A Biological Framework for Evaluating Whether a Species Is Threatened or Endangered in a Significant Portion of Its Range
Bibliographic record
Abstract
Under the U.S. Endangered Species Act (ESA), a species can be listed if it is at risk "in all or a significant portion of its range," but the ESA provides no guidance on how to interpret this key phrase. We propose a simple test to determine whether the areas of a species' range in which it is currently at risk amount to a significant portion: If the species were to become extirpated from these areas, at that point would the entire species be at risk? If so, then these areas represent a significant portion of the species' range. By establishing the species itself as the point of reference for determining significance, this test directs attention to biological risk factors and avoids difficulties inherent in subjective evaluations of importance to humans. For broadly distributed species this framework could provide ESA protection due to cumulative risks before the entire species met the criteria to be considered threatened or endangered. This framework also allows a somewhat broader concept of range to include major components of diversity necessary for long-term persistence. The concept of a historical template (i.e., conditions under which the species was known to be viable) is important in providing a fixed reference point for evaluating viability. Empirical examples illustrate how these concepts have been applied in recent ESA listing determinations. Most ESA-listed units of Pacific salmon (Oncorhynchus spp.) can be divided into multiple strata that differ in terms of ecology, geology, or life-history traits of the component populations. The goal of ESA recovery planning is to restore viable populations in enough strata that the listed unit as a whole is no longer threatened or endangered in all or a significant portion of its range. In a recent review of Pacific herring (Clupea pallasii) in Puget Sound, current status (some populations increasing and others declining) was evaluated in the context of the historical template, and it was concluded that current patterns of distribution and abundance do not depart substantially from what would be expected at any point in time under natural conditions in a large metapopulation. The Canadian lynx (Lynx canadensis) is ESA listed in the contiguous United States, where it occurs in four geographic areas. Populations in one region, the Northern Rockies/Cascades, have always been the most important for long-term persistence of the species in the United States. Because the other regions never contained more than limited amounts of good-quality lynx habitat, those areas are not considered to represent a significant portion of the species' range.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".