Flood control structures in tidal creeks associated with reduction in nursery potential for native fishes and creation of hotspots for invasive species
Bibliographic record
Abstract
Habitat connectivity is important for maintaining biodiversity and ecosystem processes yet globally is highly restricted by anthropogenic actions. Anthropogenic barriers are common in aquatic ecosystems; however, the effects of small-scale barriers such as floodgates have received relatively little study. Here we assess fish communities in ten tributaries over the spring–summer season of the lower Fraser River (British Columbia, Canada), five with floodgates and five reference sites without barriers, located primarily in agricultural land use areas. While the Fraser River supports the largest salmon runs in Canada, the lower Fraser river–floodplain ecosystem has numerous dikes and floodgates to protect valuable agricultural and urban developments. Floodgate presence was associated with reduced dissolved oxygen concentrations, threefold greater abundance of invasive fish species, and decreased abundances of five native fish species, including two salmon species. These findings provide evidence that floodgates decrease suitable habitat for native fishes, and become hotspots for non-native species. Given climate change, sea-level rise, and aging flood protection infrastructure, there is an opportunity to incorporate biodiversity considerations into further development or restoration of this infrastructure.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".