Using auxiliary population samples for sample-selection correction in models based on crowd-sourced volunteered geographic information

Abstract

Data from citizen science (CS) projects (and some social media) can offer selected samples with extensive information about human interactions with the natural world. Independently, we elicit levels of engagement with the eBird project from members of the eBird CS project and from a general-population sample. The general-population sample allows an ordered-probit model to explain propensities to engage with eBird at different levels, which we transfer to predict selection-correction terms for our independent sample of eBird members. We illustrate our method with a question posed only to our eBird-member survey sample about the radii of their individual spatial consideration sets for typical one-day birding excursions.