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Wyszukujesz frazę "zooplankton" wg kryterium: Temat


Wyświetlanie 1-7 z 7
Tytuł:
Numerical studies of the influence of food ingestion on phytoplankton and zooplankton biomasses
Autorzy:
Dzierzbicka-Glowacka, L.
Powiązania:
https://bibliotekanauki.pl/articles/47575.pdf
Data publikacji:
2002
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
biomass
nutrient
zooplankton
food ingestion
phytoplankton
mathematical model
marine ecosystem
herbivorous copepod
Opis:
This paper presents the numerical simulations of the influence of food ingestion by a herbivorous copepod on phytoplankton and zooplankton biomasses (PZB) in the sea. The numerical studies were carried out using the phytoplankton- -zooplankton-nutrient-detritus PhyZooNuDe biological upperla yer model. This takes account both of fully developed primary production and regeneration mechanisms and of daily migration of zooplankton. In this model the zooplankton is treated not as a ‘biomass’ but as organisms having definite patterns of growth, reproduction and mortality.
Źródło:
Oceanologia; 2002, 44, 1
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A turning point in the development of phytoplankton in the Vistula Lagoon (Southern Baltic Sea) at the beginning of the 21st century
Autorzy:
Kownacka, J.
Calkiewicz, J.
Kornijow, R.
Powiązania:
https://bibliotekanauki.pl/articles/2079096.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
phytoplankton community
zooplankton
multiannual change
nutrient
biomass
Vistula Lagoon
Southern Baltic Sea
21st century
Opis:
Phytoplankton community structure was studied from 2002 to 2016 in the Vistula Lagoon (southern Baltic Sea) in the context of the 2010 shift in its population, as well as the reason for this shift and its environmental impact. This evident shift was indicated by Multidimensional Scaling at the Bray Curtis similarity level of 31%. Before 2010, the primary components of phytoplankton were Cyanobacteria (up to 98% of the biomass, October 2007) and Chlorophyta (40%, July 2002). After 2010, the contribution of Cyanobacteria considerably decreased, and the proportions of other phyla increased. The total phytoplankton biomass positively correlated with phosphorus, and Cyanobacteria biomass with silica. Evident changes were also observed in the seasonal dynamics of phytoplankton. Before 2010, the highest values of biomass occurred in autumn, and were related to high biomass of Cyanobacteria. Higher biomass has been recently reached in spring, during the dominance of Ochrophyta associated with Chlorophyta, Charophyta, and Cryptophyta. Generalised additive models showed a significant decreasing trend of the total phytoplankton biomass, Cyanobacteria, Chlorophyta, and flagellates, suggesting a decrease in eutrophication. This trend is concurrent with a considerable increase in the ratio of zooplankton to phytoplankton biomass since 2010. The increased ratio, however, did not result from elevated zooplankton biomass, but from the drop in phytoplankton biomass. Therefore, the most probable reason for the decrease in phytoplankton biomass was the simultaneous decrease in the concentration of all nutrients. The potential additional impact of filtration by a new alien bivalve Rangia cuneata G. B. Sowerby I, 1832 is also discussed.
Źródło:
Oceanologia; 2020, 62, 4PA; 538-555
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modeling the ecosystem response to summer coastal upwelling in the Northern South China Sea
Autorzy:
Jiang, R.
Wang, Y.-S.
Powiązania:
https://bibliotekanauki.pl/articles/47804.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
nutrient
phytoplankton
zooplankton
ecosystem model
coastal upwelling
hydrographic condition
seasonal change
sea surface temperature
South China Sea
Opis:
A coupled three-dimensional physical model and a nitrogen-based nutrient, phytoplankton, zooplankton, and detritus (NPZD) ecosystem model were applied to simulate the summer coastal upwelling system over the continental shelf of northern South China Sea (NSCS) and its impact on hydrographic conditions and ecosystem. The simulated results were comprehensively validated against field and satellite measurements. The model results show that the near shore ecosystem of NSCS has significant responses to the summer coastal upwelling system. The Shantou Coast to the Nanri Islands of Fujian province (YD) and the east of the Leizhou Peninsula (QD) are two main regions affected by NSCS summer coast upwelling. During summer, these two coastal areas are characterized by nearshore cold and high salinity upwelling current. Further, the summer coastal upwelling serves as a perfect nutrient pump, which lifts up and advects nutrient-rich current from deep to surface, from inner shelf to about 30 km outer shelf. This nutrient source reaches its maximum in the middle of July and then begins to decrease. However, the maximum phytoplankton and chlorophyll a do not coincide with the maximum nutrients and delay for about 10 days. Because of the intensive seasonal thermocline and the complicated current transporting through Qiongzhou strait, the ecological responding of QD is less pronounced than YD. This study has a better understanding of the physically modulated ecological responses to the NSCS summer coastal upwelling system.
Źródło:
Oceanologia; 2018, 60, 1
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Numerical modelling of POC dynamics in the Southern Baltic under possible future conditions determined by nutrients, light and temperature
Autorzy:
Dzierzbicka-Glowacka, L.
