Search

This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland–atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (grassland management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites, equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can realistically capture the cut-induced seasonal variation in biometric variables (LAI: leaf area index; AGB: aboveground biomass) and in CO2 fluxes (GPP: gross primary productivity; TER: total ecosystem respiration; and NEE: net ecosystem exchange). However, improvements at grazing sites are only marginal in ORCHIDEE-GM due to the difficulty in accounting for continuous grazing disturbance and its induced complex animal–vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. For annual CO2 fluxes, the NEE bias and RMSE (root mean square error) in ORCHIDEE-GM are reduced by 53% and 20%, respectively, compared to ORCHIDEE. ORCHIDEE-GM is capable of modeling the net carbon balance (NBP) of managed temperate grasslands (37 ± 30 gC m−2 yr−1 (P < 0.01) over the 11 sites) because the management module contains provisions to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

DEUG; The grassland ecosystem mechanistic model PaSim (Pasture Simulation model) has been improved to better take into account the role of plant functional diversity by implementing 6 types of vegetation according to a typology of grasses in the cover. The integration of a functional grass typology in PaSim was evaluated on twelve European grasslands (sites) with gradients of pedoclimatic conditions and different management practices. The objectives of the stage were to: i) examine the 12 European grasslands on their functional grass typology (vegetation) using determination keys based on simple questionnaires and on the dominant species present in the cover; and ii) carry out a critical analysis concerning the performance of PaSim for different typologies, and more specifically on environmental variables sensitive to vegetation cover (e.g. photosynthesis, evapotranspiration, soil moisture). The hypothesis is that the simulations having been parameterized with a vegetation cover close to that of the plot, will give better results. The analysis showes that a parameterization with a single type of clam yields results less close to the observed values, than a plant cover composed of several functional types which varies during the year. This would be the best way to improve PaSim, if the typology could be improved for an application to geographical areas of the size of Europe. While waiting for the characterization of plant covers of a large area, the use of a default model that is calibrated at best (despite the fact that it can be improved), allows to obtain results closer to the values observed.; Le modèle mécaniste d’écosystème prairial, PaSim (Pasture Simulation Model), a été amélioré pour une meilleure prise en compte du rôle de la diversité fonctionnelle végétale en implémentant 6 types de végétation selon une typologie de prairies. L’intégration d’une typologie fonctionnelle de graminées dans le modèle PaSim a été évaluée sur douze sites prairiaux Européens couvrant des gradients pédoclimatiques et de gestion très différents. Les objectifs du stage ont été i) d’ examiner la typologie fonctionnelle sur leur typologie de la végétation (graminées) de 12 prairies européennes à l’aide de clefs de détermination basées sur des questionnaires simples et sur les espèces dominantes présentes ; et ii) réaliser une analyse critique concernant les performances du modèle de simulation Pasim paramétrer en fonction de différentes typologie, et utilisé pour estimer certains variables environnementales sensibles à la typologie des couverts végétaux (ex. photosynthèse, évapotranspiration, humidité du sol, etc.). L’hypothèse posée est que les modèles ayant été paramétrées avec un couvert végétal proche de celui de la parcelle, donnera de meilleurs résultats. Les analyses montrent qu’un paramétrage avec un seul type de prairie donne des résultats moins proches des valeurs observées qu’un couvert végétal composée de plusieurs types fonctionnels variant au cours de l’année. Ce serait la meilleure façon d’améliorer les simulations de PaSim, si la typologie pouvait être améliorés afin d’être appliqués à des zones géographiques de la taille de l’Europe. En attendent la caractérisation de couverts végétaux d’un large territoire, l’utilisation d’un modèle par défaut qui est calibré au mieux (malgré le fait qu’il soit améliorable), permet d’obtenir des résultats plus proches des valeurs observées.

Vul’Clim, une plateforme permettant d’investiguer les options d’adaptation et de mitigation à divers échelle. Application au modèle PaSim . Réseau prairies – Symposium 2017

