Published on 26 April 2025 |

Version 2025.1.0

Global monthly catches from tuna surface fisheries by 1° grid (1958-2023) (FIRMS level 0)

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FIRMS Global Tuna Atlas Technical Working Group

Description

We compiled a comprehensive dataset of geo-referenced catches from global tuna fisheries that use fishing gears set at the water's surface. This dataset was created by harmonizing public domain data from the five tuna Regional Fisheries Management Organizations (t-RFMOs) for the period 1958-2023. Under the auspices of the Fisheries and Resources Monitoring System (FIRMS) of the United Nations Food and Agriculture Organization (FAO), we developed a systematic data flow process in collaboration with the t-RFMO Secretariats. This process involved the implementation of a data exchange format adhering to the standards of the FAO Coordinating Working Party on Fishery Statistics (CWP), facilitating the seamless integration of data into the dataset.Geo-referenced catch data from tuna surface fisheries are reported in either the number of fish or live-weight equivalent (metric tonnes), with some strata providing catches in both units. The catches primarily represent the quantities of retained fish either landed or transhipped at sea and in ports. The data are stratified by year, month, fishing fleet, fishing gear, fishing mode, 1° grid area of longitude and latitude, and taxon.The dataset encompasses 42 medium- and large-sized pelagic species found in both neritic and oceanic habitats of the world's oceans. This includes 14 species of tunas, 9 species of billfish, 4 species of Spanish mackerels, 2 species of bonitos, and wahoo. Despite uncertainties and incomplete data due to under-reporting, the dataset also includes reported catches for 12 species of pelagic sharks and rays that may be either targeted or incidentally caught in tuna and tuna-like fisheries.The dataset serves as a benchmark for the monitoring and assessment of both artisanal and industrial fisheries using surrounding nets, gillnets, entangling nets, and pole-and-lines from over 70 fishing fleets across 69 countries that have exploited tuna and tuna-like species for subsistence and commercial purposes over more than six decades.

Citations (0)

Mentions (0)

Metrics

Dataset Index

1.7

FAIR Score

77%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Food and Agriculture Organization of the United Nations (UN-FAO)

