Éditeur(s) : Université de la Rochelle
Résumé : In order to better understand the functioning of the Brouage intertidal mudflat (Marennes- Oléron Basin, France), its carbon-based trophic web has been modelled and analyzed. The foodweb building is based on the 4 step method of Inverse Analysis: 1) conceive an a priori model as the graph of compartments (nodes) between which exist fluxes of material (vertices). These vertices are the unknowns for the problem; 2) gather all the existing knowledge about the ecosystem and translate it into linear equations and inequalities involving the fluxes; 3) complete this set of data by common knowledge on the behaviour of the compartments and translate it into inequalities, 4) solve the obtained linear system under the parsimony principle to find a unique solution vector. The food-web analysis is based on. The first purpose of this work was a methodological one: inverse analysis method has been adapted to consider the seasonal and spatial variability of the temperate ecosystem: two seasons have been coupled in the computation and the area has been divided into three geographical zones along a cross-shore gradient. Hence, two types of physical exchanges are involved: the benthicpelagic ones and the advection ones. Statistical results can also be obtained by coupling Monte Carlo methods to Inverse Analysis. To study the obtained networks, new indices based on Markov Chains take delay into account in describing integrative transfers of material between compartments. This lets emerge the systems' properties that are not obvious at first sight and emphasizes the role of peculiar components. The second purpose was to apply such methods to the Brouage mudflat ecosystem in order to better understand its functioning. As the knowledge and methods evolve, various food webs were computed and analyzed with the help such indices and existing ones. Sensitivity analyses allow to point at the most crucial lacks of knowledge, which can orientate future field research. New data would improve the quality of the model in two ways: one the one hand, they would validate or invalidate the outcomes and on the other hand, they would give useful information to better constrain some of the black boxes and most uncertain fluxes, especially the advection and vertical flows. The main results of the study show a strongly seasonal system in which benthic and pelagic components are linked with intensity. The system is driven by its high local benthic primary production, but also depends on imports from the basin. Each of the 3 geographic zones has a peculiar functioning. The central zone corresponds to the classical description of European intertidal mudflats: very productive, it can feed the other regions. It is a production zone. The upper part is less productive but is fed by the middle one via the water column and can be exploited by shorebirds. It is a degradation zone (material is transformed for less qualitative). The lower part strongly depends on the basin imports for its functioning, as the cultivated bivalves act as a pump for pelagic material of which a great part is deposited under the cultivation structures (oyster racks or mussels "bouchots"). It is a transformation zone.
Un double objectif (méthodologique et appliqué) a été visé par une modélisation du réseau trophique de la vasière de Brouage (Bassin de Marennes Oléron, France) à l'aide de l'analyse inverse, et son étude à l'aide de l'analyse des réseaux. L'Analyse Inverse permet en effet de reconstruire l'ensemble du réseau à partir de données éparses, le problème du manque de données étant récurrent en Ecologie. Au plan méthodologique, l'analyse inverse a été adaptée à la prise en compte des caractères saisonnier et spatialement hétérogène d'un écosystème tempéré de zone intertidale : deux saisons ont ainsi été couplées et la vasière a été considérée le long d'un transect perpendiculaire au rivage et divisé en trois zones spatiales. Deux types de flux physiques interviennent donc : les flux verticaux de dépôt et remise en suspension, et les flux d'advection via la colonne d'eau. Des pistes d'amélioration et de nouvelles méthodes sont proposées. Un résultat sous forme statistique peut être obtenu en couplant l'utilisation de méthodes de Monte Carlo à l'analyse inverse pour la construction des réseaux trophiques. Les moyens d'étude des modèles ont été enrichis par la mise au point d'indices issus de la construction de chaînes de Markov et prenant en compte le caractère temporel des transferts de matière entre compartiments. Enfin, la transformation mathématique du modèle statique pour une étude dynamique de la stabilité de l'équilibre décrit est abordée. Plusieurs modèles ont été construits au cours de l'évolution des méthodes et de l'acquisition de connaissances sur le site. Des méthodes d'analyses existantes et d'autres mises au point dans le cadre de cet ouvrage ont été appliquées aux réseaux obtenus afin de faire émerger les propriétés du fonctionnement de la vasière et de souligner le rôle de certains compartiments. Des analyses de sensibilité permettent d'évaluer la robustesse des résultats et d'orienter les recherches futures en mettant en évidence les manques les plus cruciaux. Des données supplémentaires, notamment concernant les foraminifères benthiques, le zooplancton ou les mouvements verticaux du microphytobenthos permettront de fournir de meilleures contraintes et de valider (ou non) les résultats obtenus. Les principaux résultats montrent un système au fort caractère saisonnier dont les compartiments benthiques et pélagiques sont très liés. La production primaire benthique locale est un moteur important, mais qui ne suffirait pas à suppléer l'indispensable importation de matériel détritique. Le découpage de la vasière en trois zones fait apparaître les particularités de chacune. La zone centrale correspond à la description classique des « vasières intertidales européennes » : très productive, elle peut alimenter les autres régions. C'est une zone de production et d'exportation. La partie supérieure est moins productive et reçoit de la matière de la zone de milieu d'estran via la colonne d'eau. Sa production secondaire peut alors être exploitée par les limicoles, nombreux en hiver. C'est une zone de dégradation et d'exportation. Le bas d'estran dépend fortement des importations extérieures, « pompées » par les bivalves cultivés qui sont ainsi directement responsables d'une forte sédimentation sous les structures mytilicoles et ostréicoles. C'est une zone de transformation.

