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Data-Driven Decision-Making: Antarctic Fisheries

Author(s): Jessie Golding1, Desiree Andersen1, Ellen Bledsoe1

University of Arizona

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Summary:
This is an entire module for a general education data science and ecology course. The module was originally designed as the fourth and final section of the course; the full course is openly available through the Biodiversity Data Science Corp,…

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This is an entire module for a general education data science and ecology course. The module was originally designed as the fourth and final section of the course; the full course is openly available through the Biodiversity Data Science Corp, funded by NSF (https://biodiversitydatasciencecorp.github.io/DataInTheWild_Website/). Incorporated topics include ecosystem services, sustainability, population growth, carrying capacity, maximum sustainable yield, traditional ecological knowledge and stewardship, and spatial data. Six lessons and two assignments are included. These lessons and assignments are designed for students who have experience using the R programming language. As written, the lessons use the `tidyverse` (specifically, `dplyr` and `ggplot`) but can be easily modified for base R or Python. This resource is also designed using the 4-Dimensional Ecology Education (4DEE) framework developed by the Ecological Society of America (https://www.esa.org/4dee/).

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