The "EcoRanger" module of Ecopath allows entry of a range -- hence the name -- and mean/mode values for all the basic parameters, i.e., for the biomasses, consumption rates, production rates, ecotrophic efficiencies, and all elements of the diet compositions. Random input variables are then drawn using user-selected frequency distributions (uniform, triangular, normal or lognormal) for each parameter type, and the resulting model is then evaluated (based on user-defined criteria, and physiological and mass balance constraints).
The process is repeated in a Monte-Carlo fashion, and of the model runs that pass the selection criteria, the best-fitting one is chosen using a least square criterion. This best model can then be used for further analysis, and its characteristics can be studied. Notably, a global goodness-of-fit, RE, is calculated along with parameter-specific indices (re) for each of the model inputs. An integrated Sampling - Importance Resampling scheme places the EcoRanger in a Bayesian context.
The EcoRanger module thus introduces a statistically-based approach to fitting of Ecopath models, and most importantly it helps the user select the model that best fits a given set of constraints.