Data from: Decay patterns of invasive plants and plastic trash in urban streams
Bibliographic record
Abstract
Urban streams are impacted by invasion of exotic riparian plants and the accumulation of plastic trash, which alter in-stream litter subsidies, and cause changes that cascade up the aquatic food web. The impacts of these factors on urban streams is poorly understood. We compared decay rates and invertebrate colonizers of 5 litter pack types in 4 urban streams in Victoria, British Columbia, Canada: Native Red alder (Alnus rubra) and Sitka willow (Salix sitchensis), invasive English ivy (Hedera sp.), Himalayan blackberry (Rubus armeniacus) and plastic trash (i.e. Styrofoam (polystyrene (PS)), plastic bag (high-density polyethylene (HDPE)), and Mylar (polyethylene terephthalate (PET). We tested 4 hypotheses: 1) exotic ivy and blackberry leaves would decay more slowly than native leaves; 2) exotic ivy and blackberry leaves would attract fewer and less diverse stream invertebrates than native leaves; 3) plastic trash would decay more slowly than leaves; and, 4) plastic trash would attract fewer and less diverse stream invertebrates than leaves. We found no difference between the leaf litter decay rates, however plastic trash decayed more slowly than leaves. Trash decay rates were faster than reported in marine environments, suggesting that plastic trash removal should be a management priority. Stream invertebrates colonized all pack types equally. We observed significant differences in litter decay rates and invertebrate assemblage alpha and Shannon–Wiener diversities across the 4 streams - likely related to differences in stream-specific environmental attributes including flashiness, stream discharge, and biological decay. We conclude that site-specific decay forces supersede litter quality in Pacific Coast urban streams.
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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 | 0.002 |
| 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) | 0.003 | 0.001 |
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".