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1. Les macrophytes sont-ils de bons candidats pour l’évaluation du succès d’une restauration ? L’exemple des anciens bras du Rhin reconnectés

Author

TRÉMOLIÈRES, Michèle and MEYER, Albin

Subjects
MACROPHYTES, RESTAURATION ECOLOGIQUE, INDICATEUR, EVALUATION, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350
Abstract

Lors d’opérations de restauration comme celle menée dans la plaine d’Alsace pour reconnecter d’anciens bras latéraux du Rhin au cours principal, il convient de vérifier comment ces modifications affectent la biodiversité et fonctionnalité des milieux aquatiques. Pour cela, l’étude des macrophytes peut être tout à fait pertinente.

Published
2014

2. Machine learning techniques to characterize functional traits of plankton from image data

Author

Orenstein, Eric C, Ayata, Sakina‐Dorothée, Maps, Frédéric, Becker, Érica C, Benedetti, Fabio, Biard, Tristan, Garidel‐Thoron, Thibault, Ellen, Jeffrey S, Ferrario, Filippo, Giering, Sarah LC, Guy‐Haim, Tamar, Hoebeke, Laura, Iversen, Morten Hvitfeldt, Kiørboe, Thomas, Lalonde, Jean‐François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, Mark D, Pradalier, Cédric, Romagnan, Jean‐Baptiste, Schröder, Simon‐Martin, Sonnet, Virginie, Sosik, Heidi M, Stemmann, Lars S, Stock, Michiel, Terbiyik‐Kurt, Tuba, Valcárcel‐Pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M, and Irisson, Jean‐Olivier

Subjects
Biological Sciences, Ecology, Earth Sciences, Environmental Sciences, Marine Biology & Hydrobiology, Biological sciences, Earth sciences, Environmental sciences
Abstract

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Published
2022

11. Machine learning techniques to characterize functional traits of plankton from image data

Author

Orenstein, Eric C., Ayata, Sakina Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Iversen, Morten H., Kiørboe, Thomas, Lalonde, Jean-François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas O., Niehoff, Barbara, Ohman, Mark D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon-Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik-Kurt, Tuba, Valcárcel-Pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., Irisson, Jean-Olivier, Orenstein, Eric C., Ayata, Sakina Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Iversen, Morten H., Kiørboe, Thomas, Lalonde, Jean-François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas O., Niehoff, Barbara, Ohman, Mark D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon-Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik-Kurt, Tuba, Valcárcel-Pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., and Irisson, Jean-Olivier

Abstract

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Orenstein, E., Ayata, S., Maps, F., Becker, É., Benedetti, F., Biard, T., Garidel‐Thoron, T., Ellen, J., Ferrario, F., Giering, S., Guy‐Haim, T., Hoebeke, L., Iversen, M., Kiørboe, T., Lalonde, J., Lana, A., Laviale, M., Lombard, F., Lorimer, T., Martini, S., Meyer, A., Möller, K.O., Niehoff, B., Ohman, M.D., Pradalier, C., Romagnan, J.-B., Schröder, S.-M., Sonnet, V., Sosik, H.M., Stemmann, L.S., Stock, M., Terbiyik-Kurt, T., Valcárcel-Pérez, N., Vilgrain, L., Wacquet, G., Waite, A.M., & Irisson, J. Machine learning techniques to characterize functional traits of plankton from image data. Limnology and Oceanography, 67(8), (2022): 1647-1669, https://doi.org/10.1002/lno.12101., Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms., SDA acknowledges funding from CNRS for her sabbatical in 2018–2020. Additional support was provided by the Institut des Sciences du Calcul et des Données (ISCD) of Sorbonne Université (SU) through the support of the sponsored junior team FORMAL (From ObseRving to Modeling oceAn Life), especially through the post-doctoral contract of EO. JOI acknowledges funding from the Belmont Forum, grant ANR-18-BELM-0003-01. French co-authors also wish to thank public taxpayers who fund their salaries. This work is a contribution to the scientific program of Québec Océan and the Takuvik Joint International Laboratory (UMI3376; CNRS - Université Laval). FM was supported by an NSERC Discovery Grant (RGPIN-2014-05433). MS is supported by the Research Foundation - Flanders (FWO17/PDO/067). FB received support from ETH Zürich. MDO is supported by the Gordon and Betty Moore Foundation and the U.S. National Science Foundation. ECB is supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) under the grant agreement no. 88882.438735/2019-01. TB is supported by the French National Research Agency (ANR-19-CE01-0006). NVP is supported by the Spanish State Research Agency, Ministry of Science and Innovation (PTA2016-12822-I). FL is supported by the Institut Universitaire de France (IUF). HMS was supported by the Simons Foundation (561126) and the U.S. National Science Foundation (CCF-1539256, OCE-1655686). Emily Peacock is gratefully acknowledged for expert annotation of IFCB images. LS was supported by the Chair VISION from CNRS/Sorbonne Université.

