Estimating the population size of a threatened arboreal marsupial: use of distance sampling to dispense with ad hoc survey techniques
Bibliographic record
Abstract
Context. Long-term land-use decisions potentially affecting the conservation status of rare fauna are often based on a dearth of relevant biological information and population estimates are regularly derived from ad hoc methodologies. This can significantly affect the outcomes from development assessment and approval processes. Aim. Our aims were to apply distance-sampling techniques to derive robust, quantitative estimates of the population size of a threatened arboreal marsupial, the western ringtail possum (Pseudocheirus occidentalis Thomas, 1888), demonstrate the advantages of this approach and, in doing so, provide conservation managers, decision makers and consultants with a reliable framework for surveying the species. Methods. We used line-transect sampling to derive estimates of density and abundance for P. occidentalis at two sites in south-western Western Australia where estimates were previously derived through ad hoc techniques. Key results. Our findings support the assertion that previous surveys of P. occidentalis populations have underestimated the population size to a varying extent at both of our survey sites. Land-use and development-application decisions have previously been based on similar surveys. Conclusions. Distance sampling, if applied routinely when surveying P. occidentalis, will reduce the uncertainty associated with derived estimates of abundance. Implications. Appropriate use of distance-sampling methods will enable managers and decision makers to assess more quantitatively the potential effect from, and place appropriate approval conditions on, proposals that modify or destroy P. occidentalis habitat. The use of the program Distance will enable such decisions to be based on robust, repeatable estimates of population size, with quantified confidence limits and variance estimates.
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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 | 0.003 | 0.002 |
| 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) | 0.000 | 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".