that of the host, aimed to impede or to endure the parasitic sink such as those based on the delivery of herbicides via haustoria, use of resistant or tolerant varieties and implementation of cultural practices improving crop competitiveness.

Dynamics of Weeds in the Soil Seed Bank: A Hidden Markov Model to Estimate Life History Traits from Standing Plant Time Series.

Predicting the population dynamics of annual plants is a challenge due to their hidden seed banks in the field. However, such predictions are highly valuable for determining management strategies, specifically in agricultural landscapes. In agroecosystems, most weed seeds survive during unfavourable seasons and persist for several years in the seed bank. This causes difficulties in making accurate predictions of weed population dynamics and life history traits (LHT). Consequently, it is very difficult to identify management strategies that limit both weed populations and species diversity. In this article, we present a method of assessing weed population dynamics from both standing plant time series data and an unknown seed bank. We use a Hidden Markov Model (HMM) to obtain estimates of over 3,080 botanical records for three major LHT: seed survival in the soil, plant establishment (including post-emergence mortality), and seed production of 18 common weed species. Maximum likelihood and Bayesian approaches were complementarily used to estimate LHT values. The results showed that the LHT provided by the HMM enabled fairly accurate estimates of weed populations in different crops. There was a positive correlation between estimated germination rates and an index of the specialisation to the crop type (IndVal). The relationships between estimated LHTs and that between the estimated LHTs and the ecological characteristics of weeds provided insights into weed strategies. For example, a common strategy to cope with agricultural practices in several weeds was to produce less seeds and increase germination rates. This knowledge, especially of LHT for each type of crop, should provide valuable information for developing sustainable weed management strategies.

A specialist-generalist classification of the arable flora and its response to changes in agricultural practices.

BACKGROUND: Theory in ecology points out the potential link between the degree of specialisation of organisms and their responses to disturbances and suggests that this could be a key element for understanding the assembly of communities. We evaluated this question for the arable weed flora as this group has scarcely been the focus of ecological studies so far and because weeds are restricted to habitats characterised by very high degrees of disturbance. As such, weeds offer a case study to ask how specialization relates to abundance and distribution of species in relation to the varying disturbance regimes occurring in arable crops. RESULTS: We used data derived from an extensive national monitoring network of approximately 700 arable fields scattered across France to quantify the degree of specialisation of 152 weed species using six different ecological methods. We then explored the impact of the level of disturbance occurring in arable fields by comparing the degree of specialisation of weed communities in contrasting field situations.The classification of species as specialist or generalist was consistent between different ecological indices. When applied on a large-scale data set across France, this classification highlighted that monoculture harbour significantly more specialists than crop rotations, suggesting that crop rotation increases abundance of generalist species rather than sets of species that are each specialised to the individual crop types grown in the rotation. Applied to a diachronic dataset, the classification also shows that the proportion of specialist weed species has significantly decreased in cultivated fields over the last 30 years which suggests a biotic homogenization of agricultural landscapes. CONCLUSIONS: This study shows that the concept of generalist/specialist species is particularly relevant to understand the effect of anthropogenic disturbances on the evolution of plant community composition and that ecological theories developed in stable environments are valid in highly disturbed environments such as agro-ecosystems. The approach developed here to classify arable weeds according to the breadth of their ecological niche is robust and applicable to a wide range of organisms. It is also sensitive to disturbance regime and we show here that recent changes in agricultural practices, i.e. increased levels of disturbance have favoured the most generalist species, hence leading to biotic homogenisation in arable landscapes.

Modelling binary mixtures of herbicides in populations resistant to one of the components: evaluation for resistance management.

BACKGROUND: Herbicide mixtures are commonly proposed to delay the selection of herbicide resistance in susceptible populations (called the SM strategy). However, in practice, herbicide mixtures are often used when resistance to one of the two active ingredients has already been detected in the targeted population (called the RM strategy). It is doubtful whether such a practice can select against resistance, as the corresponding selection pressure is still exerted. As a consequence, the effect of mixtures on the evolution of an already detected resistance to one of the herbicides in the combination remains largely unexplored. In the present work, a simple model was developed to explore further the necessary and sufficient conditions under which a binary RM strategy might stabilise or even reduce resistance frequency. RESULTS: Covering the hypothetical largest range of parameters, 39% of 9000 random simulations attest that the RM strategy might theoretically reduce resistance frequency. When strong enough, high genetic cost of resistance, negative cross-resistance between the herbicides associated in the mixture and reduced selection differential between resistant and susceptible plants can counterbalance the resistance advantage to one of the two applied herbicides. However, the required conditions for an RM strategy to ensure resistance containment in natural conditions seldom overlap with experimental parameter estimates given in the literature. CONCLUSION: It is concluded that the sufficient conditions for an RM strategy to be effective would rarely be encountered. As a consequence, the strategy of formulating mixtures with herbicides for which resistance has already been detected should be avoided.

