Spatial patterns in lotic invertebrate community composition: is substrate disturbance actually important?
Bibliographic record
Abstract
Twenty-five forest streams were sampled in August 1994 in Te Urewera National Park, New Zealand, to examine the effect of substrate disturbance on invertebrate community structure. Stream size, flow permanence, and riparian cover were more influential than substrate disturbance in affecting invertebrate composition. Three community types were distinguishable based on these three factors: small (<1 m wide), intermittent streams were dominated by Chironomidae; larger (1215 m wide), open streams were dominated by Chironomidae, Plecoptera, and Ephemeroptera; and intermediate-sized (110 m wide) streams with continuous riparian cover were dominated by mayflies and caddisflies. Periphyton biomass was negatively affected by substrate disturbance but not to the same degree as reported by others studying unshaded streams. This may explain why the influence of substrate disturbance on community composition was less than that of stream size, flow permanence, and riparian cover. The key effect of substrate disturbance on postdisturbance community composition in these light-limited New Zealand streams appears to be the removal of animals rather than food loss. Thus, differences between communities that experience high flows and those that do not are far less than they might be in unshaded streams in which the food base is more severely affected by substrate disturbance.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".