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Project summary
Eutrophication
has become a significant environmental problem in the Baltic Sea during recent
decades. Indications of this problem include larger and more frequent
phytoplankton blooms of cyanobacteria, increased hypoxic areas, fish kills,
etc. A complete assessment of eutrophication based on measurements of all
system parameters with a proper resolution in time and space would be by far
too costly and time- and labor-consuming. The best
approach is to use both, data from observations and mathematical models that
integrate such data. The main objective of this project is to develop, test,
validate and apply enhanced phytoplankton ecosystem model based on an improved
knowledge of the links between optical properties of seawater in the Baltic Sea
and its composition, including phytoplankton, detritus and colored
dissolved matter (CDOM). The model will be used to show how changes to these
optically important constituents (their concentrations and optical properties)
feed back to the system, impacting phytoplankton cycling, competitive
advantages of some phytoplankton types, biogeochemistry, interactions with
physical oceanographic processes and surface reflectance.
Our
operational goals are: a) to assess how the competitive capabilities of
different phytoplankton functional types are reinforced by their optical
properties; b) to derive improved understanding how physical conditions (solar
insolation, light transmission in water, winds, input of water from rivers and
North Sea etc.) and human activities (for example increased or decreased supply
of nutrients) affect the ecological status of the Baltic Sea and what are the
most important biological influences on physical processes and hydrography; c)
to asses what changes of the ecosystem can or cannot
be observed using ocean color satellite data merged
with an ecosystem model. These goals will be reached through carefully planned
numerical experiments where we will study the cause/effect relationships. Note
that only numerical models let us carry out such experiments. Without models it is impossible to quantitatively predict the
responses of a complex, nonlinear marine system to changing conditions;
The
methods will
be based on numerical modeling verified through
extensive comparisons with observational data. To simulate the physical processes we plan to use the Princeton Ocean Model (POM,
www.aos.princeton.edu/WWWPUBLIC/htdocs.pom/). This model has been used at IOPAN
before. To model phytoplankton we will use updated version of the model
developed by Neumann (2000). Our efforts will include work on the modifications
to improve the treatment of light propagation and phytoplankton photophysiology. We expect that these improvements will
have significant effects on model performance, predictions of phytoplankton
blooms, and the ability of the model to simulate physical/biological
interactions. Coupling optics to ecosystem model will provide following
advantages. (1) Subsurface light-field will be more accurate, which is
important for simulating light sensitive biogeochemical processes such as photosynthesis
and photo-oxidation, and for estimates of thermal heating of the water. (2)
Added constraints on model parameters will reduce uncertainties in ecosystem
simulations. (3) Including optical relationships will make it possible to
directly compare model output to the remotely sensed ocean color.
We will also put more emphasis on including more functional groups of
phytoplankton. We will use an approach, which allows the diverse phytoplankton
types to "self-organize" according to relative fitness (Follows et al., 2007).
This approach has not been used in the modeling
studies in the Baltic Sea so far, but it can results
in new insights about competitive capabilities of different phytoplankton
functional types.
The
significance of this project is related to the fact that
phytoplankton blooms are one of the most critical issues with environmental,
economic and health hazard impacts in the Baltic Sea. Our project will increase
basic understanding and provide information that can be used to improve the
management of this marine environment. A complete assessment of the functioning
of the Baltic ecosystem based solely on in situ experiments is impossible, due
to the complex nature of marine system. The best approach is to use numerical
models that integrate observational data, as we propose here. Our novel
approaches to ecosystem modeling should bring an
answer to a question why sometimes certain phytoplankton types (i.e.
cyanobacteria) undergo intensive blooming.
Project-Supported Peer Reviewed Publications:
1. Stramska M., and P.
Aniskiewicz. Satellite remote sensing signatures of
the Major Baltic Inflows. Remote Sens. 2019, 11, 954.
2. Stramska, M.: Stoń-Egiert, J.; Ostrowska, M. 2020.
Towards modeling growth rates of cyanobacteria in the Baltic Sea. Estuarine, Coastal and Shelf Science.
106853. 10.1016/j.ecss.2020.106853.
Project-Supported Conference Publications:
1. Stramska M., and P. Aniskiewicz. Satellite
remote sensing signatures of the Major Baltic Inflows, Geoph.
