diff --git a/ore2017/conf/functions.R b/ore2017/conf/functions.R index 4a3058c..a05b7d1 100644 --- a/ore2017/conf/functions.R +++ b/ore2017/conf/functions.R @@ -198,8 +198,8 @@ MAR = function(layers, status_year){ left_join(sustainability_score, by = c('rgn_id', 'species_code')) # fill in gaps with no data - rky <- spread(rky, year, tonnes) - rky <- gather(rky, "year", "tonnes", -c(1:3)) + #rky <- spread(rky, year, tonnes) + #rky <- gather(rky, "year", "tonnes", -c(1:3)) # 4-year rolling mean of data @@ -1751,8 +1751,7 @@ HAB = function(layers){ if(sum(d$w %in% 1 & is.na(d$health)) > 0){ warning("Some regions/habitats have extent data, but no health data. Consider estimating these values.") } - - + ## calculate scores status <- d %>% group_by(rgn_id) %>% @@ -1828,31 +1827,45 @@ ORE=function(scores){ ore_trend=SelectLayersData(layers,layers='ore_trend') %>% dplyr::select(rgn_id=id_num, score=val_num) + + #applying reference point + + wind_pwr<-lapply(ore_wind[,2], function(x) x/10000) + wind_pwr<-as.numeric(unlist(wind_pwr)) + wave_pwr<-lapply(ore_wave[,2], function(x) x/10000) + wave_pwr<-as.numeric(unlist(wave_pwr)) + + tidal_pwr<-lapply(ore_tidal[,2], function(x) x/10000) + tidal_pwr<-as.numeric(unlist(tidal_pwr)) + - lapply(wind_pwr, function(x) x/10000) - - lapply(wave_pwr, function(x) x/10000) + score=c() + score<-wind_pwr+wave_pwr+tidal_pwr + score<-score/3 - lapply(tidal_pwr, function(x) x/10000) + tr<-ore_trend[,2] + tr<-as.numeric(unlist(tr)) + + rgn_id<-ore_wave[,1] + rgn_id<-as.numeric(unlist(rgn_id)) + - ## calculate scores - status <- d %>% - group_by(rgn_id) %>% - summarize( - score = (wind_pwr+wave_pwr+tidal_pwr)/3, - dimension = 'status') %>% - ungroup() + sts<-data.frame(rgn_id,score) + s<-sts %>% + group_by(rgn_id, score) %>% + summarise( + dimension='status' + ) - trend <- d %>% - group_by(rgn_id) %>% - filter(!is.na(trend)) %>% - summarize( - score = sum(trend) / sum(w), - dimension = 'trend') %>% - ungroup() + trd<-data.frame(rgn_id,tr) + t<-trd %>% + group_by(rgn_id,tr) %>% + summarise( + dimension='trend' + ) - scores <- rbind(status, trend) %>% + scores <- rbind(s, t) %>% mutate(goal = "ORE") %>% select(region_id=rgn_id, goal, dimension, score) diff --git a/ore2017/configure_toolbox.r b/ore2017/configure_toolbox.r index 1cf9531..c1e805e 100644 --- a/ore2017/configure_toolbox.r +++ b/ore2017/configure_toolbox.r @@ -17,7 +17,7 @@ pkgs_installed <- sapply(pkgs_check, FUN = function(x) library(x, character.only library(stringr) - +setwd('ore2017') ## load scenario configuration conf = ohicore::Conf('conf') diff --git a/ore2017/layers.csv b/ore2017/layers.csv index 983f0aa..89922f9 100644 --- a/ore2017/layers.csv +++ b/ore2017/layers.csv @@ -1,107 +1,107 @@ "targets","layer","name","description","fld_value","units","filename","fld_id_num","fld_id_chr","fld_category","fld_year","fld_val_num","fld_val_chr","file_exists","year_min","year_max","val_min","val_max","val_0to1","flds_unused","flds_missing","rows_duplicated","num_ids_unique","data_na" -"AO","ao_access","Artisanal fisheries management effectiveness and opportunity","The opportunity for artisanal and recreational fishing based on the quality of management of the small-scale fishing sector","value","scaled 0-1","ao_access.csv","rgn_id",,,,"value",,TRUE,,,0,0.854,TRUE,,,,221,FALSE -"AO","ao_need","Economic need for artisanal fishing","Per capita purchasing power parity (PPP) adjusted gross domestic product (GDP): GDPpcPPP as a proxy for subsistence fishing need","value","scaled 0-1","ao_need.csv","rgn_id",,,"year","value",,TRUE,2005,2015,0.0107294720608492,1,TRUE,,,,221,FALSE -"CW","cw_chemical_trend","Chemical pollution trend","Modeled chemical pollution from commercial shipping traffic, ports and harbors, and pesticide use","trend","trend","cw_chemical_trend.csv","rgn_id",,,,"trend",,TRUE,,,-0.3833,0.6007,FALSE,,,,221,FALSE -"CW","cw_nutrient_trend","Nutrient pollution trend","Modeled data based on fertilizer consumption as a proxy for nutrient pollution","trend","trend","cw_nutrient_trend.csv","rgn_id",,,,"trend",,TRUE,,,-1,1,FALSE,,,,221,FALSE -"CW","cw_pathogen_trend","Pathogen pollution trend","Trends in percent of population without access to improved sanitation facilities as a proxy for pathogen pollution","trend","trend","cw_pathogen_trend.csv","rgn_id",,,,"trend",,TRUE,,,-0.53,0.46,FALSE,,,,221,FALSE -"CW","cw_trash_trend","Plastic trash trends","Trends in trash estimated using improperly disposed of plastics","trend","trend","cw_trash_trend.csv","rgn_id",,,,"trend",,TRUE,,,-0.209086973997465,1,FALSE,,,,221,FALSE -"CW pressure","po_chemicals_3nm","Coastal chemical pollution","Modeled chemical pollution from commercial shipping traffic, ports and harbors, land-based pesticide use (organic pollution), and urban runoff (inorganic pollution) ","pressure_score","scaled 0-1","po_chemicals_3nm.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.000314089840492316,0.989726930531591,TRUE,,,,221,FALSE -"CW pressure","po_nutrients_3nm","Coastal nutrient pollution","Modeled data based on fertilizer consumption from the Food and Agricultural Organization","pressure_score","scaled 0-1","po_nutrients_3nm.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.556896588237137,TRUE,,,,221,FALSE -"CW pressure","po_pathogens","Pathogen pollution","Percent of population without access to improved sanitation facilities as a proxy for pathogen pollution","pressure_score","scaled 0-1","po_pathogens.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.909090909090909,TRUE,,,,221,FALSE -"CW pressure","po_trash","Marine plastics","Global marine plastics","pressure_score","scaled 0-1","po_trash.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.0223096329122635,0.843154478466252,TRUE,,,,221,FALSE -"FIS","fis_b_bmsy","B/Bmsy estimates obtained using RAM data (when available) and the catch-MSY method","The ratio of fish population abundance compared to the abundance required to deliver maximum sustainable yield","bbmsy","B/Bmsy","fis_b_bmsy.csv","rgn_id",,"stock_id","year","bbmsy",,TRUE,2001,2010,0.0154,10.7,FALSE,,,,221,FALSE -"FIS","fis_meancatch","Fishery catch data","Mean commercial catch for each OHI region (averaged across years) ","mean_catch","tonnes","fis_meancatch.csv","rgn_id",,"stock_id_taxonkey","year","mean_catch",,TRUE,2001,2010,3.36290652419971e-17,6153125.16129057,FALSE,,,,221,FALSE -"FP","fp_wildcaught_weight","Food provision weights","Proportion of wild caught fisheries to mariculture","w_fis","proportion","fp_wildcaught_weight.csv","rgn_id",,,,"w_fis",,TRUE,,,0.228400667556178,1,TRUE,,,,221,FALSE -"HABCPCS","hab_extent","Habitat extent","Area of habitats: mangrove, saltmarsh, seagrass, soft-bottom, seaice, coral","km2","km2","hab_extent.csv","rgn_id",,"habitat",,"km2",,TRUE,,,0,3800720.2534611,FALSE,,,,221,FALSE -"HABCPCS","hab_health","Habitat condition","Current condition of habitat relative to historical condition","health","proportion","hab_health.csv","rgn_id",,"habitat",,"health",,TRUE,,,0,1,TRUE,,,,221,FALSE -"HABCPCS","hab_trend","Habitat condition trend","Estimated change in habitat condition during most recent 5 years","trend","trend","hab_trend.csv","rgn_id",,"habitat",,"trend",,TRUE,,,-1,1,FALSE,,,,221,FALSE -"ICO","ico_spp_iucn_status","IUCN extinction risk","IUCN extinction risk category for iconic species located within each region","category","IUCN risk category","ico_spp_iucn_status.csv","rgn_id",,"sciname","year",,"category",TRUE,2000,2016,,,FALSE,"iucn_sid",,8585,221, -"LE","le_gdp","GDP","Gross Domestic Product (GDP)","usd","2012 USD","le_gdp.csv",,"cntry_key",,"year","usd",,TRUE,1996,2011,22820838.02,14675462506263.5,FALSE,,,,221,FALSE -"LE","le_gdp_pc_ppp","GDP per capita PPP","Gross domestic product per person at purchasing power parity","usd","USD","le_gdp_pc_ppp.csv",,"cntry_key",,"year","usd",,TRUE,1980,2012,82.65764088,86506.63612,FALSE,,,,221,FALSE -"LE","le_jobs_cur_adj_value","Current jobs adjusted","Modeled LE data","value","value","le_jobs_cur_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,62.41711597,98.8240774,FALSE,,,,221,FALSE -"LE","le_jobs_cur_base_value","Current jobs base","Modeled LE data","value","value","le_jobs_cur_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,7976022.6343,FALSE,,,,221,FALSE -"LE","le_jobs_ref_adj_value","Reference jobs adjusted","Modeled LE data","value","value","le_jobs_ref_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,69.70000277,98.89999998,FALSE,,,,221,FALSE -"LE","le_jobs_ref_base_value","Reference jobs base","Modeled LE data","value","value","le_jobs_ref_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,8148031.2004,FALSE,,,,221,FALSE -"LE","le_jobs_sector_year","Jobs","Modeled LE data","value","number of jobs","le_jobs_sector_year.csv",,"cntry_key","sector","year","value",,TRUE,1990,2010,0,9966925.101,FALSE,,,,221,FALSE -"LE","le_popn","Total human population","Human population of OHI regions","count","number of people","le_popn.csv","rgn_id",,,"year","count",,TRUE,1960,2012,0,1350695000,FALSE,,,,221,FALSE -"LE","le_rev_cur_adj_value","Current revenue adjusted","Modeled LE data","value","value","le_rev_cur_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,27001199.73,13919727042705.6,FALSE,,,,221,FALSE -"LE","le_rev_cur_base_value","Current revenue base","Modeled LE data","value","value","le_rev_cur_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,1319580686744.52,FALSE,,,,221,FALSE -"LE","le_revenue_adj","Revenue adjusted","Modeled LE data","usd","USD","le_revenue_adj.csv",,"cntry_key",,"year","usd",,TRUE,1996,2011,22820838.02,14675462506263.5,FALSE,,,,221,FALSE -"LE","le_rev_ref_adj_value","Reference revenue adjusted","Modeled LE data","value","value","le_rev_ref_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,22820838.02,13667652066195.1,FALSE,,,,221,FALSE -"LE","le_rev_ref_base_value","Reference revenue base","Modeled LE data","value","value","le_rev_ref_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,284189642760,FALSE,,,,221,FALSE -"LE","le_rev_sector_year","Revenue","Modeled LE data","value","2010 USD","le_rev_sector_year.csv",,"cntry_key","sector","year","value",,TRUE,1996,2012,0,1319580686744.52,FALSE,,,,221,FALSE -"LE","le_sector_weight","Sector weight by jobs","Proportion of jobs within each sector","weight","value","le_sector_weight.csv","rgn_id",,"sector",,"weight",,TRUE,,,1,1,TRUE,,,,221,FALSE -"LE","le_unemployment","Unemployment","Modeled LE data","percent","proportion","le_unemployment.csv",,"cntry_key",,"year","percent",,TRUE,1990,2010,0.517311849999999,37.58288403,FALSE,,,,221,FALSE -"LE","le_wage_cur_adj_value","Current wages adjusted","Modeled LE data","value","value","le_wage_cur_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,1,1,TRUE,,,,221,FALSE -"LE","le_wage_cur_base_value","Current wages base","Modeled LE data","value","value","le_wage_cur_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,436558.72173255,FALSE,,,,221,FALSE -"LE","le_wage_ref_adj_value","Reference wages adjusted","Modeled LE data","value","value","le_wage_ref_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,1,1,TRUE,,,,221,FALSE -"LE","le_wage_ref_base_value","Reference wages base","Modeled LE data","value","value","le_wage_ref_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,170878.277466168,FALSE,,,,221,FALSE -"LE","le_wage_sector_year","Wages","Modeled LE data","value","2010 USD","le_wage_sector_year.csv",,"cntry_key","sector","year","value",,TRUE,1993,2008,0,436558.72173255,FALSE,,,,221,FALSE -"LE","le_workforcesize_adj","Adjusted workforce size","Modeled LE data","jobs","number of jobs","le_workforcesize_adj.csv",,"cntry_key",,"year","jobs",,TRUE,1990,2012,0,791711771.342352,FALSE,,,,221,FALSE -"LSP","lsp_prot_area_inland1km","Inland coastal protected areas","Protected areas located 1 km inland","a_prot_1km","km2","lsp_prot_area_inland1km.csv","rgn_id",,,"year","a_prot_1km",,TRUE,2000,2015,0,30449.5,FALSE,,,,221,FALSE -"LSP","lsp_prot_area_offshore3nm","Offshore coastal protected areas","Protected areas located 3nm offshore","a_prot_3nm","km2","lsp_prot_area_offshore3nm.csv","rgn_id",,,"year","a_prot_3nm",,TRUE,2000,2015,0,99060,FALSE,,,,221,FALSE -"LSP","rgn_area_inland1km","Inland area","Inland area of OHI regions within 1km of shoreline","area","km2","rgn_area_inland1km.csv","rgn_id",,,,"area",,TRUE,,,1,175147,FALSE,,,,221,FALSE -"LSP","rgn_area_offshore3nm","Offshore area","Offshore area of OHI regions within 3nm of shoreline","area","km2","rgn_area_offshore3nm.csv","rgn_id",,,,"area",,TRUE,,,12.75,621887.75,FALSE,,,,221,FALSE -"MAR","mar_coastalpopn_inland25mi","Inland coastal population","Total coastal population within 25 miles of coast.","popsum","number of people","mar_coastalpopn_inland25mi.csv","rgn_id",,,"year","popsum",,TRUE,2005,2015,0,254433578,FALSE,,,,221,FALSE -"MAR","mar_harvest_tonnes","Mariculture harvest","Tonnes of mariculture harvest","tonnes","tonnes","mar_harvest_tonnes.csv","rgn_id",,"taxa_code","year","tonnes",,TRUE,1950,2014,0,4352694,FALSE,,,,221,FALSE -"MAR","mar_sustainability_score","Mariculture sustainability score","Mariculture sustainability from the Mariculture Sustainability Index (MSI).","sust_coeff","score","mar_sustainability_score.csv","rgn_id",,"taxa_code",,"sust_coeff",,TRUE,,,0.1,1,TRUE,,,,221,FALSE -"NP","np_blast","Areas of blast fishing","Destructive artisanal blast fishing","score","score","np_blast.csv","rgn_id",,,,"score",,TRUE,,,0.006865107932434,0.874460499155564,TRUE,,,,221,FALSE -"NP","np_cyanide","Areas of poison fishing","Destructive artisanal poison (cyanide) fishing","score","score","np_cyanide.csv","rgn_id",,,,"score",,TRUE,,,0.00565484574373731,0.495137734714806,TRUE,,,,221,FALSE -"NP","np_harvest_product_weight","Relative harvest value","Value of harvest of each product relative to total harvest of six marine products (coral, fish oil, seaweed and plants, shells, sponges, ornamental fish). Used to weight contribution of each product to final score.","weight","proportion","np_harvest_product_weight.csv","rgn_id",,"product",,"weight",,TRUE,,,0,1,TRUE,,,,221,FALSE -"NP","np_harvest_tonnes","Natural product harvest","Yield in metric tonnes of six marine products (coral, fish oil, seaweed and plants, shells, sponges, ornamental fish) from FAO","tonnes","tonnes","np_harvest_tonnes.csv","rgn_id",,"product","year","tonnes",,TRUE,1976,2013,0,298403.8,FALSE,,,,221,FALSE -"NP","np_harvest_tonnes_relative","Relative harvest tonnes","Tonnes of harvest of each product relative to total harvest of six marine products (coral, fish oil, seaweed and plants, shells, sponges, ornamental fish). Used to weight contribution of each product to final score.","tonnes_rel","proportion","np_harvest_tonnes_relative.csv","rgn_id",,"product","year","tonnes_rel",,TRUE,1976,2013,0,1,TRUE,,,,221,FALSE -" pressure","cc_acid","Ocean acidification","Ocean acidification pressure scaled using biological thresholds","pressure_score","scaled 0-1","cc_acid.