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In recent decades, there has been growing interest in exploring the soil biota, highlighting the significance of soil organisms' networks in soil functioning. Here, we use a modeling approach to investigate how changes in cropping practices influence the soil food web dynamics and it relates to that of soil functioning. In an experimental trial, we tested for change in topsoil food webs after shift from conventional to alternative practices (changes in tillage intensity, amount of residues returned and N fertilization rate). Samplings were made in 16 plots of a randomized complete block design during spring of year 0, 2 and 4 after the onset of the trial. Microorganisms, microfauna, mesofauna and macrofauna were sampled, identified and grouped into trophic groups. We built a general soil food web describing plausible carbon flows between these trophic groups and computed several network indices. At the same dates, soil functions linked to C and N dynamics were measured from soil samples. We used a COSTATIS analysis to investigate relationships between temporal sequences of soil functions and soil food web indices. Significant interactive effects of the date and of agricultural systems were found on the mean and the maximum trophic level, the bacterial-to-fungal path ratio, the total biomass and the way biomass accumulates across trophic levels, the number of trophic groups and the functional redundancy in trophic groups. Similarly, organic matter transformations and enzymatic activities showed differences across date and agricultural systems. Results show that temporal changes in soil food web structure and in soil processes related to N and C cycling co-vary following changes in agricultural management practices. Management practices related to tillage exerted stronger effects on soil food web functioning than those related to the export of crop residues or reduction in mineral N fertiliser. For instance, reduced tillage lead to more complex food webs, with increas, In recent decades, there has been growing interest in exploring the soil biota, highlighting the significance of soil organisms' networks in soil functioning. Here, we use a modeling approach to investigate how changes in cropping practices influence the soil food web dynamics and it relates to that of soil functioning. In an experimental trial, we tested for change in topsoil food webs after shift from conventional to alternative practices (changes in tillage intensity, amount of residues returned and N fertilization rate). Samplings were made in 16 plots of a randomized complete block design during spring of year 0, 2 and 4 after the onset of the trial. Microorganisms, microfauna, mesofauna and macrofauna were sampled, identified and grouped into trophic groups. We built a general soil food web describing plausible carbon flows between these trophic groups and computed several network indices. At the same dates, soil functions linked to C and N dynamics were measured from soil samples. We used a COSTATIS analysis to investigate relationships between temporal sequences of soil functions and soil food web indices. Significant interactive effects of the date and of agricultural systems were found on the mean and the maximum trophic level, the bacterial-to-fungal path ratio, the total biomass and the way biomass accumulates across trophic levels, the number of trophic groups and the functional redundancy in trophic groups. Similarly, organic matter transformations and enzymatic activities showed differences across date and agricultural systems. Results show that temporal changes in soil food web structure and in soil processes related to N and C cycling co-vary following changes in agricultural management practices. Management practices related to tillage exerted stronger effects on soil food web functioning than those related to the export of crop residues or reduction in mineral N fertiliser. For instance, reduced tillage lead to more complex food webs, with incr

In recent decades, there has been growing interest in exploring the soil biota, highlighting the significance of soil organisms' networks in soil functioning. Here, we use a modeling approach to investigate how changes in cropping practices influence the soil food web dynamics and it relates to that of soil functioning. In an experimental trial, we tested for change in topsoil food webs after shift from conventional to alternative practices (changes in tillage intensity, amount of residues returned and N fertilization rate). Samplings were made in 16 plots of a randomized complete block design during spring of year 0, 2 and 4 after the onset of the trial. Microorganisms, microfauna, mesofauna and macrofauna were sampled, identified and grouped into trophic groups. We built a general soil food web describing plausible carbon flows between these trophic groups and computed several network indices. At the same dates, soil functions linked to C and N dynamics were measured from soil samples. We used a COSTATIS analysis to investigate relationships between temporal sequences of soil functions and soil food web indices. Significant interactive effects of the date and of agricultural systems were found on the mean and the maximum trophic level, the bacterial-to-fungal path ratio, the total biomass and the way biomass accumulates across trophic levels, the number of trophic groups and the functional redundancy in trophic groups. Similarly, organic matter transformations and enzymatic activities showed differences across date and agricultural systems. Results show that temporal changes in soil food web structure and in soil processes related to N and C cycling co-vary following changes in agricultural management practices. Management practices related to tillage exerted stronger effects on soil food web functioning than those related to the export of crop residues or reduction in mineral N fertiliser. For instance, reduced tillage lead to more complex food webs, with increas, In recent decades, there has been growing interest in exploring the soil biota, highlighting the significance of soil organisms' networks in soil functioning. Here, we use a modeling approach to investigate how changes in cropping practices influence the soil food web dynamics and it relates to that of soil functioning. In an experimental trial, we tested for change in topsoil food webs after shift from conventional to alternative practices (changes in tillage intensity, amount of residues returned and N fertilization rate). Samplings were made in 16 plots of a randomized complete block design during spring of year 0, 2 and 4 after the onset of the trial. Microorganisms, microfauna, mesofauna and macrofauna were sampled, identified and grouped into trophic groups. We built a general soil food web describing plausible carbon flows between these trophic groups and computed several network indices. At the same dates, soil functions linked to C and N dynamics were measured from soil samples. We used a COSTATIS analysis to investigate relationships between temporal sequences of soil functions and soil food web indices. Significant interactive effects of the date and of agricultural systems were found on the mean and the maximum trophic level, the bacterial-to-fungal path ratio, the total biomass and the way biomass accumulates across trophic levels, the number of trophic groups and the functional redundancy in trophic groups. Similarly, organic matter transformations and enzymatic activities showed differences across date and agricultural systems. Results show that temporal changes in soil food web structure and in soil processes related to N and C cycling co-vary following changes in agricultural management practices. Management practices related to tillage exerted stronger effects on soil food web functioning than those related to the export of crop residues or reduction in mineral N fertiliser. For instance, reduced tillage lead to more complex food webs, with incr

