# Treating gaps and biases in biodiversity data as a missing data problem

*PRI Rank #16 · Topics and Trends in Most Cited Wildlife Ecology and Conservation Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/wildlife-ecology-and-conservation/2026/rank-16*

| Field | Value |
| --- | --- |
| Rank | #16 |
| 18m citations | 43 |
| Journal | Biological reviews/Biological reviews of the Cambridge Philosophical Society |
| Year | 2024 |
| DOI | 10.1111/brv.13127 |
| Corresponding authors | Diana E. Bowler |
| Institution | UK Centre for Ecology & Hydrology, United Kingdom |

**Ranking page:** [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)

**Paper link:** [10.1111/brv.13127](https://doi.org/10.1111/brv.13127)

## 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

## Cite this ranking

```
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
```