Long‐term patterns in Iberian hare population dynamics in a protected area (Doñana National Park) in the southwestern Iberian Peninsula: Effects of weather conditions and plant cover
Bibliographic record
Abstract
The Iberian hare (Lepus granatensis) is a widely distributed endemic species in the Iberian Peninsula. To improve our knowledge of its population dynamics, the relative abundance and population trends of the Iberian hare were studied in the autumns of 1995-2012 in a protected area (Doñana National Park) by spotlighting in 2 different habitats: marshland and ecotones. The average relative abundance was 0.38 hare/km (SD = 0.63) in the marshland and 3.6 hares/km (SD = 4.09) in ecotones. The Iberian hare population exhibited local interannual fluctuations and a negative population trend during the study period (1995-2012). The results suggest that its populations are in decline. The flooding of parts of the marshland in June, July and October favor hare abundance in the ecotone. Hare abundance in the marshland increases as the flooded surface area increases in October. These effects are more pronounced if the rains are early (October) and partially flood the marsh. By contrast, when marsh grasses and graminoids are very high and thick (as measured using the aerial herbaceous biomass [biomass marshland] as a proxy), the abundance of hares decreases dramatically as does the area of the marsh that is flooded (in November).
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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 | 0.001 | 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".