Delaying weed adaptation to herbicide by environmental heterogeneity: a simulation approach.

BACKGROUND: Environmental heterogeneity in space or time can drive the evolutionary trajectory of an adaptive trait. This concept could be of practical significance in pesticide resistance management that aims to delay the evolution of a resistance allele. Using a population genetics model, the dynamics of herbicide resistance in a weed species was simulated in a heterogeneous environment with alternation of two unrelated herbicides in time, in space or in both time and space. The level of the environmental heterogeneity (habitat grain) was simulated by a variation in the size of the herbicide-treated areas. RESULTS: The model confirms that several strategies based on habitat heterogeneity efficiently slow down and even prevent resistance evolution. For a recessive resistant trait in outcrossing species, a medium level of environmental heterogeneity (intermediate habitat grain) was found to be the best for delaying herbicide resistance, as previously observed for insecticide resistance management. In selfing species or for a dominant resistant trait in outcrossing species, a low level of environmental heterogeneity (coarse-grained habitat) was more efficient in delaying resistance evolution when heterogeneity in both space and time were considered. CONCLUSION: This model suggests that the choice of optimal tactics for delaying herbicide resistance by enhanced heterogeneity in space or time firstly depends on the interactions between the breeding system and the dominance of the resistance allele in the presence of herbicide, then on the value of the fitness cost and lastly on the dominance of this fitness cost.

Induction of atrazine tolerance in a natural soil assemblage of microalgae reared in the laboratory.

We investigated the occurrence of tolerance to atrazine (2-chloro-4-ethylamino-6-isopropylamino-s-triazine) in soil microalgae by means of the pollution-induced community tolerance methodology. To this end, a natural soil assemblage of microalgae, reared under laboratory conditions, was used as experimental model. Experimental cultures were exposed to 0.46, 0.93, 1.85, 2.70, and 5.40 mg atrazine/L medium for 40 days. After this chronic exposure, both untreated and atrazine-pretreated cultures were subjected to a short-term dose-effect study with atrazine using average growth rate as endpoint. Results showed that chronic exposure to atrazine induced significant changes at the community level, increasing its atrazine tolerance. In addition, atrazine-pretreated assemblages seemed to display, on average, a reduced growth rate compared with untreated assemblages in the absence of atrazine. Response to the presence of atrazine could thus be achieved with some fitness cost. This suggests that the soil microalgal productivity could be diminished after exposure to atrazine.

Building of an experimental cline with Arabidopsis thaliana to estimate herbicide fitness cost.

Various management strategies aim at maintaining pesticide resistance frequency under a threshold value by taking advantage of the benefit of the fitness penalty (the cost) expressed by the resistance allele outside the treated area or during the pesticide selection "off years." One method to estimate a fitness cost is to analyze the resistance allele frequency along transects across treated and untreated areas. On the basis of the shape of the cline, this method gives the relative contributions of both gene flow and the fitness difference between genotypes in the treated and untreated areas. Taking advantage of the properties of such migration-selection balance, an artificial cline was built up to optimize the conditions where the fitness cost of two herbicide-resistant mutants (acetolactate synthase and auxin-induced target genes) in the model species Arabidopsis thaliana could be more accurately measured. The analysis of the microevolutionary dynamics in these experimental populations indicated mean fitness costs of approximately 15 and 92% for the csr1-1 and axr2-1 resistances, respectively. In addition, negative frequency dependence for the fitness cost was also detected for the axr2-1 resistance. The advantages and disadvantages of the cline approach are discussed in regard to other methods of cost estimation. This comparison highlights the powerful ability of an experimental cline to measure low fitness costs and detect sensibility to frequency-dependent variations.

