Abstract
Albatross bycatch has been increasing over the past decade in the US tuna longline fishery of the central North Pacific. A controlled field experiment was used to assess the efficacy of bird scaring or tori lines as a seabird bycatch mitigation measure for this fishery in a 3-factor sampling design with other mitigation methods (blue-dyed bait, offal discharge). A multilevel geoadditive Bayesian regression modeling approach was used to assess 3 albatross-gear interaction metrics (attempted contacts, contacts, captures) recorded for each longline set using an electronic monitoring system. We found albatross contacts with baited hooks were ca. 3 times (95% highest posterior density interval [HDI] 1–7) less likely for sets equipped with tori lines rather than without tori lines. Attempts to contact baited hooks were ca. 2 times (95% HDI 1–4) less likely for tori line-equipped sets. Albatrosses were also less likely to be captured in tori line sets but captures were too few to support strong inference compared with the contact rates. Tori lines were therefore found to be an effective management measure to mitigate albatross interactions in this fishery. Offal discharge during setting, however, was associated with higher seabird interactions—but that inference was not strong since offal discharge and blue-dyed bait were confounded treatments in some sets. Nonetheless, it was apparent that neither offal discharge nor blue-dyed bait was helpful in reducing albatross interactions in this trial and so the efficacy of those measures warrants further experimental investigation.
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Availability of data
The fisheries electronic monitoring data used in this study are owned by and are available from the U.S. government agency NOAA Fisheries and restrictions apply to their availability. Under the terms of a nondisclosure agreement with U.S. NOAA that the authors who analyzed the data had to execute, and under Sects. 1905 and 201–209 of Title 18 of the United States Code (referred to as the Trade Secrets Laws and Conflict of Interests Laws, respectively), the authors are prevented from making the U.S. government data publicly available.
Software availability
All statistical modeling software used in this study are cited in the Methods section.
References
Abraham E, Pierre J, Middleton D, Cleal J, Walker N, Waugh S (2009) Effectiveness of fish waste management strategies in reducing seabird attendance at a trawl vessel. Fish Res 95:210–219. https://doi.org/10.1016/j.fishres.2008.08.014
ACAP (2019) ACAP review and best practice advice for reducing the impact of Pelagic Longline Fisheries on seabirds agreement on the conservation of Albatrosses and Petrels Hobart, Australia
Ames R, Williams G, Fitzgerald S (2005) Using digital video monitoring systems in fisheries: application for monitoring compliance of seabird avoidance devices and seabird mortality in Pacific Halibut Longline Fisheries. NOAA Technical Memorandum NMFS‐AFSC‐152. Alaska Fisheries Science Center, National Marine Fisheries Service: Seattle
Anderson O, Small C, Croxall J et al (2011) Global seabird bycatch in longline fisheries. Endanger Species Res 14:91–106. https://doi.org/10.3354/esr00347
Baldwin S, Bauer D, Stice E, Rohde P (2011) Evaluating models for partially clustered designs. Psychol Methods 6:149–165. https://doi.org/10.1037/a0023464
Bergh M, Pikitch E, Skalski J, Wallace J (1990) The statistical design of comparative fishing experiments. Fish Res 9:143–163
Boggs C (2001) Deterring albatrosses from contacting baits during swordfish longline sets. In: Melvin E, Parish J (eds) Seabird Bycatch: Trends, Roadblocks and Solutions. University of Alaska Sea Grant, Anchorage, pp 79–94
