Oceanologia No. 52 (2) / 10
Guest Editor: Tiit Kutser (Estonian Institute, University of Tartu, Tallinn)
Contents
Papers
-
Underwater light field and spectral distribution of attenuation depth in inland and coastal waters: Tuuli Kauer, Helgi Arst, Lea Tuvikene
-
Validation of empirical and semi-analytical remote sensing algorithms for estimating absorption by Coloured Dissolved Organic Matter in the Baltic Sea from SeaWiFS and MODIS imagery: Piotr Kowalczuk, Mirosław Darecki, Monika Zabłocka, Izabela Górecka
-
In situ measurements and satellite remote sensing of case 2 waters:
first results from the Curonian Lagoon: Claudia Giardino, Mariano Bresciani, Renata Pilkaitytė, Marco Bartoli, Artūras Razinkovas
-
Improvement of MERIS level 2 products in Baltic Sea coastal areas by applying the Improved Contrast between Ocean and Land processor (ICOL) - data analysis and validation: Susanne Kratzer, Christian Vinterhav
-
Detecting cyanobacterial blooms in large North European lakes using the Maximum Chlorophyll Index: Krista Alikas, Kersti Kangro, Anu Reinart
-
Can fluctuating asymmetry in Talitrus saltator (Montagu, 1808) (Crustacea, Amphipoda) populations be used as a bioindicator
of stress on sandy beach ecosystems?: Ottavio Ottaviano, Felicita Scapini
-
Energy values and energy resources of two prawns in Baltic coastal waters: the indigenous Palaemon adspersus and
the non-indigenous Palaemon elegans: Urszula Janas, Olimpia Bruska
-
Geostrophic current patterns off the Egyptian Mediterranean coast: Mohamed Salama Kamel
Reports
Chronicle
Dissertations
Papers
Underwater light field and spectral distribution of attenuation depth in inland and coastal waters
Oceanologia 2010, 52(2), 155-170
http://dx.doi.org/10.5697/oc.52-2.155
Tuuli Kauer1,2,*, Helgi Arst1, Lea Tuvikene3
1Estonian Marine Institute, University of Tartu,
Mäealuse St. 14, EE-12618 Tallinn, Estonia
2Institute of Mathematics and Natural Sciences, Tallinn University,
Narva Rd. 25, EE-10120 Tallinn, Estonia;
e-mail: tuulikauer@ut.ee
*corresponding author
3Centre for Limnology, Institute of Agricultural and Environmental Sciences,
Estonian University of Life Sciences,
EE-61117 Rannu, Tartumaa, Estonia
keywords:
underwater light field, attenuation depth, modelling
Received 21 September 2009, revised 12 January 2010, accepted 25 January 2010.
This paper was presented at the Remote Sensing and Water Optics Workshop of the 7th Baltic Sea Science Congress, August 2009, Tallinn, Estonia.
Abstract
The daily variations in the underwater irradiance spectra at different depths were determined using a combination of in situ data
and model calculations. The spectra of the attenuation depth (relevant in optical remote sensing) were derived from these
data. The results are presented for four Estonian lakes (Koorküla Valgjärv, Võrtsjärv, Harku, and Peipsi) and for coastal
waters of the Baltic Sea (Pärnu Bay, Gulf of Riga).
References
Arst H., 2003, Optical properties and remote sensing of multicomponental water bodies, Springer-Verl. & Praxis Publ., Chichester, 231 pp.
Arst H., Erm A., Herlevi A., Kutser T., Leppäranta M., Reinart A., Virta J., 2008a, Optical properties of boreal lake waters in Finland and Estonia, Boreal. Environ. Res., 13 (2), 133-158.
Arst H., Erm A., Reinart A., Sipelgas L., Herlevi A., 2002, Calculating irradiance penetration into water bodies from the measured beam attenuation coefficient II: Application of improved model to different types of lakes, Nord. Hydrol., 33 (2-3), 227-240.
Arst H., Nõges T., Nõges P., Paavel B., 2008b, Relations of phytoplankton in situ primary production, chlorophyll and underwater irradiance in turbid lakes, [in:] European large lakes - Ecosystem changes and their ecological and socioeconomic impacts, Hydrobiologia, 599 (1), 169-176.
http://dx.doi.org/10.1007/s10750-007-9213-z
Bird R. E., Riordan C., 1986, Simple solar spectral model for direct and diffuse irradiance on horizontal and tilted planes at earth's surface for cloudless atmospheres, J. Clim. Appl. Meteorol., 25 (1), 87-97.
http://dx.doi.org/10.1175/1520-0450(1986)025<0087:SSSMFD>2.0.CO;2
Bricaud A., Morel A., Barale V., 1999, MERIS potential for ocean colour studies in the open ocean, Int. J. Remote Sens., 20 (9), 1757-1769.
http://dx.doi.org/10.1080/014311699212461
Dekker A. G., Peters S., Vos R., Rijkeboer M., 2001, Remote sensing for inland water quality detection and monitoring: State-of-art application in Friesland waters, [in:] GIS and remote sensing techniques in land- and water-management, A. Van Dijk & M. G.Bos (eds.), Kluwer Acad., Dordrecht, 17-38.