Published
2022

12. Linking Micropollutants to Trait Syndromes across Freshwater Diatom, Macroinvertebrate, and Fish Assemblages

Author

Meyer, Albin, Alric, Benjamin, Dézerald, Olivier, Billoir, Elise, Coulaud, Romain, Larras, Floriane, Mondy, Cédric P, Usseglio-polatera, Philippe, Meyer, Albin, Alric, Benjamin, Dézerald, Olivier, Billoir, Elise, Coulaud, Romain, Larras, Floriane, Mondy, Cédric P, and Usseglio-polatera, Philippe

Abstract

The ecological quality of freshwater ecosystems is endangered by various micropollutants released into the environment by human activities. The cumulative effects of these micropollutants can affect the fitness of organisms and populations and the functional diversity of stream ecosystems. In this study, we investigated the relationships between the joint toxicity of micropollutants and trait syndromes. A trait syndrome corresponds to a combination of traits that could occur together in communities due to the trait selection driven by exposure to these micropollutants. Our objectives were to (i) identify trait syndromes specific to diatom, macroinvertebrate, and fish assemblages and their responses to exposure, taking into account four micropollutant types (mineral micropollutants, pesticides, PAHs, and other organic micropollutants) and nine modes of action (only for pesticides), (ii) explore how these syndromes vary within and among the three biological compartments, (iii) investigate the trait categories driving the responses of syndromes to micropollutant exposure, and (iv) identify specific taxa, so-called paragons, which are highly representative of these syndromes. To achieve these objectives, we analyzed a dataset including the biological and physico-chemical results of 2007 sampling events from a large-scale monitoring survey routinely performed in French wadeable streams. We have identified five (diatoms), eight (macroinvertebrates), and eight (fishes) trait syndromes, either positively or negatively related to an increasing toxicity gradient of different clusters of micropollutant types or modes of action. Our analyses identified several key trait categories and sets of paragons, exhibiting good potential for highlighting exposure by specific micropollutant types and modes of action. Overall, trait syndromes might represent a novel and integrative bioassessment tool, driven by the diversity of trait-based responses to increasing gradients of micropollutan

Published
2022
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13. Machine learning techniques to characterise functional traits of plankton image data

Author

Orenstein, Eric, Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica, Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey, Ferrario, Filippo, Giering, Sarah, Guy-Haim, Tamar, Hoebeke, Laura, Iversen, Morten, Kiorboe, Thomas, Lalonde, Jean-Francois, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, Mark, Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon-Martin, Sonnet, Virginie, Sosik, Heidi, Stemmann, Lars, Stock, Michiel, Terbiyik-Kurt, Tuba, Valcárcel-Pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya, Irisson, Jean-Olivier, Orenstein, Eric, Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica, Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey, Ferrario, Filippo, Giering, Sarah, Guy-Haim, Tamar, Hoebeke, Laura, Iversen, Morten, Kiorboe, Thomas, Lalonde, Jean-Francois, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, Mark, Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon-Martin, Sonnet, Virginie, Sosik, Heidi, Stemmann, Lars, Stock, Michiel, Terbiyik-Kurt, Tuba, Valcárcel-Pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya, and Irisson, Jean-Olivier

Abstract

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Published
2022

14. Supplemental Information: Machine learning techniques to characterize functional traits of plankton from image data

Author

Orenstein, Eric C., Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Hvitfeldt, Morten, Kiørboe, Thomas, Lalonde, Jean François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, M. D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik Kurt, Tuba, Valcárcel, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., Irisson, Jean-Olivier, Orenstein, Eric C., Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Hvitfeldt, Morten, Kiørboe, Thomas, Lalonde, Jean François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, M. D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik Kurt, Tuba, Valcárcel, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., and Irisson, Jean-Olivier

