This tutorial was developed during OceanHackWeek by members of the Marine Species Distribution Model group. It shows a simple workflow to develop a marine SDM focusing on the Arabian Sea and the Bay of Bengal.
Some experience programming in R
is needed to make the most of this tutorial. To run this tutorial make sure you clone this repository into your local machine by creating a new project that uses version control (git
).
The tutorial content was developed in a R
version 4.2.2 for Linux. Full session information is included below:
R version 4.2.2 (2022-10-31)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Debian GNU/Linux 11 (bullseye)
Matrix products: default
BLAS/LAPACK: /opt/conda/lib/libopenblasp-r0.3.21.so
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_4.2.2 tools_4.2.2
If you need additional support with R
programming, you can check the following resources:
R
for Data Science - 2nd edition by Wickham, Çetinkaya-Rundel and Grolemund.- Data analysis and visualisation in
R
for ecologists
For information on how to use git
and GitHub
with R
, Happy Git and GitHub for the useR by Jenny Bryan is a great resource.
-
Eli Holmes: Research Fisheries Biologist, Northwest Fisheries Science Center, NOAA Fisheries.
-
Mackenzie Fiss: Fifth-year PhD student at Northeastern University studying carbon cycling and microbial interactions in salt marshes
-
Mary Solokas: John A. Knauss Marine Policy Fellow, National Oceanic and Atmospheric Administration
-
Tylar Murray: USF IMaRS Software Engineer - code whisperer, data viz enthusiast, scientific generalist, compulsive overengineerer, & UX PhD
-
Collins Ongore
-
Denisse Fierro Arcos: PhD candidate at the Institute for Marine and Antarctic Studies (IMAS) and Data Officer at the Integrated Marine Observing System (IMOS)
Add updates, barriers, etc. as issues.
Jam Board/team formation
- eli: got the zarr file into R!
- caitlin:
- laura: familiarizing with data and getting species occurrence data into R
- paulo: learning about packages in R
- mackenzie: getting data from the zarr file into dataframes to make working with it easier
- mary: occurrence data and differentiating land and sea sitings
- jade: occurrence data and SDM nitty gritty