1. Individual based models (IBMs) allow realistic and flexible modelling
of ecological systems, but their parametrization 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 parametrization 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 parametrization 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 for parametrizing complex IBMs with multiple data
sources, and assessing the dynamics of the population in a robust manner. Source code and
dataThe package provides
Matlab code for the individual based model and approximate Bayesian
computation based inference introduced in article "Assessing the
dynamics of natural populations by fitting individual based models with
approximate Bayesian computation" by Jukka Sirén, Luc Lens, Laurence
Cousseau and Otso Ovaskainen accepted for publication in Methods in
Ecology and Evolution. The package includes also the White-starred robin
data analyzed in the article.Code.zip