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Data from the Cornell Lab of Ornithology's citizen-science projects are
on a scale that no single person or group of researchers could ever collect
alone. These data have been accepted by the scientific community because
of the scale at which the data are collected, rigor of the analyses, intensity
of the follow-up studies, and acknowledged limitations of the data.
Carefully collected and recorded data are useful regardless of the experience
of the citizen scientist. Briefly, here are
The benefits of citizen-science data »
How we promote data quality »
How we overcome the limitations of citizen-science data »
Benefits of citizen-science data
- space: large geographic scale with data from across the
continent and beyond
- time: long time scale with information collected over
many years in the same locations
- size: huge set of data allowing comprehensive statistical
analyses and predictive modeling, for example, more than 5 million individual
birds are reported to Project FeederWatch each year
Enhancing and ensuring data quality
- protocol development: straightforward instructions are
developed for each project based on the scientific questions being asked
and anticipated methods of analysis; protocols typically include built-in
repetition or specificity that promotes participant success
- counts: birds, eggs, nests, and similar information are
discrete units that can be counted; counts are less likely to be biased
(consistently wrong in the same direction) than interpretations of behavior
or ecology
- common species: project instructions encourage reports
of common species because these data are extensive enough to allow thorough
analysis and modeling
- missing species: most projects ask participants to note
if they are reporting all of the species they observed; this allows scientists
to determine if a species is absent because is wasn't reported or because
it was not seen
- rare and unusual reports: species that are reported out
of their typical ranges and individual birds with unusual plumage are
examples of data that project staff spend considerable time verifying;
some records must be approved by regional or state experts; photo documentation
or similar verification usually is required for the records to be used
by scientists
- online data entry: each step of the online data entry
process has been carefully designed to promote careful data entry and
to simplify data for analysis
- Basic information must be "in range" to be accepted. For
example, choosing a date in the future results in a message that asks
you to check the date because it is not possible. The date must be corrected
before continuing.
- Bird species names are provided on the data entry pages. This ensures
that the database lists and accepts only recognized species ("American
Crow" rather than "crow"). Also, it can be specifically
coded by our database computers, allowing the data from all of our projects
for a particular species to be listed with exactly the same code.
- Some projects list only the bird species for the particular location
and date entered. This shortens the list and helps to prevent incorrect
entries.
- A count that is outside of a predictable range must be verified by
the participant before continuing. For example, if a report includes
a known clutch size of 4 eggs, it will not allow 5 nestlings to be reported
for the same nest.
Overcoming the limitations of citizen-science data
- patterns: most of the Lab of Ornithology's citizen-science
data allow scientists to examine patterns and trends in bird populations;
for example, changes, declines, or movements of birds in the same time
frame over a large geographic area are likely to represent phenomena that
deserve closer inspection which may or may not be possible with the data
available
- follow-up: once patterns are discovered, small, focused
studies can be developed to examine more specific effects on population
trends; the new studies sometimes evolve into new citizen-science projects;
for example, geographic trends in incubation period and hatching failure
launched a study of incubation behaviors of bluebirds using temperature
data loggers placed in bluebird nests
- indices versus estimates: it is not possible to
directly estimate the size of a bird population from our citizen-science
data; however, since participants follow specific protocols it is possible
to get an "index" of a population. Changes in the value of an
index reflect changes in a population (increases or declines, for example)
so scientists focus on these indices rather than attempting to directly
estimate population parameters
Why
count birds? »
Read
about the projects. »
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