Facilitation strength across environmental and beneficiary trait gradients in stream communities
Bibliographic record
Abstract
Ecosystem engineers modify habitats in ways that facilitate other community members by ameliorating harsh conditions. The strength of such facilitation is predicted to be influenced by both beneficiary traits and abiotic context. One key trait of animals that could control the strength of facilitation is beneficiary body size because it should determine how beneficiaries fit within and exploit stress ameliorating habitat modifications. However, few studies have measured how beneficiary body size relates to facilitation strength along environmental gradients. We examined how the strength of facilitation by net-spinning caddisflies on invertebrate communities in streams varied along an elevation gradient and based on traits of the invertebrate beneficiaries. We measured whether use of silk retreats as habitat concentrated invertebrate density and biomass compared to surrounding rock surface habitat and whether the use of retreat habitat varied across body sizes of community members along the gradient. We found that retreats substantially concentrated the densities of a diversity of taxa including eight different Orders, and this effect was greatest at high elevations. Caddisfly retreats also concentrated invertebrate biomass more as elevation increased. Body size of invertebrates inhabiting retreats was lower than that of surrounding rock habitats at low elevation sites, however, body size between retreats and rocks converged at higher elevation sites. Additionally, the body size of invertebrates found in retreats varied within and across taxa. Specifically, caddisfly retreats functioned as a potential nursery for taxa with large maximal body sizes. However, the patterns of this taxon-specific nursery effect were not influenced by elevation unlike the patterns observed based on community-level body size. Collectively, our results indicate that invertebrates use retreats in earlier life stages or when they are smaller in body size independent of life stage. Furthermore, our analysis suggests that facilitation strength intensifies as elevation increases within stream invertebrate communities. Further consideration of how trait variation and environmental gradients interact to determine the strength and direction of biotic interactions will be important as species ranges and environmental conditions continue to shift.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".