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We investigated how sampling bias in botanical dataset can influence patterns of species richness and parameter estimation from statistical analyses. We tested the effectiveness of seven commonly used sample-size-correcting methods to analyse species richness patterns for Ecuador. We found that species richness was strongly connected with sampling even after correcting for sampling effort. One method, rarefaction, performed considerably better than the other methods. The study emphasise that using big, collected datasets is not without limitations and we recommend using rarefaction for species richness estimation from these datasets.

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This page is a summary of: Reply to Feeley and Rehm: Land-use intensification increases risk of species losses from climate change, Proceedings of the National Academy of Sciences, October 2015, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.1518956112.
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