Development and Applications of Aquatic Branched Glycerol Dialkyl Glycerol Tetraethers as Indicators of Past Temperature in High-latitude Regions
Bibliographic record
Abstract
Anthropologically driven climate change will disproportionately affect high-latitude regions. Forecasting these changes necessitates a better understanding of polar climate dynamics, gained through climate reconstructions using proxies such as branched glycerol dialkyl glycerol tetraethers (brGDGTs) in sedimentary archives. While the temperature sensitivity of terrestrial-aquatic brGDGTs is well understood at the global scale, knowledge of high-latitude brGDGTs is limited, obstructing high-latitude applications of the climate proxy. Modern lacustrine and fluvial sediment samples from northwestern Canada and Alaska were compiled with previously published data to address this knowledge gap. The lacustrine data set reveals a unique brGDGT temperature response compared to global compilations, suggesting that future applications of this proxy should consider regional biases and employ environmentally appropriate transfer functions to improve paleoclimate interpretations. For regions without modern lacustrine brGDGT data sets, a pan-Arctic brGDGT-temperature transfer function was developed, which better predicts high-latitude warm-season temperatures than global equations. This transfer function was used to reconstruct warm-season temperatures since 10 ka BP from a lacustrine brGDGT record in northern Finland. A comparison of independent proxy-based reconstructions from Fennoscandia broadly corroborates the reconstruction, but also highlights some differences among proxy types (pollen, diatoms, and chironomids) with respect to the timing of peak Holocene warmth, driven partly by proxy-specific seasonal biases, which must be considered when studying Fennoscandian Holocene climate dynamics. This work also illuminated the potential of fluviolacustrine brGDGT deposits to further our knowledge of pre-Quaternary climates in Alaska (Alaska Range and east-central Alaska). A global network of modern fluvial brGDGT samples, including Alaskan and northwestern Canadian sites, was analysed and revealed a temperature response that was nearly identical to that of global lacustrine brGDGTs. A unified fluviolacustrine brGDGT-temperature transfer function was derived and usedto provide some of the few quantitative Neogene temperature constraints for the study area. This method has considerable promise for applications in other mountainous belts of the world where Cenozoic fluviolacustrine strata are exposed. This thesis provides a framework for improved applications of the brGDGT paleothermometer in high-latitude regions and in lacustrine and fluviolacustrine depositional environments during periods that are critical to informing our understanding of past climate dynamics and future change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".