Evidence for a large-scale population structure among accessions of Arabidopsis thaliana: possible causes and consequences for the distribution of linkage disequilibrium.

The existence of a large-scale population structure was investigated in Arabidopsis thaliana by studying patterns of polymorphism in a set of 71 European accessions. We used sequence polymorphism surveyed in 10 fragments of approximately 600 nucleotides and a set of nine microsatellite markers. Population structure was investigated using a model-based inference framework. Among the accessions studied, the presence of four groups was inferred using genetic data, without using prior information on the geographical origin of the accessions. Significant genetic isolation by geographical distance was detected at the group level, together with a geographical gradient in allelic richness across groups. These results are discussed with respect to the previously proposed scenario of postglacial colonization of Europe from putative glacial refugia. Finally, the contribution of the inferred structure to linkage disequilibrium among 171 pairs of essentially unlinked markers was also investigated. Linkage disequilibrium analysis revealed that significant associations detected in the whole sample were mainly due to genetic differentiation among the inferred groups. We discuss the implication of this finding for future association studies in A. thaliana.

Utilization of the three high-throughput SNP genotyping methods, the GOOD assay, Amplifluor and TaqMan, in diploid and polyploid plants.

The application of high-throughput SNP genotyping is a great challenge for many research projects in the plant genetics domain. The GOOD assay for mass spectrometry, Amplifluor and TaqMan are three methods that rely on different principles for allele discrimination and detection, specifically, primer extension, allele-specific PCR and hybridization, respectively. First, with the goal of assessing allele frequencies by means of SNP genotyping, we compared these methods on a set of three SNPs present in the herbicide resistance genes CSR, AXR1 and IXR1 of Arabidopsis thaliana. In this comparison, we obtained the best results with TaqMan based on PCR specificity, flexibility in primer design and success rate. We also used mass spectrometry for genotyping polyploid species. Finally, a combination of the three methods was used for medium- to high-throughput genotyping in a number of different plant species. Here, we show that all three genotyping technologies are successful in discriminating alleles in various plant species and discuss the factors that must be considered in assessing which method to use for a given application.

Is the cost of herbicide resistance expressed in the breakdown of the relationships between characters? A case study using synthetic-auxin-resistant Arabidopsis thaliana mutants.

A mutation endowing herbicide resistance is often found to induce a parallel morphological or fitness penalty. To test whether such 'cost' of resistance to herbicides is expressed through lower resource acquisition, changes in resource allocation, or both, is of ecological significance. Here, we analysed 12 morphological traits in 900 plants covering three herbicide resistance mutations at genes AUX1 , AXR1 and AXR2 in the model species Arabidopsis thaliana . Comparing these 2,4-D herbicide-resistant homozygous (RR) and heterozygous (RS) plants to homozygous susceptible (SS) plants, this analysis estimates the dominance level of the resistance allele on morphology. We also demonstrated that the herbicide resistance cost was primarily expressed as a change in resource acquisition (62.1-94% of the analysed traits). Although AUX1 , AXR1 and AXR2 genes act in the same metabolic pathway of auxin response, each resistance factor was found to have its own unique signature in the way the cost was expressed. Furthermore, no link was observed between the absolute fitness penalty and the respective modifications of resource acquisition and/or resource allocation in the resistant plants. These results and their implications for herbicide resistance spread and establishment are discussed.

Epistatic interactions among herbicide resistances in Arabidopsis thaliana: the fitness cost of multiresistance.

The type of interactions among deleterious mutations is considered to be crucial in numerous areas of evolutionary biology, including the evolution of sex and recombination, the evolution of ploidy, the evolution of selfing, and the conservation of small populations. Because the herbicide resistance genes could be viewed as slightly deleterious mutations in the absence of the pesticide selection pressure, the epistatic interactions among three herbicide resistance genes (acetolactate synthase CSR, cellulose synthase IXR1, and auxin-induced AXR1 target genes) were estimated in both the homozygous and the heterozygous states, giving 27 genotype combinations in the model plant Arabidopsis thaliana. By analyzing eight quantitative traits in a segregating population for the three herbicide resistances in the absence of herbicide, we found that most interactions in both the homozygous and the heterozygous states were best explained by multiplicative effects (each additional resistance gene causes a comparable reduction in fitness) rather than by synergistic effects (each additional resistance gene causes a disproportionate fitness reduction). Dominance coefficients of the herbicide resistance cost ranged from partial dominance to underdominance, with a mean dominance coefficient of 0.07. It was suggested that the csr1-1, ixr1-2, and axr1-3 resistance alleles are nearly fully recessive for the fitness cost. More interestingly, the dominance of a specific resistance gene in the absence of herbicide varied according to, first, the presence of the other resistance genes and, second, the quantitative trait analyzed. These results and their implications for multiresistance evolution are discussed in relation to the maintenance of polymorphism at resistance loci in a heterogeneous environment.

