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Quantifying fishing activity targeting subsea pipelines by commercial trap fishers

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Abstract

Over 1400 km of oil and gas pipeline infrastructure exists within the boundaries of the Pilbara Trap Managed Fishery (PTMF) operating on the North West Shelf of Australia. Some of this infrastructure has reached the end of its operational life and requires decommissioning. Location and speed data collected from 2008 to 2018 using vessel monitoring systems onboard all trap fishing vessels (n = 3) operating in the PTMF were used to understand how fishing activity near pipelines has changed through time, and to identify the best predictive variables to explain hours spent fishing km−2 week−1. The proportion of fishing activity within 200 m of a pipeline increased over the survey decade and averaged 4.2% across all years. Hours spent fishing km−2 within 200 m of any pipeline was found to be 8.0 h km−2, ~ 11.4 times more than that recorded, on average, for the remaining area of the PTMF (0.7 h km−2), and ~ 4.6 times more than the western portion of the PTMP (1.7 h km−2) where all pipeline infrastructure exists. Fishing activity within 1 km of pipelines increased after their installation, and hence time since installation was the best predictor of fishing. This study demonstrated that trap fishers in the PTMF allocate a small proportion of their time targeting pipeline infrastructure, with the area close to a pipeline experiencing a relatively greater magnitude of fishing than that elsewhere in the PTMF. As such, the results of this study provide decision makers with an understanding of the intrinsic value of this infrastructure to trap fishers.

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References

  • Baine M (2001) Artificial reefs: a review of their design, application, management and performance. Ocean Coast Manag 44:241–259

    Article  Google Scholar 

  • Bohnsack JA, Harper DE, McClellan DB, Hulsbeck M (1994) Effects of reef size on colonization and assemblage structure of fishes at artificial reefs off southeastern Florida, U.S.A. Bull Mar Sci 55:796–823

    Google Scholar 

  • Bond T, Langlois TJ, Partridge JC et al (2018a) Diel shifts and habitat associations of fish assemblages on a subsea pipeline. Fish Res 206:220–234. https://doi.org/10.1016/j.fishres.2018.05.011

    Article  Google Scholar 

  • Bond T, Partridge JC, Taylor MD et al (2018b) Fish associated with a subsea pipeline and adjacent seafloor of the North West Shelf of Western Australia. Mar Environ Res 141:53–65. https://doi.org/10.1016/j.marenvres.2018.08.003

    Article  PubMed  CAS  Google Scholar 

  • Bond T, Partridge JC, Taylor MD et al (2018c) The influence of depth and a subsea pipeline on fish assemblages and commercially fished species. PLoS ONE 13:e0207703. https://doi.org/10.1371/journal.pone.0207703

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Bond T, Prince J, Partridge JC, White D, Mclean DL (2018d) The Value of Subsea Pipelines to Marine Biodiversity. Offshore Technology Conference Asia. http://www.onepetro.org/doi/10.4043/28240-MS

  • Bureau of Safety and Environmental Enforcement (2013) “Rigs-to-Reefs” Policy. Environmental Enforcement Division, United Stated of America

  • Campbell MS, Stehfest KM, Votier SC, Hall-Spencer JM (2014) Mapping fisheries for marine spatial planning: gear-specific vessel monitoring system (VMS), marine conservation and offshore renewable energy. Mar Policy 45:293–300. https://doi.org/10.1016/j.marpol.2013.09.015

    Article  Google Scholar 

  • Chandler J, White D, Techera EJ et al (2017) Engineering and legal considerations for decommissioning of offshore oil and gas infrastructure in Australia. Ocean Eng 131:338–347. https://doi.org/10.1016/j.oceaneng.2016.12.030

    Article  Google Scholar 

  • Charles C, Gillis D, Wade E (2014) Using hidden Markov models to infer vessel activities in the snow crab (Chionoecetes opilio) fixed gear fishery and their application to catch standardization. Can J Fish Aquat Sci 71:1817–1829. https://doi.org/10.1139/cjfas-2013-0572

    Article  Google Scholar 

  • Claisse JT, Pondella DJ, Love MS et al (2014) Oil platforms off California are among the most productive marine fish habitats globally. Proc Natl Acad Sci USA 111:15462–15467. https://doi.org/10.1073/pnas.1411477111

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Commonwealth of Australia (2019) Offshore Petroleum and Greenhouse Gas Storage Act 2006. Attorney-General’s Department

  • de Groot SJ (1982) The impact of laying and maintenance of offshore pipelines on the marine environment and the North Sea fisheries. Ocean Manag 8:1–27. https://doi.org/10.1016/0302-184X(82)90011-7

    Article  Google Scholar 

  • Department of Industry, Innovation and Science (2018) Offshore Petroleum Decommissioning Guideline

  • Department of Mines, Industry Regulation and Safety (2019) WAPPIPE

  • Enever R, Lewin S, Reese A, Hooper T (2017) Mapping fishing effort: combining fishermen’s knowledge with satellite monitoring data in English waters. Fish Res 189:67. https://doi.org/10.1016/j.fishres.2017.01.009