Giardino C., Brando V. E., Dekker A. G., Strömbeck N., Candiani G., 2007, Assessment of water quality in Lake Garda (Italy) using Hyperion, Remote Sens. Environ., 109 (2), 183-195.
http://dx.doi.org/10.1016/j.rse.2006.12.017
Ivanov A., 1978, Introduction to oceanography, Mir, Moscow, 574 pp., (in Russian).
Kirk J. T. O., 1989, The assessment and prediction of optical water quality, Aust. Water Wastewater Assoc. 13th Fed. Conv., 6-10 March 1989, Canberra, Institut. Eng., Barton, 504-507.
Kirk J. T. O., 1994, Light and photosynthesis in aquatic ecosystems, Univ. Press, Cambridge, 509 pp.
http://dx.doi.org/10.1017/CBO9780511623370
Kondratyev K. Ya., 1965, Actinometry, Gidrometeoizdat, Leningrad, 690 pp., (in Russian).
Kutser T., Herlevi A., Kallio K., Arst H., 2001, A hyperspectral model for interpretation of passive optical remote sensing data from turbid lakes, Sci. Total Environ., 268 (1-3), 47-58.
http://dx.doi.org/10.1016/S0048-9697(00)00682-3
Kyewalyanga M., Platt T., Sathyendranath S., 1992, Ocean primary production calculated by spectral and broad-band models, Mar. Ecol.-Prog. Ser., 85, 171-185.
Mannheim S., Segl K., Heim B., Kaufmann H., 2004, Monitoring of lake water quality using hyperspectral CHRIS-PROBA data, Proc. 2nd CHRIS/Proba Workshop, Frascati, Italy, 28-30 April, ESA/ESRIN (ESA SP-578, July 2004), [http://earth.esa.int/workshops/chris proba 04/papers/26 mannh.pdf].
Mueller J. L., 2002, In-water radiometric profile measurements and data analysis protocols, [in:] Ocean optics protocols for satellite ocean color sensor validation, J. L. Mueller & G. S. Fargion (eds.), Vol. 1, Rev. 3, NASA Goddard Space Flight Center, Greenbelt, 123-137.
Paavel B., Arst H., Metsamaa L., Toming K., Reinart A., Allikas K., Kutser T., 2008a, Optical investigations and remote sensing of CDOM-rich coastal waters, Ocean Optics CD.
Paavel B., Arst H., Reinart A., 2008b, Variability of bio-optical parameters in two North-European large lakes, [in:] European large lakes - Ecosystem changes and their ecological and socioeconomic impacts, Hydrobiologia, 599 (1), 201-211.
http://dx.doi.org/10.1007/s10750-007-9200-4
Paavel B., Arst H., Reinart A., Herlevi A., 2006, Model calculations of diffuse attenuation coeficient spectra in lake waters, Proc. Estonian Acad. Sci. Biol. Ecol., 55 (1), 61-81.
Phillips D. M., Kirk J. T. O., 1984, Study of the spectral variation of absorption and scattering in some Australian coastal waters, Aust. J. Mar. Fresh. Res., 35 (6), 635-644.
http://dx.doi.org/10.1071/MF9840635
Reinart A., Arst H., Nõges P., Nõges T., 2000, Comparision of euphotic layer criteria in lakes, Geophysica, 36, 141-159.
Reinart A., Herlevi A., 1999, Diffuse attenuation coefficient in some Estonian and Finnish lakes, Proc. Estonian Acad. Sci. Biol. Ecol., 48, 267-283.
Sathyendranath S., 1986, Remote sensing of phytoplankton: A review with special reference to picoplankton, [in:] Photosynthetic picoplankton, T. Platt & W. K. W. Li (eds.), Can. Bull. Fish. Aquat. Sci., 214, 561-583.
