Articles | Volume 22, issue 23
https://doi.org/10.5194/bg-22-7687-2025
https://doi.org/10.5194/bg-22-7687-2025
Research article
 | 
08 Dec 2025
Research article |  | 08 Dec 2025

Utilizing probability estimates from machine learning and pollen to understand the depositional influences on branched GDGT in wetlands, peatlands, and lakes

Amy Cromartie, Cindy De Jonge, Guillemette Ménot, Mary Robles, Lucas Dugerdil, Odile Peyron, Marta Rodrigo-Gámiz, Jon Camuera, Maria Jose Ramos-Roman, Gonzalo Jiménez-Moreno, Claude Colombié, Lilit Sahakyan, and Sébastien Joannin

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-526', Joseph B. Novak, 07 Mar 2025
    • AC1: 'Reply on RC1', Amy Cromartie, 03 May 2025
  • RC2: 'Comment on egusphere-2025-526', Anonymous Referee #2, 08 Apr 2025
    • AC2: 'Reply on RC2', Amy Cromartie, 03 May 2025

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Reconsider after major revisions (16 May 2025) by Petr Kuneš
AR by Amy Cromartie on behalf of the Authors (19 Jun 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (23 Jun 2025) by Petr Kuneš
AR by Amy Cromartie on behalf of the Authors (01 Jul 2025)  Manuscript 

Post-review adjustments

AA – Author's adjustment | EA – Editor approval
AA by Amy Cromartie on behalf of the Authors (28 Nov 2025)   Author's adjustment   Manuscript
EA: Adjustments approved (28 Nov 2025) by Petr Kuneš
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Short summary
BrGDGT (branched glycerol dialkyl glycerol tetraethers) are a molecular biomarker utilized for paleotemperature reconstructions. One issue, however, with utilizing brGDGTs is that the distribution differs in relation to sediment environments (i.e., peat, lake, soil). We utilize the probability estimate outputs from five machine learning algorithms and a new modern brGDGT database to track provenance change and apply these models to two downcore records utilizing pollen, non-pollen polymorphs, and XRF (X-ray fluorescence) to confirm the models’ accuracy.
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