Conflicting selection from fire and seed predation drives fine-scaled phenotypic variation in a widespread North American conifer
Bibliographic record
Abstract
Recent work has demonstrated that evolutionary processes shape ecological dynamics on relatively short timescales (eco-evolutionary dynamics), but demonstrating these effects at large spatial scales in natural landscapes has proven difficult. We used empirical studies and modeling to investigate how selective pressures from fire and predispersal seed predation affect the evolution of serotiny, an ecologically important trait. Serotiny is a highly heritable key reproductive trait in Rocky Mountain lodgepole pine (Pinus contorta subsp. latifolia), a conifer that dominates millions of hectares in western North America. In these forests, the frequency of serotiny determines postfire seedling density with corresponding community- and ecosystem-level effects. We found that serotinous individuals have a selective advantage at high fire frequencies and low predation pressure; however, very high seed predation shifted the selective advantage to nonserotinous individuals even at high fire frequencies. Simulation modeling suggests that spatial variation in the frequency of serotiny results from heterogeneity in these two selective agents. These results, combined with previous findings showing a negative association between the density of seed predators and the frequency of serotiny at both landscape and continental scales, demonstrate that contemporary patterns in serotiny reflect an evolutionary response to conflicting selection pressures from fire and seed predation. Thus, we show that variation in the frequency of a heritable polygenic trait depends on spatial variation in two dominant selective agents, and, importantly, the effects of the local trait variation propagate with profound consequences to the structure and function of communities and ecosystems across a large landscape.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".