ohiprep_v2023

## Ocean Health Index: Lasting Special Places (LSP)

See full data prep details here.

If using these data, please see our citation policy.

Layers Created

• Coastal protected marine areas (fishing preservation) (fp_mpa_coast)
• EEZ protected marine areas (fishing preservation) (fp_mpa_eez)
• Coastal protected marine areas (habitat preservation) (hd_mpa_coast)
• EEZ protected marine areas (habitat preservation) (hd_mpa_eez)
• Inland coastal protected areas (lsp_prot_area_inland1km)
• Offshore coastal protected areas (lsp_prot_area_offshore3nm)
• Inland area (rgn_area_inland1km)
• Offshore area (rgn_area_offshore3nm)

Prep Files

• 1_prep_wdpa_rast.Rmd converts the raw WDPA data into raster
• lsp_data_prep.Rmd prepares the raster so it’s ready for processing into the ohi-global toolbox. Any gapfilling and resilience calculation is completed here as well.

Data Check Files

• check_updates.Rmd is a script for additional data checking of score changes from last year’s assessment

Methods

Downloading Data

Accessing and downloading the data was difficult in 2023 due to a downloading bug, luckly there are multiple ways to download the data from the webpage. The below directions sound easy; but it is easy to be navigated to a page where the download functionality is broken.

Directions to download data:

1: Link to specific website: https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA

2: Select the download button in the top right hand corner.

3: Download and unzip the file

4: There will be additional zip files within the zip file you download. Once unzipped, these are the three files you will use throughout the LSP dataprep.

Filter and re-project WDPA polygons

The WDPA-MPA dataset comes as a shapefile or geodatabase in WGS84 coordinate reference system.

• For OHI we have chosen to count only protected areas with defined legal protection, so we apply a filter on the STATUS attribute that selects only STATUS == “Designated”.
  • According to the WDPA Manual: STATUS as “Designated” means: “Is recognized or dedicated through legal means. Implies specific binding commitment to conservation in the long term. Applicable to government and non-government sources.”
  • Other values for STATUS include “Proposed”, “Adopted”, “Inscribed”, or “Not Reported” and “Established”.
    • “Adopted” and “Inscribed” are World Heritage or Barcelona Convention sites; while these may seem important, they are generally protected by other means (as overlapping “Designated” polygons) in addition to these values.
• In 2015, the USA started including polygons that represent marine management plans, in addition to more strictly defined protected areas. This info is contained in the “MANG_PLAN” field.
  • These programmatic management plans variously protect species, habitats, and (??) and can be MPA or non-MPA.
  • For OHI we have chosen to count only MPA programmatic management plans, omitting Non-MPA programmatic management plans.
• For ease of tallying areas, we convert the polygons to a Mollweide equal-area projection before rasterizing.

Once the polygons have been prepped, we rasterize the results to 500 m resolution.

This process is all done in the script: 1_prep_wdpa_rast.Rmd. After that is complete, move on to computing zonal statistics.

Note: Updating Scores

As with all datapreps, the .csv files in the output folder are grabbed by the functions in the calculate_scores.Rmd to update the OHI scores for the year. This data layer creates 6 different .csv files with 8 different associated layers that are used for score calculation.

This is a list of the .csv files created and their associated layer:

• mpa_eez_resilience.csv - fp_mpa_eez, hd_mpa_eez
• mpa_3nm_resilience.csv - fp_mpa_coast, hd_mpa_coast
• lsp_prot_area_inland1km.csv - lsp_prot_area_inland1km
• lsp_prot_area_offshore3nm.csv - lsp_prot_area_offshore3nm
• rgn_area_inland1km.csv - rgn_area_inland1km
• rgn_area_offshore3nm.csv - rgn_area_offshore3nm

To be sure, this is a tricky OHI score update. Be sure all the layer years are updated in the scenario_data_years.csv. The “rgn_area_inland1km.csv - rgn_area_inland1km” and the “rgn_area_offshore3nm.csv - rgn_area_offshore3nm”, as you can imagine, are the same each year and remains static and unupdated. They are not present as layers in the scenario_data_years.csv file. There are also multiple places to update in the layers_eez_base.csv, luckely all of them have the same file path with the “lsp” folder so you can use this to search the .csv file.