Bias Analysis
Thalia Ballell Carl
2024-04-12
ESVD
###1 ESVD
options(repos = "https://cloud.r-project.org")
install.packages("ggrepel")## Installing package into 'C:/Users/thali/AppData/Local/R/win-library/4.2'
## (as 'lib' is unspecified)## package 'ggrepel' successfully unpacked and MD5 sums checked
##
## The downloaded binary packages are in
## C:\Users\thali\AppData\Local\Temp\RtmpQl5yGb\downloaded_packagessetwd("C:/Users/thali/OneDrive - Wageningen University & Research/Escritorio/MASTERS/13. 14. 15. Internship/TASKS/4. DUPLICATES AND HOTSPOTS")
data <- read.csv("C:/Users/thali/OneDrive - Wageningen University & Research/Escritorio/MASTERS/13. 14. 15. Internship/TASKS/4. DUPLICATES AND HOTSPOTS/ESVD MASTER 230616.xlsx - ESVD MASTER 230616.csv")
summary(data)## ValueID StudyID Biome Biome_Code
## Min. : 20001 Min. : 2.0 Length:12390 Length:12390
## 1st Qu.: 4510016 1st Qu.: 451.0 Class :character Class :character
## Median : 8480014 Median : 848.0 Mode :character Mode :character
## Mean : 7860779 Mean : 786.1
## 3rd Qu.:11030002 3rd Qu.:1103.0
## Max. :13750001 Max. :1375.0
## NA's :1498 NA's :1498
## Biome_1 Biome_2 Biome_3 Biome_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Biome_5 Biome_6 Biome_7 ESVD2.0_Biome
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_Code ESVD2.0_Biome_1 ESVD2.0_Biome_2 ESVD2.0_Biome_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_4 ESVD2.0_Biome_5 ESVD2.0_Biome_6 ESVD2.0_Biome_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_8 ESVD2.0_Biome_10 ESVD2.0_Ecozone ESVD2.0_Ecozone_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_1 ESVD2.0_Ecozone_2 ESVD2.0_Ecozone_3 ESVD2.0_Ecozone_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_5 ESVD2.0_Ecozone_6 ESVD2.0_Ecozone_7 ESVD2.0_Ecozone_8
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_9 ESVD2.0_Ecozone_10 ESVD2.0_Ecozone_11 ESVD2.0_Ecozone_12
## Length:12390 Mode:logical Mode:logical Mode:logical
## Class :character NA's:12390 NA's:12390 NA's:12390
## Mode :character
##
##
##
##
## ESVD2.0_Ecozone_13 ESVD2.0_Ecosystem ESVD2.0_Ecosystem_Code
## Mode:logical Length:12390 Length:12390
## NA's:12390 Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_1 ESVD2.0_Ecosystem_2 ESVD2.0_Ecosystem_3
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_4 ESVD2.0_Ecosystem_5 ESVD2.0_Ecosystem_6
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_7 ESVD2.0_Ecosystem_8 ESVD2.0_Ecosystem_9
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_10 ESVD2.0_Ecosystem_11 ESVD2.0_Ecosystem_12
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem Ecosystem_Code Ecosystem_1 Ecosystem_2
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_3 Ecosystem_4 Ecosystem_5 Ecosystem_6
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_7 Ecosystem_8 Ecosystem_9 Ecosystem_10
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_11 Ecosystem_12 Ecosystem_13 Ecosystem_14
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_15 Ecosystem_Text ES_Text TEEB_ES
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## TEEB_SubES ES_1 ES_2 ES_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_4 ES_5 ES_6 ES_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_8 ES_9 ES_10 ES_11
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_12 ES_13 ES_14 ES_15
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_16 ES_17 CICES SEEA_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_1_text SEEA_ES_2_text SEEA_ES_3_text SEEA_ES_4_text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_5_text SEEA_ES_6_text SEEA_ES_7_text SEEA_ES_8_text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_9_text SEEA_ES_10_text Country Country_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_1 Country_Code_2 Country_Code_3 Country_Code_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_5 Country_Code_6 Country_Code_7 Country_Code_8
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_9 Country_1 Country_2 Country_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_4 Country_5 Country_6 Country_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_8 Country_9 Continent_Code Regions_FAO
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Scale_Text Scale_Code Location_Name Protected_Status
## Length:12390 Min. :1.000 Length:12390 Min. :0.000
## Class :character 1st Qu.:1.000 Class :character 1st Qu.:0.000
## Mode :character Median :1.000 Mode :character Median :1.000
## Mean :1.589 Mean :0.887
## 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :5.000 Max. :2.000
## NA's :1499 NA's :4165
## Site_Area Area_Unit Area_ha Site_Length
## Length:12390 Length:12390 Length:12390 Min. : 1
## Class :character Class :character Class :character 1st Qu.: 28
## Mode :character Mode :character Mode :character Median : 52
## Mean : 4082
## 3rd Qu.: 942
## Max. :700000
## NA's :12079
## Length_Unit Length_km Condition_Text Condition_Code
## Length:12390 Length:12390 Length:12390 Min. :0.000
## Class :character Class :character Class :character 1st Qu.:1.000
## Mode :character Mode :character Mode :character Median :1.000
## Mean :1.143
## 3rd Qu.:2.000
## Max. :2.000
## NA's :7824
## Latitude Longitude Valuation_Method Valuation_Method_1
## Min. :-55.062 Min. :-172.438 Length:12390 Length:12390
## 1st Qu.: 4.961 1st Qu.: -5.983 Class :character Class :character
## Median : 24.883 Median : 8.002 Mode :character Mode :character
## Mean : 24.215 Mean : 13.072
## 3rd Qu.: 50.717 3rd Qu.: 40.365
## Max. : 77.875 Max. : 178.457
## NA's :1553 NA's :1553
## Valuation_Method_2 Valuation_Method_3 Valuation_Method_4 Valuation_Method_5
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Valuation_Method_6 Valuation_Method_7 Valuation_Method_8 Valued_Change_Text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Value_Original Currency_Code Value_year Spatial_Unit
## Length:12390 Length:12390 Min. :1970 Length:12390
## Class :character Class :character 1st Qu.:2004 Class :character
## Mode :character Mode :character Median :2011 Mode :character
## Mean :2009
## 3rd Qu.:2015
## Max. :2022
## NA's :1498
## Temporal_Unit PV_Years PV_Rate Beneficiary_Unit
## Length:12390 Min. : 3.00 Min. :-0.020 Length:12390
## Class :character 1st Qu.: 20.00 1st Qu.: 0.030 Class :character
## Mode :character Median : 30.00 Median : 0.046 Mode :character
## Mean : 44.65 Mean : 0.226
## 3rd Qu.:100.00 3rd Qu.: 0.100
## Max. :111.00 Max. :75.000
## NA's :10795 NA's :10774
## Beneficiary_Number Beneficiary_Type INT._2020_ha_yr_all Authors
## Length:12390 Length:12390 Min. :0.000e+00 Length:12390
## Class :character Class :character 1st Qu.:1.700e+01 Class :character
## Mode :character Mode :character Median :1.920e+02 Mode :character
## Mean :1.479e+09
## 3rd Qu.:1.469e+03
## Max. :1.853e+12
## NA's :5739
## Year_Pub Title Reference Notes
## Min. :1973 Length:12390 Length:12390 Length:12390
## 1st Qu.:2008 Class :character Class :character Class :character
## Median :2014 Mode :character Mode :character Mode :character
## Mean :2012
## 3rd Qu.:2019
## Max. :2023
## NA's :1498
## Secondary_sources Coded_By Coded_Date Reviewer
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Review_Date Checked_by_internal Incl_Excl Comments_Incl_Excl
## Length:12390 Length:12390 Min. :0.000 Length:12390
## Class :character Class :character 1st Qu.:1.000 Class :character
## Mode :character Mode :character Median :1.000 Mode :character
## Mean :0.984
## 3rd Qu.:1.000
## Max. :1.000
## NA's :3911
## Scenario Ex_post_ante Attribute_of_baseline_1
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Metric_BL_1 Unit_BL_1 BL_atr._value_1
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Attribute_of_baseline_2 Metric_BL_2 Unit_BL_2
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## BL_2 Attribute_of_baseline_3 Metric_BL_3
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Unit_BL_3 BL_atr._value_3 Attribute_of_baseline_4
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Metric_BL_4 Unit_BL_4 BL_4 Attribute_of_C_1
## Length:12390 Length:12390 Min. : 70.0 Length:12390
## Class :character Class :character 1st Qu.: 70.0 Class :character
## Mode :character Mode :character Median : 710.0 Mode :character
## Mean : 860.3
## 3rd Qu.:1391.0
## Max. :2320.0
## NA's :12383
## Metric_of_C_1 Unit_of_C_1 C_Value_1 Attribute_of_C_2
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_2 Unit_of_C_2 C_Value_2 Attribute_of_C_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_3 Unit_of_C_3 C_Value_3 Attribute_of_C_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_4 Unit_of_C_4 C_Value_4 Attribute_of_C_5
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_5 Unit_of_C_5 C_Value_5 Attribute_of_C_6
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_6 Unit_of_C_6 C_Value_6 Value_fraction
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Value_measure net_vs_gross Value_data
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Comments_and_Notes_new_variables
## Length:12390
## Class :character
## Mode :character
##
##
##
## library(ggplot2)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(maps)
library(mapdata)
library(MASS)##
## Attaching package: 'MASS'## The following object is masked from 'package:dplyr':
##
## select##1A GEOGRAPHY
# Aggregate data by country
country_counts <- data %>%