Res. Abstracts Vol. 21, EGU2019-3269, 2019
2. Muzyka M., Jakacki
J., Stramska M., Modelling of Baltic Sea Ice - preliminary results of
sensitivity studies, Geoph. Res. Abstracts Vol. 21,
EGU2019-13942, 2019
Project-Supported Popular Science Articles:
1. Bałtyk - Poznajmy Lepiej Nasze Pieękne Morze.
Cześć 1. Wielkie Wlewy Bałtyckie
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Project-Supported Publications:
Jakowczyk M., and M. Stramska, 2014. Spatial
and temporal variability of satellite-derived sea surface temperature in the
Barents Sea, International Journal of Remote Sensing, 35, 17, 6545-6560,
http://dx.doi.org/10.1080/01431161.2014.958247
Stramska, M., and J. Bialogrodzka, 2016, Satellite observations of seasonal and
regional variability of particulate organic carbon concentration in the Barents
Sea. Oceanologia,
http://dx.doi.org/10.1016/j.oceano.2016.04.004
Stramska M., Jankowski
A., Cieszynska A. 2016, Surface currents in the Porsanger fjord in northern Norway, Polish Polar Research,
vol. 37, no. 3, pp. 337-360, 2016, doi:
10.1515/popore-2016-0018
Białogrodzka J., Stramska M., Ficek D., Wereszka M., 2017,
Total suspended particulate matter in the Porsanger
fjord (Norway) in the summers of 2014 and 2015, OCEANOLOGIA, Volume: 60Issue: 1Pages: 1-15, DOI:
10.1016/j.oceano.2017.06.002
Cieszyńska A., Stramska M., 2018,
Climate-related trends and meteorological conditions in the Porsanger
fjord, Norway OCEANOLOGIA, Volume: 60Issue: 3Pages: 344-366, DOI: 10.1016/j.oceano.2018.01.003.
Stramska M., Bersheim K. Y., Jankowski A., Seiland
H., Cieszyńska A., 2018, Observations of coastal
ocean currents in the Barents Sea (Porsangerfjord)
during the summers of 2014 and 2015, ESTUARINE COASTAL AND SHELF SCIENCE,
Volume: 211Pages:
6-22, DOI: 10.1016/j.ecss.2018.02.035
Project-Supported Publications:
Stramska M., 2014.
Particulate organic carbon in the surface waters of the North Atlantic: spatial
and temporal variability based on satellite ocean colour,
International Journal of Remote Sensing, 35:13, 4717-4738.
Świrgoń M., and M. Stramska, 2014,
Comparison of in situ and satellite ocean color determinations of particulate
organic carbon concentration in the global ocean, Oceanologia
http://dx.doi.org/10.1016/j.oceano.2014.09.002
Stramska M., and A. Cieszyńska, 2015, Ocean colour
estimates of particulate organic carbon reservoirs in the global ocean - revisited, International Journal of Remote Sensing, 36:14, 3675-3700, DOI:
10.1080/01431161.2015.1049380
Stramska, M., and J. Bialogrodzka, 2016, Satellite observations of seasonal and
regional variability of particulate organic carbon concentration in the Barents
Sea. Oceanologia,
http://dx.doi.org/10.1016/j.oceano.2016.04.004
Project-Supported Publications:
Stramska M., 2009,
Particulate organic carbon in the global ocean derived from SeaWiFS
ocean color, Deep-Sea Research I, 56, 1459-1470, doi:10.1016/j.dsr.2009.04.009.
Stramska, M, 2010, The
diffusive component of particulate organic carbon export in the North Atlantic
estimated from SeaWiFS ocean color, Deep-Sea Research
I, 284-296, doi:10.1016/j.dsr.2009.11.007
Project-Supported Publications:
Stramska M., 2009,
Particulate organic carbon in the global ocean derived from SeaWiFS
ocean color, Deep-Sea Research I, 56, 1459-1470, doi:10.1016/j.dsr.2009.04.009.
Stramska, M, 2010, The
diffusive component of particulate organic carbon export in the North Atlantic
estimated from SeaWiFS ocean color, Deep-Sea Research
I, 284-296, doi:10.1016/j.dsr.2009.11.007
Project-Supported Publications:
Stramski, D., M. Babin,
and S. B. Wozniak. 2007. Variations in the optical properties of terrigenous
mineral-rich particulate matter suspended in seawater. Limnology and
Oceanography, 52, 2418-2433.
Stramska, M., D. Stramski, M. Cichocka, A. Cieplak, and S. B. Wozniak. Effects of atmospheric
particles from Southern California on the optical properties of seawater.
Journal of Geophysical Research, 113, C08037, doi:10.1029/2007JC004407
Lahet, F. and D. Stramski.
2010. MODIS imagery of turbid plumes in San Diego coastal waters during
rainstorm events. Remote Sensing of Environment, 114, 332-344.
