Millennial stocks and fluxes of large woody debris in lakes of the <scp>N</scp>orth <scp>A</scp>merican taiga
Bibliographic record
Abstract
Summary Large woody debris (LWD) is an important cross‐boundary subsidy that enhances the productivity of lake ecosystems and the stability of aquatic food webs. LWD may also be an important carbon sink because LWD pieces are preserved for centuries in the littoral zone of lakes and rivers. However, a long‐term analysis of LWD stocks and fluxes in lakes, coupled with the reconstruction of past disturbances at the site level, has never been attempted. Large woody debris was sampled in five lakes of the Quebec taiga. Actual LWD stocks were described and residence time of the LWD pieces was established using tree‐ring and radiocarbon dating. LWD losses by decomposition and burial and other factors influencing LWD residence time were investigated using linear regressions. Impacts of wildfires on LWD fluxes during the last 1400 years were reconstructed separately for the five lakes using piecewise regression models. Fire years at each site were identified from the recruitment dates of charred LWD pieces. Large woody debris volume ranged between 0.92 and 1.57 m3 per 100 m of shoreline, and extrapolating these results to the landscape scale, it was concluded that LWD littoral carbon pools represent a minimal portion of boreal carbon storage. Large woody debris residence time in boreal lakes was confirmed to be very long. Tree‐ring dates of 1571 LWD pieces, mainly black spruce (Picea mariana (Mill.) BSP.), spanned the last 1400 years, while LWD specimens of older floating chronologies were preserved from decomposition for up to five millennia. The most influential variables explaining the variation in LWD residence time were the degree of burial and the distance from the shore. Large woody debris recruitment rates averaged 5.8 pieces per century per 100 m of shoreline. Fourteen wildfires were the primary cause for changes in the rates of tree establishment in the riparian forests and of LWD recruitment in the lakes. Synthesis. Interactions between terrestrial and aquatic ecosystems in northern boreal regions are strongly influenced by wildfires whose effects can last for centuries due to the slow large woody debris decay rate. Actual LWD stocks and carbon pools are a legacy of the past fire history.
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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".