Species diversity and changes of communities of heterotrophic flagellates (protista) in response to glacial melt in King George Island, the South Shetland Islands, Antarctica
Bibliographic record
Abstract
Abstract Glacial melt has a great influence on biological communities of the Antarctic Peninsula. Annual changes in heterotrophic flagellates from March 2008–March 2009 and effects of glacial melting on heterotrophic flagellates from December 2008–March 2009 were studied within the coastal zone of King George Island. The maximum abundance and biomass occurred in November and December (950.6–1236.2 individuals ml-1; 0.02–0.035 μg C ml-1), and the minimum in May and June (419.8–456.8 individuals ml-1; 0.018–0.019 μg C ml-1). Forty-five species were identified. The diversity of choanoflagellates, euglenids, bicosoecids, kinetoplastids and incertae sedis flagellates was greatest. Glacial melt between December and April resulted in the freshening of the surface water at the Collins Bay, giving rise to a vertical gradient of salinity (from 26‰ at the surface to 34‰ at the near-bottom layer). The trophic, size and species structure of the heterotrophic flagellates was simplified due to freshening of the surface waters. Eurybiontic and cosmopolitan species were significantly enriched in the freshened surface layer, with prevalence of small-sized mobile bacterio-detritovorous forms. The simplification of structure of the assemblage of heterotrophic flagellates can affect the stability of biological communities.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".