Spatial and sequential stock depletion through increased fisher mobility: An agent-based modeling approach

Presenter: Emilie Lindkvist

Part of the Session on Fisheries



Hi! Great approach! I am also very interested in pursuing social-ecological modelling in coastal systems in the very near future, so this is a very interesting model to look at. I am wondering if you have time series data to validate these movements. If so, how do you intend to extract the mechanism from the observed patterns? Is it just a matter of comparing profits, from what you learned through interviews? How do you establish the probability of meeting with someone else to compare profits and making the decision to move? That seems hard to put a value on, so I was wondering where that came from.

Loved the talk and the model! I will be very interested in following the beta beta model until the full release version. :slight_smile:

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Interesting talk. Like Miquel I wondered whether the empirical data also showed those cycles. I can imagine you get those cycles when agents move to the locations that give the highest returns, but fishers have also movement costs (and they do live at different locations). Is this included and will this reduce the fluctuations, or are transportation costs small compared to the returns?

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Hi and thanks Miguel! 1) time series for validation. We do have some data for movement of fishers that we hope to validate the model against, but we are in the middle of analyzing those data and have not developed the model far enough to make that validation. 2) To understand the mechanisms at play will take a lot of model sensitivity analysis, different scenarios, and other decision models for the fishers as well as additional dynamics for the fish stocks. Specifically we will add seasonality of the different fisheries as this seems to be the key driver of mobility in the Gulf. (as extracted from fisher interview data) 3) It is NOT a matter of comparing profits, this behavior will be modified as the model develops. The profit maximizer might be used as to initially understand some behavior of the model and perhaps to contrast our findings to some assumptions. 4) the profit comparing function is a standard function, and is only based on theory see e.g. Morgan 2003, Pairwise competition and the replicator equation. Let’s stay in touch, I’ll be happy to have a Skype or alike. Best Emilie

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Hi Marco, thanks for your questions. As I responded to Miguel, 1) We don’t have time series for the movement of fishers. Data on that to show exact mobility patterns of fishers are not available, but through interviews we know where fishers go and what species they target in those locations. We have landings of species though which may be able to serve as a point of validation on the marine resources. 2) Our data analysis show that fishers that migrate more long-term do this to follow stocks by seasonality primarily. We are working on incorporating this behavior as key rather than following the returns. 3) the costs of traveling are not small in relation to the returns short term, but for long-term those costs would be smaller in comparison of course, but we have not looked into this empirically nor in the model - but it is on the list!

Many steps left before we get this model to its final state, so thanks for your comments and we will keep on working! Best, Emilie

Hi Emilie,
I like your model, very interesting setting! It reminds me the famous Fishbanks game of Dennis Meadows, where there are only two fishing zones (costal and deep-sea) with the two corresponding fish stocks being independant. Is it the case also in your model (no fish migration between zones)?
Your work reminds me also a theoretical agent-based model that was designed to understand the key role of dynamics of fishing effort in predicting the impacts of regulatory measures on fisheries. This model had four fishing zones, like your prototype. See


Great model! I built an ABM to explore the environmental and market impacts of illegal, unreported, unregulated (IUU) fishing. How did you handle the schooling, movement, and reproductive habits of fish in your model? I know you use a relatively long timestep that makes this less relevant, but I wonder if you have data sources for fish behavior that you can share. In my model, I used an existing schooling ABM, but it took a huge toll on my machine’s memory. I then used available information on one type of fish with a fairly long gestation period, but that doesn’t account for the diversity of fishery. I’d love your thoughts on how to balances these factors.

Hi! thanks for the literature tip! The theoretical ABM is really useful, I had it on my radar. And now looking closer it seems to be an excellent paper to have to compare a bit results etc.

We are not yet including species movement between areas, but have discussed quite a bit how to do this and reasons for why/why not include it. For example, in general species move less than 100km and our areas are bigger than this, so this motivates not including fish migration between the areas. However the edge effect could be a reason to include some spillover. Also, some larger shark for example move up to 1000km but they are not a key specie to the small-scale fishers, but still we might learn that some species overlap between areas and could be considered belonging to the same stock. As the model moves we will see where we land on this matter but right now we don’t have it in the model, so you got it right!

Thanks again for your comments and for watching!


Hi Kyllard! Do you have a link to your model, or a description of it? I am really interested in the IUU aspects. We account for it only as a factor for each specie adding on to reported catch.
As for schooling and related stock behaviour etc, we only use the most simple logistic growth model, the Gordon-Schaeffer model. Which does not include schooling. Using this model means that in each of the four areas there is x number of fish stocks all represented by a specific growth model, parameterized by yearly r, K and current stock size. We got this data from a work in progress paper by a colleague that builds on Froese et al. 2017. There are no food web dynamics and growth is averaged out per month. So, with that said I cannot help on the schooling issue, but only wonder how important it is to your over all research question!
Also, since we look at longer effects of harvesting, we do not include the issue of finding the fish, fishers always find the fish.

Best emilie

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I’d also love to see that ABM.

Sorry for the delay. I just posted the model to OpenABM here: It was published through the 2016 SBP-BRiMS conference. Send me an email and I can send you a copy of the publication: [email protected].

I realize there are several issues with the model, not least of which is the type of fish and behaviors I claim to model. I realize now Grouper are not schooling fish the way I’ve modeled. I chose Grouper for the long gestation and lifespan, but the behavior in the model is not perfect. I wanted schooling to be featured in the model to explore how overfishing shifts the physical location of a fishery, drawing boats further out to sea; thus impacting input costs etc. In the future, I’d like to explore how the geography of fisheries contribute to international disputes such as in the South China Sea.

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