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Sustainable solutions aiming at limiting Reynoutria japonica invasion consist of frequent removal of its aerial biomass. The aims of this study were to measure the accumulation of metallic trace elements (MTE) in R. japonica, and to assess the ecotoxicological risk related to the valorization of the produced biomass. R. japonica fragmented rhizomes were regenerated in pots for 41 days on a control soil (CTL) or a moderately MTE-contaminated soil (POL, 3.6 mg Cd kg −1 DM). Growth traits were recorded, as well as MTE bioconcentration (BCF) and translocation factors (TF) from soil to plant organs. Whatever the MTE and plant organs, BCF remained below one (mean Cd-BCF for stem and leaf: 0.07 and 0.29 for CTL and POL, respectively), conversely to TF (until 2.2 for Cd and Ni in POL soil). When grown on the POL soil, R. japonica stem and leaf Cd content was close to the EU maximum regulatory limit for organic amendments or animal feed. Model simulations suggested that liver and kidney Cd concentrations would exceed the regulatory limit in food when adult cattle or sheep constantly ingest R. japonica grown on the POL soil over 200 to 800 days. The results of the present study will be useful to help managers in selecting efficient and safe solutions for the control of R. japonica invasion.

The understanding of soil organic matter (SOM) dynamics has considerably advanced in recent years. It was previously assumed that most SOM consisted of recalcitrant compounds, whereas the emerging view considers SOM as a range of polymers continuously processed into smaller molecules by decomposer enzymes. Mainstreaming this new paradigm in current models is challenging because of their ill-adapted framework. We propose the C-STABILITY model to resolve this issue. Its innovative framework combines compartmental and continuous modeling approaches to accurately reproduce SOM cycling processes. C-STABILITY emphasizes the influence of substrate accessibility on SOM turnover and makes enzymatic and microbial biotransformations of substrate explicit. Theoretical simulations provide new insights on how depolymerization and decomposers ecology impact organic matter chemistry and amount during decomposition and at steady state. The flexible mathematical structure of C-STABILITY offers a promising foundation for exploring new mechanistic hypotheses and supporting the design of future experiments.

The imperative of carbon neutrality requires a drastic, rapid, and sustained reduction in fossil energy consumption and greenhouse gas emissions. The Russia-Ukraine war has led to a major energy crisis, whose end does not seem imminent. The sudden and major increase in energy prices resulting from this crisis has major impacts on many sectors of the societies. This is especially true for agriculture, a direct consumer of energy that also has considerable indirect consumption through the manufacture, transport, and distribution of chemical inputs such as fertilizers and pesticides. Taking the example of France, from July 2021 to July 2022, farmers were challenged with price increases as high as 48% and 111% for energy and fertilizers, respectively (Agreste, 2022). At the global scale, in 2018, greenhouse gas emissions from fossil energy consumption in agriculture represented 0.9 Pg CO2 eq. (against 9.3 Pg CO2 eq. due to agriculture, excluding emissions due to this energy consumption) and those emissions have increased by 23% since 2000 (FAO, 2020). This context calls for in-depth transformation of agriculture, which is currently overly dependent on non-renewable energy in high-income economies. While research on the subject continues to grow (Box 1), this large body of work focuses more on assessing the energy consumption of current agricultural systems using multiple metrics (Box 2) than on developing supply- or demand-side alternatives that use less energy. In response to these trends, Ramankutty and Dowlatabadi (2021) suggested pathways to sustainable food systems. However, while their recommendations included energy reduction options on the food consumption side, their focus on farming practices was restricted to improving the energy efficiency of current agricultural systems and missed the necessary redesign of farming and food systems. In this article, we look back to understand how agricultural systems came to progressively depend on non-renewable energy. We then briefly review agricultural practices and systems reducing energy consumption without compromising energy efficiency. Finally, we propose future research avenues to explore pathways for reducing energy consumption without compromising food security and sustainability challenges.

