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Understanding trophic interactions in agroecosystems is crucial for harnessing ecosystem services such as pest control, thus enabling a reduction in pesticide use. Carabid beetles (Coleoptera: Carabidae) have the potential to regulate not only insect pests but also weed seeds and slugs. The aim of this study was to investigate the food choice of different carabid species in the experimental setting of a cereal field with varying seed and slug prey availability during the season. In addition to varying food availability, the effects of species identity and season on carabid food choice should also be closely examined. Therefore, the gut contents of 1,120 beetles of eight carabid species were screened for the DNA of plants, aphids, springtails, earthworms and slugs via diagnostic multiplex PCR and a nested metabarcoding approach for plant species identification. Plant DNA was detected far more often (72%) than the various animal prey types (less than 12.5% each). Within the plant detections, 80 weed species were identified in the metabarcoding, with Galinsoga parviflora/quadriradiata (Galinsoga spp.—quickweeds) as the most frequently detected species. Carabid food choice was driven by their species identity and seasonality, while no effect of increased availability of seeds and slugs on their food choice was detected. While weed seeds seem to be an important food source for carabids, their availability does not directly affect the carabid diet. The importance of consumer identity and seasonality highlight the need for a diverse carabid species community for resilient pest control services.

International audience; Abstract Carabids are important biological control agents of weeds and other pests in agricultural fields. The carabid community is built upon direct and indirect ecological effects of landscape complexity, field management intensity and biotic components that in interaction make any prediction of community size and composition challenging. We analyse a large-scale sample of 60 European cereal fields using structural equation modelling to quantify the direct effects of field management intensity and the surrounding landscape, and their indirect effect via biotic components, on carabid diversity. Our results highlight that direct and indirect effects of increasing landscape complexity, mediated by trophic resources, mainly affect carabids positively. Field management intensity only ever affects carabids through indirect effects that are generally negative, by suppressing standing weeds and weed seeds. Indirect effects on granivore carabid species depended on weed seed availability, whereas omnivores depended on the availability of both weed seeds and animal prey. Synthesis and applications. A consideration of both the direct and indirect effects of landscape and field management is necessary for predicting carabid communities. These indirect effects, mediated via trophic resources, supports the diversity and abundance of carabid communities and their provision of ecosystem services. Our results show that promoting crop diversity and connectivity to semi-natural habitats will directly enhance carabid communities in farmland by manipulating their migration from source habitats and indirectly by promoting the presence and diversity of their trophic resources. A reduction in field management intensity will preserve local standing weeds and weed seeds, and indirectly support carabid communities. These local and landscape modifications could contribute to improve the natural regulation of pests and weeds by carabids.

The fungal pathogen Zymoseptoria tritici is the causal agent of Septoria tritici blotch (STB), a major wheat disease in Western Europe. Microorganisms inhabiting wheat leaves might act as beneficial, biocontrol, or facilitating agents that could limit or stimulate the development of Z. tritici. Improving our understanding of microbial communities in the wheat phyllosphere would lead to new insights into STB management. This article provides fungal and bacterial metabarcoding datasets obtained by sampling wheat leaves with and without symptoms caused by Z. tritici. Tissues were sampled from three commercial wheat varieties on three sampling dates during a cropping season. Weeds around wheat fields were sampled as well. In total, more than 450 leaf samples were collected. The pathogen Z. tritici was quantified using quantitative PCR. We provide the raw metabarcoding datasets, the amplicon sequence variant tables obtained after bioinformatic processing, the metadata associated with each sample (sampling date, wheat variety and tissue health condition), a preliminary descriptive analysis of the data, and the code used for bioinformatic and descriptive statistical analysis. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

