Smartphone-based distributed data collection enables rapid assessment of shorebird habitat suitability

PLoS ONE
By: , and 

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Abstract

Understanding and managing dynamic coastal landscapes for beach-dependent species requires biological and geological data across the range of relevant environments and habitats. It is difficult to acquire such information; data often have limited focus due to resource constraints, are collected by non-specialists, or lack observational uniformity. We developed an open-source smartphone application called iPlover that addresses these difficulties in collecting biogeomorphic information at piping plover (Charadrius melodus) nest sites on coastal beaches. This paper describes iPlover development and evaluates data quality and utility following two years of collection (n = 1799 data points over 1500 km of coast between Maine and North Carolina, USA). We found strong agreement between field user and expert assessments and high model skill when data were used for habitat suitability prediction. Methods used here to develop and deploy a distributed data collection system have broad applicability to interdisciplinary environmental monitoring and modeling.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Smartphone-based distributed data collection enables rapid assessment of shorebird habitat suitability
Series title PLoS ONE
DOI 10.1371/journal.pone.0164979
Volume 11
Issue 11
Year Published 2016
Language English
Publisher PLOS
Contributing office(s) Woods Hole Coastal and Marine Science Center
Description e0164979; 22 p.