group_by(Country_Code) %>%
summarise(count = n())
data_clean <- data[complete.cases(data$Longitude, data$Latitude), ]
# Load map data
world_map <- map_data("world")
# Plot the map with datapoints
ggplot() +
geom_polygon(data = world_map, aes(x = long, y = lat, group = group), fill = "grey", color = "white") +
geom_point(data = data_clean, aes(x = Longitude, y = Latitude), alpha = 0.5, color = "red") +
theme_void() +
labs(title = "Heatmap of Datapoints on World Map")
ggplot(data = data_clean, aes(x = Longitude, y = Latitude)) +
geom_polygon(data = world_map, aes(x = long, y = lat, group = group), fill = "#f2f2f2", color = "#cccccc", linewidth = 0.5) +
geom_point(alpha = 0.5, size = 0.5, color = "darkgreen") +
scale_alpha(range = c(0.1, 0.7)) +
theme_minimal() +
labs(title = "Geographical Distribution of ESVD Data",
subtitle = "Datapoints",
caption = "Source: ESVD MASTER 230616") +
theme(plot.title = element_text(size = 18, face = "bold", hjust = 0.5),
plot.subtitle = element_text(size = 14, hjust = 0.5),
plot.caption = element_text(size = 10, hjust = 0),
axis.title = element_text(size = 12),
axis.text = element_text(size = 10))
# Plot the map with heatmap
ggplot() +
geom_polygon(data = world_map, aes(x = long, y = lat, group = group), fill = "darkgrey", color = "white") +
stat_density_2d(data = data_clean, aes(x = Longitude, y = Latitude, fill = after_stat(level)), geom = "polygon", alpha = 0.3) +
scale_fill_gradientn(colors = c("darkblue", "blue", "cyan", "yellow", "red"), name = "Density") +
scale_alpha(range = c(0.1, 0.5), guide = "none") +
theme_minimal() +
labs(title = "Heatmap of Datapoints on World Map")
ggplot() +
geom_polygon(data = world_map, aes(x = long, y = lat, group = group), fill = "darkgrey", color = "white") +
stat_density_2d(data = data_clean, aes(x = Longitude, y = Latitude, fill = after_stat(level)), geom = "polygon", alpha = 0.5) +
scale_fill_viridis_c(name = "Density") +
theme_minimal() +
labs(title = "Geographical Distribution of ESVD Data",
subtitle = "Density of Values",
fill = "Density",
caption = "Source: ESVD MASTER 230616",
x = "Longitude", y = "Latitude") +
theme(plot.title = element_text(size = 18, face = "bold", hjust = 0.5),
plot.subtitle = element_text(size = 14, hjust = 0.5),
plot.caption = element_text(size = 10, hjust = 0),
legend.title = element_text(size = 12),
legend.text = element_text(size = 10))
##1B BIOMES
library(dplyr)
library(tidyr)
library(ggplot2)
summary(data)## ValueID StudyID Biome Biome_Code
## Min. : 20001 Min. : 2.0 Length:12390 Length:12390
## 1st Qu.: 4510016 1st Qu.: 451.0 Class :character Class :character
## Median : 8480014 Median : 848.0 Mode :character Mode :character
## Mean : 7860779 Mean : 786.1
## 3rd Qu.:11030002 3rd Qu.:1103.0
## Max. :13750001 Max. :1375.0
## NA's :1498 NA's :1498
## Biome_1 Biome_2 Biome_3 Biome_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Biome_5 Biome_6 Biome_7 ESVD2.0_Biome
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_Code ESVD2.0_Biome_1 ESVD2.0_Biome_2 ESVD2.0_Biome_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_4 ESVD2.0_Biome_5 ESVD2.0_Biome_6 ESVD2.0_Biome_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_8 ESVD2.0_Biome_10 ESVD2.0_Ecozone ESVD2.0_Ecozone_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_1 ESVD2.0_Ecozone_2 ESVD2.0_Ecozone_3 ESVD2.0_Ecozone_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_5 ESVD2.0_Ecozone_6 ESVD2.0_Ecozone_7 ESVD2.0_Ecozone_8
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_9 ESVD2.0_Ecozone_10 ESVD2.0_Ecozone_11 ESVD2.0_Ecozone_12
## Length:12390 Mode:logical Mode:logical Mode:logical
## Class :character NA's:12390 NA's:12390 NA's:12390
## Mode :character
##
##
##
##
## ESVD2.0_Ecozone_13 ESVD2.0_Ecosystem ESVD2.0_Ecosystem_Code
## Mode:logical Length:12390 Length:12390
## NA's:12390 Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_1 ESVD2.0_Ecosystem_2 ESVD2.0_Ecosystem_3
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_4 ESVD2.0_Ecosystem_5 ESVD2.0_Ecosystem_6
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_7 ESVD2.0_Ecosystem_8 ESVD2.0_Ecosystem_9
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_10 ESVD2.0_Ecosystem_11 ESVD2.0_Ecosystem_12
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem Ecosystem_Code Ecosystem_1 Ecosystem_2
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_3 Ecosystem_4 Ecosystem_5 Ecosystem_6
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_7 Ecosystem_8 Ecosystem_9 Ecosystem_10
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_11 Ecosystem_12 Ecosystem_13 Ecosystem_14
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_15 Ecosystem_Text ES_Text TEEB_ES
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## TEEB_SubES ES_1 ES_2 ES_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_4 ES_5 ES_6 ES_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_8 ES_9 ES_10 ES_11
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_12 ES_13 ES_14 ES_15
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_16 ES_17 CICES SEEA_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_1_text SEEA_ES_2_text SEEA_ES_3_text SEEA_ES_4_text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_5_text SEEA_ES_6_text SEEA_ES_7_text SEEA_ES_8_text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_9_text SEEA_ES_10_text Country Country_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_1 Country_Code_2 Country_Code_3 Country_Code_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_5 Country_Code_6 Country_Code_7 Country_Code_8
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_9 Country_1 Country_2 Country_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_4 Country_5 Country_6 Country_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_8 Country_9 Continent_Code Regions_FAO
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Scale_Text Scale_Code Location_Name Protected_Status
## Length:12390 Min. :1.000 Length:12390 Min. :0.000
## Class :character 1st Qu.:1.000 Class :character 1st Qu.:0.000
## Mode :character Median :1.000 Mode :character Median :1.000
## Mean :1.589 Mean :0.887
## 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :5.000 Max. :2.000
## NA's :1499 NA's :4165
## Site_Area Area_Unit Area_ha Site_Length
## Length:12390 Length:12390 Length:12390 Min. : 1
## Class :character Class :character Class :character 1st Qu.: 28
## Mode :character Mode :character Mode :character Median : 52
## Mean : 4082
## 3rd Qu.: 942
## Max. :700000
## NA's :12079
## Length_Unit Length_km Condition_Text Condition_Code
## Length:12390 Length:12390 Length:12390 Min. :0.000
## Class :character Class :character Class :character 1st Qu.:1.000
## Mode :character Mode :character Mode :character Median :1.000
## Mean :1.143
## 3rd Qu.:2.000
## Max. :2.000
## NA's :7824
## Latitude Longitude Valuation_Method Valuation_Method_1
## Min. :-55.062 Min. :-172.438 Length:12390 Length:12390
## 1st Qu.: 4.961 1st Qu.: -5.983 Class :character Class :character
## Median : 24.883 Median : 8.002 Mode :character Mode :character
## Mean : 24.215 Mean : 13.072
## 3rd Qu.: 50.717 3rd Qu.: 40.365
## Max. : 77.875 Max. : 178.457
## NA's :1553 NA's :1553
## Valuation_Method_2 Valuation_Method_3 Valuation_Method_4 Valuation_Method_5
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Valuation_Method_6 Valuation_Method_7 Valuation_Method_8 Valued_Change_Text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Value_Original Currency_Code Value_year Spatial_Unit
## Length:12390 Length:12390 Min. :1970 Length:12390
## Class :character Class :character 1st Qu.:2004 Class :character
## Mode :character Mode :character Median :2011 Mode :character
## Mean :2009
## 3rd Qu.:2015
## Max. :2022
## NA's :1498
## Temporal_Unit PV_Years PV_Rate Beneficiary_Unit
## Length:12390 Min. : 3.00 Min. :-0.020 Length:12390
## Class :character 1st Qu.: 20.00 1st Qu.: 0.030 Class :character
## Mode :character Median : 30.00 Median : 0.046 Mode :character
## Mean : 44.65 Mean : 0.226
## 3rd Qu.:100.00 3rd Qu.: 0.100
## Max. :111.00 Max. :75.000
## NA's :10795 NA's :10774
## Beneficiary_Number Beneficiary_Type INT._2020_ha_yr_all Authors
## Length:12390 Length:12390 Min. :0.000e+00 Length:12390
## Class :character Class :character 1st Qu.:1.700e+01 Class :character
## Mode :character Mode :character Median :1.920e+02 Mode :character
## Mean :1.479e+09
## 3rd Qu.:1.469e+03
## Max. :1.853e+12
## NA's :5739
## Year_Pub Title Reference Notes
## Min. :1973 Length:12390 Length:12390 Length:12390
## 1st Qu.:2008 Class :character Class :character Class :character
## Median :2014 Mode :character Mode :character Mode :character
## Mean :2012
## 3rd Qu.:2019
## Max. :2023
## NA's :1498
## Secondary_sources Coded_By Coded_Date Reviewer
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Review_Date Checked_by_internal Incl_Excl Comments_Incl_Excl
## Length:12390 Length:12390 Min. :0.000 Length:12390
## Class :character Class :character 1st Qu.:1.000 Class :character
## Mode :character Mode :character Median :1.000 Mode :character
## Mean :0.984
## 3rd Qu.:1.000
## Max. :1.000
## NA's :3911
## Scenario Ex_post_ante Attribute_of_baseline_1
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Metric_BL_1 Unit_BL_1 BL_atr._value_1
