Sea Around Us - Catch Reconstruction (BIOL3305 Lecture 5) PDF

The real catch of the world: Catch reconstructions Dirk Zeller Sea Around Us – Indian Ocean End of last lecture… 2005 Something happened that changed our perception and thinking in the Sea Around Us with regards to global catch data… End of last l...

The real catch of the world: Catch reconstructions Dirk Zeller Sea Around Us – Indian Ocean End of last lecture… 2005 Something happened that changed our perception and thinking in the Sea Around Us with regards to global catch data… End of last lecture… Sea Around Us ‘treatment’ of FAO data Last lecture: Outlined how we made the FAO catch data reported by countries at the scale of large FAO areas more useful... 1. Ecological meaningful Spatially constraining catch via taxon probability distributions 2. Political relevant Filtering/limiting foreign fishing access to country’s EEZs Sea Around Us ‘treatment’ of FAO data Started us thinking about the issues of comprehensiveness of catch statistics... When working on the fisheries of their country or their region, fisheries scientists, academics, staff of environmental NGO’s and other parties, usually work with their own or local/national data, and there are few problems of accuracy. E.g., WA Fisheries experts knows their data and the caveats and limitations thereof. When working on foreign countries or regionally (ocean-basin) or globally, most actors have generally used statistics assembled by the FAO. 5/54 After working with FAO data for years, we initially thought that they were roughly correct in amounts, i.e., that any errors are more or less randomly distributed. We were wrong: The FAO statistics are fundamentally misleading The FAO data for most countries in the world are strongly biased downward (i.e., under-reported) because: 1) The countries do not report on all of their fisheries, especially not on their small-scale and non-commercial fisheries. 2) FAO data explicitly do not include discarded catches. E.g., Australian national data reported to FAO did not include recreational catches until recently… and still do not include these for earlier periods (pre- 2015) What made us first consider that such a downward data bias may be a big problem? 2002-2005: Estimate and account for the coral reef and bottom fish catches for U.S. flag island areas in the Western Pacific since 1950. State of Hawaii Guam Northern Mariana Islands American Samoa Minor islands (Midway Atoll, Johnston Atoll, Palmyra Atoll, Wake, Jarvis, Baker and Howland Islands) USA? NOAA-NMFS? Lots of resources, excellent fisheries scientists. Walk in the park, not expect to find much of a data problem…. American Samoa, Guam, Northern Mariana Islands All combined Guam 4.5 fold 77% decline Northern Mariana Islands American Samoa - Missing catch components (shore-based, subsistence, recreational) - Early time period issue Zeller et al. (2006) Coral Reefs 25(1): 144-152 Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2008) Fisheries Research 91(1): 88-97 Draft report…. Much concern and “steam”…. Workshop…. Final: report accepted… with teeth gnashing…. All combined Guam 4.5 fold 77% decline Northern Mariana Islands American Samoa Zeller et al. (2006) Coral Reefs 25(1): 144-152 Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2008) Fisheries Research 91(1): 88-97 If USA has this sort of data problem… what about the rest of the world? What’s the ‘real’ catch in the world? - ‘Reconstruct’ (re-estimate) the world’s total marine fisheries catch - Identify and estimate all unreported catch components & complement/improve officially reported data (FAO) - 15+ year-long, team research effort - > 300 people around the world Researchers Grad students International colleagues 10/54  What’s the ‘real’ catch in the world? ‘Catch reconstruction’ characteristics: – Every maritime country; Truly global coverage (not “case study approach”); North Korea, Syria, Iran, Libya, all African countries etc. – Estimates of all fisheries withdrawals from the ecosystem; – Go back to 1950; – to be able to compare present with earlier ecosystem states; – Cover and differentiate between all fisheries sectors – industrial, artisanal, subsistence, and recreational; – Include landed catch as well as discards; – because the fish don’t care who killed them; – Differentiate reported from unreported data; – Use all types of secondary information and data sources; – “No data = zero catch” is not an option. Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2015) Coral Reefs 34(1): 25-39 Zeller et al. (2016) Marine Policy 70: 145-152  What’s the ‘real’ catch in the world? “No data = zero catch” Year Gear 1 Gear 2 Gear 3 Sum of Total catch catch 1990 20 no data no data 20 +ND+ND 20 1991 30 no data no data 30+ND+ND 30 1992 40 no data no data 40+ND+ND 40 1993 50 no data no data 50+ND+ND 50 1994 60 no data no data 60+ND+ND 60 1995 70 10 no data 70+10+ND 80 1996 80 40 no data 80+40+ND 120 1997 90 50 no data 90+50+ND 140 1998 100 60 10 100+60+10 170 1999 110 70 40 110+70+40 220 2000 120 80 50 120+80+50 250 Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2015) Coral Reefs 34(1): 25-39 Zeller et al. (2016) Marine Policy 70: 145-152  What’s the ‘real’ catch in the world? “No data = zero catch” Year Gear 1 Gear 2 Gear 3 Sum of Total catch catch 1990 20 no data no data 20 +ND+ND 20 1991 30 no data no data 30+ND+ND 30 1992 40 no data no data 40+ND+ND 40 1993 50 no data no data 50+ND+ND 50 1994 60 no data no data 60+ND+ND 60 1995 70 10 no data 70+10+ND 80 1996 80 40 no data 80+40+ND 120 1997 90 50 no data 90+50+ND 140 1998 100 60 10 100+60+10 170 1999 110 70 40 110+70+40 220 2000 120 80 50 120+80+50 250 Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2015) Coral Reefs 34(1): 25-39 Zeller et al. (2016) Marine Policy 70: 145-152  What’s the ‘real’ catch in the world? “No data = zero catch” Year Gear 1 Gear 2 Gear 3 Sum of Total catch catch 1990 20 no data no data 20 +ND+ND 20 20+0+0 1991 30 no data no data 30+ND+ND 30 1992 40 no data no data 40+ND+ND 40 1993 50 no data no data 50+ND+ND 50 1994 60 no data no data 60+ND+ND 60 1995 70 10 no data 70+10+ND 80 1996 80 40 no data 80+40+ND 120 1997 90 50 no data 90+50+ND 140 1998 100 60 10 100+60+10 170 1999 110 70 40 110+70+40 220 2000 120 80 50 120+80+50 250 Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2015) Coral Reefs 34(1): 25-39 Zeller et al. (2016) Marine Policy 70: 145-152  What’s the ‘real’ catch in the world? “No data = zero catch” ? ? Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2015) Coral Reefs 34(1): 25-39 15/54 Zeller et al. (2016) Marine Policy 70: 145-152 Reconstruction approach Zeller et al. (2016) Marine Policy 70: 145-152  Our definitions Industrial sector: consisting of relatively large motorized vessels, requiring Large-scale large sums for their construction, maintenance and operation. Fish either domestically, in the waters of other countries and/or the high seas. Land catch that is overwhelmingly sold commercially. Commercial, large-scale sector. Artisanal sector: consisting of small-scale (hand lines, gillnets etc.) and fixed gears (weirs, traps, etc.) whose catch is predominantly sold commercially, notwithstanding a small fraction of catch being consumed or given away by the crew. Commercial, small-scale sector. Subsistence sector: consisting of fisheries whose primary driver is for Small-scale consumption by their family/community, rather than engage in commerce. Often these are conducted by women and children. Also, the fraction of the catch of many artisanal boats that is given away to the crews’ families or the local community. Non-commercial, small-scale sector. Recreational sector: consisting of fisheries conducted mainly for pleasure, although a fraction of the catch may end up being sold or consumed by the recreational fishers and their families and friends. Non-commercial, small- scale sector Also: Catch = Landings + Discards Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2015) Coral Reefs 34(1): 25-39 Zeller et al. (2016) Marine Policy 70: 145-152 Reconstruction approach Zeller et al. (2016) Marine Policy 70: 145-152  Steps 2 & 3: Source alternative information Brito AJ and Abdula S (2008) Relatório de Cruzeiro de investigação de camarão no Banco de Sofala realizado de 29 de Janeiro a 17 de Fevereiro de 2007. Relatorio de Cruzeiro n.46, IIP, Maputo. 62 p. Um SH and Heo SY (2010) V 9ˇUW >9F/ æ. %æU ,L. 141 p. Балыкин АВБ, Д.А. Терентьев, А.А. Бонк (2007) Распределение квот на вылов водных биоресурсов с учетом многовидового характера рыболовства. Вопросы рыболовства 3(31): 559-568. Kishita, T (1998) Gyokaku kano ryo (TAC) seido no jisshi. In: JFA (ed) Suisancho 50 Nenshi. Suisancho 50 Nenshi Henshu Iinkai. ¿F‚¥ Doherty et al. (2015) pp. 67-81 In Le Manach F and Pauly D (eds.), Fisheries catch reconstructions in the Western Indian Ocean, 1950-2010. Fisheries Centre Research Reports 23(2), University of British Columbia, Vancouver Shon et al. (2014) Fisheries Centre Working Paper #2014-20, University of British Columbia, Vancouver. 