DOI: 10.5061/dryad.1ns1rn8w7
title: Biodiversity and infrastructure interact to drive tourism to and within Costa Rica

description: Significance Tourism accounts for roughly 10% of global gross domestic
 product, with nature-based tourism its fastest-growing sector in the past
 10 years. Nature-based tourism can theoretically contribute to local and
 sustainable development by creating attractive livelihoods that support
 biodiversity conservation, but whether tourists prefer to visit more
 biodiverse destinations is poorly understood. We examine this question in
 Costa Rica and find that more biodiverse places tend indeed to attract
 more tourists, especially where there is infrastructure that makes these
 places more accessible. Safeguarding terrestrial biodiversity is critical
 to preserving the substantial economic benefits that countries derive from
 tourism. Investments in both biodiversity conservation and infrastructure
 are needed to allow biodiverse countries to rely on tourism for their
 sustainable development.
description: The methods for how data were collected or produced are all
 stated in the main manuscript and in the Supporting Information
 (SI).
description: The data contains rasters and CSVs necessary to run the code
 associated with the Echeverri, Smith, et al. PNAS paper titled:
 "Biodiversity and infrastructure interact to drive tourism to and
 within Costa Rica".  Scripts are available in:
 (https://github.com/jeffreysmith-jrs/natcapCR/blob/main/bin/tourismModel.R). These are modified versions of publicly available data (cited in the main MS) that allow reproducibility of results. The files and their descriptions are as followed: arm_diversity.tif: Map showing combined species richness of amphibians, reptiles, and mammals (unit: # of species) amphibians.tif: Map showing species richness of amphibians (unit: # of species) reptiles.tif: Map showing species richness of reptiles (unit: # of species) mammals.tif: Map showing species richness of mammals (unit: # of species) abirdDiversity.tif: Map showing species richness of birds (unit: # of species) abirdDiversity_te.tif: Map showing species richness of threatened and endemic bird species (see Costa_Rican_Birds_endemic_JZ.csv, unit: # of species) tree-cover.tif: Map showing percent tree cover (unit: percentage) distWater.tif: Map showing distance to water (unit: kilometers) distRoads.tif: Map showing distance to roads (unit: kilometers) distPAs.tif: Map showing distance to protected areas (unit: kilometers) hoteDensity.tif: Map showing hotel density (see Hotels_revised_duplicates_deleted.csv, unit: unitless index) fcover1.tif: Map showing percentage non-photosynthetic bare ground (unit: percentage) fcover2.tif: Map showing percentage photosynthetic ground cover (unit: percentage) fcover3.tif: Map showing percentage impervious ground cover (unit: percentage) bio1.tif: Map showing mean annual temperature (unit: degrees Celsius * 10) bio4.tif: Map showing temperature seasonality (unit: unitless) bio12.tif: Map showing mean annual precipitation (unit: millimeters) bio15.tif: Map showing precipitation seasonality (unit: millimeters) Hotels_revised_duplicates_deleted.csv: CSV filed containing georeferenced locations of Costa Rican hotels flickr.csv: CSV filed containing georeferenced locations of Flickr photos checklist_uploads.csv: CSV filed containing georeferenced locations of eBird checklists Costa_Rican_Birds_endemic_JZ.csv: CSV file containing data on which species are IUCN listed and/or endemic in Costa Rica compiled by paper co-author Jim Zook <strong>In addition, we have included 6 result maps which allow for reproducibility of figures:</strong> ebird_base.tif: Predicted tourism using model constructed with all predictor variables and eBird checklists (unit: index between 0 and 1) ebird_noBio.tif: Predicted tourism using model constructed without biodiversity predictor variables and eBird checklists (unit: index between 0 and 1) ebird_noInfra.tif: Predicted tourism using model constructed without infrastructure variables and eBird checklists (unit: index between 0 and 1) flickr_base.tif: Predicted tourism using model constructed with all predictor variables and flickr photos (unit: index between 0 and 1) flickr_noBio.tif: Predicted tourism using model constructed without biodiversity predictor variables and flickr photos (unit: index between 0 and 1) flickr_noInfra.tif: Predicted tourism using model constructed without infrastructure variables flickr photos (unit: index between 0 and 1)