Merge branch 'gh-pages' of https://github.com/OHI-Science/ohiprep_v2023…

… into gh-pages

globalprep/fis/readme.md

@@ -4,10 +4,10 @@ This folder describes the methods used to prepare data for the Fisheries subgoal
 
 More information about this goal is available [here](http://ohi-science.org/goals/#food-provision).
 
-The folders in this file include the metadata, R scripts, and data for each assessement year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
+The folders in this file include the metadata, R scripts, and data for each assessment year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
 
 Our [data managment SOP](https://rawgit.com/OHI-Science/ohiprep/master/src/dataOrganization_SOP.html) describes how we manage OHI global data, including a description of the file structure.
 
-Please see our [citation policy](http://ohi-science.org/citation-policy/) if you use OHI data or methods.
+Please see our [citation policy](https://oceanhealthindex.org/global-scores/data-download/) if you use OHI data or methods.
 
 Thank you!

globalprep/fis/v2023/readme.md

@@ -1,15 +1,15 @@
 ## Ocean Health Index: Fisheries Sub-goal (FIS)
 
-See full details for how the SAUP catch data was prepped [here](http://ohi-science.github.io/ohiprep_v2021/globalprep/fis/v2021/STEP2a_saup_catch_prep.html).
+See full details for how the SAUP catch data was prepped [here](http://ohi-science.github.io/ohiprep_v2023/globalprep/fis/v2023/STEP2a_saup_catch_prep.html).
 
-See full details for how BBmsy was calculated [here](http://ohi-science.github.io/ohiprep_v2021/globalprep/fis/v2021/STEP3_calculate_bbmsy.html).
+See full details for how BBmsy was calculated [here](http://ohi-science.github.io/ohiprep_v2023/globalprep/fis/v2023/STEP3_calculate_bbmsy.html).
 
 See full details for how RAM data was prepped
-[here RAM dataprep](http://ohi-science.github.io/ohiprep_v2021/globalprep/fis/v2021/STEP4a_RAM_data_prep.html)
-[here RAM_CMSY](http://ohi-science.github.io/ohiprep_v2021/globalprep/fis/v2021/STEP5_RAM_CMSY_combine.html)
+[here RAM dataprep](http://ohi-science.github.io/ohiprep_v2023/globalprep/fis/v2023/STEP4a_RAM_data_prep.html)
+[here RAM_CMSY](http://ohi-science.github.io/ohiprep_v2023/globalprep/fis/v2023/STEP5_RAM_CMSY_combine.html)
 
 
-If using these data, please see our [citation policy](http://ohi-science.org/citation-policy/).
+If using these data, please see our [citation policy](https://oceanhealthindex.org/global-scores/data-download/).
 
 ### Layers Created
 
@@ -23,8 +23,8 @@ A description of files:
 
 * STEP2a_saup_catch_prep.Rmd: Preps the spatialized catch data (at half degree cells) for use in goal weighting and stock status calculations. Auxiliary prep file, **STEP2b_species_resilience_lookup_table.Rmd**: Uses FishBase to find the Resilience for each of the species in the SAUP database. The Resilience information is needed for running catch-MSY to estimate B/Bmsy. Outputs:
 
-   - `git-annex/globalprep/fis/v2021/int/stock_catch_by_rgn.csv`
-   - `int/taxon_key_v2021.csv`
+   - `git-annex/globalprep/fis/v2022/int/stock_catch_by_rgn.csv`
+   - `int/taxon_key_v2022.csv`
    - `output/stock_catch.csv`
    - `output/mean_catch.csv`
    - `output/FP_fis_catch.csv`

globalprep/fp/README.md

@@ -4,10 +4,10 @@ This folder describes the methods used to prepare data for the food provision go
 
 More information about the food provision goal is available [here](http://ohi-science.org/goals/#food-provision).
 
-The folders in this file include the metadata, R scripts, and data for each assessement year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
+The folders in this file include the metadata, R scripts, and data for each assessment year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
 
 Our [data managment SOP](https://rawgit.com/OHI-Science/ohiprep/master/src/dataOrganization_SOP.html) describes how we manage OHI global data, including a description of the file structure.
 
-Please see our [citation policy](http://ohi-science.org/citation-policy/) if you use OHI data or methods.
+Please see our [citation policy](https://oceanhealthindex.org/global-scores/data-download/) if you use OHI data or methods.
 
