Insects can limit seed productivity at the treeline
Bibliographic record
Abstract
Numerous factors contribute to the variability in treeline change; however, the potential role of insect predation in limiting seed productivity is not well documented. Conditions for seed germination, establishment, and survival are not limiting at the Mealy Mountains treeline (Labrador, Canada), but seedlings are rarely encountered, suggesting a seed-related bottleneck to recruitment. Mature cones were collected in 2008 from four tree species (black spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.), balsam fir (Abies balsamea (L.) Mill.), eastern larch (Larix laricina (Du Roi) K. Koch), and white spruce (Picea glauca (Moench) Voss)) across three treeline zones (forest, transition, and krummholz) to assess potential seed limitation. During that year, an unexpectedly high diversity of insect larvae caused extensive reproductive loss and damaged the cones of ∼85% of trees sampled, confirming that treeline change models should include seed predation. Seed germination was low and variable in all treeline zones, although significantly higher in black spruce and eastern larch. Most reproductive quality measures decreased significantly with elevation, although no differences among zones or tree species in the percentages of seeds damaged by insects were found (mean ± standard deviation: 31% ± 23%). Based on tree density and seed production, black spruce is predicted to lead the treeline expansion in the Mealy Mountains. Although climate warming may create conditions conducive for increased seed production, predispersal seed predation may limit future treeline expansion.
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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 | 0.000 | 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) | 0.001 | 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".