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.0966879482359667,0.692411167229037,TRUE,,,,221,FALSE -" pressure","cc_slr","Sea level rise","Sea level rise pressure","pressure_score","scaled 0-1","cc_slr.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.622744456810226,TRUE,,,,221,FALSE -" pressure","cc_sst","Sea surface temperature anomolies","Sea surface temperature anomolies","pressure_score","scaled 0-1","cc_sst.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.788254063816159,TRUE,,,,221,FALSE -" pressure","cc_uv","UV radiation pressure","Modeled UV radiation based on Erythemal UV Irradiance data provided by GES DISC.","pressure_score","scaled 0-1","cc_uv.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.736063358627025,TRUE,,,,221,FALSE -" pressure","fp_art_hb","High bycatch due to artisanal fishing ","The presence of destructive artisanal blast and poison (cyanide) fishing.","pressure_score","scaled 0-1","fp_art_hb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00790365073391053,1,TRUE,,,,221,FALSE -" pressure","fp_art_lb","Low bycatch due to artisanal fishing ","Extent of artisanal fishing (including: artisanal, subsistence, and recreational catch)","pressure_score","scaled 0-1","fp_art_lb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00084897442244204,0.826165403212667,TRUE,,,,221,FALSE -" pressure","fp_com_hb","High bycatch due to commercial fishing ","Modeled destructive commercial fishing practices by 5 gear types and scaled by Net Primary Productivity","pressure_score","scaled 0-1","fp_com_hb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00333270126858887,0.733160374369164,TRUE,,,,221,FALSE -" pressure","fp_com_lb","Low bycatch due to commercial fishing ","Modeled destructive commercial fishing practices by 2 gear types and scaled by Net Primary Productivity","pressure_score","scaled 0-1","fp_com_lb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00333270126858887,0.733160374369164,TRUE,,,,221,FALSE -" pressure","fp_targetharvest","Targeted harvest of cetaceans and marine turtles","Targeted harvest of cetaceans and marine turtles","pressure_score","scaled 0-1","fp_targetharvest.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" pressure","hd_habitat","Management and protection of habitat to preserve biodiversity","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: habitat related questions","resilience score","scaled 0-1","hd_habitat.csv","rgn_id",,,,"resilience.score",,TRUE,,,0.138087289287079,1,TRUE,,,,221,FALSE -" pressure","hd_intertidal","Intertidal habitat destruction","Coastal population density (25 mi from shore) as a proxy for intertidal habitat destruction","pressure_score","scaled 0-1","hd_intertidal.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" pressure","hd_subtidal_hb","Subtidal hardbottom habitat destruction","High bycatch artisanal fishing practices (blast fishing) as a proxy for subtidal hard bottom habitat destruction","score","scaled 0-1","hd_subtidal_hb.csv","rgn_id",,,,"score",,TRUE,,,0.006865107932434,0.874460499155564,TRUE,,,,221,FALSE -" pressure","hd_subtidal_sb","Subtidal softbottom habitat destruction","Demersal destructive commercial fishing practices (i.e., trawling) in softbottom habitat as a proxy for soft bottom habitat destruction","pressure_score","scaled 0-1","hd_subtidal_sb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.950344604978492,TRUE,,,,221,FALSE -" pressure","po_chemicals","Chemical pollution","Modeled chemical pollution from commercial shipping traffic, ports and harbors, and pesticide use","pressure_score","scaled 0-1","po_chemicals.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00747125428241358,0.990734614993975,TRUE,,,,221,FALSE -" pressure","po_nutrients","Nutrient pollution","Modeled data based on fertilizer consumption from the Food and Agricultural Organization","pressure_score","scaled 0-1","po_nutrients.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.592252354120511,TRUE,,,,221,FALSE -" pressure","po_water","Management and regulations to control water pollution to preserve biodiversity","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: tourism related questions","resilience score","scaled 0-1","po_water.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" pressure","sp_alien","Nonindigenous species","Measure of harmful invasive species","pressures.score","scaled 0-1","sp_alien.csv","rgn_id",,,,"pressures.score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" pressure","sp_genetic","Genetic escapes","Introduced mariculture species (Mariculture Sustainability Index) as a proxy for genetic escapes ","pressure_score","scaled 0-1","sp_genetic.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.1,1,TRUE,,,,221,FALSE -" pressure","ss_spi","Weakness of social progress","Inverse of Social Progress Index scores","pressure_score","scaled 0-1","ss_spi.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.0991,0.629592741607178,TRUE,,,,221,FALSE -" pressure","ss_wgi","Weakness of governance","Inverse of World Governance Indicators (WGI) six combined scores","pressure_score","scaled 0-1","ss_wgi.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.126337814331055,0.943051262696584,TRUE,,,,221,FALSE -" pressure resilience","element_wts_cp_km2_x_protection","Coastal protection weights","Habitat extent multiplied by habitat protection rank for: coral, mangrove (offshore and inland 1km), saltmarsh, sea ice (shoreline), and seagrass","extent_rank","extent*rank","element_wts_cp_km2_x_protection.csv","rgn_id",,"habitat",,"extent_rank",,TRUE,,,0.000108,2800227.27272727,FALSE,,,,221,FALSE -" pressure resilience","element_wts_cs_km2_x_storage","Carbon storage weights","Habitat extent multiplied by carbon storage capacity for: mangrove (offshore and inland 1km), saltmarsh, and sea ice","extent_rank","extent*storage","element_wts_cs_km2_x_storage.csv","rgn_id",,"habitat",,"extent_rank",,TRUE,,,0.003753,3317914.748642,FALSE,,,,221,FALSE -" pressure resilience","element_wts_hab_pres_abs","Habitat weights","List of habitats in each region","boolean","boolean","element_wts_hab_pres_abs.csv","rgn_id",,"habitat",,"boolean",,TRUE,,,1,1,TRUE,,,,221,FALSE -" resilience","fp_habitat","Management and protection of habitat to preserve biodiversity (fisheries)","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: habitat related questions","resilience score","scaled 0-1","fp_habitat.csv","rgn_id",,,,"resilience.score",,TRUE,,,0.138087289287079,1,TRUE,,,,221,FALSE -" resilience","fp_mora","Commercial fishing management","Regulations and management of commerical fishing","value","scaled 0-1","fp_mora.csv","rgn_id",,,,"value",,TRUE,,,0,0.814394256522431,TRUE,,,,221,FALSE -" resilience","fp_mora_artisanal","Artisanal fisheries management effectiveness and opportunity","The opportunity for artisanal and recreational fishing based on the quality of management of the small-scale fishing sector","value","scaled 0-1","fp_mora_artisanal.csv","rgn_id",,,,"value",,TRUE,,,0,0.854,TRUE,,,,221,FALSE -" resilience","fp_mpa_coast","Coastal protected marine areas to protect fishery resources","Protected marine areas within 3nm of coastline (lasting special places goal calculated for coastal zone)","resilience.score","scaled 0-1","fp_mpa_coast.