This project was developed during OceanHackWeek 2024 with the goal of creating an interactive tool using R to show the predicted distribution of some iconic Gulf of Maine species.
Biological
We obtained species occurrence data from the Ocean Biodiversity Information System (OBIS) via the robis package. Since absences were not recorded in this data, we generated 1000 random background points (pseudo-absences).
Environmental
We obtained environmental data from Bio-ORACLE and used the stars package to wrangle the raster files.
We used predictions of future environmental conditions from the Atmosphere/Ocean General Circulation Model (AOGCM).
- Gather species occurrence data
We first defined our spatio-temporal bounds, using the latitude-longitude boundaries of (42, -71, 45, -64) to define our Gulf of Maine area of interest, and time boundaries of 2000-2020. Then, we cropped our occurrence data to fit these bounds and created a binary presence/absence column for analysis, using 1000 background points as absences. We also made a function to gather species data from OBIS using a section called "species" so that we could create models for more than one species.
- Gather observational environmental data
We picked some environmental variables we were interested in, including surface temperature, bottom temperature, surface salinity, bottom salinity, and surface chlorophyll concentration. We then found these variables in our set bounds.
- Prep data for model
We created a YAML file with the names of species, latitude-longitude boundaries, start and end years for data, and all the environmental covariate layers we wanted to include to make it easy for our function to pull the data it needed (rather than us having to input it every time). We then created functions to call data from the YAML file into the model.
- Make model
Using the maxnet package and our occurrence and environmental dataframes, we created a logistic model to plot response curves.
- Predict and visualize
We selected the AOGCM climate model and scenarios RCP26, RCP45, RCP60, and RCP85 to predict future environmental conditions for our area of interest, and concatenated the environmental data raster files into a raster stack. Then, we plotted the suitability of the environment for the species on a scale of 0-1 (1 being most suitable). We took the raster image for this plot and used the leaflet package to put it on a geographical map.
- Develop tool
Lastly, we created an R Shiny app to make our model accessible and interactive. We added dropdown boxes for users to select from five different species, year (current, 2050, or 2100), and climate scenarios to visualize SDMs on a map for their selected inputs.
| Name | Role |
|---|---|
| Ben Tupper | Project Mentor |
| Camille Ross | Project Mentor |
| Hallie Arno | Participant |
| Jessie Maguire | Participant |
| Mugdha Chiplunkar | Participant |
Data
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OBIS (2023) Ocean Biodiversity Information System. Intergovernmental Oceanographic Commission of UNESCO. www.obis.org. Accessed: 2024-08-27
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Assis, J., Fernández Bejarano, S.J., Salazar, V.W., Schepers, L., Gouvêa, L., Fragkopoulou, E., Leclercq, F., Vanhoorne, B., Tyberghein, L., Serrão, E.A., Verbruggen, H., De Clerck, O. (2024) Bio-ORACLE v3.0. Pushing marine data layers to the CMIP6 Earth system models of climate change research. Global Ecology and Biogeography. DOI: 10.1111/geb.13813. Accessed: 2024-08-27
Packages
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Provoost P, Bosch S (2022). robis: Ocean Biodiversity Information System (OBIS) Client. R package version 2.11.3, https://CRAN.R-project.org/package=robis.
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Bosch S, Fernandez S (2023). sdmpredictors: Species Distribution Modelling Predictor Datasets. R package version 0.2.15, https://CRAN.R-project.org/package=sdmpredictors.
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Phillips S (2021). maxnet: Fitting 'Maxent' Species Distribution Models with 'glmnet'. R package version 0.1.4, https://CRAN.R-project.org/package=maxnet.
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Pebesma E (2021). stars: Spatiotemporal Arrays, Raster and Vector Data Cubes. R package version 0.5-5, https://CRAN.R-project.org/package=stars.
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Cheng J, Karambelkar B, Xie Y (2022). leaflet: Create Interactive Web Maps with the JavaScript 'Leaflet' Library. R package version 2.1.1, https://CRAN.R-project.org/package=leaflet.
Other
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Wikipedia contributors. "Representative Concentration Pathway." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 15 Aug. 2024. Web. Accessed: 2024-08-30
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“Cetorhinus Maximus.” Discover Fishes, www.floridamuseum.ufl.edu/discover-fish/species-profiles/cetorhinus-maximus/. Accessed 30 Aug. 2024.
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Fisheries, NOAA. “Longfin Squid.” NOAA, 22 Aug. 2024, www.fisheries.noaa.gov/species/longfin-squid.