Life-history phenology strongly influences population vulnerability to toxicants: a case study with the mudsnail Potamopyrgus antipodarum.

International audienceOne of the main objectives of ecological risk assessment is to evaluate the effects of toxicants on ecologically relevant biological systems such as populations or communities. However, the effects of toxicants are commonly measured on selected subindividual or individual endpoints due to their specificity against chemical stressors. Introducing these effects into population models is a promising way to predict impacts on populations. The models currently employed are very simplistic, and their environmental relevance needs to be improved to establish the ecological relevance of hazard assessment. The present study with the gastropod Potamopyrgus antipodarum combines a field experimental approach with a modeling framework. It clarifies the role played by seasonal variability of life-history traits in the population's vulnerability to the alteration of individual performance, potentially due to toxic stress. The present study comprised 3 steps: 1) characterization of the seasonal variability in life-history traits of a local population over 1 yr by using in situ experiments on caged snails, coupled with a demographic follow-up; 2) development of a periodic matrix population model that visualizes the monthly variability of population dynamics; and 3) simulation of the demographic consequences of an alteration in life-history traits (i.e., fertility, juvenile, and adult survival). The results revealed that demographic impacts strongly depend on the season when alterations of individual performance occur. Model analysis showed that this seasonal variability in population vulnerability is strongly related to the phenology of the population. The authors emphasize that improving the realism of population models is a major objective for ecological risk assessment, and that taking into account species phenology in modeling approaches should be a priority

Optimisation of the variational method for vibrational Hamiltonian eigenvalues computation

International audienceWe propose here an efficient method to define a representative approximation subspace to compute the first eigenvalues of the vibrational Hamiltonian which are those of interest in the experimental results

Adaptive vibrational configuration interaction (A-VCI): a posteriori error estimation to efficiently compute anharmonic IR spectra

International audienceA new variational algorithm called adaptive vibrational configuration interaction (A-VCI) intended for the resolution of the vibrational Schrödinger equation was developed. The main advantage of this approach is to efficiently reduce the dimension of the active space generated into the configuration interaction (CI) process. Here, we assume that the Hamiltonian writes as a sum of products of operators. This adaptive algorithm was developed with the use of three correlated conditions i.e. a suitable starting space ; a criterion for convergence, and a procedure to expand the approximate space. The velocity of the algorithm was increased with the use of a posteriori error estimator (residue) to select the most relevant direction to increase the space. Two examples have been selected for benchmark. In the case of H 2 CO, we mainly study the performance of A-VCI algorithm: comparison with the variation-perturbation method, choice of the initial space, residual contributions. For CH 3 CN, we compare the A-VCI results with a computed reference spectrum using the same potential energy surface and for an active space reduced by about 90 %

Efficient basis selection for the computation of vibrational spectrum

International audienceWe propose here an efficient method to define an approximation subspace to compute the first vibrational frequencies of the molecular Hamiltonian which are those of interest in the experimental results

Décomposition en valeurs singulières randomisée et positionnement multidimensionel à base de tâches

The multidimensional scaling (MDS) is an important and robust algorithm for representing individual cases of a dataset out of their respective dissimilarities. However, heuristics, possibly trading-off with robustness, are often preferred in practice due to the potentially prohibitive memory and computational costs of the MDS. The recent introduction of random projection techniques within the MDS allowed it to be become competitive on larger testcases. The goal of this manuscript is to propose a high-performance distributed-memory MDS based on random projection for processing data sets of even larger size (up to one million items). We propose a task-based design of the whole algorithm and we implement it within an efficient software stack including state-of-the-art numerical solvers, runtime systems and communication layers. The outcome is the ability to efficiently apply robust MDS to large datasets on modern supercomputers. We assess the resulting algorithm and software stack to the point cloud visualization for analyzing distances between sequencesin metabarcoding.Le positionnement multidimensionnel (MDS) est un algorithme important et robuste pour représenter les cas individuels d’un ensemble de données en fonction de leurs dissimilarités respectives. Cependant, les heuristiques, qui peuvent être un compromis avec la robustesse, sont souvent préférées en pratique en raison de sa consommation mémoire et de ses coûts potentiellement prohibitifs. L’introduction récente de techniques de projection aléatoire dans le MDS lui a permis de devenir compétitif sur des cas test plus importants. L’objectif de ce manuscrit est de proposer un MDS haute performance basé sur la projection aléatoire pour le traitement d’ensembles de données de taille encore plus grande (jusqu’à un million d’éléments). Nous proposons une conception de l’algorithme et nous l’implémentons dans une pile logicielle efficace, comprenant des solveurs numériques de pointe ainsi des systèmes d’exécution et des couches de communication optimisés. L’aboutissement de ce travail résultat est la capacité d’appliquer efficacement le MDS robuste à de grands ensembles de données sur des super-ordinateurs modernes. Nous évaluons l’algorithme etla pile logicielle résultants à la visualisation de nuages de points pour l’analyse des distances entre séquences de metabarcoding