International audience; Given the negative environmental effects of conventional agricultural techniques, the need for biodiversity-friendly agriculture systems that rely more on ecosystem services and less on chemical inputs is becoming increasingly urgent. In this paper, we focus on crop protection strategies that are alternatives to the use of pesticides. Diversification of the plant component of agricultural areas at different space and time scales has been presented as a powerful socio-economic and agro-ecological mechanism for the sustainable control of pests. Our interdisciplinary group of scientific experts examined the literature on the ecological effects of plant diversification on pests and their natural enemies, as well as the social science literature on the conditions for farmers to adopt the corresponding practices, to assess the potential offered by plant diversification.We developed a conceptual framework that connects the agro-ecological and socio-economic components of an agricultural landscape in a dynamic loop accounting for interactions among elements at different spatial and temporal scales and their feedback effects. This article presents this framework and illustrates its application to the case of wheat production and protection. By explicitly connecting each level of agro-ecological organization with the potential socio-economic drivers and limitations underpinning the adoption and implementation of plant diversification in landscapes, this framework makes it possible to ana yse the synergies and antagonisms between different modes of diversification and the conditions of their deployment. Exploring this framework is a prerequisite to the identification of opportunities and key feed-back loops for designing diversification strategies that unlock the agro-ecological potential of f uture production systems. We conclude that there is a need for interdisciplinary research in experimental landscapes involving farmers and other local stakeholders to design sustainable future agricultural landscapes that deliver high levels of biological control services..

The fungal pathogen Zymoseptoria tritici is the causal agent of Septoria tritici blotch (STB), a major wheat disease in Western Europe. Microorganisms inhabiting wheat leaves might act as beneficial, biocontrol or facilitating agents that could limit or stimulate the development of Z. tritici. Improving our understanding of microbial communities in the wheat phyllosphere would lead to new insights into STB management. This resource announcement provides fungal and bacterial metabarcoding datasets obtained by sampling wheat leaves differing in the presence of symptoms caused by Z. tritici. Tissues were sampled from three wheat commercial varieties on three sampling dates during a cropping season. Weeds around wheat fields were sampled as well. In total, more than 450 leaf samples were collected. The pathogen Z. tritici was quantified using qPCR. We provide the raw metabarcoding datasets, the Amplicon Sequence Variant (ASV) tables obtained after bioinformatic processing, the metadata associated to each sample (sampling date, wheat variety and tissue health condition), a preliminary descriptive analysis of the data, and the code used for bioinformatic and descriptive statistical analysis.

Despite substantial policy efforts made by the French government to reduce dependence on pesticides, farming practices are only changing slowly. This paper analyses the socio-economic trade-offs that 110 farmers are currently facing in the transition to agro-ecological practices. A mixed-method approach - a quantitative discrete choice experiment (DCE) and qualitative interviews - was set up to understand these farmers' motivations and perspectives, and how policy can improve to accompany them on the road to low chemical input farming. Results of the DCE indicate that the majority of the farmers in our sample are keen to change practices but are at a loss as to how this can be done, as a number of preferences for this transition came out as inconclusive. Qualitative interviews with a representative sample of the farmers that took part in the DCE complemented this result by illustrating a deep uncertainty for the future and a disconnect felt between authorities and themselves as a group. We argue that this uncertainty contributed to a lack of clear-cut solutions established through the DCE. The indepth discussions with farmers illustrated the wish for concrete and local policy measures based on farmers' networks and peer support.

Ecological networks are valuable for ecosystem analysis but their use is often limited by a lack of data because many types of ecological interaction, for example, predation, are short‐lived and difficult to observe or detect. While there are different methods for inferring the presence of interactions, they have rarely been used to predict the interaction strengths that are required to construct weighted, or quantitative, ecological networks.Here, we develop a trait‐based approach suitable for inferring weighted networks, that is, with varying interaction strengths. We developed the method for seed‐feeding carabid ground beetles (Coleoptera: Carabidae) although the principles can be applied to other species and types of interaction.Using existing literature data from experimental seed‐feeding trials, we predicted a per‐individual interaction cost index based on carabid and seed size. This was scaled up to the population level to create inferred weighted networks using the abundance of carabids and seeds from empirical samples and energetic intake rates of carabids from the literature. From these weighted networks, we also derived a novel measure of expected predation pressure per seed type per network.This method was applied to existing ecological survey data from 255 arable fields with carabid data from pitfall traps and plant seeds from seed rain traps. Analysis of these inferred networks led to testable hypotheses about how network structure and predation pressure varied among fields.Inferred networks are valuable because (a) they provide null models for the structuring of food webs to test against empirical species interaction data, for example, DNA analysis of carabid gut regurgitates and (b) they allow weighted networks to be constructed whenever we can estimate interactions between species and have ecological census data available. This permits ecological network analysis even at times and in places when interactions were not directly assessed., Ecological networks are valuable for ecosystem analysis, but often limited by lack of data on interactions between species. Here, we develop a trait‐based approach to infer interaction strengths with mechanistic models and take existing ecological census data (samples of species: of carabid ground beetles and weed seeds) to construct inferred quantitative food webs.

