Resource subsidies across the land–freshwater interface and responses in recipient communities
Bibliographic record
Abstract
Abstract Fluxes of resource subsidies, such as terrestrial leaf litter to streams and adult aquatic insects to riparian predators, are examples of important links between adjacent ecosystems. The importance of these cross‐ecosystem resource flows from donor systems to recipient consumers is increasingly recognized. Streams, especially small streams with their high edge ratio with the terrestrial system, provide excellent models for the study of subsidies and a large portion of this literature has been produced by aquatic scientists. Field experiments manipulating flows between small streams and their riparian areas (e.g. leaf litter, terrestrial invertebrates, and adult aquatic insects to riparian areas) have indicated that consumers in streams and riparian areas are highly dependent upon such subsidies and the value of the subsidies are further modified by patterns of retention and pathways of use. Experiments typically indicate rapid growth or demographic responses by consumers, indicating these populations are resource limited or at levels of incipient population limitation, and can capitalize on short‐term resource pulses. More press manipulations are still necessary to determine the dynamical consequences of subsidies for recipient communities. The nature of the subsidy (e.g. species of litter or invertebrates) and its timing are also important details that need further study. Finally, there are opportunities to consider the evolution of life cycle timing (modelling), interception strategies by recipient populations and short‐term and long‐term responses of communities. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".