From 4cb12db50e911194d2fda6ac702e8946e9d42009 Mon Sep 17 00:00:00 2001
From: Laura Brenskelle <160157051+laurabrenskelle@users.noreply.github.com>
Date: Fri, 13 Sep 2024 11:38:38 -0400
Subject: [PATCH 01/15] Update environment-python_and_r.yml
Adding dplyr and gh R packages
---
.binder/environment-python_and_r.yml | 2 ++
1 file changed, 2 insertions(+)
diff --git a/.binder/environment-python_and_r.yml b/.binder/environment-python_and_r.yml
index 6442dad6..8db45885 100644
--- a/.binder/environment-python_and_r.yml
+++ b/.binder/environment-python_and_r.yml
@@ -73,10 +73,12 @@ dependencies:
# R packages.
- rpy2
- r-base=4
+ - r-dplyr
- r-dt
- r-finch
- r-ggfortify
- r-ggplot2
+ - r-gh
- r-gsw
- r-httr
- r-irkernel
From 3e07a6153542bc50625b08517fefdb377ea685cc Mon Sep 17 00:00:00 2001
From: Laura Brenskelle <160157051+laurabrenskelle@users.noreply.github.com>
Date: Fri, 13 Sep 2024 12:40:55 -0400
Subject: [PATCH 02/15] Add files via upload
---
.../OBIS_EOVs.ipynb | 257 ++++++++++++++++++
1 file changed, 257 insertions(+)
create mode 100644 jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/OBIS_EOVs.ipynb
diff --git a/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/OBIS_EOVs.ipynb b/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/OBIS_EOVs.ipynb
new file mode 100644
index 00000000..57918a19
--- /dev/null
+++ b/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/OBIS_EOVs.ipynb
@@ -0,0 +1,257 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "ad98f7a1-d7a1-4a51-a9a2-0da9da7fe042",
+ "metadata": {},
+ "source": [
+ "# Using aphiaIDs to download OBIS occurrences for Bio/Eco EOVs\n",
+ "\n",
+ "Created: 2024-09-13"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "390bf2be-3828-4705-b64b-ed68005ff98b",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "library(gh)\n",
+ "library(readr)\n",
+ "library(robis)\n",
+ "library(dplyr)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "43964864-7fe8-4139-a9d0-2a844161ccd1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# first we will pull the files where the EOV taxonomy are stored from GitHub\n",
+ "repo_files <- gh(\"GET /repos/:owner/:repo/contents/:path\",\n",
+ " owner = \"ioos\",\n",
+ " repo = \"marine_life_data_network\",\n",
+ " path = \"eov_taxonomy\")\n",
+ "\n",
+ "for (file_info in repo_files) {\n",
+ " if (file_info$type == \"file\") {\n",
+ " download.file(file_info$download_url, destfile = file_info$name)\n",
+ " }\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "0bb6ab17-d239-410c-90d0-dcb50359b095",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# let's try mangroves as our first example\n",
+ "# we will open the mangroves taxonomy CSV that we downloaded and grab the taxonIDs\n",
+ "mangroves <- read.csv(\"mangroves.csv\")\n",
+ "mangroves$ID <- gsub(\"urn:lsid:marinespecies.org:taxname.\", \"\", mangroves$acceptedTaxonId)\n",
+ "mangroves$ID <- as.numeric(mangroves$ID)\n",
+ "mangroveIdentifiers <- paste(mangroves$ID, collapse = \", \")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "d9aa2697-4ca0-4631-8d77-b0407e7a73b5",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Retrieved 5000 records of approximately 132901 (3%)\n",
+ "Retrieved 10000 records of approximately 132901 (7%)\n",
+ "Retrieved 15000 records of approximately 132901 (11%)\n",
+ "Retrieved 20000 records of approximately 132901 (15%)\n",
+ "Retrieved 25000 records of approximately 132901 (18%)\n",
+ "Retrieved 30000 records of approximately 132901 (22%)\n",
+ "Retrieved 35000 records of approximately 132901 (26%)\n",
+ "Retrieved 40000 records of approximately 132901 (30%)\n",
+ "Retrieved 45000 records of approximately 132901 (33%)\n",
+ "Retrieved 50000 records of approximately 132901 (37%)\n",
+ "Retrieved 55000 records of approximately 132901 (41%)\n",
