ohiprep_v2024

## 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.

This site is open source. Improve this page.