Quantifying temporal changes in the monetary value of forest cultural ecosystem services globally: a meta-analysis: Supporting Dataset
#### About:
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Paper Author: Dr Maximilian Nawrath (Norwegian Institute for Water Research). Correspondence: Max.Nawrath@niva.no
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Repo Author: Dr Peter King (University of Leeds). Correspondence: p.king1@leeds.ac.uk
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Co-authors: Prof. Martin Dallimer (Imperial), Dr. Gail E. Austen (Kent), Dr. Katherine N. Irvine (James Hutton Institute), Prof. Robert D. Fish (Kent), Dr. Jessica C. Fisher (Kent), Prof. Zoe G. Davies (Kent)
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Status: Published in ***Environmental Research Letters*** --- [in press]
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Keywords: Benefit transfer, biodiversity, non-market valuation, recreation, revealed preference, stated preference
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Last Change: 11/08/2026
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Run: all scripts in order via
here("00_MetaAnalysis.R") -
License: code in this repository is MIT (see
LICENSE).
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This research was funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Consolidator Grant No. 726104) and by the Norwegian Research Council (Grant Contract Number 342628/L10).
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This work is part of Work Package 4 for the RELATE project: https://research.kent.ac.uk/relate/
Data Pipeline:
Each step reads the previous step's output. Replicators start from Data_StepOne.csv (pre-generated). The raw-extraction translation step that produces Data_StepOne.csv from the raw extraction sheet is not part of this deposit (kept in the authors' private working copy).
| Step | File | Rows | Unique studies | Produces |
|---|---|---|---|---|
| 0 | Data_StepZero.csv |
--- | --- | Raw extraction sheet |
| 1 | Data_StepOne.csv |
1993 | 331 | Translated extraction (replicator entry point) |
| 2 | Data_StepTwo.csv |
705 | 138 | PPP-deflated estimation sample |
| 2b | Data_StepTwo_Full.csv |
1092 | 152 | Full sample (all methods and years) |
| 3 | Data_StepThree.csv |
705 | 138 | + log-mean effect sizes (yi, vi) |
| 4 | Data_StepFour.csv |
705 | 138 | + Cook's Distance outlier flags |
.
├── 00_MetaAnalysis.R
├── CITATION.cff
├── Data
│ ├── Codebook.csv # generated by 04_Codebook
│ ├── Data_StepFour.csv
│ ├── Data_StepOne.csv # replicator entry point
│ ├── Data_StepThree.csv
│ ├── Data_StepTwo.csv
│ ├── Data_StepTwo_Full.csv
│ ├── Data_StepZero.csv
│ └── ExcelWorksheet_README.txt # documents the pre-R Excel formulas behind the raw-extraction QC columns
├── LICENSE
├── Output
│ ├── Models
│ │ ├── Model_CE_Final_Robust_PrePandemic.rds
│ │ ├── Model_CE_Recreation_Robust_PrePandemic.rds
│ │ ├── Model_CV_Final_Robust_PrePandemic.rds
│ │ ├── Model_CV_Recreation_Robust_PrePandemic.rds
│ │ ├── Model_HP_Final_PrePandemic.rds
│ │ └── Model_TC_Final_Robust_PrePandemic.rds
│ ├── Plots
│ │ ├── Figure2_StackedBarStudies_Final.png
│ │ ├── Figure3_StudiesByCES_Final.png
│ │ ├── Figure5_StudyCountByMethodByDecade_Final.png
│ │ ├── Figure6_EffectSizes_Final.png
│ │ └── Figure6B_EffectSizesByCountry_Final.png
│ └── Tables
│ ├── CooksDistance.csv / .txt
│ ├── Model_{CE,CV,TC,HP}_Final_PrePandemic.txt # full diagnostics (script 05-08 direct output)
│ ├── Model_{CE,CV,TC,HP}_Final.txt # short diagnostics, as Table 3/4 (scripts 11/12)
│ ├── Model_{CE,CV}_Recreation.txt # recreation-subsample, short diagnostics (script 13)
│ ├── Table1_VariableSummary.txt # Table 1
│ ├── Table2.txt # Table 2
│ ├── Table3_ModelOutput_SP.txt # Table 3
│ ├── Table4_ModelOutput_RP.txt # Table 4
│ ├── TableS2_AllStudies.txt # Table S2 (supplementary)
│ ├── TableS4_StudiesBy{Continent,IncomeClass}Decade.txt # Table S4 (supplementary; Figure 4 input)
│ ├── TableS5_StudiesByCountryDecadeMethod.txt # Table S5 (supplementary; Figure 4 input)
│ └── TableS6_ModelOutput_SP_Recreation.txt # Table S6 (supplementary; recreation-only sensitivity)
├── README.md
├── Scripts
│ ├── Setup
│ │ ├── 01_MetaAnalysis_Setup_DataSetup.R
│ │ ├── 02_MetaAnalysis_Setup_EffectSizes.R
│ │ ├── 03_MetaAnalysis_Setup_OutlierAnalysis.R
│ │ └── 04_MetaAnalysis_Setup_Codebook.R
│ ├── MAModels
│ │ ├── 05_MetaAnalysis_Model_CE.R
│ │ ├── 06_MetaAnalysis_Model_CV.R
│ │ ├── 07_MetaAnalysis_Model_TC.R
│ │ └── 08_MetaAnalysis_Model_HP.R
│ ├── Tables
│ │ ├── 09_MetaAnalysis_Table1_VariableSummary.R
│ │ ├── 10_MetaAnalysis_Table2_MethodSummary.R
│ │ ├── 11_MetaAnalysis_Table3_SPModels.R
│ │ ├── 12_MetaAnalysis_Table4_RPModels.R
│ │ ├── 13_MetaAnalysis_TableS6_Recreation.R
│ │ └── 14_MetaAnalysis_TableS2_AllStudies.R
│ ├── Plotting
│ │ ├── 15_MetaAnalysis_Figure2_StackedBarStudies.R
│ │ ├── 16_MetaAnalysis_Figure3_StudiesByCES.R
│ │ ├── 17_MetaAnalysis_Figure4_SpatialCounts.R
│ │ ├── 18_MetaAnalysis_Figure5_StudyCountByMethodByDecade.R
│ │ ├── 19_MetaAnalysis_Figure6_EffectSizes.R
│ │ └── 20_MetaAnalysis_Figure6B_EffectSizesByCountry.R
│ └── Utils
│ └── outputter.R
└── WP4.Rproj
Archival note: The session information below is from the original analysis run (R 4.5.0, August 2025) and is provided for reference. The pipeline requires R ≥ 4.5.0 and the packages listed; exact versions are not enforced.
# > sessioninfo::session_info()
# ─ Session info ────────────────────────────────────────────────────────────────────────────
# setting value
# version R version 4.5.0 (2025-04-11 ucrt)
# os Windows 11 x64 (build 22631)
# system x86_64, mingw32
# ui RStudio
# language (EN)
# collate English_United Kingdom.utf8
# ctype English_United Kingdom.utf8
# tz Europe/London
# date 2025-08-01
# rstudio 2023.06.2+561 Mountain Hydrangea (desktop)
# pandoc 3.1.1 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
# quarto ERROR: Unknown command "TMPDIR=C:/Users/[]/AppData/Local/Temp/RtmpAbfat8/filea09c66692e55". Did you mean command "create-project"? @ C:\\PROGRA~1\\RStudio\\RESOUR~1\\app\\bin\\quarto\\bin\\quarto.exe
#
# ─ Packages ────────────────────────────────────────────────────────────────────────────────
# package * version date (UTC) lib source
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