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Attribute_of_baseline_2 Metric_BL_2 Unit_BL_2
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## BL_2 Attribute_of_baseline_3 Metric_BL_3
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Unit_BL_3 BL_atr._value_3 Attribute_of_baseline_4
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Metric_BL_4 Unit_BL_4 BL_4 Attribute_of_C_1
## Length:12390 Length:12390 Min. : 70.0 Length:12390
## Class :character Class :character 1st Qu.: 70.0 Class :character
## Mode :character Mode :character Median : 710.0 Mode :character
## Mean : 860.3
## 3rd Qu.:1391.0
## Max. :2320.0
## NA's :12383
## Metric_of_C_1 Unit_of_C_1 C_Value_1 Attribute_of_C_2
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_2 Unit_of_C_2 C_Value_2 Attribute_of_C_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_3 Unit_of_C_3 C_Value_3 Attribute_of_C_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_4 Unit_of_C_4 C_Value_4 Attribute_of_C_5
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_5 Unit_of_C_5 C_Value_5 Attribute_of_C_6
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_6 Unit_of_C_6 C_Value_6 Value_fraction
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Value_measure net_vs_gross Value_data
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Comments_and_Notes_new_variables
## Length:12390
## Class :character
## Mode :character
##
##
##
## # Gather the specified columns into a new dataframe
gathered_data <- gather(data, key = "Column", value = "Biomess",
ESVD2.0_Biome_1:ESVD2.0_Biome_10)
# Filter out empty cells
gathered_data <- gathered_data[!is.na(gathered_data$Biomess) & gathered_data$Biomess != "", ]
# Reset row names
rownames(gathered_data) <- NULL
# Show the first few rows of the gathered data
head(gathered_data)## ValueID StudyID Biome Biome_Code
## 1 20001 2 Coastal systems (incl wetlands) 3
## 2 30001 3 Coral reefs 2
## 3 30002 3 Coral reefs 2
## 4 30003 3 Coral reefs 2
## 5 30004 3 Coral reefs 2
## 6 30005 3 Coral reefs 2
## Biome_1 Biome_2 Biome_3 Biome_4 Biome_5 Biome_6
## 1 Coastal systems (incl wetlands)
## 2 Coral reefs
## 3 Coral reefs
## 4 Coral reefs
## 5 Coral reefs
## 6 Coral reefs
## Biome_7 ESVD2.0_Biome ESVD2.0_Biome_Code ESVD2.0_Ecozone
## 1 Coastal systems 2 Coastal wetlands and river deltas
## 2 Marine 1 Shelf sea
## 3 Marine 1 Shelf sea
## 4 Marine 1 Shelf sea
## 5 Marine 1 Shelf sea
## 6 Marine 1 Shelf sea
## ESVD2.0_Ecozone_Code ESVD2.0_Ecozone_1 ESVD2.0_Ecozone_2
## 1 2.4 Coastal wetlands and river deltas
## 2 1.1 Shelf sea
## 3 1.1 Shelf sea
## 4 1.1 Shelf sea
## 5 1.1 Shelf sea
## 6 1.1 Shelf sea
## ESVD2.0_Ecozone_3 ESVD2.0_Ecozone_4 ESVD2.0_Ecozone_5 ESVD2.0_Ecozone_6
## 1
## 2
## 3
## 4
## 5
## 6
## ESVD2.0_Ecozone_7 ESVD2.0_Ecozone_8 ESVD2.0_Ecozone_9 ESVD2.0_Ecozone_10
## 1 NA
## 2 NA
## 3 NA
## 4 NA
## 5 NA
## 6 NA
## ESVD2.0_Ecozone_11 ESVD2.0_Ecozone_12 ESVD2.0_Ecozone_13 ESVD2.0_Ecosystem
## 1 NA NA NA Mangroves
## 2 NA NA NA Coral reefs
## 3 NA NA NA Coral reefs
## 4 NA NA NA Coral reefs
## 5 NA NA NA Coral reefs
## 6 NA NA NA Coral reefs
## ESVD2.0_Ecosystem_Code ESVD2.0_Ecosystem_1 ESVD2.0_Ecosystem_2
## 1 2.4.2 Mangroves
## 2 1.1.3 Coral reefs
## 3 1.1.3 Coral reefs
## 4 1.1.3 Coral reefs
## 5 1.1.3 Coral reefs
## 6 1.1.3 Coral reefs
## ESVD2.0_Ecosystem_3 ESVD2.0_Ecosystem_4 ESVD2.0_Ecosystem_5
## 1
## 2
## 3
## 4
## 5
## 6
## ESVD2.0_Ecosystem_6 ESVD2.0_Ecosystem_7 ESVD2.0_Ecosystem_8
## 1
## 2
## 3
## 4
## 5
## 6
## ESVD2.0_Ecosystem_9 ESVD2.0_Ecosystem_10 ESVD2.0_Ecosystem_11
## 1
## 2
## 3
## 4
## 5
## 6
## ESVD2.0_Ecosystem_12 Ecosystem Ecosystem_Code Ecosystem_1 Ecosystem_2
## 1 Mangroves 3.4 Mangroves
## 2 Barrier reefs 2.1 Barrier reefs
## 3 Barrier reefs 2.1 Barrier reefs
## 4 Barrier reefs 2.1 Barrier reefs
## 5 Barrier reefs 2.1 Barrier reefs
## 6 Barrier reefs 2.1 Barrier reefs
## Ecosystem_3 Ecosystem_4 Ecosystem_5 Ecosystem_6 Ecosystem_7 Ecosystem_8
## 1
## 2
## 3
## 4
## 5
## 6
## Ecosystem_9 Ecosystem_10 Ecosystem_11 Ecosystem_12 Ecosystem_13 Ecosystem_14
## 1
## 2
## 3
## 4
## 5
## 6
## Ecosystem_15 Ecosystem_Text ES_Text TEEB_ES TEEB_SubES
## 1 Mangrove Fisheries 1 11
## 2 Barrier Reef Fisheries 1; 19 11; 194
## 3 Barrier Reef Tourism value 19 192
## 4 Barrier Reef Recreational value 19 191
## 5 Barrier Reef Fisheries 1; 19 11; 194
## 6 Barrier Reef Tourism value 19 192
## ES_1
## 1 Food
## 2 Food
## 3 Opportunities for recreation and tourism
## 4 Opportunities for recreation and tourism
## 5 Food
## 6 Opportunities for recreation and tourism
## ES_2 ES_3 ES_4 ES_5 ES_6 ES_7 ES_8 ES_9
## 1
## 2 Opportunities for recreation and tourism
## 3
## 4
## 5 Opportunities for recreation and tourism
## 6
## ES_10 ES_11 ES_12 ES_13 ES_14 ES_15 ES_16 ES_17 CICES SEEA_Code
## 1 1.1.6.1 1.6
## 2 1.1.6.1; 1.3.X.X 1.6; 3.1
## 3 3.1.1.1; 3.1.1.2 3.1
## 4 3.1.1.1; 3.1.1.2 3.1
## 5 1.1.6.1; 1.3.X.X 1.6; 3.1
## 6 3.1.1.1; 3.1.1.2 3.1
## SEEA_ES_1_text
## 1 Wild fish and other natural aquatic biomass provisioning services
## 2 Wild fish and other natural aquatic biomass provisioning services
## 3 Recreation-related services
## 4 Recreation-related services
## 5 Wild fish and other natural aquatic biomass provisioning services
## 6 Recreation-related services
## SEEA_ES_2_text SEEA_ES_3_text SEEA_ES_4_text SEEA_ES_5_text
## 1
## 2 Recreation-related services
## 3
## 4
## 5 Recreation-related services
## 6
## SEEA_ES_6_text SEEA_ES_7_text SEEA_ES_8_text SEEA_ES_9_text SEEA_ES_10_text
## 1
## 2
## 3
## 4
## 5
## 6
## Country Country_Code Country_Code_1 Country_Code_2
## 1 Mexico, United Mexican States MEX MEX
## 2 Australia, Commonwealth of AUS AUS
## 3 Australia, Commonwealth of AUS AUS
## 4 Australia, Commonwealth of AUS AUS
## 5 Australia, Commonwealth of AUS AUS
## 6 Australia, Commonwealth of AUS AUS
## Country_Code_3 Country_Code_4 Country_Code_5 Country_Code_6 Country_Code_7
## 1
## 2
## 3
## 4
## 5
## 6
## Country_Code_8 Country_Code_9 Country_1 Country_2
## 1 Mexico, United Mexican States
## 2 Australia, Commonwealth of
## 3 Australia, Commonwealth of
## 4 Australia, Commonwealth of
## 5 Australia, Commonwealth of
## 6 Australia, Commonwealth of
## Country_3 Country_4 Country_5 Country_6 Country_7 Country_8 Country_9
## 1
## 2
## 3
## 4
## 5
## 6
## Continent_Code Regions_FAO Scale_Text Scale_Code
## 1 NoA Central America & the Caribbean Sub-national 2
## 2 OC Oceania National 3
## 3 OC Oceania National 3
## 4 OC Oceania National 3
## 5 OC Oceania National 3
## 6 OC Oceania National 3
## Location_Name Protected_Status Site_Area Area_Unit Area_ha Site_Length
## 1 Gulf of California 1 50 km2 5000 NA
## 2 Great Barrier Reef 2 7253.4 km2 725340 NA
## 3 Great Barrier Reef 2 7253.4 km2 725340 NA
## 4 Great Barrier Reef 2 7253.4 km2 725340 NA
## 5 Great Barrier Reef 2 7253.4 km2 725340 NA
## 6 Great Barrier Reef 2 7253.4 km2 725340 NA
## Length_Unit Length_km
## 1
## 2
## 3
## 4
## 5
## 6
## Condition_Text
## 1 mangroves are disappearing at a regional rate of 2% annually because of sedimentation, eutrophication, and deforestation
## 2
## 3
## 4
## 5
## 6
## Condition_Code Latitude Longitude Valuation_Method Valuation_Method_1
## 1 1 28.000 -112.0 PF PF
## 2 NA -18.283 147.7 IO IO
## 3 NA -18.283 147.7 IO IO
## 4 NA -18.283 147.7 FI FI
## 5 NA -18.283 147.7 IO IO
## 6 NA -18.283 147.7 IO IO
## Valuation_Method_2 Valuation_Method_3 Valuation_Method_4 Valuation_Method_5
## 1
## 2
## 3
## 4
## 5
## 6
## Valuation_Method_6 Valuation_Method_7 Valuation_Method_8
## 1
## 2
## 3
## 4
## 5
## 6
## Valued_Change_Text Value_Original Currency_Code
## 1 the current flow of services without any change 37500 USD
## 2 139000000 AUD
## 3 5117000000 AUD
## 4 153000000 AUD
## 5 130000000 AUD
## 6 4764000000 AUD
## Value_year Spatial_Unit Temporal_Unit PV_Years PV_Rate Beneficiary_Unit
## 1 2005 hectare year NA NA total
## 2 2007 total area year NA NA total
## 3 2007 total area year NA NA total
## 4 2007 total area year NA NA total
## 5 2006 total area year NA NA total
## 6 2006 total area year NA NA total
## Beneficiary_Number Beneficiary_Type INT._2020_ha_yr_all
## 1 Fisheries 53760.51
## 2 residents, general public 160.48
## 3 general public, visitors, tourists 5907.76
## 4 visitors 176.64
## 5 residents, general public 157.61
## 6 visitors, tourists 5775.86
## Authors Year_Pub
## 1 Aburto-Oropeza et al 2008
## 2 Access Economics 2009
## 3 Access Economics 2009
## 4 Access Economics 2009
## 5 Access Economics 2009
## 6 Access Economics 2009
## Title
## 1 Mangroves in the Gulf of California increase fishery yields
## 2 Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## 3 Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## 4 Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## 5 Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## 6 Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## Reference
## 1 Aburto-Oropeza, O., Ezcurra, E., Danemann, G., Valdez, V., Murray, J., & Sala, E. (2008). Mangroves in the Gulf of California increase fishery yields. Proceedings of the National Academy of Sciences, 105(30), 10456-10459.
