Assessing Coastal Wetland Carbon and Mineral Accumulation Response to Changing Climate, Cape Espenberg, Alaska
Bibliographic record
Abstract
The Arctic is experiencing warming and ecological shifts due to climate change and the compounding effects of polar amplification. Arctic Alaskan coastal marsh environments, such as the Cape Espenberg barrier beach system, offer an opportunity to determine the carbon cycle response to changing climate by examining sediment records that have been preserved through time as shoreline-parallel, linear geometry prograding geomorphic features. This study determines the carbon and mineral accumulation trends in marsh environments at Cape Espenberg for both paleo (~776 CE to 1850 CE) and modern (post-1850 CE) time frames. A comprehensive physical and chemical dataset, including radioisotope (137Cs, 210Pb, 14C), stable isotope (δ13C), element concentration (%C, %N, C:N), and dry bulk density, has been built for several sediment cores. Results indicate that carbon and mineral accumulation rates have increased from paleo to modern times, potentially because of better growing and preservation conditions for organic matter in a modern climate. Paleoclimate trends in the Medieval Climate Anomaly (MCA) and warm periods interspersed within the Little Ice Age (LIA) also correlate with greater contributions of wetland organic matter, as evidenced by lighter δ13C values. Cold climate periods within the LIA correlate with increased aquatic organic matter sourcing and heavier δ13C values, with some spikes of wetland sources interspersed throughout the LIA. Future temperatures are predicted to rise with global climate change, which may continue to expand carbon stores in Arctic coastal wetland sediments. This has been observed in the swale environments at Cape Espenberg, where increasingly favourable growing and soil-preservation conditions (i.e. wet/anoxic soils and lower salinity to limit organic material decay, higher temperatures to promote growth) are increasing the carbon storage within Arctic coastal carbon reservoirs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".