Post‐release survival of translocated fishers: implications for translocation success
Bibliographic record
Abstract
Abstract As a vital tool for the conservation of species at risk, translocations are also opportunities to identify factors that influence translocation success. We evaluated factors associated with post‐release survival of 90 radio‐tracked fishers (Pekania pennanti) translocated from central British Columbia, Canada, to the Olympic Peninsula of Washington, USA, from 2008 to 2011. We hypothesized that the survival of translocated fishers would be affected by the same factors that influence the survival of resident, native fishers (i.e., sex, age, season, body condition), and additional factors that were associated with the translocation process (e.g., duration of captivity, release date, yr of release). Fisher survival was most strongly influenced by translocation year (i.e., release‐yr cohort), season, sex, and age class of fisher; whereas duration of captivity, standardized body mass, release date, and number of intact canines did not influence survival. Survival was lowest for fishers released in cohort 2 in 2009 and during the breeding season (Mar–Jun), and was greatest for juveniles and males. When combined across release‐year cohorts, year 1 survival rates were greatest for juvenile males followed by juvenile females, adult females, and adult males. Sex and age‐related differences in survival of translocated fishers were counter to those commonly reported for established fisher populations, where adult females often have the highest survival rates and juveniles the lowest. Predation (40%) and vehicle strikes (20%) were the most common causes of known mortality among the 24 recovered fishers for which cause of death was determined. We speculate that females face higher risks of mortality in translocated populations because their small size makes them more vulnerable to predation and because adult females in resident populations are less likely than males and juveniles to disperse. Our findings support designing translocations that favor releasing a preponderance of female fishers in recognition of their lower survival rates and to ensure adequate breeders are established in the population, and juvenile and young adult fishers to enhance survival of both sexes. Releases conducted over multiple years will minimize the impact of stochastic annual events that may adversely affect survival in any given year. Persistence, widespread distribution, and documented reproduction of fishers within our study area for ≥6 years following the last releases indicate that survival parameters we measured contributed toward successful population establishment over the short term.
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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 | 0.000 |
| 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".