## 2 Access Economics (2009) Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## 3 Access Economics (2009) Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## 4 Access Economics (2009) Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## 5 Access Economics (2009) Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## 6 Access Economics (2009) Economic Contribution of the Great Barrier Reef Marine Park, 2006-2007
## Notes
## 1
## 2 Site area is the estimated area of coral cover; values for 2006&2005 taken from 2009 report for methodological consistency
## 3 Site area is the estimated area of coral cover; values for 2006&2005 taken from 2009 report for methodological consistency
## 4 Site area is the estimated area of coral cover; values for 2006&2005 taken from 2009 report for methodological consistency
## 5 Site area is the estimated area of coral cover; values for 2006&2005 taken from 2009 report for methodological consistency
## 6 Site area is the estimated area of coral cover; values for 2006&2005 taken from 2009 report for methodological consistency
## Secondary_sources Coded_By Coded_Date Reviewer
## 1 Luat Do 24/12/2019 Luke Brander
## 2 Luke Brander, Florian Eppink 26/11/2019 Kirsten Oleson
## 3 Luke Brander, Florian Eppink 26/11/2019 Kirsten Oleson
## 4 Luke Brander, Florian Eppink 26/11/2019 Kirsten Oleson
## 5 Luke Brander, Florian Eppink 26/11/2019 Kirsten Oleson
## 6 Luke Brander, Florian Eppink 26/11/2019 Kirsten Oleson
## Review_Date Checked_by_internal Incl_Excl Comments_Incl_Excl Scenario
## 1 9/4/2020 1
## 2 13/5/2020 1
## 3 13/5/2020 1
## 4 13/5/2020 1
## 5 13/5/2020 1
## 6 13/5/2020 1
## Ex_post_ante Attribute_of_baseline_1 Metric_BL_1 Unit_BL_1 BL_atr._value_1
## 1
## 2
## 3
## 4
## 5
## 6
## Attribute_of_baseline_2 Metric_BL_2 Unit_BL_2 BL_2 Attribute_of_baseline_3
## 1
## 2
## 3
## 4
## 5
## 6
## Metric_BL_3 Unit_BL_3 BL_atr._value_3 Attribute_of_baseline_4 Metric_BL_4
## 1
## 2
## 3
## 4
## 5
## 6
## Unit_BL_4 BL_4 Attribute_of_C_1 Metric_of_C_1 Unit_of_C_1 C_Value_1
## 1 NA
## 2 NA
## 3 NA
## 4 NA
## 5 NA
## 6 NA
## Attribute_of_C_2 Metric_of_C_2 Unit_of_C_2 C_Value_2 Attribute_of_C_3
## 1
## 2
## 3
## 4
## 5
## 6
## Metric_of_C_3 Unit_of_C_3 C_Value_3 Attribute_of_C_4 Metric_of_C_4
## 1
## 2
## 3
## 4
## 5
## 6
## Unit_of_C_4 C_Value_4 Attribute_of_C_5 Metric_of_C_5 Unit_of_C_5 C_Value_5
## 1
## 2
## 3
## 4
## 5
## 6
## Attribute_of_C_6 Metric_of_C_6 Unit_of_C_6 C_Value_6 Value_fraction
## 1
## 2
## 3
## 4
## 5
## 6
## Value_measure net_vs_gross Value_data Comments_and_Notes_new_variables
## 1
## 2
## 3
## 4
## 5
## 6
## Column Biomess
## 1 ESVD2.0_Biome_1 Coastal systems
## 2 ESVD2.0_Biome_1 Marine
## 3 ESVD2.0_Biome_1 Marine
## 4 ESVD2.0_Biome_1 Marine
## 5 ESVD2.0_Biome_1 Marine
## 6 ESVD2.0_Biome_1 Marine# Select only the "Biome" column
gathered_data <- gathered_data[c('Biomess')]
#FIX ERRORS
gathered_data <- gathered_data %>%
mutate(Biomess = ifelse(Biomess == "Coastal systems biome", "Coastal systems", Biomess))
gathered_data <- gathered_data %>%
separate_rows(Biomess, sep = "; ")
gathered_data <- gathered_data %>%
mutate(Biomess = ifelse(Biomess == "Rivers and Lakes", "Rivers and lakes", Biomess))
gathered_data <- gathered_data %>%
mutate(Biomess = ifelse(Biomess == "Temperate forests and woodland", "Temperate forest and woodland", Biomess))
# Count the frequency of each biome
biome_counts <- table(gathered_data$Biomess)
# Convert the counts to a data frame
biome_counts_df <- as.data.frame(biome_counts)
colnames(biome_counts_df) <- c("Biome", "Frequency")
desired_order <- c("Marine", "Coastal systems", "Inland wetlands", "Rivers and lakes",
"Tropical and subtropical forests", "Temperate forest and woodland", "Cold climate evergreen forest and woodland", "Shrubland and shrubby woodland",
"Rangelands and natural grasslands", "Desert and semi desert", "Polar and alpine systems", "Subterranean systems",
"Intensive land use", "Anthropogenic systems",
"Urban green and blue infrastructure")
biome_counts_df$Biome <- factor(biome_counts_df$Biome, levels = desired_order)
biome_counts_df <- biome_counts_df[order(match(biome_counts_df$Biome, desired_order)), ]
library(RColorBrewer)
library(viridis)## Loading required package: viridisLite##
## Attaching package: 'viridis'## The following object is masked from 'package:maps':
##
## unemplibrary(ggthemes)
custom_palette <- viridis(23)
# Create the pie chart
pie_chart <- ggplot(biome_counts_df, aes(x = "", y = Frequency, fill = Biome)) +
geom_bar(stat = "identity", width = 1) +
coord_polar("y", start = 0.5) +
theme_excel_new() +
scale_fill_manual(values = custom_palette) +
geom_text(aes(label = paste0(round((Frequency/sum(Frequency)) * 100, 1), "%"),
x = 1.7),
position = position_stack(vjust = 0.5),
color = "black", size = 3, fontface = "bold") +
theme(legend.position = "right",
legend.title = element_text(size = 10, face = "bold"),
plot.title = element_text(size = 14, face = "bold"),
plot.subtitle = element_text(size = 12),
plot.caption = element_text(size = 8),
panel.grid = element_blank()) + # Remove grid lines
labs(title = "Biome Distribution",
subtitle = "ESVD2.0_Biome",
caption = "Source: ESVD MASTER 230616")
# Print the modified pie chart
print(pie_chart)
#create radar chart
biome_counts_df <- biome_counts_df %>%
mutate(Biome_Number = as.numeric(factor(Biome, levels = unique(Biome))))
biome_counts_df$Biome_Number <- as.factor(biome_counts_df$Biome_Number)
new_row <- data.frame(Biome = "Other", Frequency = 0, Biome_Number = "16")
biome_counts_df <- rbind(biome_counts_df, new_row)
library(ggplot2)
library(dplyr)
library(scales)##
## Attaching package: 'scales'## The following object is masked from 'package:viridis':
##
## viridis_pallegend_labels <- c("1. Marine", "2. Coastal systems", "3. Inland wetlands", "4. Rivers and lakes",
"5. Tropical and subtropical forests", "6. Temperate forest and woodland", "7. Cold climate evergreen forest and woodland", "8. Shrubland and shrubby woodland",
"9. Rangelands and natural grasslands", "10. Desert and semi desert", "11. Polar and alpine systems", "12. Subterranean systems",
"13. Intensive land use", "14. Anthropogenic systems",
"15. Urban green and blue infrastructure", "16. Other")
ggplot(biome_counts_df, aes(x = Biome_Number, y = Frequency, color = Biome)) +
geom_line(size = 1) + # Thicker lines
geom_point(size = 3) + # White-filled points
geom_path() +
coord_polar(start = 0) +
labs(title = "Biome Distribution",
subtitle = "ESVD2.0_Biome",
caption = "Source: ESVD MASTER 230616",
x = NULL, # Remove x-axis label
y = NULL) + # Remove y-axis label
scale_y_continuous(labels = scales::comma) +
scale_color_manual(values = custom_palette, labels = legend_labels) + # Use custom color palette
theme_light() + # Minimal theme
theme(legend.position = "right", # Move legend to the bottom
axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1), # Adjust x-axis text angle and position
plot.title = element_text(size = 16, face = "bold"), # Larger and bold title
plot.subtitle = element_text(size = 12), # Smaller subtitle
legend.text = element_text(size = 10), # Smaller legend text
legend.key.size = unit(0.5, "cm")) # Smaller legend key size## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.## `geom_line()`: Each group consists of only one observation.
