Long‐term C accumulation and total C stocks in boreal lakes in northern Québec
Bibliographic record
Abstract
Here we assess total sediment organic C stocks and long‐term C accumulation rates in 13 boreal lakes in northern Québec spanning a wide range of morphometric shapes. The lake basins were mapped using a sub‐bottom profiler to obtain total sediment volume, which we combined with organic carbon profiles from Holocene cores to obtain total C mass. The estimated long‐term areal C accumulation rates averaged 3.8 g C m −2 yr −1 , lower than previous reports for other boreal and temperate regions. The difference relative to previous studies may have resulted from our use of the detailed echosounding mapping approach, which yields more realistic estimates of total sediment volume. Total sediment C stocks were not related to lake trophic status or to DOC concentration, but rather to lake area and to the lake dynamic ratio (√lake area/mean water depth). We hypothesize that scaling of C accumulation to lake morphometry is more a reflection of the intrinsic capacity of lakes to retain carbon. We show that C loading does in fact play a significant role in the patterns of C accumulation in lakes, but that this role is strongly modulated by both lake size and shape, which in turn determine the ability of lakes to retain the carbon that has been loaded. Upscaling to the regional level using the empirical lake size relationships developed here results in an areal‐weighted average C stock of 23 kg C m −2 (per unit of lake area), or 3.8 kg m −2 (per unit landscape), which represents around 25% of the total landscape C storage in this boreal region. Because of the lake‐size scaling of C accumulation, the total lake C stocks at the regional level depend not only on the total lake area, but more importantly on the local lake size distribution.
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".