Conditional effects of aquatic insects of small tributaries on mainstream assemblages: position within drainage network matters
Bibliographic record
Abstract
Tributaries may affect fauna in a mainstream by changing bottom substrate and increasing spatial heterogeneity. Additionally, we hypothesized that fauna in the mainstream may be affected by drifting migrants from tributaries. In nine stream networks, we sampled a similar microhabitat immediately upstream and downstream of two confluences. In each network, one confluence was located in the network centre and one in the periphery, and they were distinguished by low and high ratios of tributary size, respectively. We assessed whether the aquatic fauna at sites downstream from confluences was species-richer, distinct in composition and structure, and whether it included the fauna of upstream sites. We found that richness, rarefied richness, and abundance at downstream sites were not higher than at their upstream counterparts. Faunas at downstream sites were not nested subsets of those at upstream sites. Macroinvertebrate assemblage composition and structure differed between downstream and upstream sites in the peripheral confluences (high tributary to mainstream (T:M) ratios), but not in central confluences (low T:M ratios). Thus, effects of small tributaries on receiving mainstreams are dependent on the T:M ratio.
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 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".