## ℹ Do you need to adjust the group aesthetic?## `geom_path()`: Each group consists of only one observation.
## ℹ Do you need to adjust the group aesthetic?
##1C ES
summary(data)## ValueID StudyID Biome Biome_Code
## Min. : 20001 Min. : 2.0 Length:12390 Length:12390
## 1st Qu.: 4510016 1st Qu.: 451.0 Class :character Class :character
## Median : 8480014 Median : 848.0 Mode :character Mode :character
## Mean : 7860779 Mean : 786.1
## 3rd Qu.:11030002 3rd Qu.:1103.0
## Max. :13750001 Max. :1375.0
## NA's :1498 NA's :1498
## Biome_1 Biome_2 Biome_3 Biome_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Biome_5 Biome_6 Biome_7 ESVD2.0_Biome
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_Code ESVD2.0_Biome_1 ESVD2.0_Biome_2 ESVD2.0_Biome_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_4 ESVD2.0_Biome_5 ESVD2.0_Biome_6 ESVD2.0_Biome_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Biome_8 ESVD2.0_Biome_10 ESVD2.0_Ecozone ESVD2.0_Ecozone_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_1 ESVD2.0_Ecozone_2 ESVD2.0_Ecozone_3 ESVD2.0_Ecozone_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_5 ESVD2.0_Ecozone_6 ESVD2.0_Ecozone_7 ESVD2.0_Ecozone_8
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecozone_9 ESVD2.0_Ecozone_10 ESVD2.0_Ecozone_11 ESVD2.0_Ecozone_12
## Length:12390 Mode:logical Mode:logical Mode:logical
## Class :character NA's:12390 NA's:12390 NA's:12390
## Mode :character
##
##
##
##
## ESVD2.0_Ecozone_13 ESVD2.0_Ecosystem ESVD2.0_Ecosystem_Code
## Mode:logical Length:12390 Length:12390
## NA's:12390 Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_1 ESVD2.0_Ecosystem_2 ESVD2.0_Ecosystem_3
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_4 ESVD2.0_Ecosystem_5 ESVD2.0_Ecosystem_6
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_7 ESVD2.0_Ecosystem_8 ESVD2.0_Ecosystem_9
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## ESVD2.0_Ecosystem_10 ESVD2.0_Ecosystem_11 ESVD2.0_Ecosystem_12
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem Ecosystem_Code Ecosystem_1 Ecosystem_2
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_3 Ecosystem_4 Ecosystem_5 Ecosystem_6
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_7 Ecosystem_8 Ecosystem_9 Ecosystem_10
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_11 Ecosystem_12 Ecosystem_13 Ecosystem_14
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Ecosystem_15 Ecosystem_Text ES_Text TEEB_ES
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## TEEB_SubES ES_1 ES_2 ES_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_4 ES_5 ES_6 ES_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_8 ES_9 ES_10 ES_11
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_12 ES_13 ES_14 ES_15
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ES_16 ES_17 CICES SEEA_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_1_text SEEA_ES_2_text SEEA_ES_3_text SEEA_ES_4_text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_5_text SEEA_ES_6_text SEEA_ES_7_text SEEA_ES_8_text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## SEEA_ES_9_text SEEA_ES_10_text Country Country_Code
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_1 Country_Code_2 Country_Code_3 Country_Code_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_5 Country_Code_6 Country_Code_7 Country_Code_8
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_Code_9 Country_1 Country_2 Country_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_4 Country_5 Country_6 Country_7
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Country_8 Country_9 Continent_Code Regions_FAO
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Scale_Text Scale_Code Location_Name Protected_Status
## Length:12390 Min. :1.000 Length:12390 Min. :0.000
## Class :character 1st Qu.:1.000 Class :character 1st Qu.:0.000
## Mode :character Median :1.000 Mode :character Median :1.000
## Mean :1.589 Mean :0.887
## 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :5.000 Max. :2.000
## NA's :1499 NA's :4165
## Site_Area Area_Unit Area_ha Site_Length
## Length:12390 Length:12390 Length:12390 Min. : 1
## Class :character Class :character Class :character 1st Qu.: 28
## Mode :character Mode :character Mode :character Median : 52
## Mean : 4082
## 3rd Qu.: 942
## Max. :700000
## NA's :12079
## Length_Unit Length_km Condition_Text Condition_Code
## Length:12390 Length:12390 Length:12390 Min. :0.000
## Class :character Class :character Class :character 1st Qu.:1.000
## Mode :character Mode :character Mode :character Median :1.000
## Mean :1.143
## 3rd Qu.:2.000
## Max. :2.000
## NA's :7824
## Latitude Longitude Valuation_Method Valuation_Method_1
## Min. :-55.062 Min. :-172.438 Length:12390 Length:12390
## 1st Qu.: 4.961 1st Qu.: -5.983 Class :character Class :character
## Median : 24.883 Median : 8.002 Mode :character Mode :character
## Mean : 24.215 Mean : 13.072
## 3rd Qu.: 50.717 3rd Qu.: 40.365
## Max. : 77.875 Max. : 178.457
## NA's :1553 NA's :1553
## Valuation_Method_2 Valuation_Method_3 Valuation_Method_4 Valuation_Method_5
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Valuation_Method_6 Valuation_Method_7 Valuation_Method_8 Valued_Change_Text
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Value_Original Currency_Code Value_year Spatial_Unit
## Length:12390 Length:12390 Min. :1970 Length:12390
## Class :character Class :character 1st Qu.:2004 Class :character
## Mode :character Mode :character Median :2011 Mode :character
## Mean :2009
## 3rd Qu.:2015
## Max. :2022
## NA's :1498
## Temporal_Unit PV_Years PV_Rate Beneficiary_Unit
## Length:12390 Min. : 3.00 Min. :-0.020 Length:12390
## Class :character 1st Qu.: 20.00 1st Qu.: 0.030 Class :character
## Mode :character Median : 30.00 Median : 0.046 Mode :character
## Mean : 44.65 Mean : 0.226
## 3rd Qu.:100.00 3rd Qu.: 0.100
## Max. :111.00 Max. :75.000
## NA's :10795 NA's :10774
## Beneficiary_Number Beneficiary_Type INT._2020_ha_yr_all Authors
## Length:12390 Length:12390 Min. :0.000e+00 Length:12390
## Class :character Class :character 1st Qu.:1.700e+01 Class :character
## Mode :character Mode :character Median :1.920e+02 Mode :character
## Mean :1.479e+09
## 3rd Qu.:1.469e+03
## Max. :1.853e+12
## NA's :5739
## Year_Pub Title Reference Notes
## Min. :1973 Length:12390 Length:12390 Length:12390
## 1st Qu.:2008 Class :character Class :character Class :character
## Median :2014 Mode :character Mode :character Mode :character
## Mean :2012
## 3rd Qu.:2019
## Max. :2023
## NA's :1498
## Secondary_sources Coded_By Coded_Date Reviewer
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Review_Date Checked_by_internal Incl_Excl Comments_Incl_Excl
## Length:12390 Length:12390 Min. :0.000 Length:12390
## Class :character Class :character 1st Qu.:1.000 Class :character
## Mode :character Mode :character Median :1.000 Mode :character
## Mean :0.984
## 3rd Qu.:1.000
## Max. :1.000
## NA's :3911
## Scenario Ex_post_ante Attribute_of_baseline_1
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Metric_BL_1 Unit_BL_1 BL_atr._value_1
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Attribute_of_baseline_2 Metric_BL_2 Unit_BL_2
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## BL_2 Attribute_of_baseline_3 Metric_BL_3
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Unit_BL_3 BL_atr._value_3 Attribute_of_baseline_4
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Metric_BL_4 Unit_BL_4 BL_4 Attribute_of_C_1
## Length:12390 Length:12390 Min. : 70.0 Length:12390
## Class :character Class :character 1st Qu.: 70.0 Class :character
## Mode :character Mode :character Median : 710.0 Mode :character
## Mean : 860.3
## 3rd Qu.:1391.0
## Max. :2320.0
## NA's :12383
## Metric_of_C_1 Unit_of_C_1 C_Value_1 Attribute_of_C_2
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_2 Unit_of_C_2 C_Value_2 Attribute_of_C_3
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_3 Unit_of_C_3 C_Value_3 Attribute_of_C_4
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_4 Unit_of_C_4 C_Value_4 Attribute_of_C_5
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_5 Unit_of_C_5 C_Value_5 Attribute_of_C_6
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Metric_of_C_6 Unit_of_C_6 C_Value_6 Value_fraction
## Length:12390 Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Value_measure net_vs_gross Value_data
## Length:12390 Length:12390 Length:12390
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Comments_and_Notes_new_variables
## Length:12390
## Class :character
## Mode :character
##
##
##
## gathered_data2 <- gather(data, key = "Column", value = "ESs",
ES_1:ES_17)
gathered_data2 <- gathered_data2[c('ESs')]
head(gathered_data2)## ESs
## 1 Food
## 2 Food
## 3 Opportunities for recreation and tourism
## 4 Opportunities for recreation and tourism
## 5 Food
## 6 Opportunities for recreation and tourismgathered_data2 <- subset(gathered_data2, !is.na(ESs) & ESs != "")
#Correct errors at the ES level
gathered_data2$ES <- NA
