We were interested in problems of overfishing, and found out that in Alaskan waters, there is a quota imposed on Halibut (a type of fish) catches to counter such problems. Different fishing zones have different quota.

What it does

It is a tool to predict fish stock quota in different fishing zones through 2020, based on sea surface temperature and historical allocations across the fishing zones. Fishing companies can estimate how much resources to allocate to fishing Halibut in these waters, so that excess resources can be used to catch other types of fish in other areas. This helps to balance conservation efforts (by meeting the quota), and gives fishing companies the flexibility to adapt to these quota requirements.

How we built it

We use R, with CartoDB to provide the maptiles. The fishing zones are dictated by the IPHC, from which we also got the shp files for the zones. We use Shiny to make the app interactive, so that users can see historical quotas in different zones from 1993 onwards. PlanetOs is used to obtain sea surface temperatures in the area, with the annual average used to create a model to predict quotas in the future. If there are changes in the estimate of the sea surface temperatures, the user can toggle the temperature through a slider input.

Challenges we ran into

It was challenging to dynamically update the estimated quotas in the regions.

Accomplishments that we're proud of

An app that looks functional, using multiple platforms (mostly sponsors at the event)

What we learned

About overfishing issues in the region, also integrating information together into a workable app.

What's next for HalibutCatch

Create a more accurate predictive model using factors that go beyond sea surface temperature.

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