12 pages; International audience; The prediction of pest regulation by multi-predator communities often remains challenging because of variable and opposite effects of niche complementarity and predator interference. Carabid communities are regulating weeds in arable fields and include a mix of species ranging from granivores to predators that are obligate omnivores. It is not clear from field studies whether granivore and obligate omnivore species either contribute equally or are complementary in the process of weed suppression, and little is known about the impact of potential predator interference within carabid communities on weed suppression. We compared the weed seed foraging strategy of the granivore Harpalus affinis and the obligate omnivore Poecilus cupreus. Using no-choice test experiments, we compared their activity and seed acceptance for four weed species through a scoring of the proportion of tested individuals consuming weeds, their latency before the consumption of the first seed and the total number of seeds consumed. We then evaluated their seed acceptance for dandelion seed Taraxacum officinale under predator interference by using chemical cues of carabids and tested the impact of three treatments, namely cues of intraspecific competition, interspecific competition and intraguild predation. We found that the obligate omnivore P. cupreus was highly active, had a low latency before consuming its first seed but had an interest in only two of the four weed species. P. cupreus seed acceptance remained unchanged in the presence of predator cues. By contrast, H. affinis was slow to start its seed consumption, accepted equally seeds of the four weed species and significantly increased its seed consumption in the presence of cues mimicking intraguild predation. These findings indicate that the two species differ in their foraging strategies, and as such, could have different contributions to weed seed suppression. This novel result calls for further studies documenting the foraging strategy of carabid species that thrive in arable fields as this could significantly improve our understanding of the delivery of weed seed regulation.

International audience; Humanity is facing existential, societal challenges related to food security, ecosystem conservation, antimicrobial resistance, etc, and Artificial Intelligence (AI) is already playing an important role in tackling these new challenges. Most current AI approaches are limited when it comes to ‘knowledge transfer’ with humans, i.e. it is difficult to incorporate existing human knowledge and also the output knowledge is not human comprehensible. In this chapter we demonstrate how a combination of comprehensible machine learning, text-mining and domain knowledge could enhance human-machine collaboration for the purpose of automated scientific discovery where humans and computers jointly develop and evaluate scientific theories. As a case study, we describe a combination of logic-based machine learning (which included human-encoded ecological background knowledge) and text-mining from scientific publications (to verify machine-learned hypotheses) for the purpose of automated discovery of ecological interaction networks (food-webs) to detect change in agricultural ecosystems using the Farm Scale Evaluations (FSEs) of genetically modified herbicide-tolerant (GMHT) crops dataset. The results included novel food-web hypotheses, some confirmed by subsequent experimental studies (e.g. DNA analysis) and published in scientific journals. These machine-leaned food-webs were also used as the basis of a recent study revealing resilience of agro-ecosystems to changes in farming management using GMHT crops.

