Evolution in Population Parameters: Density-Dependent Selection or Density-Dependent Fitness?
Bibliographic record
Abstract
Density-dependent selection is one of earliest topics of joint interest to both ecologists and evolutionary biologists and thus occupies an important position in the histories of these disciplines. This joint interest is driven by the fact that density-dependent selection is the simplest form of feedback between an ecological effect of an organism's own making (crowding due to sustained population growth) and the selective response to the resulting conditions. This makes density-dependent selection perhaps the simplest process through which we see the full reciprocity between ecology and evolution. In this article, we begin by tracing the history of studying the reciprocity between ecology and evolution, which we see as combining the questions of evolutionary ecology with the assumptions and approaches of ecological genetics. In particular, density-dependent fitness and density-dependent selection were critical concepts underlying ideas about adaptation to biotic selection pressures and the coadaptation of interacting species. However, theory points to a critical distinction between density-dependent fitness and density-dependent selection in their influences on complex evolutionary and ecological interactions among coexisting species. Although density-dependent fitness is manifestly evident in empirical studies, evidence of density-dependent selection is much less common. This leads to the larger question of how prevalent and important density-dependent selection might really be. Life-history variation in the least killifish Heterandria formosa appears to reflect the action of density-dependent selection, and yet compelling evidence is elusive, even in this well-studied system, which suggests some important challenges for understanding density-driven feedbacks between ecology and evolution.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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".