Demystifying Negative Connotations of Hybridization for Less Biased Conservation Policies
Bibliographic record
Abstract
Interspecific hybridization is one of the most controversial—and usually neglected—issues in conservation due to its multiple evolutionary consequences that might include the origin and transfer of adaptations, the blur of distinctive lineages or the formation of maladaptive hybrids. However, despite different outcomes, most conservation laws do not offer any possibility of hybrids being protected since they are perceived as a threat to the survival of pure species. We assessed how much hybridization has contributed to species extinction considering all IUCN Red Data assessments. However, we found that it has been scarcely reported as a threat contributing to extinction: only 11 extinct species out of 120,369 assessments mentioned hybridization. Although the causes that contribute to species extinctions should be controlled, the reasons for not conserving hybrids seem subjective rather than empirically supported. In a genomic era where hybridization is being more frequently detected, the debate involving the conservation of hybrids should be re-opened. Should we conserve hybrids despite the possibility of gene flow with parental species? Should we protect only natural hybrids? The resolution of this debate goes to the heart of what we mean to conserve and the time scale of conservation. But hybridization is part of the evolutionary process and might even increase in the future due to human-induced changes. As such, it becomes clear that we need to move beyond the causes and instead tackle the consequences of hybridization to create environmental policies for the management of hybrids, considering both positive and negative consequences.
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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 | 0.026 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".