A modelling approach for the thermal acclimation of plant photosynthesis and respiration is presented that accounts for changes in the maximum carbon (C) assimilation with changing growth temperature. It is motivated by one key observation, i.e. the optimum temperature for plant processes increases with increasing growth temperature, and two corollary expectations: (i) this determines a modification of the response curve of C assimilation, and (ii) plant C release (respiration) is also affected by changing growth temperature. Simple relations are proposed to model these phenomena, consistent with the Farquhar model of photosynthesis. The incorporation of temperature acclimation of plant photosynthesis and respiration into the Farquhar-based scheme of the Pasture Simulation model (PaSim; EMS: existing modelling solution, MMS: modified modelling solution) is proposed as a way to reduce the uncertainty in estimations of harvested or standing above ground biomass and C fluxes from grassland systems in Central France. Here we show that, across a flux tower grassland site spanning two alternative grazing regimes (Laqueuille, 45° 38′ N, 02° 44′ E, 1040 m a.s.l.), acclimation parameterizations improve model ability to reproduce observed ecosystem respiration (especially with extensive grazing, where root mean square error [RMSE] lowered from 15.20 to 11.59 g C m−2 week−1). An assessment at two grassland systems (Saint-Genes-Champanelle and Theix, 45° 43′ N, 03° 01′ E, 880 m a.s.l.) with alternative cutting regimes and climate conditions also showed some improvements in biomass estimates (e.g. with frequent cutting and experimental extreme summer event RMSE changed from 0.86 to 0.40 t DM ha−1). The consequences of acclimation for simulated grassland outputs depend on the conditions evaluated which requires further studies. However, our results suggest that grassland modelling omitting plant temperature acclimation is likely to overestimate C emissions, thus biasing projections of future C storage and estimates of policy-making indicators.

Predicting regional and global carbon (C) and water dynamics on grasslands has become of major interest, as grasslands are one of the most widespread vegetation types worldwide, providing a number of ecosystem services (such as forage production and C storage). The present study is a contribution to a regional-scale analysis of the C and water cycles on managed grasslands. The mechanistic biogeochemical model PaSim (Pasture Simulation model) was evaluated at 12 grassland sites in Europe. A new parameterization was obtained on a common set of eco-physiological parameters, which represented an improvement of previous parameterization schemes (essentially obtained via calibration at specific sites). We found that C and water fluxes estimated with the parameter set are in good agreement with observations. The model with the new parameters estimated that European grassland are a sink of C with 213?g?C?m-2?yr-1, which is close to the observed net ecosystem exchange (NEE) flux of the studied sites (185?g?C?m-2?yr-1 on average). The estimated yearly average gross primary productivity (GPP) and ecosystem respiration (RECO) for all of the study sites are 1220 and 1006?g?C?m-2?yr-1, respectively, in agreement with observed average GPP (1230?g?C?m-2?yr-1) and RECO (1046?g?C?m-2?yr-1). For both variables aggregated on a weekly basis, the root mean square error (RMSE) was ~5-16?g?C?week-1 across the study sites, while the goodness of fit (R2) was ~0.4-0.9. For evapotranspiration (ET), the average value of simulated ET (415?mm?yr-1) for all sites and years is close to the average value of the observed ET (451?mm?yr-1) by flux towers (on a weekly basis, RMSE~2-8?mm?week-1; R2?=?0.3-0.9). However, further model development is needed to better represent soil water dynamics under dry conditions and soil temperature in winter. A quantification of the uncertainties introduced by spatially generalized parameter values in C and water exchange estimates is also necessary. In addition, some uncertainties in the input management data call for the need to improve the quality of the observational system. A mechanistic biogeochemical pasture simulation model (PaSim) is improved by using a common set of eco-physiological parameters.PaSim was evaluated at 12 grassland sites in Europe, performing regional-scale analysis of carbon and water cycles.PaSim estimated that European grasslands are a carbon sink of 213?g?C?m-2?yr-1.PaSim overestimated the soil water content during dry periods.

National audience

Ce stage s’inscrit dans le cadre du dispositif CIRAD – INRA CARPAGG (CARbone des PAturages de Guyane et Gaz à effet de serres) et dans la continuité du projet EPAD (Efficience environnementale et Productions Animales pour le Développement Durable (ANR 2010-2014). Le dispositif CARPAGG vise à étudier les potentiels de stockage de carbone dans les sols des prairies pâturées issues de déforestation en Guyane dans le but d’établir des bilans carbone et des Gaz à Effet de Serre (GES) des systèmes herbagers. L’objectif d’EPAD était d’exploiter la diversité des systèmes d’élevages en vue d’explorer leurs efficiences dans le cadre de l’intensification écologique de l’élevage. Les études en cours sur les bilans carbone en exploitation d’élevage bovin font partie des apports de CARPAGG à l'Observatoire Guyanais du Carbone et des GES qui cofinance ce stage avec le CIRAD. Elles se réalisent en collaboration avec l’INRA UREP (Unité de Recherche sur l’Ecosystème Prairial) et l’UMR ECOFOG (ECOlogie des FOrêts de Guyane) et en lien avec l’Institut KaRibéen et Amazonien de l’Elevage (IKARE).

