TREE STORIES ABOUT A PEATLAND: TREE-RING RECONSTRUCTIONS OF WATER TABLE AND LARCH SAWFLY OUTBREAKS IN SASKATCHEWAN
Bibliographic record
Abstract
Eastern larch (Larix laricina) and black spruce (Picea mariana) are the most dominant tree species in peatlands in Canada, however interactions between peatland hydrology and species-specific radial growth are poorly understood. This study investigates the relationships between the growth/hydrological response of eastern larch and black spruce across a topographical gradient within a peatland in Saskatchewan. Tree-ring analysis revealed that peatland hydrology is the main factor driving radial-tree growth. Black spruce on the edge of the fen showed a positive relationship to increased water-table level, while eastern larch in the fen revealed a negative correlation to water-table level rise. Further analysis illustrated that radial-tree growth response to hydrology is dependent on specific water-table levels according to species and micro-site. Identified thresholds indicated that only 8 cm of variability in water-table level can greatly affect the fen forest dynamics. Once the relationship between tree ring and hydrology was established, a multiple- species regression equation was derived from tree-ring data to reconstruct past water-table levels. Results indicated that eastern larch and black spruce are suitable proxies to reconstruct hydrological variability at the site. Eastern larch ring widths are not only subjected to change by hydrology, but they can also be altered by exposure to larch sawfly outbreaks (Pristiphora erichsonii). Researchers have often been limited in their ability to draw accurate conclusions regarding the history of sawfly outbreaks in peatlands. Water-table level suppressions result in similar radial-growth patterns as when trees are defoliated by larch sawfly, making accurate diagnoses of larch sawfly outbreak a challenge. In this study I investigated the relationship between sawfly outbreaks and peatland hydrology. Five outbreaks where identified using traditional dendroecological analysis. The last outbreak identified was found to be a result of hydrological growth suppression and not sawfly defoliation. Observations indicated that periods of low water-table level may lead to increased populations of larch sawfly in northern Saskatchewan. I stress the necessity of using long-term hydrological analyses to accurately infer outbreak periods to distinguish them from water-table suppression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".