Sathyendranath S., Platt T., Caverhill C. M., Warnock R. E., Lewis M. R., 1989, Remote sensing of oceanic primary production: computations using a spectral model, Deep-Sea Res., 36 (3), 431-453.
http://dx.doi.org/10.1016/0198-0149(89)90046-0
Schofield O., Bidigare R. R., Prezelin B. B., 1990, Spectral photosynthesis, quantum yield and blue-green light enhancement of productivity rates in the diatom Chaetoceros gracile and the prymnesiophyte Emiliana huxleyi, Mar. Ecol.-Prog. Ser., 64, 175-186.
http://dx.doi.org/10.3354/meps064175
Smith R. C., Prezelin B. B., Bidigare R. R., Baker K. S., 1989, Bio-optical modeling of photosynthetic production in coastal waters, Limnol. Oceanogr., 34 (8), 1524-1544.
http://dx.doi.org/10.4319/lo.1989.34.8.1524
Sosik H. M., 1996, Bio-optical modeling of primary production: consequences of variability in quantum yield and specific absorption, Mar. Ecol.-Prog. Ser., 143, 225-238.
http://dx.doi.org/10.3354/meps143225
Van Mol B., Park Y.-J., Ruddick K., Nechad B., 2004, Mapping of chlorophyll and suspended particulate matter maps from chris imagery of the Oostende core site, Proc. 2nd CHRIS/Proba Workshop, Frascati, Italy, 28-30 April, ESA/ESRIN (ESA SP-578, July 2004), [http://earth.esa.int/workshops/chrisproba 04/papers/29 vanmol.pdf].
Validation of empirical and semi-analytical remote sensing algorithms for estimating absorption by Coloured Dissolved Organic Matter
in the Baltic Sea from SeaWiFS and MODIS imagery
Oceanologia 2010, 52(2), 171-196
http://dx.doi.org/10.5697/oc.52-2.171
Piotr Kowalczuk*, Mirosław Darecki, Monika Zabłocka, Izabela Górecka
Institute of Oceanology, Polish Academy of Science,
ul. Powstańców Warszawy 55, PL-81-712 Sopot, Poland;
e-mail: piotr@iopan.gda.pl
*corresponding author
keywords:
remote sensing, ocean colour, satellite validation, SeaWiFS, MODIS, coloured dissolved organic matter, absorption
Received 18 November 2009, revised 7 April 2010, accepted 12 April 2010.
This paper was presented at the Remote Sensing and Water Optics Workshop of the 7th Baltic Sea Science Congress, August 2009, Tallinn, Estonia.
This study was funded by Statutory Research Programme No. II.5 at the Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland and by research grant No. N N306 294233 awarded to PK by the Polish Ministry of Science and Higher Education.
Abstract
An extensive bio-optical data set obtained from field measurements was used to evaluate the performance of an empirical (Kowalczuk
et al. 2005) and two semi-analytical algorithms: Carder et al. (1999) and GSM01 (Maritorena et al. 2002) for estimating CDOM
absorption in the Baltic Sea. The data set includes coincident measurements of radiometric quantities and absorption coefficients
of CDOM made during 43 cruises between 2000 and 2008. In the first stage of the analysis, the accuracy of the empirical algorithm
by Kowalczuk et al. (2005) was assessed using in situ measurements of remote sensing reflectance. Validation results improved when
matching points located in Gulf of Gdańsk close to the Vistula River mouth were eliminated from the data set. The calculated
errors in the estimation of aCDOM(400) in the first phase of the analysis were Bias = -0.02, RMSE = 0.46 and R2 = 0.70.
In the second stage, the empirical algorithm was tested on satellite data from SeaWiFS and MODIS imagery. The satellite data were
corrected atmospherically with the MUMM algorithm designed for turbid coastal and inland waters and implemented in the SeaDAS
software. The results of the best case scenario for estimating the CDOM absorption coefficient aCDOM(400), based on SeaWiFS
data, were Bias = -0.02, RMSE = 0.23 and R2 = 0.40. The validation of the Kowalczuk et al. (2005) empirical algorithm applied to
MODIS data led to a less accurate estimate of aCDOM(400): Bias = -0.03, RMSE = 0.19 and R2 = 0.29. This assessment of the accuracy of standard semi-analytical algorithms available in the SeaWiFS and MODIS imagery processing software revealed that both algorithms (GSM_01 and Carder) underestimate CDOM absorption in the Baltic Sea with mean systematic and random errors in excess of 70%. The paper presents examples of the
application of the Kowalczuk et al. (2005) empirical algorithm for producing maps of the seasonal distribution of aCDOM(400) in the Baltic Sea between 2004 and 2008.