National audience; The weed soil seedbank is of interest in agroecosystems as a major source of weedinfestation in fields and as a reservoir of plant and seed-feeder diversity. A seedbankis a characteristic of annual plants and has been the focus of numerous studies, as itreflects the past aboveground vegetation and is the reservoir of the future vegetation.Therefore, it potentially can be used to evaluate the past, present and futureannual weed communities. The goal of this paper was to provide guidelines to helpresearchers to do a weed seedbank survey. Through a qualitative review of 60 weedseedbank articles, we investigate why and how the seedbank has been studied inagronomy. It shows that seedbank studies have been performed to address the followingfour major objectives: (a) the assessment of weed management practices onweed communities; (b) the relationship between seedbank and aboveground vegetation;(c) the study of composition and diversity of seedbank in a given area; and,(d) the quantification of seedbank as a food resource for wildlife. Because the analysishighlighted a wide range of methodologies to estimate the seedbank, we criticallyreviewed them. We show that the selected methodology strongly affects theseedbank estimate. Nevertheless, in our sample of research articles, the analysis revealedthat the choice of the methodology was not always justified in terms of achievinga particular scientific goal, but was often determined by the resources availablefor the experiment (e.g., workload). While studying the soil seedbank remains ofinterest for scientists (proved by the amount of recent publications), it is time consumingand requires considerable botanical skill. Innovative methods of estimationare scarce and novel methodological developments are needed to increase the qualityand reliability of the data obtained.

Agriculture is under pressure to achieve sustainable development goals for biodiversity and ecosystem services. Services in agro-ecosystems are typically driven by key species, and changes in the community composition and species abundance can have multifaceted effects. Assessment of individual services overlooks co-variance between different, but related, services coupled by a common group of species. This partial view ignores how effects propagate through an ecosystem. We conduct an analysis of 374 agricultural multilayer networks of two related services of weed seed regulation and gastropod mollusc predation delivered by carabid beetles. We found that weed seed regulation increased with the herbivore predation interaction frequency, computed from the network of trophic links between carabids and weed seeds in the herbivore layer. Weed seed regulation and herbivore interaction frequencies declined as the interaction frequencies between carabids and molluscs in the carnivore layer increased. This suggests that carabids can switch to gastropod predation with community change, and that link turnover rewires the herbivore and carnivore network layers affecting seed regulation. Our study reveals that ecosystem services are governed by ecological plasticity in structurally complex, multi-layer networks. Sustainable management therefore needs to go beyond the autecological approaches to ecosystem services that predominate, particularly in agriculture., Clare Gray et al. construct multilayer networks of weed seed regulation and pest gastropod predation by carabid beetles in 374 agricultural fields and show that these ecosystem services are mediated by trophic interaction frequencies. This study reveals that ecosystem services are governed by ecological plasticity in structurally complex, multi-layer trophic networks and these could assist in the assessment of the contribution of biodiversity to ecosystem services.

International audience; We believe that approaches to landscape modification should explicitly include farmers, given their understanding of landscape management practices, and consider climate change, so that the landscapes are designed for future environmental conditions. Climate change is an existential threat to farmers and current patterns of arable agriculture, leading to increases in the variability of agricultural productivity and crop failure. The performance of many of the crops that are currently highly productive will decline significantly and the geographical envelopes within which these crops can be grown are expected to shift northwards in Europe. Farmers will likely be faced with a choice: either leave farming or modify the crops that are grown, adopting new cultivars or species able to be cultivated profitably under future climatic conditions. We hypothesised that farmers do not adopt new crops or cultivars individually but use crops within sequences, called rotations, which are agronomically well understood. We know from past research that changes to rotations will lead to changes in biodiversity and the ecosystem services furnished by farmland, both within a field and at landscape scales. Here, we show how we might: use farmer knowledge of crop agronomy to propose future crop rotations in the light of climate change predictions; model these crop rotations to estimate likely effects on economy, biodiversity and ecosystem services; and validate these predictions through empirical study in regions where the rotations are already used. A workflow of co-development would have the benefit of generating practical rotations built on farmer knowledge and demonstrate empirically the predicted economic and ecological effects, markedly increasing the likely credibility of the results for farmers. Such a methodology has the potential to transform future sustainable agricultural landscapes.