Brothers N, Cooper J, Lokkeborg S (1999) The incidental catch of seabirds by Longline Fisheries: worldwide review and technical guidelines for mitigation. FAO Fisheries Circular 937. Food and Agriculture Organization of the United Nations, Rome
Bürkner P (2017) brms: an R package for Bayesian multilevel models using Stan. J Stat Softw 80:1–28. https://doi.org/10.18637/jss.v080.i01
Candlish J, Teare M, Dimairo M, Flight L, Mandefield L, Walters S (2018) Appropriate statistical methods for analysing partially nested randomised controlled trials with continuous outcomes: a simulation study. BMC Med Res Methodol 18:105. https://doi.org/10.1186/s12874-018-0559-x
Carpenter B, Gelman A, Hoffman M et al (2017) Stan: a probabilistic programming language. J Stat Softw 76:1–32
CCAMLR (2018) Minimisation of the incidental mortality of seabirds in the course of Longline Fishing or Longline Fishing Research in the convention area. Conservation Measure 25–02. Commission for the Conservation of Antarctic Marine Living Resources, Hobart, Australia
CCSBT (2020) Resolution to align CCSBT’s ecological related species measures with those of other Tuna RFMOs. Commission for the Conservation of Southern Bluefin Tuna, Hobart, Australia
Chalmers I (2007) The lethal consequences of failing to make use of all relevant evidence about the effects of medical treatments: the need for systematic reviews. In: Rothwell P (ed) Treating Individuals: from randomized trials to personalised medicine. Elsevier, London, pp 37–58
Chalmers I, Bracken M, Djulbegovic B et al (2014) How to increase value and reduce waste when research priorities are set. The Lancet 383:156–165
Cherel Y, Weimerskirch H, Duhamel G (1996) Interactions between longline vessels and seabirds in Kreguelen waters and a method to reduce seabird mortality. Biol Conserv 75:63–70. https://doi.org/10.1016/0006-3207(95)00037-2
Chordata (2019) Open source electronic monitoring for commercial fisheries. https://pt.chrdta.com/em/ and https://bitbucket.org/fisherieselectronicmonitoring/. Chordata, Juneau, Alaska
Congdon P (2003) Applied Bayesian modelling. Wiley
Cox T, Lewison R, Zydelis R, Crowder L, Safina C, Read A (2007) Comparing effectiveness of experimental and implemented bycatch reduction measures: the ideal and the real. Conserv Biol 21:1155–1164
Davies T, Jonsen I (2011) Identifying nonproportionality of fishery-independent survey data to estimate population trends and assess recovery potential for cusk (Brosme brosme). Can J Fish Aquat Sci 68:413–425
Delord K, Gasco N, Weimerskirch H, Barbraud C, Micol T (2005) Seabird mortality in the Patagonian toothfish longline fishery around Crozet and Kerguelen Islands, 2001–2003. CCAMLR Sci 12:53–80
Dias M et al (2019) Threats to seabirds: a global assessment. Bio Cons 237:525–537
Domingo A, Jiménez S, Abreu M, Forselledo R, Yates O (2017) Effectiveness of tori line use to reduce seabird bycatch in pelagic longline fishing. PLoS ONE 12:e0184465
Dorai-Raj S (2014) binom: Binomial confidence intervals for several parameterizations. R package version 1.1–1. https://CRAN.R-project.org/package=binom
Evans D (2003) Hierarchy of evidence: a framework for ranking evidence evaluating healthcare interventions. J Clin Nurs 12:77–84
Fahrmeir L, Lang S (2001) Bayesian inference for generalised additive mixed models based on Markov random field priors. Appl Stat 50:201–220
Gabry J, Simpson D, Vehtari A, Betancourt M, Gelman A (2019) Visualization in Bayesian workflow. J R Soc Ser A 182:1–14
Gelfand A, Schliep E (2016) Spatial statistics and Gaussian processes: a beautiful marriage. Spat Stat 18(Part A):86–104
