The role of climate and hydrology fluctuations in shaping Northern Alaska plant community over the last three millennia
Bibliographic record
Abstract
Rising temperatures observed in recent decades are driving changes in the development of wetland ecosystems in Arctic regions. Therefore, there is a need to assess the current ecological state of peatlands in the Arctic zone to predict their development in the future. This study uses high-resolution multi-proxy palaeoecological analyses (plant macrofossils, pollen, testate amoebae, peat stoichiometry and stable isotopes), supported by radiocarbon ( 14 C) and lead ( 210 Pb and 239+240 Pu), from two peat profiles covering the last 3200 and 1350 years, respectively, located on the northern part of Alaska. We aim to (i) determine the timing of the peat initiation process; ii) identify predominant peat-forming plant species; iii) reconstruct local and regional vegetation changes; iv) reconstruct hydrological changes and v) explore the role of climate-induced hydrological changes on the development of Arctic peat-forming and shrubs plant communities. Our studies revealed that 1) peat initiation occurred at ca. 1200 BCE and 350 BCE through a paludification process; 2) plant communities dominated by sedges and brown mosses played a key role as a main peat-forming species and remained stable for centuries; 3) changes in the composition of dominant peat-forming plants, from sedges and brown mosses, common in wet habitats to Sphagnum and brown mosses typical of drier habitats, were linked to climate warming between 1940 CE and 1960 CE and 4) the drop of the water table depth level during warm climate phases facilitated the spread of shrub and dwarf shrubs in the Arctic plain. Our study shows that the recent surge in woody vegetation exceeds any recorded expansion in the past three millennia, documenting the rapid changes occurring in Arctic plant communities from Northern Alaska.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".