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A novel method to handle the effect of uneven sampling effort in biodiversity databases
Iker Pardo1, María P Pata, Daniel Gómez
1Conservation of Biodiversity, Pyrenean Institute of Ecology (CSIC), Zaragoza, Spain. iker.pardo@ipe.csic.es
Plos One
|January 18, 2013
Summary
Reliable biodiversity mapping requires accurate sampling effort assessment. The new FIDEGAM method effectively distinguishes well-sampled areas from poorly-sampled ones, improving biodiversity data reliability.
Area of Science:
- Ecology
- Biodiversity Science
- Conservation Biology
Background:
- Biodiversity distribution analyses using databases face uncertainty due to sampling bias.
- Quantifying sampling effort is crucial for reliable biodiversity assessments.
- Existing methods for assessing sampling completeness have unknown statistical limitations.
Purpose of the Study:
- To evaluate the discrimination capability of sampling effort assessment methods.
- To compare the performance of two existing methods with a new method, FIDEGAM.
- To assess the accuracy of methods in representing true sampling completeness.
Main Methods:
- Species accumulation curves were used as the basis for all methods.
- Receiver Operating Characteristic (ROC) analyses were employed to assess discrimination capacity.
- Simulations were conducted with known species richness to evaluate method accuracy.
Main Results:
- FIDEGAM demonstrated excellent discrimination between well- and poorly-sampled areas across all scenarios.
- Existing methods failed to reliably distinguish sampling completeness.
- FIDEGAM's output strongly correlated with true species detection rates in simulations.
Conclusions:
- FIDEGAM is a highly accurate and reliable method for quantifying sampling effort in biodiversity databases.
- The method can significantly enhance the reliability of spatial biodiversity analyses.
- Accurate sampling effort quantification is essential for robust ecological research and conservation planning.
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