Overview
Through this application the user can implement two fisheries stock assessment models/approaches:
• the stochastic surplus production model in continuous time (SPiCT) [1] and
• the statistical catch-at-age stock assessment model developed as part of the assessment for all (a4a) [2].
The SPiCT application includes the two time-variant productivity extensions, allowing for gradually varying productivity or regimes of productivity [3]. The a4a assessment is modified to include environmental variability on recruitment though an external environmental index provided by the user. The application was developed in Shiny under the R language programming environment [4, 5] and is accessible at: http://shiny.her.hcmr.gr:50500/.
Documentation
SPiCT manual: https://github.com/DTUAqua/spict/raw/master/spict/inst/doc/spict_handbook.pdf Help files Test files, source code and official manuals for both approaches can be found https://cloudfs.hcmr.gr/index.php/s/yRqWk0zTTOCWbZT
Acknowledgments
This application is part of the PANDORA’s toolbox (https://www.ices.dk/pandora/Pages/default.aspx) developed as part of the PANDORA project https://www.pandora-fisheries-project.eu/
Developers
Contacts: Danai Mantopoulou-Palouka, Maria Kikeri, Vasiliki Sgardeli, Dimitrios Damalas [email protected], [email protected], [email protected],
References
[1] Pedersen, M.W., Berg, C.W. (2017). A stochastic surplus production model in continuous time. Fish and Fisheries, 18: 226-243.
[2] Jardim, E., Millar, C.P., Mosqueira, I., Scott, F., Osio, G.C., Ferretti, M., Alzorriz, N., Orio, A. (2015). What if stock assessment is as simple as a linear model? The a4a initiative. ICES Journal of Marine Science, 72: 232-236.
[3] Mildenberger, T.K., Berg, C.W., Pedersen, M.W., Kokkalis, A., Nielsen, J.R. (2020). Time-variant productivity in biomass dynamic models on seasonal and long-term scales, ICES Journal of Marine Science, 77(1): 174-187.
[4] R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
[5] Chang, W., Cheng, J., Allaire, J.J., Xie, Y., McPherson, J. (2020). shiny: Web Application Framework for R. R package version 1.5.0. https://CRAN.R-project.org/package=shiny
Disclaimer
This software is free to use for educational and demonstration purposes only and comes with absolutely no warranty. It is distributed under the MIT license.