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" resilience","fp_mpa_eez","EEZ protected marine areas to protect fishery resources","Protected marine areas within EEZ to protect fishery resource (lasting special places goal results)","resilience.score","scaled 0-1","fp_mpa_eez.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" resilience","g_cites","CITES signatories","Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) signatories","resilience_score","scaled 0-1","g_cites.csv","rgn_id",,,,"resilience_score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" resilience","g_mariculture","Management of mariculture practices to preserve biodiversity","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: mariculture related questions","resilience score","scaled 0-1","g_mariculture.csv","rgn_id",,,,"resilience.score",,TRUE,,,0.054428393263486,1,TRUE,,,,221,FALSE -" resilience","g_msi_gov","Mariculture Sustainability Index","Mariculture practice assessment criteria from the Mariculture Sustainability Index (MSI)","resilience score","scaled 0-1","g_msi_gov.csv","rgn_id",,,,"resilience.score",,TRUE,,,0.1,0.8576923077,TRUE,,,,221,FALSE -" resilience","g_tourism","Management of tourism to preserve biodiversity","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: tourism related questions","resilience score","scaled 0-1","g_tourism.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" resilience","hd_mpa_coast","Coastal protected marine areas to protect against habitat destruction","Protected marine areas within 3nm of coastline (lasting special places goal status score)","resilience.score","scaled 0-1","hd_mpa_coast.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" resilience","hd_mpa_eez","Protected marine areas within EEZ to protect against habitat destruction","Protected marine areas within EEZ (lasting special places status score for entire EEZ)","resilience.score","scaled 0-1","hd_mpa_eez.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" resilience","li_gci","Competitiveness in achieving sustained economic prosperity","Global Competitiveness Index (GCI) scores from the World Economic Forum","score","scaled","li_gci.csv","rgn_id",,,,"score",,TRUE,,,0.398989454285714,0.806451177571429,TRUE,,,,221,FALSE -" resilience","li_sector_evenness","Sector evenness as a measure of economic diversity","Shannon's Diversity Index calculated sector evenness based on the total number of sectors and the proportion of jobs belonging to any sector","resilience score","scaled","li_sector_evenness.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,0.997518269205,TRUE,,,,221,FALSE -" resilience","res_spi","Social Progress Index","Social Progress Index scores","resilience_score","scaled 0-1","res_spi.csv","rgn_id",,,,"resilience_score",,TRUE,,,0.370407258392822,0.9009,TRUE,,,,221,FALSE -" resilience","sp_alien_species","Management of nonindigenous species","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: invasive species related questions","resilience score","scaled 0-1","sp_alien_species.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,221,FALSE -" resilience","species_diversity_3nm","Measure of coastal ecological integrity","Marine species condition (same calculation and data as the species subgoal status score) calculated within 3 nm of shoreline as a proxy for ecological integrity","score","scaled 0-1","species_diversity_3nm.csv","rgn_id",,,,"score",,TRUE,,,0.877105422176482,0.962966768212714,TRUE,,,,221,FALSE -" resilience","species_diversity_eez","Measure of ecological integrity","Marine species condition (species subgoal status score) as a proxy for ecological integrity","score","scaled 0-1","species_diversity_eez.csv","rgn_id",,,,"score",,TRUE,,,0.871981848756887,0.961226989799502,TRUE,,,,221,FALSE -" resilience","wgi_all","Strength of governance","World Governance Indicators (WGI) six combined scores","resilience_score","scaled 0-1","wgi_all.csv","rgn_id",,,,"resilience_score",,TRUE,,,0.0569487373034157,0.873662185668945,TRUE,,,,221,FALSE -" spatial","cntry_rgn","ISO country codes","Lookup table of country codes (based on ISO 3166 country codes) and Ocean Health Index region idenifiers.","rgn_id","region id","cntry_rgn.csv",,"cntry_key",,,"rgn_id",,TRUE,,,1,250,FALSE,,,,221,FALSE -" spatial","rgn_area","Region areas based on EEZ boundaries","Area of Ocean Health Index regions modified from exclusive economic zones ","area_km2","km2","rgn_area.csv","rgn_id",,,,"area_km2",,TRUE,,,12.7630587776,31886958.884907,FALSE,,,,221,FALSE -"spatial ","rgn_georegions","UN geopolitical region classifications","Lookup table of Ocean Health Index regions and UN geopolitical regions (3 levels), often used for gapfilling missing data","georgn_id","UN regions","rgn_georegions.csv","rgn_id",,"level",,"georgn_id",,TRUE,,,1,999,FALSE,,,,221,FALSE -"spatial ","rgn_global","OHI regions","Subset of regions that are not deleted or disputed ","label","label","rgn_global.csv","rgn_id",,,,,"label",TRUE,,,,,FALSE,,,,221, -"spatial ","rgn_labels","Regions ","Regions by type (eez, subocean, unclaimed)","label","label","rgn_labels.csv","rgn_id",,"type",,,"label",TRUE,,,,,FALSE,,,,221, -"SPP","spp_status","Average species condition","Species condition based on average of IUCN threat categories","score","status score","spp_status.csv","rgn_id",,,,"score",,TRUE,,,0.871981848756887,0.961226989799502,TRUE,,,,221,FALSE -"SPP","spp_trend","Average species condition trend","Species trends based on average of IUCN population trend data","score","trend score","spp_trend.csv","rgn_id",,,,"score",,TRUE,,,-0.307391304347826,-0.0514800222979872,FALSE,,,,221,FALSE -"TR","tr_jobs_pct_tourism","Percent direct employment in tourism","Percent direct employment in tourism","Ep","proportion","tr_jobs_pct_tourism.csv","rgn_id",,,"year","ep",,TRUE,1988,2026,-1e-04,0.782726,FALSE,,,,221,FALSE -"TR","tr_sustainability","Tourism sustainability index","Tourism Competitiveness Index (TTCI)","S_score","score","tr_sustainability.csv","rgn_id",,,,"s_score",,TRUE,,,2.58,5.3406,FALSE,,,,221,FALSE -"TR","tr_travelwarnings","US State Department travel warnings","Countries with US State Department travel warnings","multiplier","score","tr_travelwarnings.csv","rgn_id",,,"year","multiplier",,TRUE,2008,2016,0,1,TRUE,,,,221,FALSE -"ORE","ore_wind_power","Offshore wind energy","","wind_power","W","ore_wind_power.csv","rgn_id",,,,"wind_power",,TRUE,,,0,3206898.533,FALSE,,,,221,FALSE -"ORE","ore_wave_power","Offshore wave energy","","wave_power","W/m","ore_wave_power.csv","rgn_id",,,,"wave_power",,TRUE,,,0,23.82656023,FALSE,,,,221,FALSE -"ORE","ore_tidal_power","Offshore tidal