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Statistical solutions for error and bias in global citizen science datasets
Citation
Bird, TJ and Bates, AE and Lefcheck, JS and Hill, NA and Thomson, RJ and Edgar, GJ and Stuart-Smith, RD and Wotherspoon, S and Krkosek, M and Stuart-Smith, JF and Pecl, GT and Barrett, N and Frusher, S, Statistical solutions for error and bias in global citizen science datasets, Biological Conservation, 173 pp. 144-154. ISSN 0006-3207 (2014) [Refereed Article]
Copyright Statement
Copyright 2013 Elsevier
DOI: doi:10.1016/j.biocon.2013.07.037
Abstract
Networks of citizen scientists (CS) have the potential to observe biodiversity and species distributions at
global scales. Yet the adoption of such datasets in conservation science may be hindered by a perception
that the data are of low quality. This perception likely stems from the propensity of data generated by CS
to contain greater levels of variability (e.g., measurement error) or bias (e.g., spatio-temporal clustering)
in comparison to data collected by scientists or instruments. Modern analytical approaches can account
for many types of error and bias typical of CS datasets. It is possible to (1) describe how pseudo-replication
in sampling influences the overall variability in response data using mixed-effects modeling, (2) integrate
data to explicitly model the sampling process and account for bias using a hierarchical modeling
framework, and (3) examine the relative influence of many different or related explanatory factors using
machine learning tools. Information from these modeling approaches can be used to predict species distributions
and to estimate biodiversity. Even so, achieving the full potential from CS projects requires
meta-data describing the sampling process, reference data to allow for standardization, and insightful
modeling suitable to the question of interest.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | volunteer data, statistical analysis, experimental design, linear models, additive models, species distribution models, biodiversity, reef life survey |
| Research Division: | Agricultural and Veterinary Sciences |
| Research Group: | Fisheries Sciences |
| Research Field: | Fisheries Sciences not elsewhere classified |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding Knowledge |
| Objective Field: | Expanding Knowledge in the Biological Sciences |
| UTAS Author: | Bird, TJ (Mr Tomas Bird) |
| UTAS Author: | Bates, AE (Dr Amanda Bates) |
| UTAS Author: | Hill, NA (Dr Nicole Hill) |
| UTAS Author: | Thomson, RJ (Dr Russell Thomson) |
| UTAS Author: | Edgar, GJ (Professor Graham Edgar) |
| UTAS Author: | Stuart-Smith, RD (Dr Rick Stuart-Smith) |
| UTAS Author: | Wotherspoon, S (Dr Simon Wotherspoon) |
| UTAS Author: | Stuart-Smith, JF (Dr Jemina Stuart-Smith) |
| UTAS Author: | Pecl, GT (Professor Gretta Pecl) |
| UTAS Author: | Barrett, N (Associate Professor Neville Barrett) |
| UTAS Author: | Frusher, S (Professor Stewart Frusher) |
| ID Code: | 86722 |
| Year Published: | 2014 |
| Web of Science® Times Cited: | 108 |
| Deposited By: | Sustainable Marine Research Collaboration |
| Deposited On: | 2013-10-16 |
| Last Modified: | 2017-11-15 |
| Downloads: | 0 |
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