Assessing the dynamics of natural populations by fitting individual-based models with approximate Bayesian computation
Authored by Luc Lens, Otso Ovaskainen, Jukka Siren, Laurence Cousseau
Date Published: 2018
DOI: 10.1111/2041-210x.12964
Sponsors:
No sponsors listed
Platforms:
MATLAB
Model Documentation:
ODD
Mathematical description
Model Code URLs:
https://datadryad.org/resource/doi:10.5061/dryad.851jr
Abstract
1. Individual-based models (IBMs) allow realistic and flexible modelling
of ecological systems, but their parameterization with empirical data is
statistically and computationally challenging. Approximate Bayesian
computation (ABC) has been proposed as an efficient approach for
inference with IBMs, but its applicability to data on natural
populations has not been yet fully explored.
2. We construct an IBM for the metapopulation dynamics of a species
inhabiting a fragmented patch network, and develop an ABC method for
parameterization of the model. We consider several scenarios of data
availability from count data to combination of mark-recapture and
genetic data. We analyse both simulated and real data on white-starred
robin (Pogonocichla stellata), a passerine bird living in montane forest
environment in Kenya, and assess how the amount and type of data affect
the estimates of model parameters and indicators of population state.
3. The indicators of the population state could be reliably estimated
using the ABC method, but full parameterization was not achieved due to
strong posterior correlations between model parameters. While the
combination of the data types did not provide more accurate estimates
for most of the indicators of population state or model parameters than
the most informative data type (ringing data or genetic data) alone, the
combined data allowed robust simultaneous estimation of all unknown
quantities.
4. Our results show that ABC methods provide a powerful and flexible
technique forparameterizing complex IBMs with multiple data sources, and
assessing the dynamics of the population in a robust manner.
Tags
individual-based models
Population dynamics
calibration
ecology
statistics
Protocol
Inference
Forest
Parameters
Approximate bayesian computation
Metapopulation dynamics
Abundance
Chain monte-carlo
Fragmented landscape
Multiple data sources