energy","","power","W","ore_tidal_power.csv","rgn_id",,,,"power",,TRUE,,,0,186.81,FALSE,,,,221,FALSE -"ORE","ore_trend","Offshore trend","","score","trend","ore_trend.csv","rgn_id",,,,"score",,TRUE,,,0.6752,0.6752,TRUE,,,,221,FALSE +"AO","ao_access","Artisanal fisheries management effectiveness and opportunity","The opportunity for artisanal and recreational fishing based on the quality of management of the small-scale fishing sector","value","scaled 0-1","ao_access.csv","rgn_id",,,,"value",,TRUE,,,0,0.854,TRUE,,,,250,FALSE +"AO","ao_need","Economic need for artisanal fishing","Per capita purchasing power parity (PPP) adjusted gross domestic product (GDP): GDPpcPPP as a proxy for subsistence fishing need","value","scaled 0-1","ao_need.csv","rgn_id",,,"year","value",,TRUE,2005,2015,0.0107294720608492,1,TRUE,,,,250,FALSE +"CW","cw_chemical_trend","Chemical pollution trend","Modeled chemical pollution from commercial shipping traffic, ports and harbors, and pesticide use","trend","trend","cw_chemical_trend.csv","rgn_id",,,,"trend",,TRUE,,,-0.3833,0.6007,FALSE,,,,250,FALSE +"CW","cw_nutrient_trend","Nutrient pollution trend","Modeled data based on fertilizer consumption as a proxy for nutrient pollution","trend","trend","cw_nutrient_trend.csv","rgn_id",,,,"trend",,TRUE,,,-1,1,FALSE,,,,250,FALSE +"CW","cw_pathogen_trend","Pathogen pollution trend","Trends in percent of population without access to improved sanitation facilities as a proxy for pathogen pollution","trend","trend","cw_pathogen_trend.csv","rgn_id",,,,"trend",,TRUE,,,-0.53,0.46,FALSE,,,,250,FALSE +"CW","cw_trash_trend","Plastic trash trends","Trends in trash estimated using improperly disposed of plastics","trend","trend","cw_trash_trend.csv","rgn_id",,,,"trend",,TRUE,,,-0.209086973997465,1,FALSE,,,,250,FALSE +"CW pressure","po_chemicals_3nm","Coastal chemical pollution","Modeled chemical pollution from commercial shipping traffic, ports and harbors, land-based pesticide use (organic pollution), and urban runoff (inorganic pollution) ","pressure_score","scaled 0-1","po_chemicals_3nm.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.000314089840492316,0.989726930531591,TRUE,,,,250,FALSE +"CW pressure","po_nutrients_3nm","Coastal nutrient pollution","Modeled data based on fertilizer consumption from the Food and Agricultural Organization","pressure_score","scaled 0-1","po_nutrients_3nm.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.556896588237137,TRUE,,,,250,FALSE +"CW pressure","po_pathogens","Pathogen pollution","Percent of population without access to improved sanitation facilities as a proxy for pathogen pollution","pressure_score","scaled 0-1","po_pathogens.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.909090909090909,TRUE,,,,250,FALSE +"CW pressure","po_trash","Marine plastics","Global marine plastics","pressure_score","scaled 0-1","po_trash.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.0223096329122635,0.843154478466252,TRUE,,,,250,FALSE +"FIS","fis_b_bmsy","B/Bmsy estimates obtained using RAM data (when available) and the catch-MSY method","The ratio of fish population abundance compared to the abundance required to deliver maximum sustainable yield","bbmsy","B/Bmsy","fis_b_bmsy.csv","rgn_id",,"stock_id","year","bbmsy",,TRUE,2001,2010,0.0154,10.7,FALSE,,,,250,FALSE +"FIS","fis_meancatch","Fishery catch data","Mean commercial catch for each OHI region (averaged across years) ","mean_catch","tonnes","fis_meancatch.csv","rgn_id",,"stock_id_taxonkey","year","mean_catch",,TRUE,2001,2010,3.36290652419971e-17,6153125.16129057,FALSE,,,,250,FALSE +"FP","fp_wildcaught_weight","Food provision weights","Proportion of wild caught fisheries to mariculture","w_fis","proportion","fp_wildcaught_weight.csv","rgn_id",,,,"w_fis",,TRUE,,,0.228400667556178,1,TRUE,,,,250,FALSE +"HABCPCS","hab_extent","Habitat extent","Area of habitats: mangrove, saltmarsh, seagrass, soft-bottom, seaice, coral","km2","km2","hab_extent.csv","rgn_id",,"habitat",,"km2",,TRUE,,,0,3800720.2534611,FALSE,,,,250,FALSE +"HABCPCS","hab_health","Habitat condition","Current condition of habitat relative to historical condition","health","proportion","hab_health.csv","rgn_id",,"habitat",,"health",,TRUE,,,0,1,TRUE,,,,250,FALSE +"HABCPCS","hab_trend","Habitat condition trend","Estimated change in habitat condition during most recent 5 years","trend","trend","hab_trend.csv","rgn_id",,"habitat",,"trend",,TRUE,,,-1,1,FALSE,,,,250,FALSE +"ICO","ico_spp_iucn_status","IUCN extinction risk","IUCN extinction risk category for iconic species located within each region","category","IUCN risk category","ico_spp_iucn_status.csv","rgn_id",,"sciname","year",,"category",TRUE,2000,2016,,,FALSE,"iucn_sid",,8585,250, +"LE","le_gdp","GDP","Gross Domestic Product (GDP)","usd","2012 USD","le_gdp.csv",,"cntry_key",,"year","usd",,TRUE,1996,2011,22820838.02,14675462506263.5,FALSE,,,,250,FALSE +"LE","le_gdp_pc_ppp","GDP per capita PPP","Gross domestic product per person at purchasing power parity","usd","USD","le_gdp_pc_ppp.csv",,"cntry_key",,"year","usd",,TRUE,1980,2012,82.65764088,86506.63612,FALSE,,,,250,FALSE +"LE","le_jobs_cur_adj_value","Current jobs adjusted","Modeled LE data","value","value","le_jobs_cur_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,62.41711597,98.8240774,FALSE,,,,250,FALSE +"LE","le_jobs_cur_base_value","Current jobs base","Modeled LE data","value","value","le_jobs_cur_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,7976022.6343,FALSE,,,,250,FALSE +"LE","le_jobs_ref_adj_value","Reference jobs adjusted","Modeled LE data","value","value","le_jobs_ref_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,69.70000277,98.89999998,FALSE,,,,250,FALSE +"LE","le_jobs_ref_base_value","Reference jobs base","Modeled LE data","value","value","le_jobs_ref_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,8148031.2004,FALSE,,,,250,FALSE +"LE","le_jobs_sector_year","Jobs","Modeled LE data","value","number of jobs","le_jobs_sector_year.csv",,"cntry_key","sector","year","value",,TRUE,1990,2010,0,9966925.101,FALSE,,,,250,FALSE +"LE","le_popn","Total human population","Human population of OHI regions","count","number of people","le_popn.csv","rgn_id",,,"year","count",,TRUE,1960,2012,0,1350695000,FALSE,,,,250,FALSE +"LE","le_rev_cur_adj_value","Current revenue adjusted","Modeled LE data","value","value","le_rev_cur_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,27001199.73,13919727042705.6,FALSE,,,,250,FALSE +"LE","le_rev_cur_base_value","Current revenue base","Modeled LE data","value","value","le_rev_cur_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,1319580686744.52,FALSE,,,,250,FALSE +"LE","le_revenue_adj","Revenue adjusted","Modeled LE data","usd","USD","le_revenue_adj.csv",,"cntry_key",,"year","usd",,TRUE,1996,2011,22820838.02,14675462506263.5,FALSE,,,,250,FALSE +"LE","le_rev_ref_adj_value","Reference revenue adjusted","Modeled LE data","value","value","le_rev_ref_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,22820838.02,13667652066195.1,FALSE,,,,250,FALSE +"LE","le_rev_ref_base_value","Reference revenue base","Modeled LE data","value","value","le_rev_ref_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,284189642760,FALSE,,,,250,FALSE +"LE","le_rev_sector_year","Revenue","Modeled