Climate Change Impacts the Value of Cultural Ecosystem Services: A Case Study from South Africa

This dataset supports the manuscript examining the impacts of climate change on the non-market value of birding cultural ecosystem services (CES) in South Africa. Using eBird citizen science data, Maxent modeling, and the travel cost method, the study maps current and future birding CES non-market use value and evaluates its vulnerability under various climate scenarios. The data highlights differences between domestic and international birders and provides insights into CES drivers and their resilience to global change. Source Data: eBird Data: Period: 2010–2019 Original Source: eBird (downloaded from GBIF) Filtered for user-days: One unique upload per user per day. Excluded: Urban areas masked out using the Africapolis database. Derived Data: Birding Suitability Maps: Generated using Maxent modeling. Suitability scores: Range 0–1. Separate models for domestic, international, and combined birders. Travel Cost Method Data: Travel distances: Calculated using Haversine formula (international) and Google Maps API (domestic). Other attributes used to calculate travel costs for each datapoint. Cost estimates: For international and domestic. CES Value Maps: Modeled from regression between suitability and travel cost data. Future projections under SSP245 and SSP585 scenarios. Future Scenarios: Suitability and value for climate, biodiversity, and land cover scenarios. File Inventory: Processed Data: ebirdPointswValues.shp: Geolocated user days with associated metadata. ebirdObserverHomeState.csv: List of unique users in our dataset and the most common country they upload in throughout all eBird data and the count of uploads they have. ValuationDataset.csv: Data associated with each upload used for valuation, along with the travel cost valuations. TravelCostAnalysis_ZAgrid.shp: Grid of South Africa with associated travel costs and suitability scores within each grid cell. MaxentOutput folder : Folder of Maxent suitability output for all models. Usage Notes: Citation: Please cite the manuscript when using this dataset:Manley, K., Ayompe, L. M., & Egoh, B. N. (2025). Climate Change Impacts the Non-Market Value of Nature: A Case Study of Birding Cultural Ecosystem Services in South Africa. PLOS Climate. Software Requirements: Maxent: For replicating suitability modeling (ArcGIS Pro also has a Maxent tool). Python/R: For travel cost and CES value calculations (requires geopy, googlemaps, and sklearn libraries for python). Data Access: eBird data requires an account and API key from eBird or can be directly downloaded from GBIF. Covariate data sources and preprocessing steps are detailed in the methods sections and in detail in Table S1.