Hydrological connection links zooplankton communities and improves juvenile Chinook salmon growth in intertidal marshes
Bibliographic record
Abstract
Many once coupled habitats are now disconnected due to human infrastructure that prevents not only the transfer of organisms but also fundamental ecosystem processes. Here we investigate the importance of hydrologic connectivity between remnant floodplain and freshwater intertidal marsh habitats for zooplankton metacommunity dynamics and juvenile Chinook salmon growth in the Sacramento-San Joaquin Delta, California, U.S.A. during a connected flood and disconnected drought year. Hydrological connection led to highly similar zooplankton communities between habitats. Further, we found that connected intertidal marsh habitats had approximately twice the total abundance of zooplankton of upstream floodplains and, in some cases, 15 times greater abundance than during disconnection. Gut content analysis demonstrated that salmon in our study utilized these abundant zooplankton food resources which likely contributed to elevated juvenile salmon growth rates in connected intertidal marsh habitats, where salmon had 25% greater growth rates (mm day −1 ) than those reared in disconnected marsh habitats. These results provide strong evidence for the importance of connectivity for metacommunity dynamics as well as productivity in historically coupled ecosystems and provide important information for future management and restoration.
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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 | 0.000 |
| 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 | 0.001 |
| 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".