The role of native riparian tree species in decomposition of invasive tree of heaven (Ailanthus altissima) leaf litter in an urban stream
Bibliographic record
Abstract
Abstract Increasingly, interactions between human and natural systems centre on the multi-scale restoration of ecosystems. Humans rely on ecosystem services provided by streams, yet human activities degrade water quality worldwide. Replanting streamside vegetation is a common restoration practice, since trees reduce runoff and stabilize banks. But does riparian tree biodiversity matter? Detrital inputs from riparian vegetation impact in-stream processes, e.g., leaf decomposition. Since the increasing distribution of invasive plant species alters the structure of streamside forest communities, input of invasive litter to streams could alter such processes. We followed decomposition rates of the invasive tree of heaven (Ailanthus altissima, TOH) and 6 native leaf species in an urban stream and complemented this effort with laboratory feeding experiments employing the same treatments and 2 common aquatic detritivores. TOH breakdown was rapid, exceeding native leaf decay. Mixing TOH with native species reduce...
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".