Modelling beyond data is uninformative: a comment on State-space modelling reveals proximate causes of harbour seal population declines by Matthiopoulos et al.

Detailed models have the potential to reveal important processes underlying patterns in data. However, model fitting depends on the availability of sufficient data, and the results obtained from the models depend on detailed assumptions. In a recent paper, Matthiopoulos et al. fitted Bayesian state space models to a limited dataset and attempted to explain the recent trajectory of the harbour seal population in the Moray Firth, in northern Scotland. They went on to suggest that the results could help explain recent declines in other nearby populations. This Comment describes the implications of understating the uncertainty that the model required for convergence, questions the robustness of the results, highlights the differences between the areas, and cautions against extrapolating across these populations. The distinction between models that can be fitted to a dataset and those that provide useful information about the systems that generated the data is also considered.