LE data","value","2010 USD","le_rev_sector_year.csv",,"cntry_key","sector","year","value",,TRUE,1996,2012,0,1319580686744.52,FALSE,,,,250,FALSE +"LE","le_sector_weight","Sector weight by jobs","Proportion of jobs within each sector","weight","value","le_sector_weight.csv","rgn_id",,"sector",,"weight",,TRUE,,,1,1,TRUE,,,,250,FALSE +"LE","le_unemployment","Unemployment","Modeled LE data","percent","proportion","le_unemployment.csv",,"cntry_key",,"year","percent",,TRUE,1990,2010,0.517311849999999,37.58288403,FALSE,,,,250,FALSE +"LE","le_wage_cur_adj_value","Current wages adjusted","Modeled LE data","value","value","le_wage_cur_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,1,1,TRUE,,,,250,FALSE +"LE","le_wage_cur_base_value","Current wages base","Modeled LE data","value","value","le_wage_cur_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,436558.72173255,FALSE,,,,250,FALSE +"LE","le_wage_ref_adj_value","Reference wages adjusted","Modeled LE data","value","value","le_wage_ref_adj_value.csv",,"cntry_key","sector",,"value",,TRUE,,,1,1,TRUE,,,,250,FALSE +"LE","le_wage_ref_base_value","Reference wages base","Modeled LE data","value","value","le_wage_ref_base_value.csv",,"cntry_key","sector",,"value",,TRUE,,,0,170878.277466168,FALSE,,,,250,FALSE +"LE","le_wage_sector_year","Wages","Modeled LE data","value","2010 USD","le_wage_sector_year.csv",,"cntry_key","sector","year","value",,TRUE,1993,2008,0,436558.72173255,FALSE,,,,250,FALSE +"LE","le_workforcesize_adj","Adjusted workforce size","Modeled LE data","jobs","number of jobs","le_workforcesize_adj.csv",,"cntry_key",,"year","jobs",,TRUE,1990,2012,0,791711771.342352,FALSE,,,,250,FALSE +"LSP","lsp_prot_area_inland1km","Inland coastal protected areas","Protected areas located 1 km inland","a_prot_1km","km2","lsp_prot_area_inland1km.csv","rgn_id",,,"year","a_prot_1km",,TRUE,2000,2015,0,30449.5,FALSE,,,,250,FALSE +"LSP","lsp_prot_area_offshore3nm","Offshore coastal protected areas","Protected areas located 3nm offshore","a_prot_3nm","km2","lsp_prot_area_offshore3nm.csv","rgn_id",,,"year","a_prot_3nm",,TRUE,2000,2015,0,99060,FALSE,,,,250,FALSE +"LSP","rgn_area_inland1km","Inland area","Inland area of OHI regions within 1km of shoreline","area","km2","rgn_area_inland1km.csv","rgn_id",,,,"area",,TRUE,,,1,175147,FALSE,,,,250,FALSE +"LSP","rgn_area_offshore3nm","Offshore area","Offshore area of OHI regions within 3nm of shoreline","area","km2","rgn_area_offshore3nm.csv","rgn_id",,,,"area",,TRUE,,,12.75,621887.75,FALSE,,,,250,FALSE +"MAR","mar_coastalpopn_inland25mi","Inland coastal population","Total coastal population within 25 miles of coast.","popsum","number of people","mar_coastalpopn_inland25mi.csv","rgn_id",,,"year","popsum",,TRUE,2005,2015,0,254433578,FALSE,,,,250,FALSE +"MAR","mar_harvest_tonnes","Mariculture harvest","Tonnes of mariculture harvest","tonnes","tonnes","mar_harvest_tonnes.csv","rgn_id",,"taxa_code","year","tonnes",,TRUE,1950,2014,0,4352694,FALSE,,,,250,FALSE +"MAR","mar_sustainability_score","Mariculture sustainability score","Mariculture sustainability from the Mariculture Sustainability Index (MSI).","sust_coeff","score","mar_sustainability_score.csv","rgn_id",,"taxa_code",,"sust_coeff",,TRUE,,,0.1,1,TRUE,,,,250,FALSE +"NP","np_blast","Areas of blast fishing","Destructive artisanal blast fishing","score","score","np_blast.csv","rgn_id",,,,"score",,TRUE,,,0.006865107932434,0.874460499155564,TRUE,,,,250,FALSE +"NP","np_cyanide","Areas of poison fishing","Destructive artisanal poison (cyanide) fishing","score","score","np_cyanide.csv","rgn_id",,,,"score",,TRUE,,,0.00565484574373731,0.495137734714806,TRUE,,,,250,FALSE +"NP","np_harvest_product_weight","Relative harvest value","Value of harvest of each product relative to total harvest of six marine products (coral, fish oil, seaweed and plants, shells, sponges, ornamental fish). Used to weight contribution of each product to final score.","weight","proportion","np_harvest_product_weight.csv","rgn_id",,"product",,"weight",,TRUE,,,0,1,TRUE,,,,250,FALSE +"NP","np_harvest_tonnes","Natural product harvest","Yield in metric tonnes of six marine products (coral, fish oil, seaweed and plants, shells, sponges, ornamental fish) from FAO","tonnes","tonnes","np_harvest_tonnes.csv","rgn_id",,"product","year","tonnes",,TRUE,1976,2013,0,298403.8,FALSE,,,,250,FALSE +"NP","np_harvest_tonnes_relative","Relative harvest tonnes","Tonnes of harvest of each product relative to total harvest of six marine products (coral, fish oil, seaweed and plants, shells, sponges, ornamental fish). Used to weight contribution of each product to final score.","tonnes_rel","proportion","np_harvest_tonnes_relative.csv","rgn_id",,"product","year","tonnes_rel",,TRUE,1976,2013,0,1,TRUE,,,,250,FALSE +" pressure","cc_acid","Ocean acidification","Ocean acidification pressure scaled using biological thresholds","pressure_score","scaled 0-1","cc_acid.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.0966879482359667,0.692411167229037,TRUE,,,,250,FALSE +" pressure","cc_slr","Sea level rise","Sea level rise pressure","pressure_score","scaled 0-1","cc_slr.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.622744456810226,TRUE,,,,250,FALSE +" pressure","cc_sst","Sea surface temperature anomolies","Sea surface temperature anomolies","pressure_score","scaled 0-1","cc_sst.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.788254063816159,TRUE,,,,250,FALSE +" pressure","cc_uv","UV radiation pressure","Modeled UV radiation based on Erythemal UV Irradiance data provided by GES DISC.","pressure_score","scaled 0-1","cc_uv.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.736063358627025,TRUE,,,,250,FALSE +" pressure","fp_art_hb","High bycatch due to artisanal fishing ","The presence of destructive artisanal blast and poison (cyanide) fishing.","pressure_score","scaled 0-1","fp_art_hb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00790365073391053,1,TRUE,,,,250,FALSE +" pressure","fp_art_lb","Low bycatch due to artisanal fishing ","Extent of artisanal fishing (including: artisanal, subsistence, and recreational catch)","pressure_score","scaled 0-1","fp_art_lb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00084897442244204,0.826165403212667,TRUE,,,,250,FALSE +" pressure","fp_com_hb","High bycatch due to commercial fishing ","Modeled destructive commercial fishing practices by 5 gear types and scaled by Net Primary Productivity","pressure_score","scaled 0-1","fp_com_hb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00333270126858887,0.733160374369164,TRUE,,,,250,FALSE +" pressure","fp_com_lb","Low bycatch due to commercial fishing ","Modeled destructive commercial fishing practices by 2 gear types and scaled by Net Primary Productivity","pressure_score","scaled 0-1","fp_com_lb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00333270126858887,0.733160374369164,TRUE,,,,250,FALSE +" pressure","fp_targetharvest","Targeted harvest of cetaceans and marine turtles","Targeted harvest of cetaceans and marine turtles","pressure_score","scaled 0-1","fp_targetharvest.