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Quantifying data quality in a citizen science monitoring program: False negatives, false positives and occupancy trends
- Source :
- Conservation Science and Practice, Vol 1, Iss 7, Pp n/a-n/a (2019)
- Publication Year :
- 2019
- Publisher :
- Wiley, 2019.
-
Abstract
- Data collected by volunteers are an important source of information used in species management decisions, yet concerns are often raised over the quality of such data. Two major forms of error exist in occupancy datasets; failing to observe a species when present (imperfect detection—also known as false negatives), and falsely reporting a species as present (false‐positive errors). Estimating these rates allows us to quantify volunteer data quality, and may prevent the inference of erroneous trends. We use a new parameterization of a dynamic occupancy model to estimate and adjust for false‐negative and false‐positive errors, producing accurate estimates of occupancy. We validated this model using simulations and applied it to 12 species datasets collected from a 15‐year, large‐scale volunteer amphibian monitoring program. False‐positive rates were low for most, but not all, species, and accounting for these errors led to quantitative differences in occupancy, although trends remained consistent even when these effects were ignored. We present a model that represents an intuitive way of quantifying the quality of volunteer monitoring datasets, and which can produce unbiased estimates of occupancy despite the presence of multiple types of observation error. Importantly, this allows the quality of volunteer monitoring data to be assessed without relying on comparisons with expert data.
- Subjects :
- false positive
lcsh:QH1-199.5
Occupancy
Computer science
media_common.quotation_subject
Inference
imperfect detection
lcsh:General. Including nature conservation, geographical distribution
volunteer
10127 Institute of Evolutionary Biology and Environmental Studies
lcsh:QH540-549.5
citizen science
Statistics
Citizen science
False positive paradox
Quality (business)
occupancy model
General Environmental Science
media_common
false negative
Monitoring program
observation bias
monitoring
trend
Data quality
Monitoring data
570 Life sciences
biology
590 Animals (Zoology)
false‐positive
General Earth and Planetary Sciences
amphibian
occupancy modeling
lcsh:Ecology
Subjects
Details
- ISSN :
- 25784854
- Volume :
- 1
- Database :
- OpenAIRE
- Journal :
- Conservation Science and Practice
- Accession number :
- edsair.doi.dedup.....cd891b3dbe5e2891ec261d99f9f8082c