47 research outputs found

    The stress hormone corticosterone in a marine top predatorreflects short-term changes in food availability

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    -In many seabird studies, single annual proxies of prey abundance have been used to explain variability in breeding performance, but much more important is probably the timing of prey availability relative to the breeding season when energy demand is at a maximum. Until now, intraseasonal variation in prey availability has been difficult to quantify in seabirds. Using a state-of-the-art ocean drift model of larval cod Gadus morhua, an important constituent of the diet of common guillemots Uria aalge in the southwestern Barents Sea, we were able to show clear, short-term correlations between food availability and measurements of the stress hormone corticosterone (CORT) in parental guillemots over a 3-year period (2009–2011). The model allowed the extraction of abundance and size of cod larvae with very high spatial (4 km) and temporal resolutions (1 day) and showed that cod larvae from adjacent northern spawning grounds in Norway were always available near the guillemot breeding colony while those from more distant southerly spawning grounds were less frequent, but larger. The latter arrived in waves whose magnitude and timing, and thus overlap with the guillemot breeding season, varied between years. CORT levels in adult guillemots were lower in birds caught after a week with high frequencies of southern cod larvae. This pattern was restricted to the two years (2009 and 2010) in which southern larvae arrived before the end of the guillemot breeding season. Any such pattern was masked in 2011 by already exceptionally high numbers of cod larvae in the region throughout chick-rearing period. The findings suggest that CORT levels in breeding birds increase when the arrival of southern sizable larvae does not match the period of peak energy requirements during breeding. Common guillemot, CORT, food availability, seabird, Uria aalg

    Biomass of Scyphozoan Jellyfish, and Its Spatial Association with 0-Group Fish in the Barents Sea

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    An 0-group fish survey is conducted annually in the Barents Sea in order to estimate fish population abundance. Data on jellyfish by-catch have been recorded since 1980, although this dataset has never been analysed. In recent years, however, the ecological importance of jellyfish medusae has become widely recognized. In this paper the biomass of jellyfish (medusae) in 0–60 m depths is calculated for the period 1980–2010. During this period the climate changed from cold to warm, and changes in zooplankton and fish distribution and abundance were observed. This paper discusses the less well known ecosystem component; jellyfish medusae within the Phylum Cnidaria, and their spatial and temporal variation. The long term average was ca. 9×108 kg, with some years showing biomasses in excess of 5×109 kg. The biomasses were low during 1980s, increased during 1990s, and were highest in early 2000s with a subsequent decline. The bulk of the jellyfish were observed in the central parts of the Barents Sea, which is a core area for most 0-group fishes. Jellyfish were associated with haddock in the western area, with haddock and herring in the central and coastal area, and with capelin in the northern area of the Barents Sea. The jellyfish were present in the temperature interval 1°C<T<10°C, with peak densities at ca. 5.5°C, and the greatest proportion of the jellyfish occurring between 4.0–7.0°C. It seems that the ongoing warming trend may be favourable for Barents Sea jellyfish medusae; however their biomass has showed a recent moderate decline during years with record high temperatures in the Barents Sea. Jellyfish are undoubtedly an important component of the Barents Sea ecosystem, and the data presented here represent the best summary of jellyfish biomass and distribution yet published for the region

    Spawning of bluefin tuna in the black sea: historical evidence, environmental constraints and population plasticity

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    <div><p>The lucrative and highly migratory Atlantic bluefin tuna, <em>Thunnus thynnus</em> (Linnaeus 1758<em>;</em> Scombridae), used to be distributed widely throughout the north Atlantic Ocean, Mediterranean Sea and Black Sea. Its migrations have supported sustainable fisheries and impacted local cultures since antiquity, but its biogeographic range has contracted since the 1950s. Most recently, the species disappeared from the Black Sea in the late 1980s and has not yet recovered. Reasons for the Black Sea disappearance, and the species-wide range contraction, are unclear. However bluefin tuna formerly foraged and possibly spawned in the Black Sea. Loss of a locally-reproducing population would represent a decline in population richness, and an increase in species vulnerability to perturbations such as exploitation and environmental change. Here we identify the main genetic and phenotypic adaptations that the population must have (had) in order to reproduce successfully in the specific hydrographic (estuarine) conditions of the Black Sea. By comparing hydrographic conditions in spawning areas of the three species of bluefin tunas, and applying a mechanistic model of egg buoyancy and sinking rate, we show that reproduction in the Black Sea must have required specific adaptations of egg buoyancy, fertilisation and development for reproductive success. Such adaptations by local populations of marine fish species spawning in estuarine areas are common as is evident from a meta-analysis of egg buoyancy data from 16 species of fish. We conclude that these adaptations would have been necessary for successful local reproduction by bluefin tuna in the Black Sea, and that a locally-adapted reproducing population may have disappeared. Recovery of bluefin tuna in the Black Sea, either for spawning or foraging, will occur fastest if any remaining locally adapted individuals are allowed to survive, and by conservation and recovery of depleted Mediterranean populations which could through time re-establish local Black Sea spawning and foraging.</p> </div