Assigned Domain

Subfield

Global and Planetary Change

Field

Environmental Science

Domain

Physical Sciences

Confidence Score

63%

Source

Scholar Data Model

Keywords

fisherymarine fisheryfishery resourcefish stockcommercial fisheryfisheries managementfishery datafishery statisticsfishery resourcesfishery stocksfishery sciencesCCSBT [CCSBT]IATTC [IATTC]ICCAT [ICCAT]IOTC [IOTC]WCFPC [WCPFC]Angola [AGO]Albania [ALB]Argentina [ARG]Australia [AUS]Benin [BEN]Belize [BLZ]Bermuda [BMU]Bolivia (Plurinat.State) [BOL]Brazil [BRA]Barbados [BRB]Canada [CAN]China [CHN]Côte d'Ivoire [CIV]Congo, Republic of [COG]Cook Islands [COK]Colombia [COL]Comoros [COM]Cabo Verde [CPV]Costa Rica [CRI]Cuba [CUB]Curaçao [CUW]Cayman Islands [CYM]Dominica [DMA]Algeria [DZA]Ecuador [ECU]Egypt [EGY]Bulgaria (EU) [EUBGR]Cyprus (EU) [EUCYP]Germany (EU) [EUDEU]Denmark (EU) [EUDNK]Spain (EU) [EUESP]France (EU) [EUFRA]Greece (EU) [EUGRC]Croatia (EU) [EUHRV]Ireland (EU) [EUIRL]Italy (EU) [EUITA]Malta (EU) [EUMLT]Netherlands (EU) [EUNLD]Portugal (EU) [EUPRT]Fiji, Republic of [FJI]Falkland Is.(Malvinas) [FLK]Faroe Islands [FRO]Micronesia,Fed.States of [FSM]Gabon [GAB]United Kingdom [GBR]UK (territories) [GBRT]Ghana [GHA]Guinea [GIN]Equatorial Guinea [GNQ]Grenada [GRD]Guatemala [GTM]Honduras [HND]Indonesia [IDN]India [IND]Iran (Islamic Rep. of) [IRN]Iceland [ISL]Japan [JPN]Kenya [KEN]Kiribati [KIR]Saint Kitts and Nevis [KNA]Korea, Republic of [KOR]Libya [LBY]Sri Lanka [LKA]Morocco [MAR]Madagascar [MDG]Maldives [MDV]Mexico [MEX]Marshall Islands [MHL]Mozambique [MOZ]Mauritius [MUS]Malaysia [MYS]Namibia [NAM]Other nei [NEI]Nicaragua [NIC]Niue [NIU]Norway [NOR]New Zealand [NZL]Oman [OMN]Pakistan [PAK]Panama [PAN]Peru [PER]Philippines [PHL]Palau [PLW]Papua New Guinea [PNG]Russian Federation [RUS]Serbia and Montenegro [SCG]Senegal [SEN]Saint Helena [SHN]Solomon Islands [SLB]Sierra Leone [SLE]El Salvador [SLV]St. Pierre and Miquelon [SPM]Un. Sov. Soc. Rep. [SUN]Suriname [SUR]Seychelles [SYC]Syrian Arab Republic [SYR]Turks and Caicos Is. [TCA]Thailand [THA]Tonga [TON]Trinidad and Tobago [TTO]Tunisia [TUN]Turkey [TUR]Tuvalu [TUV]Taiwan Province of China [TWN]Tanzania, United Rep. of [TZA]Uruguay [URY]United States of America [USA]Saint Vincent/Grenadines [VCT]Venezuela, Boliv Rep of [VEN]British Virgin Islands [VGB]Vanuatu [VUT]Samoa [WSM]Yemen [YEM]South Africa [ZAF]Harpoons [10.1]Gear nei [10.9]Gear not known [99.9]Purse seines [01.1]Surrounding nets without purse lines [01.2]Beach seines [02.1]Seine nets nei [02.9]Bottom pair trawls [03.15]Midwater pair trawls [03.22]Midwater trawls (nei) [03.29]Trawls (nei) [03.9]Lift nets (nei) [05.9]Falling gear (nei) [06.9]Drift gillnets [07.2]Fixed (on stakes) gillnets [07.4]Trammel nets [07.5]Gillnets and entangling nets (nei) [07.9]Stationary uncovered pound nets [08.1]Traps (nei) [08.9]Handlines and hand-operated pole-and-lines [09.1]Mechanized lines and pole-and-lines [09.2]Set longlines [09.31]Drifting longlines [09.32]Longlines (nei) [09.39]Vertical lines [09.4]Trolling lines [09.5]Hooks and lines (nei) [09.9]Atlantic bonito [BON]Bonitos nei [BZX]Plain bonito [BOP]Wahoo [WAH]Narrow-barred Spanish mackerel [COM]Indo-Pacific king mackerel [GUT]King mackerel [KGM]Atlantic Spanish mackerel [SSM]Cero [CER]West African Spanish mackerel [MAW]Serra Spanish mackerel [BRS]Seerfishes nei [KGX]Frigate tuna [FRI]Bullet tuna [BLT]Frigate and bullet tunas [FRZ]Little tunny(=Atl.black skipj) [LTA]Black skipjack [BKJ]Kawakawa [KAW]Skipjack tuna [SKJ]Atlantic bluefin tuna [BFT]Pacific bluefin tuna [PBF]Longtail tuna [LOT]Blackfin tuna [BLF]Albacore [ALB]Southern bluefin tuna [SBF]Yellowfin tuna [YFT]Bigeye tuna [BET]True tunas nei [TUS]Slender tuna [SLT]Tunas nei [TUN]Indo-Pacific sailfish [SFA]Atlantic sailfish [SAI]Blue marlin [BUM]Marlins nei [BXQ]Black marlin [BLM]Atlantic white marlin [WHM]Striped marlin [MLS]Mediterranean spearfish [MSP]Shortbill spearfish [SSP]Longbill spearfish [SPF]Marlins,sailfishes,etc. nei [BIL]Swordfish [SWO]Thresher [ALV]Pelagic thresher [PTH]Bigeye thresher [BTH]Thresher sharks nei [THR]Shortfin mako [SMA]Longfin mako [LMA]Mako sharks [MAK]Porbeagle [POR]Silky shark [FAL]Oceanic whitetip shark [OCS]Blue shark [BSH]Requiem sharks nei [RSK]Scalloped hammerhead [SPL]Great hammerhead [SPK]Smooth hammerhead [SPZ]Hammerhead sharks nei [SPN]Hammerhead sharks, etc. nei [SPY]Rays, stingrays, mantas nei [SRX]Giant manta [RMB]Devil fish [RMM]Chilean devil ray [RMT]Mantas, devil rays nei [MAN]Various sharks nei [SKH]Log school [LS]Free school [FS]Other set types combined [OTH]Undefined school [UNK]Retained catch [RC]Discarded dead [DD]Discarded alive [DL]Metric tons [t]Number of fishes [no]Original sample [original_sample]Raised [raised]Unknown [unknown]

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00