Local and landscape habitat determinants of water vole distribution in a patchy Mediterranean environment
Bibliographic record
Abstract
We studied the distribution of a water-dependent species (southern water vole, Arvicola sapidus) in a Mediterranean region (Doñana National Park, southwest Spain) characterized by a complex array of different-sized ponds (where voles were confined) embedded in a mostly unsuitable landscape. For each surveyed pond (n = 185), a total of 26 variables related to both local (20) and landscape (6) attributes were quantified, and the presence of voles was evaluated by finding their typical signs (latrines). We found signs of water voles in 60% of ponds, despite the fact that most of them (84%) were totally dried out. A generalized linear model analysis showed that water voles were sensitive to both local and landscape attributes of ponds. At a landscape scale, presence of voles was more likely in ponds located outside the national park, close to other ponds holding voles, and far away from areas rich in potential predators and competitors. At a local scale, ponds with water voles were characterized by abundant grasses, banks well covered by brushes, low altitude, and low abundance of rabbits (Oryctolagus cuniculus). We also studied the use of microhabitat by voles within four specific ponds and found that they preferred plots of higher vegetation cover; thus, there was consistency in some cues used by water voles at the population/subpopulation scale (among different ponds) and at the behavioral scale (within ponds). Our study strongly supports the notion that the entire vole population is structured in distinct subpopulations, which are affected by a hierarchy of processes ranging from metapopulation dynamics and influenced by the landscape within which ponds are embedded as well as the local habitat quality.
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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 | 0.001 | 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) | 0.001 | 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".