References
Aas E., Høkedal J., Sørensen K., 2005, Spectral backscattering coefficient in coastal water, Int. J. Remote Sens., 26 (2), 331-343.
http://dx.doi.org/10.1080/01431160410001720324
Bailey S. W., Werdell P. J., 2006, A multi-sensor approach for the on-orbit validation of ocean color satellite data products, Remote Sens. Environ., 102 (1-2), 12-23.
http://dx.doi.org/10.1016/j.rse.2006.01.015
Bélanger S., Xie H., Krotkov N., Larouche P., Vincent W. F., Babin M., 2006, Photomineralization of terrigenous dissolved organic matter in Arctic coastal waters from 1979 to 2003: Interannual variability and implications of climate change, Global Biogeochem.Cy., 20 (4), GB4005, doi:10.1029/2006GB002708.
http://dx.doi.org/10.1029/2006GB002708
Blough N. V., Del Vecchio R., 2002, Chromophoric DOM in the coastal environment [in:] Biogeochemistry of marine dissolved organic matter D. Hansell & C. Carlson (eds.), Acad. Press, New York, 509-546.
Carder K. L., Chen F. R., Lee Z. P., Hawes S. K., 1999, Semianalytic moderate-resolution imaging spectrometer algorithms for chlorophyll a and absorption with bio-optical domains based on nitrate-depletion temperatures, J. Geophys. Res., 104 (C3), 5403-5421.
http://dx.doi.org/10.1029/1998JC900082
Darecki M., Stramski D., 2004, An evaluation of MODIS and SeaWiFS bio-optical algorithms in the Baltic Sea, Remote Sens. Environ., 89 (3), 326-350.
http://dx.doi.org/10.1016/j.rse.2003.10.012
Darecki M., Weeks A., Sagan S., Kowalczuk P., Kaczmarek S., 2003, Optical characteristics of two contrasting case 2 waters and their in uence on remote sensing algorithms, Cont. Shelf Res., 23, 237-250.
http://dx.doi.org/10.1016/S0278-4343(02)00222-4
Del Castillo C. E., Miller R. L., 2008, On the use of ocean color remote sensing to measure the transport of dissolved organic carbon by the Mississippi River Plume Remote Sens. Environ., 112 (3), 836-844.
Del Vecchio R., Subramaniam A., Uz S. Schollaert, Ballabrera Poy R., Brown C. W., Blough N. V., 2009, Decadal time-series of SeaWiFS retrieved CDOM absorption and estimated CO2 photoproduction on the continental shelf of the eastern United States, Geophys.Res. Lett., 36, L02602, doi:10.1029/2008GL036169.
http://dx.doi.org/10.1029/2008GL036169
D'Sa E. J., Hu C., Muller Karger F. E., Carder K. L., 2002, Estimation of colored dissolved organic matter and salinity fields in case 2 waters using SeaWiFS: Examples from Florida Bay and Florida Shelf, Proc. Indian Acad. Sci.(Earth and Planetary Sciences), 111 (3), 197-207.
D'Sa E. J., Miller R. L., 2003, Bio-optical properties in waters in uenced by the Mississippi River during low ow conditions, Remote Sens. Environ., 84 (4), 538-549.
http://dx.doi.org/10.1016/S0034-4257(02)00163-3
Fargion G. S., Mueller J. L., 2000, Ocean optics protocols for satellite ocean color sensor validation, Revision 2 NASA Tech. Memo. 200 209966, NASA Goddard Space Flight Center, Greenbelt, MD.
Fichot C. G., Sathyendranath S., Miller W. L., 2008, SeaUV and SeaUV(C): Algorithms for the retrieval of UV/visible diffuse attenuation coefficients from ocean color, Remote Sens. Environ., 112 (4), 1584-1602.
Garver S. A., Siegel D. A., 1997, Inherent optical property inversion of ocean color spectra and its biogeochemical interpretation, 1. Time series from the Sargasso Sea, J. Geophys. Res., 102 (8), 18607-18625.
http://dx.doi.org/10.1029/96JC03243
Gordon H. R., Ding K., 1992, Self-shading of in-water instruments, Limnol. Oceanogr., 37 (3), 491-500.
http://dx.doi.org/10.4319/lo.1992.37.3.0491
Gregg W. W., Casey N. W., 2004, Global and regional evaluation of the SeaWiFS chlorophyll data set, Remote Sens. Environ., 93 (4), 463-479.
http://dx.doi.org/10.1016/j.rse.2003.12.012
Hansell D. A., Carlson C. A., 2001, Marine dissolved organic matter and the carbon cycle, Oceanography, 14 (4), 41-49.
