Compensatory immigration depends on adjacent population size and habitat quality but not on landscape connectivity
Bibliographic record
Abstract
1. Populations experiencing localized mortality can recover in the short term by net movement of individuals from adjacent areas, a process called compensatory immigration or spillover. Little is known about the factors influencing the magnitude of compensatory immigration or its impact on source populations. Such information is important for understanding metapopulation dynamics, the use of protected areas for conservation, management of exploited populations and pest control. 2. Using two small, territorial damselfish species (Stegastes diencaeus and S. adustus) in their naturally fragmented habitat, we quantified compensatory immigration in response to localized mortality, assessed its impact on adjacent source populations and examined the importance of potential immigrants, habitat quality and landscape connectivity as limiting factors. On seven experimental sites, we repeatedly removed 15% of the initial population size until none remained and immigration ceased. 3. Immigrants replaced 16-72% of original residents in S. diencaeus and 0-69% in S. adustus. The proportion of the source population that immigrated into depleted areas varied from 9% to 61% in S. diencaeus and from 3% to 21% in S. adustus. In S. diencaeus, compensatory immigration was strongly affected by habitat quality, to a lesser extent by the abundance of potential immigrants and not by landscape connectivity. In S. adustus, immigration was strongly affected by the density of potential migrants and not by habitat quality and landscape connectivity. On two control sites, immigration in the absence of creation of vacancies was extremely rare. 4. Immigration occurred in response to localized mortality and was therefore compensatory. It was highly variable, sometimes producing substantial impacts on both depleted and source populations. The magnitude of compensatory immigration was influenced primarily by the availability of immigrants and by the potential improvement in territory quality that they could achieve by immigrating and not by their ability to reach the depleted area.
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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 | 0.000 |
| 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".