Hydraulic synchrony of spawning sites amongst Earth’s riverine fishes
Bibliographic record
Abstract
Abstract Earth’s riverine fishes utilize a suite of reproductive guilds, broadly following four guilds: nest guarders, broadcast pelagic spawners, broadcast benthic spawners and nest non-guarders 1 , 2 , and these guilds utilize different mechanisms to aerate eggs 3,4 . Globally, river fishes populations are declining 5 , and spawning habitat rehabilitation has become a popular tool to counter these declines 6 . However, there is a lack of understanding as to what classifies suitable spawning habitats for riverine fishes, thereby limiting the efficacy of these efforts and thus the restoration of the target species. Using data from n = 220 peer-reviewed papers and examining n = 128 unique species, we show the existence of a hydraulic pattern (defined by Froude number ( Fr ), a non-dimensional hydraulic parameter) that characterizes the reproductive guilds of riverine fishes. We found nest guarders, broadcast pelagic spawners, benthic spawners, and nest non-guarders selected sites with mean Fr = 0.05, 0.11, 0.22, and 0.28, respectively. Some of the fishes in this study are living fossils, suggesting that that these hydraulic preference patterns may be consistent across time. Our results suggest this hydraulic pattern can guide spawning habitat rehabilitation for all riverine fish species globally in absence of specific spawning habitat information for a species, where resource managers can establish the reproductive guild of the species of interest, and then apply the specific hydraulic requirements ( Fr range) of that reproductive guild, as presented herein, in the rehabilitation of the target species.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".