Foraging benefits and limited niche overlap promote a mixed species association between two solitary species of spider
Bibliographic record
Abstract
Mixed species associations are of general importance because of the diversity of ecological relations they can represent (e.g., mutualisms, commensalisms, exploitative relationships). We test for a non-random association between two normally solitary species of spider, the black widow ( Latrodectus mactans ) and the orchard spider ( Leucage venusta ). We use field observations comparing solitary and associated individuals of both species to elucidate what effect the association has on prey capture. We then evaluate what influence the association has on prey consumption, as inferred from change in body mass after a reciprocal removal experiment. From our field census we confirm that these species associate non-randomly in wild populations; furthermore, we failed to detect a difference in the number or kinds of prey which hit solitary and associated webs of either species, suggesting the association is not merely an aggregation to microhabitats which afford higher prey availability. Our observational data on prey capture indicate the association serves to increase the capture efficiency of Le. venusta , in part through ricocheted prey, but we failed to detect a prey capture effect for La. mactans . The results of our reciprocal removal experiment suggest the relationship is a commensalism: benefiting Le. venusta and leaving La. mactans unaffected.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".