Kulinski, K.
Maciejewska, A.
Jakacki, J.
Pempkowiak, J.
Powiązania:
https://bibliotekanauki.pl/articles/47783.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
Baltic Sea
detritus
natural mortality
numerical modelling
nutrient
particulate organic carbon
phytoplankton
predator
primary production
temperature
temporal change
zooplankton
Opis:
This paper discusses predictions of particulate organic carbon (POC) concentra- tions in the southern Baltic Sea. The study is based on the one-dimensional Particulate Organic Carbon Model (1D POC), described in detail by Dzierzbicka- Głowacka et al. (2010a). The POC concentration is determined as the sum of phytoplankton, zoo- plankton and dead organic matter (detritus) concentrations. Temporal changes in the phytoplankton biomass are caused by primary production, mortality, grazing by zooplankton and sinking. The zooplankton biomass is affected by ingestion, excretion, faecal production, mortality and carnivorous grazing. The changes in the pelagic detritus concentration are determined by the input of dead phytoplankton and zooplankton, the natural mortality of predators, faecal pellets, and sinks – sedimentation, zooplankton grazing and biochemical decomposition. The model simulations were done for selected locations in the southern Baltic Sea (Gdańsk Deep, Bornholm Deep and Gotland Deep) under predicted conditions characterized by changes of temperature, nutrient concentrations and light availability. The results cover the daily, monthly, seasonal and annual POC concentration patterns in the upper water layer. If the assumed trends in light, nutrients and temperature in the southern Baltic correctly predict the conditions in 2050, our calculations indicate that we can expect a two- to three-fold increase in POC concentration in late spring and a shift towards postponed maximum POC concentration. It can also be anticipated that, as a result of the increase in POC, oxygenation of the water layer beneath the halocline will decrease, while the supply of food to organisms at higher trophic levels will increase.
Źródło:
Oceanologia; 2011, 53, 4
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Activation of the operational ecohydrodynamic model (3D CEMBS) – the ecosystem module
Autorzy:
Dzierzbicka-Glowacka, L.
Janecki, M.
Nowicki, A.
Jakacki, J.
Powiązania:
https://bibliotekanauki.pl/articles/47755.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
Baltic Sea
ecosystem model
3D CEMBS model
Baltic ecosystem
ecohydrodynamic model
chlorophyll a
phytoplankton
nutrient
zooplankton
oxygen
hydrodynamic parameter
Źródło:
Oceanologia; 2013, 55, 3
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Seasonal changes in particulate organic matter (POM) concentrations and properties measured from deep areas of the Baltic Sea
Autorzy:
Winogradow, A.
Mackiewicz, A.
Pempkowiak, J.
Powiązania:
https://bibliotekanauki.pl/articles/47588.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
particulate organic matter
seasonal change
particulate organic carbon
chlorophyll a
heterotrophic bacteria
zooplankton
dissolved organic compound
nutrient
deep water
Baltic Sea
Źródło:
Oceanologia; 2019, 61, 4
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Particulate organic carbon in the Southern Baltic Sea: numerical simulations and experimental data
Autorzy:
Dzierzbicka-Glowacka, L.
Kulinski, K.
Maciejewska, A.
Jakacki, J.
Pempkowiak, J.
Powiązania:
https://bibliotekanauki.pl/articles/48082.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
Baltic Sea
Gdansk Deep
calcification
carbon cycle
detritus
nutrient
organic compound
organic matter
particulate organic carbon
photosynthesis
phytoplankton
primary production
sea water
validation
zooplankton
Opis:
Particulate Organic Carbon (POC) is an important component in the carbon cycle of land-locked seas. In this paper, we assess the POC concentration in the Gdańsk Deep, southern Baltic Sea. Our study is based on both a 1D POC Model and current POC concentration measurements. The aim is twofold: (i) validation of simulated concentrations with actual measurements, and (ii) a qualitative assessment of the sources contributing to the POC pool. The POC model consists of six coupled equations: five diffusion-type equations for phytoplankton, zooplankton, pelagic detritus and nutrients (phosphate and total inorganic nitrogen) and one ordinary differential equation for detritus at the bottom. The POC concentration is determined as the sum of phytoplankton, zoo-plankton and pelagic detritus concentrations, all expressed in carbon equivalents. Bacteria are not simulated in this paper. The observed large fluctuations of POC concentrations are attributed to its appreciable seasonal variability. The maximum concentration of POC varied between 870 mgC m−3 in May and 580 mgC m−3 in September, coinciding with the period of maximum dead organic matter and phytoplankton biomass concentrations. The results of the numerical simulations are in good agreement with observed values. The difference between the modelled and observed POC concentrations is equal to 3–28% and depends on the month for which the calculations were made, although no time trend of the difference is observed. The conclusion is that the numerical simulations are a ufficiently good reflection of POC dynamics in the Baltic.
Źródło:
Oceanologia; 2010, 52, 4
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-7 z 7

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