Droits : info:eu-repo/semantics/openAccess
http://archimer.ifremer.fr/doc/2005/these-2260.pdf
http://archimer.ifremer.fr/doc/00000/2260/

Éditeur(s) : HAL CCSD INRIA
Résumé : International audience
Computational probabilistic modeling and Bayesian inference has met a great success over the past fifteen years through the development of Monte Carlo methods and the ever increasing performance of computers. Through methods such as Monte Carlo Markov chain and sequential Monte Carlo Bayesian inference effectively combines with Markovian modelling. This approach has been very successful in ecology and agronomy. We analyze the development of this approach applied to a few examples of natural resources management.
La modélisation probabiliste et l'inférence bayésienne computationnelles rencontrent un très grand succès depuis une quinzaine d'années grâce au développement des méthodes de Monte Carlo et aux performances toujours croissantes des moyens de calcul. Au travers d'outils comme les méthodes de Monte Carlo par chaîne de Markov et les méthodes de Monte Carlo séquentielles, l'inférence bayésienne se combine efficacement à la modélisation markovienne. Cette approche est également très répendue dans le domaine de l'écologie et l'agronomie. Nous faisons le point sur les développements de cette approche appliquée à quelques exemples de gestion de ressources naturelles.
ARIMA

inria-00506383
https://hal.inria.fr/inria-00506383
https://hal.inria.fr/inria-00506383/document

Éditeur(s) : HAL CCSD
Résumé : International audience
Semi-volatile organic compounds (SVOCs) partition indoors between the gas phase, airborne particles, settled dust, and other surfaces. Unknown concentrations of SVOCs in the gas phase (Cg) can be predicted from their measured concentrations in airborne particles. In previous studies, the prediction of Cg depended largely on choosing a specific equation for the calculation of the particle/gas partition coefficient. Moreover, the prediction of Cg is frequently performed at a reference temperature rather than the real indoor temperature. In this paper, a probabilistic approach based on Monte Carlo simulation was developed to predict the distribution of SVOCs' Cg from their concentrations in airborne particles at the target indoor temperature. Moreover, the distribution of the particle/gas partition coefficient of each SVOC at the target temperature was used. The approach was validated using two measured datasets in the literature: the predicted Cg from concentrations measured in airborne particles and the measured Cg were generally of the same order of magnitude. The distributions of the Cg of 66 SVOCs in the French housing stock were then predicted. The SVOCs with the highest median Cg, ranging from 1 ng/m3 to > 100 ng/m3, included 8 phthalates (DEP, DiBP, DBP, DEHP, BBP, DMP, DiNP, and DMEP), 4 polycyclic aromatic hydrocarbons (fluorene, phenanthrene, fluoranthene, and anthracene), 2 alkylphenols (4-tert-butylphenol and 4-tert-octylphenol), 2 synthetic musks (galaxolide and tonalide), tributyl phosphate, and heptachlor. The nationwide, representative, predicted Cg values of SVOCs are frequently of the same order of magnitude in Europe and North America, whereas these Cg values in Chinese and Indian dwellings and the Cg of polybrominated diphenyl ethers in U.S. dwellings are generally higher. © 2016 Elsevier B.V.
Science of the Total Environment

hal-01467547
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01467547
DOI : 10.1016/j.scitotenv.2016.10.074
PUBMED : 27788447