Hooker S. B., Esaias W. E., 1993, An overview of the SeaWiFS project, Eos Trans. Amer. Geophys. Union, 74, 241-246.
http://dx.doi.org/10.1029/93EO00945
Jerlov N. G., 1976, Marine optics, Elsevier, New York, 231 pp.
Johannessen S. C., Miller W. L., 2001, Quantum yield for the photochemical production of dissolved inorganic carbon in seawater, Mar. Chem., 76 (4), 271-283.
http://dx.doi.org/10.1016/S0304-4203(01)00067-6
Johannessen S. C., Miller W. L., Cullen J. J., 2003, Calculation of UV attenuation and colored dissolved organic matter absorption spectra from measurements of ocean color, J. Geophys. Res., 108 (C9), 3301, doi:10.1029/2000JC000514.
http://dx.doi.org/10.1029/2000JC000514
Kahru M., 1997, Using satellites to monitor large-scale environmental change: A case study of cyanobacteria blooms in the Baltic Sea [in:] M. Kahru & C. W. Brown (eds.), Monitoring algal blooms: New techniques for detecting large scale environmental change, Springer Verl. Land. Biosci., 43-61.
Kahru M., Mitchell B. G., 1999, Empirical chlorophyll algorithm and preliminary SeaWiFS validation for the California Current, Int.J. Remote Sens., 20, 3421-3429.
http://dx.doi.org/10.1080/014311699211453
Kahru M., Mitchell B. G., 2001, Seasonal and non-seasonal variability of satellite derived chlorophyll and colored dissolved organic matter concentration in the California Current, J. Geophys. Res., 106 (C2), 2517-2529.
http://dx.doi.org/10.1029/1999JC000094
Kahru M., Savchuk O. P., Elmgren R., 2007, Satellite measurements of cyanobacterial bloom frequency in the Baltic Sea: interannual and spatial variability, Mar. Ecol. Prog. Ser., 343, 15-23.
http://dx.doi.org/10.3354/meps06943
Kowalczuk P., 1999, Seasonal variability of yellow substance absorption in the surface layer of the Baltic Sea, J. Geophys. Res., 104 (C12), 30047-30058.
http://dx.doi.org/10.1029/1999JC900198
Kowalczuk P., Darecki M., Olszewski J., Kaczmarek S., 2005, Empirical relationships between Coloured Dissolved Organic Matter (CDOM) absorption and apparent optical properties in Baltic Sea waters, Int.J. Remote Sens., 26 (2),345-370.
http://dx.doi.org/10.1080/01431160410001720270
Kowalczuk P., Kaczmarek S., 1996, Analysis of temporal and spatial variability of yellow substance absorption in the Southern Baltic, Oceanologia, 38 (1), 3-32.
Kowalczuk P., Sagan S., Olszewski J., Darecki M., Hapter R., 1999, Seasonal changes in selected optical parameters in the Pomeranian Bay in 1996-1997 Oceanologia, 41 (3), 309-334.
Kowalczuk P., Stedmon C. A., Markager S., 2006, Modeling absorption by CDOM in the Baltic Sea from season, salinity and chlorophyll, Mar. Chem., 101 (1-2), 1-11.
http://dx.doi.org/10.1016/j.marchem.2005.12.005
Kutser T., 2004, Quantitative detection of chlorophyll in cyanobacterial blooms by satellite remote sensing, Limnol. Oceanogr., 49 (6), 2179-2189.
http://dx.doi.org/10.4319/lo.2004.49.6.2179
Kutser T., Paavel B., Metsamaa L., Vahtmäe E., 2009, Mapping coloured dissolved organic matter concentration in coastal waters, Int. J. Remote Sens., 30 (22), 5843-5849.
http://dx.doi.org/10.1080/01431160902744837
Mannino A., Russ M. E., Hooker S. B., 2008, Algorithm development and validation for satellite-derived distributions of DOC and CDOM in the U.S. Middle Atlantic Bight, J. Geophys. Res., 113, C07051, doi:10.1029/2007JC004493.
http://dx.doi.org/10.1029/2007JC004493
Maritorena S., Siegel D. A., Peterson A. R., 2002, Optimization of of a semi-analytical ocean color model for global-scale applications Appl. Optics, 41 (15), 2705-2714.
http://dx.doi.org/10.1364/AO.41.002705
Melin F., Maritorena S., 2007, Data merger success criteria [in:] Ocean colour data merging, W. Gregg (ed.), IOCCG Rep. No. 6, Dartmouth, CA, 68 pp.