Deltas are complex social-ecological systems (SESs) that involve many economic activities that interconnect closely with ecological processes and biodiversity. Sustainable management of such intricate SESs requires developing an integrated and understandable representation of their main human and ecological entities, processes, and interactions. We developed a formal representation of the Ile de Camargue (center of the Rhône delta), in which hydro-saline dynamics, water management, economic activities (e.g., agriculture, hunting, fishing, tourism), and natural environments (i.e., habitats for biodiversity) interact. The conceptual model was based on four submodels that provided complementary representations of i) water governance, ii) agriculture, and iii) bird and iv) fish communities. The conceptual model highlights the strong relationships (i.e., causal chains, feedback loops, interactions, side effects, and trade-offs) among the multiple entities of this deltaic SES. It provides information about the region and describes deltas as a SES to support decision-making. One major feedback loop in the delta concerned relationships among regulations, rice fields, and use of marshes as a habitat for birds: strengthening pesticide regulations to improve water quality and bird habitats caused the area of rice cultivation to decrease which degraded habitat conditions for birds. Directly related to pesticide use, the most common trade-off is to decide whether water management should prioritize water quality or quantity in the delta’s Vaccarès lagoon, and opinion differs among stakeholders. The conceptual model could be used as a starting point to develop computer-based integrated assessment and modeling to explore dynamics of and resilience to climate change in the Ile de Camargue.

The biofilm matrix can be considered to be a shared space for the encased microbial cells, comprising a wide variety of extracellular polymeric substances (EPS), such as polysaccharides, proteins, amyloids, lipids and extracellular DNA (eDNA), as well as membrane vesicles and humic-like microbially derived refractory substances. EPS are dynamic in space and time and their components interact in complex ways, fulfilling various functions: to stabilize the matrix, acquire nutrients, retain and protect eDNA or exoenzymes, or offer sorption sites for ions and hydrophobic substances. The retention of exoenzymes effectively renders the biofilm matrix an external digestion system influencing the global turnover of biopolymers, considering the ubiquitous relevance of biofilms. Physico-chemical and biological interactions and environmental conditions enable biofilm systems to morph into films, microcolonies and macrocolonies, films, ridges, ripples, columns, pellicles, bubbles, mushrooms and suspended aggregates — in response to the very diverse conditions confronting a particular biofilm community. Assembly and dynamics of the matrix are mostly coordinated by secondary messengers, signalling molecules or small RNAs, in both medically relevant and environmental biofilms. Fully deciphering how bacteria provide structure to the matrix, and thus facilitate and benefit from extracellular reactions, remains the challenge for future biofilm research.In this Review, Flemming et al. revisit our understanding of the biofilm matrix, focusing on the diversity of the extracellular polymeric substance components and novel aspects of mechanisms and consequences of their functional interactions.

(1) Although most past studies are based on static analyses of the pest regulation drivers, evidence shows that a greater focus on the temporal dynamics of these interactions is urgently required to develop more efficient strategies. (2) Focusing on aphids, we systematically reviewed (i) empirical knowledge on the drivers influencing the dynamics of aphid–natural enemy interactions and (ii) models developed to simulate temporal or spatio-temporal aphid dynamics. (3) Reviewed studies mainly focus on the abundance dynamics of aphids and their natural enemies, and on aphid population growth rates. The dynamics of parasitism and predation are rarely measured empirically, although it is often represented in models. Temperature is mostly positively correlated with aphid population growth rates. Plant phenology and landscape effects are poorly represented in models. (4) We propose a research agenda to progress towards models and empirical knowledge usable to design effective CBC strategies. We claim that crossover works between empirical and modeling community will help design new empirical settings based on simulation results and build more accurate and robust models integrating more key drivers of aphid dynamics. Such models, turned into decision support systems, are urgently needed by farmers and advisors in order to design effective integrated pest management.

The estimation of irrigation water requirements (IWR) amount and timing is crucial for designing water management strategies at the regional scale. Irrigation requirements can be estimated with different types of models: very complex and detailed crop models, agent-based models, or simplified modeling approaches. Because simplified approaches are often preferred, in this study, we evaluate the consequences of using simplified approaches for IWR assessment at a catchment scale and the consequences of various modeling choices, providing information on the uncertainties. To this end, different simple modeling approaches based on the CropWat model are compared with an agent-based approach (MAELIA), which serves as a benchmark. To assess simulations in detail, partial variance is calculated for several indicators characterizing daily simulated irrigation. Our sensitivity analysis, applied over a sub-catchment of the Aveyron River (southwestern France), shows a high variability in simulations produced by CropWat between the modeling assumptions tested, principally explained by the rules for irrigation triggering and the quantification of daily irrigation. The analysis also shows that several simplified approaches are able to reproduce the irrigation simulated by the high-accuracy MAELIA model, but not necessarily corresponding to an optimal irrigation scheme. Hence, this study confirms the possibility of assessing daily irrigation with simplified approaches, but warns about high modeling uncertainties, reflecting uncertainty in effective irrigation practices. This uncertainty can be taken into account by water managers and modelers through the combination of a set of irrigation models.

