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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Original data for Piou et al. "Soil moisture from remote sensing to forecast Desert locust presence"
Original data for Piou et al. "Soil moisture from remote sensing to forecast Desert locust presence"
13 nov. 2018
PIOU, Cyril; GAY, Pierre-Emmanuel; BENAHI, Ahmed Salem; BABAH EBBE, Mohamed Abdallahi; CHIHRANE, Jamal; GHAOUT, Saïd; CISSÉ, Sory; DIAKITÉ, Fakaba; LAZAR, Mohammed; CRESSMAN, Keith; MERLIN, Olivier; ESCORIHUELA, Maria-José, 2018, "Original data for Piou et al. "Soil moisture from remote sensing to forecast Desert locust presence"", https://doi.org/10.18167/DVN1/AGVOW7, CIRAD Dataverse, V1
Dataset used in the analyses relating soil moisture estimates and other remote sensing estimates to the presence/absence of desert locust in Algeria, Mali, Mauriania and Morocco.
DesertLocustSMELLSdataset.txt
13 nov. 2018 - Original data for Piou et al. "Soil moisture from remote sensing to forecast Desert locust presence"
Plain Text - 18,4 MB - MD5: 38018d9e4940c5a076c2100dfb75cfe6
Data
Multi-agent model ALMMAS 1.0.2: source code
Multi-agent model ALMMAS 1.0.2: source code
15 oct. 2018
GAY, Pierre-Emmanuel; PIOU, Cyril, 2018, "Multi-agent model ALMMAS 1.0.2: source code", https://doi.org/10.18167/DVN1/ARUTUO, CIRAD Dataverse, V2
Multi-agent model ALMMAS 1.0.2 source code for NetLogo (v. 6.0.4)
ALMMAS 1.0.2.nlogo
15 oct. 2018 - Multi-agent model ALMMAS 1.0.2: source code
text/nlogo - 55,1 KB - MD5: 487745cef34bea8cb5ef57d8c530c4ed
Code
Suitable for Nlogo 6.0.4. With an upgrade of the info tab display
Readme.txt
11 juil. 2018 - Multi-agent model ALMMAS 1.0.2: source code
Plain Text - 79 B - MD5: 20c0b79b96fa22c37c51f8fcb7498f2f
Documentation
Where to download NetLogo
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