Nest-tree selection by the threatened brush-tailed phascogale (Phascogale tapoatafa) (Marsupialia : Dasyuridae) in a highly fragmented agricultural landscape
Bibliographic record
Abstract
The conservation of roosting and nesting resources is of critical concern for many hollow-dependent species around the world. We investigated the nest-tree requirements of the threatened brush-tailed phascogale (Phascogale tapoatafa) in a highly cleared agricultural landscape in south-eastern Australia. We documented the physical characteristics of selected nest trees and describe the spatial and temporal patterns of nest-tree use as revealed by radio-tracking. Nine phascogales (seven females, two males) were radio-tracked between March and July 1999 in an area where most woodland habitat is confined to linear strips along roads and streams or small patches and scattered trees in cleared farmland. Female phascogales were monitored for 13–35 days over periods of 5–15 weeks and two males were monitored for 2 and 9 days respectively. A total of 185 nest-tree fixes was collected and all nests occupied by phascogales were in standing trees. Eighty-three nest trees were identified, ranging in diameter at breast height (dbh) from 25 to 171 cm, with a mean dbh for the trees used by each individual phascogale of >80 cm. Phascogales did not discriminate between canopy tree species in selecting nest trees, but showed highly significant selection for trees in the largest size class. All individuals used multiple nest trees, with the seven females occupying an average of 11.4 nest trees from a mean of 25 diurnal locations. The number of nest trees continued to increase throughout the study, suggesting that more would be identified during a longer or more intensive study. Occupied nest trees were located throughout each individual’s home range, highlighting the importance of a continuous spatial distribution of suitable nest trees across the landscape. Nest trees were also located in adjacent farmland up to 225 m from roadside vegetation, demonstrating the value that scattered clumps and even single trees in farmland can have for wildlife conservation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".