Identifying hidden sinks in growing populations from individual fates and movements: The feral horses of Sable Island
Bibliographic record
Abstract
ABSTRACT Identifying the existence of population sinks is critical for conservation and management. However, because of density‐dependent dispersal, sinks can sometimes be masked by immigration events, especially during phases of population growth. We present a large‐scale, empirical demonstration of within‐population source‐sink dynamics using the feral horses (Equus ferus caballus) of Sable Island National Park Reserve, Nova Scotia, Canada, as a model. We tracked the fates and movements of 98.7% of the female population (n = 190–237) across 3 demographic clusters (subunits) during a period of rapid population growth (2008–2010; 24.7% increase in density). All subunits experienced increases in population size each year (λ > 1.0). Our individual‐based analysis showed that western Sable Island, where water availability was greatest, behaved as a source and would have grown with or without immigration in all years. However, the central (and fastest growing subunit) would have declined from 2008–2009 (λ = 0.951) without immigration. Further, the eastern subunit would have declined in 2 intervals (λ = 0.932, 0.999) without immigration. Our study demonstrates that the propensity of habitat to act as a sink can be masked during a period of population growth because of density‐dependent immigration from adjacent habitats. These findings present a caution to managers charged with conserving wide‐ranging species with long population cycles for which effects of immigration on local population growth rate can be difficult to isolate using standard methods of enumeration. © 2013 The Wildlife Society.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".