Smaller species experience mild adversity under shading in an old-field plant community
Bibliographic record
Abstract
Plant competition experiments commonly suggest that larger species have an advantage, especially in light acquisition. However, within crowded natural vegetation, where competition evidently impacts fitness, most resident species are relatively small. It remains unclear, therefore, whether the size-advantage observed in controlled experiments is realized in habitats under intensive competition. We tested for evidence of a size-advantage in competition for light in an old-field plant community composed of herbaceous perennial species. We investigated whether larger species contributed to reduced light penetration (i.e., greater shading), and examined the impact of shade on smaller species by testing whether their abundance and richness were lower in plots with less light penetration. Light penetration in plots ranged from 0.3-72.4%. Plots with greater mean species height had significantly lower light penetration. Plots with lower light penetration had significantly lower small species abundance and richness. However, the impact of shade on small species abundance and richness was relatively small (R 2 values between 8% and 15%) and depended on how we defined “small species”. Significant effects were more common when analyses focused on individuals that reached reproduction; focusing on only flowering plants can clarify patterns. Our results confirm that light penetration in herbaceous vegetation can be comparable to levels seen in forests, that plots with taller species cast more shade, and that smaller species are less abundant and diverse in plots where light penetration is low. However, variation in mean plot height explained less than 10% of variation in light penetration, and light penetration explained 5-15% of variation in small species abundance and richness. Coupled with the fact that reproductive small species were present even within the most heavily shaded plots, our results suggest that any advantage in light competition by large species is limited. One explanation is that some small species in these communities are shade tolerant.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".