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Published on: December 9, 2015
Site-occupancy distribution modeling to correct population-trend estimates derived from opportunistic observations
Marc Kéry1, J Andrew Royle, Hans Schmid
1Swiss Ornithological Institute, 6204 Sempach, Switzerland. marc.kery@vogelwarte.ch
Summary
Citizen scientists
Area of Science:
- Ecology
- Biodiversity Monitoring
- Citizen Science
Background:
- Estimating species population trends from opportunistic citizen science data is challenging due to variable observation effort.
- Distinguishing genuine population changes from effort variations requires robust analytical methods.
Purpose of the Study:
- To develop and validate a method for correcting annual variations in observation effort when estimating species occupancy trends from citizen science data.
- To provide unbiased estimators for species distribution, colonization, and extinction rates.
Main Methods:
- Generated detection histories for all surveyed sites.
- Applied site-occupancy models directly to detection-history data to estimate detectability (representing observation effort) and occupancy.
- Used within-season replicate surveys to inform detectability estimates.
Main Results:
- The developed method successfully corrected for annual variations in observation effort.
- Site-occupancy models provided unbiased estimates of species distribution and distributional change rates.
- Detectability was consistently less than 1 and varied annually, highlighting the need for effort correction.
Conclusions:
- The proposed method offers a robust solution for analyzing opportunistic species observations, accounting for variable effort.
- Accurate species distribution modeling and trend estimation are achievable with citizen science data using this approach.
- The method is broadly applicable to global biodiversity monitoring and species distribution modeling efforts.
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