Rainfall events and downstream drift of microcrustacean zooplankton in a Newfoundland boreal stream
Bibliographic record
Abstract
While rainfall events may lead to flushing of zooplankton from lakes, with implications for stream productivity near lake outlets, consideration also needs to be given to zooplankton transported farther downstream. To evaluate such downstream transport, daytime invertebrate drift, stream discharge, and rainfall events were monitored over 4 summers in Cook's Brook, Newfoundland, at a downstream site 1.0 km below the outlet of Big Cook's Pond and an upstream site 1.0 km upstream of the pond. Microcrustacean zooplankton were abundant in some downstream samples; high percent zooplankton abundance (8794%) corresponded to the highest total invertebrate drift densities. Percent zooplankton in downstream drift was strongly correlated with recent rainfall (rS = 0.815, p = 0.025) and stream discharge (rS = 0.964, p = 0.001). The majority of microcrustaceans in the drift were planktonic cladocerans and copepods, the species composition being similar to that in Big Cook's Pond. No zooplankton were ever collected from the upstream site. Ephemeroptera, Diptera, Trichoptera, and Ostracoda were abundant in most drift samples. Zooplankton drift (mean = 0.17 individuals/m3) in Cook's Brook appears to be catastrophic drift, with high precipitation rates and resultant increased flushing rate in Big Cook's Pond leading to "washout" of microcrustaceans 1 km downstream.
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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 | 0.000 |
| 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 | 0.000 |
| 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".