A young age of subspecific divergence in the desert locust inferred by ABC Random Forest

Chapuis Marie Pierre, Raynal Louis, Plantamp Christophe, Meynard Christine N., Blondin Laurence, Marin Jean-Michel, Estoup Arnaud. 2020. A young age of subspecific divergence in the desert locust inferred by ABC Random Forest. Molecular Ecology, 29 (23) : pp. 4542-4558.

Journal article ; Article de revue à facteur d'impact
[img] Version Online first - Anglais
Access restricted to CIRAD agents
Use under authorization by the author or CIRAD.

Télécharger (3MB) | Request a copy
[img] Published version - Anglais
Access restricted to CIRAD agents
Use under authorization by the author or CIRAD.

Télécharger (1MB) | Request a copy

Url - jeu de données :

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Psychologie-éthologie-ergonomie

Abstract : Dating population divergence within species from molecular data and relating such dating to climatic and biogeographic changes is not trivial. Yet it can help formulating evolutionary hypotheses regarding local adaptation and future responses to changing environments. Key issues include statistical selection of a demographic and historical scenario among a set of possible scenarios, and estimation of the parameter(s) of interest under the chosen scenario. Such inferences greatly benefit from (i) independent information on evolutionary rate and pattern at genetic markers and (ii) new statistical approaches, such as approximate Bayesian computation ‐ Random Forest (ABC‐RF), which provides reliable inference at a low computational cost and the possibility to measure prediction quality at the exact position of the observed dataset. Here, we show full potential of the ABC‐RF approach including prior knowledge on microsatellite genetic markers to decipher the evolutionary history of the African arid‐adapted pest locust, Schistocerca gregaria, with support for a southern colonization of Africa, from a low number of founders of northern origin, dating back 2.6 Ky (90% CI: 0.9 – 6.6 Ky). We verify that this divergence time estimate accurately reflected true divergence time values by computing accuracy at a local posterior scale from simulated pseudo‐observed datasets. The inferred divergence history is better explained by the peculiar biology of S. gregaria, which involves a density‐dependent swarming phase with some exceptional spectacular migrations, rather than a continuous colonization resulting from the continental expansion of open vegetation habitats during more ancient Quaternary glacial climatic episodes.

Mots-clés Agrovoc : Schistocerca gregaria, Modèle de simulation, Modèle mathématique, Dynamique des populations, Population animale, Orthoptera

Mots-clés géographiques Agrovoc : Afrique

Mots-clés libres : Approximate Bayesian computation, Colonization, Divergence time, Holocene, Orthoptera, Random forest

Classification Agris : H10 - Pests of plants

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Auteurs et affiliations

  • Chapuis Marie Pierre, CIRAD-BIOS-UMR CBGP (FRA) - auteur correspondant
  • Raynal Louis, Université de Montpellier (FRA)
  • Plantamp Christophe, ANSES (FRA)
  • Meynard Christine N., INRAE (FRA)
  • Blondin Laurence, CIRAD-BIOS-UMR BGPI (FRA)
  • Marin Jean-Michel, Université de Montpellier (FRA)
  • Estoup Arnaud, INRAE (FRA)

Source : Cirad-Agritrop (

View Item (staff only) View Item (staff only)

[ Page générée et mise en cache le 2021-01-18 ]