+ "Retrieved 60000 records of approximately 132901 (45%)\n",
+ "Retrieved 65000 records of approximately 132901 (48%)\n",
+ "Retrieved 70000 records of approximately 132901 (52%)\n",
+ "Retrieved 75000 records of approximately 132901 (56%)\n",
+ "Retrieved 80000 records of approximately 132901 (60%)\n",
+ "Retrieved 85000 records of approximately 132901 (63%)\n",
+ "Retrieved 90000 records of approximately 132901 (67%)\n",
+ "Retrieved 95000 records of approximately 132901 (71%)\n",
+ "Retrieved 1e+05 records of approximately 132901 (75%)\n",
+ "Retrieved 105000 records of approximately 132901 (79%)\n",
+ "Retrieved 110000 records of approximately 132901 (82%)\n",
+ "Retrieved 115000 records of approximately 132901 (86%)\n",
+ "Retrieved 120000 records of approximately 132901 (90%)\n",
+ "Retrieved 125000 records of approximately 132901 (94%)\n",
+ "Retrieved 130000 records of approximately 132901 (97%)\n",
+ "Retrieved 132901 records of approximately 132901 (100%)\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "132901"
+ ],
+ "text/latex": [
+ "132901"
+ ],
+ "text/markdown": [
+ "132901"
+ ],
+ "text/plain": [
+ "[1] 132901"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# using the taxonIDs from the last step, let's search OBIS for occurrence data for this EOV\n",
+ "# this will take a bit to download because there were over 130k records when this script was written in Sept 2024\n",
+ "mangrove_occ <- robis::occurrence(taxonid = mangroveIdentifiers)\n",
+ "# let's check how many occurrences we got from OBIS\n",
+ "nrow(mangrove_occ)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1ccc9837-4585-4020-852b-cdc6b33ae62d",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1] \"235048, 235033, 234450, 234495, 235086, 235089, 235091, 235106, 235056, 235060, 235045, 235116, 235063, 235072, 235075, 235077, 235068, 234488, 235103\"\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Retrieved 5000 records of approximately 132901 (3%)\n",
+ "Retrieved 10000 records of approximately 132901 (7%)\n",
+ "Retrieved 15000 records of approximately 132901 (11%)\n",
+ "Retrieved 20000 records of approximately 132901 (15%)\n",
+ "Retrieved 25000 records of approximately 132901 (18%)\n",
+ "Retrieved 30000 records of approximately 132901 (22%)\n",
+ "Retrieved 35000 records of approximately 132901 (26%)\n",
+ "Retrieved 40000 records of approximately 132901 (30%)\n",
+ "Retrieved 45000 records of approximately 132901 (33%)\n",
+ "Retrieved 50000 records of approximately 132901 (37%)\n",
+ "Retrieved 55000 records of approximately 132901 (41%)\n",
+ "Retrieved 60000 records of approximately 132901 (45%)\n",
+ "Retrieved 65000 records of approximately 132901 (48%)\n",
+ "Retrieved 70000 records of approximately 132901 (52%)\n",
+ "Retrieved 75000 records of approximately 132901 (56%)\n",
+ "Retrieved 80000 records of approximately 132901 (60%)\n",
+ "Retrieved 85000 records of approximately 132901 (63%)\n",
+ "Retrieved 90000 records of approximately 132901 (67%)\n",
+ "Retrieved 95000 records of approximately 132901 (71%)\n",
+ "Retrieved 1e+05 records of approximately 132901 (75%)\n",
+ "Retrieved 105000 records of approximately 132901 (79%)\n",
+ "Retrieved 110000 records of approximately 132901 (82%)\n",
+ "Retrieved 115000 records of approximately 132901 (86%)\n",
+ "Retrieved 120000 records of approximately 132901 (90%)\n",
+ "Retrieved 125000 records of approximately 132901 (94%)\n",
+ "Retrieved 130000 records of approximately 132901 (97%)\n",
+ "Retrieved 132901 records of approximately 132901 (100%)\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "132901"
+ ],
+ "text/latex": [
+ "132901"
+ ],
+ "text/markdown": [
+ "132901"
+ ],
+ "text/plain": [
+ "[1] 132901"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "\t\n",
+ "\t\t\n",
