Tracking the invasive and euryhaline pikeperch <scp><i>Sander lucioperca</i></scp> in the lower River Thames using acoustic telemetry indicates no movements into areas of relatively high salinity
Bibliographic record
Abstract
Abstract Native to Central and Eastern Europe, the euryhaline pikeperch Sander lucioperca can acclimatize to elevated salinity levels (e.g., up to 30‰), but it remains unknown whether their invasive populations use this ability to inhabit and/or disperse through brackish waters, such as estuaries and inshore areas. To test whether invasive pikeperch show a propensity to move into areas of relatively high salinity, their spatial use and movement patterns (e.g., home range, distances moved, and movement rates) were assessed using acoustic telemetry in the upper River Thames estuary, southeast England. Analyses revealed that individual pikeperch were capable of moving relatively long distances in a short time (e.g., speeds up to 70 m min−1), with movement patterns associated more with tidal state and elevation at the water surface (both assumed to relate to changes in salinity) than diurnal changes. There were no recorded movements of any pikeperch into the more saline, downstream waters of the estuary where salinity levels were recorded to over 40‰, with the mean salinity in the most downstream area where pikeperch were detected being 1.39‰ (range of logger: 1.22–1.71). The results suggest that these pikeperch did not use high salinity waters when less saline waters were available, and thus the risk that they will use to move through high salinity areas to expand their invasive range appears low. Accordingly, efforts to minimize risks of the further dispersal of invasive pikeperch populations can focus on control and containment programmes within fresh waters.
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 | 0.000 |
| 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 | 0.000 |
| 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".