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different biochemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2O production potential. High concentrations of these components are associated with immature residues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N2O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local climatic and soil conditions as well as land use and management. More targeted mitigation efforts for N2O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2O emission factors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N2O emissions.

Multi-model ensembles are becoming increasingly accepted for the estimation of agricultural carbon-nitrogen fluxes, productivity and sustainability. There is mounting evidence that with some site-specific observations available for model calibration (with vegetation data as a minimum requirement), median outputs assimilated from biogeochemical models (multi-model medians) provide more accurate simulations than individual models. Here, we evaluate potential deficiencies in how model ensembles represent (in relation to climatic factors) the processes underlying biogeochemical outputs in complex agricultural systems such as grassland and crop rotations including fallow periods. We do that by exploring the correlation of model residuals. We restricted the distinction between partial and full calibration to the two most relevant calibration stages, i.e. with plant data only (partial) and with a combination of plant, soil physical and biogeochemical data (full). It introduces and evaluates the trade-off between (1) what is practical to apply for model users and beneficiaries, and (2) what constitutes best modelling practice. The lower correlations obtained overall with fully calibrated models highlight the centrality of the full calibration scenario for identifying areas of model structures that require further development.

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different bio-chemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2O production po-tential. High concentrations of these components are associated with immature resi-dues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N2O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local cli-matic and soil conditions as well as land use and management. More targeted mitiga-tion efforts for N2O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2O emission fac-tors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N2O emissions.

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different bio-chemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2O production po-tential. High concentrations of these components are associated with immature resi-dues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N2O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local cli-matic and soil conditions as well as land use and management. More targeted mitiga-tion efforts for N2O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2O emission fac-tors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N2O emissions.

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different bio-chemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2O production po-tential. High concentrations of these components are associated with immature resi-dues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N2O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local cli-matic and soil conditions as well as land use and management. More targeted mitiga-tion efforts for N2O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2O emission fac-tors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N2O emissions.

We have read with interest an opinion paper recently published in the European Journal of Soil Science (Berthelin et al., 2022). This paper presents some interesting considerations, at least one of which is already well known to soil scientists working on soil organic carbon (SOC), that is, a large portion (80%–90%) of fresh carbon inputs to soil is subject to rapid mineralization. The short-term mineralization kinetics of organic inputs is well-known and accounted for in soil organic matter models. Thus, clearly, the long-term predictions based on these models do not overlook short-term mineralization. We point out that many agronomic practices can significantly contribute to SOC sequestration. If conducted responsibly whilst fully recognising the caveats, SOC sequestration can lead to a win-win situation where agriculture can both contribute to the mitigation of climate change and adapt to it, whilst at the same time delivering other co-benefits such as reduced soil erosion and enhanced biodiversity.

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. How- ever, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N2O). Previous meta- analyses have linked various biochemical properties of crop residues to N2O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N2Oemissions from specific residues. Here we combine comprehensive databases for N2O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N2O emissions. On average, crop residue incorporation increased soil N2O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N2O emissions. Crop residue effects on N2O emissions were best pre- dicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N2Oemissions differed widely in terms offormand direction. However, due to the strong correlations among these properties, wewere able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N2O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and lowC:N ratio) strongly stim- ulated N2O emissions, whereas mature residues with opposite characteristics had marginal effects on N2O. The most important crop types belonging to the immature residue group – cover crops, grasslands and vegetables – are important for the

