Rain, predators and vegetation lushness may structure web‐building spider communities along precipitation gradients
Bibliographic record
Abstract
1. Web building spider communities represent a vehicle for addressing how abiotic and biotic factors interact to structure natural communities. 2. The present study investigates how intense rainfall and potential predation by ants affect the proportion of three‐dimensional (3D) versus two‐dimensional (2D) spider webs along precipitation gradients. 3. Besides capturing prey, 3D webs may provide protection against predators, but they require a much greater material investment to be built than 2D webs. If costs take precedence over predator protection benefits, the proportion of 3D webs would decrease as precipitation increases (the ‘rain intensity’ hypothesis). Alternatively, if predator protection benefits take precedence, and the abundance of ants and other predators increases with precipitation, the proportion of 3D webs would increase with precipitation (the ‘predation risk’ hypothesis). 4. Seven sites were selected along a rain gradient of relatively uniform elevation and latitude in western Ecuador. Rain intensity, ant abundance and vegetation lushness (leaf area, canopy cover, tree diameter) were all observed to increase along the gradient, as did vegetation cover immediately above each web. 5. Relative to 2D webs, 3D webs increased in frequency with annual rainfall, consistent with the predation risk hypothesis but counter to the rain intensity hypothesis. 6. In areas of greater precipitation, however, lusher vegetation provided greater immediate vegetation cover to webs. Microhabitat factors may thus mitigate the destructive power of intense rainfall, thus allowing the predator protection benefits of 3D webs to be realised despite the occurrence of strong rains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".