Evaluating the influence of different aspects of habitat fragmentation on mating patterns and pollen dispersal in the bird‐pollinated<i>Banksia sphaerocarpa</i>var.<i>caesia</i>
Bibliographic record
Abstract
Habitat fragmentation can significantly affect mating and pollen dispersal patterns in plant populations, although the differential effects of the various aspects of fragmentation are poorly understood. In this study, we used eight microsatellite loci to investigate the effect of fragmentation on the mating system and pollen dispersal within one large and eight small population remnants of Banksia sphaerocarpa var. caesia, a bird-pollinated shrub in the southern agricultural region of Western Australia. The large population had a much larger neighbourhood size and lower selfing rate, maternal pollen pool differentiation and within-plot mean pollen dispersal distance than the small populations. Outcrossing was consistently high and ranged from 85.7% ± 2.6 to 98.5% ± 0.9, and mating patterns suggested nearest-neighbour pollination. Pollen immigration into small populations ranged from 2.8% ± 1.8 to 16.5% ± 3.2. Using the small populations, we tested for correlations between various fragmentation variables and mating system and pollen dispersal parameters. We found significant negative linear relationships between population isolation and outcrossing rate; population shape and neighbourhood size; and conspecific density and mean pollen dispersal distance. There were significant positive linear relationships between population shape and pollen pool differentiation and between population size and number of different fathers per seed crop. Our results suggest that birds may use a series of fragmented populations as a vegetation corridor while foraging across the landscape and that population connectivity is a critical determinant of pollinator visitation. Our results also suggest that the effect of a linear population shape on the mating system and pollen dispersal is routinely underestimated.
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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) | 0.000 | 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 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".