International audience

International audience; Pitfall trapping is widely used for studying the abundance and diversity of ground-dwelling arthropods and smallvertebrates. Meta-analysis is a powerful technique to synthesize information across studies, but it requires standardizationto make study results comparable. It has never been studied how results of pitfall trapping should be standardized to obtainestimates of activity-density and diversity that are comparable across studies. We analysed samples of Carabidae(Coleoptera) from annual crops, reported in 104 publications from Europe and North-America, spanning a period of42 years, to find (i) a scaling for pitfall trapping effort to assess activity-density and diversity in pitfall catches across studies; and, (ii) to determine the sources of variability in the catch per unit effort. The total catch was proportional to the number of trap days, with a mean of 1.33 beetles/(trap days). The number of species was allometrically related to the trapping effort defined as the product of the number of traps, their perimeter and the time of exposure in the field. The mean species richness was 7.15 species/(m days)0.25. The size of the catch and the number of species adjusted per unit effort were higher in crops with narrow as compared to wide rows. Other factors were explored but were not influential. There was no significant change in abundance or diversity of carabids in arable land over the 42 years covered. The results give insight in factors affecting carabid abundance and diversity in field studies and enable standardization of pitfall catches across the literature.

International audience; Biomonitoring ecosystems is necessary in order to evaluate risks and to efficiently manage ecosystems and their associated services. Agrosystems are the target of multiple stressors that can affect many species through effects cascading along food webs. However, classic biomonitoring, focused on species diversity or indicator species, might be a poor predictor of the risk of such whole-ecosystem perturbations. Thanks to high-throughput sequencing methods, however, it might be possible to obtain sufficient information about entire ecological communities to infer the functioning of their associated interaction networks, and thus monitor more closely the risk of the collapse of entire food webs due to external stressors. In the course of the ‘next-generation biomonitoring’ project, we collectively sought to experiment with this idea of inferring ecological networks on the basis of metabarcoding information gathered on different systems. We here give an overview of issues and preliminary results associated with this endeavour and highlight the main difficulties that such next-generation biomonitoring is still facing. Going from sampling protocols up to methods for comparing inferred networks, through biomolecular, bioinformatic, and network inference, we review all steps of the process, with a view towards generality and transferability towards other systems. © 2022 Elsevier Ltd

Weed management is a resource-intensive practice in arable agriculture, with direct and long-term impacts on both productivity and biodiversity (e.g. plant, pollinators and farmland wildlife). In conventional systems, weed control relies on crop management and herbicide inputs, but for more sustainable production systems, use of herbicides needs to be reduced. This requires a good understanding of the processes that regulate arable weed dynamics in arable fields.We adopted a systems framework to understand and model interacting components that drive the weed dynamics in 168 arable fields. Within this framework, we built a structural equation model (SEM) to quantify the direct and indirect effects of crop rotation (i.e. crops in the previous three years and the current year) and carabid beetles (Coleoptera: Carabidae) on weed density, seed abundance and accumulation in the seedbank. We included results from a mechanistic approach to infer interactions between seed-feeding carabid beetles and seeds to estimate predation pressure in each field.Our results show that weeds in arable fields are regulated by crop type, sowing season, and activity density of carabid beetles. We found a direct effect of crop rotation, including both past and current field management practice, on weed abundance in the field and its seedbank. There was also an indirect effect of crops on weed seed accumulation in the seedbank via the effect of seed-eating carabid beetles. The efficiency of weed control by carabid beetles depended on the cumulative predation pressure, which indicates the importance of functional diversity as well as abundance.Farmers and agronomists can capitalise on the ecosystem services provided by carabid beetles by adapting agronomic practices and crop rotation to maintain a rich fauna of seed-eating carabids in fields and potentially across the agricultural landscapes. When integrated with rotational management practices, this ecosystem services can improve the efficiency of weed management and contribute to the sustainability of cropping systems.

