Sensitivity analyses: Delving more deeply into the modelling framework

Published on
April 3, 2017

ESR Update - Sensitivity analyses can be defined as the investigation of how the uncertainty in the output of a model can be attributed to different sources of input in the model. In the context of this model, it refers to understanding how the parameters and states (input) of the model influence the optimized values (output) from the genetic algorithm. More specifically, we wanted to investigate the influence of release strategies on the selection of life history parameters by the genetic algorithm.

Author: Wouter Plouvier, MSc.