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Dryad

Data from: Can avian functional traits predict cultural ecosystem services?

Cite this dataset

Echeverri, Alejandra et al. (2019). Data from: Can avian functional traits predict cultural ecosystem services? [Dataset]. Dryad. https://doi.org/10.5061/dryad.cjsxksn1p

Abstract

  1. The functional trait diversity of species assemblages can predict the provision of ecosystem services such as pollination and carbon sequestration, but it is unclear whether the same trait-based framework can be applied to identify the factors that underpin cultural ecosystem services and disservices. 
  2. To explore the relationship between traits and the contribution of species to cultural ecosystem services and disservices, we conducted 404 questionnaire surveys with birdwatchers and local residents in Guanacaste, Costa Rica.
  3. We used an information-theoretic approach to identify which of 20 functional traits for 199 Costa Rican bird species best predicted their cultural ecosystem service scores related to birdwatching, acoustic aesthetics, education and local identity, as well as disservices (e.g., harm to crops). 
  4. We found that diet was the most important variable explaining perceptions of cultural ecosystem service and disservice providers. Aesthetic traits such as plumage colour and pattern were important in explaining birdwatching scores. We also found people have a high affinity for forest-affiliated birds. 
  5. The insight that functional traits can explain variation among cultural perspectives on values derived from birds offers a first step towards a trait-based system for understanding the species attributes that underpin cultural ecosystem services and disservices.

Methods

These data were collected trait by trait from different sources including EltonTrait database, information from the Stiles & Skutch (1989) book, and also morphological traits were collected by visiting museum collections across the world. Plumage color/pattern traits were collected from the Garrigues & Dean book, and acoustic traits were collected from Xeno-canto recordings and by processing them in the raven pro software. For full details on trait data collection, please read the Echeverri, et al. (2019) People and Nature manuscript.

Usage notes

The description of each variable is in the table of the Echeverri, et al. (2019) People and Nature manuscript.

Funding

National Geographic Society, Award: National Geographic Young Explorers Grant, C335-16

US Forest Service, Award: 16-IJ-11242309-057

Social Sciences and Humanities Research Council, Award: Human-nature relationships and values from meanings to mitigation and practice

Natural Environment Research Council, Award: NE/I028068/1