Carabids are generalist predators that contribute to the agricultural ecosystem service of seedbank regulation via weed seed predation. To facilitate adoption of this ecosystem services by farmers, knowledge of weed seed predation and the resilience of seedbank regulation with co-varying availability of alternative prey is crucial. Using assessments of the seedbank and predation on seed cards in 57 cereal fields across Europe, we demonstrate a regulatory effect on the soil seedbank, at a continental scale, by groups formed of omnivore, seed-eating (granivore + omnivore) and all species of carabids just prior to the crop-harvest. Regulation was associated with a positive relationship between the activity-density of carabids and seed predation, as measured on seed cards. We found that per capita seed consumption on the cards co-varied negatively with the biomass of alternative prey, i.e. Aphididae, Collembola and total alternative prey biomass. Our results underline the importance of weed seedbank regulation by carabids, across geographically significant scales, and indicate that the effectiveness of this biocontrol may depend on the availability of alternative prey that disrupt the weed seed predation.

Ecological networks are valuable for ecosystem analysis but their use is often limited by a lack of data because many types of ecological interaction, e.g. predation, are short-lived and difficult to observe or detect. There are different methods for inferring the presence of interactions, which we lack methods to predict interaction strengths and so use weighted network analysis.Here, we develop a trait-based approach suitable for creating quantitative networks, i.e. with varying interaction strengths. We developed the method for seed-feeding carabid ground beetles (Coleoptera: Carabidae) although the principles can be applied to other interactions.We used existing literature data from experimental seed-feeding trials to predict a per-individual interaction cost index based on carabid and seed size with frequency-dependent prey selection and assuming bottom up control. This was scaled up to the population level to create predicted inferred weighted networks using the abundance of carabids and seeds in samples from arable fields and energetic intake rates of carabids from the literature. From these weighted networks, we also calculated a novel measure of predation pressure.We applied it to existing ecological survey data from 255 arable fields with carabid data from pitfall traps and plant seeds from seed rain traps. Analysis of these inferred networks led to testable hypotheses about how networks and predation pressure varied amongst fields.Inferred networks are valuable because (i) they provide null models for the structuring of food webs to test against empirical species interaction data, e.g. DNA analysis of carabid gut regurgitates, and (ii) they allow weighted inferred networks to be constructed whenever we can estimate interactions between species and have ecological census data available. This would permit network analysis even at times and in places when interactions were not directly assessed.

Carabid beetles (Coleoptera: Carabidae) provide important ecological services and are frequently used as a bio-indicator in monitoring environmental quality. The abundance and diversity of carabids is usually determined using pitfall trapping, but trap catches are difficult to compare between studies due to variation in trapping effort. The standardization of the catch for trapping effort has not been previously addressed in a global analysis of studies in the literature.The aims of this study are (i) to define a method for estimating the effect of trapping effort on the size of the pitfall catch, and (ii) to explore factors related to study designs, sampling method, study origin, and level of data aggregation to determine how these factors affect the catch per unit effort in pitfall trapping.We conducted a meta-analysis on the activity-density and diversity of carabids across studies, based on published data from Europe and North-America to analyse whether standardization of catch measurements might be possible. Data were extracted from 104 publications, spanning a period of 42 years.The total catch was proportional to the number of trap days, and ranged from 0.19-9.53 beetles/(trap day) across studies (95% range), with a mean of 1.33 beetles/(trap day). The number of species was allometrically related to the trapping effort defined as the product of the number of traps, their perimeter and the time of exposure in the field, and characterized by a power exponent of 0.25. Species richness ranged across studies from 2.30-13.18 species/(m day)0.25(95% range) with a mean of 7.15 species/(m day)0.25. The size of the catch and the number of species were higher in crops with narrow as compared to wide rows. There was no significant change in abundance or diversity of carabids in arable land over the 42 years covered. We also found that increasing trapping effort may not yield more accurate results.The results show that it is possible to standardize activity-density-based catches and species diversity for trapping effort across studies using a power transformation, allowing meta-analysis of such data, e.g. to elucidate factors affecting abundance and diversity of the focal taxa.

