Conditioning IOTC Albacore OMs using the ABC approach

For the current suite of IOTC MSE work, the general approach to conditioning the required
set of Operating Models (OMs) has been to use the species-specic stock assessment model
structure as the basis for the OMs. A grid of model runs, formulated using a set of alternative
assumptions and inputs, is constructed around the base case assessment model. In [1] an
alternative and complementary approach was outlined where, instead of the assessment being
the basis for conditioning, a suite of possible prior states of historical dynamics and current
status are dened. The available, but mostly the more recent, data are included within
an estimation scheme built on emerging Approximate Bayesian Computation (ABC) and
Synthetic Likelihood (SL) concepts [2, 3]. The aim is to generate a distribution of current
abundance, mortality and status that is consistent with both the available data and the suite
of possible prior states of nature dened beforehand, some of them informed by the stock
assessment results. This set of recent dynamics can then be used to initialise the OMs used
to project the stock into the future, and test the candidate MPs.