gathered_data2 <- gathered_data2 %>%
separate_rows(ESs, sep = "; ")
gathered_data2 <- gathered_data2 %>%
mutate(ESs = ifelse(ESs == "Existence, bequest value", "Existence, bequest values\n", ESs))
gathered_data2 <- gathered_data2 %>%
mutate(ESs = ifelse(ESs == "Existence, bequest value", "Water purification ", ESs))
# Classify ES readings into categories
gathered_data2$ES[gathered_data2$ESs %in% c("Abatement of noise", "Waste treatment", "Water purification")] <- "11. Waste treatment"
gathered_data2$ES[gathered_data2$ESs %in% c("Aesthetic information", "Aesthetic information ", "Attractive landscapes")] <- "18. Aesthetic information"
gathered_data2$ES[gathered_data2$ESs == "Air quality regulation"] <- "7. Air quality regulation"
gathered_data2$ES[gathered_data2$ESs %in% c("Artistic inspiration", "Cultural use", "Inspiration for culture, art and design")] <- "20. Inspiration for culture, art and design"
gathered_data2$ES[gathered_data2$ESs %in% c("Bequest value", "Bequest values", "Existence", "Existence value", "Existence, bequest value", "Existence, bequest values", "Existence, bequest values", "Existence, bequest values")] <- "23. Existence, bequest values"
gathered_data2$ES[gathered_data2$ESs %in% c( "Biodiversity protection", "Maintenance of genetic diversity")] <- "17. Maintenance of genetic diversity"
gathered_data2$ES[gathered_data2$ESs == "Biological control"] <- "15. Biological control"
gathered_data2$ES[gathered_data2$ESs %in% c("Climate regulation", "Climate regulation ")] <- "8. Climate regulation"
gathered_data2$ES[gathered_data2$ESs %in% c("Ecotourism", "Opportunities for recreation ", "Opportunities for recreation and tourism", "Recreation", " Recreation", "Tourism")] <- "19. Opportunities for recreation and tourism"
gathered_data2$ES[gathered_data2$ESs %in% c("Erosion prevention", "Erosion prevention ")] <- "12. Erosion prevention"
gathered_data2$ES[gathered_data2$ESs %in% c("Fish", "Food")] <- "1. Food"
gathered_data2$ES[gathered_data2$ESs %in% c("Flood prevention", "Moderation of extreme events", "Prevention of extreme events [unspecified]")] <- "9. Moderation of extreme events"
gathered_data2$ES[gathered_data2$ESs == "Genetic resources"] <- "4. Genetic resources"
gathered_data2$ES[gathered_data2$ESs %in% c("Information for cognitive development")] <- "22. Information for cognitive development"
gathered_data2$ES[gathered_data2$ESs == "Maintenance of life cycles"] <- "16. Maintenance of life cycles"
gathered_data2$ES[gathered_data2$ESs %in% c("Maintenance of soil fertility", "Nutrient cycling")] <- "13. Maintenance of soil fertility"
gathered_data2$ES[gathered_data2$ESs == "Medicinal resources"] <- "5. Medicinal resources"
gathered_data2$ES[gathered_data2$ESs == "Ornamental resources"] <- "6. Ornamental resources"
gathered_data2$ES[gathered_data2$ESs %in% c("Other raw", "Raw materials", "Raw Materials", "Raw materials ")] <- "3. Raw materials"
gathered_data2$ES[gathered_data2$ESs == "Pollination"] <- "14. Pollination"
gathered_data2$ES[gathered_data2$ESs %in% c("Regulation of water flows", "Regulation of water flows ", "Regulation of water flows")] <- "10. Regulation of water flows"
gathered_data2$ES[gathered_data2$ESs %in% c("Spiritual / Religious use", "Spiritual experience")] <- "21. Spiritual experience"
gathered_data2$ES[gathered_data2$ESs == "Water"] <- "2. Water"
na_rows <- subset(gathered_data2, is.na(ES))
print(na_rows)## # A tibble: 21 × 2
## ESs ES
## <chr> <chr>
## 1 "Existence, bequest values\n" <NA>
## 2 "Existence, bequest values\n" <NA>
## 3 "Existence, bequest values\n" <NA>
## 4 "Existence, bequest values\n" <NA>
## 5 "Existence, bequest values\n" <NA>
## 6 "Existence, bequest values\n" <NA>
## 7 "Existence, bequest values\n" <NA>
## 8 "Existence, bequest values\n" <NA>
## 9 "Existence, bequest values\n" <NA>
## 10 "Existence, bequest values\n" <NA>
## # ℹ 11 more rowsES_counts <- table(gathered_data2$ES)
ES_counts_df <- as.data.frame(ES_counts)
colnames(ES_counts_df) <- c("ES", "Frequency")
ES_counts_df$ES_general <- NA
ES_counts_df$ES_general[ES_counts_df$ES %in% c("1. Food", "2. Water", "3. Raw materials", "4. Genetic resources", "5. Medicinal resources", "6. Ornamental resources")] <- "Provisioning"
ES_counts_df$ES_general[ES_counts_df$ES %in% c("7. Air quality regulation", "8. Climate regulation", "9. Moderation of extreme events", "10. Regulation of water flows", "11. Waste treatment", "12. Erosion prevention", "13. Maintenance of soil fertility", "14. Pollination", "15. Biological control")] <- "Regulating"
ES_counts_df$ES_general[ES_counts_df$ES %in% c("16. Maintenance of life cycles", "17. Maintenance of genetic diversity")] <- "Habitat"
ES_counts_df$ES_general[ES_counts_df$ES %in% c("18. Aesthetic information", "19. Opportunities for recreation and tourism", "20. Inspiration for culture, art and design", "21. Spiritual experience", "22. Information for cognitive development", "23. Existence, bequest values")] <- "Cultural"
desired_order <- c("1. Food", "2. Water", "3. Raw materials", "4. Genetic resources", "5. Medicinal resources", "6. Ornamental resources",
"7. Air quality regulation", "8. Climate regulation", "9. Moderation of extreme events", "10. Regulation of water flows", "11. Waste treatment", "12. Erosion prevention", "13. Maintenance of soil fertility", "14. Pollination", "15. Biological control",
"16. Maintenance of life cycles", "17. Maintenance of genetic diversity",
"18. Aesthetic information", "19. Opportunities for recreation and tourism", "20. Inspiration for culture, art and design", "21. Spiritual experience", "22. Information for cognitive development", "23. Existence, bequest values")
ES_counts_df$ES <- factor(ES_counts_df$ES, levels = desired_order)
#ES Category
install.packages("ggrepel")## Installing package into 'C:/Users/thali/AppData/Local/R/win-library/4.2'
## (as 'lib' is unspecified)## package 'ggrepel' successfully unpacked and MD5 sums checked
##
## The downloaded binary packages are in
## C:\Users\thali\AppData\Local\Temp\RtmpQl5yGb\downloaded_packageslibrary(ggrepel)
custom_palette <- viridis(23)
library(ggplot2)
ggplot(ES_counts_df, aes(x = "", y = Frequency, fill = ES)) +
geom_bar(stat = "identity", width = 0.5) +
coord_polar("y", start = 0) +
scale_fill_manual(values = custom_palette) +
geom_text(aes(label = paste0(round(Frequency / sum(Frequency) * 100), "%")),
position = position_stack(vjust = 0.5), size = 2.5, fontface = "bold",
colour = "white", check_overlap = TRUE) +
theme(legend.position = "right",
legend.title = element_text(size = 20, face = "bold"),
plot.title = element_text(size = 14, face = "bold"),
plot.subtitle = element_text(size = 12),
plot.caption = element_text(size = 8)) +
labs(title = "Distribution of Ecosystem Services",
fill = "Ecosystem Service",
subtitle = "ES_TEEB",
caption = "Source: ESVD MASTER 230616") +
theme_void() +
theme(legend.position = "right") +
geom_polygon(data = data.frame(x = c(0, rep(NA, 100), 0),
y = c(0, rep(NA, 100), 0)),
aes(x = x, y = y), fill = "white", color = NA)
VSL
##2 VSL
library(readxl)
library(tidyr)
#2A GEOGRAPHY
dataG <- read_excel("C:/Users/thali/OneDrive - Wageningen University & Research/Escritorio/MASTERS/13. 14. 15. Internship/TASKS/4. DUPLICATES AND HOTSPOTS/VSLxlsx.xlsx")
dataG <- separate_rows(dataG, Country, sep = ";")
country_counts <- table(dataG$Country)
country_counts_df <- as.data.frame(country_counts)
colnames(country_counts_df) <- c("Country", "Frequency")
country_counts_df$Country <- sub(",.*", "", country_counts_df$Country)
country_counts_df$Country <- gsub("^\\s+", "", country_counts_df$Country)
country_counts_df$Country <- trimws(country_counts_df$Country, "right")
print(country_counts_df)## Country Frequency