Morel A., Gentili B., 1993, Diffuse re ectance of oceanic waters, II Bidirectional aspects, Appl. Optics, 32 (33), 6864-6872.
http://dx.doi.org/10.1364/AO.32.006864
Morel A., Prieur L., 1977, Analysis in variation of ocean color, Limnol. Oceanogr., 22 (4), 709-722.
http://dx.doi.org/10.4319/lo.1977.22.4.0709
Moses W. J., Gitelson A. A., Berdnikov S., Povazhniy V., 2009, Estimation of chlorophyll a concentration in case II waters using MODIS and MERIS data - successes and challenges, Environ. Res. Lett., 4, 045005, doi:10.1088/17489326/4/4/045005, 8 pp.
Mueller J. L., Austin R. W., 1992, Ocean optics protocols for SeaWiFS validation, NASA Tech. Memo. 104566, Vol. 5, NASA Goddard Space Flight Center, Greenbelt, MD, 43 pp.
Olszewski J., Sagan S., Darecki M., 1992, Spatial and temporal changes in some optical parameters in the southern Baltic Oceanologia, 33, 87-103.
Olszewski J., Sokólski M., Kuśmierczyk Michulec J., 1995, The method of continuous measurements of the diffusivity of the natural light field over the sea, Oceanologia, 37 (2), 299-310.
O'Reilly J. E., Maritorena S., Mitchell B. G., Siegel D. A., Carder K. L., Garver S.A.,Kahru M.,McClain C.R.,1998,Ocean color algorithms for SeaWiFS, J. Geophys. Res., 103 (C11), 24937-24953.
http://dx.doi.org/10.1029/98JC02160
Reinart A., Kutser T., 2006, Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea, Remote Sens. Environ., 102 (1-2), 74-85.
http://dx.doi.org/10.1016/j.rse.2006.02.013
Ruddick K. G., Ovidio F., Rijkeboer M., 2000, Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters, Appl. Optics, 39 (6), 897-912.
http://dx.doi.org/10.1364/AO.39.000897
Sagan S., 1991, Light transmission in the water of the southern Baltic Sea, Diss. Monogr. 2, Inst. Oceanol. PAN, Sopot, 137 pp., (in Polish).
Sagan S., 2008, The inherent optical properties of Baltic waters Diss. Monogr. 21, Inst. Oceanol., Sopot, 244 pp., (in Polish).
Sathyendranath S.(ed.), 2000, Remote sensing of ocean colour in coastal, and other optically-complex, waters IOCCG Rep.No. 3, Dartmouth, CA, 140 pp.
Siegel H., Gerth M., Ohde T., Heene T., 2005, Ocean colour remote sensing relevant water constituents and optical properties of the Baltic Sea, Int. J. Remote Sens., 26 (2), 315-334.
http://dx.doi.org/10.1080/01431160410001723709
Siegel D. A., Maritorena S., Nelson N. B., Behrenfeld M. J., 2005a,In-dependence and interdependencies among global ocean color properties: Reassessing the bio-optical assumption, J. Geophys. Res., 110, C07011, doi:10.1029/2004JC002527.
http://dx.doi.org/10.1029/2004JC002527
Siegel D. A., Maritorena S., Nelson N. B., Behrenfeld M. J., McClain C. R., 2005b, Colored dissolved organic matter and its in uence on the satellite-based characterization of the ocean biosphere, Geophys. Res. Lett., 32, L20605, doi:10.1029/2005GL024310.
http://dx.doi.org/10.1029/2005GL024310
Siegel D. A., Maritorena S., Nelson N. B., Hansell D. A., Lorenzi Kayser M.,2002, Global distribution and dynamics of colored dissolved and detrital organic materials, J. Geophys. Res., 107 (C12), 3228, doi:10.1029/2001JC000965.
http://dx.doi.org/10.1029/2001JC000965
Sverdrup H.U., 1953, On conditions for the vernal blooming of phytoplankton, J. Cons. Cons. Int. Explor. Mer., 18 (3), 287-295.
Zibordi G., Ferrari G. M., 1995, Instrument self-shading in underwater optical measurements: Experimental data Appl.Optics,34 (2),2750-2754.
http://dx.doi.org/10.1364/AO.34.002750
In situ measurements and satellite remote sensing of case 2 waters: first results from the Curonian Lagoon
Oceanologia 2010, 52(2), 197-210
http://dx.doi.org/10.5697/oc.52-2.197
Claudia Giardino1,*, Mariano Bresciani1, Renata Pilkaitytė2, Marco Bartoli3, Artūras Razinkovas2
1Optical Remote Sensing Group, CNR-IREA,
via Bassini 15, 20133 Milano, Italy;
e-mail: giardino.c@irea.cnr.it
*corresponding author
2Coastal Research and Planning Institute, University of Klaipeda,
H. Manto 84, LT-92294 Klaipeda, Lithuania
3Environmental Science Department, University of Parma,
viale G. P. Usberti 33/A, 43100 Parma, Italy
keywords:
satellite images, lagoon, eutrophication
Received 18 September 2009, revised 19 February 2010, accepted 8 April 2010.