Gelman A, Hill J (2007) Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, New York
Gelman A, Hwang J, Vehtari A (2014) Understanding predictive information criteria for Bayesian models. Stat Comput 24:997–1016
Gilman E, Boggs C, Brothers N (2003) Performance assessment of an underwater setting chute to mitigate seabird bycatch in the Hawaii pelagic longline tuna fishery. Ocean Coast Manag 46:985–1010
Gilman E, Brothers N, Kobayashi D (2005) Principles and approaches to abate seabird bycatch in longline fisheries. Fish Fish 6:35–49
Gilman E, Chaloupka M, Wiedoff B, Willson J (2014) Mitigating seabird bycatch during hauling by pelagic longline vessels. PLoS ONE 9:e84499
Gilman E, Chaloupka M, Peschon J, Ellgen S (2016) Risk factors for seabird bycatch in a pelagic longline tuna fishery. PLoS ONE 11:e0155477
Gilman E, Castejon V, Loganimoce E, Chaloupka M (2020) Capability of a pilot fisheries electronic monitoring system to meet scientific and compliance monitoring objectives. Mar Policy. https://doi.org/10.1016/j.marpol.2019.103792
Goad D (2017) Tori line designs for small longline vessels. New Zealand Department of Conservation, Wellington
Goad D, Debski I (2017) Tori line designs and specifications for small Pelagic Longline Vessels. WCPFC-SC13–2017/EB-WP-08 Rev 1. Western and Central Pacific Fisheries Commission, Kolonia, Federated States of Micronesia
Gray C, Kennelly S (2018) Bycatches of endangered, threatened and protected species in marine fisheries. Rev Fish Biol Fisheries 28:521–541
IATTC (2012) Resolution to mitigate the impact on seabirds of fishing for species covered by the IATTC. Resolution C-11–02. Inter-American Tropical Tuna Commission, La Jolla, USA
ICCAT (2011) Supplemental recommendation by ICCAT on reducing incidental by-catch of seabirds in ICCAT Longline Fishery. Recommendation 11–09. International Commission for the Conservation of Atlantic Tunas, Madrid
IOTC (2012) Resolution 12/06 on reducing the incidental bycatch of seabirds in Longline Fisheries. Resolution 12/06. Indian Ocean Tuna Commission, Mahe, Seychelles
IUCN (2021) The IUCN Red List of Threatened Species. Version 2020–3. www.iucnredlist.org, ISSN 2307–8235. International Union for the Conservation of Nature, Gland, Switzerland
Japan Ministry of Agriculture, Forestry and Fisheries (2008) Restrictions of Fishing Gear Specified by the Minister of Agriculture, Forestry, and Fisheries, Pursuant to the Provisions of Article 20–2 of the Ministerial Ordinance Regulating Specific Fisheries Permitted by the Minister. Minister of Agriculture, Forestry, and Fisheries Public Notice No.1193, July 25 (2008) In Japanese. Ministry of Agriculture, Forestry and Fisheries, Tokyo, Japan
Jensen S, Schaarschmidt F, Onofri A, Ritz C (2018) Experimental design matters for statistical analysis: how to handle blocking. Pest Manag Sci 74:523–534
Jimenez S, Domingo A, Abreu M, Brazeiro A (2012) Bycatch susceptibility in pelagic longline fisheries: Are albatrosses affected by the diving behaviour of medium-sized petrels? Aquat Conserv 22:436–445
Jimenez S, Domingo A, Winder H et al (2020) Towards mitigation of seabird bycatch: large-scale effectiveness of night setting and tori lines across multiple pelagic longline fleets. Bio Cons 247:108642
Kammann E, Wand M (2003) Geoadditive models. Appl Stat 52:1–18
Katsumata N, Okamoto K, Oshima K, Ochi D (2019) Research update about the effective design of Tori line for Japanese Small-scale Fleet in the North Pacific. WCPFC-SC15–2019/EB-WP-06. Western and Central Pacific Fisheries Commission, Kolonia, Federated States of Micronesia
Kay M (2020a) tidybayes: tidy data and geoms for Bayesian models. R package version 2(1):1. https://doi.org/10.5281/zenodo.1308151
