How should I approach generating recommendations for fish stock management?
How should I approach generating recommendations for fish stock management?
Loading saved threads...
user18937561 · External communityPost link
External question — Data Science Stack Exchange
Author: user18937561
Original post: https://datascience.stackexchange.com/questions/122727
License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/
Adaptation: HTML converted to plain text; contact email addresses removed.
I've been asked to "Model and study the size and age composition of fish populations as dynamical systems for a given area and generate recommendations for seasonal fish stock management based on model output analysis."
The data I have available are taken from fishing reports and for each fishing trip I have the
species
of fish caught, the
weight
of fish caught, the
time
, the
location
, the
time spent fishing
and the
fishing gear
type used. Therefore, I understand that I may not be able to study the
age composition
of the stock, without the appropriate data.
The model and analysis shall include ocean temperatures, currents, salinity, meteorological and other available relevant and available data such as euphotic depth and dissolved oxygen concentrations.
How would you recommend I approach this project? Any advice on appropriate models to use will be greatly appreciated.
Quote
Report
lpounng · External communityPost link
External answer — Data Science Stack Exchange
Author: lpounng
Original post: https://datascience.stackexchange.com/a/122739
License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/
Adaptation: HTML converted to plain text; contact email addresses removed.
The first thing to ask is always, "
why
are we doing this?" Is it for sustainable fishing? Maximize the amount of fish caught? The purpose of the project leads to very different approach.
Second thing to ask is, "
what
are some possible recommendations, and what constraints are there?" It is a waste of time to recommend something at the end of project which is not executable.
The principle is NOT mess with all the data/models/buzzwords first, but set out to
understand the problem and background
. Have you discussed with the stakeholders (e.g. professor, business owner) about the project scope? What do you know about fishing population? Have you done your literature review on what have been done by others? What approach they took and what conclusion was drawn?
Garbage in, garbage out. Don't randomly dump some data in some model and pray - it just gives you garbage back. Not how data science works.
Quote
Report
Post Reply
Quoted from Forex.com.bd-Editorial External question — Data Science Stack Exchange Author: user18937561 Source score (net votes, not local likes): 0 Original post: https://datascience.stackexchange.com/questions/122727 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. I've been asked to "Model and study the size and age composition of fish populations as dynamical systems for a given area and generate recommendations for seasonal fish stock management based on model output analysis." The data I have available are taken from fishing reports and for each fishing trip I have the species of fish caught, the weight of fish caught, the time , the location , the time spent fishing and the fishing gear type used. Therefore, I understand that I may not be able to study the age composition of the stock, without the appropriate data. The model and analysis shall include ocean temperatures, currents, salinity, meteorological and other available relevant and available data such as euphotic depth and dissolved oxygen concentrations. How would you recommend I approach this project? Any advice on appropriate models to use will be greatly appreciated.
Checking account access…