Territoriality modifies the effects of habitat complexity on animal behavior: a meta-analysis
Bibliographic record
Abstract
Abstract Augmenting habitat complexity by adding structure has been used to increase the population density of some territorial species in the wild and to reduce aggression among captive animals. However, it is unknown if all territorial species are affected similarly by habitat complexity, and whether these effects extend to non-territorial species. We conducted a meta-analysis to compare the behavior of a wide range of territorial and non-territorial taxa in complex and open habitats to determine the effects of habitat complexity on 1) territory size, 2) population density, 3) rate and time spent on aggression, 4) rate and time devoted to foraging, 5) rate and time spent being active, 6) shyness/boldness, 7) survival rate, and 8) exploratory behavior. Overall, all measures were significantly affected by habitat complexity, but the responses of territorial and non-territorial species differed. As predicted, territorial species were less aggressive, had smaller territories and higher densities in complex habitats, whereas non-territorial species were more aggressive and did not differ in population density. Territorial species were bolder but not more active in complex habitats, whereas non-territorial species were more active but not bolder. Although the survival of non-territorial species increased in complex habitats, no such increase was observed for territorial species. The increased safety from predators provided by complex habitats may have been balanced by the higher population densities and bolder behavior in territorial species. Our analysis suggests that territorial and non-territorial animals respond differently to habitat complexity, perhaps due to the strong reliance on visual cues by territorial animals.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".