    Article  Google Scholar 

  • FAO (2008) Fisheries self-governance: new directions in fisheries management. Case Stud Fish self-governance FAO Fish Tech Pap No 504 1–19

  • Feist BE, Samhouri JF, Forney KA, Saez LE (2021) Footprints of fixed-gear fisheries in relation to rising whale entanglements on the US West Coast. Fish Manag Ecol Fme. https://doi.org/10.1111/fme.12478

    Article  Google Scholar 

  • Fisher R, Wilson SK, Sin TM et al (2018) A simple function for full-subsets multiple regression in ecology with R. Ecol Evol. https://doi.org/10.1002/ece3.4134

    Article  PubMed  PubMed Central  Google Scholar 

  • Fitzpatrick BM, Harvey ES, Heyward AJ et al (2012) Habitat specialization in tropical continental shelf demersal fish assemblages. PLoS ONE 7:e39634. https://doi.org/10.1371/journal.pone.0039634

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Fock HO (2008) Fisheries in the context of marine spatial planning: defining principal areas for fisheries in the German EEZ. Mar Policy 32:728–739. https://doi.org/10.1016/j.marpol.2007.12.010

    Article  Google Scholar 

  • Gerritsen H, Lordan C (2011) Integrating vessel monitoring systems (VMS) data with daily catch data from logbooks to explore the spatial distribution of catch and effort at high resolution. ICES J Mar Sci 68:245–252. https://doi.org/10.1093/icesjms/fsq137

    Article  Google Scholar 

  • Hamzah BA (2003) International rules on decommissioning of offshore installations: some observations. Mar Policy 27:339–348. https://doi.org/10.1016/S0308-597X(03)00040-X

    Article  Google Scholar 

  • Hart DR (2002) Yield-and biomass-per-recruit analysis for rotational fisheries, with an application to the Atlantic sea scallop (Placopecten magellanicus)

  • Hart A, Murphy D, Syers C, Kalinowski P (2019) Sea Cucumber resource status report 2018. In: Gaughan DJ, Santoro K (eds) Status reports of the fisheries and aquatic resources of Western Australia 2016/17: The State of the Fisheries. Department of Primary Industries and Regional Development, Western Australia, pp 136–138

  • Hijmans RJ (2019) raster: Geographic Data Analysis and Modeling. R package version 3.0-7. https://CRAN.R-project.org/package=raster

  • Hijmans RJ (2019) geosphere: spherical trigonometry. R package version 1.5-10. pp 1–40. https://CRAN.R-project.org/package=geosphere

  • IMO (1989) International Maritime Organization, Guidelines and Standards for the Removal of Offshore Installations and Structures on the Continental Shelf and in the Exclusive Eeconomic Zone (IMO resolution a.672 (16))

  • Keitt TH, Bivand R, Pebesma E, Rowlingson B (2009) The rgdal Package: Bindings for the Geospatial Data Abstraction Library. 4

  • Kim K, Lee KM (2020) Convolutional neural network-based gear type identification from automatic identification system trajectory data. Appl Sci 10:4010. https://doi.org/10.3390/app10114010

    Article  CAS  Google Scholar 

  • Leckie SHF, Draper S, White DJ et al (2015) Lifelong embedment and spanning of a pipeline on a mobile seabed. Coast Eng 95:130–146. https://doi.org/10.1016/j.coastaleng.2014.10.003

    Article  Google Scholar 

  • Lee J, South AB, Jennings S (2010) Developing reliable, repeatable, and accessible methods to provide high-resolution estimates of fishing-effort distributions from vessel monitoring system (VMS) data. ICES J Mar Sci 67:1260–1271. https://doi.org/10.1093/icesjms/fsq010

    Article  Google Scholar 

  • Lowden R (2005) Management of Queensland sea cucumber stocks. Beche-de-Mer Inf Bull 2005–2005

  • Marzuki MI, Gaspar P, Garello R et al (2018) Fishing gear identification from vessel-monitoring-system-based fishing vessel trajectories. IEEE J Ocean Eng 43:689–699. https://doi.org/10.1109/JOE.2017.2723278

    Article  Google Scholar 

  • McLean DL, Partridge JC, Bond T et al (2017) Using industry ROV videos to assess fish associations with subsea pipelines. Cont Shelf Res 141:76–97. https://doi.org/10.1016/j.csr.2017.05.006

    Article  Google Scholar 

  • Mills CM, Townsend SE, Jennings S et al (2007) Estimating high resolution trawl fishing effort from satellite-based vessel monitoring system data. ICES J Mar Sci 64:248–255. https://doi.org/10.1093/icesjms/fsl026

    Article  Google Scholar 

  • Mullowney DR, Dawe EG (2009) Development of performance indices for the Newfoundland and Labrador snow crab (Chionoecetes opilio) fishery using data from a vessel monitoring system. Fish Res 100:248–254. https://doi.org/10.1016/j.fishres.2009.08.006

    Article  Google Scholar 

  • Newman SJ (2002) Growth rate, age determination, natural mortality and production potential of the scarlet seaperch, Lutjanus malabaricus Schneider 1801, off the Pilbara coast of north-western Australia. Fish Res 58:215–225. https://doi.org/10.1016/S0165-7836(01)00367-8

