Outputs and Observation

Outputs and Observation

This page introduces the main OSMOSE outputs and the tools used to transform simulated ecosystem states into quantities that can be analysed, plotted, or compared with data.

OSMOSE stores information at different levels of detail, from school-level state variables to population and ecosystem indicators. Because OSMOSE is an individual-based and spatially explicit model, outputs can often be aggregated in different ways depending on the scientific question, the spatial and temporal resolution needed, and the type of data used for comparison.

Observation is treated as a specific part of the OSMOSE workflow. At the Java level, the Observation Module provides tools to simulate surveys as observers of the state of the ecosystem. These observers can filter the model state according to survey properties such as spatial coverage, timing, selectivity, and target groups. In addition, R post-processing tools allow users to work with outputs at different aggregation levels, including taxonomic aggregation, functional groups, spatial regions, time periods, size classes, and other derived indicators.

Pages in this topic

• Standard outputs
  Describes the outputs commonly produced by OSMOSE simulations and used in most applications.

• Optional outputs
  Describes additional outputs that can be activated depending on the objectives of the simulation, such as detailed trophic flows, predation information, or diagnostic outputs.

• School-level outputs
  Describes outputs at the level of schools, the elementary simulation units in OSMOSE.

• Population indicators
  Describes indicators computed at the species or population level, such as biomass, abundance, catch, size structure, or age structure.

• Ecosystem indicators
  Describes indicators computed at the ecosystem or community level, such as trophic indicators, size spectra, biodiversity indicators, or aggregated biomass by group.

• Survey filtering and Selectivity
  Describes how simulated surveys can filter the ecosystem state by area, time, species, size, or other sampling characteristics. It also describes how size selectivity and catchability can be used to make simulated outputs more comparable with survey or fishery data.

• Aggregation
  Describes how outputs can be aggregated after the simulation, including taxonomic aggregation, functional grouping, spatial aggregation, temporal aggregation, and aggregation by size or age classes.

Observation and post-processing workflow

The observation workflow can be understood as two complementary steps.

First, the core simulator can produce outputs through observers that access the state of the ecosystem during the simulation. This is useful when the objective is to reproduce the structure of a survey or observation process directly during model execution.

Second, the R package can read and post-process simulation outputs to produce derived quantities, diagnostic plots, and indicators at different aggregation levels. This step is especially useful when analysing model results, preparing calibration data, comparing simulations with observations, or producing scenario summaries.

Users who want to understand what OSMOSE produces should start with Standard outputs and Population indicators.

Users working with survey data, calibration, or model-data comparison should read the pages on Survey filtering and Selectivity and Aggregation.

For technical details on the Java-level observer system, see Observation Module. For practical tools to read, analyse, and plot outputs, see Reading outputs and Analysing and plotting results.