Yannick Agnan

The concept of soil health is becoming increasingly popular. Yet, the way to measure it remains unclear, which hinders its effective consideration in decision-making processes. We propose a general framework to interpret soil data, including the scoring of absolute soil quality (the state of an indicator representative of a soil function regarding an absolute maximum) and (ii) the scoring of soil health (the relative level of an indicator with respect to soil intrinsic potential). We underline that the scoring of soil quality and potential quality is central in land planning and excavated soil reemployment (i.e., matching land future use with soil capabilities) whereas soil health, as the mirror of soil degradation, is essential for soil restoration and sustainable management. We illustrate the approach with saturated hydraulic conductivity as an indicator of soil infiltration capacity for 42 measurements from contrasting soil types and uses, and demonstrate that the approach can be generalized to other soil indicators and functions. Overall, we outline the need to refine target or threshold values for the scoring of both soil quality and soil health, thereby better equipping stakeholders for sustainable soil management and land planning.

The concept of soil health is becoming increasingly popular. Yet, the way to measure it remains unclear, which hinders its effective consideration in decision-making processes. We propose a general framework to interpret soil data, including the scoring of absolute soil quality (the state of an indicator representative of a soil function regarding an absolute maximum) and (ii) the scoring of soil health (the relative level of an indicator with respect to soil intrinsic potential). We underline that the scoring of soil quality and potential quality is central in land planning and excavated soil reemployment (i.e., matching land future use with soil capabilities) whereas soil health, as the mirror of soil degradation, is essential for soil restoration and sustainable management. We illustrate the approach with saturated hydraulic conductivity as an indicator of soil infiltration capacity for 42 measurements from contrasting soil types and uses, and demonstrate that the approach can be generalized to other soil indicators and functions. Overall, we outline the need to refine target or threshold values for the scoring of both soil quality and soil health, thereby better equipping stakeholders for sustainable soil management and land planning.

The concept of soil health is becoming increasingly popular. Yet, the way to measure it remains unclear, which hinders its effective consideration in decision-making processes. We propose a general framework to interpret soil data, including the scoring of absolute soil quality (the state of an indicator representative of a soil function regarding an absolute maximum) and (ii) the scoring of soil health (the relative level of an indicator with respect to soil intrinsic potential). We underline that the scoring of soil quality and potential quality is central in land planning and excavated soil reemployment (i.e., matching land future use with soil capabilities) whereas soil health, as the mirror of soil degradation, is essential for soil restoration and sustainable management. We illustrate the approach with saturated hydraulic conductivity as an indicator of soil infiltration capacity for 42 measurements from contrasting soil types and uses, and demonstrate that the approach can be generalized to other soil indicators and functions. Overall, we outline the need to refine target or threshold values for the scoring of both soil quality and soil health, thereby better equipping stakeholders for sustainable soil management and land planning.

The concept of soil health is becoming increasingly popular. Yet, the way to measure it remains unclear, which hinders its effective consideration in decision-making processes. We propose a general framework to interpret soil data, including the scoring of absolute soil quality (the state of an indicator representative of a soil function regarding an absolute maximum) and (ii) the scoring of soil health (the relative level of an indicator with respect to soil intrinsic potential). We underline that the scoring of soil quality and potential quality is central in land planning and excavated soil reemployment (i.e., matching land future use with soil capabilities) whereas soil health, as the mirror of soil degradation, is essential for soil restoration and sustainable management. We illustrate the approach with saturated hydraulic conductivity as an indicator of soil infiltration capacity for 42 measurements from contrasting soil types and uses, and demonstrate that the approach can be generalized to other soil indicators and functions. Overall, we outline the need to refine target or threshold values for the scoring of both soil quality and soil health, thereby better equipping stakeholders for sustainable soil management and land planning.

The concept of soil health is becoming increasingly popular. Yet, the way to measure it remains unclear, which hinders its effective consideration in decision-making processes. We propose a general framework to interpret soil data, including the scoring of absolute soil quality (the state of an indicator representative of a soil function regarding an absolute maximum) and (ii) the scoring of soil health (the relative level of an indicator with respect to soil intrinsic potential). We underline that the scoring of soil quality and potential quality is central in land planning and excavated soil reemployment (i.e., matching land future use with soil capabilities) whereas soil health, as the mirror of soil degradation, is essential for soil restoration and sustainable management. We illustrate the approach with saturated hydraulic conductivity as an indicator of soil infiltration capacity for 42 measurements from contrasting soil types and uses, and demonstrate that the approach can be generalized to other soil indicators and functions. Overall, we outline the need to refine target or threshold values for the scoring of both soil quality and soil health, thereby better equipping stakeholders for sustainable soil management and land planning.

