Carbon and hydrogen isotopes of <i>n</i>‐alkanes in soils reconstructed after mining disturbance
Bibliographic record
Abstract
Abstract Ecosystem reconstruction after mining disturbance is a challenge considering the multitude of factors that affect soil formation and revegetation. In the boreal forest of western Canada, peat material is often used as the organic amendment for land reclamation to upland forest. Carbon and water dynamics of peat‐dominated ecosystems differ from natural upland forest soils. The objective of this work was to evaluate the evolution of soils reconstructed after mining disturbance using 13 C and 2 H analyses of n ‐alkane tracers. Ten soils from natural ecosystems were sampled (0–10 cm) and compared with 11 soils from novel ecosystems ranging in age from 0 to 30 yr, as well as a fresh peat sample. Soils supported different vegetation, including pine ( Pinus spp.), aspen ( Populus spp.), and white spruce [ Picea glauca (Moench) Voss]. Despite overlaps for some individual n ‐alkanes, we found a dominance of n ‐C 25 in reconstructed soils, also dominant in the peat material, and a dominance of n ‐C 27 in natural soils, one of the dominant n ‐alkanes in natural forest vegetation. In addition, there was a significant difference in odd n ‐alkane δ 2 H and δ 13 C values between natural and reconstructed soils ( p < .05). Differences in δ 2 H values, more negative for reconstructed soils than for natural soils, were attributed to changes in soil moisture, from wetter peat‐dominated soils to drier upland forests; among forest types, δ 2 H values were most negative under pine vegetation. The δ 13 C composition of odd n ‐alkanes, in particular n ‐C 27 , was significantly related to tree age ( p < .05). Overall, both 2 H and 13 C isotopic signatures of odd n ‐alkanes exhibited differences between natural and reconstructed soils. However, within the reconstructed soils, neither isotopic signature showed a clear evolution with age since reclamation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".