Leaf quality influences invertebrate colonization and drift in a temperate rainforest stream
Bibliographic record
Abstract
Changes in riparian forest composition and diversity, such as plantations of exotic species, may alter resource quality, detritivore assemblages, and litter breakdown rates in streams. We hypothesized that different litter resources may influence colonization and drift of invertebrates inhabiting small, temperate rainforest streams in southwestern British Columbia, Canada. Leaves of different quality and origin were incubated in stream-side channels to test this hypothesis. The sequence of leaf decomposition rates was as follows: alder > alder + cedar > cedar ≥ eucalyptus. Cedar litter decayed faster when mixed with alder than when alone. Invertebrates colonizing leaf bags were predominantly collector–gatherers and shredders, particularly on alder leaves. Drift density varied over the incubation period and seemed to be controlled by leaf quality, since there were more individuals drifting from channels with alder leaves than from channels with cedar or eucalyptus. However, we observed different species-specific invertebrate responses controlled by leaf traits, particularly by numerically dominant chironomid species. Indeed, invertebrate drift from channels incubated with alder bags was mostly due to pupation and emergence of orthoclad midges, whereas this was not observed in the other channels. This differential response in colonization and drift has the potential to modify the transfer rates of organic matter to higher trophic levels and thus ecosystem functioning.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".