Published
2022

15. Machine learning techniques to characterize functional traits of plankton from image data

Author

Centre National de la Recherche Scientifique (France), Belmont Forum, Université Laval, Natural Sciences and Engineering Research Council of Canada, Research Foundation - Flanders, ETH Zurich, Gordon and Betty Moore Foundation, National Science Foundation (US), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil), Agence Nationale de la Recherche (France), Ministerio de Economía y Competitividad (España), Institut Universitaire de France, Simons Foundation, Sorbonne Université, Orenstein, Eric C., Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Hvitfeldt, Morten, Kiørboe, Thomas, Lalonde, Jean François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, M. D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik Kurt, Tuba, Valcárcel, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., Irisson, Jean-Olivier, Centre National de la Recherche Scientifique (France), Belmont Forum, Université Laval, Natural Sciences and Engineering Research Council of Canada, Research Foundation - Flanders, ETH Zurich, Gordon and Betty Moore Foundation, National Science Foundation (US), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil), Agence Nationale de la Recherche (France), Ministerio de Economía y Competitividad (España), Institut Universitaire de France, Simons Foundation, Sorbonne Université, Orenstein, Eric C., Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Hvitfeldt, Morten, Kiørboe, Thomas, Lalonde, Jean François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, M. D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik Kurt, Tuba, Valcárcel, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., and Irisson, Jean-Olivier

Abstract

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Published
2022

19. Développement d’un indicateur phytoplancton très grands cours d’eau : Présentation et bilan de la base de données nationales

Author

Prygiel, Emilie, Lasseron, Frédéric, Laplace-Treyture, Christophe, Meyer, Albin, Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement - Direction Nord-Picardie (Cerema Direction Nord-Picardie), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema), Ecosystèmes aquatiques et changements globaux (UR EABX), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), OFB, Cerema - Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement, and INRAE UR-EABX

Subjects
Cours d 'eau, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Phytoplancton, Base de données, Typologie de cours d'eau, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

En réponse à un appel à manifestation d’intérêt « développement en matière de surveillance et d’évaluation de l’état des eaux et des milieux aquatiques continentaux, littoraux et marins dans le cadre des directives européennes », le projet DIPCEAU vise au développement d’un indicateur phytoplancton pour l’évaluation de l’état écologique des grands cours d’eau. Les données nouvellement acquises sur le maillon phytoplancton en grands cours d’eau sur le territoire métropolitain doivent permettre d’élaborer une 1ère version d’un indicateur d’état écologique pour 2022. L’indice sera ensuite transféré vers l’outil de calcul de l’état écologique des masses d’eau (SEEE) et sera raccordé aux travaux précédents d’intercalibration européenne. Pour ce faire, un protocole d’acquisition standardisé des données phytoplancton a été rédigé par INRAE (Laplace-Treyture et al., 2010) puis mis en œuvre au cours des années suivantes afin de disposer d’un jeu de données suffisant pour le développement d’un indicateur. A partir de 2016, ces données ont été regroupées et bancarisées par le Cerema dans une base structurée de données communes. La 1ère partie de ce rapport contient un retour sur la campagne de bancarisation des données 2019, dernièrement acquises. La partie 2 rappelle le schéma d’organisation de la base de données. Puis un bilan de la qualité et de la pertinence des données pour le développement de l’indicateur est ensuite présenté dans une 3ème partie.

