The significance of ratios of detritus types and micro‐organism productivity to competitive interactions between aquatic insect detritivores
Bibliographic record
Abstract
Investigations of competitive interactions emphasize non-detrital resources, even though detritus is a major component of most food webs. Studies of competing species focus usually on single resource types, although consumers in nature are likely to encounter mixtures of resource types that may affect whether competition results in exclusion or coexistence. The invasive mosquito Aedes albopictus is capable of excluding the native mosquito Ochlerotatus triseriatus in competition for single detritus types in laboratory and field microcosms. In this study, we used nine ratios of two detritus types (animal and leaf) common in natural containers to test whether detritus ratios affect the outcome of competition. Under intraspecific and interspecific competition, A. albopictus attained higher survival and estimated population growth rate than did O. triseriatus. Unlike past studies, both species had positive growth and high adult survival, with little evidence of competitive effects, under one resource ratio (10:1 ratio of leaf : animal detritus) regardless of mosquito densities, suggesting potential coexistence. Path analysis showed that densities of larvae had negative effects on population growth for O. triseriatus but not for A. albopictus, indicating competitive superiority of A. albopictus. Population growth of both species was affected strongly by the direct paths from animal (positive) and leaf (negative) detritus, and the indirect effect of leaf detritus via bacterial production (positive). Field sampling established that detritus entered real tree holes in ratios similar to those in our experiment, suggesting that natural variation in detritus ratios may influence local coexistence of these species. Seasonal variation in ratios of plant and animal detritus indicated that temporal as well as spatial variation in inputs may be important for potential coexistence.
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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 | 0.000 |
| 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".