La réduction des émissions de gaz à effet de serre (GES) constitue un enjeu majeur dans la recherche agroenvironnementale. C’est dans ce but que l’INRA a développé un modèle de simulation, FarmSim , qui permet de simuler une exploitation agricole en agrégeant plusieurs autres modèles dont PaSim pour les prairies, et CERES pour les cultures. Les bilans en sortie de ces différents modèles sont ensuite agrégés afin d’avoir un bilan de GES au niveau de l’exploitation agricole. Cependant, du fait du traitement indépendant des composants de la ferme (prairies, cultures) par ces modèles, il était impossible de simuler des rotations prairies/cultures. J’ai ainsi dans un premier temps modifié FarmSim en vue de le rendre stable puis ai implémenté le mécanisme de rotations. Ceci fait, j’ai développé une plateforme afin de lancer des simulations spatialisées avec ce modèle. Mots-clés : gaz à effet de serre, FarmSim, PaSim, CERES, rotations, Reduction of greenhouse gases (GHG) emissions is at stake in the food-environmental research field. In order to act complementary, INRA scientists developed a simulation model, FarmSim which is able to simulate a complete farm by making use of other models: PaSim , for grasslands and CERES for crops. Outputs of all these nested models are then merged in order to produce the final result. However, because each of the farm components (grasslands, crops) was only processed by its corresponding model, it was impossible to simulate grasslands/croplands rotations . In a first time, I upgraded FarmSim to make it stable, then I implemented plots rotations. Once done, I developed a platform in order to launch large-scale simulations with this model.

Le présent travail a pour but de caractériser la variabilité du changement climatique et de ses effets sur les cultures fourragères selon les régions et les saisons. Récemment, plusieurs études sur ce thème, utilisant différents modèles et méthodes, ont été réalisées en France. Il s'agit donc de faire une synthèse de ces travaux qui, ayant utilisé des hypothèses de travail différentes, ont obtenu des résultats parfois différents. La multiplicité des méthodes a permis de montrer certains invariants dans le climat et les productions annuelles et saisonnières. L'avance printanière, l'existence de production hivernale et l'apparition ou l'accentuation du creux estival ont été mis en évidence - à des degrés divers - avec tous les modèles. La prévision d'une augmentation globale de production dans le futur proche fait également l'unanimité. Dans le futur, quelle que soit l'échéance, une augmentation est prévue principalement à cause des effets positifs du CO2, en particulier de la réduction de transpiration qu'il provoque. A long terme, les effets négatifs de la température et de l'augmentation de l'ETP risquent de dominer les effets positifs du CO2 et de provoquer une diminution globale de production : ce sont l'occurrence de cette diminution et son échéance qui font débat. Après analyse, l'augmentation de production dans le futur lointain, trouvée systématiquement avec un modèle d'une seule des deux études dont il est question ici, pourrait provenir de l'augmentation du rayonnement vue et utilisée dans cette étude, ainsi que d'une fertilisation beaucoup plus favorable., Recently, 4 simulation games using different models and methods were developed in France for characterizing climate change variability and its effect on forage crops, depending on the region and the season of year. A comparative analysis was used to determine global trends as well as possible causes of divergence. In the short term, results pointed to a global increase in production, and in the medium term, showed a spring advance, winter production, and a slump in the summer. In the longer term, a global decrease in production might be triggered by a high increase in temperature, the negative effect of lower rainfall, and the increase in ET, which the positive effect of higher CO2 levels may not manage to compensate. Certain factors (with regards to sunshine and fertilization) could explain these divergences between models.

The Pasture Simulation model (PaSim) was used to simulate agronomic and environmental services at 12 grassland sites in France, comparing near past climate conditions (1970–1999) and projections for near (2020–2049) and far future (2070–2099). Modelled climate change impacts were assessed using statistical and threshold-based analysis on managed (intensive, extensive) grasslands (permanent, sown), comparing shallow and deep soils, and for an ensemble of emission scenarios, climate models, and downscaling/initialization methods. Results show a significant drift of all sites towards more arid climates by the end of the century. Significant reductions in annual water drainage and herbage protein content are projected, together with new opportunities for annual and seasonal herbage production, in spring and winter especially. Simulated future conditions also show an increased interannual and seasonal variability of production. Contrary to expectations, current natural conditions reflecting large water availability are not expected to reduce future risks of negative climate change impacts on grassland systems. Notably, milk production from aftermath grazing of permanent grasslands established on deep soils at Mirecourt (humid site) is estimated to fall down below one-third of the current median value in four out of 30 years (∼13%) for 2070–2099, whereas similar shortfalls were not observed with the baseline climate. Balancing risks and opportunities, permanent extensive grasslands can be viewed as a trade-off between the continuity of grassland service provision and the mitigation of greenhouse gas emissions.