Published
2021

21. Diagnostic écologique multi-compartiments des cours d’eau. Action 7 : Développement d’un indice biologique pour les cours d’eau de Mayotte, fondé sur la macrofaune benthique

Author

Meyer, Albin, Mary, Nathalie, Houviez, Lucie, Gomez, Livia, Usseglio-Polatera, Philippe, Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Etude des Hydrosystèmes Continentaux Tropicaux (ETHYC'O), OFB, and Rapport Université de Lorraine (LIEC) pour l’OFB

Subjects
île de Mayotte, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, indice, [SDE]Environmental Sciences, invertébrés, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDE.ES]Environmental Sciences/Environmental and Society, bioindication, cours d'eau
Published
2020

22. Diagnostic écologique multi-compartiments des cours d’eau. Action 1 : définition des conditions de référence pour les Grands Cours d’Eau (GCE) et les Très Grands Cours d’Eau (TGCE), action 2 : proposition d’une version opérationnelle de l’indice I2M2-GCE et action 3 : proposition d’un outil diagnostique pour les Grands Cours d’Eau

Author

MEYER, Albin, COULAUD, Romain, VELLINGER, Céline, CHARDON, Thomas, USSEGLIO-POLATERA, Philippe, USSEGLIO-POLATERA, PHILIPPE, Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Le Havre Normandie - UFR Sciences et Techniques (ULHN UFR ST), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU), Stress Environnementaux et BIOsurveillance des milieux aquatiques (SEBIO), Institut National de l'Environnement Industriel et des Risques (INERIS)-Université de Reims Champagne-Ardenne (URCA)-Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU)-SFR Condorcet, Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), OFB, and Rapport Université de Lorraine (LIEC) pour l’OFB

Subjects
[SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE] Environmental Sciences, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, grands cours d'eau, indice, [SDE]Environmental Sciences, [SDV.EE.ECO] Life Sciences [q-bio]/Ecology, environment/Ecosystems, invertébrés, [SDE.ES] Environmental Sciences/Environmental and Society, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDE.ES]Environmental Sciences/Environmental and Society, bioindication
Published
2020

23. Morphological vs. DNA metabarcoding approaches for the evaluation of stream ecological status with benthic invertebrates: Testing different combinations of markers and strategies of data filtering

Author

Meyer, Albin, primary, Boyer, Frédéric, additional, Valentini, Alice, additional, Bonin, Aurélie, additional, Ficetola, Gentile Francesco, additional, Beisel, Jean‐Nicolas, additional, Bouquerel, Jonathan, additional, Wagner, Philippe, additional, Gaboriaud, Coline, additional, Leese, Florian, additional, Dejean, Tony, additional, Taberlet, Pierre, additional, and Usseglio‐Polatera, Philippe, additional

Published
2020
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25. A database of West European headwater macroinvertebrate stoichiometric traits.

Author

Beck, Miriam, Billoir, Elise, Felten, Vincent, Meyer, Albin, Usseglio‐Polatera, Philippe, Danger, Michael, and Gonzalez, Angelica

Subjects
CHEMICAL equilibrium, NUTRIENT cycles, DATABASES, CHEMICAL energy, FRESHWATER invertebrates
Abstract

Motivation: Ecological stoichiometry investigates the equilibrium and the fluxes of chemical elements and energy between organisms and their environment. Several studies have pointed out the value of integrating stoichiometric traits for a better understanding of the mechanisms behind community and ecosystem processes. Especially in the light of globally changing nutrient levels in freshwater systems, the link between stoichiometric traits and nutrient cycling or trophic interactions can improve our investigations of a species' or community's response to these changes. Benthic macroinvertebrate assemblages are widely used for biomonitoring in freshwaters, providing a large number of datasets gathering information about their taxonomic diversity at many different spatial and temporal scales. Likewise, an increasing number of large databases gives ready access to information on a variety of macroinvertebrate biological traits. The addition of stoichiometric traits to this pool of available information could thus expand the application of trait approaches and facilitate the study of the links between nutrient cycling and ecosystem functioning. Main types of variables contained: The database contains information on the elemental contents of 188 taxa, in terms of the major nutrients %C, %N and %P and the corresponding molar ratios C:N, C:P and N:P. We provide calculated taxon mean values as well as the underlying raw data at the individual level that were obtained from field sampling, supplemented by a literature search (n = 1,555; 174 taxa). Major taxa and level of measurements: The database contains information on 188 macroinvertebrate taxa, available at species (n = 33), genus (96), tribe (9), subfamily (6), family (42), order (1) or class (1) levels. Software format:.csv file. [ABSTRACT FROM AUTHOR]

Published
2022
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26. Une certaine incertitude : précision et confiance en bio-indication. L’exemple des diatomées et des macro-invertébrés

Author

Meyer, Albin, Billoir, Elise, Usseglio-Polatera, Philippe, Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), and USSEGLIO-POLATERA, PHILIPPE

