Elemental Conservation Units: Communicating Extinction Risk without Dictating Targets for Protection
Bibliographic record
Abstract
Conservation biologists mostly agree on the need to identify and protect biodiversity below the species level but have not yet resolved the best approach. We addressed 2 issues relevant to this debate. First, we distinguished between the abstract goal of preserving the maximum amount of unique biodiversity and the pragmatic goal of minimizing the loss of ecological goods and services given that further loss of biodiversity seems inevitable. Second, we distinguished between the scientific task of assessing extinction risk and the normative task of choosing targets for protection. We propose that scientific advice on extinction risk be given at the smallest meaningful scale: the elemental conservation unit (ECU). An ECU is a demographically isolated population whose probability of extinction over the time scale of interest (say 100 years) is not substantially affected by natural immigration from other populations. Within this time frame, the loss of an ECU would be irreversible without human intervention. Society's decision to protect an ECU ought to reflect human values that have social, economic, and political dimensions. Scientists can best inform this decision by providing advice about the probability that an ECU will be lost and the ecological and evolutionary consequences of that loss in a form that can be integrated into landscape planning. The ECU approach provides maximum flexibility to decision makers and ensures that the scientific task of assessing extinction risk informs, but remains distinct from, the normative social challenge of setting conservation targets.
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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 | 0.032 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.011 | 0.026 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".