Dominance variation across six herbicides of the Arabidopsis thaliana csr1-1 and csr1-2 resistance alleles.

Dominance of a resistance trait can be defined as a measure of the relative position of the phenotype of the heterozygote RS compared with the phenotype of the two corresponding homozygotes, SS and RR. This parameter has been shown to have primary importance in the dynamics of pesticide resistance evolution. Literature on insecticide resistance suggests that dominance levels in the presence of insecticide vary greatly from completely recessive to completely dominant. With insecticides, both the chemical applied and the dosages used have been demonstrated to affect the dominance. By contrast, almost all herbicide resistances have been found to be inherited as partially to totally dominant traits. This discrepancy between weeds and insects may partly result from the methodologies applied to measure the dominance, ie a single dose for herbicide versus several doses for insecticide. Using two well-known resistances (csr1-1 and csr1-2) to acetolactate synthase (ALS) inhibitors in Arabidopsis thaliana (L) Heynh (mouse-ear cress), we used several herbicide doses to determine the dominance level to six ALS-inhibiting herbicides. The dominance level in the presence of herbicide varied from completely dominant to completely recessive, depending on the resistance allele and the herbicide tested. The dominance of the csr1-1 and csr1-2 resistance alleles ranged from 0 (completely recessive) to 1.1 (dominant) and from 0 to 0.3 (partially dominant), respectively. The recessivity of some resistance alleles in the presence of herbicide could lead to the development of improved resistance management in order to delay or avoid herbicide resistance evolution, especially in the control of outcrossing weed species.

Multigenerational versus single generation studies to estimate herbicide resistance fitness cost in Arabidopsis thaliana.

The evolution of resistance in response to pesticide selection is expected to be delayed if fitness costs are associated with resistance genes. The estimate of fitness costs usually involves comparing major growth traits of resistant versus susceptible individuals in the absence of pesticide. Ideally, a measure of changes in resistance allele frequency over several generations would allow the best estimate of the overall fitness cost of a resistance gene. In greenhouse conditions, we monitored the dynamics of the evolution of the frequencies of six herbicide-resistant mutations (acetolactate synthase, cellulose synthase, and auxin-induced target genes) in the model species Arabidopsis thaliana in a multigenerational study covering five to seven nonoverlapping generations. The microevolutionary dynamics in experimental populations indicated a mean fitness cost of 38%, 73%, and 94% for the ixr1-2, axr1-3, and axr2-1 resistances, respectively; no fitness cost for the csr1-1, and ixr2-1 resistances; and a transient advantage for the aux1-7 resistance. The result for the csr1-1 resistance contrasts with a cost of 37% based on total seed number in a previous study, demonstrating that single generation studies could have limitation for detecting cost. A positive frequency dependence for the fitness cost was also detected for the ixr1-2 resistance. The results are discussed in relation to the maintenance of polymorphism at resistance loci.

Nested core collections maximizing genetic diversity in Arabidopsis thaliana.

The successful exploitation of natural genetic diversity requires a basic knowledge of the extent of the variation present in a species. To study natural variation in Arabidopsis thaliana, we defined nested core collections maximizing the diversity present among a worldwide set of 265 accessions. The core collections were generated based on DNA sequence data from a limited number of fragments evenly distributed in the genome and were shown to successfully capture the molecular diversity in other loci as well as the morphological diversity. The core collections are available to the scientific community and thus provide an important resource for the study of genetic variation and its functional consequences in Arabidopsis. Moreover, this strategy can be used in other species to provide a rational framework for undertaking diversity surveys, including single nucleotide polymorphism (SNP) discovery and phenotyping, allowing the utilization of genetic variation for the study of complex traits.