Spiders and subsidies: results from the riparian zone of a coastal temperate rainforest
Bibliographic record
Abstract
1. Aquatic insects emerging from streams can provide an important energy subsidy to recipient consumers such as riparian web-building spiders. This subsidy has been hypothesized to be of little importance where the primary productivity of the recipient habitat exceeds that of the donor habitat. 2. To test this hypothesis, we manipulated emerging stream insect abundance in a productive riparian rainforest in a replicated design using greenhouse-type exclosures, contrasted with unmanipulated stream reaches (four exclosures on two streams). 3. Experimental exclosures resulted in a 62.9% decrease in aquatic insect abundance in exclusion reaches compared with control reaches. The overall density of riparian spiders was significantly positively correlated with aquatic insect abundances. Horizontal orb weavers (Tetragnathidae) showed a strong response to aquatic insect reduction - abundance at exclosure sites was 57% lower than at control sites. Several spider families that have not been associated with tracking aquatic insect subsidies also showed significantly decreased abundance when aquatic insects were reduced. 4. This result is contrary to predictions of weak subsidy effects where recipient net primary productivity is high. These results suggest that predicting the importance of resource subsidies for food webs requires a focus on the relative abundance of subsidy materials in recipient and donor habitats and not simply on the total flux of energy between systems.
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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 | 0.000 | 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".