This paper was presented at the Remote Sensing and Water Optics Workshop of the 7th Baltic Sea Science Congress, August 2009, Tallinn, Estonia.
Abstract
In this study we present calibration/validation activities associated with satellite MERIS image processing and aimed at estimating
chl a and CDOM in the Curonian Lagoon. Field data were used to validate the performances of two atmospheric correction algorithms,
to build a band-ratio algorithm for chl a and to validate MERIS-derived maps. The neural network-based Case 2 Regional processor was
found suitable for mapping CDOM; for chl a the band-ratio algorithm applied to image data corrected with the 6S code was found more
appropriate. Maps were in agreement with in situ measurements.
This study confirmed the importance of atmospheric correction to estimate water quality and demonstrated the usefulness of
MERIS in investigating eutrophic aquatic ecosystems.
References
Baker K. S., Smith R. C., 1990, Irradiance transmittance through the air-water interface, Ocean Optics X, R. W. Spinrad (ed.), Proc. SPIE, 1302, 556-565.
Beutler M., Wiltshire K. H., Meyer B., Moldaenke C., Lüring C., Meyerhöfer M., Hansen U.-P., Dau H., 2002, A uorometric method for the differentiation of algal populations in vivo and in situ, Photosynth. Res., 72 (1), 39-53.
http://dx.doi.org/10.1023/A:1016026607048
Breber P., Povilanskas R., Armaitienė A., 2008, Recent evolution of fishery and land reclamation in Curonian and Lesina lagoons, Hydrobiologia, 611 (1), 105-114.
http://dx.doi.org/10.1007/s10750-008-9453-6
Dall’Olmo G., Gitelson A. A., 2005, Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results, Appl. Optics, 44 (3), 412-422.
http://dx.doi.org/10.1364/AO.44.000412
Dall’Olmo G., Gitelson A. A., Rundquist D. C., 2003, Towards a unified approach for remote estimation of chlorophyll-a in both terrestrial vegetation and turbid productive waters, Geophys. Res. Lett., 30 (18), 1938.
http://dx.doi.org/10.1029/2003GL018065
Dekker A. G., 1993, Detection of optical water quality parameters for eutrophic waters by high resolution remote sensing, Ph. D. thesis, Free University, Amsterdam; The Netherlands.
Doerffer R., Schiller H., 2008, MERIS regional coastal and lake case 2 water project - Atmospheric Correction ATBD, v. 1.0, May 2008, GKSS Res. Centre, Geesthacht.
Floricioiu D., Rott H., 2005, Atmospheric correction of MERIS data over perialpine regions, MERIS-(A)ATSR Workshop, Frascati, Italy, 26-30 September 2005, CD-ROM ISBN 92-9092-908-1 ESA.
Fomferra N., Brockmann C., 2005, Beam - the ENVISAT MERIS and AATSR toolbox, Proc. MERIS-(A)ATSR Workshop, Frascati, Italy, ESA/ESRIN, [http://www.brockmann-consult.de/beam/].
Giardino C., Brando V. E., Dekker A. G., Strömbeck N., Candiani G., 2007, Assessment of water quality in Lake Garda (Italy) using Hyperion, Remote Sens. Environ., 109 (2), 183-195.
http://dx.doi.org/10.1016/j.rse.2006.12.017
Gitelson A., 1992, The peak near 700 nm on radiance spectra of algae and water: relationship of its magnitude and position with chlorophyll concentration, Int. J. Remote Sens., 13 (17), 3367-3373.
http://dx.doi.org/10.1080/01431169208904125
Gitelson A. A., Schalles J. F., Hladik C. M., 2007, Remote chlorophyll-a retrieval in turbid, productive estuaries: Chesapeake Bay case study, Remote Sens. Environ., 109 (4), 464-472.
http://dx.doi.org/10.1016/j.rse.2007.01.016
Han F. G., Rundquist D. C., 1997, Comparison of NIR/RED ratio and first derivate of re ectance in estimating algal-chlorophyll concentration: A case study in a turbid reservoir, Remote Sens. Environ., 62 (3), 253-261.
http://dx.doi.org/10.1016/S0034-4257(97)00106-5
Kahru M., Savchuk O. P., Elmgren R., 2007, Satellite measurements of cyanobacterial bloom frequency in the Baltic Sea: interannual and spatial variability, Mar. Ecol.-Prog. Ser., 343, 15-23.
