946 resultados para Specialization and Integration
Resumo:
The effects of temperature and food was examined for Calanus finmarchicus and C. glacialis during 3 phases of the phytoplankton spring bloom in Disko Bay, western Greenland. The 2 species were collected during pre-bloom, bloom, and post-bloom and exposed to temperatures from 0 to 10°C, combined with deficient or excess food. Fecal pellet and egg production were measured as indices for grazing and secondary production, respectively. Furthermore, changes in body carbon, nitrogen, and lipid content were measured. C. glacialis sampled before the bloom and incubated with excess food exhibited high specific egg production at temperatures between 0 and 2.5°C. Higher temperatures did not increase egg production considerably, whereas egg production for C. finmarchicus more than tripled between 2.5 and 5°C. Starved C. glacialis produced eggs at all temperatures stimulated by increasing temperatures, whereas starved C. finmarchicus needed temperatures above 5°C to produce eggs fueled by their lipid stores. Few C. finmarchicus had mature gonads at the initiation of the pre-bloom and bloom experiment, and egg production of C. finmarchicus therefore only increased as the ratio of individuals with mature gonads increased. During the bloom, both C. glacialis and C. finmarchicus used the high food availability for egg production, while refueling or exhausting their lipid stores, respectively. Finally, during the post-bloom experiment, production was low by C. finmarchicus, whereas C. glacialis had terminated production. Our results suggest that a future warmer ocean will reduce the advantage of early spawning by C. glacialis and that C. finmarchicus will become increasingly prevalent.
Resumo:
Here we present a new, pan-North-Atlantic compilation of data on key mesozooplankton species, including the most important copepod, Calanus finmarchicus. Distributional data of eight representative zooplankton taxa, from recent (2000-2009) Continuous Plankton Recorder data, are presented, along with basin-scale data of the phytoplankton colour index. Then we present a compilation of data on C. finmarchicus, including observations of abundance, demography, egg production and female size, with accompanying data on temperature and chlorophyll. . This is a contribution by Canadian, European and US scientists and their institutions.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
Analysis for micro-molar concentrations of nitrate and nitrite, nitrite, phosphate, silicate and ammonia was undertaken on a SEAL Analytical UK Ltd, AA3 segmented flow autoanalyser following methods described by Kirkwood (1996). Samples were drawn from Niskin bottles on the CTD into 15ml polycarbonate centrifuge tubes and kept refrigerated at approximately 4oC until analysis, which generally commenced within 30 minutes. Overall 23 runs with 597 samples were analysed. This is a total of 502 CTD samples, 69 underway samples and 26 from other sources. An artificial seawater matrix (ASW) of 40g/litre sodium chloride was used as the inter-sample wash and standard matrix. The nutrient free status of this solution was checked by running Ocean Scientific International (OSI) low nutrient seawater (LNS) on every run. A single set of mixed standards were made up by diluting 5mM solutions made from weighed dried salts in 1litre of ASW into plastic 250ml volumetric flasks that had been cleaned by washing in MilliQ water (MQ). Data processing was undertaken using SEAL Analytical UK Ltd proprietary software (AACE 6.07) and was performed within a few hours of the run being finished. The sample time was 60 seconds and the wash time was 30 seconds. The lines were washed daily with wash solutions specific for each chemistry, but comprised of MQ, MQ and SDS, MQ and Triton-X, or MQ and Brij-35. Three times during the cruise the phosphate and silicate channels were washed with a weak sodium hypochlorite solution.
Resumo:
The tuna stomach database from AZTI-Tecnalia corresponds to 7 years of sampling from 2004 to 2011. Due to the absence of continuity in the different projects dealing with the feeding ecology of tunas, the sampling could not be performed every year for both species, and no sample was collected in 2008. However, the fish stomach content record contents composition - by prey weight - of 1525 albacore caught in the Bay of Biscay and surrounding waters of the North Atlantic Drift Region in 2005 (n=397), 2006 (n=196), 2007 (n=37), 2009 (n=95), 2010 (n=566) and 2011 (n=234) ; and of 686 bluefin tunas caught in the Southeastern Bay of Biscay in 2004 (n=32), 2005 (n=36), 2006 (n=3), 2009 (n=257), 2010 (n=233) and 2011 (n=125). Samples have been obtained from scientific research surveys (using a variety of different fishing gears), from commercial fisheries catches, from individual fish voluntarily sampled by recreational fishermen and from fish accidentally stranded on coastlines. Each predator is identified by an ID and its length and wet weight are given. In case the wet weight could not be measured, it was estimated through a length-weight relationship equation and is indicated in the comment for the Predator mass column. The total weight of each prey is given, as well as the weight of each prey taxonomic group in each stomach.