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. How- ever, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N2O). Previous meta- analyses have linked various biochemical properties of crop residues to N2O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N2Oemissions from specific residues. Here we combine comprehensive databases for N2O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N2O emissions. On average, crop residue incorporation increased soil N2O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N2O emissions. Crop residue effects on N2O emissions were best pre- dicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N2Oemissions differed widely in terms offormand direction. However, due to the strong correlations among these properties, wewere able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N2O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and lowC:N ratio) strongly stim- ulated N2O emissions, whereas mature residues with opposite characteristics had marginal effects on N2O. The most important crop types belonging to the immature residue group – cover crops, grasslands and vegetables – are important for the

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. How- ever, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N2O). Previous meta- analyses have linked various biochemical properties of crop residues to N2O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N2Oemissions from specific residues. Here we combine comprehensive databases for N2O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N2O emissions. On average, crop residue incorporation increased soil N2O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N2O emissions. Crop residue effects on N2O emissions were best pre- dicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N2Oemissions differed widely in terms offormand direction. However, due to the strong correlations among these properties, wewere able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N2O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and lowC:N ratio) strongly stim- ulated N2O emissions, whereas mature residues with opposite characteristics had marginal effects on N2O. The most important crop types belonging to the immature residue group – cover crops, grasslands and vegetables – are important for the

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. How- ever, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N2O). Previous meta- analyses have linked various biochemical properties of crop residues to N2O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N2Oemissions from specific residues. Here we combine comprehensive databases for N2O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N2O emissions. On average, crop residue incorporation increased soil N2O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N2O emissions. Crop residue effects on N2O emissions were best pre- dicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N2Oemissions differed widely in terms offormand direction. However, due to the strong correlations among these properties, wewere able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N2O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and lowC:N ratio) strongly stim- ulated N2O emissions, whereas mature residues with opposite characteristics had marginal effects on N2O. The most important crop types belonging to the immature residue group – cover crops, grasslands and vegetables – are important for the

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. How- ever, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N2O). Previous meta- analyses have linked various biochemical properties of crop residues to N2O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N2Oemissions from specific residues. Here we combine comprehensive databases for N2O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N2O emissions. On average, crop residue incorporation increased soil N2O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N2O emissions. Crop residue effects on N2O emissions were best pre- dicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N2Oemissions differed widely in terms offormand direction. However, due to the strong correlations among these properties, wewere able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N2O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and lowC:N ratio) strongly stim- ulated N2O emissions, whereas mature residues with opposite characteristics had marginal effects on N2O. The most important crop types belonging to the immature residue group – cover crops, grasslands and vegetables – are important for the

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. How- ever, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N2O). Previous meta- analyses have linked various biochemical properties of crop residues to N2O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N2Oemissions from specific residues. Here we combine comprehensive databases for N2O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N2O emissions. On average, crop residue incorporation increased soil N2O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N2O emissions. Crop residue effects on N2O emissions were best pre- dicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N2Oemissions differed widely in terms offormand direction. However, due to the strong correlations among these properties, wewere able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N2O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and lowC:N ratio) strongly stim- ulated N2O emissions, whereas mature residues with opposite characteristics had marginal effects on N2O. The most important crop types belonging to the immature residue group – cover crops, grasslands and vegetables – are important for the

We have read with interest an opinion paper recently published in the European Journal of Soil Science (Berthelin et al., 2022). This paper presents some interesting considerations, at least one of which is already well known to soil scientists working on soil organic carbon (SOC), that is, a large portion (80%–90%) of fresh carbon inputs to soil is subject to rapid mineralization. The short-term mineralization kinetics of organic inputs is well-known and accounted for in soil organic matter models. Thus, clearly, the long-term predictions based on these models do not overlook short-term mineralization. We point out that many agronomic practices can significantly contribute to SOC sequestration. If conducted responsibly whilst fully recognising the caveats, SOC sequestration can lead to a win-win situation where agriculture can both contribute to the mitigation of climate change and adapt to it, whilst at the same time delivering other co-benefits such as reduced soil erosion and enhanced biodiversity.

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. How- ever, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N2O). Previous meta- analyses have linked various biochemical properties of crop residues to N2O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N2Oemissions from specific residues. Here we combine comprehensive databases for N2O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N2O emissions. On average, crop residue incorporation increased soil N2O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N2O emissions. Crop residue effects on N2O emissions were best pre- dicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N2Oemissions differed widely in terms offormand direction. However, due to the strong correlations among these properties, wewere able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N2O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and lowC:N ratio) strongly stim- ulated N2O emissions, whereas mature residues with opposite characteristics had marginal effects on N2O. The most important crop types belonging to the immature residue group – cover crops, grasslands and vegetables – are important for the

