How safe is mist netting? evaluating the risk of injury and mortality to birds
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
Summary 1. The capture of birds using mist nets is a widely utilized technique for monitoring avian populations. While the method is assumed to be safe, very few studies have addressed how frequently injuries and mortalities occur and the associated risks have not been formally evaluated. 2. We quantified the rates of mortality and injury at 22 banding organizations in the United States and Canada and used capture data from five organizations to determine what kinds of incidents occur most frequently. Analyses focused on passerines and near‐passerines, but other groups were included. We evaluated whether body mass, age, sex, mist net mesh size, month and time of day or frequency of capture are related to the risk or type of incident. We also compared the recapture histories over time between birds that were injured and those that were never injured for 16 species. 3. The average rate of injury was 0·59%, while mortality was 0·23%. Birds captured frequently were less at risk to incident. Body mass was positively correlated with incident and larger birds were at greater risk to predation, leg injuries, broken legs, internal bleeding and cuts, while smaller birds were more prone to stress, tangling‐related injuries and wing strain. Rates of incident varied among species, with some at greater risk than others. We found no evidence for increased mortality over time of injured birds compared with uninjured birds. 4. We provide the first comprehensive evaluation of the risks associated with mist netting. Our results indicate that (1) injury and mortality rates below one percent can be achieved during mist netting and (2) injured birds are likely to survive in comparable numbers to uninjured birds after release. While overall risks are low, this study identified vulnerable species and traits that may increase a bird’s susceptibility to incident that should be considered in banding protocols aimed at minimizing injury and mortality. Projects using mist nets should monitor their performance and compare their results to those of other organizations.
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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 | 0.003 | 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 it