Bycatch mortality can cause extirpation in four freshwater turtle species
Bibliographic record
Abstract
Abstract Bycatch of non‐target species in commercial fishing nets can have adverse impacts on their populations. Freshwater turtle populations are particularly susceptible to increases in adult mortality, and freshwater turtles are among the most threatened vertebrates. As a case study, the population‐level impacts of bycatch mortality on freshwater turtles were evaluated in Lake Opinicon, Ontario, Canada, a lake that supports a small‐scale commercial fishery. Using population viability analyses, the impacts of bycatch on common snapping turtles ( Chelydra serpentina ), eastern musk turtles ( Sternotherus odoratus ), northern map turtles ( Graptemys geographica ), and painted turtles ( Chrysemys picta ) were evaluated. In all four species, even low levels of additional annual female mortality as a result of bycatch were sufficient either to reduce population size or to cause extirpation of the local population within 500 years. Bycatch reduction programmes, such as seasonal closures and implementation of bycatch reduction devices, can help alleviate the risk of extirpation. Changes to fishing season length could help reduce the number of snapping turtles and musk turtles captured. Installation of simple bycatch reduction devices can exclude between 95% and 100% of snapping turtles and between 0% and 97% of the other three species, depending on the width of the exclusion device. If combined, these two bycatch reduction methods would help prevent adult female mortality and help maintain turtle populations in Lake Opinicon. Although these findings are specific to the study area, the same principles apply to other areas where similar simple bycatch reduction strategies can be employed to prevent the extirpation of other freshwater turtle species. Considering the consequences of bycatch and of bycatch reduction programmes on populations provides managers with important information to support development of risk‐averse conservation strategies. Copyright © 2014 John Wiley & Sons, Ltd.
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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) | 0.002 | 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 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".