L'incorporation des résidus de cultures et de couverts végétaux au sol est une pratique adoptée par les agriculteurs pour accroitre le stock de matières organiques des sols et recycler les nutriments. Mais la décomposition des résidus est une source d'émissions plus ou moins importante de gaz à effet de serre, comme le protoxyde d'azote (N2O). L'étude des caractéristiques des résidus enfouis au regard des pratiques culturales réalisées doit permettre de mieux gérer ces restitutions afin d'en limiter les conséquences sur l'environnement. Les émissions de N2O sont estimées dans les inventaires d'émissions selon la méthode IPCC (2019). Celle-ci est basée sur l'estimation des quantités d'azote recyclées par les résidus de culture (parties aériennes et souterraines) affectées d'un facteur d'émission (Ef) standard pour tous types de cultures, dont la valeur est 0.005 à 0.006 kg N-N2O par kg N recyclé, l'azote recyclé étant calculé à partir de la quantité de biomasse recyclée et de la richesse en azote de cette biomasse. Le travail présenté a été réalisé dans le cadre du projet ResidueGas (programme européen ERA-GAS) dont INRAE était partenaire. L'objectif global du projet était d'améliorer l'estimation de la contribution des résidus de cultures aux émissions de gaz à effet de serre de l'agriculture. Nous présentons trois résultats principaux de ce projet.

L'incorporation des résidus de cultures et de couverts végétaux au sol est une pratique adoptée par les agriculteurs pour accroitre le stock de matières organiques des sols et recycler les nutriments. Mais la décomposition des résidus est une source d'émissions plus ou moins importante de gaz à effet de serre, comme le protoxyde d'azote (N2O). L'étude des caractéristiques des résidus enfouis au regard des pratiques culturales réalisées doit permettre de mieux gérer ces restitutions afin d'en limiter les conséquences sur l'environnement. Les émissions de N2O sont estimées dans les inventaires d'émissions selon la méthode IPCC (2019). Celle-ci est basée sur l'estimation des quantités d'azote recyclées par les résidus de culture (parties aériennes et souterraines) affectées d'un facteur d'émission (Ef) standard pour tous types de cultures, dont la valeur est 0.005 à 0.006 kg N-N2O par kg N recyclé, l'azote recyclé étant calculé à partir de la quantité de biomasse recyclée et de la richesse en azote de cette biomasse. Le travail présenté a été réalisé dans le cadre du projet ResidueGas (programme européen ERA-GAS) dont INRAE était partenaire. L'objectif global du projet était d'améliorer l'estimation de la contribution des résidus de cultures aux émissions de gaz à effet de serre de l'agriculture. Nous présentons trois résultats principaux de ce projet.

This dataset presents the chemical characteristics of plant biomass and crop residues from agrosystems in European areas (carbon and nitrogen contents and biochemical composition). These data have been collected from the scientific literature. The specific data and their origins are presented. The mean values from these data are also provided by major production type (main crops, forage and pasture crops, green manure and cover crops, vegetable crops and energy crops), species and litter type. These data were collected as part of the framework of the European project ResidueGas (ERA-GAS, 2017-2021), which aims to improve the estimation of greenhouse gas emissions associated with crop residues.

L'incorporation des résidus de cultures et de couverts végétaux au sol est une pratique adoptée par les agriculteurs pour accroitre le stock de matières organiques des sols et recycler les nutriments. Mais la décomposition des résidus est une source d'émissions plus ou moins importante de gaz à effet de serre, comme le protoxyde d'azote (N2O). L'étude des caractéristiques des résidus enfouis au regard des pratiques culturales réalisées doit permettre de mieux gérer ces restitutions afin d'en limiter les conséquences sur l'environnement. Les émissions de N2O sont estimées dans les inventaires d'émissions selon la méthode IPCC (2019). Celle-ci est basée sur l'estimation des quantités d'azote recyclées par les résidus de culture (parties aériennes et souterraines) affectées d'un facteur d'émission (Ef) standard pour tous types de cultures, dont la valeur est 0.005 à 0.006 kg N-N2O par kg N recyclé, l'azote recyclé étant calculé à partir de la quantité de biomasse recyclée et de la richesse en azote de cette biomasse. Le travail présenté a été réalisé dans le cadre du projet ResidueGas (programme européen ERA-GAS) dont INRAE était partenaire. L'objectif global du projet était d'améliorer l'estimation de la contribution des résidus de cultures aux émissions de gaz à effet de serre de l'agriculture. Nous présentons trois résultats principaux de ce projet.

This dataset presents the chemical characteristics of plant biomass and crop residues from agrosystems in European areas (carbon and nitrogen contents and biochemical composition). These data have been collected from the scientific literature. The specific data and their origins are presented. The mean values from these data are also provided by major production type (main crops, forage and pasture crops, green manure and cover crops, vegetable crops and energy crops), species and litter type. These data were collected as part of the framework of the European project ResidueGas (ERA-GAS, 2017-2021), which aims to improve the estimation of greenhouse gas emissions associated with crop residues.

Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs - C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are avai

A potential strategy for mitigating nitrous oxide (N2O) emissions from permanent grasslands is the partial substitution of fertilizer nitrogen (Nfert) with symbiotically fixed nitrogen (Nsymb) from legumes. The input of Nsymb reduces the energy costs of producing fertilizer and provides a supply of nitrogen (N) for plants that is more synchronous to plant demand than occasional fertilizer applications. Legumes have been promoted as a potential N2O mitigation strategy for grasslands, but evidence to support their efficacy is limited, partly due to the difficulty in conducting experiments across the large range of potential combinations of legume proportions and fertilizer N inputs. These experimental constraints can be overcome by biogeochemical models that can vary legume-fertilizer combinations and subsequently aid the design of targeted experiments. Using two variants each of two biogeochemical models (APSIM and DayCent), we tested the N2O mitigation potential and productivity of full factorial combinations of legume proportions and fertilizer rates for five temperate grassland sites across the globe. Both models showed that replacing fertilizer with legumes reduced N2O emissions without reducing productivity across a broad range of legume-fertilizer combinations. Although the models were consistent with the relative changes of N2O emissions compared to the baseline scenario (200 kg N ha−1 yr−1; no legumes), they predicted different levels of absolute N2O emissions and thus also of absolute N2O emission reductions; both were greater in DayCent than in APSIM. We recommend confirming these results with experimental studies assessing the effect of clover proportions in the range 30–50% and ≤150 kg N ha−1 yr−1 input as these were identified as best-bet climate smart agricultural practices.

Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs - C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricult

Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs - C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are avai

This chapter examines payment for unmarketed agroecosystem services as a means to promote agricultural diversity as well as payment for agricultural diversity as a way to increase the supply of wanted unmarketed agroecosystem services. The importance of treating agricultural diversity as a multidimensional concept is emphasized, and several of its dimensions are identified. After assessing generally policies for paying farmers for the supply of unmarketed agroecosystem services, particular attention is given to payments for on-farm product diversity as a means of sustaining or increasing the supply of desired unmarketed agroecosystem services. The importance of this diversification being integrated to achieve this end is stressed. Economic theory (despite its limitations) is shown to be helpful in identifying issues that need to be addressed when considering policies for paying farmers for their supply of agroecosystem services, for example, the importance of distinguishing the allocative and income distribution effects of such policies. The analysis of these matters is facilitated by the introduction of a simple social cost-benefit inequality and a specific economic model. The importance of taking account of public administration costs and legal barriers and their efficiency aspects when assessing the costs and benefits of agricultural policies is stressed because these aspects are frequently overlooked. Other relevant aspects of agricultural diversity, such as regional diversity, are also briefly examined. An alternative to paying farmers for the supply of wanted agroecosystem services is to penalize them for not doing so. This is examined. The prospect of greater agricultural diversity resulting in the short term in reduced supply of agricultural products (and an increase in their real prices) but a more sustainable supply of these products in the long term is raised.

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N2O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N2O emissions. Yield-scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The pote

In the present work, we compare the effect of mature crop residues mixed into a ferralitic soil or placed as a single layer on soil surface on the mineralisation of C and N over 55days. As residues, we used dry stems of rice, soybean, sorghum, brachiaria and wheat. There were no significant effects of residue placement on C mineralisation kinetics. Decomposition of the residues on the soil surface slightly increased net N mineralisation for residues having the smallest C/N ratio

Carbon and N cycles are intimately associated during the residue decomposition process in soils. The overall N availability (residue + soil N) controls the rate of residue decomposition under N limiting conditions. Therefore studies have demonstrated low N availability reduced C mineralization rate on short term by reducing opportunist microbial biomass growth. However the effect of N availability on C mineralization and microbial biomass growth and composition on longer term, are still poorly understood. In the context of biofuel perennial plant production with Miscanthus, in which N amendments are limited, we investigated the effects of N availability on C and N dynamics, microbial dynamics and enzymatic functions on the short and long terms. Miscanthus leaves were incubated in an agricultural soil for > 500 days at two levels of soil N availability by adding inorganic N or not. C and N mineralization, microbial biomass C, ergosterol, xylanase and laccase activities and 18S-rRNA and 16S-rRNA were determined at several dates during the experiment. Results showed that a high N availability increased the rate of residue C mineralized in the short term (< 1 year) together with an increase in microbial C, fungal ergosterol, and enzymatic activities related to C degradation (xylanase). However, the high N availability suppressed laccase activity while it has no significant effect on 18S- and 16S r-RNA microbial communities. On longer term (> 1 year), high N availability slightly decreased C mineralization compared to low N treatment demonstrating the antagonist effect of N on residue decomposition. (Texte intégral)