 Thank you!

globalprep/fp/v2023/FP_script.Rmd

@@ -25,7 +25,7 @@ This script combines the fisheries catch data with the mariculture production da
 
 # Methods
 
-```{r}
+```{r, eval = FALSE}
 ## load libraries
 library(dplyr)
 library(tidyr)
@@ -44,20 +44,20 @@ source('http://ohi-science.org/ohiprep_v2021/workflow/R/common.R')
 # Import Output Data: Mariculture data
 
 Mariculture production in tonnes.
-```{r}
-mar <- read.csv(file.path("..", "..", "mar", paste0("v", scen_year), "output", "MAR_FP_data.csv"))
+```{r, eval = FALSE}
+mar <- read.csv(file.path("..", "..", "mar", paste0("v", scen_year), "output", "MAR_FP_data.csv")) # see metadata in its prep
 ```
 
 Fisheries data.
-```{r}
+```{r, eval = FALSE}
 fis <- read.csv(file.path("..", "..", "fis", paste0("v", scen_year), "output", "FP_fis_catch.csv")) %>%
-  dplyr::select(rgn_id, year, fis_t = fis_catch)
+  dplyr::select(rgn_id, year, fis_t = fis_catch) # see metadata in its prep
 ```
 
 # Wrangle 
 
 ## Tidy MAR data
-```{r}
+```{r, eval = FALSE}
 mar_tidy <- mar %>%
   group_by(rgn_id, year) %>%
   summarize(mar_t = sum(value, na.rm=TRUE)) %>%
@@ -70,7 +70,7 @@ filter(mar_tidy, rgn_id == 95) # ok, this makes sense
 
 ## Tidy FIS data
 
-```{r}
+```{r, eval = FALSE}
 fis_tidy <- fis %>%
   mutate(fis_t = ifelse(fis_t == 0, NA, fis_t)) %>%  # 11 NA values is correct (there were 0 in v2023)
   group_by(rgn_id) %>%
@@ -82,7 +82,7 @@ fis_tidy <- fis %>%
 ## Combine MAR and FIS
 
 Adjust years so they are equivalent.
-```{r}
+```{r, eval = FALSE}
 adjust <- max(mar_tidy$year) - max(fis_tidy$year)
 
 mar_adjust <- mar_tidy %>%
@@ -107,7 +107,7 @@ hist(tmp_weights$w_fis,
 # Data check
 
 Compare to previous year data
-```{r}
+```{r, eval = FALSE}
 compare <- read.csv(paste0("../../fp/v", prev_scen_year, "/output/wildcaught_weight.csv")) %>%
   rename(w_fis_old = w_fis) %>%
   left_join(tmp_weights, by = c('rgn_id', 'year'))
@@ -119,7 +119,7 @@ abline(0, 1, col="red")
 
 # Save data
 
-```{r}
+```{r, eval = FALSE}
 write.csv(tmp_weights, 'output/wildcaught_weight.csv', row.names=FALSE)
 
 ## add gf file (no gapfilling)

globalprep/np/v2023/STEP1c_np_fishfeed_prep.Rmd

@@ -30,6 +30,8 @@ This script takes the SAUP 2023 catch data, a list of fish oil/fish meal (FOFM)
 
 # Data Source
 
+## Sea Around us
+
 **Reference**: Pauly D., Zeller D., Palomares M.L.D. (Editors), 2020. Sea Around Us Concepts, Design and Data (seaaroundus.org).
 
 **Downloaded**: September 27, 2022
@@ -42,6 +44,8 @@ This script takes the SAUP 2023 catch data, a list of fish oil/fish meal (FOFM)
 
 **Additional Information**: [Methods](http://www.seaaroundus.org/sea-around-us-methods-index/)
 
+## Avoiding the ecological limits of forage fish
+
 **Reference**: Froehlich, H.E., Jacobsen, N.S., Essington, T.E., Clavelle, T., and Halpern, B.S. (2018). Avoiding the ecological limits of forage fish for fed aquaculture. Nature Sustainability 1, 298.
 
