Resiliency in masting systems: Do evolved seed escape strategies benefit an endangered pine?
Bibliographic record
Abstract
Abstract Satiation of predispersal seed predators by mast years has been demonstrated in many intact ecosystems. When disease causes mortality of seed‐bearing trees in an ecosystem, the abundance of food sources may alter seed predator behavior and abundance, and the ecosystem services derived from mutualistic seed dispersers. We used the endangered limber pine (Pinus flexilis) to examine whether the benefits of interannual variation in cone production vary depending on the severity of white pine blister rust (Cronartium ribicola) infections, the abundance of seed predator populations, and stand characteristics. We compared infection level, cone production, cone predation, and abundance of red squirrels (Tamiasciurus hudsonicus) in 17 stands over two mast years and two nonmast years. Stands were selected from a southern and northern ecosystem within Alberta's montane ecoregion, with varying forest composition and history of blister rust infection. Considerable variability in interannual cone production, and proportionately greater cone escape (those remaining in stands) in the 2010 mast year led to 10 times greater cone escape overall in the mast year than in nonmast years. Model selection using Akaike's information criterion (AIC) suggests that both cone escape and proportion cone escape from seed predators depended primarily on temporal variability in cone production among mast vs. nonmast years, basal area of canopy trees within stands, squirrel abundance, and ecosystem differences. Several two‐way and three‐way interactions between masting, ecosystems, and predator abundance were selected by AIC for inclusion into the best model of the a priori candidate set for both the cone escape model and proportion cone escape model. Our study suggests that masting confers temporal resiliency in seed escape in declining limber pine ecosystems, even under varying disease and seed predator threats. These findings also suggest that evolved seed escape strategies may be resilient to a variety of ecological conditions, including low reproductive capacity. Nonetheless, proximate ecological conditions may determine the fate of declining species, as predator behavior differed between ecosystems, and greater net cone escape in favorable stands may be necessary to attract mutualistic seed dispersers.
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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 | 0.000 |
| 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".