Core principle of Conservation Agriculture is to maintain soil cover by crop residue mulching or cover crops. Mulching practice affects many agroecosystem services, through water dynamics and C and N transformations (Coppens et al., 2007) and their impact on climate change, water and nutrient cycling and soil biological activity. The objectives of this work were (i) to quantify the effects of biotic (diversity of mulches and soil types) and abiotic (climatic conditions) factors on soil functions such as C stabilization, C and N mineralization and transport, GHG emission, microbial dynamics and diversity; (ii) to assess by modeling how these factors affect agroecosystem services in a range of agricultural conditions met in conservation agriculture of France, Brazil and Madagascar. An experiment was performed in controlled conditions with soil columns. The treatments varied either by the type of residue mulch (Zea mais + Doliquos lablab or Triticum aestivum + Medicago sativa), or by the type of soil (sandy or loamy soil ) and by the water regime (manipulated through the intensity and frequency of rain applied to the soil columns). The Pastis_Mulch model (Findeling et al., 2007) tested on the measured data, was then used to simulate different scenarii, particularly different crop rotations and associations representative of the CA agrosystems (amount and quality of crop mulches), amount and distribution of rainfall (dry and wet years) and types of soil. The results allowed to rank the factors according to their positive and negative effects on the different ecosystem services involved. (Texte intégral)

We have modified a commercial DNA extraction kit for soil to simultaneously co-extract RNA. In this new procedure RNA and DNA are separated by two selective purifications in cascade without the need of DNAase or RNAse digestion. Consequently DNA and RNA are respectively purified from the whole co-extraction solution. Nucleic acids extraction is based on the action of SDS coupled with an efficient bead-beating step, but it does not require any solvent. Avoiding the use of solvents, which are damaging for human health and environmental quality, was one of our most important motivations to develop this protocol. In a second time, we have optimized this protocol to improve the DNA and RNA yield, but kipping those yields below the saturation limit of the kit to assess and quantify the variations of molecular biomass of the total (DNA) and the active (RNA) part of microbial communities in natural samples. We have also introduced a first step of homogenization of soil sample in liquid nitrogen to improve the reliability of the fungal 18S gene sequence quantification. Finally, we have shown that this protocol can be applied to a wide diversity of soils whatever their mineralogy and metal content (2 Ferralsols, 1 Vertisol, 2 Andosols from Madagascar), texture or biomass content (1 poor sandy soil from Congo and one carbon rich temperate soil sample submitted or not to a 1 month cold stress). * E Tournier, L. Amenc and AL. Pablo contributed equally to this study. (Texte intégral)

We have modified a commercial DNA extraction kit for soil to simultaneously co-extract RNA. In this new procedure RNA and DNA are separated by two selective purifications in cascade without the need of DNAase or RNAse digestion. Consequently DNA and RNA are respectively purified from the whole co-extraction solution. Nucleic acids extraction is based on the action of SDS coupled with an efficient bead-beating step, but it does not require any solvent. Avoiding the use of solvents, which are damaging for human health and environmental quality, was one of our most important motivations to develop this protocol. In a second time, we have optimized this protocol to improve the DNA and RNA yield, but kipping those yields below the saturation limit of the kit to assess and quantify the variations of molecular biomass of the total (DNA) and the active (RNA) part of microbial communities in natural samples. We have also introduced a first step of homogenization of soil sample in liquid nitrogen to improve the reliability of the fungal 18S gene sequence quantification. Finally, we have shown that this protocol can be applied to a wide diversity of soils whatever their mineralogy and metal content (2 Ferralsols, 1 Vertisol, 2 Andosols from Madagascar), texture or biomass content (1 poor sandy soil from Congo and one carbon rich temperate soil sample submitted or not to a 1 month cold stress). * E Tournier, L. Amenc and AL. Pablo contributed equally to this study. (Texte intégral)

Carbon and N cycles are intimately associated during the residue decomposition process in soils. The overall N availability (residue + soil N) controls the rate of residue decomposition under N limiting conditions. Therefore studies have demonstrated low N availability reduced C mineralization rate on short term by reducing opportunist microbial biomass growth. However the effect of N availability on C mineralization and microbial biomass growth and composition on longer term, are still poorly understood. In the context of biofuel perennial plant production with Miscanthus, in which N amendments are limited, we investigated the effects of N availability on C and N dynamics, microbial dynamics and enzymatic functions on the short and long terms. Miscanthus leaves were incubated in an agricultural soil for > 500 days at two levels of soil N availability by adding inorganic N or not. C and N mineralization, microbial biomass C, ergosterol, xylanase and laccase activities and 18S-rRNA and 16S-rRNA were determined at several dates during the experiment. Results showed that a high N availability increased the rate of residue C mineralized in the short term (< 1 year) together with an increase in microbial C, fungal ergosterol, and enzymatic activities related to C degradation (xylanase). However, the high N availability suppressed laccase activity while it has no significant effect on 18S- and 16S r-RNA microbial communities. On longer term (> 1 year), high N availability slightly decreased C mineralization compared to low N treatment demonstrating the antagonist effect of N on residue decomposition. (Texte intégral)

