Little owl ( <i>Athene noctua</i> ) pellets enhance seed germination under salinity stress in two leguminous plant species
Bibliographic record
Abstract
As central-place foragers, owls accumulate prey remains, in the form of rejection pellets, around their roosting and nesting sites, which may modify top soil composition and influence seed germination. However, the effects of owl pellets on seed germination still remain understudied. In this study, we conducted germination assays on two plant species from south Tunisia to assess whether a prior treatment of the seeds with the filtrate of little owl (Athene noctua) pellets affected germination rates under different salinity conditions. Results showed enhanced germination in pellet-treated seeds compared to untreated seeds. Pellet treatment was also associated with reduced inhibitory effects of salt on seed germination. Moreover, at the scale of a little owl territory, the concentrations of organic matter and total nitrogen in the top soil were higher at the nesting site compared to a nearby unused site, providing some evidence of a fertilizing effect of pellets. Overall, our findings suggest that little owls play a significant role in shaping plant dynamics and ecosystem functioning in arid North African areas, where the soil is poor and threatened by salinization. We suggest that little owls may be relevant actors in eventual restoration and rehabilitation plans of degraded ecosystems in these areas.
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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 | 0.000 |
| 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) | 0.001 | 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".