    J-embeddable reducible surfaces

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    Retention of Coastal Cod Eggs in a Fjord Caused by Interactions between Egg Buoyancy and Circulation Pattern

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    Norwegian coastal cod form a stationary population of Atlantic cod Gadus morhua consisting of several genetically separated subpopulations. A small-scale differentiation in marine populations with pelagic eggs and larvae is made possible by local retention of early life stages in coastal environments. A numerical model was used to simulate the circulation in a fjord system in northern Norway over 2 years with different river runoff patterns. The dispersal of cod eggs was calculated with a particle-tracking model that used three-dimensional currents. The observed thickness of the low-salinity surface layer was well reproduced by the model, but the surface salinity was generally lower in the model than in the observations. The cod eggs attained a subsurface vertical distribution, avoiding the surface and causing retention. Interannual variations in river runoff can cause small changes in the vertical distribution of cod eggs and larger changes in the vertical current structure. Retention in the fjord system was strong in both years, but some eggs were subjected to offshore transport over a limited time period. The timing of offshore transport depended on the precipitation and temperatures in adjacent drainage areas. A possible match between maximized spawning and offshore transport may have a negative effect on local recruitment

    Impact of data assimilation on E

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    Using four-dimensional variational analysis, we produce an estimate of the state of a coastal region in Northern Norway during the late winter and spring in 1984. We use satellite sea surface temperature and in situ observations from a series of intensive field campaigns, and obtain a more realistic distribution of water masses both in the horizontal and the vertical than a pure downscaling approach can achieve. Although the distribution of Eulerian surface current speeds are similar, we find that they are more variable and less dependent on model bathymetry in our reanalysis compared to a hindcast produced using the same modeling system. Lagrangian drift currents on the other hand are significantly changed, with overall higher kinetic energy levels in the reanalysis than in the hindcast, particularly in the superinertial frequency band

    OpenDrift v1.0: a generic framework for trajectory modelling

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    OpenDrift is an open-source Python-based framework for Lagrangian particle modelling under development at the Norwegian Meteorological Institute with contributions from the wider scientific community. The framework is highly generic and modular, and is designed to be used for any type of drift calculations in the ocean or atmosphere. A specific module within the OpenDrift framework corresponds to a Lagrangian particle model in the traditional sense. A number of modules have already been developed, including an oil drift module, a stochastic search-and-rescue module, a pelagic egg module, and a basic module for atmospheric drift. The framework allows for the ingestion of an unspecified number of forcing fields (scalar and vectorial) from various sources, including Eulerian ocean, atmosphere and wave models, but also measurements or a priori values for the same variables. A basic backtracking mechanism is inherent, using sign reversal of the total displacement vector and negative time stepping. OpenDrift is fast and simple to set up and use on Linux, Mac and Windows environments, and can be used with minimal or no Python experience. It is designed for flexibility, and researchers may easily adapt or write modules for their specific purpose. OpenDrift is also designed for performance, and simulations with millions of particles may be performed on a laptop. Further, OpenDrift is designed for robustness and is in daily operational use for emergency preparedness modelling (oil drift, search and rescue, and drifting ships) at the Norwegian Meteorological Institute

    OpenDrift v1.0: A generic framework for trajectory modelling

    Get PDF
    OpenDrift is an open-source Python-based framework for Lagrangian particle modelling under development at the Norwegian Meteorological Institute with contributions from the wider scientific community. The framework is highly generic and modular, and is designed to be used for any type of drift calculations in the ocean or atmosphere. A specific module within the OpenDrift framework corresponds to a Lagrangian particle model in the traditional sense. A number of modules have already been developed, including an oil drift module, a stochastic search-and-rescue module, a pelagic egg module, and a basic module for atmospheric drift. The framework allows for the ingestion of an unspecified number of forcing fields (scalar and vectorial) from various sources, including Eulerian ocean, atmosphere and wave models, but also measurements or a priori values for the same variables. A basic backtracking mechanism is inherent, using sign reversal of the total displacement vector and negative time stepping. OpenDrift is fast and simple to set up and use on Linux, Mac and Windows environments, and can be used with minimal or no Python experience. It is designed for flexibility, and researchers may easily adapt or write modules for their specific purpose. OpenDrift is also designed for performance, and simulations with millions of particles may be performed on a laptop. Further, OpenDrift is designed for robustness and is in daily operational use for emergency preparedness modelling (oil drift, search and rescue, and drifting ships) at the Norwegian Meteorological Institute
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