Periphyton consumption by an invasive snail species is greater in simplified than in complex habitats
Bibliographic record
Abstract
Habitat complexity may stabilize consumer–resource interactions and reduce the probability of invasion in aquatic habitats. We tested the hypotheses that (i) higher habitat complexity reduces resource consumption independently of grazer species, but that (ii) invasive grazers have a greater influence on decreasing resources independently of habitat complexity. We performed an experiment using artificial substrates to simulate different complexity levels. We evaluated Melanoides tuberculata (O.F. Müller, 1774) and Aylacostoma chloroticum Hylton Scott, 1954 consumption of specific algal groups and the interaction between habitat complexity and grazer species. Moreover, we evaluated grazer activity on the different substrates during the experiment. The results support only the first hypothesis and indicate lower resource consumption on complex substrates compared with simpler substrates. Additionally, the effect of the grazing of the invasive species on taxon richness was greater in simplified than in complex habitats. The grazing activity on the substrate suggests a relationship between resource exploitation and habitat complexity in which the invasive grazing species visited the simple habitat less frequently. However, the effects of invasive grazers on food resources were higher on the simple substrate. The effects of grazing activity on food resources depend on the interaction between habitat complexity and grazer species. In this way, the introduction of an invasive species may have negative impacts on the structure and function of periphytic communities, mainly in simplified aquatic ecosystems.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".