Subjects
[SDE] Environmental Sciences, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE]Environmental Sciences, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2019

27. Evaluating the taxonomic and functional diversity of stream benthic invertebrate assemblages: morphological versus DNA metabarcoding approaches

Author

Meyer, Albin, Usseglio-Polatera, Philippe, Boyer, Frédéric, Valentini, Alice, Bonin, Aurelie, Ficetola, Francesco Gentile, Beisel, Jean-Nicolas, Bouquerel, Jonathan, Wagner, Philippe, Dejean, Tony, Taberlet, Pierre, Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), and USSEGLIO-POLATERA, PHILIPPE

Subjects
[SDE] Environmental Sciences, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE]Environmental Sciences, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

28. Développement d’un indice biologique pour les cours d’eau de Mayotte, fondé sur la macrofaune benthique

Author

MEYER, Albin, MARY, Nathalie, HOUVIEZ, Lucie, GOMEZ, Livia, USSEGLIO-POLATERA, Philippe, Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Etude des Hydrosystèmes Continentaux Tropicaux (ETHYC'O), AFB, and Rapport Université de Lorraine (LIEC) pour l’AFB

Subjects
[SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Bioindication indices, [SDE]Environmental Sciences, Mayotte island, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, invertebrates, streams, [SDE.ES]Environmental Sciences/Environmental and Society, diagnostic tool
Published
2019

29. Nouvelle localités de Tricholeiochiton fagesii (Guignard, 1879) en France (Trichoptera, Hydroptilidae)

Author

labat, Frédéric, Auzeric, Eva, Courte, Mathieu, fernadez, Nadia, Gaillard, Damien, Grac, Corinne, Lambert, Joyce, Meyer, Albin, Moreau, Aurélie, Poujardieu, Benjamin, Tarozzi, Nicolas, Laboratoire Image, Ville, Environnement (LIVE), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), and univOAK, Archive ouverte

Subjects
[SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

Dans le cadre du projet de recherche BIOME (Bioindication Mares et Etangs) et du projet d'étude interdisciplinaire du Woerr, dix nouvelles localités de Tricholeiochiton fagesii ont été identifiées. Cette espèce n'avait à ce jour fait l'objet que de deux captures récentes en France dans la Brenne. Les résultats confirment la relative rareté de l'espèce, rencontrée dans moins de 5% des plans d'eau suivis, aux typologies variées.

Published
2019

30. Morphological vs. DNA metabarcoding approaches for the evaluation of stream ecological status with benthic invertebrates: Testing different combinations of markers and strategies of data filtering.

Author

Meyer, Albin, Boyer, Frédéric, Valentini, Alice, Bonin, Aurélie, Ficetola, Gentile Francesco, Beisel, Jean‐Nicolas, Bouquerel, Jonathan, Wagner, Philippe, Gaboriaud, Coline, Leese, Florian, Dejean, Tony, Taberlet, Pierre, and Usseglio‐Polatera, Philippe

Subjects
*GENETIC barcoding, *DNA, *DNA fingerprinting, *BULK solids, *INVERTEBRATES
Abstract

Macroinvertebrate assemblages are the most common bioindicators used for stream biomonitoring, yet the standard approach exhibits several time‐consuming steps, including the sorting and identification of organisms based on morphological criteria. In this study, we examined if DNA metabarcoding could be used as an efficient molecular‐based alternative to the morphology‐based monitoring of streams using macroinvertebrates. We compared results achieved with the standard morphological identification of organisms sampled in 18 sites located on 15 French wadeable streams to results obtained with the DNA metabarcoding identification of sorted bulk material of the same macroinvertebrate samples, using read numbers (expressed as relative frequencies) as a proxy for abundances. In particular, we evaluated how combining and filtering metabarcoding data obtained from three different markers (COI: BF1‐BR2, 18S: Euka02 and 16S: Inse01) could improve the efficiency of bioassessment. In total, 140 taxa were identified based on morphological criteria, and 127 were identified based on DNA metabarcoding using the three markers, with an overlap of 99 taxa. The threshold values used for sequence filtering based on the "best identity" criterion and the number of reads had an effect on the assessment efficiency of data obtained with each marker. Compared to single marker results, combining data from different markers allowed us to improve the match between biotic index values obtained with the bulk DNA versus morphology‐based approaches. Both approaches assigned the same ecological quality class to a majority (86%) of the site sampling events, highlighting both the efficiency of metabarcoding as a biomonitoring tool but also the need for further research to improve this efficiency. [ABSTRACT FROM AUTHOR]

Published
2021
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31. Comparison of markers for the monitoring of freshwater benthic biodiversity through DNA metabarcoding.