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" pressure","hd_habitat","Management and protection of habitat to preserve biodiversity","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: habitat related questions","resilience score","scaled 0-1","hd_habitat.csv","rgn_id",,,,"resilience.score",,TRUE,,,0.138087289287079,1,TRUE,,,,250,FALSE +" pressure","hd_intertidal","Intertidal habitat destruction","Coastal population density (25 mi from shore) as a proxy for intertidal habitat destruction","pressure_score","scaled 0-1","hd_intertidal.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" pressure","hd_subtidal_hb","Subtidal hardbottom habitat destruction","High bycatch artisanal fishing practices (blast fishing) as a proxy for subtidal hard bottom habitat destruction","score","scaled 0-1","hd_subtidal_hb.csv","rgn_id",,,,"score",,TRUE,,,0.006865107932434,0.874460499155564,TRUE,,,,250,FALSE +" pressure","hd_subtidal_sb","Subtidal softbottom habitat destruction","Demersal destructive commercial fishing practices (i.e., trawling) in softbottom habitat as a proxy for soft bottom habitat destruction","pressure_score","scaled 0-1","hd_subtidal_sb.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.950344604978492,TRUE,,,,250,FALSE +" pressure","po_chemicals","Chemical pollution","Modeled chemical pollution from commercial shipping traffic, ports and harbors, and pesticide use","pressure_score","scaled 0-1","po_chemicals.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.00747125428241358,0.990734614993975,TRUE,,,,250,FALSE +" pressure","po_nutrients","Nutrient pollution","Modeled data based on fertilizer consumption from the Food and Agricultural Organization","pressure_score","scaled 0-1","po_nutrients.csv","rgn_id",,,,"pressure_score",,TRUE,,,0,0.592252354120511,TRUE,,,,250,FALSE +" pressure","po_water","Management and regulations to control water pollution to preserve biodiversity","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: tourism related questions","resilience score","scaled 0-1","po_water.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" pressure","sp_alien","Nonindigenous species","Measure of harmful invasive species","pressures.score","scaled 0-1","sp_alien.csv","rgn_id",,,,"pressures.score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" pressure","sp_genetic","Genetic escapes","Introduced mariculture species (Mariculture Sustainability Index) as a proxy for genetic escapes ","pressure_score","scaled 0-1","sp_genetic.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.1,1,TRUE,,,,250,FALSE +" pressure","ss_spi","Weakness of social progress","Inverse of Social Progress Index scores","pressure_score","scaled 0-1","ss_spi.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.0991,0.629592741607178,TRUE,,,,250,FALSE +" pressure","ss_wgi","Weakness of governance","Inverse of World Governance Indicators (WGI) six combined scores","pressure_score","scaled 0-1","ss_wgi.csv","rgn_id",,,,"pressure_score",,TRUE,,,0.126337814331055,0.943051262696584,TRUE,,,,250,FALSE +" pressure resilience","element_wts_cp_km2_x_protection","Coastal protection weights","Habitat extent multiplied by habitat protection rank for: coral, mangrove (offshore and inland 1km), saltmarsh, sea ice (shoreline), and seagrass","extent_rank","extent*rank","element_wts_cp_km2_x_protection.csv","rgn_id",,"habitat",,"extent_rank",,TRUE,,,0.000108,2800227.27272727,FALSE,,,,250,FALSE +" pressure resilience","element_wts_cs_km2_x_storage","Carbon storage weights","Habitat extent multiplied by carbon storage capacity for: mangrove (offshore and inland 1km), saltmarsh, and sea ice","extent_rank","extent*storage","element_wts_cs_km2_x_storage.csv","rgn_id",,"habitat",,"extent_rank",,TRUE,,,0.003753,3317914.748642,FALSE,,,,250,FALSE +" pressure resilience","element_wts_hab_pres_abs","Habitat weights","List of habitats in each region","boolean","boolean","element_wts_hab_pres_abs.csv","rgn_id",,"habitat",,"boolean",,TRUE,,,1,1,TRUE,,,,250,FALSE +" resilience","fp_habitat","Management and protection of habitat to preserve biodiversity (fisheries)","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: habitat related questions","resilience score","scaled 0-1","fp_habitat.csv","rgn_id",,,,"resilience.score",,TRUE,,,0.138087289287079,1,TRUE,,,,250,FALSE +" resilience","fp_mora","Commercial fishing management","Regulations and management of commerical fishing","value","scaled 0-1","fp_mora.csv","rgn_id",,,,"value",,TRUE,,,0,0.814394256522431,TRUE,,,,250,FALSE +" resilience","fp_mora_artisanal","Artisanal fisheries management effectiveness and opportunity","The opportunity for artisanal and recreational fishing based on the quality of management of the small-scale fishing sector","value","scaled 0-1","fp_mora_artisanal.csv","rgn_id",,,,"value",,TRUE,,,0,0.854,TRUE,,,,250,FALSE +" resilience","fp_mpa_coast","Coastal protected marine areas to protect fishery resources","Protected marine areas within 3nm of coastline (lasting special places goal calculated for coastal zone)","resilience.score","scaled 0-1","fp_mpa_coast.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" resilience","fp_mpa_eez","EEZ protected marine areas to protect fishery resources","Protected marine areas within EEZ to protect fishery resource (lasting special places goal results)","resilience.score","scaled 0-1","fp_mpa_eez.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" resilience","g_cites","CITES signatories","Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) signatories","resilience_score","scaled 0-1","g_cites.csv","rgn_id",,,,"resilience_score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" resilience","g_mariculture","Management of mariculture practices to preserve biodiversity","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: mariculture related questions","resilience score","scaled 0-1","g_mariculture.csv","rgn_id",,,,"resilience.score",,TRUE,,,0.054428393263486,1,TRUE,,,,250,FALSE +" resilience","g_msi_gov","Mariculture Sustainability Index","Mariculture practice assessment criteria from the Mariculture Sustainability Index (MSI)","resilience score","scaled 0-1","g_msi_gov.csv","rgn_id",,,,"resilience.score",,TRUE,,,0.1,0.8576923077,TRUE,,,,250,FALSE +" resilience","g_tourism","Management of tourism to preserve biodiversity","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: tourism related questions","resilience score","scaled 0-1","g_tourism.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" resilience","hd_mpa_coast","Coastal protected marine areas to protect against habitat destruction","Protected marine areas within 3nm of coastline (lasting special places goal status score)","resilience.score","scaled 0-1","hd_mpa_coast.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" resilience","hd_mpa_eez","Protected marine areas within EEZ to protect against habitat destruction","Protected marine areas within EEZ (lasting special places status score for entire EEZ)","resilience.score","scaled 0-1","hd_mpa_eez.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" resilience","li_gci","Competitiveness in achieving sustained economic prosperity","Global Competitiveness Index (GCI) scores from the World Economic Forum","score","scaled","li_gci.csv","rgn_id",,,,"score",,TRUE,,,0.398989454285714,0.806451177571429,TRUE,,,,250,FALSE +" resilience","li_sector_evenness","Sector evenness as a measure of economic diversity","Shannon's Diversity Index calculated sector evenness based on the total number of sectors and the proportion of jobs belonging to any sector","resilience score","scaled","li_sector_evenness.