Rapid in-stream decomposition of leaves of common buckthorn (<i>Rhamnus cathartica</i>), an invasive tree species
Bibliographic record
Abstract
Headwater streams derive a majority of their energy from allochthonous inputs; alteration of these inputs may lead to changes in stream communities and ecological function. Common buckthorn (Rhamnus cathartica) is invasive over much of the northern United States and southern Canada, and has the potential to become an ecosystem dominant and alter stream communities. However, while much is known of the effects of buckthorn on terrestrial ecosystems, little is known of its effects on aquatic ecosystems. Using leaf collection nets, we estimated that leaf fall to the stream consisted predominantly of green ash (69.0%) and common buckthorn (24.2%). Green ash leaves fell from September through mid-October, reaching its peak in early October, whereas common buckthorn contributed leaves for an additional month until mid-November. We placed leaf packs of common buckthorn and two native species, American elm and green ash, in a headwater stream to determine differences in leaf decomposition rates. Common buckthorn leaves decomposed more rapidly than the native species, with processing coefficients of 6.9 (ash) and 5.3 (elm) times greater. After 21 days of incubation, buckthorn leaf packs had less than half the initial biomass remaining, whereas ash and elm did not reach this point within this 84-day study. These results suggest that buckthorn has the potential to alter stream food webs by changing the timing of leaf fall and the duration of available allochthonous energy sources. Changes to riparian forests are likely to be exacerbated as common buckthorn alters soils to inhibit the growth of other trees and as the emerald ash borer, an invasive beetle, adversely affects native ash forests.
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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) | 0.000 | 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".