International audience; The Bayesian method for the calibration of complex models, applying Markov Chain Monte Carlo (MCMC) algorithm, was used to quantify the uncertainty associated with the parameterization of the Pasture Simulation Model (PaSim) for the evaluation of climate change impacts. A case study of applying the method to calibrate 2008 and 2009 model parameters in a mountain grassland in the Central Eastern Alps (Stubai, Austria, 47° 05′ North, 11° 11′ East) is presented to assess the effects of changes in climate conditions (with or without temperature extremes). In the case study, the prior distributions of the 17 most influential parameters used to estimate vegetation and soil variables were based on both literature and previous studies, and subsequently updated using the likelihood distributions resulting from site-specific measurements. The posterior uncertainty distribution of the model results was generated using Monte Carlo simulations with posterior parameter probability distributions. It was shown that using site-specific information to update the prior uncertainty distribution, the resulting uncertainty associated with the model results could be reduced. As an example, for the parameter „maximum specific leaf area‟, the coefficient of variation was reduced of about 99% compared to the prior probability. Posterior estimations of output variables were closer to observations, e.g. the RMSE of the leaf area index was reduced to about the half of that of prior distribution. Similar results were also obtained with other parameters and model outputs. These results indicate that, thanks to the incorporation of quantitative uncertainty analysis into grassland simulation, a better informed decision can be made with respect to climate change where specific impacts and issues of adaptation arise.

International audience; The large C stocks present in the subsoil could be an important factor in the feedback of SOM dynamics to climate change. Additionally, the subsoil has gained interest as potential hotspot for enhanced C sequestration as stabilized SOM. Therefore, subsoil SOM dynamics have become an important research topic. However, issues addressed remain scattered, and natural variability in structure and dynamics of subsoil SOM between soil types or ecosystems is often overlooked. The general focus of this session will be to increase our understanding of how properties and dynamics of subsoil SOM are affected by soil type, ecosystem and soil management. Specific issues of interest are: Spatial heterogeneity of the soil profile and its role in C sequestration and stabilisation in subsoil (e.g. flow paths for DOC and water , root channels, rhizosphere, input of fresh organic matter, aggregate structure, Submicron-scale, O2 availability, redox potential, pH…) Differences in residence time of SOM compounds between topsoil and subsoil horizons (e.g. Bulk soil organic matter vs compounds such as proteins, lignin, sugars…) and how are these differences related to soil type, management or ecosystem? Vulnerability of subsoil carbon to climate change (e.g CO2, temperature, drought effects) and to environmental change (e.g. N addition). Can we identify subsoil biophysical conditions that lead to vulnerable “hotspots”? Incorporation of subsoil C dynamics in SOM models: current approaches and knowledge gaps.

National audience; Une des attentes forte de la société et des décideurs politiques est de mieux comprendre et de pouvoir anticiper les réponses des agro-écosystèmes aux changements climatiques et atmosphériques anticipés. La prévision sur le long-terme de ces impacts sur la contribution des agro-écosystèmes à l’effet de serre et sur leur potentiel d’atténuation des émissions permis par le stockage de carbone dans la matière organique des sols repose nécessairement sur l’utilisation de modèles ; ce type d’outil permettant de confronter ses sorties (résultats) aux données observes ou mesurés dans des situations réelles, et d’en tirer des questionnements sur notre capacité à comprendre ou à prédire le système étudié.

National audience

The large C stocks present in the subsoil could be an important factor in the feedback of SOM dynamics to climate change. Additionally, the subsoil has gained interest as potential hotspot for enhanced C sequestration as stabilized SOM. Therefore, subsoil SOM dynamics have become an important research topic. However, issues addressed remain scattered, and natural variability in structure and dynamics of subsoil SOM between soil types or ecosystems is often overlooked. The general focus of this session will be to increase our understanding of how properties and dynamics of subsoil SOM are affected by soil type, ecosystem and soil management. Specific issues of interest are: Spatial heterogeneity of the soil profile and its role in C sequestration and stabilisation in subsoil (e.g. flow paths for DOC and water , root channels, rhizosphere, input of fresh organic matter, aggregate structure, Submicron-scale, O2 availability, redox potential, pH…) Differences in residence time of SOM compounds between topsoil and subsoil horizons (e.g. Bulk soil organic matter vs compounds such as proteins, lignin, sugars…) and how are these differences related to soil type, management or ecosystem? Vulnerability of subsoil carbon to climate change (e.g CO2, temperature, drought effects) and to environmental change (e.g. N addition). Can we identify subsoil biophysical conditions that lead to vulnerable “hotspots”? Incorporation of subsoil C dynamics in SOM models: current approaches and knowledge gaps.

