Bycatch loss
Salvin's albatross
Salvin's albatross
Photo credit: Frans Lanting

Seabird bycatch loss rate variability in pelagic longline fisheries by Zhou et al

doi:10.1016/j.biocon.2020.108590

Background The incidental mortality of seabirds from fisheries ranks as the greatest threat impacting seabirds globally.

Problem statement However, its impact on seabird populations may have been substantially underestimated due to lost, undetected bycatch. To estimate the full extent of the bycatch problem, knowledge about the magnitude and variability of lost bycatch is necessary.

Contribution Based on a long-term dataset, this study aims to facilitate the loss-corrected bycatch estimates for pelagic longline fisheries that do not have a concurrent bycatch loss observation component. We analyze information from all types of fishery interactions of seabirds to improve the estimate of bycatch loss rate and also reveal its variability. Specifically, we analyze how environmental and ecological factors affect seabird bycatch loss rate using Bayesian state-space models. Results show strong species effects in the bycatch loss rate. Inclement weather and strong competition among seabird species also affect bycatch loss rate.

Recommendations Estimates of the species-specific bycatch loss rate indicate that, for some species, the loss can well exceed the average loss rate, suggesting that seabird bycatch loss cannot be further ignored in assessing the fishery impact on seabird populations. To gauge the full scale of seabird bycatch, it is critical to account for this lost bycatch in bycatch assessments, at minimum, using an average loss rate with the ultimate goal of species-specific loss-corrected assessments.

This is the first publication in this series of studies to unravel the difficulties in documenting seabird bycatch in pelagic longline fisheries. The next two studies analyze the interaction frequency and bycatch vulnerability part of the bycatch process, respectively.

The term "bycatch loss" needs some explanation. Here, "bycatch loss" is the difference between (a) the number of seabirds captured and (b) the number of seabird bycatches recorded by an observer with a traditional haul-only observation protocol tasked to collect any catch/bycatch at gear retrieval. Most seabirds are captured at the gear deployment (aka line setting), which is followed by hours of line soaking and line hauling. A few things could happen between the capture of a seabird and the documentation of its capture at gear retrieval:

  1. Consumption by sharks
  2. Physically torn off the hook
  3. Escaped with/without injuries
  4. Bycatch concealment by crew

The bycatch loss examined here only estimates the loss from the first 3 factors. The last factor is a human factor that can be dealt with more efficiently by other means, and in this study, the crew were specifically asked not to discard any seabird caught, and NB is experienced enough not to be tricked by the crew. 😎

This modeling study is directly based on Nigel's seminal work on revealing a shocking ~50% seabird bycatch loss in traditional observer programs. The contribution of this modeling work is exploring the variation of bycatch loss with biological and spatial-temporal factors with the goal of providing a more accurate loss rate to be used in bycatch assessments. Nigel's original work provides a raw estimate of the loss rate, and here we provide a standardized estimate of it. This is similar to the standardization of CPUE indices if you are familiar with that.

I hope I have provided enough motivation for you to download the full paper and read it yourself. Here is the link:
https://doi.org/10.1016/j.biocon.2020.108590
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