Author

Ficetola, Gentile Francesco, Boyer, Frédéric, Valentini, Alice, Bonin, Aurélie, Meyer, Albin, Dejean, Tony, Gaboriaud, Coline, Usseglio‐Polatera, Philippe, and Taberlet, Pierre

Subjects
FRESHWATER biodiversity, GENETIC barcoding, DNA primers, DNA, BIODIVERSITY monitoring, ECOLOGICAL impact
Abstract

Metabarcoding of bulk or environmental DNA has great potential for biomonitoring of freshwater environments. However, successful application of metabarcoding to biodiversity monitoring requires universal primers with high taxonomic coverage that amplify highly variable, short metabarcodes with high taxonomic resolution. Moreover, reliable and extensive reference databases are essential to match the outcome of metabarcoding analyses with available taxonomy and biomonitoring indices. Benthic invertebrates, particularly insects, are key taxa for freshwater bioassessment. Nevertheless, few studies have so far assessed markers for metabarcoding of freshwater macrobenthos. Here we combined in silico and laboratory analyses to test the performance of different markers amplifying regions in the 18S rDNA (Euka02), 16S rDNA (Inse01) and COI (BF1_BR2‐COI) genes, and developed an extensive database of benthic macroinvertebrates of France and Europe, with a particular focus on key insect orders (Ephemeroptera, Plecoptera and Trichoptera). Analyses on 1,514 individuals representing different taxa of benthic macroinvertebrates showed very different amplification success across primer combinations. The Euka02 marker showed the highest universality, while the Inse01 marker showed excellent performance for the amplification of insects. BF1_BR2‐COI showed the highest resolution, while the resolution of Euka02 was often limited. By combining our data with GenBank information, we developed a curated database including sequences representing 822 genera. The heterogeneous performance of the different primers highlights the complexity in identifying the best markers, and advocates for the integration of multiple metabarcodes for a more comprehensive and accurate understanding of ecological impacts on freshwater biodiversity. [ABSTRACT FROM AUTHOR]

Published
2021
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32. Using taxonomic and functional trait-based approaches to investigate the effect of large wood-induced hydro-geomorphological processes on river invertebrates to inform river restoration design

Author

Grabowski, Robert, Magliozzi, Chiara, Robertson, Anne, Meyer, Albin, Usseglio-Polatera, Philippe, School of Water Science, Cranfield University, University of Roehampton, United Kingdom, Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), and USSEGLIO-POLATERA, PHILIPPE

Subjects
[SDE] Environmental Sciences, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE]Environmental Sciences, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

33. Assessing changes in invertebrates traits: the effect of large wood

Author

Usseglio-Polatera, Philippe, Magliozzi, Chiara, Meyer, Albin, Grabowski, Robert, USSEGLIO-POLATERA, PHILIPPE, Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), School of Water Science, and Cranfield University

Subjects
[SDE] Environmental Sciences, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE]Environmental Sciences, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

35. Impact de la redynamisation d'anciennes annexes hydrauliques sur la dynamique des macro-invertébrés benthiques et sur la végétation aquatique et rivulaire

Author

Meyer, Albin, Grac, Corinne, Schmitt, Laurent, Combroux, Isabelle, Tremolieres, Michele, univOAK, Archive ouverte, Laboratoire Image, Ville, Environnement (LIVE), and Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV.EE]Life Sciences [q-bio]/Ecology, environment, [SDV.EE] Life Sciences [q-bio]/Ecology, environment
Abstract

