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OHI-Science / ohicore

Ocean Health Index - R library of core functions
http://ohi-science.org/ohicore
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LSP: update WDPA MPA data for 2014 #88

Closed jules32 closed 10 years ago

jules32 commented 10 years ago

Hi @bbest, @bshalpern, @Melsteroni and @katlongo,

I've accessed the shapefiles from WDPA through April 2014. I'm not sure how different they are from our last access in August 2013, but there are likely some changes in there. The data are saved on Neptune data_edit:

data_edit/git-annex/Global/WDPA-MPA_v2014.

Julie

bbest commented 10 years ago

Great, thanks Julie! I can process this after Stockholm, or anyone else is welcome to give it a go starting with:

neptune_data:model/GL-WDPA-MPA_v2013
bbest commented 10 years ago

From @katlongo...

OHI 2014 – remaining to dos:

OHI 2014 - extended:

bbest commented 10 years ago

Hi @katlongo, @bshalpern, and @jules32,

I finished WDPA for 2014. Below is the relevant portion of the README from ohiprep:Global/WDPA-MPA_v2014.

I registered the regional summary files in the layers_global:

layer dir_2014a fn_2014a
lsp_prot_area_inland1km ohiprep:Global/WDPA-MPA_v2014/data lsp_protarea_inland1km.csv
lsp_prot_area_offshore3nm ohiprep:Global/WDPA-MPA_v2014/data lsp_protarea_offshore3nm.csv

These will get used by ohi-global in LSP with 2013 as the max year for the 2014 EEZ (and descending max years for other EEZ scenarios 2013 and 2012).

BB

GL-WDPA-MPA_v2014

Files produced

Scripts

  1. model.py
    • selects the STATUS=Designated from the raw WDPA polygons, creates an ordering to prefer year based on:
      1. DESIG_TYPE: Regional > National > International
      2. STATUS_YR: early > later
    • converts the WDPA polygons to raster, assigning STATUS_YR to cell value, using inland1km and offshore3nm as a mask
    • tabulates area of regions by year established (STATUS_YR)
  2. digest.R consumes the dbf table and writes out csv files with fields: rgn_id, year, area_km2

Methods 2014

.#. Marine and terrestrial protected areas

Update: additional year and regional type available

Description: Data on protected areas were accessed from the United Nations Environment Programme - World Conservation Monitoring Centre’s World Database on Protected Areas (WDPA) through http://www.protectedplanet.net on March 28, 2014. We used only WDPA polygons (not points) with a status of “designated” (not “proposed”). These polygons were converted to a 1km Mollweide raster by the value of the year in which the park was decreed “designated”. For cases in which polygons overlapped, priority was given first to the parks with a designation type of the finest resolution (regional over national over international) and then by earliest year. In the future, we hope to apply buffers to parks spatially assigned as points based on area with extra logic to portion out the parks based on percentage marine vs terrestrial and limited to within country borders where applicable (Visconti et al. 2013). Spatial subsets used within the Lasting Special Places subgoal include the offshore 3 nm and inland 1km. The most recent full year was used for LSP status to be inclusive as possible, but presume a 3-year lag in exhaustive reporting to better estimate a trend.

Figure

map

katlongo commented 10 years ago

oohhh very cool - love the arrowed maps

— - - - - - —

~ ><> ~ ~

<> ~ ~ ><>

Catherine Longo, PhD Project scientist, Marine Science Institute (UCSB)

National Center for Ecological Analysis and Synthesis (NCEAS) 735 State Street, Suite 300 Santa Barbara, CA 93101 Telephone: (805) 893-7523

Email: longo@nceas.ucsb.edu Web: http://www.nceas.ucsb.edu/postdocs

On Jun 18, 2014, at 5:07 PM, Ben Best notifications@github.com wrote:

Finished WDPA for 2014. Here's the relevant portion of the README.

GL-WDPA-MPA_v2014

Files produced

lsp_protarea_inland1km.csv lsp_protarea_offshore3nm.csv Scripts

model.py

selects the STATUS=Designated from the raw WDPA polygons, creates an ordering to prefer year based on:

DESIG_TYPE: Regional > National > International STATUS_YR: early > later converts the WDPA polygons to raster, assigning STATUS_YR to cell value, using inland1km and offshore3nm as a mask tabulates area of regions by year established (STATUS_YR) digest.R consumes the dbf table and writes out csv files with fields: rgn_id, year, area_km2 Methods 2014

.#. Marine and terrestrial protected areas

Update: additional year and regional type available

Description: Data on protected areas were accessed from the United Nations Environment Programme - World Conservation Monitoring Centre’s World Database on Protected Areas (WDPA) through http://www.protectedplanet.net on March 28, 2014. We used only WDPA polygons (not points) with a status of “designated” (not “proposed”). These polygons were converted to a 1km Mollweide raster by the value of the year in which the park was decreed “designated”. For cases in which polygons overlapped, priority was given first to the parks with a designation type of the finest resolution (regional over national over international) and then by earliest year. In the future, we hope to apply buffers to parks spatially assigned as points based on area with extra logic to portion out the parks based on percentage marine vs terrestrial and limited to within country borders where applicable (Visconti et al. 2013). Spatial subsets used within the Lasting Special Places subgoal include the offshore 3 nm and inland 1km. The most recent full year was used for LSP status to be inclusive as possible, but presume a 3-year lag in exhaustive reporting to better estimate a trend.

Figure

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