Insect seed and cone predation reduces reproductive potential of treeline conifers across northern Canada
Bibliographic record
Abstract
Abstract Aim: Altitudinal and latitudinal treeline ecotones have not consistently responded to climate warming the in direction and/or magnitude as predicted by climate alone, suggesting that non-climatic mechanisms (e.g., biotic interactions) are also mediating treeline range dynamics. Through a collaborative research approach, we assessed environmental conditions associated with insect cone granivory and how this biotic interaction may govern the reproductive potential, and therefore range dynamics, of spruce-dominated treelines across northern Canada. Location: Ten boreal forest treelines, tundra and alpine, from Yukon to Newfoundland and Labrador, Canada Taxa: White spruce (Picea glauca (Moench) Voss), Black spruce (Picea mariana (Mill.) B.S.P.), Strobilomyia spp., Megastigmus spp. Methods: Treeline sites were assessed for presence and magnitude of pre-seed dispersal granivory by insects, and viability of available seed was determined. We quantified stand density metrics, organic layer depth, and understory vegetation composition at each location and, subsequently, incorporated those variables into generalized linear mixed models to establish predictors of granivory magnitude and viability of available seed. Results: Our findings reveal the widespread presence of insect granivory across sites, however, site-specific patterns of granivory were associated with increased moss cover and decreased shrub cover and stand density. While all black-spruce-dominated sites exhibited seed viability rates greater than 50%, the number of seeds produced per cone varied, suggesting that within-site abiotic conditions and biotic interaction pressures limit successful colonization of novel environments in advance of seed dispersal. Main Conclusions: Results from the modelled relationships between cone granivory, seed viability, and environmental conditions represent an essential step toward generalizing how and when biotic interactions across subarctic treelines influence boreal tree range dynamics before seed dispersal. Connections between granivory magnitude and site-level stand density will help establish how treeline form (e.g., discrete or diffuse) may drive patterns of future insect outbreaks under continued climate warming.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".