International audience; Durant les deux derniers siècles les aménagements du Rhin, et en particulier la canalisation et les aménagements hydro-électriques, ont mené à un découplage entre le fleuve et sa plaine alluviale. Dans la plaine du Rhin Supérieur l'arrêt des flux actifs d’eau et de sédiment dans les anciens bras et anastomoses a progressivement conduit à des phénomènes d'atterrissement de ces chenaux, voire à une disparition complète de ces milieux aquatiques alluviaux. La prise de conscience au niveau européen du mauvais état de ces annexes fluviales a mené à la mise en place de programmes de restauration (ex. INTERREG, LIFE Rhin vivant). En rive gauche (côté Alsacien) de nombreuses anciennes annexes hydrauliques du Rhin ont ainsi été restaurées et reconnectées durant les vingt dernières années dans le cadre de ces programmes. Des projets de recherche ont porté sur l’analyse de la dynamique des compartiments biologiques de ces rivières suite à leur redynamisation. Dans la plaine d’Alsace nous avons suivi durant plusieurs années l'évolution post-restauration de la composition et de la structure des communautés de macro-invertébrés benthiques, de la végétation aquatique et/ou rivulaire. Cette évolution a été également comparée à celle observée dans des bras dits de référence encore existants, qui n'ont jamais été déconnectés du fleuve. Nous avons observé que la recolonisation de ces bras restaurés par les macrophytes et les macro-invertébrés intervient très rapidement après la restauration, avec des communautés que l'on peut considérer comme stabilisées dès quelques années après les travaux. La composition et la structure de ces communautés sont fortement expliquées par les caractéristiques hydromorphologiques des bras restaurés, qui présentent alors des communautés similaires à celles des bras de référence lorsque ces caractéristiques sont elles aussi similaires. La végétation rivulaire herbacée subit des modifications de sa richesse spécifique et de sa composition lors des débordements. Ainsi la diversité des caractéristiques hydromorphologiques de ces bras restaurés, à rattacher à une diversité de débit entrant et de morphologie des cours d'eau, promeut la biodiversité à l'échelle de la plaine alluviale.

Published
2017

37. Suivi des communautés de macro-invertébrés dans les bras restaurés du Rhin en plaine d'Alsace

Author

Meyer, Albin, Grac, Corinne, Combroux, I., Schmitt, Laurent, Tremolieres, Michèle, and GRAC, Corinne

Subjects
[SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE.IE] Environmental Sciences/Environmental Engineering
Abstract

D'anciens bras latéraux du Rhin ont été restaurés et reconnectés durant les 20 dernières années dans le cadre de différents projets de restauration (Interreg, LIFE Rhin Vivant). Les communautés de macro-invertébrés de 12 anciens bras du Rhin ont été étudiées dans le but d'évaluer le succès de ces travaux de restauration. Ces 12 bras comprennent 9 bras restaurés et reconnectés, soit au cours principal du Rhin soit à un canal latéral de drainage, et 3 bras de référence, jamais déconnectés. Ce suivi a eu lieu en 2009 et en 2010, et il a été couplé à de nombreuses analyses chimiques (eau et sédiment) et hydro-morphologiques.Les communautés identifiées dans ces bras sont liées principalement à deux facteurs, la diversité des substrats et l'alimentation en eau (Rhin ou canal latéral). Ainsi les communautés de ces 12 bras sont dominées par des crustacés invasifs s'excluant mutuellement : Echinogammarus sp. pour les bras connectés au canal latéral et Dikerogammarus sp. pour les bras connectés au Rhin. Des mollusques exotiques, tels que Dreissena sp., Corbicula sp. et Potamopyrgus sp., font aussi partie des taxons les plus abondants. La richesse taxonomique et la diversité fonctionnelle des bras restaurés sont similaires à celles des bras de référence. Néanmoins ces reconnexions ne semblent pas favoriser la recolonisation de ces bras par des espèces patrimoniales.Ces reconnexions semblent avoir permis de restaurer la fonctionnalité de ces bras pour les communautés de macro-invertébrés. Cependant l'absence d'espèces patrimoniales montre les limites de tels projets sur la restauration de la valeur patrimoniale de ces bras.