+ "\t\t\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\t\n",
+ "\t\n",
+ "\t\t\n",
+ "\n",
+ "\t\n",
+ "\n"
+ ],
+ "text/plain": [
+ "HTML widgets cannot be represented in plain text (need html)"
+ ]
+ },
+ "metadata": {
+ "text/html": {
+ "isolated": true
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# use the built in leaflet capability from robis to map the occurrences\n",
+ "map_leaflet(mangrove_occ,\n",
+ " provider_tiles = \"Esri.WorldGrayCanvas\",\n",
+ " popup = function(x) { x[\"scientificName\"] },\n",
+ " )"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "R",
+ "language": "R",
+ "name": "ir"
+ },
+ "language_info": {
+ "codemirror_mode": "r",
+ "file_extension": ".r",
+ "mimetype": "text/x-r-source",
+ "name": "R",
+ "pygments_lexer": "r",
+ "version": "4.1.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
From 109124ec665f18cc9e5003f8cea57ecfeb37bd9e Mon Sep 17 00:00:00 2001
From: Laura Brenskelle <160157051+laurabrenskelle@users.noreply.github.com>
Date: Fri, 13 Sep 2024 15:47:07 -0400
Subject: [PATCH 03/15] Adding updated OBIS_EOV file
---
.../2024-09-13-OBIS_EOVs.ipynb | 233 ++++++++++++++++++
1 file changed, 233 insertions(+)
create mode 100644 jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2024-09-13-OBIS_EOVs.ipynb
diff --git a/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2024-09-13-OBIS_EOVs.ipynb b/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2024-09-13-OBIS_EOVs.ipynb
new file mode 100644
index 00000000..975f28d4
--- /dev/null
+++ b/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2024-09-13-OBIS_EOVs.ipynb
@@ -0,0 +1,233 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "ad98f7a1-d7a1-4a51-a9a2-0da9da7fe042",
+ "metadata": {},
+ "source": [
+ "# Using aphiaIDs to download OBIS occurrences for Bio/Eco EOVs\n",
+ "\n",
+ "Created: 2024-09-13"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "390bf2be-3828-4705-b64b-ed68005ff98b",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Attaching package: 'dplyr'\n",
+ "\n",
+ "\n",
+ "The following objects are masked from 'package:stats':\n",
+ "\n",
+ " filter, lag\n",
+ "\n",
+ "\n",
+ "The following objects are masked from 'package:base':\n",
+ "\n",
+ " intersect, setdiff, setequal, union\n",
+ "\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "library(gh)\n",
+ "library(readr)\n",
+ "library(robis)\n",
+ "library(dplyr)\n",
+ "library(htmlwidgets)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "43964864-7fe8-4139-a9d0-2a844161ccd1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# first we will pull the files where the EOV taxonomy are stored from GitHub\n",
+ "repo_files <- gh(\"GET /repos/:owner/:repo/contents/:path\",\n",
+ " owner = \"ioos\",\n",
+ " repo = \"marine_life_data_network\",\n",
+ " path = \"eov_taxonomy\")\n",
+ "\n",
+ "for (file_info in repo_files) {\n",
+ " if (file_info$type == \"file\") {\n",
+ " download.file(file_info$download_url, destfile = file_info$name)\n",
+ " }\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "0bb6ab17-d239-410c-90d0-dcb50359b095",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# let's try mangroves as our first example\n",
+ "# we will open the mangroves taxonomy CSV that we downloaded and grab the taxonIDs\n",
+ "mangroves <- read.csv(\"mangroves.csv\")\n",
+ "mangroves$ID <- gsub(\"urn:lsid:marinespecies.org:taxname.\", \"\", mangroves$acceptedTaxonId)\n",
+ "mangroves$ID <- as.numeric(mangroves$ID)\n",
+ "mangroveIdentifiers <- paste(mangroves$ID, collapse = \", \")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "d9aa2697-4ca0-4631-8d77-b0407e7a73b5",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Retrieved 5000 records of approximately 132901 (3%)\n",
+ "Retrieved 10000 records of approximately 132901 (7%)\n",
