R codes for simulation testing variety of data poor/rare species estimation method < in preparation >
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Contributors: Kotaro Ono1*
1 Institute of Marine Research, Bergen, Norway.
* Corresponding author: kotaro.ono@hi.no
The purpose of this github repository is to create a spatially explicit simulation framework to generate more "realistic" data from the fishery which can then be used to test the performance of variety of estimation methods. The generated data could represent catches of targetted & non-targetted fish species but also bycatch of seabird/marine mammals i.e. any type of catch event that the user is interested in.
The model simulates the abundance in space of k number of species with each species having its own population and movement dynamics both in space and time (season). Fishery activity is based on theory of ideal free distribution where fishers distribute their effort based on the expected revenue of the fishing grounds 8with some randomness). The spatial extent of each fisher can be specified so that some might only fish in certain area of the simulated space. Primary sampling unit is then either a vessel or a haul and we can specify different level of sampling intensity depending on the scenario examined.
To configure the simulation to best match each study case, users are required to search & provide the necessary information on the species population characteristics (ref the excel help file to guide in the search of the parameter information) and fishery characteristics. Once the intial condition is set,post-hoc adjustments need to be made to refine the model (e.g. price and catchability values) to match the catch composition observed in the data, scale of the catches, and the amount of zero-inflation in the data per species.
In this repository, you will find the necessary R- and C++ code to run the simulation, and test a variey of data poor estimation models.
The code is available in the R/ folder and divided into different scripts. In short, the R/OM.R file specifies the scenario and runs estimation methods. The remaining scripts are utlity functions to run the spatial explicit population dynamics model under the conditions specified in R/OM.R or run the probabilistic sampling for data collection, and more.
Some models (i.e. the multispecies DFA ) are implemented using Template Model Builder (TMB) and the C++ code can be found in the src/ folder.
Documentation about the model will be added into the docs/ folder
Kotaro Ono - kotkot
This project is licensed under the GNU GPLv3 License - see LICENSE for details.
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