Both reintroduction and recolonization likely contributed to the re-establishment of a fisher population in east-central Alberta
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recently, Stewart et al. (2017) investigated the origins of contemporary fisher populations in the Cooking Lake Moraine (CLM) of east-central Alberta, Canada, where fishers (Pekania pennanti) from Ontario and Manitoba, Canada were reintroduced in the early 1990s. To address this objective, Stewart et al. (2017) compared microsatellite alleles from extant fisher populations in the CLM to those from Ontario, Manitoba, and other Alberta populations. They reported that the CLM population clustered with adjacent native Alberta populations, consistent with recolonization, but also that 2 of 109 microsatellite alleles in the CLM occurred only in the source populations from Ontario and Manitoba. Rather than allowing for the possibility that these alleles descended from reintroduced fishers, the authors speculated that they represented random mutations among fishers that recolonized the area naturally from nearby populations in Alberta, and concluded that the reintroduction had failed completely. We disagree with this conclusion for 2 reasons. We contend it is more likely that the 2 alleles represent a genetic signature from the individuals released during the reintroduction, rather than being the result of mutations. We further suggest that, irrespective of the genetic legacy of introduced fishers in the recovered population, the presence of reintroduced fishers in the CLM may have helped facilitate natural recolonization of the area by fishers from surrounding areas. In our view, Stewart et al.’s (2017) findings do not demonstrate conclusively that the reintroduction program failed; on the contrary, we argue that their findings indicate that reintroduced fishers likely contributed to the long-term persistence of fishers in the CLM. The uncertainty surrounding this case underscores the importance of genetic monitoring following reintroductions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it