11 p Sobolevskaya and Divovich (2015) Fisheries Centre Working Paper #2015-45, University of British Columbia, Vancouver. 64 p Swartz and Ishimura (2014) Fisheries Science 80(4):643-651 Reconstruction approach 20/54 Zeller et al. (2016) Marine Policy 70: 145-152  Steps 4 & 5: Anchor point expansion and time series interpolation Requires informed assumptions 1. Source (local study) applicable to all areas of coast? Brazil: north (tropical, small-scale) vs. south (temperate, industrial) 2. How do various sources for ‘same’ thing relate? American Samoa shore-based fisheries: subsistence vs. commercial reef spear 3. Development over time? Related to economic development (GDP) or population growth? 4. Political-societal influences Mozambique: Civil war impact on coastal migration 5. Others? Need to know and understand each country’s history as well as socio- economic and political developments Clearly documend and describe Zeller et al. (2016) Marine Policy 70: 145-152 Reconstruction approach 20/57 Zeller et al. (2016) Marine Policy 70: 145-152 Step 7: Quantify data uncertainty: ‘Score’ quality of time series data Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152  Reconstruction: Jigsaw puzzle Edges & corners = reported catch data Reconstructed data = reported + unreported Zeller et al. (2007) Fishery Bulletin 105(2): 266-277 Zeller et al. (2015) Coral Reefs 34(1): 25-39 Pauly and Zeller (2016) Nature Communications 7: 10244. Suppl. Mat.  Reconstructed data: 273 Exclusive Economic Zones (EEZs)… domestic catch only Makes domestic catches more accurate & politically relevant Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152 25/54 Coulter et al. (2020) Fisheries Research 221: 105379 NOT reconstructed: Foreign catches inside EEZs and most catches in high seas - But: Heidrich KN, Meeuwig JJ and Zeller D (2023) Reconstructing past fisheries catches for large pelagic species in the Indian Ocean. Frontiers in Marine Science 10: 1177872. https://doi.org/10.3389/fmars.2023.1177872 Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152 Coulter et al. (2020) Fisheries Research 221: 105379 Our catch reconstruction database has three catch data layers (or types of catch data) Layer 1) “Reconstructed domestic catch” Japan fishing in Japan’s home EEZ waters Layer 2) “Inferred foreign catch” Japan fishing in other countries’ EEZ waters or in the high seas for anything other than large pelagic species under Tuna RFMO mandates (tuna, billfishes and pelagic sharks) Layer 3) “Assigned Tuna RFMO catch” Japan fishing in other countries’ EEZ waters or in the high seas for large pelagic species under Tuna RFMO mandates (tuna, billfishes and pelagic sharks) Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152 Coulter et al. (2020) Fisheries Research 221: 105379 Thus, our catch database has three catch data layers (or types of catch data) Layer 1) “Reconstructed domestic catch” Japan fishing in Japan’s home EEZ waters Detailed estimation of reported & unreported catches Documented in catch reconstruction reports and/or papers for every maritime country Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152 Coulter et al. (2020) Fisheries Research 221: 105379 Thus, our catch database has three catch data layers (or types of catch data) Layer 2) “Inferred foreign catch” Japan fishing in other countries’ EEZ waters or in the high seas for anything other than large pelagic species under Tuna RFMO mandates (tuna, billfishes and pelagic sharks) Relying on FAO data: ̵ “Non-home” FAO areas = FAO reported data ̵ “Home” FAO area = FAO reported – Layer 1 reported Not reconstructed Example: Japan Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152 Coulter et al. (2020) Fisheries Research 221: 105379  Japan Home FAO area Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152 30/54 Coulter et al. (2020) Fisheries Research 221: 105379 Thus, our catch database has three catch data layers (or types of catch data) Layer 3) “Assigned Tuna RFMO catch” Japan fishing in other countries’ EEZ waters or in the high seas for large pelagic species under Tuna RFMO mandates (tuna, billfishes and pelagic sharks) Tuna RFMO reported data, spatially harmonized & prelim. discards added Not fully reconstructed, but see Heidrich et al. (2023) Please read