Dangerous life at the edge: Implications of seed predation for roadside revegetation
Bibliographic record
Abstract
Abstract Question Anthropogenic edges caused by transport infrastructure such as dirt roads and trails (also known as Soft Linear Developments; SLD) are pervasive in almost every terrestrial ecosystem. Revegetating these edges may reduce some of their negative effects, such as their permeability to biological invasions and detrimental effects on wildlife, potentially becoming suitable habitat for a broad range of species. Selecting species with low post‐dispersal seed predation rates may improve the effectiveness of revegetation programmes. Location Mediterranean scrublands in SW Spain. Methods We made offerings of a total of 16,000 seeds of eight species of fleshy‐fruit shrubs both along SLD edges and scrubland interiors in two independent blocks in each of three distant locations. Using four types of selective enclosure, we assessed the relative contribution of three seed predator guilds (ants, rodents and birds) to seed predation rates both along SLD edges and scrubland interiors. Results The effects of anthropogenic edges on seed predation rates were species‐specific. The large and hard‐seeded species Chamaerops humilis was not predated at all. Juniperus phoenicea and Corema album seeds had higher predation rates in scrubland interiors than in edges. The small‐seeded Rubus ulmifolius experienced relatively low seed predation rates compared to the other species. Predation rates for this species were higher along SLD edges than in scrubland interiors. Ants were the main seed predators in the area, and showed marked preferences for J. macrocarpa and C. album seeds at both SLD edges and scrubland interiors. Conclusions Our results show the strong context‐dependency of seed predation rates in both SLD edges and scrubland interiors, and thus the importance of well spatially and temporally replicated studies. Species with large and hard seeds may be good candidates for roadside revegetation programmes. However, the relative suitability of plant species would depend on the seed predator community. Our findings confirm that studies on seed predation may help planning cost‐effective species selection for edge revegetation efforts worldwide.
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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) | 0.003 | 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".