Adaptation, density dependence and the responses of trophic level abundances to mortality
Bibliographic record
Abstract
We use simple models to examine how the abundances of three trophic levels change in response to mortality imposed on each one of the levels. The models contain two factors whose joint effects have not been incorporated into previous analyses: direct density dependence ('self-damping') at trophic levels above the bottom level, and adaptive change on the middle trophic level. The adaptive change involves balancing foraging gains and risks of predation. The combination of this type of adaptation and self-damping leads to a wide variety of potential responses of trophic level abundances to increased per capita mortality at any one level. However, the signs of the responses at each level can often be predicted from a knowledge of the strength of direct density dependence together with three additional quantities: the shape of the relationship between resource intake and per capita growth rate for the middle level; the curvature of the function relating the fitness of the middle level species to its foraging effort; and the change in the ratio of predation vulnerability to foraging effort as effort changes. Some possible responses include a decrease in all three levels with increased mortality of the top level, and an increased density of either the middle or top level, following increased mortality imposed on it or its prey. We show that the responses of trophic levels to mortalities are similar for several different mechanisms of adaptive change on the middle level - micro-evolution or behaviour, species replacement and induced defence. Possible evidence for some of the novel predictions is discussed, as is the need for experimental studies of the consequences of mortality rates at all trophic levels, quantification of direct density dependence, and studies of the shapes of functional and numerical responses. [KEYWORDS: adaptive foraging; bottom-up effect; density dependence food web; inducible defences; top-down effect; tritrophic system]
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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 | 0.004 | 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 | 0.002 |
| 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".