Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore tuna (Thunnus alalunga) in the North Atlantic for the period 1956-1972, compiled from statistics about ICCAT fishery region L1

The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2007

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore tuna (Thunnus alalunga) in the North Atlantic for the period 1999-2007, compiled from statistics about ICCAT fishery region T11

The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore tuna (Thunnus alalunga) in the North Atlantic for the period 1987-2009, compiled from statistics about ICCAT fishery region L3

The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore tuna (Thunnus alalunga) in the North Atlantic for the period 1973-2011, compiled from statistics about ICCAT fishery region L2

The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2008

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2006

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic in May 2006

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2011

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Zooplankton abundance and size structure in the North Atlantic from MSM26_133-14

Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment at 9 stations in the North Atlantic, from the Iceland Basin in the East to the Labrador Sea in the West. The data were sampled along vertical profiles by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA) and a fluorescence sensor (F, ECO Puck chlorophyll a fluorometer, WET Labs Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10(body volume) increments, see Edvardsen et al. (2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). Fluorescence was roughly converted into chlorophyll based on filtered chlorophyll values obtained from station 10 in the Labrador Sea. Due to the low number of filtered samples that was used for the conversion the resulting chlorophyll values should be considered with care. CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column, see Herman et al., (2004, doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

Zooplankton abundance and size structure in the North Atlantic from MSM26_135-21

Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment at 9 stations in the North Atlantic, from the Iceland Basin in the East to the Labrador Sea in the West. The data were sampled along vertical profiles by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA) and a fluorescence sensor (F, ECO Puck chlorophyll a fluorometer, WET Labs Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10(body volume) increments, see Edvardsen et al. (2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). Fluorescence was roughly converted into chlorophyll based on filtered chlorophyll values obtained from station 10 in the Labrador Sea. Due to the low number of filtered samples that was used for the conversion the resulting chlorophyll values should be considered with care. CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column, see Herman et al., (2004, doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

Zooplankton abundance and size structure in the North Atlantic from MSM26_127-22

Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment at 9 stations in the North Atlantic, from the Iceland Basin in the East to the Labrador Sea in the West. The data were sampled along vertical profiles by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA) and a fluorescence sensor (F, ECO Puck chlorophyll a fluorometer, WET Labs Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10(body volume) increments, see Edvardsen et al. (2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). Fluorescence was roughly converted into chlorophyll based on filtered chlorophyll values obtained from station 10 in the Labrador Sea. Due to the low number of filtered samples that was used for the conversion the resulting chlorophyll values should be considered with care. CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column, see Herman et al., (2004, doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

Rates of egg production, grazing and mortatlity of Calanus finmarchicus measured experimentally in the North Atlantic during the Maria S. Merian cruise MSM26, spring 2013

An incubation experiment at five different temperatures was used to assess the potential for adaptation of Calanus finmarchicus to future warming of the ocean. During a short term (3 h) and long term (6 day) exposure of individual females to a gradient of temperature stress, egg production and fecal pellet production were monitored to indicate secondary production and grazing rates. A longer term (10 day) exposure to elevated temperatures followed by a return to ambient sea temperatures was used to assess the potential recovery of individuals exposed to temperature stress. Females were picked out from WP2 net samples and acclimatised in 2 L bottles of GFF filtered seawater with Thalassiosira weissflogii as prey for >48 h at ambient SST. Experimental bottles were filled with filtered seawater (GFF filtered from non-toxic seawater supply) and acclimated to experimental temperature overnight (0, 5, 10, 15 and 20 °C). Individual females were transferred into bottles using forceps and the bottles were inoculated with T. weissflogii to a final concentration of 5 µg chl L-1. Bottles were then placed into water baths and incubated for 3h or 6 d, and monitored for egg and fecal pellet production rates. A 10 day exposure experiment was used to test the potential for recovery from temperature stress, by returning females incubated at 5, 10, 15 and 20 °C back to 10 °C for 24 h and counting egg and fecal pellet production.