Enhancing coastal migratory shorebird conservation through the Shorebird Stopover and Staging Habitat Quality Index (SSSHQI) : A proof of concept and pre-feasibility study
Bibliographic record
Abstract
Shorebirds are an ecologically important group of organisms that are experiencing global widespread population declines. A leading driver of population declines is the loss of important coastal habitats, especially tidal flats at staging and stopover sites. To increase understanding about the condition of globally distributed coastal shorebird habitats and prevent further loss of these species, a novel habitat quality assessment framework termed the “Shorebird Stopover and Staging Habitat Quality Index” (SSSHQI) was developed. The index’s purpose was to estimate the relative quality of coastal habitats used by migratory shorebirds thereby allowing for more informed conservation planning and efficient allocation of resources for management. Biophysical and distributional habitat quality proxy measures related to foraging and roosting habitats were selected for the SSSHQI, which combined the measures into a single numerical value representative of relative habitat quality. As a proof of concept, the SSSHQI was applied to two case study sites: the Fraser River Estuary, Canada and Port Curtis, Australia. Following this, a pre-feasibility study was employed to explore the SSSHQI’s strengths, limitations, and viability as a tool for shorebird conservation. The results of implementing the SSSHQI suggested that both case study sites were “Good” quality habitats, each with strengths and deficiencies related to foraging and roosting habitat. The pre-feasibility analysis revealed that multiple aspects of the index that measure roosting site quality and shorebird diversity, rely considerably on previously collected data. When these data requirements were met the SSSHQI’s proxies were simple, low-cost, and informative measures to assess and compare the relative quality of different coastal shorebird habitats. However, adjusting scoring schemes to account for site-specific differences in tidal flat morphology and refining proxy measures to consider important upper tidal flat areas would improve the SSSHQI’s accuracy and increase its utility as a tool for understanding and comparing the quality of coastal shorebird staging and stopover habitats.
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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 | 0.001 | 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 | 0.000 |
| 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".