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FishCensus Model
FishCensus is an agent-based model that simulates underwater visual census of fish populations, a method used worldwide to survey shallow marine and freshwater habitats that involves a diver counting fish species to estimate their density. It can help estimate sampling bias, apply correction factors to field surveys and decide on the best method to survey a particular species, given its behavioural traits, detectability or speed. A modified vector-based boids-like movement submodel is used for fish, and complex behaviours such as schooling or diver avoidance / attraction can be represented.
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How it works
The FishCensus model comes with two separate programs. The Species Creator is used to create new fish species or observe/edit existing ones. Species parameters can be exported as a .csv file and imported into the main model where the simulation happens.
In the main FishCensus program, a virtual diver uses a pre-selected survey method (e.g. fixed distance or timed transect, stationary point counts) to count the fish and estimate their density. The true density of fish is pre-determined and known, which allows for the quantification of bias, a measure that is unknown in the field, where determining the true abundance is very difficult.
For a quick start guide, go to the tutorial page of this wiki.
Installation and documentation
FishCensus is programmed in NetLogo, a program and language specifically at building agent-based models. Installation is very easy and straightforward:
- Download and install NetLogo 5.3.1;
- Get the latest stable release of the FishCensus model from OpenABM;
- Get the "rnd" folder from the "required NL extensions folder you find in the model package and move it to your NetLogo 5.3.1/app/extensions folder.
- Open the FishCensus.nlogo file to run the model with existing species, or
- Open the FishCensus Species Creator.nlogo file to create and export your own species!
Copyright, citation and contacts
If you use this model, please cite the original publication:
Pais, M.P., Cabral,H.N., 2017. Fish behaviour effects on the accuracy and precision of underwater visual census surveys. A virtual ecologist approach using an individual-based model. Ecological Modelling 346, 58-69.
Please check the model page at OpenABM for instructions on how to cite the model itself.
Copyright 2016 Miguel Pessanha Pais
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
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