The International Union for Conservation of Nature Red List does not account for intraspecific diversity
Bibliographic record
Abstract
Abstract The International Union for Conservation of Nature (IUCN) Red List identifies threatened and endangered species and is a key instrument in global biodiversity conservation efforts. Our understanding of the structure and value of genetic biodiversity below the species level is rapidly increasing. Nonetheless, the IUCN assessment criteria overlook genetic variation within species. Here, we address this blind spot and discuss the principles of species conservation status classification relative to intraspecific biodiversity. We focus on coastal species, which thrive in heterogeneous environments known to drive genetic differentiation. The focal example species, Atlantic cod and sugar kelp, have contrasting life histories, are ecologically and economically important constituents of the coastal ecosystem, and are currently not classified as threatened in Norway and Canada. We expose important variation in population structure, the presence of ecotypes and genetic-environment covariation, as well as loss of ecotypes that threatens the conservation of these species. Because the genetic makeup of species directly influences their resilience, omitting this information from conservation status assessments can result in loss of adaptive capacity to future stressors, such as climate change. Consequently, recognizing and preserving intraspecific variation emerges as vital for species’ abilities to adapt to and survive in future ocean conditions.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".