Coastal to Riverine Entry Timing During the Spawning Migration of the European Shads (<i>Alosa</i> spp.): Drivers and Phenological Trends for the French Atlantic Coast Populations
Bibliographic record
Abstract
ABSTRACT During the spawning migration of the anadromous allis Alosa alosa and twaite Alosa fallax shads, timing of river entry is decisive to ensure that arrival in the spawning grounds matches with favourable conditions for reproductive success. Identifying the environmental cues that drive the timing of river entry is therefore crucial to understanding the implications of climate change for shad populations and to implementing management measures for these threatened species. In this study, data from fisheries and fish counting stations located in the estuaries or low reaches of 10 rivers were combined to investigate the effects of coastal, river conditions and abundance on the timing of migration. Phenological trends were quantified at five sites with more than 20 years' monitoring, and we analysed whether these trends aligned with the period when river temperatures were in the most favourable range for offspring survival. The results indicated that the temporality of spring warming in coastal habitats and photoperiod were key drivers influencing river entry timing. Their relative influence varied between models predicting migration initiation, median and end dates. Significant shifts toward earlier and longer migration periods were quantified. At the site with the longest monitoring time series, the shift in migration timing increased the time lag between early shad arrival and the period of most favourable breeding temperatures. Therefore, further studies should assess the repercussions of earlier spawning migration on the phenology and success of reproduction and juvenile stages.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".