Seed Availability Does Not Ensure Regeneration in Northern Ecosystems of the Endangered Limber Pine
Bibliographic record
Abstract
Research Highlights: When biotic interactions such as disease alter both the seed production capacity of stands, and seedling survivorship, the relative importance of seed availability versus substrate specificity may alter future regeneration opportunities for plant populations. Background and Objectives: We investigated the importance of disease severity, seed availability, and substrate limitation to the regeneration dynamics of the endangered limber pine, Pinus flexilis, in two ecosystems with varying forest composition, and different histories of white pine blister rust infection (WPBR; Cronartium ribicola). Materials and Methods: A total of 17 stands from the montane ecoregion (Alberta, Canada) were sampled for seed production between 2007–2010, seedling density, and age structure. Model selection using an information theoretic approach compared a series of a priori models and their combinations, based on our hypotheses on the role biotic variables play in the regeneration process. Results: Despite higher rates of WPBR infection, 2.3 times more seed was available for avian dispersers in the southern ecosystem. Recent seedling regeneration did not correspond to seed production (83 versus 251 seedlings/ha, in southern versus northern ecosystems, respectively), resulting in a seven-fold difference in seed to seedling ratios between ecosystems. Models suggest that disease and vegetation cover were important factors explaining the absence of regeneration in 79.4% of the plots sampled, while basal area (BA) of live limber pine, rocky substrates, ecosystem, South aspects, and slope enhanced limber pine regeneration. Seedling age structures suggest that recent regeneration is less likely in more diseased landscapes, than it was historically (40% versus 72.8% of seedlings < 20 years old, respectively, in southern versus northern ecosystems). Conclusions: At the northern limits of limber pine’s range, seed availability does not ensure regeneration, suggesting that other environmental or biotic factors hinder regeneration. Regeneration was consistently predicted to be lower in the southern ecosystem than in the northern ecosystem, suggesting that natural regeneration and the potential for population recovery are ecosystem dependent. We recommend that monitoring recent seedlings will aid the identification of biotic and abiotic factors affecting regeneration.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".