 **Downloaded**: July 7, 2020. Obtained from Melanie Frazier (NCEAS).
@@ -52,15 +56,17 @@ This script takes the SAUP 2023 catch data, a list of fish oil/fish meal (FOFM)
 
 **Format**: CSV format
 
-**Reference**: [RAM Legacy Stock Assessment Database](http://ramlegacy.org) v4.495
+## RAM Legacy Data
+
+**Reference**: [RAM Legacy Stock Assessment Database](http://ramlegacy.org) v4.61, 05/10/2023
 
-**Downloaded**: 06/03/2021
+**Downloaded**: 07/6/2023
 
 **Description**: B/Bmsy value by stock and year (other data, which we do not use, are also available in the database)
 
 **Native data resolution**: stock (fish stock, species and region specific)
 
-**Time range**: 1950 - 2024
+**Time range**: 1800 - 2022
 
 **Format**: CSV format
 

globalprep/np/v2023/STEP2_np_weighting_prep.Rmd

@@ -33,6 +33,8 @@ in ohi global.
 
 # Data Source
 
+## FAO
+
 **Reference**:\
 <http://www.fao.org/fishery/statistics/software/fishstatj/en#downlApp>
 App release date: July 2021 FAO raw commodities quantity 1976_2021 FAO
@@ -49,6 +51,8 @@ details).
 
 **Time range**: 1976-2021
 
+## Sea Around Us Concepts
+
 **Reference**: Pauly D., Zeller D., Palomares M.L.D. (Editors), 2020.
 Sea Around Us Concepts, Design and Data (seaaroundus.org).
 
@@ -65,6 +69,8 @@ taxonomic information.
 **Additional Information**:
 [Methods](http://www.seaaroundus.org/sea-around-us-methods-index/)
 
+## Avoiding the ecological limits of forage fish for fed aquaculture
+
 **Reference**: Froehlich, H.E., Jacobsen, N.S., Essington, T.E.,
 Clavelle, T., and Halpern, B.S. (2018). Avoiding the ecological limits
 of forage fish for fed aquaculture. Nature Sustainability 1, 298.
@@ -77,26 +83,28 @@ of forage fish for fed aquaculture. Nature Sustainability 1, 298.
 
 **Format**: CSV format
 
+## RAM
+
 **Reference**: [RAM Legacy Stock Assessment
-Database](http://ramlegacy.org) v4.491
+Database](http://ramlegacy.org) v4.61, 05/10/2023
 
-**Downloaded**: 06/03/2021
+**Downloaded**: 07/6/2023
 
 **Description**: B/Bmsy value by stock and year (other data, which we do
 not use, are also available in the database)
 
 **Native data resolution**: stock (fish stock, species and region
 specific)
 
-**Time range**: 1950 - 2024
+**Time range**: 1800 - 2022
 
 **Format**: CSV format
 
 **Additional Information**: We use the finalized b/bmsy layer from
 OHI-global for this data prep. We do not actually read in the raw RAM
-data here. We only use up to year == 2018.
+data here.
 
--   DOI: 10.5281/zenodo.2542919
+## FAO
 
 **Reference**:\
 <http://www.fao.org/fishery/statistics/software/fishstatj/en#downlApp>

globalprep/prs_alien/README.md

@@ -2,10 +2,10 @@
 
 This folder describes the methods used to prepare data for the nonindigenous species data for the global OHI assessment.  These data are used as a pressure.
 
-The folders in this file include the metadata, R scripts, and data for each assessement year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
+The folders in this file include the metadata, R scripts, and data for each assessment year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
 
 Our [data managment SOP](https://rawgit.com/OHI-Science/ohiprep/master/src/dataOrganization_SOP.html) describes how we manage OHI global data, including a description of the file structure.
 
-Please see our [citation policy](http://ohi-science.org/citation-policy/) if you use OHI data or methods.
+Please see our [citation policy](https://oceanhealthindex.org/global-scores/data-download/) if you use OHI data or methods.
 
 Thank you!

globalprep/prs_alien/v2023/README.md

@@ -10,5 +10,5 @@ Information about [calculating pressure](http://ohi-science.github.io/ohiprep_v2
 
 ### Additional information
 
-If using these data, please see our [citation policy](http://ohi-science.org/citation-policy/).
+If using these data, please see our [citation policy](https://oceanhealthindex.org/global-scores/data-download/).
 

globalprep/prs_coral_harvest/v2023/prs_coral_harvest.Rmd

@@ -44,7 +44,7 @@ FAO raw commodities metadata found [here](https://www.fao.org/fishery/en/collect
 
 **Downloaded**: July 19, 2023
 
-**Description**:  Quantity (tonnes) and value (USD) of raw commodities (Exports only) for each country, taxa, year.  The FAO data is subset to include commodities in these categories: shells, corals, ornamental fish, fish oil, seaweed and plants, sponges (see: raw/commodities2products.csv for details).
+**Description**:  Quantity (tonnes) and value (USD) of raw commodities (Exports only) for each country, taxa, year. The FAO data is subset to include commodities in these categories: shells, corals, ornamental fish, fish oil, seaweed and plants, sponges (see: raw/commodities2products.csv for details).
 