Éditeur(s) : HAL CCSD
Résumé : International audience
In many situations it is important to be able to propose N independent real- izations of a given distribution law. We propose a strategy for making N parallel Monte Carlo Markov Chains (MCMC) interact in order to get an approximation of an indepen- dent N-sample of a given target law. In this method each individual chain proposes can- didates for all other chains. We prove that the set of interacting chains is itself a MCMC method for the product of N target measures. Compared to independent parallel chains this method is more time consuming, but we show through examples that it possesses many advantages. This approach is applied to a biomass evolution model.
International Conference on Applied Statistics for Development in Africa Sada'07
Cotonou, Benin

inria-00506398
https://hal.inria.fr/inria-00506398
https://hal.inria.fr/inria-00506398/document
https://hal.inria.fr/inria-00506398/file/campillo2007b.pdf

Éditeur(s) : HAL CCSD INRIA
Résumé : International audience
Markov chain Monte Carlo (MCMC) methods together with hidden Markov models are extensively used in the Bayesian inference for many scientific fields like environment and ecology. Through simulated examples we show that the speed of convergence of these methods can be very low. In order to improve the convergence properties, we propose a method to make parallel chains interact. We apply this method to a biomass evolution model for fisheries.
Les méthodes de Monte Carlo par chaînes de Markov (MCMC) couplées à des modèles de Markov cachés sont utilisées dans de nombreux domaines, notamment en environnement et en écologie. Sur des exemples simples, nous montrons que la vitesse de convergence de ces méthodes peut être très faible. Nous proposons de mettre en interaction plusieurs algorithmes MCMC pour accélérer cette convergence. Nous appliquons ces méthodes à un modèle d'évolution de la biomasse d'une pêcherie.
ISSN: 1638-5713

inria-00506386
https://hal.inria.fr/inria-00506386
https://hal.inria.fr/inria-00506386/document
https://hal.inria.fr/inria-00506386/file/campillo2008d.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
Bayesian modelling is fluently employed to assess natural ressources. It is associated with Monte Carlo Markov Chains (MCMC) to get an approximation of the distribution law of interest. Hence in such situations it is important to be able to propose N independent realiza- tions of this distribution law. We propose a strategy for making N parallel Monte Carlo Markov Chains interact in order to get an approximation of an independent N -sample of a given target law. In this method each individual chain proposes candidates for all other chains. We prove that the set of interacting chains is itself a MCMC method for the product of N target measures. Compared to independent parallel chains this method is more time consuming, but we show through example that it possesses many advantages. This approach will be applied to a forest dynamic model.
International Conference on Approximation Methods and Numerical Modelling in Environment and Natural Resources
Granada, Spain

inria-00506591
https://hal.inria.fr/inria-00506591
https://hal.inria.fr/inria-00506591/document
https://hal.inria.fr/inria-00506591/file/campillo2007c.pdf

Éditeur(s) : HAL CCSD Elsevier
Résumé : Analyses of tree diversity and community composition in tropical rain forests are usually based either on general herbarium data or on a restricted number of botanical plots. Despite their high taxonomic accuracy, both types of data are difficult to extrapolate to landscape scales. Meanwhile, forestry surveys provide quantitative occurrence data on large areas, and are thus increasingly used for landscape-scale analyses of tree diversity. However, the reliability of these approaches has been challenged because of the ambiguity of the common (vernacular) names used by foresters and the complexity of tree taxonomy in those hyper-diverse communities.We developed and tested a novel approach to evaluate taxonomic reliability of forestry surveys and to propagate the resulting uncertainty in the estimates of several diversity indicators (alpha and beta entropy, Fisher-alpha and Sørensen similarity). Our approach is based on Monte-Carlo processes that simulate communities by taking into account the expected accuracy and reliability of common names. We tested this method in French Guiana, on 9 one-hectare plots (4279 trees – DBH ⩾ 10 cm) for which both common names and standardized taxonomic determinations were available. We then applied our method of community simulation on large forestry inventories (560 ha) at the landscape scale and compared the diversity indices obtained for 10 sites with those computed from precise botanical determination situated at the same localities.We found that taxonomic reliability of forestry inventories varied from 22% (species level) to 83% (family level) in this Amazonian region. Indices computed directly with raw forestry data resulted in incorrect values, except for Gini–Simpson beta-diversity. On the contrary, our correction method provides more accurate diversity estimates, highly correlated with botanical measurements, for almost all diversity indices at both regional and local scales. We obtained a robust ranking of sites consistent with those shown by botanical inventories.These results show that (i) forestry inventories represent a significant part of taxonomic information, (ii) the relative diversity of regional sites can be successfully ranked using forestry inventory data using our method and (iii) forestry inventories can valuably contribute to the detection of large-scale diversity patterns when biases are well-controlled and corrected.The tools we developed as R-functions are available in supplementary material and can be adapted with local parameters to be used for forest management and conservation issues in other regional contexts
ISSN: 0378-1127

hal-01204219
https://hal.archives-ouvertes.fr/hal-01204219
DOI : 10.1016/j.foreco.2014.05.045
PRODINRA : 286554

