Predictive capacity of Ecopath with Ecosim: Model performance and ecological indicators' response to imprecision. (September 2021)

• Record Type: Journal Article
• Authors: Susini, Irene; Todd, Victoria L.G.
• Is Part Of: Environmental modelling & software. Volume 143(2021)
• Publication Date: 2021-09
• Subjects: Ecosystem modelling -- Ecosystem-based management -- Model performance -- Ewe -- Uncertainty -- Monte Carlo; EwE Ecopath with Ecosim -- SA Sensitivity Analysis -- LSA Local Sensitivity Analysis -- GSA Global Sensitivity Analysis -- OAT One-At-a-Time -- ECOIND Ecological Indicators -- B Biomass -- EE Ecotrophic Efficiency -- P/B Production-to-Biomass ratio -- Q/B Consumption-to-Biomass ratio -- mTLco mean Trophic Level of the community -- TST Total System Throughput -- CI Confidence Interval -- CV Coefficient of Variation -- RMSE Root-Mean-Square Error -- SI Sensitivity Index -- TL Trophic Level; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2021.105098
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The ecosystem modelling complex 'Ecopath with Ecosim' has been implemented extensively in the field of marine science; however, despite its widespread application, descriptions of its functionality remain arcane in the literature. This study conducts an evaluation of the software's prediction capacity using eight published Ecopath models. Response of six ecosystem-status indicators to four basic input variables to which imprecision had been added was investigated. Kempton's Q Index and total system throughput emerged as the most consistently responsive parameters. Moreover, input biomass was identified as a 'high-leverage' parameter, its influence on outputs being greater than that exerted by any other input variable. This study constitutes one of the first comprehensive investigations of the response of selected outputs to imprecise input values, and provides sufficient basis to warrant a sensitivity assessment of the software, as well as introduction of a dedicated tool to perform such a task within Ecopath with Ecosim. Highlights: We assess the prediction precision of Ecopath with Ecosim (EwE) software. We investigate six ecosystem indicators' response to imprecision under 61 modelling scenarios. We identify Kempton's Q and Total System Throughput as the most responsive indicators. We identify input biomass and production-to-biomass as high-leverage parameters; and. We highlight disadvantages of Monte Carlo routine usage for EwE model balancing.