ArticleNature ecology & evolution2023
Empirical evidence of widespread exaggeration bias and selective reporting in ecology.
Article in Nature ecology & evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis reveals weak associations between reef fishes and corals.Nature ecology & evolution · 2024Pooled it
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- Tropical forest carbon sequestration accelerated by nitrogen.Nature communications · 2026Article
- Standard and non-standard measurements of wood density: how big is the breach?Annals of botany · 2025Article
- From policy to practice: progress towards data- and code-sharing in ecology and evolution.Proceedings. Biological sciences · 2025Article
- Conceptual and ethical considerations in invasion science.Bioscience · 2025Article
- Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology.BMC biology · 2025Article
- How will we prepare for an uncertain future? The value of open data and code for unborn generations facing climate change.Proceedings. Biological sciences · 2025Article
- Article
- A large-scale in silico replication of ecological and evolutionary studies.Nature ecology & evolution · 2024Article
- Impact of redefining statistical significance on P-hacking and false positive rates: An agent-based model.PloS one · 2024Article
- Computationally reproducing results from meta-analyses in ecology and evolutionary biology using shared code and data.PloS one · 2024Article
- Finding the right power balance: Better study design and collaboration can reduce dependence on statistical power.PLoS biology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In many scientific disciplines, common research practices have led to unreliable and exaggerated evidence about scientific phenomena. Here we describe some of these practices and quantify their pervasiveness in recent ecology publications in five popular journals. In an analysis of over 350 studies published between 2018 and 2020, we detect empirical evidence of exaggeration bias and selective reporting of statistically significant results. This evidence implies that the published effect sizes in ecology journals exaggerate the importance of the ecological relationships that they aim to quantify. An exaggerated evidence base hinders the ability of empirical ecology to reliably contribute to science, policy, and management. To increase the credibility of ecology research, we describe a set of actions that ecologists should take, including changes to scientific norms about what high-quality ecology looks like and expectations about what high-quality studies can deliver.
Indexed as
Identifiers
37537387What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.