## 1 Algeria 1
## 2 Australia 1
## 3 Bolivia 2
## 4 Cambodia 1
## 5 Cameroon 1
## 6 China 1
## 7 Colombia 1
## 8 Costa Rica 2
## 9 Ecuador 1
## 10 Egypt 1
## 11 El Salvador 1
## 12 Finland 1
## 13 France 1
## 14 French Guiana 1
## 15 Guatemala 2
## 16 Guinea 1
## 17 Guyana 1
## 18 Honduras 1
## 19 Hungary 2
## 20 Ireland 1
## 21 Italy 1
## 22 Kenya 1
## 23 Lao People's Democratic Republic 3
## 24 Mali 1
## 25 Mexico 1
## 26 Myanmar 1
## 27 Nicaragua 1
## 28 Niger 1
## 29 Nigeria 1
## 30 Norway 1
## 31 Pakistan 1
## 32 Panama 1
## 33 Peru 2
## 34 Poland 1
## 35 Portugal 1
## 36 Romania 2
## 37 Slovenia 1
## 38 Somalia 1
## 39 Sri Lanka 1
## 40 Sudan 1
## 41 Suriname 2
## 42 Sweden 1
## 43 Tanzania 2
## 44 Thailand 2
## 45 Turkey 1
## 46 Uganda 1
## 47 United Kingdom of Great Britain & Northern Ireland 2
## 48 United States of America 3
## 49 Venezuela 1
## 50 Vietnam 2
## 51 Australia 18
## 52 Austria 6
## 53 Bangladesh 4
## 54 Belgium 4
## 55 Belize 4
## 56 Benin 1
## 57 Bermuda 1
## 58 Bhutan 1
## 59 Bolivia 1
## 60 Bonaire 3
## 61 Brazil 24
## 62 Bulgaria 1
## 63 Burkina Faso 4
## 64 Cambodia 3
## 65 Cameroon 2
## 66 Canada 7
## 67 China 50
## 68 Colombia 3
## 69 Costa Rica 6
## 70 Côte d'Ivoire 1
## 71 Cuba 2
## 72 Czech Republic 3
## 73 Denmark 5
## 74 Egypt 1
## 75 El Salvador 1
## 76 Ethiopia 5
## 77 Finland 15
## 78 France 14
## 79 Germany 65
## 80 Ghana 6
## 81 Greece 4
## 82 Guatemala 3
## 83 Guyana 1
## 84 Honduras 2
## 85 Hong Kong 3
## 86 India 27
## 87 Indonesia 23
## 88 Iran 6
## 89 Ireland 6
## 90 Israel 3
## 91 Italy 19
## 92 Japan 2
## 93 Jordan 1
## 94 Kenya 2
## 95 Korea 3
## 96 Lao People's Democratic Republic 3
## 97 Lebanon 1
## 98 Liberia 1
## 99 Lithuania 1
## 100 Madagascar 2
## 101 Malaysia 18
## 102 Mali 5
## 103 Mauritania 2
## 104 Mexico 18
## 105 Moldova 1
## 106 Morocco 1
## 107 Mozambique 1
## 108 Myanmar 2
## 109 Nepal 3
## 110 Netherlands 34
## 111 New Zealand 3
## 112 Nigeria 6
## 113 Norway 10
## 114 Pakistan 3
## 115 Panama 4
## 116 Papua New Guinea 1
## 117 Peru 8
## 118 Philippines 6
## 119 Poland 9
## 120 Portugal 14
## 121 Romania 1
## 122 Russian Federation 2
## 123 Saudi Arabia 1
## 124 Senegal 5
## 125 Serbia 1
## 126 Solomon Islands 1
## 127 South Africa 6
## 128 Spain 45
## 129 Sri Lanka 5
## 130 Suriname 2
## 131 Sweden 8
## 132 Switzerland 10
## 133 Taiwan 3
## 134 Tanzania 1
## 135 Thailand 6
## 136 Turkey 9
## 137 Uganda 2
## 138 United Arab Emirates 1
## 139 United Kingdom of Great Britain & Northern Ireland 27
## 140 United States of America 85
## 141 Uruguay 2
## 142 Venezuela 1
## 143 Vietnam 10
## 144 World 14
## 145 Zambia 1
## 146 Zimbabwe 1country_counts_df <- country_counts_df %>%
filter(Country != "World")
country_lookup <- data.frame(
non_standard_name = c("Lao People's Democratic Republic",
"United Kingdom of Great Britain & Northern Ireland",
"United States of America",
"Côte d'Ivoire",
"Russian Federation",
"Solomon Islands"),
standard_name = c("Laos",
"United Kingdom",
"United States of America",
"Ivory Coast",
"Russia",
"Solomon Islands")
)
# Convert non-standard names to standard names
country_counts_df <- left_join(country_counts_df, country_lookup, by = c("Country" = "non_standard_name")) %>%
mutate(Country = ifelse(is.na(standard_name), Country, standard_name))
country_counts_df <- country_counts_df[order(country_counts_df$Frequency, decreasing = TRUE), ]
print(country_counts_df)## Country Frequency standard_name
## 140 United States of America 85 United States of America
## 79 Germany 65 <NA>
## 67 China 50 <NA>
## 128 Spain 45 <NA>
## 110 Netherlands 34 <NA>
## 86 India 27 <NA>
## 139 United Kingdom 27 United Kingdom
## 61 Brazil 24 <NA>
## 87 Indonesia 23 <NA>
## 91 Italy 19 <NA>
## 51 Australia 18 <NA>
## 101 Malaysia 18 <NA>
## 104 Mexico 18 <NA>
## 77 Finland 15 <NA>
## 78 France 14 <NA>
## 120 Portugal 14 <NA>
## 113 Norway 10 <NA>
## 132 Switzerland 10 <NA>
## 143 Vietnam 10 <NA>
## 119 Poland 9 <NA>
## 136 Turkey 9 <NA>
## 117 Peru 8 <NA>
## 131 Sweden 8 <NA>
## 66 Canada 7 <NA>
## 52 Austria 6 <NA>
## 69 Costa Rica 6 <NA>
## 80 Ghana 6 <NA>
## 88 Iran 6 <NA>
## 89 Ireland 6 <NA>
## 112 Nigeria 6 <NA>
## 118 Philippines 6 <NA>
## 127 South Africa 6 <NA>
## 135 Thailand 6 <NA>
## 73 Denmark 5 <NA>
## 76 Ethiopia 5 <NA>
## 102 Mali 5 <NA>
## 124 Senegal 5 <NA>
## 129 Sri Lanka 5 <NA>
## 53 Bangladesh 4 <NA>
## 54 Belgium 4 <NA>
## 55 Belize 4 <NA>
## 63 Burkina Faso 4 <NA>
## 81 Greece 4 <NA>
## 115 Panama 4 <NA>
## 23 Laos 3 Laos
## 48 United States of America 3 United States of America
## 60 Bonaire 3 <NA>
## 64 Cambodia 3 <NA>
## 68 Colombia 3 <NA>
## 72 Czech Republic 3 <NA>
## 82 Guatemala 3 <NA>
## 85 Hong Kong 3 <NA>
## 90 Israel 3 <NA>
## 95 Korea 3 <NA>
## 96 Laos 3 Laos
## 109 Nepal 3 <NA>
## 111 New Zealand 3 <NA>
## 114 Pakistan 3 <NA>
## 133 Taiwan 3 <NA>
## 3 Bolivia 2 <NA>
## 8 Costa Rica 2 <NA>
## 15 Guatemala 2 <NA>
## 19 Hungary 2 <NA>
## 33 Peru 2 <NA>
## 36 Romania 2 <NA>
## 41 Suriname 2 <NA>
## 43 Tanzania 2 <NA>
## 44 Thailand 2 <NA>
## 47 United Kingdom 2 United Kingdom
## 50 Vietnam 2 <NA>
## 65 Cameroon 2 <NA>
## 71 Cuba 2 <NA>
## 84 Honduras 2 <NA>
## 92 Japan 2 <NA>
## 94 Kenya 2 <NA>
## 100 Madagascar 2 <NA>
## 103 Mauritania 2 <NA>
## 108 Myanmar 2 <NA>
## 122 Russia 2 Russia
## 130 Suriname 2 <NA>
## 137 Uganda 2 <NA>
## 141 Uruguay 2 <NA>
## 1 Algeria 1 <NA>
## 2 Australia 1 <NA>
## 4 Cambodia 1 <NA>
## 5 Cameroon 1 <NA>
## 6 China 1 <NA>
## 7 Colombia 1 <NA>
## 9 Ecuador 1 <NA>
## 10 Egypt 1 <NA>
## 11 El Salvador 1 <NA>
## 12 Finland 1 <NA>
## 13 France 1 <NA>
## 14 French Guiana 1 <NA>
## 16 Guinea 1 <NA>
## 17 Guyana 1 <NA>
## 18 Honduras 1 <NA>
## 20 Ireland 1 <NA>
## 21 Italy 1 <NA>
## 22 Kenya 1 <NA>
## 24 Mali 1 <NA>
## 25 Mexico 1 <NA>
## 26 Myanmar 1 <NA>
## 27 Nicaragua 1 <NA>
## 28 Niger 1 <NA>
## 29 Nigeria 1 <NA>
## 30 Norway 1 <NA>
## 31 Pakistan 1 <NA>
## 32 Panama 1 <NA>
## 34 Poland 1 <NA>
## 35 Portugal 1 <NA>
## 37 Slovenia 1 <NA>
## 38 Somalia 1 <NA>
## 39 Sri Lanka 1 <NA>
## 40 Sudan 1 <NA>
## 42 Sweden 1 <NA>
## 45 Turkey 1 <NA>
## 46 Uganda 1 <NA>
## 49 Venezuela 1 <NA>
## 56 Benin 1 <NA>
## 57 Bermuda 1 <NA>
## 58 Bhutan 1 <NA>
## 59 Bolivia 1 <NA>
## 62 Bulgaria 1 <NA>
## 70 Ivory Coast 1 Ivory Coast
## 74 Egypt 1 <NA>
## 75 El Salvador 1 <NA>
## 83 Guyana 1 <NA>
## 93 Jordan 1 <NA>
## 97 Lebanon 1 <NA>
## 98 Liberia 1 <NA>
## 99 Lithuania 1 <NA>
## 105 Moldova 1 <NA>
## 106 Morocco 1 <NA>
## 107 Mozambique 1 <NA>
## 116 Papua New Guinea 1 <NA>
## 121 Romania 1 <NA>
## 123 Saudi Arabia 1 <NA>
## 125 Serbia 1 <NA>
## 126 Solomon Islands 1 Solomon Islands
## 134 Tanzania 1 <NA>
## 138 United Arab Emirates 1 <NA>
## 142 Venezuela 1 <NA>
## 144 Zambia 1 <NA>
## 145 Zimbabwe 1 <NA># Load map data
world_map <- map_data("world")
library(rworldmap)## Loading required package: sp## The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
## which was just loaded, will retire in October 2023.
## Please refer to R-spatial evolution reports for details, especially
## https://r-spatial.org/r/2023/05/15/evolution4.html.
## It may be desirable to make the sf package available;
## package maintainers should consider adding sf to Suggests:.
## The sp package is now running under evolution status 2
## (status 2 uses the sf package in place of rgdal)## ### Welcome to rworldmap ##### For a short introduction type : vignette('rworldmap')frequency.map <- joinCountryData2Map(country_counts_df, joinCode = "NAME", nameJoinColumn = "Country")## 144 codes from your data successfully matched countries in the map
## 1 codes from your data failed to match with a country code in the map
## 139 codes from the map weren't represented in your datalibrary(ggplot2)
library(scales)
library(sf)## Linking to GEOS 3.9.3, GDAL 3.5.2, PROJ 8.2.1; sf_use_s2() is TRUElibrary(rnaturalearth)
library(rnaturalearthdata)##
## Attaching package: 'rnaturalearthdata'## The following object is masked from 'package:rnaturalearth':
##
## countries110world <- ne_countries(scale = "medium", returnclass = "sf")
frequency.world <- merge(world, country_counts_df, by.x="admin", by.y="Country")
world_map <- map_data("world")
ggplot(data = frequency.world) +
geom_map(data = world_map, map = world_map,
aes(x = long, y = lat, map_id = region), fill = "lightgrey", color = "white") + # Add world map
geom_sf(aes(fill=Frequency), color = "white") + # Set border color to white
scale_fill_gradient(name = "Density", limits = c(0, max(frequency.world$Frequency)),
low = "lightblue", high = "darkblue") + # Customize the color scale
labs(title = "Geographical Distribution of VSL Data; Density of Studies",
caption = "Source: Valuation Studies List") + # Add a title
theme_minimal() + # Use a minimal theme
theme(plot.title = element_text(hjust = 0.5)) ## Warning in geom_map(data = world_map, map = world_map, aes(x = long, y = lat, :
## Ignoring unknown aesthetics: x and y
#2B BIOME
library(dplyr)
dataB <- read_excel("C:/Users/thali/OneDrive - Wageningen University & Research/Escritorio/MASTERS/13. 14. 15. Internship/TASKS/4. DUPLICATES AND HOTSPOTS/Biomes.xlsx")
dataB <- separate_rows(dataB, Biome, sep = ";")
biomes_counts <- table(dataB$Biome)
biomes_counts_df <- as.data.frame(biomes_counts)
colnames(biomes_counts_df) <- c("Biome", "Frequency")
biomes_counts_df$Biome <- trimws(biomes_counts_df$Biome)
biomes_counts_df <- biomes_counts_df %>%
group_by(Biome) %>%
summarise(Frequency = sum(Frequency))
biomes_counts_df <- biomes_counts_df %>%
mutate(Biome = case_when(
Biome == "Open sea/ocean" ~ "1",
Biome == "Coral reefs" ~ "1",
Biome == "Coastal systems (incl wetlands)" ~ "2",
Biome == "Inland wetlands" ~ "3",
Biome == "Rivers and lakes" ~ "4",
Biome == "Tropical forests" ~ "5",
Biome == "Temperate forests" ~ "6",
Biome == "Woodland & Shrubland" ~ "8",
Biome == "Grass-/Rangeland" ~ "9",
Biome == "Desert" ~ "10",
Biome == "Tundra" ~ "8",
Biome == "High mountain & Polar systems" ~ "11",
Biome == "Inland Un- or Sparsely Vegetated" ~ "12",
Biome == "Cultivated areas" ~ "13",
Biome == "Rangelands and natural grasslands" ~ "9",
Biome == "Desert and semi desert" ~ "10",
Biome == "Polar and alpine systems" ~ "11",
Biome == "Subterranean systems" ~ "12",
Biome == "Intensive land use" ~ "13",
Biome == "Urban Green and Blue Infrastructure" ~ "15",
Biome == "Other" ~ "16",