Wozniak, S.B., D. Stramski, M. Stramska, R. A. Reynolds, V. M. Wright, E. Y. Miksic, M. Cichocka, and A. M. Cieplak. Optical variability of seawater in relation to
particle concentration, composition, and size distribution in the nearshore
marine environment at Imperial Beach, California. Journal of Geophysical
Research, submitted
Project-Supported Publications:
Stramska, M., and D. Stramski. 2005. Variability of particulate organic carbon
concentration in the north polar Atlantic based on ocean color observations
with Sea-viewing Wide Field-of-view Sensor (SeaWiFS).
Journal of Geophysical Research, 110, C10018, doi:10.1029/2004JC002762.
Stramska, M . 2006. Diffusive component of the vertical flux of
particulate organic carbon in the north polar Atlantic. Oceanologia,
48, 1-23.
Stramski, D., R. A. Reynolds, M. Babin, S. Kaczmarek, M. R. Lewis,
R. Roettgers, A. Sciandra, M.
Stramska, M. S. Twardowski, and H. Claustre. 2007. Relationships between the surface
concentration of particulate organic carbon and optical properties in the
eastern South Pacific and eastern Atlantic Oceans, Biogeosciences
Discussions, 4, 3453-3530.
Project-Supported Publications:
Lee, Z.-P., M. Darecki, K. L. Carder, C. O. Davis, D. Stramski,
and W. J. Rhea. 2005. Diffuse attenuation coefficient of downwelling
irradiance: An evaluation of remote sensing methods. Journal of Geophysical
Research, 110, C02017, doi: 10.1029/2004JC002573.
Stramska, M., and D. Stramski. 2005. Effects of nonuniform
vertical profile of chlorophyll concentration on remote-sensing reflectance of
the ocean. Applied Optics, 44, 1735-1747.
Stramska, M . 2005. Interannual variability
of seasonal phytoplankton blooms in the north polar Atlantic in response to
atmospheric forcing. Journal of Geophysical Research, 110, C05016, doi: 10.1029/2004JC002457.
Stramska, M., and D. Stramski. 2005. Variability of particulate organic carbon
concentration in the north polar Atlantic based on ocean color observations
with Sea-viewing Wide Field-of-view Sensor (SeaWiFS).
Journal of Geophysical Research, 110, C10018, doi:10.1029/2004JC002762.
Stramska, M., D. Stramski, S. Kaczmarek, D. B.
Allison, and J. Schwarz. 2006. Seasonal and regional differentiation of
bio-optical properties within the north polar Atlantic. Journal of Geophysical
Research, 111, C08003, doi:10.1029/2005JC003293
Stramska, M . 2006. Diffusive component of the vertical flux of
particulate organic carbon in the north polar Atlantic. Oceanologia,
48, 1-23.
Project-Supported Publications:
Stramska, M., D. Stramski, B. G. Mitchell, and C. D. Mobley. 2000.
Estimation of the absorption and backscattering coefficients from in-water
radiometric measurements. Limnology and Oceanography, 45, 628-641.
Loisel, H., and D. Stramski.
2000. Estimation of the inherent optical properties of natural waters from
irradiance attenuation coefficient and reflectance in the presence of Raman scattering.
Applied Optics, 39, 3001-3011.
Stramski, D. and J. Tegowski.
2001. Effects of intermittent entrainment of air bubbles by breaking wind waves
on ocean reflectance and underwater light field. Journal of Geophysical
Research, 106(C12), 31345-31360.
Stramska, D. and T. Petelski. 2003. Observations of oceanic whitecaps in the
north polar waters of the Atlantic. Journal of Geophysical Research, 108(C3),
3086, doi:10.1029/2002JC001321.
Stramska, M., D. Stramski, R. Hapter, S. Kaczmarek, and J. Ston. 2003.
Bio-optical relationships and ocean color algorithms for the north polar region
of the Atlantic. Journal of Geophysical Research, 108(C5), 3143,
doi:10.1029/2001JC001195.
Darecki, M. and D. Stramski.
2004. An evaluation of MODIS and SeaWiFS bio-optical
algorithms in the Baltic Sea. Remote Sensing of Environment, 89, 326-350.
Stramska, M., D. Stramski, S. Kaczmarek, D. B.
Allison, and J. Schwarz. 2006. Seasonal and regional differentiation of
bio-optical properties within the north polar Atlantic. Journal of Geophysical
Research, 111, C08003, doi:10.1029/2005JC003293.