Koala Counter: Recording Citizen Scientists’ search paths to Improve Data Quality

Abstract

Biodiversity monitoring is key for developing informed solutions to the threats facing our environment, including habitat loss, increasing pollution, wildlife trafficking and climate change. Citizen science is increasingly used for collecting species observational data at wide spatial and temporal scales that are difficult and expensive to achieve using traditional means. Current apps used for citizen science biodiversity monitoring provide methods to record observational data on species’ presence, including photos, location, date, time and an assortment of other data. However, data about species absences as well as automatically generated and accurate data on both search effort and search locations have been lacking. Koala Counter is a free, cross-platform (Android & iOS), open-source app that was developed for a citizen science project to collect koala population data to inform koala conservation and management in South Australia. The app uses mobile phone sensors to transparently and automatically record metadata such as species observation location and time, the search path the user takes, the time taken while searching and GPS location precision. We tested this in the Citizen Science event “The Great Koala Count 2” in South Australia during November 2016. Observations, paths and search effort data were accurate overall. Location accuracy was good, with some exceptions. Use of the app indicated a number of potential improvements that would further increase data quality. Recording search paths offers a potentially valuable method of recording spatial and temporal components of search effort, improving on simple records of species observations and time taken, especially when no observations are made. These data may enable better ecological modelling by supplying accurate search effort data as well as enabling improved inference of species absence. Search paths also show locations that have not been searched, which is valuable information in management of citizen science monitoring programs. © 2020 The Author(s)