Inducible defenses and rotifer food chain dynamics
Bibliographic record
Abstract
Theoretical studies have predicted that inducible defenses affect food chain dynamics and persistence. Here we review and evaluate laboratory experiments that tested hypotheses developed from these theoretical studies. This review specifically focuses on the effects of inducible defenses in phytoplankton-rotifer food chain dynamics. First, we describe the occurrence of colony formation within different strains of green algae (Scenedesmaceae) in response to infochemicals released during grazing by the herbivorous rotifer Brachionus calyciflorus . Then we examined the effects of inducible defenses on the population dynamics of this planktonic system in which algal strains that differed in their defense strategies were used. Simple food chains were composed of green algae (Scenedesmaceae), herbivorous rotifers ( Brachionus calyciflorus ) and carnivorous rotifers ( Asplanchna brightwellii ). In this system B. calyciflorus exhibits an inducible defense against predation by developing long postero-lateral spines. Experimental studies showed that inducible defenses, as opposed to their absence, could prevent high-amplitude population fluctuations. We discuss the dual effects of induced defenses on extinction probabilities and consider the fit of a theoretical model to experimental data to understand the mechanisms that underlie the observed dynamics.
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 | 0.001 | 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".