Directed dispersal by rotational shepherding supports landscape genetic connectivity in a calcareous grassland plant
Bibliographic record
Abstract
Directed dispersal by animal vectors has been found to have large effects on the structure and dynamics of plant populations adapted to frugivory. Yet, empirical data are lacking on the potential of directed dispersal by rotational grazing of domestic animals to mediate gene flow across the landscape. Here, we investigated the potential effect of large-flock shepherding on landscape-scale genetic structure in the calcareous grassland plant Dianthus carthusianorum, whose seeds lack morphological adaptations to dispersal to animals or wind. We found a significant pattern of genetic structure differentiating population within grazed patches of three nonoverlapping shepherding systems and populations of ungrazed patches. Among ungrazed patches, we found a strong and significant effect of isolation by distance (r = 0.56). In contrast, genetic distance between grazed patches within the same herding system was unrelated to geographical distance but significantly related to distance along shepherding routes (r = 0.44). This latter effect of connectivity along shepherding routes suggests that gene flow is spatially restricted occurring mostly between adjacent populations. While this study used nuclear markers that integrate gene flow by pollen and seed, the significant difference in the genetic structure between ungrazed patches and patches connected by large-flock shepherding indicates the potential of directed seed dispersal by sheep across the landscape.
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 | 0.000 | 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 | 0.000 | 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".