    Article  Google Scholar 

  • Newman SJ, Dunk IJ (2003) Age validation, growth, mortality, and additional population parameters of the goldband snapper (Pristipomoides multidens) off the Kimberley coast of northwestern Australia. Fish Bull 101:116–128

    Google Scholar 

  • Newman SJ, Skepper CL, Mitsopoulos GEA et al (2011) Assessment of the potential impacts of trap usage and ghost fishing on the Northern Demersal Scalefish Fishery. Rev Fish Sci 19:74–84. https://doi.org/10.1080/10641262.2010.543961

    Article  Google Scholar 

  • Newman SJ, Brown JI, Fairclough DV et al (2018) A risk assessment and prioritisation approach to the selection of indicator species for the assessment of multi-species, multi-gear, multi-sector fishery resources. Mar Policy 88:11–22. https://doi.org/10.1016/j.marpol.2017.10.028

    Article  Google Scholar 

  • Newman SJ, Wakefield C, Skepper C, et al (2019) North coast demersal resource status report 2017. In: Gaughan DJ, Santoro K (eds) Status reports of the fisheries and aquatic resources of Western Australia 2016/17: The State of the Fisheries. Department of Primary Industries and Regional Development, Western Australia, pp 125–133

  • Oil & Gas UK (2013) Decommissioning of Pipelines in the North Sea Region 2013

  • Pebesma EJ, Bivand RS (2005) Classes and methods for spatial data in R. R News 5:9–13

    Google Scholar 

  • Rijnsdorp AD, Buys AM, Storbeck F, Visser EG (1998) Micro-scale distribution of beam trawl effort in the southern North Sea between 1993 and 1996 in relation to the trawling frequency of the sea bed and the impact on benthic organisms. ICES J Mar Sci 55:403–419. https://doi.org/10.1006/jmsc.1997.0326

    Article  Google Scholar 

  • Rouse S, Hayes P, Wilding TA (2018a) Commercial fisheries losses arising from interactions with offshore pipelines and other oil and gas infrastructure and activities. ICES J Mar Sci. https://doi.org/10.1093/icesjms/fsy116

    Article  Google Scholar 

  • Rouse S, Kafas A, Catarino R, Peter H (2018b) Commercial fisheries interactions with oil and gas pipelines in the North Sea: considerations for decommissioning. ICES J Mar Sci 75:279–286. https://doi.org/10.1093/icesjms/fsx121

    Article  Google Scholar 

  • Sainsbury KJ, Campbell RA, Lindholm R, Whitelaw AW (1997) Experimental management of an Australian multi-species fishery: examining the possibility of trawl-induced habitat modification. Am Fish Soc Symp 20:107–112

    Google Scholar 

  • Sluczanowski PR (1984) A management oriented model of an abalone fishery whose substocks are subject to pulse fishing. Can J Fish Aquat Sci 41:1008–1014. https://doi.org/10.1139/f84-117

    Article  Google Scholar 

  • Smith JA, Lowry MB, Champion C, Suthers IM (2016) A designed artificial reef is among the most productive marine fish habitats: new metrics to address ‘production versus attraction.’ Mar Biol 163:1–8. https://doi.org/10.1007/s00227-016-2967-y

    Article  Google Scholar 

  • Speare P, Stowar M (2007) Preliminary findings from the first baseline survey of the Magnetic Shoals Project Progress Report

  • Sumer BM, Fredsøe J (2002) The mechanics of scour in the marine environment. World Scientific, Singapore

    Book  Google Scholar 

  • Sunarmo, Affandi A, Sumpeno S (2021) Clustering spatial temporal distribution of fishing vessel based lOn VMS data using K-means. Institute of Electrical and Electronics Engineers (IEEE), pp 1–6

  • Tweedie M (1984) An index which distinguishes between some important exponential families. In: Statistics: applications and new directions: Proceedings Indian statistical institute golden Jubilee international conference, pp 579–604

  • Watson JT, Haynie AC (2016) Using vessel monitoring system data to identify and characterize trips made by fishing vessels in the United States North Pacific. PLoS ONE 11:e0165173. https://doi.org/10.1371/journal.pone.0165173

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Wickham H (2016) tidyverse: Easily Install and Load “Tidyverse” Packages. R Packag. version 1.0.0

  • Wickham H, Grolemund G (2011) Dates and times made easy with lubridate. J Stat Softw 40:1–25

    Google Scholar 

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Acknowledgements

We thank the Department of Primary Industries and Regional Development for providing access to VMS data for the purpose of this project. Thank you to fishers of the PTMF for support and comment on this manuscript. This study was supported by the Australian Government, Woodside Energy Ltd, and The University of Western Australia, through Research Training Program (RTP) Scholarship, Woodside Top-Top and UWA Safety-Net Top-Up Scholarships.

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Bond, T., McLean, D.L., Wakefield, C.B. et al. Quantifying fishing activity targeting subsea pipelines by commercial trap fishers. Rev Fish Biol Fisheries 31, 1009–1023 (2021). https://doi.org/10.1007/s11160-021-09686-4

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