Core principle of Conservation Agriculture is to maintain soil cover by crop residue mulching or cover crops. Mulching practice affects many agroecosystem services, through water dynamics and C and N transformations (Coppens et al., 2007) and their impact on climate change, water and nutrient cycling and soil biological activity. The objectives of this work were (i) to quantify the effects of biotic (diversity of mulches and soil types) and abiotic (climatic conditions) factors on soil functions such as C stabilization, C and N mineralization and transport, GHG emission, microbial dynamics and diversity; (ii) to assess by modeling how these factors affect agroecosystem services in a range of agricultural conditions met in conservation agriculture of France, Brazil and Madagascar. An experiment was performed in controlled conditions with soil columns. The treatments varied either by the type of residue mulch (Zea mais + Doliquos lablab or Triticum aestivum + Medicago sativa), or by the type of soil (sandy or loamy soil ) and by the water regime (manipulated through the intensity and frequency of rain applied to the soil columns). The Pastis_Mulch model (Findeling et al., 2007) tested on the measured data, was then used to simulate different scenarii, particularly different crop rotations and associations representative of the CA agrosystems (amount and quality of crop mulches), amount and distribution of rainfall (dry and wet years) and types of soil. The results allowed to rank the factors according to their positive and negative effects on the different ecosystem services involved. (Texte intégral)

Models are useful tools to evaluate environmental impacts associated with nitrogen management in cropping systems and to predict them correctly. The purpose of this chapter was to analyze whether existing models satisfactorily simulate N losses in agroecosystems, require input data that are accessible, and can incorporate agricultural and climatic changes. The literature on 62 nitrogen models was reviewed. Each model was analyzed to identify the processes simulated, the equations used, the time and space scales, the input data and their degree of accessibility, and finally its performance. The review showed that a wide range of formalisms have been developed to model N processes. N losses such as nitrate leaching give better performance than N gas emissions, underlining the need to improve the understanding and modeling of denitrification and volatilization. It also revealed the narrow range of crop families parameterized and validated with field measurements. The main trend in modeling over the last 15 years has been the shift from mechanistic models to functional models, with a simplification of the equations involved and an aggregation of modules according to specific objectives. The more recent models have thus generally been based on specific contexts and cannot be directly extrapolated to other pedoclimatic and crop contexts, yet this is necessary for evaluating scenarios involving changes in land use and management or climatic uncertainties.

Models are useful tools to evaluate environmental impacts associated with nitrogen management in cropping systems and to predict them correctly. The purpose of this chapter was to analyze whether existing models satisfactorily simulate N losses in agroecosystems, require input data that are accessible, and can incorporate agricultural and climatic changes. The literature on 62 nitrogen models was reviewed. Each model was analyzed to identify the processes simulated, the equations used, the time and space scales, the input data and their degree of accessibility, and finally its performance. The review showed that a wide range of formalisms have been developed to model N processes. N losses such as nitrate leaching give better performance than N gas emissions, underlining the need to improve the understanding and modeling of denitrification and volatilization. It also revealed the narrow range of crop families parameterized and validated with field measurements. The main trend in modeling over the last 15 years has been the shift from mechanistic models to functional models, with a simplification of the equations involved and an aggregation of modules according to specific objectives. The more recent models have thus generally been based on specific contexts and cannot be directly extrapolated to other pedoclimatic and crop contexts, yet this is necessary for evaluating scenarios involving changes in land use and management or climatic uncertainties.

Models are useful tools to evaluate environmental impacts associated with nitrogen management in cropping systems and to predict them correctly. The purpose of this chapter was to analyze whether existing models satisfactorily simulate N losses in agroecosystems, require input data that are accessible, and can incorporate agricultural and climatic changes. The literature on 62 nitrogen models was reviewed. Each model was analyzed to identify the processes simulated, the equations used, the time and space scales, the input data and their degree of accessibility, and finally its performance. The review showed that a wide range of formalisms have been developed to model N processes. N losses such as nitrate leaching give better performance than N gas emissions, underlining the need to improve the understanding and modeling of denitrification and volatilization. It also revealed the narrow range of crop families parameterized and validated with field measurements. The main trend in modeling over the last 15 years has been the shift from mechanistic models to functional models, with a simplification of the equations involved and an aggregation of modules according to specific objectives. The more recent models have thus generally been based on specific contexts and cannot be directly extrapolated to other pedoclimatic and crop contexts, yet this is necessary for evaluating scenarios involving changes in land use and management or climatic uncertainties.

