Productive Capacity of Semi-Alluvial Streams in Ontario: The Importance of Alluvial Material for Fish, Benthic Invertebrates, Periphyton and Organic Matter.
Bibliographic record
Abstract
Changes in climate and land-use practices are leading to higher peak flows and increased transport capacity of channel substrate. Semi-alluvial streams underlain by bedrock or clay were examined to understand the potential impacts of alluvium loss on the biological community and overall productive capacity of semi-alluvial rivers. More specifically, this research investigates the productivity of gravels, bedrock, and consolidated clay, through the biomass and density of periphyton, coarse particulate organic matter, benthic invertebrates, and fish. The ecological approach undertaken demonstrates the relationships among each trophic level and linkages to productive capacity between different substrate types. Significant results were detected at the stream type level and substrate level. Bedrock-based streams were overall more productive in terms of CPOM, biomass and density of benthos in comparison to clay-based streams. Stream reaches with small to large areas of exposed bedrock or clay at the site level did not differ to areas with 100% gravel coverage in the comparison of any variable, including stream fishes. At the substrate level, gravels demonstrated the highest productive capacity in comparison to bedrock and clay substrates. CPOM biomass in gravels compared to bedrock and clay at a ratio of 30:14:1, respectively. Biomass of benthic invertebrates also demonstrated a higher productivity on gravels with a ratio of 59:19:1 in comparison to bedrock and clay, respectively. Positive relationships between CPOM and benthic invertebrate biomass were detected in both stream types. Relationships were also detected between fish biomass and benthic invertebrate biomass. Examination of benthic fishes also demonstrated positive relationships with benthic invertebrate biomass and density. Clay substrate on all accounts supported little biota. Results indicate alluvium loss in clay bed streams could reduce productive capacity. Understanding and integration of the potential impacts of alluvium loss would aid management and No Net Loss compensation plans to protect fisheries resources in semi-alluvial streams.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".