Rule of Plum: Comparison of lead-210 dates derived from Bayesian analysis and the Constant Rate of Supply model using simulated and real datasets
Bibliographic record
Abstract
To understand changes in peat accumulation in response to recent and rapid climate or anthropogenic change, accurate ages for the last 100-200 years are essential. Dating this period is often complicated by poor resolution and large errors associated with calibrating radiocarbon (<sup>14</sup>C) ages. The use of lead-210 (<sup>210</sup>Pb) is a popular method as it allows for the measurement of absolute and continuous dates for the last 150 years of peat accumulation.<br/><br/>In ombrotrophic peatlands, the <sup>210</sup>Pb dating method has traditionally relied on the Constant Rate of Supply (CRS) model which uses the radioactive decay equation to provide a logarithmic model to approximate dates, resulting in a restrictive model. Key limitations of the CRS model are: (1) the accurate estimation of the supported lead which varies between sites and can be problematic if sampling of the total inventory is not continuous (e.g. interval measurements, lack of samples); (2) the inconsistent assessment of uncertainties. The Plum model was developed in a statistical framework with a Bayesian approach, notably resulting in longer chronologies and more realistic uncertainty estimations, and has the advantage of not double-modelling dates for final age-depth models.<br/><br/>Here, we present two thorough tests of Plum. First, we created scenarios using simulated datasets with known age-depth functions in a range of shapes and with varying sampling resolution. These simulations are created using the physical behavior that most <sup>210</sup>Pb dating models are based on. Plum and CRS model outputs are compared under each scenario. We also take this opportunity to demonstrate the new Plum R package, for use by non-statisticians in palaeoecological studies. Second, we present a comparison of <sup>210</sup>Pb dates derived from CRS models and from Plum using real peat cores from Eastern Canada with additional independent dating controls. These cores represent a thorough test for Plum, as permafrost thaw during the last 50 years has drastically altered stratigraphy and peat type (e.g. shift from ligneous peat to Sphagnum moss) affecting <sup>210</sup>Pb retention within the peat. Recent decadal-scale changes are still poorly represented so accurate dating is now essential to quantify changes in carbon accumulation rates and predict future trends.<br/><br/><br/>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".