Spinning in the rain: Interactions between spider web morphology and microhabitat use
Bibliographic record
Abstract
Abstract Although the effects of abiotic factors on species distributions and habitat selection have been widely investigated, studies have rarely succeeded at identifying the factors behind selection at the microhabitat level. Spider webs are extended phenotypes expected to be subject to fitness trade‐offs. We tested the hypothesis that spiders with three‐dimensional webs (tangle and sheet‐and‐tangle), which require more material to be built than two‐dimensional orbicular webs, occupy microhabitats where they are better protected from strong rains. We show that tangle and sheet‐and‐tangle webs were indeed significantly more likely to be under immediate cover than expected by chance and than orb webs. Tangle webs occurred closest to the cover and were largely protected, whereas sheet‐and‐tangle webs, likely due to their larger size and mostly horizontal position, tended to be more exposed. Sheet‐and‐tangle webs, however, occurred more often against tree trunks, where we show rain to be less intense. We further show that the proportion of 3D webs under immediate cover increased with annual precipitation along a dry to wet gradient in western Ecuador, an effect absent for 2D webs. The latter finding suggests that, in addition to using leaves for structural support, spiders with 3D webs seek microhabitat locations to shelter themselves and their webs from strong rains. Our findings illustrate how microhabitat selection may allow organisms to cope with abiotic factors at broader geographical scales, thus influencing organismal fitness and community structure. Abstract in Spanish is available with online only
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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 | 0.003 |
| 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) | 0.003 | 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".