Using opportunistic records from a recreational fishing magazine to assess population trends of sharks
Bibliographic record
Abstract
Detecting and determining changes in the occurrence and abundance of species is a priority for effective management of resources and for conservation of biodiversity. In the absence of long-term monitoring data, potential population declines may be very difficult to establish. Therefore, alternative information on occurrence of species to infer population trends is highly valued. Records of sharks (i.e., Notorynchus cepedianus, Carcharias taurus, Galeorhinus galeus, and Carcharhinus brachyurus) off northern Argentina from a recreational fishing magazine (Weekend), between 1973 and 2008, were reviewed with the aim of evaluating population trends with opportunistic data sources. For each shark species, the number of occurrences per year in the magazine was registered. Our analyses were based on a nonprobabilistic method (McPherson and Myers’ approach) designed to determine population trends with opportunistic sighting records. In this approach we included the number of classified ads offering fishing guide services published per year in the magazine as a measure of observation effort. For each species, we fitted generalized linear models with a Poisson error structure and a log link, where the response variable was the number of occurrences per year, the explanatory variable was the year, and the logarithm of the number of fishing guide ads was specified as an offset in each model. For both approaches, the models estimated that populations of the four shark species have suffered declines. Estimates produced by these models will help to determine the magnitude of population changes where a paucity of data prevents more precise analysis.
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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) | 0.001 | 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 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".