Periphyton and invertebrate response to wood placement in large pacific coastal rivers
Bibliographic record
Abstract
Abstract Wood abundance in aquatic systems has been dramatically reduced compared to historical levels due to anthropogenic activities that led to wood removal and stream simplification. As a result, reintroduction of wood to aquatic systems is now a widely used and relatively well‐studied restoration technique for increasing habitat complexity. Although stream periphyton (biofilm) and invertebrates serve as food sources for a variety of predators including fish, birds and bats, data on how lower trophic levels respond to wood placement are relatively scarce. The purpose of this study was to test the hypothesis that periphyton biomass and aquatic invertebrate density were higher on Engineered Log Jams (ELJs) than on inorganic substrates in two large Pacific Northwest river systems. Among years and rivers, periphyton biomass and invertebrate densities were significantly higher on ELJs than on cobbles within the same reach. Invertebrate communities on ELJs were dominated by meiofauna (<500 µm), whereas cobbles were dominated by larger chironomids. We attribute these trophic level differences to substrate type, as we did not detect taxonomic differences between cobbles in reaches with and without ELJs. We show that adding wood to reaches with little or no naturally occurring wood increased overall habitat surface area and thereby the potential for increased productivity relative to reaches with low levels of wood. Finally, wood supports a unique community of invertebrates that are often overlooked in lotic system studies but may be contributing substantially to overall biological diversity. Published in 2009 by 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 | 0.000 | 0.001 |
| 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".