Kay M (2020b) ggdist: visualizations of distributions and uncertainty. R package version 2.3.0. https://mjskay.github.io/ggdist/
Kelter R (2020) Analysis of Bayesian posterior significance and effect size indices for the two-sample t-test to support reproducible medical research. BMC Med Res Methodol 20:88. https://doi.org/10.1186/s12874-020-00968-2
Kezama K, Harada T, Deguchi T, Suzuki H, Watanuki Y (2019) Foraging behavior of black-footed albatross Phoebastria nigripes rearing chicks on the Ogasawara Islands. Ornithol Sci 18:27–37
Kruschke J, Liddell T (2018) The Bayesian new statistics: hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychon Bull Rev 25:178–206
Lemoine N (2019) Moving beyond noninformative priors: why and how to choose weakly informative priors in Bayesian analyses. Oikos 128:912–928
Lenth R (2016) Least-squares means: the R package lsmeans. J Stat Softw 69:1–33
Lenth R (2020) emmeans: estimated marginal means, aka least-squares means. R package version 1.5.2–1. https://CRAN.R-project.org/package=emmeans
Makowski D, Ben-Shachar M, Lüdecke D (2019) bayestestR: describing effects and their uncertainty, existence and significance within the Bayesian framework. J Open Source Softw 4:1541. https://doi.org/10.21105/joss.01541
McElderry H, Schrader J, McCullough D, Illingworth J, Fitzgerald S, Davis S (2004) Electronic monitoring of seabird interactions with trawl third‐wire cables on trawl vessels—a pilot study. NOAA Technical Memorandum NMFS‐AFSC‐147. Alaska Fisheries Science Center, National Marine Fisheries Service, Seattle
McElderry H, Beck M, Pria M, Anderson S (2011) Electronic monitoring in the New Zealand inshore trawl fishery: a pilot study. DOC Marine Conservation Services Series 9. Department of Conservation, Wellington
McNamara B, Torre L, Kaaialii G (1999) Hawaii Longline seabird mortality mitigation project. Western Pacific Regional Fishery Management Council, Honolulu
Melvin E, Guy T, Read L (2013) Reducing seabird bycatch in the South African joint venture tuna fishery using bird-scaring lines, branch line weighting and nighttime setting of hooks. Fish Res 147:72–82
Melvin E, Guy T, Read L (2014) Best practice seabird bycatch mitigation for pelagic longline fisheries targeting tuna and related species. Fish Res 149:5–18
Nakagawa S, Poulin R, Mengersen K, Reinhold K, Engqvist L, Lagisz M, Senior A (2015) Meta-analysis of variation: ecological and evolutionary applications and beyond. Methods Ecol Evol 6:143–152
New Zealand Ministry for Primary Industries (2020) Fisheries (Seabird Mitigation Measures—Surface Longlines) Circular (No. 2) (2019) Notice Number MPI 1111. Ministry for Primary Industries, Wellington
Pedersen T (2020) patchwork: the composer of plots. R package version 1.1.0. https://CRAN.R-project.org/package=patchwork
Phillips R, Gales R, Baker G et al (2016) The conservation status and priorities for albatrosses and large petrels. Bio Cons 201:169–183
Piasente M, Stanley B, Timmiss T, McElderry H, Pria M, Dyas M (2012) Electronic onboard monitoring pilot project for the eastern tuna and billfish fishery. FRDC Project 2009/048. ST‐IP‐05. Kolonia, Federated States of Micronesia: Western and Central Pacific Fisheries Commission
Pierre J (2018) Using electronic monitoring imagery to characterize protected species interactions with commercial fisheries: a primer and review. JPEC Ltd, Lower Hutt, New Zealand
Pierre J, Abraham E, Richard Y, Cleal J, Middleton D (2012) Controlling trawler waste discharge to reduce seabird mortality. Fish Res 131:30–38
South Africa Department of Agriculture, Forestry and Fisheries (2019) Section B. Permit Conditions: Large Pelagic Longline Fishery. Fishing Season: 2019/2020. Department of Agriculture, Forestry and Fisheries, Pretoria