Modèles ecologiques pour l'extrapolation des effets écotoxicologiques enregistrés lors de biotests in situ cheZ Gammarus

[Departement_IRSTEA]Eaux [TR1_IRSTEA]BELCAInternational audienceEvaluating the effects of chemical contamination on populations and ecological communities still constitutes a challenging necessity in environmental management. However the toxic effects of contaminants are commonly measured by means of organism-level responses. Linking such effects measures with ecological models is a promising way to apprehend population-level impacts. In this way, population models are currently increasingly used in predictive risk assessment procedures, but their use in environmental diagnostic framework remains limited due to their lack of ecological realism. The present study with the crustacean amphipod Gammarus fossarum, a sentinel species in freshwater monitoring, combines a dual field and laboratory experimental approach with a population modelling framework. In this way, we developed an ecologically-relevant periodic matrix population model for Gammarus. This model allowed us to capture the population dynamics in the field, and to understand the particular pattern of demographic sensitivities induced by Gammarus life-history phenology. The model we developed provided a robust population-level assessment of in situ-based effects measures recorded during a biomonitoring program on a French watershed impacted by past mining activities. Thus, our study illustrates the potential of population modelling when seeking to decipher the role of environmental toxic contamination in ecological perturbations

Modelling and change of scales in ecotoxicological risk assessmment : methodological developments for two freshwater macroinvertebrates, Gammarus pulex (crustacean) and Potamopyrgus antipodarum (gastropod)

Les réglementations conduisent à multiplier les évaluations du risque écologique lié au rejet des substances chimiques dans les milieux aquatiques avec pour objectif de protéger les populations naturelles. Cependant, ce niveau de protection visé ne peut être utilisé facilement pour établir un lien direct entre une contamination et ses effets. Pour palier cette difficulté, les approches multi-échelles basées sur l'étude des effets des contaminations sur des marqueurs individuels puis sur l'extrapolation de ces effets au niveau des poipulations à partir de modèles de dynamique de population représentent des démarches prometteuses et commencent à être bien acceptées dans les démarches prédictives.Cependant, leur utilisation pour le diagnostic de la qualité des milieux aquatiques reste pour le moment très rare, d'une part en raison de la forte variabilité des réponses des marqueurs individuels in situ liée à l'influence de divers facteurs environnementaux confondants pour l'évaluation de la toxicité, et d'autre part à cause du manque de pertinence environnementale des modèles actuellement proposés. Centré sur l'utilisation de deux espèces couramment observées dans les cours d'eau européens et présentant des caractéristiques écologiques et phylogéniques contrastées : le crustacé Gammarus fossarum et le mollusque Potamopyrgus antipodarum, ce travail doctoral a permis : 1- de proposer une méthodologie pour prendre en compte l'influence des facteurs de confusion dans le but d'améliorer la lecture des bioessais in situ basés sur la mesure des marqueurs individuels sur des organismes encagés et 2- de développer des modèles de dynamique de population écologiquemnt pertinents.The regulatory framework lead to increase the assessments of the ecological risk linked to the dischaarge of chemical substances in aquatic environment with the aim to protect natural populations. However, this target level of protection cannot be used so easily to etablish a direcet link between a contamination and its effects. In order to overcome this difficulty, the multi-scale approaches based on the study of the effects of the contaminations on individual markers and then on the extrapolation of these effects at the population level with population dynamic models reprensent promising tools and start to bewell accepted in predictive processes. Yet, their use for the diagnosis of water quality remainsrare for the moment, on the one hand, because of the important varaibility of answers of individual makers in situ linked to the influence of diverse confounding environmental factors for the assessments of toxicity and, on the other hand, because pf the lack of environmental relevance of models currently proposed. Focused on the use of 2 species widely observed in European rivers and presenting contrastingecological and phylogenetic characteristics : the Grammar fossarum crutacean and the Potamopyrgus antipodarum mollusc, this doctoral degree first propose a methodology to consider the influenceof confounding factors in order to improve the reading of biological in situ tests based on the measurment of individual markers on caged organisms and second, to develop ecologically relevant population models. Thus, this work allowed to underline the importance of the consideration of confounding factors (i.e. temperature), in different in situ tests based on the measurment of individul markers on caged organisms. Moreover, population models for both species have been defined in order to test the influence of life histories and seasonal variations on demographic sensitivity of populations