+ "Retrieved 15000 records of approximately 132901 (11%)\n",
+ "Retrieved 20000 records of approximately 132901 (15%)\n",
+ "Retrieved 25000 records of approximately 132901 (18%)\n",
+ "Retrieved 30000 records of approximately 132901 (22%)\n",
+ "Retrieved 35000 records of approximately 132901 (26%)\n",
+ "Retrieved 40000 records of approximately 132901 (30%)\n",
+ "Retrieved 45000 records of approximately 132901 (33%)\n",
+ "Retrieved 50000 records of approximately 132901 (37%)\n",
+ "Retrieved 55000 records of approximately 132901 (41%)\n",
+ "Retrieved 60000 records of approximately 132901 (45%)\n",
+ "Retrieved 65000 records of approximately 132901 (48%)\n",
+ "Retrieved 70000 records of approximately 132901 (52%)\n",
+ "Retrieved 75000 records of approximately 132901 (56%)\n",
+ "Retrieved 80000 records of approximately 132901 (60%)\n",
+ "Retrieved 85000 records of approximately 132901 (63%)\n",
+ "Retrieved 90000 records of approximately 132901 (67%)\n",
+ "Retrieved 95000 records of approximately 132901 (71%)\n",
+ "Retrieved 1e+05 records of approximately 132901 (75%)\n",
+ "Retrieved 105000 records of approximately 132901 (79%)\n",
+ "Retrieved 110000 records of approximately 132901 (82%)\n",
+ "Retrieved 115000 records of approximately 132901 (86%)\n",
+ "Retrieved 120000 records of approximately 132901 (90%)\n",
+ "Retrieved 125000 records of approximately 132901 (94%)\n",
+ "Retrieved 130000 records of approximately 132901 (97%)\n",
+ "Retrieved 132901 records of approximately 132901 (100%)\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "132901"
+ ],
+ "text/latex": [
+ "132901"
+ ],
+ "text/markdown": [
+ "132901"
+ ],
+ "text/plain": [
+ "[1] 132901"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# using the taxonIDs from the last step, let's search OBIS for occurrence data for this EOV\n",
+ "# this will take a bit to download because there were over 130k records when this script was written in Sept 2024\n",
+ "mangrove_occ <- robis::occurrence(taxonid = mangroveIdentifiers)\n",
+ "# let's check how many occurrences we got from OBIS\n",
+ "nrow(mangrove_occ)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "1ccc9837-4585-4020-852b-cdc6b33ae62d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "\t\n",
+ "\t\t\n",
+ "\t\t\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\t\n",
+ "\t\n",
+ "\t\t\n",
+ "\n",
+ "\t\n",
+ "\n"
+ ],
+ "text/plain": [
+ "HTML widgets cannot be represented in plain text (need html)"
+ ]
+ },
+ "metadata": {
+ "text/html": {
+ "isolated": true
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# use the built in leaflet capability from robis to map the occurrences\n",
+ "m <- map_leaflet(mangrove_occ,\n",
+ " provider_tiles = \"Esri.WorldGrayCanvas\",\n",
+ " popup = function(x) { x[\"scientificName\"] },\n",
+ " )\n",
+ "m"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "13a8bc6c-5963-4e4e-acab-f0f6de776045",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# if you want to save the leaflet map\n",
+ "saveWidget(m, \"mangroveMap.html\", selfcontained = TRUE)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "R",
+ "language": "R",
+ "name": "ir"
+ },
+ "language_info": {
+ "codemirror_mode": "r",
+ "file_extension": ".r",
+ "mimetype": "text/x-r-source",
+ "name": "R",
+ "pygments_lexer": "r",
+ "version": "4.1.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
From a82fe2fc00f2d802ec442be6131ffff261103227 Mon Sep 17 00:00:00 2001
From: Laura Brenskelle <160157051+laurabrenskelle@users.noreply.github.com>
Date: Wed, 18 Sep 2024 14:57:13 -0400
Subject: [PATCH 04/15] Updating OBIS EOV file
---
.../2024-09-13-OBIS_EOVs.ipynb | 218 +++++++-----------
1 file changed, 78 insertions(+), 140 deletions(-)