Coulter et al. (2020) & Heidrich et al. (2023) RFMO Regional Fisheries Management Organization E.g. IOTC (Indian Ocean Tuna Commission) Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152 Coulter et al. (2020) Fisheries Research 221: 105379 Heidrich et al. (2023) Frontiers in Marine Science 10: 1177872 Pauly and Zeller (2016) Nature Communications 7: 10244 Zeller et al. (2016) Marine Policy 70: 145-152 Coulter et al. (2020) Fisheries Research 221: 105379 Core Sea Around Us databases: - Catch data (reconstructed) - 273 individual EEZ catch reconstructions (Layer 1) - Inferred foreign non-tuna & global tuna dataset (Layers 2 & 3) - By fishing country (>180) - By year (1950-2019) - By taxon (> 3,000) - By fishing sector (industrial, artisanal, subsistence, recreational) - By ‘catch type’ (landed catch, discarded catch) - By ‘reporting status’ (reported, unreported) - By fishing gear (separate lecture) - By end use (separate lecture) - Taxon distributions - Biological probability distributions, > 3,000 taxa - Fishing access database - Which country fishes in which EEZ, when & what - Fishing access agreements & observed access - GIS ocean data layer - 150,000 GIS grid cells @ ½ degree latitude x ½ degree longitude Zeller et al. (2016) Marine Policy 70: 145-152 Spatial allocation Zeller et al. (2016) Marine Policy 70: 145-152  What we have done so far >> 500 peer-reviewed articles 12 books & > 20 book chapters > 500 technical reports Developed world’s largest online data & information system for fisheries – www.seaaroundus.org – Freely available – Open Access 35/54 Our mapping allows global spatial patterns to be discerned Global catches etc. Pauly and Zeller, editors (2016) Global Atlas of Marine Fisheries. Island Press, xvii + 486 p. Global catches Pauly and Zeller (2016) Nature Communications 7:10244 30-50% higher 1.2 x 106 t/year 0.4 x 106 t/year Why do trends differ? Pauly and Zeller (2016) Nature Communications 7:10244 Pauly and Zeller (2017a) Marine Policy 77: 176-181 Pauly and Zeller (2017b) Marine Policy 81: 406-410 Zeller and Pauly (2018) Marine Policy 90: 14-19  ‘Presentist bias’ − Data reporting over-emphasizing ‘the present’ vis-à-vis ‘the past’ − Inadvertent by-product of improvements in data collection systems 40/54 Zeller and Pauly (2018) Marine Policy 90:14-19 ‘Presentist bias’ A: industrial B: artisanal C: recreational C B A Zeller and Pauly (2018) Marine Policy 90:14-19 ‘Presentist bias’ A: industrial B: artisanal C: recreational C B A Zeller and Pauly (2018) Marine Policy 90:14-19 ‘Presentist bias’ A: industrial B: artisanal C: recreational C* C B* B A Zeller and Pauly (2018) Marine Policy 90:14-19 ‘Presentist bias’ A: industrial B: artisanal C: recreational C B A Zeller and Pauly (2018) Marine Policy 90:14-19  ‘Presentist bias’ Unreported Reported 45/54 Zeller and Pauly (2018) Marine Policy 90:14-19  ‘Presentist bias’ At least 4 very clear cases documented so far: Mozambique: Jacquet et al. (2010) African Journal of Marine Science 32(2): 197-206. Tanzania: Jacquet et al. (2010) African Journal of Marine Science 32(2): 197-206. Kenya: McAlpine (2019) MSc thesis, UWA, Crawley. 45 p. Greece: Tsikliras et al. (2020) Marine Policy 117: 103886. Many more likely hidden in reported data…. Often subtle Zeller and Pauly (2018) Marine Policy 90:14-19 Things FAO not able to do… Catch by fishing sector Pauly and Zeller (2016) Nature Communications 7:10244  Things FAO not able to do… Definition of fishing sector Developed Developing Pauly and Zeller (2016) Nature Communications 7:10244 An important comparison This graph highlights the crucial role of small- scale fisheries, so far often neglected. Massive conflict between these sectors in most countries… Indeed, we would achieve most stated aims of fisheries management plans (particularly their social aims) by dedicated arrangements for carefully managed small-scale fisheries, and termination of industrial subsidies. Zeller and Pauly (2019) Global Sustainability 2: e11 Pauly and Zeller, editors (2016) Global Atlas of Marine Fisheries. Island Press  Things FAO not able to do… Catch by various geographies Large Marine Ecosystems Marine Ecoregions High Seas waters 50/54 Zeller et al. (2016) Marine Policy 70: 145-152 Zeller et al. (2020) Environmental Development 36: 100543 Zeller et al. (2020) Environmental Development 36: 100543 53/54 Zeller et al. (2020) Environmental Development 36: 100543 Sea Around Us – Indian Ocean