L’UMR CBGP – Centre de Biologie pour la Gestion des Populations – a pour vocation de comprendre les mécanismes qui régissent l’évolution de populations d'organismes importants pour l’agronomie, les forêts, la santé humaine ou la conservation de la biodiversité. Les recherches portent sur des modèles biologiques et sont développées selon six axes : origine et caractérisation de la biodiversité ; adaptation des phytophages, de leurs ennemis naturels et de leurs symbiontes ; écologie et évolution des zoonoses ; biologie, écologie et évolution des espèces envahissantes ; génomique statistique et évolutive des populations ; approches moléculaires et bioinformatiques haut débit. Nos tutelles sont l'INRAE, le CIRAD, l'IRD et l'Institut Agro-Montpellier.

UMR CBGP – Centre de Biologie pour la Gestion des Populations – aims to understand the mechanisms that govern populations of organisms that are important to agriculture, forest, human health and biodiversity conservation. Studies concern biological models and follow six lines of research: origin and characterization of biodiversity; adaptation of plant eaters, their natural enemies and symbionts; ecology and evolution of zoonoses; biology, ecology and evolution of invasive species; statistical and evolutionary population genomics; and high-throughput molecular and bioinformatics techniques. Our supervising bodies are INRAE, CIRAD, IRD and Institut Agro-Montpellier.
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1 to 10 of 12 Results
Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
1 mars 2024
Chapuis, Marie-Pierre; Benoit, Laure; Galan, Maxime, 2023, "Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"", https://doi.org/10.18167/DVN1/D31UAV, CIRAD Dataverse, V2, UNF:6:3cpS5HiYLk+POaq90NQuug== [fileUNF]
Shell script for preprocessing of raw sequences ; R scripts for data filtering, reduction and analysis ; abundance table data.
Multi-agent model SANDMAN: source code
Multi-agent model SANDMAN: source code
2 oct. 2023
SOREL, Maeva; GAY, Pierre-Emmanuel; PIOU, Cyril, 2023, "Multi-agent model SANDMAN: source code", https://doi.org/10.18167/DVN1/1UIN2P, CIRAD Dataverse, V2
Multi-agent model SANDMAN source code for NetLogo (v. 6.3.0). [Swarm migrAtion uNder winD, teMperature and vegetAtion iNfluence]
Original data for "Chapuis et al., 2023. Domestication provides durum wheat with protection from locust herbivory. Ecology and Evolution, 13(1): e9741"
Original data for "Chapuis et al., 2023. Domestication provides durum wheat with protection from locust herbivory. Ecology and Evolution, 13(1): e9741"
18 janv. 2023
CHAPUIS, Marie-Pierre; LEMENAGER, Nicolas; PIOU, Cyril; ROUMET, Pierre; MARCHE, Héloïse; CENTANNI, Julia; ESTIENNE, Christophe; ECARNOT, Martin; VASSEUR, François; VIOLLE, Cyrille; KAZAKOU, Elena, 2023, "Original data for "Chapuis et al., 2023. Domestication provides durum wheat with protection from locust herbivory. Ecology and Evolution, 13(1): e9741"", https://doi.org/10.18167/DVN1/HFGUJH, CIRAD Dataverse, V1
Functional and nutritional leaf trait data, behavioural insect data, and R scripts for analyses.
Original data used in Vernier et al.'s work: "Faeces' odours attract gregarious locust hoppers"
Original data used in Vernier et al.'s work: "Faeces' odours attract gregarious locust hoppers"
9 nov. 2022
Vernier, Camille; Barthes, Nicolas; Chapuis, Marie-Pierre; Foucaud, Julien; Huguenin, Joris; Lemenager, Nicolas; Piou, Cyril, 2022, "Original data used in Vernier et al.'s work: "Faeces' odours attract gregarious locust hoppers"", https://doi.org/10.18167/DVN1/D3OP8O, CIRAD Dataverse, V1, UNF:6:R/QcjJUh0JNkL7XCE6g8uw== [fileUNF]
Data of behavioral assays and chemical analyses. R scripts and .csv files.