Interactions between plant pathogens and other plant-associated microorganisms regulate disease. Deciphering the networks formed by these interactions, termed pathobiomes, is crucial to disease management. Our aim was to investigate whether microbial association networks inferred from metabarcoding data give relevant insights into pathobiomes, by testing whether inferred associations contain signals of ecological interactions. We used Poisson Lognormal Models to construct microbial association networks from metabarcoding data and then investigated whether some of these associations corresponded to interactions measurable in co-cultures or known in the literature, by using grapevine (Vitis vinifera) and the fungal pathogen causing powdery mildew (Erysiphe necator) as a model system. Our model suggested that the pathogen species was associated with 23 other fungal species, forming its putative pathobiome. These associations were not known as interactions in the literature, but one of them was confirmed by our co-culture experiments. The yeast Buckleyzyma aurantiaca impeded pathogen growth and reproduction, in line with the negative association found in the microbial network. Co-cultures also supported another association involving two yeast species. Together, these findings indicate that microbial networks can provide plausible hypotheses of ecological interactions that could be used to develop microbiome-based strategies for crop protection.

International audience; A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (A) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (B) De novo bioindicator analyses; (C) Structural community metrics including inferred ecological networks; and (D) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programs that leverage recent analytical advancements, while pointing out current limitations and future research needs.

International audience; There is growing interest in the potential for combining eDNA and artificial intelligence (machine learning) to detect and evaluate in real time changes in ecosystems at the global scale, in a more sensitive and cost-effective way than current biomonitoring methods. Machine learning might make better use of the eDNA census data that can currently be collected to evaluate the network of ecological interactions that are at the base of the services that ecosystems supply and that we wish to protect. To date, eDNA and machine learning developments have effectively progressed in parallel and in isolation in various spheres of ecosystem monitoring (disease, invasion, conservation, etc. in aerial, terrestrial, and aquatic systems).The goal of this Research Topic is to explore the range of ongoing activities to build the next generation of biomonitoring tools and in doing so to make researchers in the different spheres aware of the breadth of work being undertaken, and to set a unifying research agenda (the key questions) for the development of global biomonitoring using eDNA and machine learning.The scope of this Research Topic will be to explore:1. eDNA approaches currently being used in case study systems from all spheres of monitoring;2. Theoretical underpinnings of machine learning for biomonitoring;3. What type of networks do we need to reconstruct for effective monitoring (co-occurrence, trophic, etc);4. Examples of learning large scale, replicated networks from eDNA in the different spheres;5. Statistical and analytical approaches to analysing large-scale, highly replicated networks;6. Technological developments necessary to build a next-generation biomonitoring framework at the global scale;7. A research agenda paper that develops “10 key questions for eDNA and machine learning in biomonitoring”.Details for Authors: The Research Topic “A next-generation of global biomonitoring to detect ecosystem change” will publish conceptual, data, case study, technological and synthetic papers on eDNA and machine learning approaches for developing a unified next-generation biomonitoring framework. Paper length conforms to the guidelines of the journal Frontiers in Ecology and Evolution.

11 pages; International audience; Carabid beetles may play a role in the regulation of arable weeds, when seed predation is directly density‐dependent and consumption increases more than proportionally with seed density. We quantified the effect of seed and carabid density on consumption by two carabid species (Poecilus cupreus and Harpalus affinis) of the weed species Taraxacum officinale and Viola arvensis. For each pairing of carabid and weed species, we quantified per capita seed mortality (PCSM) over 72 h under combinations of low and high densities of carabids and seeds, aiming to assess whether per capita consumption increased more or less than proportionally with seed density. We tested three hypotheses: (i) PCSM is constant as seed availability increases; (ii) for a fixed seed density, PCSM decreases with increasing numbers of carabid conspecifics; and (iii) the response of PCSM changes with the interaction between seed and carabid density. Without intraspecific competition, we detected a seed density‐independent predation effect, which became inverse density‐dependent over time. At similar seed densities, the presence of conspecific carabids did not affect PCSM, although it led to a faster shift towards inverse density dependence in T. officinale. The findings of the present study suggest that a sufficiently large carabid numerical response might lead to direct predation density‐dependence.