Éditeur(s) : HAL CCSD
Résumé : For ecology scientists, spatial statistics are a set of tools allowing characterization of the structure of a point set, for instance a map of trees in a forest plot. This structure is defined implicitly as a departure from complete spatial randomness (CSR), the result of a Poisson point process. Inhomogeneity of the process and non-independence of points are its causes. As they cannot be disentangled by analyzing the data, so-called "spatial concentration" or "aggregation" (evenness due to repulsion also exists but is actually rare) usually concerns non-independence while intensity is assumed as known. The literature of point processes and measures of spatial structures is reviewed to clarify concepts and choices. The purpose of this thesis was to produce methodological enhancements. Its main results are: * A test for the most used statistic, Ripley's K function, against the null hypothesis of CSR. It can replace Monte-Carlo simulations used until now in the literature. * An extension of K to inhomogeneous processes, within a typology of available statistics (absolute, relative and topographic measures). When data is available as number of objects per zones (say a number of tree in each forest plot) rather than their exact position, information theory is used to define a general framework allowing to characterize spatial structure (of species) and diversity (of plots) as two aspects of a single measure of inequality. This framework is applied to Shannon's index of biodiversity to derive a self-sufficient definition of beta diversity, its calculation independently from the difference between gamma and alpha diversity, and a statistical test of significance against the null hypothesis that plots are samples of the same community. The way is paved for other applications to measures of diversity and spatial structures. As a conclusion, it appears clear that pattern characterization tools are a first step to deal with ecological questionings. Their development is still a matter of research. Yet, they are far from sufficient to address ecological processes as point processes ignore the temporal aspect of object locations.
Les statistiques spatiales sont pour les écologues un ensemble d'outils permettant de caractériser la structure d'un semis de points, par exemple une carte représentant des emplacements des arbres dans une parcelle de forêt. Cette structure est définie implicitement comme un écart à semis complètement aléatoire, résultat d'un processus de Poisson. L'hétérogénéité du processus ponctuel dont le semis de points est une réalisation et la non-indépendance des points en sont les causes indiscernables, ce qui amène généralement à supposer l'intensité du processus connu et nommer " concentration spatiale " ou " agrégation " (la régularité spatiale est possible, mais rare en pratique) la non-indépendance. Une revue de la littérature des processus ponctuels et des mesures de structures spatiales est fournie pour clarifier les concepts et les choix. L'objectif de ce travail de thèse était de produire des améliorations méthodologiques. Ses résultats principaux sont : * L'établissement d'un test pour la principale statistique utilisée, la fonction K de Ripley, permettant de s'affranchir de la méthode de Monte-Carlo utilisée dans la littérature pour rejeter l'hypothèse nulle d'un processus complètement aléatoire. * L'extension de K aux processus hétérogènes, dans le cadre d'une typologie claire des statistiques (absolues, relatives, topographiques). Lorsque la position exacte des objets n'est pas connue, mais que des effectifs par zone sont disponibles (par exemple des nombres d'arbres par parcelle), la théorie de l'information est utilisée pour définir un cadre général permettant de caractériser la structure spatiale (des espèces dans les parcelles) et la diversité (des parcelles, en termes d'espèces) comme deux aspects d'une même mesure d'inégalité. Ce cadre est appliqué à l'indice de biodiversité de Shannon pour définir clairement la mesure de diversité bêta, son calcul direct indépendamment de la différence entre diversités gamma et alpha, et fournir un test statistique de non nullité. La voie est ouverte pour l'application à d'autres mesures de diversité et de structure spatiale. En conclusion, il semble clair que ces outils de caractérisation sont un premier pas pour traiter les questions écologiques, leur développement étant toujours du domaine de la recherche. Ils sont cependant très insuffisants pour répondre à des questions liées aux processus écologiques, assez éloignés des processus ponctuels qui ignorent l'aspect temporel de l'installation des objets.
https://pastel.archives-ouvertes.fr/pastel-00540327

NNT : 2010AGPT0075
pastel-00540327
https://pastel.archives-ouvertes.fr/pastel-00540327
https://pastel.archives-ouvertes.fr/pastel-00540327/document
https://pastel.archives-ouvertes.fr/pastel-00540327/file/13_Marcon2010.pdf