Original data for "Javal et al. 2022. Does host plant drive variation in microbial gut communities in a recently shifted pest? Microbial Ecology (2022)"
Original data for "Javal et al. 2022. Does host plant drive variation in microbial gut communities in a recently shifted pest? Microbial Ecology (2022)"
29 août 2022
Javal, Marion; Terblanche, John; Benoit, Laure; Conlong, Desmond; Lloyd, James; Chapuis, Marie-Pierre, 2022, "Original data for "Javal et al. 2022. Does host plant drive variation in microbial gut communities in a recently shifted pest? Microbial Ecology (2022)"", https://doi.org/10.18167/DVN1/4KYM3B, CIRAD Dataverse, V1, UNF:6:hw/k9VXTEae1/JbguJzMtQ== [fileUNF]
Dataset describing microbial gut communities in a recently shifted pest, Cacosceles newmannii in 2018 in Kwazulu Natal, South Africa.
An agent-based model to simulate the boosted Sterile Insect Technique for fruit fly management
An agent-based model to simulate the boosted Sterile Insect Technique for fruit fly management
16 mars 2022
DIOUF, Esther; PIOU, Cyril, 2022, "An agent-based model to simulate the boosted Sterile Insect Technique for fruit fly management", https://doi.org/10.18167/DVN1/5WELPP, CIRAD Dataverse, V1
Multi-agent model BOOSTIT source code for NetLogo (v. 6.1.1)
Original data for "Chapuis et al., 2021. Additive genetic variance for traits least related to fitness increases with environmental stress in the desert locust, Schistocerca gregaria. Ecology and Evolution, 11: 13930-13947."
Original data for "Chapuis et al., 2021. Additive genetic variance for traits least related to fitness increases with environmental stress in the desert locust, Schistocerca gregaria. Ecology and Evolution, 11: 13930-13947."
23 sept. 2021
CHAPUIS, Marie-Pierre; PELISSIE, Benjamin; PIOU, Cyril; JOURDAN-PINEAU, Hélène, 2021, "Original data for "Chapuis et al., 2021. Additive genetic variance for traits least related to fitness increases with environmental stress in the desert locust, Schistocerca gregaria. Ecology and Evolution, 11: 13930-13947."", https://doi.org/10.18167/DVN1/S735JB, CIRAD Dataverse, V1
Phenotypic and pedigree data and R scripts for analyses (v. 4.0.4).
Multi-agent model ALMMAS 1.5: source code
Multi-agent model ALMMAS 1.5: source code
20 janv. 2021
GAY, Pierre-Emmanuel; PIOU, Cyril, 2021, "Multi-agent model ALMMAS 1.5: source code", https://doi.org/10.18167/DVN1/M7PDP8, CIRAD Dataverse, V1
Multi-agent model ALMMAS 1.5 source code for NetLogo (v. 6.1.1)
Original data for "Chapuis et al., 2020. A young age of subspecific divergence in the desert locust Schistocerca gregaria inferred by ABC Random Forest. Molecular Ecology, 29(23): 4542-4558."
Original data for "Chapuis et al., 2020. A young age of subspecific divergence in the desert locust Schistocerca gregaria inferred by ABC Random Forest. Molecular Ecology, 29(23): 4542-4558."
14 janv. 2020
CHAPUIS, Marie-Pierre; RAYNAL, Louis; PLANTAMP, Christophe; MEYNARD, Christine N.; BLONDIN, Laurence; MARIN, Jean-Michel; ESTOUP, Arnaud, 2020, "Original data for "Chapuis et al., 2020. A young age of subspecific divergence in the desert locust Schistocerca gregaria inferred by ABC Random Forest. Molecular Ecology, 29(23): 4542-4558."", https://doi.org/10.18167/DVN1/ZNSKGK, CIRAD Dataverse, V1
Microsatellite genotypic data and R scripts for ABC-RF analyses
Multi-agent model ALMMAS 1.4: source code
Multi-agent model ALMMAS 1.4: source code
25 juil. 2019
GAY, Pierre-Emmanuel; PIOU, Cyril, 2019, "Multi-agent model ALMMAS 1.4: source code", https://doi.org/10.18167/DVN1/MJHW2L, CIRAD Dataverse, V1
Multi-agent model ALMMAS 1.4 source code for NetLogo (v. 6.0.4)
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