A recovery network leads to the natural recolonization of an archipelago and a potential trailing edge refuge
Bibliographic record
Abstract
Abstract Rapid environmental change is reshaping ecosystems and driving species loss globally. Carnivore populations have declined and retracted rapidly and have been the target of numerous translocation projects. Success, however, is complicated when these efforts occur in novel ecosystems. Identifying refuges, locations that are resistant to environmental change, within a translocation framework should improve population recovery and persistence. American martens ( Martes americana ) are the most frequently translocated carnivore in North America. As elsewhere, martens were extirpated across much of the Great Lakes region by the 1930s and, despite multiple translocations beginning in the 1950s, martens remain of regional conservation concern. Surprisingly, martens were rediscovered in 2014 on the Apostle Islands of Lake Superior after a putative absence of >40 yr. To identify the source of martens to the islands and understand connectivity of the reintroduction network, we collected genetic data on martens from the archipelago and from all regional reintroduction sites. In total, we genotyped 483 individual martens, 43 of which inhabited the Apostle Islands (densities 0.42–1.46 km −2 ). Coalescent analyses supported the contemporary recolonization of the Apostle Islands with progenitors likely originating from Michigan, which were sourced from Ontario. We also identified movements by a first‐order relative between the Apostle Islands and the recovery network. We detected some regional gene flow, but in an unexpected direction: individuals moving from the islands to the mainland. Our findings suggest that the Apostle Islands were naturally recolonized by progeny of translocated individuals and now act as a source back to the reintroduction sites on the mainland. We suggest that the Apostle Islands, given its protection from disturbance, complex forest structure, and reduced carnivore competition, will act as a potential refuge for marten along their trailing range boundary and a central node for regional recovery. Our work reveals that translocations, even those occurring along southern range boundaries, can create recovery networks that function like natural metapopulations. Identifying refuges, locations that are resistant to environmental change, within these recovery networks can further improve species recovery, even within novel environments. Future translocation planning should a priori identify potential refuges and sources to improve short‐term recovery and long‐term persistence.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".