3 Work Package 3: Evaluating and testing of long-term management strategies
3.1 Evaluating the utility of a Novel Harvest Control Rule in the management of long-lived sporadically recruiting species through Management Strategy Evaluation
Cian Kelly (UiB), Mikko Heino (UiB), Daniel Howell (IMR)
2019-08-16
The code for the masters thesis work with the above title. Contains a Novel HCR, which reflected an Escapement HCR, was tested on a stock whose dynamics was informed by Greenland halibut (Reinhardtius hippoglossoides). The code is implemented as a modification of the FLBEIA software (https://github.com/flr/FLBEIA).
Download (software): cian-flbeia_alternative.zip
Related identifiers: https://bora.uib.no/bora-xmlui/handle/1956/20734
3.2 Ecological effects and ecosystem shifts caused by mass mortality events on early life stages of fish
Holly Perryman (IMR; https://orcid.org/0000-0001-9341-682X), and Ina Nilson (University of Bergen/IMR)
2019-11-06
The following deposition contains scripts for creating the figures in Olsen et al. (2019). This deposition includes example files for executing the code. The files are inputs and outputs to/from the Norwegian and Barents Seas Atlantis model.
Jupyter notebook: (show) (download)
Download (software): holly-MMEmanuscript477196.R
Related identifiers: https://doi.org/10.3389/fmars.2019.00669
References: Olsen, E., Eide, C.H., Nilsen, I., Perryman, H.A. and Vikebø, F., 2019. Ecological effects and ecosystem shifts caused by mass mortality events on early life stages of fish. Frontiers in Marine Science, 6, p.669.
Keywords: Atlantis; marine ecosystem model; data processing; biomass trends; spider plots
3.3 Atlantis-R interface
Ibrahim Umar (IMR), Holly Perryman (IMR), Rebecca Gorton (CSIRO), Elizabeth A. Fulton (CSIRO)
2019-10-24
The marine ecosystem model Atlantis is structured following the MSE framework, meaning Atlantis simulates both the operating model and the management procedure. This is an advantageous feature for simulating MSE under and ecosystem-based context, however it may be cumbersome to program complicated/specific management procedures into Atlantis. To integrate Atlantis into the REDUS framework, Atlantis was programmed to send/receive data back and forth with the statistical software R. With this new functionality, Atlantis can be treated solely as an operating model while R is used to simulate the management procedure. Thus, management procedures previously programmed in R can now be simulated under an ecosystem-based context within Atlantis.
License: LGPL3 + CSIRO-proprietary
URL (software): https://git.imr.no/REDUS/atlantis-code
Keywords: ecosystem, MSE, simulation, C, marine, box, model, multi-species, biogeochemical, physical
3.4 GadgetR
Ibrahim Umar (IMR), Bjarki Thor Elvarsson (Hafro), James Begley (Hafro), Hoskuldur Bjornsson (Hafro), Gunnar Stefnasson (Hafro), Lorna Taylor (Hafro), Daniel Howell (IMR), Sigurdur Hannesson (Hafro), Narfi Stefansson (Hafro), Hersir Sigurgeirsson (Hafro), Morten Nygard Asnes (IMR), Kristin Froysa (IMR), Audbjorg Jakobsdottir (Hafro), Jon Gudmundsson (Hafro), Gudmundur Einarsson (Hafro), Thordis Linda Thorarinsdottir (Hafro), Kristjana Yr Jonsdottir (Hafro), Mark G. Johnson (US-EPA), Bill Goffe (USM)
2018-06-21
GadgetR is an R library that allows users to create a two-way interface to the simulation function (via a “gadget -s” command line switch) of Hafro’s Globally applicable Area Disaggregated General Ecosystem Toolbox (Gadget) program. To simply put, GadgetR provides users flexibility to explicitly control gadget simulation steps, and inspect and modify (as needed) gadget internal objects (such as recruitment parameters, fleet consumption amount, among others) at any point in time during the simulation. These functionalities are especially useful when you want to use a gadget model as an operating model (single or multi- species) in existing management strategy (MSE) frameworks in R (FLR/mse or FLBEIA). GadgetR ships with the latest Gadget program (version 2.2.00-BETA) and retains all of the original Gadget program functionality.
License: GPL2
URL (software): https://github.com/REDUS-IMR/gadget
Related identifiers: https://redus-imr.github.io/gadget/articles/quickstart.html
Keywords: simulation, optimization, multi-species, stock, gadget ecosystem, R, C++, MSE
3.5 Multi Fleet Deterministic Projection (MFDP)
Ibrahim Umar (IMR)
2020-12-18
Program for the fisheries short-term prediction. Allows for multi-fleet catch constraints and multi-annual prediction. This program is an attempt to re-create the original Multi Fleet Deterministic Projection (MFDP) program for fisheries in R.
License: LGPL3
Jupyter notebook: (show) (download)
URL (software): https://github.com/REDUS-IMR/mfdp
Keywords: mfdp, fisheries, forecast, multi-year, REDUS, IMR
3.6 MSE Framework
Ibrahim Umar (IMR), Daisuke Goto (IMR), Alfonso Perez Rodriguez (IMR)
2019-03-14
FLR-Gadget is a Management Strategy Evaluation (MSE) framework using FLR (The Fisheries Library in R) mse (https://github.com/flr/mse) with an R package of customized Gadget (Globally applicable Area Disaggregated General Ecosystem Toolbox, https://github.com/Hafro/gadget2), GadgetR (https://github.com/REDUS-IMR/gadget), as an operating model (OM). This framework is designed to run single and multi- species MSEs. The OM can be age- or length- based. The framework runs short-cut and full-feedback MSEs. Currently, a4a (Assessment for All, https://github.com/flr/FLa4a) statistical catch-at-age model and SAM (State-space Assessment Model, https://github.com/flr/FLSAM) are implemented as an assessment model.
License: LGPL3
Jupyter notebook: (show) (download)
URL (software): https://github.com/dgoto2/flr-gadget
Keywords: IMR, REDUS, FLR, MSE, multi-species, simulation, framework, R, fisheries, gadget
3.7 mse-bootstrap-gcp
Ibrahim Umar (IMR), Jennifer Devine (IMR), Daisuke Goto (IMR)
2019-02-24
Scripts for running the North Sea Saithe Management Strategy Evaluation (MSE) on Google Cloud Platform (GCP)
License: LGPL3
URL (software): https://github.com/REDUS-IMR/mse-bootstrap-gcp
Keywords: IMR, REDUS, bash, GCP, MSE, North Sea Saithe, simulation, parallel
3.8 North Sea saithe Management Strategy Evaluation (MSE)
Jennifer Devine (IMR), Daisuke Goto (IMR), Ibrahim Umar (IMR), Colin Millar (ICES), Jose De Oliveira (CEFAS), Simon Fischer (CEFAS)
2019-06-17
A management strategy evaluation (MSE) framework for North Sea saithe (Pollachius virens) in Subareas 4, 6 and Division 3.a (North Sea, Rockall and West of Scotland, Skagerrak and Kattegat) developed using the Fisheries Library in R mse package as part of the Workshop on North Sea stocks Management Strategy Evaluation (WKNSMSE).
URL (software): https://github.com/ices-taf/wk_WKNSMSE_pok.27.3a46
Related identifiers: https://doi.org/10.17895/ices.pub.5090
Keywords: mse, saithe, ices, north sea, R, FLR, REDUS, IMR