Response of the Nitrogen Isotopic Composition of Tree-Rings Following Tree-Clearing and Land-Use Change
Bibliographic record
Abstract
Clear-cutting of forests affects the nitrogen cycle and the nitrogen isotopic composition of bioavailable ammonium and nitrate in the soil. Here, we have used nitrogen isotopic variations of tree-rings in red oak (Quercus rubra) and white oak (Quercus alba) as indicators of changes in the nitrogen cycle on a local scale. The delta15N values of late-wood from trees at two remnant forest stands in Ontario, Canada, that underwent large-scale tree-clearing and permanent land-use change at different times were measured. Trees from the perimeter of each stand record a marked 1.5-2.5 per thousand increase in the delta15N values of their tree-rings relative to the values in trees from the center of the stand, with the shift synchronous with the tree-clearing and land-use change. This shift was most likely due to increased rates of nitrification and nitrate leaching in the soil as a result of tree-clearing combined with permanent changes in hydrology and probable fertilizer use accompanying the change in land-use. Nitrogen concentration in tree-rings was not affected bytree-clearing and the associated change in land-use. These results indicate that changes in nitrogen cycling in forest ecosystems, whether due to climate change, land-use change, or other environmental changes (increased O3, other atmospheric pollutants, insects, etc.), can be faithfully monitored with nitrogen isotopic compositions of tree-rings and that dendrogeochemical analysis can be incorporated into studies of the effects of long-term anthropogenic effects on forest ecosystems.
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 | 0.000 | 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 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".