International audience; Seed predators are an integral part of agroecosystems, where they can reduce the populations of weeds. The preference of predators for seeds and the observed predation rate may be affected by the properties of seeds (e.g. taxonomy, chemical composition, physical defence). In this work, we focused on seed consumption of Taraxacum officinale Web. and Stellaria media (L.) Vill., from France and the Czech Republic, by three species of ground beetle that are seed predators (Coleoptera: Carabidae): Poecilus cupreus (L.), Pterostichus melanarius (Illiger) and Anchomenus dorsalis (Pontoppidan). The seed species were offered in arenas, simultaneously, under three different experimental manipulations of moisture and seed coat conditions: dry and intact, water-imbibed and intact, and water-imbibed with a damaged seed coat. Seed consumption was checked after 0.5, 1, 2, 24, and 48 hrs of exposure. Anchomenus dorsalis largely refused to feed on seeds. Taraxacum officinale seeds with damaged coats were most preferred by the remaining two species of carabids. The consumption by P. cupreus of T. officinale seeds with damaged coats increased from 0.18% after 0.5 hrs to 83.83% after 48 hrs, and by P. melanarius from 13.76% after 0.5 hrs to 76.77% after 48 hrs. Seeds of S. media were consumed less. There was a significant difference in consumption rates due to the country of origin of the seeds, but there were no differences between the carabid sexes. That carabids preferred water-imbibed and damaged seeds may suggest an involvement of olfactory clues in the seed selection process, and/or shorter seed-handling times. © 2020. All Rights Reserved.

International audience; Environmental DNA contains information on the species interaction networks that support ecosystem functions and services. Next‐Generation Biomonitoring proposes the use of this data to reconstruct ecological networks in real‐time and then compute network‐level properties to assess ecosystem change. We investigated the relevance of this proposal by assessing: (1) the replicability of DNA‐based networks in the absence of ecosystem change; and, (2) the benefits and shortcomings of community‐ and network‐level properties for monitoring change. We selected crop‐associated microbial networks as a case study since they support disease regulation services in agroecosystems and analyzed their response to change in agricultural practice between organic and conventional systems. Using two statistical methods of network inference, we showed that network‐level properties, especially β‐properties, could detect change. Moreover, consensus networks revealed robust signals of interactions between the most abundant species, that differed between agricultural systems. These findings complemented those obtained with community‐level data, that showed, in particular, a greater microbial diversity in the organic system. The limitations of network‐level data included (i) the very high variability of network replicates within each system; (ii) the low number of network replicates per system, due to the large number of samples needed to build each network; and, (iii) the difficulty in interpreting links of inferred networks. Tools and frameworks developed over the last decade to infer and compare microbial networks are therefore relevant to biomonitoring, provided that the DNA metabarcoding datasets are large enough to build many network replicates and progress is made to increase network replicability and interpretation.

Seed predators are an integral part of agrocoenoses where they contribute to the reduction of weed populations. Although they are taking part in biological control of weed seeds, we still do not understand which properties of seeds are responsible for variable attractiveness of different species of seeds to carabids beetles. Seed coat provides a physical barrier and hinders volatiles to be released from the seeds when these are dry. In this work, we focused on seed preferences of Taraxacum officinale and Stellaria media by a ground beetle (Coleoptera: Carabidae) species, Poecilus cupreus, which is known as an omnivorous species. The seeds were used in three different states - dry, imbibed and with crushed seed coat, and from two different origins. The seeds were presented simultaneously in an experimental arena. Seed consumption was assessed after 30 minutes, 24 hours and 48 hours of exposure. There was no statistically significant difference between seeds with different origin. The most preferred seeds were T. officinale with damaged seed coat. The total consumption of these seeds was was 0.1 % after 30 minutes, 13.8 % after 1 day and 71.5 % after 48 hours. The seeds of S. media were consumed less. This indicates that the consumption was enhanced by either an increase of volatile compounds from the damaged seeds that attracted the beetles, or from shorter handling time due to reduced physical barrier of the crushed coat.