La contamination atmosphérique par les métaux/métalloïdes (As, Cd, Cu, Pb, Sb, Zn…) et par les composés azotés impacte durablement les écosystèmes. L’évaluation des dépôts atmosphériques responsables de ces effets néfastes reste éparse car complexe, en particulier dans les environnements éloignés des sources de contamination comme les massifs forestiers. La prospection et l’estimation des éléments traces et de l’azote apportés dans ces dépôts ont été réalisées à l’échelle nationale à travers deux approches de biosurveillance par les lichens et les mousses : la bioaccumulation et la bioindication. L’enregistrement des éléments traces par les organismes indique une forte pression lithogénique dans ces milieux éloignés des sources directes, qui s’inclut dans le bruit de fond géochimique (e. g. Al, As, Co, Cr, Fe, Ni et Ti). Des sources additionnelles issues des activités anthropiques plus locales complètent régionalement les cortèges des éléments chimiques enregistrés (Cd, Cu, Sb ou Zn). La comparaison des échantillons de lichens et de mousses avec des spécimens historiques d’herbiers nous permet de retrouver ce contexte régional durant les siècles passés, et notamment de conforter les signatures lithologiques à travers le temps grâce aux terres rares. Ainsi, l’utilisation du charbon fossile apparaît être la source de contamination métallique dominante durant la fin du XIX e siècle et le début du XX e siècle, et plus récemment, une source additionnelle comme le transport routier (cas de Pb) a pu être notée. En parallèle, des facteurs influençant la bioaccumulation des métaux ont été testés : l’espèce considérée joue sur la capture des particules atmosphériques à travers la morphologie du thalle, et l’écorce support ne présente que peu d’influence. En considérant les signatures des dépôts atmosphériques, la végétation au travers des pluviolessivats apparaît influencer davantage les mousses terricoles que les lichens corticoles, ces derniers étant plus représentatifs des dépôts totaux. Des expérimentations de sorption/désorption montrent un processus rapide d’accumulation (une semaine) pour Pb et Cd, mais ne montrent ni compétition entre les métaux bioaccumulés, ni influence du lessivage sur la bioaccumulation. De nouvelles données concernant la sensibilité des espèces lichéniques face aux polluants métalliques ont pu être obtenues à partir de relevés de bioindication couplés à des analyses statistiques multivariées.

Living cover crops play a key role in reducing nitrogen leaching to groundwater during fallow periods. They also enhance soil microbial activity through root exudates, improving soil structure and increasing organic matter content. While the degradation of pesticides in soil relies primarily on microbial biodegradation, the extent to which cover crops influence this degradation remains poorly quantified. The objective of this study was to evaluate to what extent pesticide residues with contrasting physicochemical properties are affected by living cover crops. We conducted a greenhouse experiment testing two cover crop densities against a bare soil control, and quantified residues (by LC-QTOFMS) of 18 pesticide ingredients (active substances and safeners) in both soil and soil solution. We then related the observed reduction in residues to key physicochemical properties of the pesticide ingredients. Our results show that thin cover crops (0.4 t_DM ha⁻¹) reduce pesticide leaching 80 d after sowing relative to bare soil, retaining residues in the topsoil. Moreover, well-developed cover crops (1 t_DM ha⁻¹) reduce soil pesticide residues by more than 33 % for compounds with low to high water solubility (s⩽1400 mg L⁻¹) and low to moderate soil mobility (K_oc⩾160 mL g⁻¹). This effect is likely due to enhanced pesticide degradation of the retained pesticide in the rhizosphere. These findings confirm previous studies focused on individual compounds, individual cover crop types or individual soil compartments, while providing new thresholds for physicochemical properties associated with significant pesticide degradation. By directly enhancing pesticide degradation within the soil compartment where pesticides are applied, cover crops limit their transfer to other environmental compartments, particularly groundwater.

Air pollution and climate change remain critical environmental challenges, particularly in urban areas, where conventional monitoring networks are often too sparse to capture fine‐scale exposure gradients due to their high operational costs. Epiphytic lichen biomonitoring provides a valuable complementary approach, as these organisms are sensitive to both air pollutants and climate conditions. Despite the existence of a standardized European protocol, large‐scale implementation is hindered by the absence of a robust interpretative framework and incomplete knowledge of species‐specific responses to pollutants and climate variables. This study initiated the development of a standardized interpretative framework for European lichen biomonitoring data by identifying a core set of indicator species with clear responses to major air pollutants and climate variables. To achieve this, we compiled and harmonized raw lichen data from 58 studies that applied the European protocol and modeled the response of 43 lichen species to dominant air pollutants (NH ₃ , NO _x , and SO ₂ ) and climate variables (mean air temperature, mean relative humidity, and temperature seasonality). While confirming established trends, our models allowed us to decouple species responses to reduced (NH ₃ ) vs. oxidized (NO _x ) nitrogen compounds, a distinction rarely achievable in local studies due to insufficient contrast in pollutant gradients. We also provided actionable recommendations to enhance comparability, such as prioritizing widespread, well‐studied tree species and standardizing lichen taxa groupings. Our study established a foundation for a harmonized European interpretative framework by identifying low‐bias, ecologically meaningful indicator species. Future efforts should focus on translating sensitivity classifications into actionable air quality indices and refining regional‐scale assessments.