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.
Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

121 to 130 of 148 Results
setup_steriles_males.nls
16 mars 2022 - An agent-based model to simulate the boosted Sterile Insect Technique for fruit fly management
Unknown - 4,5 KB - MD5: 96e2e5632f844ff9c5bc92bc230acdad
Code
Part of nlogo source code. The setup of the sterile males and the number that will be released in each orchard.
setup_wild_flies.nls
16 mars 2022 - An agent-based model to simulate the boosted Sterile Insect Technique for fruit fly management
Unknown - 2,3 KB - MD5: ff779fc8110f1c98b277a76a4d4b1b03
Code
Part of Nlogo source code. The setup of the different stages of the fly and their location in the orchards.
tempAcceptHumidity.csv
16 mars 2022 - An agent-based model to simulate the boosted Sterile Insect Technique for fruit fly management
Comma Separated Values - 11,9 KB - MD5: 473c2d58d64de9e0a7d05217d4cd8a69
Data
Temperature and fruit availability input data
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).
DesertLocust_Dataset.txt
23 sept. 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."
Plain Text - 78,2 KB - MD5: 86fc14b1f49806508fba558f90a83beb
Data
Phenotypic measurements for the 483 desert locust individuals surveyed at the 4th laboratory generation (i.e., the half-sib/full-sib families)
DesertLocust_Pedigree.txt
23 sept. 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."
Plain Text - 14,3 KB - MD5: a64c68333f6d14867d5896772ee5bc24
Data
Four-generation pedigree data, including the 4th generation half-sib/full-sib families (for phenotypic measurements) and the three prior generations (for environmental standardization within laboratory)
ScriptR_Genetic_Analyses.R
23 sept. 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."
R Syntax - 27,0 KB - MD5: 2b4af3891d5e7acf4736f892d6360f97
Code
R script to run (1) quantitative genetic analyses on the 10 traits data measured in the 264 desert locust individuals and (2) simulation analysis of the statistical power of our quantitative genetics analysis
ScriptR_Phenotypic_Analyses.R
23 sept. 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."
R Syntax - 13,5 KB - MD5: 1eae8a93a71b014ba9e946088c6195cb
Code
R script to run phenotypic analyses on the 10 traits data measured in the 264 desert locust individuals
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)
ALMMAS1.5.nlogo
20 janv. 2021 - Multi-agent model ALMMAS 1.5: source code
text/nlogo - 123,1 KB - MD5: d2d16dc4f3082d2389a66a1aedc3ad39
Code
Suitable for Netlogo 6.1.1
Add Data

Log in to create a dataverse or add a dataset.

Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.