Microhabitat selection in the potentially endangered wolf spider Donacosa merlini (Araneae, Lycosidae): implications for spider conservation
Bibliographic record
Abstract
Habitat quality affects many components of animal fitness and animals are expected to be distributed in the space accordingly. Mismatch between habitat preferences and fitness may relate to scale-dependent effects and trade-offs between costs and benefits of moving to high-quality habitats. We investigated the effects of habitat quality and habitat selection in Donacosa merlini Alderweireldt and Jocqué, 1991, a burrowing wolf spider included in the Spanish Invertebrates Red Data Book. Particularly, we compared burrow size and density and analysed the relationship between burrow presence and vegetation at two different scales. At a regional scale, we found strong differences in burrow size and density. Burrow density affected burrow aggregation, which was utmost under mean densities. At both spatial scales, burrows were found at relatively clear (or low-covered) patches, as scrubs were lower and nearest vegetation was farther from burrows than randomly expected. Our results suggest habitat selection and effects of habitat quality on the life history of D. merlini. In spite of the recent expansion of the species distribution area, our data support the need for suitable habitat management programs. Information about ecological requirements is paramount to correctly assess spider conservation status. This topic has received little attention in spite of the diversity and the relevance of spider ecological roles.
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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".