A global compilation of diatom silica oxygen isotope records from lake sediment – trends and implications for climate reconstruction
Bibliographic record
Abstract
Abstract. Oxygen isotopes in biogenic silica (δ18OBSi) from lake sediments allow for quantitative reconstruction of past hydroclimate and proxy-model comparison in terrestrial environments. The signals of individual records have been attributed to different factors, such as air temperature (Tair), atmospheric circulation patterns, hydrological changes, and lake evaporation. While every lake has its own local set of drivers of δ18O variability, here we explore the extent to which regional or even global signals emerge from a series of paleoenvironmental records. This study provides a comprehensive compilation and combined statistical evaluation of the existing lake sediment δ18OBSi records, largely missing in other summary publications (i.e. PAGES network). For this purpose, we have identified and compiled 71 down-core records published to date and complemented these datasets with additional lake basin parameters (e.g. lake water residence time and catchment size) to best characterize the signal properties. Records feature widely different temporal coverage and resolution, ranging from decadal-scale records covering the past 150 years to records with multi-millennial-scale resolution spanning glacial–interglacial cycles. The best coverage in number of records (N = 37) and data points (N = 2112) is available for Northern Hemispheric (NH) extratropical regions throughout the Holocene (roughly corresponding to Marine Isotope Stage 1; MIS 1). To address the different variabilities and temporal offsets, records were brought to a common temporal resolution by binning and subsequently filtered for hydrologically open lakes with lake water residence times < 100 years. For mid- to high-latitude (> 45° N) lakes, we find common δ18OBSi patterns among the lake records during both the Holocene and Common Era (CE). These include maxima and minima corresponding to known climate episodes, such as the Holocene Thermal Maximum (HTM), Neoglacial Cooling, Medieval Climate Anomaly (MCA) and the Little Ice Age (LIA). These patterns are in line with long-term air temperature changes supported by previously published climate reconstructions from other archives, as well as Holocene summer insolation changes. In conclusion, oxygen isotope records from NH extratropical lake sediments feature a common climate signal at centennial (for CE) and millennial (for Holocene) timescales despite stemming from different lakes in different geographic locations and hence constitute a valuable proxy for past climate reconstructions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".