SPATIAL PATTERNS OF BENTHIC INVERTEBRATES IN REGULATED AND NATURAL RIVERS
Bibliographic record
Abstract
ABSTRACT Daily fluctuating flows in regulated rivers can lead to extensive areas of substrate that experience drying and wetting. I investigated the longitudinal and lateral patterns of benthic invertebrates in the regulated peaking Magpie River and neighbouring natural rivers. Nearly half of all invertebrates collected in the Magpie River originated from the upstream reservoir. Both lentic and lotic invertebrates, however, decreased in abundance to natural levels 5–8 km downstream. Closest to the dam, lotic invertebrates were twice as abundant as those found in natural rivers. In natural rivers Diptera, Ephemeroptera, Coleoptera and Trichoptera were more common in the shallow and slower areas along transects. The opposite was true in the regulated Magpie where densities increased with water depth and velocity, particularly for the dominant groups Diptera and Trichoptera. The abundance of worm‐like organisms (e.g. Enchytraeidae, Lumbricidae, Naididae) and snails (Basommatophora) increased considerably in the varial zone. There were 10 times more Odonata and Plecoptera in the natural rivers, but lateral trends were not evident in either type of river. The influence of sampling location along transects on the interpretation of the community composition can be clearly seen in a resampling of the data. This study illustrates the presence of longitudinal and lateral gradients, and this knowledge needs to be incorporated into the design of research or monitoring programmes. Failing to do so could jeopardize decisions with the management of our flowing waters. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".