An approach to assess the potential impacts of human disturbance on wintering tropical shorebirds
Bibliographic record
Abstract
Abstract Numerous studies have documented behavioural changes in wildlife because of human disturbance. Disturbance may threaten waders if there are no alternative habitats or foraging times. Here we compared human and dog densities, natural and anthropogenic disturbance rates, prey availability and wader foraging rates at five sites in and around Khao Sam Roi Yod National Park, Thailand, with different shorebird densities, to assess whether disturbance forced wintering waders to under-use high quality sites consistently. We also examined diel and tidal variability in prey densities and tested whether people and dogs cause temporary displacement or reductions in foraging rates. Although there were significant differences in shorebird, human and dog densities as well as anthropogenic disturbance rates and prey availability amongst the five sites, there was no indication that birds were being displaced from the highest quality habitat. There was little diel or tidal variation in most types of prey. People did not temporarily displace waders but did reduce foraging rates. The availability of high quality, alternative foraging habitat with low human disturbance, and nocturnal prey availability, along with the lack of any short-term displacement of birds from areas of high disturbance suggest that disturbance is unlikely to affect wader fitness in this National Park. By examining a range of important habitat characteristics and wader spatial distributions, our study demonstrates a method and a theoretical framework to evaluate the possible impacts of human disturbance on wildlife.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".