Desalination and temperature increase will shift seasonal grazing patterns of invasive <i>Gammarus tigrinus</i> on charophytes
Bibliographic record
Abstract
Abstract Charophytes are a refuge for zooplankton and stabilize sediments, but they are also a food source for various animal species (water birds, fishes, invertebrates). Especially the introduction of new species, like Gammarus tigrinus , into the Baltic Sea led to yet not understood changes in the food web. Furthermore, future projections point to increased water temperatures at lowered salinity levels affecting species capacity to acclimatize to changing abiotic factors. In this study we investigated the influence of temperature and salinity on the grazing pressure of Gammarus tigrinus on two charophyte species: Chara aspera and Chara tomentosa . The grazing experiments were conducted in a full factorial design with the factors salinity (3 – 13 g kg -1 ), temperature (5 – 30 °C), and charophyte species. Grazing rates were determined as mass deviation within 48 hours considering biomass changes in the presence and absence of gammarids. Grazing rate were further used to calculate charophyte losses in two coastal lagoons with different salinity concentrations for recent and future time periods. The potential grazing peak of about 24 °C is not yet reached in these coastal waters but may be reached in the near future as shown by our future projection results. However, the temperature increase, and desalination will cause a shift in seasonal individual grazing patterns from summer to spring and autumn. Desalination and temperature increase can lead to a shift in optimal habitats for G. tigrinus in the future.
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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 | 0.000 |
| 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".