Population structure effect on reproduction of a rare plant: beyond population size effect
Bibliographic record
Abstract
Several studies have evaluated the effect of population size on plant reproductive output, but there are few studies concerning the effect of other population structure variables on plant reproduction. In this study, we went beyond population size effect and we tested the effect of some population spatial variables such as plant density, plant aggregation, population structure, and population identity on plant reproductive success and fitness in large populations (>1000 individuals) of Centaurea hyssopifolia Vahl., an endemic species of central Spain. We analysed the reproductive output (capitula, flowers, and seeds) and another two components of plant fitness (seed mass and germinability) in 350 individuals from seven populations in 2002 and 2003. All populations were similar in size but differed in other population spatial characteristics (density, plant aggregation pattern, population plant size structure). We used Morisita’s aggregation index to characterize the level of plant aggregation within populations. Population plant size structure variable determined the proportion of different sized plants in a population. We used generalized linear mixed models to model the contribution of these population spatial variables to several reproductive parameters. Our results showed that whereas the aggregation index exerted a positive control on plant seed set, plant density had a negative effect, and plant population size structure did not significantly influence any response variable. Density only exerted a negative effect on seed set. On the contrary, plant aggregation had a positive effect. Seed mass was also larger in more aggregated populations, although no differences in seed germinability were observed. We detected the effect of population attributes on reproduction in terms of seed set, but we did not detect any effect on other overall reproductive variables measured at plant level. To sum up, our results showed that if population fragments were large enough, spatial population attributes became crucial factors for plant reproductive output and fitness. These easily measurable population variables may improve the conservation management of rare plant species.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".