National audience; Grassland/livestock systems differ in their wherewithal to enhance the magnitude of GHG fluxes (CO2, CH4, N2O) and their global warming potential (GWP). A simulation study was performed using the model PASIM to extrapolate potential emissions from grassland/livestock systems under alternative climate/soil/plant/management regimes at 12 French sites. Fluxes of CO2 associated with those of N2O indicate that both gases may be controlled by similar or concomitant environmental factors. In particular, CO2 and N2O fluxes were higher in the temporary grasslands, where grass management (mowing, N fertilization) promotes increased plant respiration and soil organic matter turnover. In these systems, high CO2 and N2O emissions were accompanied by absence of CH4 emissions. Similar responses were observed with intensive permanent grasslands, where the presence of grazing animals also determines CH4 emissions. High CH4, and low CO2 and N2O fluxes were generally estimated with extensive permanent pastures. While there are site-to-site and climate-to-climate variations, a general conclusion is that the GWP is expected to decrease in the future as result of increased soil dryness and C stocking. Also, temporary grasslands are indicated as the most desirable land use in reducing global warming. Strategies to enhance fertilizer use efficiency, animal feed and return of animal waste could be explored as adaptation/mitigation measures.

National audience; Given the recognized importance of grasslands to the global carbon budget, a simulation study was performed using the model PASIM to extrapolate potential impacts of altered climate regimes on grassland resources. An array of scenarios was sketched to be representative of climate/soil/plant/management interactions at 12 French sites. SRES climate change projections for near (2020-2049) and far (2070-2099) future were constructed using a range of climate models and settings which mark the limits of uncertainty associated with current climate modelling. PASIM was employed to generate a variety of outputs related to biomass productivity and C budget. Based on alternative scenarios, air temperature rise by ~1-4 °C to the end of 21st century, combined with increasing CO2 levels, translates into increased yields although generally accompanied by decreased precipitations. The latter is likely the main cause of the larger variability of yield observed from year to year under modified climate. A more complex response was observed for spatial and temporal variation of soil organic C. The risk of general driest conditions associated with climate change may not be reflected in yield and C losses due to concurrent effects of increased atmospheric CO2 concentrations, but calls for consideration of water resources depletion. Margins for adaptations can be explored in terms of crop management (e.g., effects of different cutting dates or grazing periods).

Une demande sociétale majeure concerne notre capacité à réaliser des bilans de gaz à effet de serre (GES) dans l’optique d’estimer la contribution au changement climatique des systèmes mais aussi d’anticiper leurs adaptations à ces derniers. C’est en partie pour répondre à cette demande que le modèle PASIM (Riedo et al., 1998) a été initialement développé. PASIM est un modèle biogéochimique qui simule le fonctionnement d’une parcelle de prairie en considérant les flux des principaux de GES (CO2, N2O, CH4).

Master; J'ai effectué mon stage de fin d'étude d'ingénieur ISIMA au sein de l'Institut National de la Recherche Agronomique (INRA), dans l'Unité de Recherche sur l'Ecosystème Prairial (UREP). Mon stage a été effectué en collaboration avec l'Institut de Radioprotection et de Sûreté Nucléaire (IRSN). J'ai été chargé d'ajouter la gestion du carbone 14 au sein de PaSim, modèle de simulation de prairie gérant déjà les flux de carbone et d'azote. Il m'a donc fallu faire la distinction, au sein du modèle, entre le carbone 12 et le carbone 14. Pour implémenter cela j'ai tout d'abord ajouté une fraction de carbone 14 pour ensuite raisonner en terme de quantité. Au final, un taux exprimé en Becquerels par kilo de carbone 14 fut la solution retenue. Pour faciliter l'utilisation de PaSim, et ainsi permettre à l'IRSN de le prendre en main plus rapidement, une interface graphique a été réalisée lors d'un projet d'élève ingénieur en troisième année à l'ISIMA. Durant mon stage j'ai aussi été en charge de la maintenance et de la mise à jour de cette interface.