ArticleGeophysical research letters2021
Statistical Uncertainty in Paleoclimate Proxy Reconstructions.
Article in Geophysical research letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed.
- High-resolution XRF-CS/ICP-MS mineral element data calibration and potential applications in sub-Antarctic peat records.Scientific reports · 2026Article
- Quantitative assessment of past variations in Sphagnum bog community structure using paleo-species distribution modeling.Ecology · 2025Article
- Statistical Uncertainty in Paleoclimate Proxy Reconstructions.Geophysical research letters · 2021Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A quantitative analysis of any environment older than the instrumental record relies on proxies. Uncertainties associated with proxy reconstructions are often underestimated, which can lead to artificial conflict between different proxies, and between data and models. In this paper, using ordinary least squares linear regression as a common example, we describe a simple, robust and generalizable method for quantifying uncertainty in proxy reconstructions. We highlight the primary controls on the magnitude of uncertainty, and compare this simple estimate to equivalent estimates from Bayesian, nonparametric and fiducial statistical frameworks. We discuss when it may be possible to reduce uncertainties, and conclude that the unexplained variance in the calibration must always feature in the uncertainty in the reconstruction. This directs future research toward explaining as much of the variance in the calibration data as possible. We also advocate for a "data-forward" approach, that clearly decouples the presentation of proxy data from plausible environmental inferences.
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Registered trials
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