Treating gaps and biases in biodiversity data as a missing data problem
Most Cited Paper
in Wildlife Ecology and Conservation
18 Months Post-Publication
Class of 2026
“Treating gaps and biases in biodiversity data as a missing data problem”
A research intelligence initiative by Pepkio
pri.pepkio.com/top-papers/wildlife-ecology-and-conservation/2026/
Topics
biodiversity monitoring data · Data gaps · Data gaps · spatial gaps · temporal gaps · sampling bias · species trends · long-term species trend modelling · missing data theory · missing data classes · subsampling · weighting techniques · imputation · bias reduction · parameter estimate uncertainty · factors driving missingness · Occurrence records · species abundances · Conservation prioritization · data representativeness
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Pepkio Research Index (PRI). Topics and Trends in Most Cited Wildlife Ecology and Conservation Papers, Class of 2026. https://pri.pepkio.com/top-papers/wildlife-ecology-and-conservation/2026. Accessed 2026-07-17. Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459