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,0.997518269205,TRUE,,,,250,FALSE +" resilience","res_spi","Social Progress Index","Social Progress Index scores","resilience_score","scaled 0-1","res_spi.csv","rgn_id",,,,"resilience_score",,TRUE,,,0.370407258392822,0.9009,TRUE,,,,250,FALSE +" resilience","sp_alien_species","Management of nonindigenous species","Survey responses by country to the Convention on Biologicial Diversity (CBD) Third National Report: invasive species related questions","resilience score","scaled 0-1","sp_alien_species.csv","rgn_id",,,,"resilience.score",,TRUE,,,0,1,TRUE,,,,250,FALSE +" resilience","species_diversity_3nm","Measure of coastal ecological integrity","Marine species condition (same calculation and data as the species subgoal status score) calculated within 3 nm of shoreline as a proxy for ecological integrity","score","scaled 0-1","species_diversity_3nm.csv","rgn_id",,,,"score",,TRUE,,,0.877105422176482,0.962966768212714,TRUE,,,,250,FALSE +" resilience","species_diversity_eez","Measure of ecological integrity","Marine species condition (species subgoal status score) as a proxy for ecological integrity","score","scaled 0-1","species_diversity_eez.csv","rgn_id",,,,"score",,TRUE,,,0.871981848756887,0.961226989799502,TRUE,,,,250,FALSE +" resilience","wgi_all","Strength of governance","World Governance Indicators (WGI) six combined scores","resilience_score","scaled 0-1","wgi_all.csv","rgn_id",,,,"resilience_score",,TRUE,,,0.0569487373034157,0.873662185668945,TRUE,,,,250,FALSE +" spatial","cntry_rgn","ISO country codes","Lookup table of country codes (based on ISO 3166 country codes) and Ocean Health Index region idenifiers.","rgn_id","region id","cntry_rgn.csv",,"cntry_key",,,"rgn_id",,TRUE,,,1,250,FALSE,,,,250,FALSE +" spatial","rgn_area","Region areas based on EEZ boundaries","Area of Ocean Health Index regions modified from exclusive economic zones ","area_km2","km2","rgn_area.csv","rgn_id",,,,"area_km2",,TRUE,,,12.7630587776,31886958.884907,FALSE,,,,250,FALSE +"spatial ","rgn_georegions","UN geopolitical region classifications","Lookup table of Ocean Health Index regions and UN geopolitical regions (3 levels), often used for gapfilling missing data","georgn_id","UN regions","rgn_georegions.csv","rgn_id",,"level",,"georgn_id",,TRUE,,,1,999,FALSE,,,,250,FALSE +"spatial ","rgn_global","OHI regions","Subset of regions that are not deleted or disputed ","label","label","rgn_global.csv","rgn_id",,,,,"label",TRUE,,,,,FALSE,,,,250, +"spatial ","rgn_labels","Regions ","Regions by type (eez, subocean, unclaimed)","label","label","rgn_labels.csv","rgn_id",,"type",,,"label",TRUE,,,,,FALSE,,,,250, +"SPP","spp_status","Average species condition","Species condition based on average of IUCN threat categories","score","status score","spp_status.csv","rgn_id",,,,"score",,TRUE,,,0.871981848756887,0.961226989799502,TRUE,,,,250,FALSE +"SPP","spp_trend","Average species condition trend","Species trends based on average of IUCN population trend data","score","trend score","spp_trend.csv","rgn_id",,,,"score",,TRUE,,,-0.307391304347826,-0.0514800222979872,FALSE,,,,250,FALSE +"TR","tr_jobs_pct_tourism","Percent direct employment in tourism","Percent direct employment in tourism","Ep","proportion","tr_jobs_pct_tourism.csv","rgn_id",,,"year","ep",,TRUE,1988,2026,-1e-04,0.782726,FALSE,,,,250,FALSE +"TR","tr_sustainability","Tourism sustainability index","Tourism Competitiveness Index (TTCI)","S_score","score","tr_sustainability.csv","rgn_id",,,,"s_score",,TRUE,,,2.58,5.3406,FALSE,,,,250,FALSE +"TR","tr_travelwarnings","US State Department travel warnings","Countries with US State Department travel warnings","multiplier","score","tr_travelwarnings.csv","rgn_id",,,"year","multiplier",,TRUE,2008,2016,0,1,TRUE,,,,250,FALSE +"ORE","ore_wind_power","Offshore wind energy","","wind_power","W","ore_wind_power.csv","rgn_id",,,,"wind_power",,TRUE,,,0,3206898.533,FALSE,,,,250,FALSE +"ORE","ore_wave_power","Offshore wave energy","","wave_power","W/m","ore_wave_power.csv","rgn_id",,,,"wave_power",,TRUE,,,0,23.82656023,FALSE,,,,250,FALSE +"ORE","ore_tidal_power","Offshore tidal energy","","power","W","ore_tidal_power.csv","rgn_id",,,,"power",,TRUE,,,0,186.81,FALSE,,,,250,FALSE +"ORE","ore_trend","Offshore trend","","score","trend","ore_trend.csv","rgn_id",,,,"score",,TRUE,,,0.6752,0.6752,TRUE,,,,250,FALSE diff --git a/ore2017/layers/ore_trend.csv b/ore2017/layers/ore_trend.csv index 9b3aca0..ee03452 100644 --- a/ore2017/layers/ore_trend.csv +++ b/ore2017/layers/ore_trend.csv @@ -20,9 +20,12 @@ rgn_id,score 19,0.6752 20,0.6752 21,0.6752 +22,0.6752 +23,0.6752 24,0.6752 25,0.6752 26,0.6752 +27,0.6752 28,0.6752 29,0.6752 30,0.6752 @@ -78,9 +81,11 @@ rgn_id,score 80,0.6752 81,0.6752 82,0.6752 +83,0.6752 84,0.6752 85,0.6752 86,0.6752 +87,0.6752 88,0.6752 89,0.6752 90,0.6752 @@ -102,6 +107,7 @@ rgn_id,score 106,0.6752 107,0.6752 108,0.6752 +109,0.6752 110,0.6752 111,0.6752 112,0.6752 @@ -120,6 +126,7 @@ rgn_id,score 125,0.6752 126,0.6752 127,0.6752 +128,0.6752 129,0.6752 130,0.6752 131,0.6752 @@ -133,6 +140,7 @@ rgn_id,score 139,0.6752 140,0.6752 141,0.6752 +142,0.6752 143,0.6752 144,0.6752 145,0.6752 @@ -150,14 +158,17 @@ rgn_id,score 157,0.6752 158,0.6752 159,0.6752 +160,0.6752 161,0.6752 162,0.6752 163,0.6752 164,0.6752 +165,0.6752 166,0.6752 167,0.6752 168,0.6752 169,0.6752 +170,0.6752 171,0.6752 172,0.6752 173,0.6752 @@ -188,6 +199,7 @@ rgn_id,score 198,0.6752 199,0.6752 200,0.6752 +201,0.6752 202,0.6752 203,0.6752 204,0.6752 @@ -197,11 +209,13 @@ rgn_id,score 208,0.6752 209,0.6752 210,0.6752 +211,0.6752 212,0.6752 213,0.6752 214,0.6752 215,0.6752 216,0.6752 +217,0.6752 218,0.6752 219,0.6752 220,0.6752 @@ -209,13 +223,28 @@ rgn_id,score 222,0.6752 223,0.6752 224,0.6752 +225,0.6752 +226,0.6752 227,0.6752 228,0.6752 +229,0.6752 +230,0.6752 231,0.6752 232,0.6752 +233,0.6752 +234,0.6752 +235,0.6752 +236,0.6752 237,0.6752 +238,0.6752 +239,0.6752 +240,0.6752 +241,0.6752 +242,0.6752 +243,0.6752 244,0.6752 245,0.6752 +246,0.6752 247,0.6752 248,0.6752 249,0.6752 diff --git a/ore2017/temp/referencePoints.csv b/ore2017/temp/referencePoints.csv index 8e50670..5bb214b 100644 --- a/ore2017/temp/referencePoints.csv +++ b/ore2017/temp/referencePoints.csv @@ -1,5 +1,5 @@ "goal","method","reference_point" -"MAR","spatial 95th quantile","region id: 73 value: 0.0144976059300736" +"MAR","spatial 95th quantile","region id: 143 value: 0.014627074305077" "AO","??",NA "NP","Harvest peak within region times 0.65 buffer","varies for each region" "CS","Health/condition variable based on current vs. historic extent","varies for each region/habitat" @@ -10,3 +10,4 @@ "CW","spatial: pressures scaled from 0-1 at raster level",NA "HAB","Health/condition variable based on current vs. historic extent","varies for each region/habitat" "SPP","Average of IUCN risk categories, scaled to historic extinction",NA +"ORE","Amount of energy enough to power 1000 houses","1e+06"