Using repeat citizen science surveys of koalas to assess their population trend in the north-west of New South Wales: scale matters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scale matters when assessing population trends. Whereas traditional field-based ecological surveys are generally restricted to small temporal and spatial scales, community (citizen science) surveys allow wider consideration of population trends. We used repeat community surveys (completed in 2006 and 2015) to assess population change in koalas (Phascolarctos cinereus) across an area of 36 900 km2 in the north-west of New South Wales. In both community surveys we asked respondents to record the location of their koala sightings as well as those of eight other common species. We further asked respondents about their perceptions of population change. Through three different measures (likelihood of koala occurrence, number of koalas observed per respondent, and the perception of population change), we found that koala numbers were declining across the region during the study period. The timing and broad and consistent geographic spread of the decline suggests that broad-scale environmental factors, such as weather, are important drivers of this change. This information will allow managers to place conservation efforts into an appropriate spatial context. While such information sourced from the community can provide critical information on threatened species, including the koala, this study highlights the limits of such information.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it