To be or not to be a superpredator: a multidisciplinary assessment of the Iberian lynx in a reintroduction social scenario
Bibliographic record
Abstract
Since 2015, following reintroductions, an Iberian lynx population in Vale do Guadiana (Portugal) has been breeding and expanding, bringing changes to both ecosystems and residents’ perceptions. We describe how ecological monitoring, genetic analysis and social surveys contribute to assess this new scenario of coexistence with ecological and social repercussions. Departing from a specific case of a monitored lynx family, we present, for the first time, molecular proof of interspecific competition between lynxes and other carnivores. We assessed and compared knowledge of local key actors about the superpredator effect of the lynx previous to and following reintroduction. Data on damage experienced by livestock breeders with foxes and perceptions about it are integrated here, demonstrating how important this lynx role can be for local actors. We present proof of the killing of two foxes and a genet by lynxes through the amplification of a specific lynx DNA region and other molecular analyses carried out on saliva samples. Local actors, who previously were skeptical about the lynx’s ecological effects, do recognize its effect over other wild carnivores presently. This is a major benefit, since social perceptions have been conditioning the acceptance of the lynx, its future expansion, and the whole process of reintroduction. We also present the first documented case of a natural migrant from Doñana (SW Spain) effectively integrated and reproducing in the Vale do Guadiana population. This case study demonstrates the importance of multidisciplinary knowledge in conservation programmes and how genetics and social surveys provide complementary information for monitoring in reintroduction and, generally, conservation programs of an umbrella species.
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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 | 0.003 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".