 **Time range**: 1976-2021
 

globalprep/prs_coral_harvest/v2023/prs_coral_harvest.html

@@ -9,7 +9,7 @@
 <meta http-equiv="X-UA-Compatible" content="IE=EDGE" />
 
 
-<meta name="author" content="Compiled on Tue Sep 5 17:02:51 2023 by egg" />
+<meta name="author" content="Compiled on Mon Sep 11 08:12:50 2023 by egg" />
 
 
 <title>OHI 2023: Coral Harvest Pressure</title>
@@ -1646,7 +1646,7 @@
 
 
 <h1 class="title toc-ignore">OHI 2023: Coral Harvest Pressure</h1>
-<h4 class="author"><em>Compiled on Tue Sep 5 17:02:51 2023 by
+<h4 class="author"><em>Compiled on Mon Sep 11 08:12:50 2023 by
 egg</em></h4>
 
 </div>

globalprep/prs_coral_harvest/v2023/readme.md

@@ -2,10 +2,10 @@
 
 This folder describes the methods used to prepare data for the coral harvest pressure layer for OHI global. 
 
-The folders in this file include the metadata, R scripts, and data for each assessement year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
+The folders in this file include the metadata, R scripts, and data for each assessment year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
 
 Our [data managment SOP](https://rawgit.com/OHI-Science/ohiprep/master/src/dataOrganization_SOP.html) describes how we manage OHI global data, including a description of the file structure.
 
-Please see our [citation policy](http://ohi-science.org/citation-policy/) if you use OHI data or methods.
+Please see our [citation policy](https://oceanhealthindex.org/global-scores/data-download/) if you use OHI data or methods.
 
 Thank you!

globalprep/prs_slr/readme.md

@@ -2,9 +2,9 @@
 
 This folder describes the methods used to prepare data for the Sea Level Rise pressure layer for the global OHI assessment.
 
-The folders in this file include the metadata, R scripts, and data for each assessement year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
+The folders in this file include the metadata, R scripts, and data for each assessment year (i.e., the year the assessment was conducted).  The most current year represents the best available data and methods, and previous years are maintained for archival purposes.
 
 Our [data managment SOP](https://rawgit.com/OHI-Science/ohiprep/master/src/dataOrganization_SOP.html) describes how we manage OHI global data, including a description of the file structure.
 
-Please see our [citation policy](http://ohi-science.org/citation-policy/) if you use OHI data or methods.
+Please see our [citation policy](https://oceanhealthindex.org/global-scores/data-download/) if you use OHI data or methods.
 

globalprep/prs_slr/v2023/readme.md

@@ -4,6 +4,6 @@ See full data prep details [here](https://ohi-science.github.io/ohiprep_v2023/gl
 
 This serves as a pressure for CP, CS, ECO, HAB, LIV, LSP, MAR, NP, & TR.
 
-If using these data, please see our [citation policy](http://ohi-science.org/citation-policy/).
+If using these data, please see our [citation policy](https://oceanhealthindex.org/global-scores/data-download/).
 
 

globalprep/prs_slr/v2023/slr_layer_prep_v2.Rmd

@@ -33,7 +33,7 @@ This process is completed entirely within this script. The raw data is downloade
 - One additional year of data, 2021, was added 
 - Add in code to automatically create folders when applicable
 - Add in some more tic/tocs
-- Had to change `terra` code back to `raster` for one chunk (making the histograms) to get it to work: commented out this code and added a version of histograms that works with `terra`
+- Had to change `terra` code back to `raster` for one chunk (making the histograms) to get it to work; later, commented out this code and added a version of histograms that works with `terra`
 
 ***
 
@@ -532,7 +532,7 @@ plotData <- regions_stats_clean %>%
   dplyr::arrange(rgn_name, year) %>%
   data.frame()
 
-# This does not work at the moment, probably due to lack of Flash support
+# this does not work at the moment, probably due to lack of Flash support
 # Motion <- gvisMotionChart(plotData, idvar = "rgn_name", timevar = "year")
 # plot(Motion)
 # print(Motion, file = "slr.html")