diff --git a/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2024-09-13-OBIS_EOVs.ipynb b/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2024-09-13-OBIS_EOVs.ipynb
index 975f28d4..d42ae8e5 100644
--- a/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2024-09-13-OBIS_EOVs.ipynb
+++ b/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2024-09-13-OBIS_EOVs.ipynb
@@ -7,38 +7,22 @@
"source": [
"# Using aphiaIDs to download OBIS occurrences for Bio/Eco EOVs\n",
"\n",
- "Created: 2024-09-13"
+ "Created: 2024-09-13\n",
+ "\n",
+ "The [IOOS Marine Life Data Network](https://ioos.github.io/marine_life_data_network/) has developed a list of aphiaIDs for taxa mentioned in the [GOOS Biology and Ecosystems Variables](https://goosocean.org/what-we-do/framework/essential-ocean-variables/). These lists are meant to assist in querying OBIS to evaluate the abundance and distribution of these taxa. Here is an R notebook of how this might work using mangroves as an example."
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "390bf2be-3828-4705-b64b-ed68005ff98b",
"metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\n",
- "Attaching package: 'dplyr'\n",
- "\n",
- "\n",
- "The following objects are masked from 'package:stats':\n",
- "\n",
- " filter, lag\n",
- "\n",
- "\n",
- "The following objects are masked from 'package:base':\n",
- "\n",
- " intersect, setdiff, setequal, union\n",
- "\n",
- "\n"
- ]
+ "scrolled": true,
+ "vscode": {
+ "languageId": "r"
}
- ],
+ },
+ "outputs": [],
"source": [
"library(gh)\n",
"library(readr)\n",
@@ -47,153 +31,95 @@
"library(htmlwidgets)"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "3089302a",
+ "metadata": {},
+ "source": [
+ "First, we will pull the file with the mangrove aphiaIDs from the Marine Life Data Network GitHub repo. **Note**: the acceptedTaxonIds in these files are based on what was up-to-date in the [WoRMS](https://marinespecies.org/) database as of the date this script was written."
+ ]
+ },
{
"cell_type": "code",
"execution_count": 5,
"id": "43964864-7fe8-4139-a9d0-2a844161ccd1",
- "metadata": {},
+ "metadata": {
+ "vscode": {
+ "languageId": "r"
+ }
+ },
"outputs": [],
"source": [
- "# first we will pull the files where the EOV taxonomy are stored from GitHub\n",
- "repo_files <- gh(\"GET /repos/:owner/:repo/contents/:path\",\n",
- " owner = \"ioos\",\n",
- " repo = \"marine_life_data_network\",\n",
- " path = \"eov_taxonomy\")\n",
- "\n",
- "for (file_info in repo_files) {\n",
- " if (file_info$type == \"file\") {\n",
- " download.file(file_info$download_url, destfile = file_info$name)\n",
- " }\n",
- "}"
+ "mangroves <- read.csv(\"https://raw.githubusercontent.com/ioos/marine_life_data_network/main/eov_taxonomy/mangroves.csv\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "45fa26db",
+ "metadata": {},
+ "source": [
+ "Now we will do a bit of cleanup to get a list of aphiaIDs for mangroves so we can run our `robis` query using these as taxon identifiers."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0bb6ab17-d239-410c-90d0-dcb50359b095",
- "metadata": {},
+ "metadata": {
+ "vscode": {
+ "languageId": "r"
+ }
+ },
"outputs": [],
"source": [
- "# let's try mangroves as our first example\n",
- "# we will open the mangroves taxonomy CSV that we downloaded and grab the taxonIDs\n",
- "mangroves <- read.csv(\"mangroves.csv\")\n",
"mangroves$ID <- gsub(\"urn:lsid:marinespecies.org:taxname.\", \"\", mangroves$acceptedTaxonId)\n",
"mangroves$ID <- as.numeric(mangroves$ID)\n",
"mangroveIdentifiers <- paste(mangroves$ID, collapse = \", \")"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "8a6cefa9",
+ "metadata": {},
+ "source": [
+ "Using the taxonIDs from the last step, let's query OBIS for occurrence data for mangroves. This step may take a bit of time to run. When this script was written, there were over 130,000 records for mangroves in OBIS."
