4.9. Mortality algorithm

mortality.algorithm defines the choice of the mortality algorithm (either ‘stochastic’ or ‘iterative’)

mortality.subdt is the number of mortality time-steps within one Osmose time step.

4.9.1. Stochastic algorithm

Main features of the stochastic algorithm are:

  • Every cause of mortality (predation, natural, fishing, starvation) competes with each other. The subdt in the mortality process ensures that the random order of the mortality sources within a cell does not bias the mortality outcome.

  • Stochasticity and competition within the predation process, meaning that the loop over the schools as preys or predators is random and what has been preyed upon by a predator is not available anymore to the other predators that come later in the loop.

  • Asynchronous updating of school biomass (it means biomass are updated on the fly).

4.9.2. Iterative algorithm

Main features of the iterative algorithm:

  • It is assumed that every cause is independant and concomitant

  • No stochasticity neither competition within predation process: every predator sees preys as they are at the beginning of the time-step.

  • Synchronous updating of school biomass (it means biomass are updated at the end of the mortality process)

By default Osmose will use the stochastic algorithm and this parameter should not be changed unless one knows exactly what he/she is doing. Detailed information on the mortality algorithm is available here