Solutions for loss of information in high‐beta‐diversity community data
Robert J. Smith · 2016 · Methods in Ecology and Evolution
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Summary Dissimilarity measures, which gauge compositional resemblance between sample units, tend to lose information with increasing distance along ecological gradients. This undesirable property is especially common in high‐beta‐diversity…
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Metadata source: OpenAlex · DOI 10.1111/2041-210x.12652