Diet and functional feeding groups of Chironomidae (Diptera) in Alpine freshwater habitats
Bibliographic record
Abstract
A gut content analysis (GCA) was performed to quantify the relative use of food resources by larvae of chironomids (Diptera: Chironomidae) inhabiting different Alpine freshwater habitats fed by meltwater (kryal), groundwater (krenal) and mixed waters (glacio-rhithral, proglacial pond) in the Italian Alps (Trentino). GCA was performed on the 13 most frequent and abundant taxa in these habitats: Diamesa bertrami, Diamesa latitarsis, Diamesa steinboecki, Diamesa zernyi, Pseudokiefferiella parva, Eukiefferiella minor, Metriocnemus eurynotus gr., Parametriocnemus stylatus, Thienemanniella clavicornis, Tvetenia calvescens, Macropelopia sp., Zavrelimyia sp., Micropsectra atrofasciata gr. Guts were removed, mounted in Canada Balsam, and examined under a microscope (1000x). The gut of each individual was assumed to be 100% full, and proportions of the different food items were estimated using a 10x10 grid designed with the NIS-BR software. Food items were divided into 10 categories: Mineral Material, Animal Tissue, Algae (except diatoms), Diatoms, Plant tissue, Amorphous detritus, Lichens, Bryophytes, Fungi, and Pollen. The gut content of different taxa contained significantly different (p < 0.05) food categories based on a non-parametric statistical test. Differences in the diet were observed between species living in the same habitat type and classified into the same trophic category (detritivores, grazers, or predators) and individuals belonging to the same species living in different habitat types. A certain trophic flexibility and omnivory was found, which may facilitate the adaptation of chironomids to changes in available resources due to glacier retreat
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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 | 0.000 | 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".