The continued decline of the Palila ( Loxioides bailleui ) on Mauna Kea, Island of Hawaiʻi
Bibliographic record
Abstract
Palila (Loxioides bailleui) are critically endangered Hawaiian honeycreepers specializing on māmane (Sophora chrysophylla) seeds and restricted to Mauna Kea volcano on the Island of Hawaiʻi. Recently, the population was estimated to decline by 89% between 1998 and 2021, despite decades of ungulate removal, fence construction, māmane regeneration, fire suppression, and predator control. To inform managers with the most recent update on the status and trends of the Palila population, we analyzed annual bird survey data collected using point-transect distance sampling since 1998, including new annual survey data from 2022, 2023, and 2024. Prior to analysis, we predicted the population trajectory would change between 2021 and 2024 because of continued management actions promoting habitat recovery. We used distance sampling, log-linear regression, and state-space modeling to produce the new estimates and analyze trends across the time series. The 2022 population estimate was 367 to 742 birds (95% confidence interval; point estimate: 545), the lowest in recorded history. The 2023 and 2024 estimates of 374 to 842 birds (point estimate: 596) and 412 to 970 birds (point estimate: 666) were the second and third lowest in our time series, respectively. Our estimates for years before 2022 show population fluctuations between 4000 to 6800 birds from 1998 to 2005, then a steep decline through 2010. For the next decade, abundance fluctuated around 1000 birds, before declining again in 2021 to less than 700 birds. From 1998 to 2024, the population declined by more than 90%, or 205 birds per year, with 100% statistical support for an overall downward trend, despite significant management efforts and research. The greatest threats facing the Palila, if familiar, are not being eliminated swiftly enough to promote their recovery. The currently small and range-limited population is vulnerable to future climate-related events such as drought and fire. Continued monitoring can help to assess the response of Palila to adaptive management actions and changing environmental conditions.
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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".