Settlement in Novel Habitats Induced by Social Information May Disrupt Community Structure
Bibliographic record
Abstract
Birds may colonize new habitats because of introduction, changing environmental conditions, and/or altered social or environmental cues. However, aside from introduced (often invasive) species, little is known about the consequences of such colonizations for members of existing communities. If the realized niche is influenced by the presence or absence of heterospecific competitors, then addition of a species to a novel habitat or location could result in extirpation or avoidance if members of the existing community are subdominant. Alternatively, if for some species heterospecific cues are the primary means for collecting information about a site's quality, heterospecific attraction could occur. To test these predictions, we experimentally induced free-living Black-throated Blue Warblers (Dendroica caerulescens) to colonize a novel environment within their existing range. We used dynamic occupancy modeling to test for the dynamics of colonization and local extinction as a function of our experimental treatment. We found strong evidence for dynamic occupancy by birds during the breeding season; colonizations and extirpations were common. Although dynamics were not generally well explained by our experimental introduction of Black-throated Blue Warblers, we found some support for the heterospecific-avoidance hypothesis; three of the four species we examined that prefer early seral forests tended to abandon a site once Black-throated Blue Warblers occupied it. We suggest that heterospecific interactions should be considered when species' distributions are projected in relation to climate change. Our results provide a caution that managers broadcasting a species' song to increase its abundance should consider the technique's effects on the broader community.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".