A global meta‐analysis of exotic versus native leaf decay in stream ecosystems
Bibliographic record
Abstract
Abstract Streams are reliant on streamside plants for allochthonous inputs that form the base of the stream food web. The impact of exotic leaves on stream ecosystems has been investigated regionally, but not assessed globally. In this study, we conducted a global meta‐analysis contrasting native and exotic aquatic litter decay. We used a linear mixed effects model to identify how the site‐specific factors and experimental treatments of latitude, temperature, pH , conductivity and the exclusion of invertebrates (via mesh size) cause relative differences in exotic and native decay rates. Subsequently, we assessed whether differences in native and exotic litter decay rates were driven by the intrinsic factors of leaf litter quality. We found that overall leaf litter decay rates were similar for native and exotic leaves on a global scale. However, we also found that exotic leaves decayed faster than native leaves at higher stream temperatures and in larger mesh sizes (allowing macroinvertebrate access); yet, those differences disappeared at lower temperatures and in finer mesh sizes which excluded macroinvertebrates. Post hoc analysis of leaf quality suggested that differences between higher native and lower exotic leaf C:N ratios might explain differences in decomposition rates observed at high temperature, and differences between lower native and higher exotic leaf C:P ratios associated with differences in decomposition rates observed at coarse mesh sizes. Our study suggests that exotic leaf litter is likely to have the most impact in high‐temperature stream ecosystems and that the nature of the impact is potentially related to the C:N ratio differences between native and exotic leaves. This might indicate that higher temperature stream ecosystems are more vulnerable to changes in litter decay rates due to invasion by exotic plant species than lower temperature stream ecosystems, and should be monitored accordingly. We recommend that future leaf litter decay studies include stream discharge measurements and leaf litter quality information so that both intrinsic and extrinsic factors that impact litter decay can be fully accounted for when assessing the factors that drive differences in leaf litter decay rates.
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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 | 0.019 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".