Biomath (Dec 2018)

Bayesian inference of a dynamical model evaluating Deltamethrin effect on Daphnia survival

  • Abdoulaye Diouf,
  • Baba Issa Camara,
  • Diene Ngom,
  • Hela Toumi,
  • Vincent Felten,
  • Jean-Francois Masfaraud,
  • Jean-Francois Ferard

DOI
https://doi.org/10.11145/j.biomath.2018.12.177
Journal volume & issue
Vol. 7, no. 2

Abstract

Read online

The toxicokinetic and toxicodynamic models (TK-TD) are very well-known for their ability, at both the individual and the population level, to accurately describe life cycles such as the growth, reproduction and survival of sentinel organisms under the influence of an ecological biomarker. Being dynamics, the consistent inference of life history and environmental traits parameters that engender them is sometimes very complex numerically, especially as these parameters vary from one individual to another. In this paper, we estimate the parameters of a survival model TK-TD already applied and validated by the implementation of the R package GUTS (the General Unified Threshold Model of Survival) by another coding applied to another very recent implementation of Bayesian inference with the R package deBInfer in order to evaluate the survival effects of our ecotoxicological biomarker called Deltamethrin on our Daphnia sample. The study allowed us to evaluate from a population point of view especially the threshold concentration not to be exceeded to observe a survival effect commonly known NEC (No effect Concentration) and possibly determine the correlations between different variables of life history and the environment traits.