Crop diversification represents a key lever to support the development of sustainable agri-food systems. Knowledge on trade-offs and carry over effects from different crop diversification strategies is essential to inform agricultural stakeholders of potential costs and benefits. This knowledge is limited by existing data and performance measures predominantly focused on single crops, rather than complete rotations. Moreover, sustainability performance indicators are often used for assessment purposes, rather than supporting stakeholder learning and actions. A new set of 32 indicators was developed to address these needs, and used to evaluate the environmental, economic and social sustainability of the diversified agricultural systems highlighted in the case studies, which are often characterized by data availability constraints. This approach was tested in France, Germany and Italy to determine a critical ex-post diagnosis of the existing systems, and for the assessment of ex-ante innovative scenarios. The results will be used to support these case studies in the identification and design of more sustainable agricultural systems. Although the framework is based on feasible and proxy indicators, the assessment outcomes have allowed local actors to reflect on the effects generated by the implemented crop diversification strategies. Key issues include trade-offs occurring between optimizing economic and environmental performance.

Aims: A field experiment was conducted to evaluate the effects of alley cropping systems on microbial activity and soil organic matter (SOM) pools. We hypothesized that enzyme activity and labile pools of SOM are early and sensitive indicators of changes induced by tree introduction in the cropping systems.Methods: Poplar-alfalfa and alder-gramineous (cereal or ryegrass) associations and their respective control systems (alfalfa and gramineous) were compared in terms of soil carbon (C), nitrogen (N) and water contents, SOM labile pools, NIRS-MIRS spectra and microbial enzyme activity in the topsoil (0–15 cm) for 4 years after tree planting.Results: After 1 year, tree introduction induced a decrease in soil water content, microbial biomass N and some enzyme activities under alfalfa system. After 4 years, tree introduction resulted in higher soil water contents in both systems (alfalfa and gramineous); higher microbial biomass N and lower C:N in alfalfa-poplar plots compared to control plots. MIRS-NIRS analyses showed a greatest differentiation in SOM quality between alfalfa-based systems.Conclusions: The effects of temperate agroforestry systems on SOC in the topsoil are relatively weak in the first years after tree introduction. Observed effects were more pronounced in the alfalfa-poplar system, probably due to higher tree growth. Further studies will provide insights into the longer-term effects of these systems on soil functioning.

In most current farming system classifications (e.g. \"conventional\"versus \"organic\"), each type of farming system encompasses a wide variety of farming practices and performances. Classifying farming systems using concepts such as \"ecological\", \"sustainable intensification\"or \"agro-ecology\"is not satisfactory because the concepts \"overlap in. definitions, principles and practices, thus creating. confusion in their meanings, interpretations and implications\". Existing classifications most often focus either on biotechnical functioning or on socio-economic contexts of farming systems. We reviewed the literature to develop an original analytical framework of the diversity of farming systems and agriculture models that deal with these limits. To describe this framework, we first present the main differences between three biotechnical types of farming systems differing in the role of ecosystem services and external inputs: chemical input-, biological input-and biodiversity-based farming systems. Second, we describe four key socio-economic contexts which determine development and functioning of these farming systems: globalised commodity-based food systems, circular economies, alternative food systems and integrated landscape approaches. Third, we present our original analytical framework of agriculture models, defined as biotechnical types of farming systems associated with one or a combination of socio-economic contexts differing in the role of relationships based on global market prices and \"territorial embeddedness\". We demonstrate the potential of this framework by describing six key agriculture models and reviewing key scientific issues in agronomy associated with each one. We then analyse the added value of our analytical framework and its generic character. Lastly, we discuss transversal research issues of the agriculture models, concerning the technologies required, their function in the bioeconomy, their multi-criteria and multi-level assessments, their co-existence and the transitions between them.