Sato N, Katsumata N, Yokota K, Uehara T, Fusejima I, Minami H (2016) Tori-lines with weighted branch lines reduce seabird bycatch in eastern South Pacific longline fishery. Aquat Conserv Mar Freshwat Ecosyst 26:95–107
Searle S, Speed F, Milliken G (1980) Population marginal means in the linear model: an alternative to least squares means. Am Stat 34:216–221
Sutton A, Abrams K, Jones D, Sheldon T, Song F (2000) Methods for meta-analysis in medical research. Wiley, New York
Tuyl F, Gerlach R, Mengersen K (2008) Comparison of Bayes-Laplace, Jeffreys, and other priors: the case of zero events. Am Stat 62:40–44
Uruguay Direccion Nacional de Recursos Acuqticos (2015) Revision de Planes de Accion Nacional para la conservacion de Aves Marinas y Condrictios en las Pesquerias Uruguayas. Direccion Nacional de Recursos Acuqticos, Ministerio de Ganaderia Agricultura y Pesca, Montevideo
Vehtari A, Gelman A, Gabry J (2017) Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput 27:1413–1432. https://doi.org/10.1007/s11222-016-9696-4
WCPFC (2018) Conservation and Management Measure to Mitigate the Impact of Fishing for Highly Migratory Fish Stocks on Seabirds. CMM 2018–03. Western and Central Pacific Fisheries Commission, Kolonia, Federated States of Micronesia
Wickham H (2016) ggplot2: elegant graphics for data analysis, 2nd edn. Springer, New York
Wood S (2006) Generalized additive models: an introduction with R. Chapman and Hall/CRC, Boca Raton
WPRFMC (2020) Annual Stock Assessment and Fishery Evaluation Report for U.S. Pacific Island Pelagic Fisheries Ecosystem Plan 2019. Western Pacific Regional Fishery Management Council, Honolulu
Yao Y, Vehtari A, Simpson D, Gelman A (2018) Using stacking to average Bayesian predictive distributions (with discussion). Bayesian Anal 13:917–1003. https://doi.org/10.1214/17-BA1091
Yokota K, Minami H, Kiyota M (2011) Effectiveness of tori-lines for further reduction of incidental catch of seabirds in pelagic longline fisheries. Fish Sci 77:479–485. https://doi.org/10.1007/s12562-011-0357-4
Zeileis A, Fisher J, Hornik K, Ihaka R, McWhite C, Murrell P, Stauffer R, Wilke C (2020) colorspace: a toolbox for manipulating and assessing colors and palettes. J Stat Softw 96:1–4. https://doi.org/10.18637/jss.v096.i01
Acknowledgements
We are grateful to the captains, crew and owners of the participating fishing vessels Janthina, St. Marianne, St. Damien, Queen Diamond 2, Queen Alina, Golden Phoenix, and Hawaii Ocean. We thank David Goad of Vita Maris, and Daisuke Ochi and Haruka Hayashi of the Japan Fisheries Research and Education Agency for advice on tori line designs and materials. We thank John Wang, U.S. National Marine Fisheries Service, for his contributions to the study. Sean Martin of Pacific Ocean Producers kindly provided access to their warehouse to build tori lines. Lizzie Pearmain of BirdLife International kindly assisted with providing access to albatross distribution data.
Funding
EG, MC and HN received funding from the Western Pacific Regional Fishery Management Council for this study. This project was supported by the NOAA Cooperative Research Program through NOAA and Council Award NA15NMF4410066, the Joint Institute for Marine and Atmospheric Research, and the Pacific Islands Fisheries Science Center.
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Gilman, E., Chaloupka, M., Ishizaki, A. et al. Tori lines mitigate seabird bycatch in a pelagic longline fishery. Rev Fish Biol Fisheries 31, 653–666 (2021). https://doi.org/10.1007/s11160-021-09659-7
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DOI: https://doi.org/10.1007/s11160-021-09659-7