RESPONSE OF PREDATORS TO LOSS AND FRAGMENTATION OF PREY HABITAT: A REVIEW OF THEORY
Bibliographic record
Abstract
Despite extensive empirical research and previous reviews, no clear patterns regarding the effects of habitat loss and fragmentation on predator-prey interactions have emerged. We suggest that this is because empirical researchers do not design their studies to test specific hypotheses arising from the theoretical literature. In fact, theoretical work is almost completely ignored by empirical researchers, perhaps because it may be inaccessible to them. The purpose of this paper is to review theoretical work on the effects of habitat loss and fragmentation on predator-prey interactions. We provide a summary of clear, testable theoretical predictions for empirical researchers. To test one or more of these predictions, an empiricist will need certain information on the predator and prey species of interest. This includes: (1) whether the predator is a specialist on one prey species or feeds on many kinds of prey (omnivore and generalist); (2) whether the predator is restricted to the same habitat type as the focal prey (specialist), can use a variety of habitats but has higher survival in the prey habitat (omnivore), or lives primarily outside of the focal prey's habitat (generalist); (3) whether prey-only patches have lower prey extinction rates than predator-prey patches; and (4) whether the prey emigrate at higher rates from predator-prey patches than from prey-only patches. Empiricists also need to be clear on whether they are testing a prediction about habitat loss or habitat fragmentation and need to conduct empirical studies at spatial scales appropriate for testing the theoretical prediction(s). We suggest that appropriate use of the theoretical predictions in future empirical research will resolve the apparent inconsistencies in the empirical literature on this topic.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".