Offspring size–number tradeoffs and food quality feedbacks impact population dynamics in a <i>Daphnia–</i> algae system
Bibliographic record
Abstract
Population fluctuations can be affected by both extrinsic (e.g. weather patterns, food availability) and intrinsic (e.g. life‐history) factors. A key life‐history tradeoff is the production of offspring size versus number, ranging from many small offspring to few large offspring. Models show that this life‐history tradeoff in offspring size and number, through maturation time, can have significant impacts on population dynamics. However, few manipulative experiments have been conducted that can isolate life‐history effects from impacts of extrinsic factors in consumer–resource systems. We experimentally tested the effect of an offspring size–number tradeoff on population stability and food availability in a consumer–resource system. Using Daphnia pulex , we created a shift from many, small offspring being produced to fewer, larger offspring. Two sets of experiments were performed to examine the interaction of an extrinsic factor (light levels) and intrinsic population structure on dynamics, and we controlled for the ingestion pressure on algal prey at the time of the manipulation. We predicted that the tradeoff would impact internal consumer population characteristics, including biasing the stage structure towards adults, increasing adult size, and increasing average population‐level reproduction. This adult‐dominated stage structure was predicted to then lead to instability and a low quantity–high quality food state. Under all light levels, the manipulated populations became dominated by large adults. Contrary to predictions, the amplitudes of fluctuations in Daphnia biomass were lower in populations shifted to few–large offspring, representing higher stability in these populations. Furthermore, in high light conditions, a stable low Daphnia – high algae biomass (low food quality) state was observed in few–large offspring treatments but not in control (many–small offspring) treatments. Our results show a strong link between light levels as an extrinsic factor and the life‐history tradeoff of consumer offspring size versus number that impacts consumer–resource population dynamics through feedbacks with resource quality.
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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".