As part of our work to create a bycatch assessment toolkit, we’ve developed a simulation platform called ‘SCOTI’ to guide the design of bycatch monitoring and mitigation trials across CIBBRiNA case studies.
By modelling realistic fishing conditions, species risk profiles, and monitoring constraints, the platform helps researchers understand how different sampling strategies affect accuracy, precision, and the power to detect the impacts of mitigation measures. This approach is especially valuable for rare or irregular bycatch events which are very challenging to estimate precisely using traditional statistical methods.
Our new report explains how SCOTI works, and provides results based on its application to a variety of fishing conditions.
Result highlights
- Bycatch rarity drives monitoring needs. When bycatch is very rare or includes occasional large events, much higher monitoring coverage is required to achieve precise and unbiased estimates.
- SCOTI supports the planning of bycatch mitigation trials. The platform can estimate power and required sample sizes, even when early trial phases detect no bycatch, helping to design efficient and statistically robust trials.
- It is far better to monitor a little across many vessels than to monitor a lot on just a few, because vessels often differ more than expected. Even small amounts of data from normally unmonitored vessels can greatly improve the overall picture of fleet-wide bycatch.
- Accurate results depend on how monitoring is spread out, as shown by applying SCOTI to our deepwater longline case study. Observing whole hauls works best, but if that is not possible, collecting information at the smaller “segment” level can still improve reliability.
Read the full report here, or access SCOTI directly.