Increases in temperature and freshwater inputs will shift grazing patterns of a coastal mesograzer on foundation species
Bibliographic record
Abstract
Abstract Foundation species, and the roles that they play in structuring ecosystems, are threatened by global change. For example, charophytes are a refuge for zooplankton and stabilize sediments, but they are also a food source for various animal species (water birds, fishes, and invertebrates). Particularly, the introduction of new species, such as Gammarus tigrinus , into the Baltic Sea led to yet not understood changes in the food web. Furthermore, future projections point to increased water temperatures and freshwater inputs 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 G. 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 h considering biomass changes in the presence and absence of gammarids. Grazing rates were further used to calculate charophyte losses in two coastal lagoons with different salinity concentrations for recent and future time periods. Increasing freshwater inputs can buffer charophyte biomass loss at higher temperatures. Gammarids had a higher grazing impact on C. aspera than on C. tomentosa . 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, a temperature increase and decrease in salinity will cause a shift in seasonal individual grazing patterns from summer to spring and autumn. An increase in temperature and freshwater input can lead to a shift in optimal habitats for G. tigrinus in the future. These interactions between abiotic and biotic factors will affect the future spatial distribution that charophytes can exploit as foundation 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 | 0.000 |
| 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".