High individual variability in space use by translocated, imperiled New England cottontail (<i>Sylvilagus transitionalis</i>)
Bibliographic record
Abstract
Translocations are an established element of restoration plans for threatened species, but success in establishing new populations is often limited, highlighting the need for careful evaluation of translocation efforts. Variation among individuals may contribute to poorly placed translocations, particularly when there is variation in the spatial ecology of target species. As a test of this we investigated the spatial ecology of imperiled New England cottontail ( Sylvilagus transitionalis (Bangs, 1895)) in Rhode Island, USA. We combined telemetry data with remotely-sensed vegetation data to evaluate the home ranges, resource selection, and survival of translocated cottontails at three sites, including one where we also tracked resident cottontails. Despite instances of alignment among individuals, we found a wide span of home range estimates and high individual variability on resource selection. Both of these results suggest that population-level inferences of translocated individuals may fail to capture important aspects of animal ecology at the individual level. Further, we found lower survival compared to residents at one of our sites and literature values for other resident populations. Our results suggest that there are benefits to considering variation among individuals when designing management plans to support translocations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".