Habitat‐dependent competition and the coexistence of Australian heathland rodents
Bibliographic record
Abstract
When competing species depress one another's fitness in the habitats that they occupy, their competitive effects will emerge in each species’ pattern of density‐dependent habitat choice. Thus, a regression analysis of joint densities, corrected by the habitat effect, should reveal the magnitude of interspecific competition. We tested this idea by 1) demonstrating the connection between removal experiments and regression estimates of competition with those obtained from isodars (regressions that implicitly incorporate evolutionarily stable strategies of habitat selection) and 2) evaluating whether interspecific competition inferred from isodars corresponded with the inferences emerging from regression and field experiments. Previous removal experiments on two herbivorous rodents occupying coastal wet heathlands in eastern Australia documented that competition between Rattus lutreolus and Pseudomys gracilicaudatus is asymmetrically biased in favor of the much larger Rattus . The asymmetry in competition was also revealed by regression estimates of competition. Isodar analyses illustrate a habitat‐dependent mechanism for the asymmetry. Rattus compete effectively with Pseudomys in both ‘wetter’ and ‘drier’ patches of heath whereas Pseudomys appear to exert a competitive effect in only the drier sites. The magnitude of competition measured by a removal experiment in an area with more‐or‐less equal amounts of both habitats will be biased in favor of Rattus . More generally, one can use the isodar estimates to draw isolegs and isoclines of competitive coexistence. Isoclines for the two Australian rodents imply dynamic equilibria of stable competitive coexistence that vary with plant succession in fire‐dominated heathland ecosystems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".