Resource subsidy flows across freshwater–terrestrial boundaries and influence on processes linking adjacent ecosystems
Bibliographic record
Abstract
Abstract Freshwaters receive more than water from their catchments, including a large amount of materials and biologically available energy, referred to as cross‐ecosystem resource subsidies. The passive flows of energy such as leaf litter and terrestrial invertebrate inputs, as well as dissolved organic carbon, are donor‐controlled, whereas other flows, such as between fish and fish‐eating birds, have more directly coupled feedbacks. There are also flows upstream or to the terrestrial environment in the form of adult aquatic insects, salmon carcasses and particulate carbon through overbank flooding, as well as directed foraging activities. Hypotheses about the effects of flux rates, timing, quality and physical structure of such resource subsidies on the responses of consumers have been experimentally tested at many trophic levels. Many freshwater and terrestrial consumers depend on these subsidies for at least part of their life cycle, and timing of inputs can affect growth. Developing more quantitative relations between the population and community responses across gradients of cross‐ecosystem resource subsidy input rates will require exploring the shape of the relations, as well as the effects of quality and timing on responses. The stage is now set to consider how resource subsidies might affect the stability of communities and processes such as the strength of trophic cascades. The high degree of connectivity between the land and water are essential to biodiversity conservation and to ensuring that critical aquatic ecosystem services are sustained. The management of riparian areas is a key to the security of these values. Copyright © 2014 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".