Published
2015

38. Processes and dynamics of recolonization and biodiversity in side-channels of the Rhine river (France) and other restored streams after reconnection

Author

Meyer, Albin, Laboratoire d'Hydrologie et de Géochimie de Strasbourg (LHyGeS), Ecole et Observatoire des Sciences de la Terre (EOST), Université de Strasbourg (UNISTRA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Strasbourg, Michèle Trémolières, and STAR, ABES

Subjects
River, Restoration ecology, Reconnection, Rhine, Rivière, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Nutrients, Biodiversity, Écologie végétale, [SDV.BID]Life Sciences [q-bio]/Biodiversity, Écologie de la restauration, Vegetation ecology, Macrophytes, [SDU.STU] Sciences of the Universe [physics]/Earth Sciences, Nutriments, Hydro-géomorphologie, Reconnexion, Hydro-geomorphology, Biodiversité, Rhin, Ecosystem, [SDV.BID] Life Sciences [q-bio]/Biodiversity, Écosystème
Abstract

During the last 20 years, side channels of the Rhine have been reconnected to the main course. The objective of this thesis is to assess the efficiency of restoration and the recovery of the ecosystems functionality. The aquatic plant communities were used as indicators of changes. Many factors were monitored: plant communities, their biological characteristics, flux and bank of propagules, the chemistry of water, sediment and plants, hydro-geomorphology. This study was conducted in 9 restored sites and 3 reference sites. Three aquatic plant communities were identified: eutrophic, mesotrophic and rheophilic. The composition of these communities is first linked to physical conditions and second to trophic level, together with flux of propagules. Reconnections allowed the restored sites to exhibit communities and ecological functioning similar to reference sites, in a relatively short time., Durant les 20 dernières années d'anciens bras latéraux du Rhin ont été restaurés par reconnexion au cours principal. L'objectif de cette thèse est d'évaluer l'efficacité de la restauration et de vérifier si l'écosystème aquatique a retrouvé sa fonctionnalité. Les communautés végétales aquatiques sont utilisées ici comme indicateurs de ces changements. De nombreux facteurs ont été mesurés : les communautés végétales, leurs traits biologiques, les flux et stocks de diaspores, la chimie de l'eau, du sédiment et des plantes, l'hydro-géomorphologie. Cette étude a été menée dans 9 sites restaurés et 3 sites de référence. Trois communautés végétales ont été identifiées : une "eutrophe", une "mésotrophe", et une "rhéophile". La composition de ces communautés est liée aux conditions physiques et trophiques, et aux flux de diaspores. Les reconnexions ont permis aux sites restaurés de retrouver des communautés et une fonctionnalité écologique semblables à celles des sites de référence.

Published
2012

41. Dynamics of Nutrient Contents (Phosphorus, Nitrogen) in Water, Sediment and Plants After Restoration of Connectivity in Side-Channels of the River Rhine.

Author

Meyer, Albin, Combroux, Isabelle, and Trémolières, Michèle

Subjects
*PLANT nutrients, *PLANT-water relationships, *SEDIMENTS, *RESTORATION ecology, *CLIMATE change, *MACROPHYTES, *STREAM plants
Abstract

During the last century, canalization of the Rhine river led to disconnection of side-arms, over-sedimentation of these channels, loss of the fluvial dynamics, and aquatic vegetation change or disappearance. Recent restoration projects aim to reconnect disconnected arms to the main channel. The objective of this study was to assess the nutrient dynamics in restored channels during the vegetation colonization process. In spring, summer, and autumn 2009, the phosphorus and nitrogen contents were measured in water, sediment, and plants, sampled in six channels, two reference sites and four restored ones at different dates. Aquatic vegetation was monitored during the same period. Sites were mesotrophic related to the water nutrient concentrations. However, vegetation communities indicated a eutrophic level, as they were dominated by species like Elodea nuttallii, Myriophyllum spicatum, and Potamogeton perfoliatus. Sites were discriminated by P content and mineral nitrogen in the sediment. We showed an effect of species and season on the plant nutrient content, but there was no relationship between plant nutrient content and nutrients in water and sediment. A negative correlation between mean N plant content and the cover of each species was found. Vegetation characteristics (species richness and cover) and bioavailable phosphorus in the sediment were also correlated. In the restored side-arms of the river Rhine, phosphorus-rich sediment seems to be important in the recolonization dynamics, as it was linked to higher species richness, whereas nitrogen played a role in the colonization patterns as a growth limiting factor. [ABSTRACT FROM AUTHOR]

Published
2013
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