Bayesian emulation and calibration of an individual-based model of microbial communities
Authored by O K Oyebamiji, D J Wilkinson, B Li, P G Jayathilake, P Zuliani, T P Curtis
Date Published: 2019
DOI: 10.1016/j.jocs.2018.12.007
Sponsors:
United Kingdom Engineering and Physical Sciences Research Council (EPSRC)
Platforms:
C++
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
https://github.com/nufeb/NUFEB/releases
Abstract
Individual-based (IB) modelling has been widely used for studying the
emergence of complex interactions of bacterial biofilms and their
environment. We describe the emulation and calibration of an expensive
dynamic simulator of an IB model of microbial communities. We used a
combination of multivariate dynamic linear models (DLM) and a Gaussian
process to estimate the model parameters of our dynamic emulators. The
emulators incorporate a smoothly varying and nonstationary trend that is
modelled as a deterministic function of explanatory variables while the
Gaussian process (GP) is allowed to capture the remaining intrinsic
local variations. We applied this emulation strategy for parameter
calibration of a newly developed model for simulation of microbial
communities against the iDynoMiCS model. The percentage of variance
explained for the four outputs biomass concentration, the total number
of particles, biofilm average height and surface roughness range between
84-92\% and 97-99\% for univariate and multivariate emulators
respectively. The simulation-based sensitivity analysis identified
carbon substrate, oxygen concentration and maximum specific growth rate
for heterotrophic bacteria as the most critical variables for
predictions. The calibration results also indicated a general reduction
of uncertainty levels in most of the parameters. The study has helped us
identify the tradeoff in using different types of models for microbial
simulation. The approach illustrated here provides a tractable and
computationally efficient technique for calibrating the parameters of an
expensive computer model. Crown Copyright (C) 2018 Published by Elsevier
B.V.
Tags
calibration
Bayesian model
Mcmc
Biofilm
Dynamic linear model