Ecological response of <i>Rotaria rotatoria</i> (Bdelloid Rotifera) to unbalanced nitrogen in food: experimental insights from life history strategy and feeding behavior
Bibliographic record
Abstract
Nitrogen (N) cycle in ecosystems has been overbalanced by human activities. However, it remains uncertain whether the altered N supply results in a change in the elemental composition of phytoplankton and, consequently, affects the life history strategy of zooplankton. To investigate these impacts, a simple lab-based food chain was established. Results show that lack or excess of nitrogen reduced algal density, cell volume, growth rate and chlorophyll content. Moreover, N content in algae significantly increased with increased N concentration in the medium, and reached saturation at concentrations ≥5 mg·L−1. Feeding on algae grown in a low-nitrogen or no nitrogen mediums resulted in faster decline in age-specific survival of rotifers, and slower population growth, as well as longer generation time. In order to make up for nutritional shortage, grazing and filtration rates increased. On the other hand, rotifers feeding on algae grown in high-N mediums (A50 and A200) had significantly shorter average lifespan and life expectancy at hatching. Therefore, nitrogen imbalances have adverse effects on the growth, development and reproduction of both primary producers and herbivorous zooplankton in the food chain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".