Treating gaps and biases in biodiversity data as a missing data problem
Most Cited Paper
in Species Distribution and Climate Change
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/species-distribution-and-climate-change/2026/
Topics
Biodiversity monitoring · Data gaps · Data gaps · Data gaps · Data gaps · Data bias · species trends · long-term species trend modelling · missing data theory · missing data theory · subsampling · weighting techniques · imputation · bias reduction · parameter estimate uncertainty · factors driving missingness · species occurrence data · species abundances · Conservation prioritization · data representativeness
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Pepkio Research Index (PRI). Topics and Trends in Most Cited Species Distribution and Climate Change Papers, Class of 2026. https://pri.pepkio.com/top-papers/species-distribution-and-climate-change/2026. Accessed 2026-07-21. 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