Models are useful tools to evaluate environmental impacts associated with nitrogen management in cropping systems and to predict them correctly. The purpose of this chapter was to analyze whether existing models satisfactorily simulate N losses in agroecosystems, require input data that are accessible, and can incorporate agricultural and climatic changes. The literature on 62 nitrogen models was reviewed. Each model was analyzed to identify the processes simulated, the equations used, the time and space scales, the input data and their degree of accessibility, and finally its performance. The review showed that a wide range of formalisms have been developed to model N processes. N losses such as nitrate leaching give better performance than N gas emissions, underlining the need to improve the understanding and modeling of denitrification and volatilization. It also revealed the narrow range of crop families parameterized and validated with field measurements. The main trend in modeling over the last 15 years has been the shift from mechanistic models to functional models, with a simplification of the equations involved and an aggregation of modules according to specific objectives. The more recent models have thus generally been based on specific contexts and cannot be directly extrapolated to other pedoclimatic and crop contexts, yet this is necessary for evaluating scenarios involving changes in land use and management or climatic uncertainties.

Reduced or no-tillage has been proved to be an effective strategy against soil erosion. Leaving a mulch at the soil surface minimises runoff and reduces changes in soil water content. Less is known about the implications of the change in crop residue localisation on carbon sequestration, nitrate leaching and the emission of greenhouse gasses, in relation to their biochemical quality. Laboratory studies were conducted to evaluate the interactions of crop residue localisation and quality on soil physical and biological properties. Soil columns with 13C15N-labelled rape or rye residues, left as mulch at the soil surface or incorporated homogeneously in the upper 10 cm, were incubated during 9 weeks at 20°C. They went through 3 dry-wet cycles, induced by the application of an artificial rain (2.5h at 12 mm/h), followed by a 3-week evaporation period (Recous et al., this conference). The soil and residue moisture contents, the soil matric potential, the composition of the soil solution at different depths in the soil columns and the evaporation rate were measured during the incubation. Carbon mineralisation and residue decomposition were determined by measuring the CO2-flux and the concentration of 13C-CO2 at the soil surface. At different depths, soil was analysed for total C and N (with their isotopic excess), soluble carbon, mineral nitrogen and microbial activity. The experimental data were used to validate the PASTIS-model (Garnier et al., 2003), a mechanistic and one-dimensional model of transport and biotransformations in soil, and to test a 'mulch'- module that was added to this model (Reyes Gomez, 2002). PASTIS allowed to simulate the soil water evaporation, CO2-fluxes, nitrate transport and the amounts of residual carbon in the soil during our incubation experiment. The C and N isotopes were measured and simulated to trace the residue-derived C and N in the soil. Modelling helped to identify and quantify the contribution of the various physical and biological p

Reduced or no-tillage has been proved to be an effective strategy against soil erosion. Leaving a mulch at the soil surface minimises runoff and reduces changes in soil water content. Less is known about the implications of the change in crop residue localisation on carbon sequestration, nitrate leaching and the emission of greenhouse gasses, in relation to their biochemical quality. Laboratory studies were conducted to evaluate the interactions of crop residue localisation and quality on soil physical and biological properties. Soil columns with 13C15N-labelled rape or rye residues, left as mulch at the soil surface or incorporated homogeneously in the upper 10 cm, were incubated during 9 weeks at 20°C. They went through 3 dry-wet cycles, induced by the application of an artificial rain (2.5h at 12 mm/h), followed by a 3-week evaporation period (Recous et al., this conference). The soil and residue moisture contents, the soil matric potential, the composition of the soil solution at different depths in the soil columns and the evaporation rate were measured during the incubation. Carbon mineralisation and residue decomposition were determined by measuring the CO2-flux and the concentration of 13C-CO2 at the soil surface. At different depths, soil was analysed for total C and N (with their isotopic excess), soluble carbon, mineral nitrogen and microbial activity. The experimental data were used to validate the PASTIS-model (Garnier et al., 2003), a mechanistic and one-dimensional model of transport and biotransformations in soil, and to test a 'mulch'- module that was added to this model (Reyes Gomez, 2002). PASTIS allowed to simulate the soil water evaporation, CO2-fluxes, nitrate transport and the amounts of residual carbon in the soil during our incubation experiment. The C and N isotopes were measured and simulated to trace the residue-derived C and N in the soil. Modelling helped to identify and quantify the contribution of the various physical and biological p

In the present work, we compare the effect of mature crop residues mixed into a ferralitic soil or placed as a single layer on soil surface on the mineralisation of C and N over 55days. As residues, we used dry stems of rice, soybean, sorghum, brachiaria and wheat. There were no significant effects of residue placement on C mineralisation kinetics. Decomposition of the residues on the soil surface slightly increased net N mineralisation for residues having the smallest C/N ratio