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
Random walk (RW) or Continuous Time Random Walk (CTRW) are recurring Monte Carlo methods used to model convective and diffusive transport in complex heterogeneous media. Many applications can be found, including fluid mechanic, hydrology, and chemical reactors modeling. These methods are easy to implement, very versatile and flexible enough to become appealing for many applications because they generally overlook of deeply simplify the building of explicit complex meshes required by deterministic methods. RW and CTRW provide a good physical understanding of the interactions between the space scales of het-erogeneities and the transport phenomena under consideration. In addition, they can result in efficient up-scaling methods, especially in context of flow and transport in fractured media. In the present study, we review the applications of RW or CTRW for several situations coping with various spatial scales, and different insights into up-scaling applications. RW and CTRW advantages and downsides are also discussed, thus providing a few avenues for further works and applications.
ISSN: 0169-3913

hal-01449131
https://hal.archives-ouvertes.fr/hal-01449131
https://hal.archives-ouvertes.fr/hal-01449131/document
https://hal.archives-ouvertes.fr/hal-01449131/file/0025972-02.pdf
DOI : 10.1007/s11242-016-0693-z

Éditeur(s) : HAL CCSD American Chemical Society
Résumé : Absolute Mα and Mβ X-ray intensities were measured for the elements Pt, Au, Pb, U, and Th by electron impact for energies ranging from 6 to 38 keV. Experimental data were obtained by measuring the X-ray intensity emitted from bulk samples with an electron microprobe using high-resolution wavelength-dispersive spectrometers. Recorded X-ray intensities were converted into absolute X-ray yields by evaluation of the detector efficiency and then compared with X-ray intensities calculated by means of Monte Carlo simulations. Simulated Mα and Mβ X-ray intensities were found to be in good agreement with the measurements, allowing their use in standardless quantification methods. A procedure and a software program were developed to accurately obtain virtual standard values. Standardless quantifications of Pb and U were tested on standards of PbS, PbTe, PbCl2, vanadinite, and UO2.
ISSN: 0003-2700

hal-01217495
https://hal.archives-ouvertes.fr/hal-01217495
DOI : 10.1021/acs.analchem.5b01443

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
Random walk (RW) methods are recurring Monte Carlo methods used to modelconvective and diffusive transport in complex heterogeneous media. Many applications canbe found, including fluid mechanic, hydrology and chemical reactors modeling. These methodsare easy to implement, very versatile and flexible enough to become appealing for manyapplications because they generally overlook or deeply simplify the building of explicit complexmeshes required by deterministic methods. RWprovides a good physical understandingof the interactions between the space scales of heterogeneities and the transport phenomenaunder consideration. In addition, they can result in efficient upscaling methods, especiallyin the context of flow and transport in fractured media. In the present study, we review theapplications of RW to several situations that cope with diverse spatial scales and differentinsights into upscaling problems. The advantages and downsides of RW are also discussed,thus providing a few avenues for further works and applications.
ISSN: 0169-3913

insu-01308060
https://hal-insu.archives-ouvertes.fr/insu-01308060
DOI : 10.1007/s11242-016-0693-z

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
To evaluate the performance of downhole and surface geophysical monitoring methods, a series of shallow gas injection-monitoring experiments has been performed in a coastal saline aquifer at Maguelone, France. The recorded data include pressure measurements with a Westbay multilevel completion and CO2 saturation at an observation well derived from electrical resistivity with a modified Waxman-Smits (MWS) model. In this work, the aim is to develop a simulation model capturing the gas transport behavior and consistent with field data. For this purpose, the simulation of the CO2 injection experiment is carried out with two conceptual models, a homogeneous model and a heterogeneous model treated with multiple realization Monte Carlo simulations. Numerical simulator TOUGH2 with the equation of state module EOS7C is used for the simulations. Comparison of the model results with field data suggests that the pressure responses are captured with relatively good accuracy. Similarly, the model also provides an overall reasonable agreement and correct order of magnitude for predicted gas saturation values. However, as the heterogeneity pattern in the field data remains largely unknown, the model predictions can only be used to capture the mean behavior as well as to provide insights into how heterogeneity can influence the system behavior, by means of sensitivity analyses of the influence of heterogeneities on individual realizations.
ISSN: 1750-5836

hal-01467240
https://hal.archives-ouvertes.fr/hal-01467240
DOI : 10.1016/j.ijggc.2016.09.006