Modélisation et changements d'échelles pour l'évaluation écotoxicologique : application à deux macroinvertébrés aquatiques, Gammarus fossarum (crustacé amphipode) et potamopyrgus antipodarum (mollusque gastéropode)

The regulatory framework lead to increase the assessments of the ecological risk linked to the dischaarge of chemical substances in aquatic environment with the aim to protect natural populations. However, this target level of protection cannot be used so easily to etablish a direcet link between a contamination and its effects. In order to overcome this difficulty, the multi-scale approaches based on the study of the effects of the contaminations on individual markers and then on the extrapolation of these effects at the population level with population dynamic models reprensent promising tools and start to bewell accepted in predictive processes. Yet, their use for the diagnosis of water quality remainsrare for the moment, on the one hand, because of the important varaibility of answers of individual makers in situ linked to the influence of diverse confounding environmental factors for the assessments of toxicity and, on the other hand, because pf the lack of environmental relevance of models currently proposed. Focused on the use of 2 species widely observed in European rivers and presenting contrastingecological and phylogenetic characteristics : the Grammar fossarum crutacean and the Potamopyrgus antipodarum mollusc, this doctoral degree first propose a methodology to consider the influenceof confounding factors in order to improve the reading of biological in situ tests based on the measurment of individual markers on caged organisms and second, to develop ecologically relevant population models. Thus, this work allowed to underline the importance of the consideration of confounding factors (i.e. temperature), in different in situ tests based on the measurment of individul markers on caged organisms. Moreover, population models for both species have been defined in order to test the influence of life histories and seasonal variations on demographic sensitivity of populations.Les réglementations conduisent à multiplier les évaluations du risque écologique lié au rejet des substances chimiques dans les milieux aquatiques avec pour objectif de protéger les populations naturelles. Cependant, ce niveau de protection visé ne peut être utilisé facilement pour établir un lien direct entre une contamination et ses effets. Pour palier cette difficulté, les approches multi-échelles basées sur l'étude des effets des contaminations sur des marqueurs individuels puis sur l'extrapolation de ces effets au niveau des poipulations à partir de modèles de dynamique de population représentent des démarches prometteuses et commencent à être bien acceptées dans les démarches prédictives.Cependant, leur utilisation pour le diagnostic de la qualité des milieux aquatiques reste pour le moment très rare, d'une part en raison de la forte variabilité des réponses des marqueurs individuels in situ liée à l'influence de divers facteurs environnementaux confondants pour l'évaluation de la toxicité, et d'autre part à cause du manque de pertinence environnementale des modèles actuellement proposés. Centré sur l'utilisation de deux espèces couramment observées dans les cours d'eau européens et présentant des caractéristiques écologiques et phylogéniques contrastées : le crustacé Gammarus fossarum et le mollusque Potamopyrgus antipodarum, ce travail doctoral a permis : 1- de proposer une méthodologie pour prendre en compte l'influence des facteurs de confusion dans le but d'améliorer la lecture des bioessais in situ basés sur la mesure des marqueurs individuels sur des organismes encagés et 2- de développer des modèles de dynamique de population écologiquemnt pertinents