Trends in Quercus Macrocarpa Vessel Areas and their Implications for Tree-Ring Paleoflood Studies
Bibliographic record
Abstract
Changes in mean earlywood vessel areas in mature Quercus macrocarpa were analyzed to determine possible sources of bias in paleoflood records derived from anatomical tree-ring signatures. Tree-ring cores were collected at intervals along the vertical axis of four Q. macrocarpa in a flood-prone stand near the Red River in Manitoba. The WinCELL PRO image analysis system was used to measure mean vessel areas in each annual ring. Most cores displayed a pronounced juvenile increase in mean vessel area before stabilizing between 40 and 60 years. The lowest samples from several trees contain rings with anomalously small mean vessel areas that are coincident with high-magnitude Red River floods in 1950 and 1997. The anatomical response of Q. macrocarpa appears to be conditional on the relative timing of earlywood development and flooding. Flood signatures are most strongly developed near the tree base and become less evident up the trunk. Most signatures disappear between one and three meters in height. Differences in flood response between trees are likely caused by internal differences rather than hydrological or topographic factors. Paleoflood studies based on samples obtained exclusively at breast height may miss some anatomical flood signatures and underestimate flood frequency relative to earlier intervals.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".