Saving the Dinaric lynx: multidisciplinary monitoring and stakeholder engagement support large carnivore restoration in human-dominated landscape
Bibliographic record
Abstract
Abstract Translocations are central to large carnivore restoration efforts, but inadequate monitoring often inhibits effective conservation decision-making. Extinctions, reintroductions, poaching and high inbreeding levels of the Central European populations of Eurasian lynx ( Lynx lynx ) typify the carnivore conservation challenges in the Anthropocene. Recently, several conservation efforts were initiated to improve the genetic and demographic status, but were met with variable success. Here, we report on a successful, stakeholder-engaged translocation effort to reinforce the highly-inbred Dinaric lynx population and create a new stepping-stone subpopulation in the Southeastern Alps. We used multidisciplinary and internationally-coordinated monitoring using systematic camera- trapping, non-invasive genetic sampling, GPS-tracking of translocated and remnant individuals, recording of reproductive events and interspecific interactions, as well as the simultaneous tracking of the public and stakeholders’ support of carnivore conservation before, during and after the translocation process across the three countries. Among the 22 translocated wild-caught Carpathian lynx, 68% successfully integrated into the population and local ecosystems and at least 59% reproduced. Probability of dispersing from the release areas was 3-times lower when soft-release rather than hard-release method was used. Translocated individuals had lower natural mortality, higher reproductive success and similar ungulate kill rates compared to the remnant lynx. Cooperation with local hunters and protected area managers enabled us to conduct multi-year camera-trapping and non-invasive genetic monitoring across a 12,000-km 2 transboundary area. Results indicate a reversal in population decline, as the lynx abundance increased for >40% during the 4-year translocation period. Effective inbreeding decreased from 0.32 to 0.08-0.19, suggesting a 2- to 4-fold increase in fitness. Furthermore, successful establishment of a new stepping-stone subpopulation represents an important step towards restoring the Central European lynx metapopulation. Robust partnerships with local communities and hunters coupled with transparent communication helped maintain high public and stakeholder support for lynx conservation throughout the translocation process. Lessons learned about the importance of stakeholder involvement and multidisciplinary monitoring conducted across several countries provide a successful example for further efforts to restore large carnivores in human-dominated ecosystems.
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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 | 0.001 | 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 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".