Geographic variation in resin canal defenses in seedlings from the Sitka spruce × white spruce introgression zone
Bibliographic record
Abstract
Seedlings from 18 provenances along a coast-interior transect in the Picea sitchensis (Bong.) Carrière × Picea glauca (Moench) Voss introgression zone in northwestern British Columbia were mechanically wounded at the beginning of their third growing season to simulate natural attack by the white pine weevil, Pissodes strobi (Peck). Constitutive resin canals (CRC) in the cortex and traumatic resin canals (TRC) in the xylem of terminal shoots were characterized microscopically 4 months after wounding. Wounding resulted in a large increase in CRC size and in TRC number and density. Provenances differed significantly in TRC number and in CRC number, size, total area, and the proportion of total bark area occupied by CRC. CRC number and size, TRC number, and provenance weevil resistance (obtained from previously published data) increased with increasing latitude, elevation, and distance from the Pacific Ocean (i.e., towards the P. glauca end of the introgression zone) and decreased with increasing longitude (i.e., towards P. sitchensis). These traits also increased with aridity and continentality and decreased with most temperature, precipitation, and growing season length variables. Statistically significant multiple regression models related variation in some resin canal traits to geographic (r 2 = 0.71) and climatic (r 2 = 0.62) variables. Provenance mean values for weevil resistance were positively associated with predicted values for TRC number and CRC size. These results indicate that it is possible to predict locations in the introgression zone containing trees that possess desirable resin canal traits using geographic or climatic variables.
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 | 0.002 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".