+ ]
+ },
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"id": "d9aa2697-4ca0-4631-8d77-b0407e7a73b5",
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Retrieved 5000 records of approximately 132901 (3%)\n",
- "Retrieved 10000 records of approximately 132901 (7%)\n",
- "Retrieved 15000 records of approximately 132901 (11%)\n",
- "Retrieved 20000 records of approximately 132901 (15%)\n",
- "Retrieved 25000 records of approximately 132901 (18%)\n",
- "Retrieved 30000 records of approximately 132901 (22%)\n",
- "Retrieved 35000 records of approximately 132901 (26%)\n",
- "Retrieved 40000 records of approximately 132901 (30%)\n",
- "Retrieved 45000 records of approximately 132901 (33%)\n",
- "Retrieved 50000 records of approximately 132901 (37%)\n",
- "Retrieved 55000 records of approximately 132901 (41%)\n",
- "Retrieved 60000 records of approximately 132901 (45%)\n",
- "Retrieved 65000 records of approximately 132901 (48%)\n",
- "Retrieved 70000 records of approximately 132901 (52%)\n",
- "Retrieved 75000 records of approximately 132901 (56%)\n",
- "Retrieved 80000 records of approximately 132901 (60%)\n",
- "Retrieved 85000 records of approximately 132901 (63%)\n",
- "Retrieved 90000 records of approximately 132901 (67%)\n",
- "Retrieved 95000 records of approximately 132901 (71%)\n",
- "Retrieved 1e+05 records of approximately 132901 (75%)\n",
- "Retrieved 105000 records of approximately 132901 (79%)\n",
- "Retrieved 110000 records of approximately 132901 (82%)\n",
- "Retrieved 115000 records of approximately 132901 (86%)\n",
- "Retrieved 120000 records of approximately 132901 (90%)\n",
- "Retrieved 125000 records of approximately 132901 (94%)\n",
- "Retrieved 130000 records of approximately 132901 (97%)\n",
- "Retrieved 132901 records of approximately 132901 (100%)\n"
- ]
- },
- {
- "data": {
- "text/html": [
- "132901"
- ],
- "text/latex": [
- "132901"
- ],
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- "132901"
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- "[1] 132901"
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- },
- "metadata": {},
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+ "metadata": {
+ "vscode": {
+ "languageId": "r"
}
- ],
+ },
+ "outputs": [],
"source": [
- "# using the taxonIDs from the last step, let's search OBIS for occurrence data for this EOV\n",
- "# this will take a bit to download because there were over 130k records when this script was written in Sept 2024\n",
"mangrove_occ <- robis::occurrence(taxonid = mangroveIdentifiers)\n",
"# let's check how many occurrences we got from OBIS\n",
"nrow(mangrove_occ)"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "c837a3ac",
+ "metadata": {},
+ "source": [
+ "Now that we have all of our mangrove records from OBIS, we will map the global distribution of records using the `map_leaflet` function found in the `robis` package. With the leaflet functionality, you can zoom into records, click them, and it list the scientific name for that occurrence record."
+ ]
+ },
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"id": "1ccc9837-4585-4020-852b-cdc6b33ae62d",
- "metadata": {},
- "outputs": [
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