Conservation of erupting ungulate populations on islands – a comment
Bibliographic record
Abstract
A generalised model for herbivores experiencing abundant forage over time is that their numbers erupt and then decline. This model has been applied to fluctuations in caribou (Rangifer tarandus) populations especially those on islands. Since this generalised model for erupting herbivores was first proposed, two assumptions have slipped in (1) that an erupting population will crash; and (2) that the crash will be density-dependent. The problem with the assumptions is that, without testing, they can lead to inappropriate management such as culls. The first assumption arises from uncritical use of earlier accounts and the second assumption from not discriminating between the effects of environmental variation from the effects of the high herbivore numbers on forage availability (density-dependence). Often typical densitydependent effects such as lowered initial reproduction, reduced early survival of calves, and subsequent calf, yearling and juvenile survival are used to justify the contention that there are too many herbivores. But such reasoning is flawed unless cause/effect relationships are established and the role of environmental variation is evaluated. We argue that it is overly simplistic to believe that every population’s subsequent performance and fate will follow a singular pattern with only one paramount factor driving and ultimately dictating an inevitable outcome. The relative importance of unpredictable abiotic factors in influencing and causing variation in the response of ungulate populations should be investigated, no matter whether those factors are sporadic or periodic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".