Stable Carbon Isotope Compositions of Eastern Beringian Grasses and Sedges: Investigating Their Potential as Paleoenvironmental Indicators
Bibliographic record
Abstract
The nature of vegetation cover present in Beringia during the last glaciation remains unclear. Uncertainty rests partly with the limitations of conventional paleoecological methods. A lack of sufficient taxonomic resolution most notably associated with the grasses and sedges restricts the paleoecological inferences that can be made. Stable isotope measurements of subfossil plants are frequently used to enhance paleoenvironmental reconstructions. We present an investigation of the stable carbon isotope composition (δ13C) of modern and subfossil grasses and sedges (graminoids) from Eastern Beringia. Modern grasses from wet habitats had a mean δ13C of −29.1‰ (standard deviation [SD] = 2.1‰, n = 75), while those from dry habitats had a mean of −26.9‰ (SD = 1.19, n = 27). Sedges (n = ~50) from dry, wet, marsh, and sand dune habitats had specific habitat ranges. Four modern C4 grasses had δ13C values typical of C4 plants. Analyses were also conducted using subfossil graminoid remains from several sedimentary paleoecological contexts (e.g., arctic ground squirrel nests, loess, permafrost, and paleosols) in Eastern Beringia. Results from these subfossil samples, ranging in age from >40,000 to ca. 11,000 cal. yr BP, illustrate that the δ13C of graminoid remains has altered during the past. The range of variation in the subfossil samples is within the range from modern graminoid specimens from dry and wet habitats. The results indicate that stable isotopes could contribute to a comprehensive and multiproxy reconstruction of Beringian paleoenvironments.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".