TRUE ~ Biome
))
new_row1 <- data.frame(Biome = "7", Frequency = 0)
new_row2 <- data.frame(Biome = "14", Frequency = 0)
biomes_counts_df <- rbind(biomes_counts_df, new_row1)
biomes_counts_df <- rbind(biomes_counts_df, new_row2)
biomes_counts_df$Biome <- factor(biomes_counts_df$Biome, levels = desired_order)
biomes_counts_df <- biomes_counts_df[order(match(biomes_counts_df$Biome, desired_order)), ]
print(levels(biomes_counts_df$Biome))## [1] "1. Food"
## [2] "2. Water"
## [3] "3. Raw materials"
## [4] "4. Genetic resources"
## [5] "5. Medicinal resources"
## [6] "6. Ornamental resources"
## [7] "7. Air quality regulation"
## [8] "8. Climate regulation"
## [9] "9. Moderation of extreme events"
## [10] "10. Regulation of water flows"
## [11] "11. Waste treatment"
## [12] "12. Erosion prevention"
## [13] "13. Maintenance of soil fertility"
## [14] "14. Pollination"
## [15] "15. Biological control"
## [16] "16. Maintenance of life cycles"
## [17] "17. Maintenance of genetic diversity"
## [18] "18. Aesthetic information"
## [19] "19. Opportunities for recreation and tourism"
## [20] "20. Inspiration for culture, art and design"
## [21] "21. Spiritual experience"
## [22] "22. Information for cognitive development"
## [23] "23. Existence, bequest values"biomes_counts_df <- biomes_counts_df %>%
group_by(Biome) %>%
summarize(Frequency = sum(Frequency))
library(ggplot2)
library(dplyr)
library(scales)
legend_labels <- c("1. Marine", "2. Coastal systems", "3. Inland wetlands", "4. Rivers and lakes",
"5. Tropical and subtropical forests", "6. Temperate forest and woodland", "7. Cold climate evergreen forest and woodland", "8. Shrubland and shrubby woodland",
"9. Rangelands and natural grasslands", "10. Desert and semi desert", "11. Polar and alpine systems", "12. Subterranean systems",
"13. Intensive land use", "14. Anthropogenic systems",
"15. Urban green and blue infrastructure", "16. Other")
# Radar plot with legend
custom_palette <- viridis(23)
ggplot(biomes_counts_df, aes(x = Biome, y = Frequency, color = Biome)) +
geom_point(size = 3) + # White-filled points
coord_polar(start = 0) +
labs(title = "Frequency of Biomes",
subtitle = "Unread Studies",
caption = "Source: Valuation Studies List",
x = NULL, # Remove x-axis label
y = NULL) + # Remove y-axis label
scale_y_continuous(labels = scales::comma) +
scale_color_manual(values = custom_palette, labels = legend_labels) + # Use custom color palette
theme_light() + # Minimal theme
theme(legend.position = "right", # Move legend to the bottom
axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1), # Adjust x-axis text angle and position
plot.title = element_text(size = 16, face = "bold"), # Larger and bold title
plot.subtitle = element_text(size = 12), # Smaller subtitle
legend.text = element_text(size = 10), # Smaller legend text
legend.key.size = unit(0.5, "cm")) # Smaller legend key size
#standardised radar chart
biomes_counts_df <- biome_counts_df %>%
mutate(Biome_Number = as.numeric(factor(Biome, levels = unique(Biome))))
biome_counts_df$Biome_Number <- as.factor(biome_counts_df$Biome_Number)
new_row <- data.frame(Biome = "Other", Frequency = 0, Biome_Number = "16")
biome_counts_df <- rbind(biome_counts_df, new_row)
library(ggplot2)
library(dplyr)
library(scales)
legend_labels <- c("1. Marine", "2. Coastal systems", "3. Inland wetlands", "4. Rivers and lakes",
"5. Tropical and subtropical forests", "6. Temperate forest and woodland", "7. Cold climate evergreen forest and woodland", "8. Shrubland and shrubby woodland",
"9. Rangelands and natural grasslands", "10. Desert and semi desert", "11. Polar and alpine systems", "12. Subterranean systems",
"13. Intensive land use", "14. Anthropogenic systems",
"15. Urban green and blue infrastructure", "16. Other")
ggplot(biome_counts_df, aes(x = Biome_Number, y = Frequency, color = Biome)) +
geom_point(size = 3) + # White-filled points
coord_polar(start = 0) +
labs(title = "Biome Distribution",
subtitle = "ESVD2.0_Biome",
caption = "Source: ESVD MASTER 230616",
x = NULL, # Remove x-axis label
y = NULL) + # Remove y-axis label
scale_y_continuous(labels = scales::comma) +
scale_color_manual(values = custom_palette, labels = legend_labels) + # Use custom color palette
theme_light() + # Minimal theme
theme(legend.position = "right", # Move legend to the bottom
axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1), # Adjust x-axis text angle and position
plot.title = element_text(size = 16, face = "bold"), # Larger and bold title
plot.subtitle = element_text(size = 12), # Smaller subtitle
legend.text = element_text(size = 10), # Smaller legend text
legend.key.size = unit(0.5, "cm")) # Smaller legend key size
#2C ES
dataE <- read_excel("C:/Users/thali/OneDrive - Wageningen University & Research/Escritorio/MASTERS/13. 14. 15. Internship/TASKS/4. DUPLICATES AND HOTSPOTS/ES.xlsx")
dataE <- separate_rows(dataE, ES, sep = ";")
ES_counts <- table(dataE$ES)
ES_counts_df <- as.data.frame(ES_counts)
colnames(ES_counts_df) <- c("ES", "Frequency")
ES_counts_df$ES <- trimws(ES_counts_df$ES)
ES_counts_df <- ES_counts_df %>%
group_by(ES) %>%
summarise(Frequency = sum(Frequency))
ES_counts_df$ES[ES_counts_df$ES %in% c("Abatement of noise", "Waste treatment", "Water purification")] <- "11. Waste treatment"
ES_counts_df$ES[ES_counts_df$ES %in% c("Aesthetic information", "Aesthetic information ", "Attractive landscapes")] <- "18. Aesthetic information"
ES_counts_df$ES[ES_counts_df$ES == "Air quality regulation"] <- "7. Air quality regulation"
ES_counts_df$ES[ES_counts_df$ES %in% c("Artistic inspiration", "Cultural use", "Inspiration for culture, art and design")] <- "20. Inspiration for culture, art and design"
ES_counts_df$ES[ES_counts_df$ES %in% c("Bequest value", "Bequest values", "Existence", "Existence value", "Existence, bequest value", "Existence, bequest values", "Existence, bequest values", "Existence, bequest values")] <- "23. Existence, bequest values"
ES_counts_df$ES[ES_counts_df$ES %in% c( "Biodiversity protection", "Maintenance of genetic diversity")] <- "17. Maintenance of genetic diversity"
ES_counts_df$ES[ES_counts_df$ES == "Biological control"] <- "15. Biological control"
ES_counts_df$ES[ES_counts_df$ES %in% c("Climate regulation", "Climate regulation ")] <- "8. Climate regulation"
ES_counts_df$ES[ES_counts_df$ES %in% c("Ecotourism", "Opportunities for recreation ", "Opportunities for recreation and tourism", "Recreation", " Recreation", "Tourism")] <- "19. Opportunities for recreation and tourism"
ES_counts_df$ES[ES_counts_df$ES %in% c("Erosion prevention", "Erosion prevention ")] <- "12. Erosion prevention"
ES_counts_df$ES[ES_counts_df$ES %in% c("Fish", "Food")] <- "1. Food"
ES_counts_df$ES[ES_counts_df$ES %in% c("Flood prevention", "Moderation of extreme events", "Prevention of extreme events [unspecified]")] <- "9. Moderation of extreme events"
ES_counts_df$ES[ES_counts_df$ES == "Genetic resources"] <- "4. Genetic resources"
ES_counts_df$ES[ES_counts_df$ES %in% c("Information for cognitive development")] <- "22. Information for cognitive development"
ES_counts_df$ES[ES_counts_df$ES == "Maintenance of life cycles"] <- "16. Maintenance of life cycles"
ES_counts_df$ES[ES_counts_df$ES %in% c("Maintenance of soil fertility", "Nutrient cycling")] <- "13. Maintenance of soil fertility"
ES_counts_df$ES[ES_counts_df$ES == "Medicinal resources"] <- "5. Medicinal resources"
ES_counts_df$ES[ES_counts_df$ES == "Ornamental resources"] <- "6. Ornamental resources"
ES_counts_df$ES[ES_counts_df$ES %in% c("Other raw", "Raw materials", "Raw Materials", "Raw materials ")] <- "3. Raw materials"
ES_counts_df$ES[ES_counts_df$ES == "Pollination"] <- "14. Pollination"
ES_counts_df$ES[ES_counts_df$ES %in% c("Regulation of water flows", "Regulation of water flows ", "Regulation of water flows")] <- "10. Regulation of water flows"
ES_counts_df$ES[ES_counts_df$ES %in% c("Spiritual / Religious use", "Spiritual experience")] <- "21. Spiritual experience"
ES_counts_df$ES[ES_counts_df$ES == "Water"] <- "2. Water"
ES_counts_df <- ES_counts_df %>%
arrange(ES)
ggplot(ES_counts_df, aes(x = "", y = Frequency, fill = ES)) +
geom_bar(stat = "identity", width = 0.5) +
coord_polar("y", start = 0) +
scale_fill_manual(values = custom_palette) +
geom_text(aes(label = paste0(round(Frequency / sum(Frequency) * 100), "%")),
position = position_stack(vjust = 0.5), size = 3, fontface = "bold",
colour = "white", check_overlap = TRUE) +
theme(legend.position = "right",
legend.title = element_text(size = 20, face = "bold"),
plot.title = element_text(size = 14, face = "bold"),
plot.subtitle = element_text(size = 12),
plot.caption = element_text(size = 8)) +
labs(title = "Distribution of Ecosystem Services",
fill = "Ecosystem Service",
subtitle = "Unread Studies",
caption = "Source: Valuation Studies List") +
theme_void() +
theme(legend.position = "right") +
geom_polygon(data = data.frame(x = c(0, rep(NA, 100), 0),
y = c(0, rep(NA, 100), 0)),
aes(x = x, y = y), fill = "white", color = NA)