http://dx.doi.org/10.3354/meps06943
Keller P. A., 2001, Comparison of two inversion techniques of a semi-analytical model for the determination of lake water constituents using imaging spectrometry data, Sci. Total Environ., 268 (1-3), 189-196.
http://dx.doi.org/10.1016/S0048-9697(00)00690-2
Kotchenova S. Y., Vermote E. F., Matarrese R., Klemm Jr. F. J., 2006, Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part I: Path radiance, Appl. Optics, 45 (26), 6762-6774.
http://dx.doi.org/10.1364/AO.45.006762
Kratzer S., Brockmann C., Moore G., 2008, Using MERIS full resolution data to monitor coastal waters. A case study from Himmerfjärden, a fjord-like bay in the northwestern Baltic Sea, Remote Sens. Environ., 112 (5), 2284-2300.
http://dx.doi.org/10.1016/j.rse.2007.10.006
Krevs A., Koreiviene J., Paskauskas R., Sulijiene R., 2007, Phytoplankton production and community respiration in different zones of the Curonian lagoon during the midsummer vegetation period, Trans. Waters Bull., 1 (1), 17-26.
Kutser T., 2009, Passive optical remote sensing of cyanobacteria and other intense phytoplankton blooms in coastal and inland waters, Int. J. Remote Sens., 30 (17), 4401-4425.
http://dx.doi.org/10.1080/01431160802562305
Kutser T., Metsamaa L., Strömbeck N., Vahtmäe E., 2006, Monitoring cyanobacterial blooms by satellite remote sensing, Estuar. Coast. Shelf Sci., 67 (1-2), 303-312.
http://dx.doi.org/10.1016/j.ecss.2005.11.024
Kutser T., Pierson D. C., Kallio K., Reinart A., Sobek S., 2005, Mapping lake CDOM by satellite remote sensing, Remote Sens. Environ., 94 (4), 535.540.
Lorenzen C. J., 1967, Determination of chlorophyll and pheo-pigments: spectro-photometric equations, Limnol. Oceanogr., 12 (2), 343-346.
http://dx.doi.org/10.4319/lo.1967.12.2.0343
Ložys L., 2004, The growth of pikeperch (Sander lucioperca L.) and perch (Perca uviatilis L.) under different water temperature and salinity conditions in the Curonian Lagoon and Lithuanian coastal waters of the Baltic Sea, Hydrobiologia, 514 (1-3), 105-113.
http://dx.doi.org/10.1023/B:hydr.0000018211.26378.b9
Morel A., Prieur L., 1977, Analysis of variations in ocean color, Limnol. Oceanogr., 22 (4), 709-722.
http://dx.doi.org/10.4319/lo.1977.22.4.0709
Paldavičienċ A., Mazur-Marzec H., Razinkovas H., 2009, Toxic cyanobacteria blooms in the Lithuanian part of the Curonian Lagoon, Oceanologia, 51 (2), 203-216.
Pierson D. C., Strömbeck N., 2001, Estimation of radiance re ectance and the concentrations of optically active substances in Lake Mälaren, Sweden, based on direct and inverse solutions of a simple model, Sci. Total Environ., 268 (1-3), 171-188.
http://dx.doi.org/10.1016/S0048-9697(00)00680-X
Reinart A., Kutser T., 2006, Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea, Remote Sens. Environ., 102 (1-2), 74-85.
http://dx.doi.org/10.1016/j.rse.2006.02.013
Ruiz-Verdù A., Koponen S., Heege T., Doerffer R., Brockmann C., Kallio K., Pyhalahti T., Pena-Martìnez R., Polvorinos À., Heblinski J., Ylostalo P., Conde L., Odermatt D., Estellès V., Pulliainen J., 2008, Development of MERIS lake water algorithms: validation results from Europe, Proc. 2nd MERIS/(A)ATSR User Workshop, Frascati, Italy, ESA/ESRIN.
Schalles J. F., 2006, Optical remote sensing techniques to estimate phytoplankton chlorophyll a concentrations in coastal waters with varying suspended matter and CDOM concentrations, [in:] Remote sensing of aquatic coastal ecosystem processes: Science and management applications, L. Richardson & E. Ledrew (eds.), Springer, Berlin, 27-79.
Strömbeck N., Pierson E., 2001. The effects of variability in the inherent optical properties on estimations of chlorophyll a by remote sensing in Swedish freshwaters, Sci. Total Environ., 268 (1-3), 123-137.
http://dx.doi.org/10.1016/S0048-9697(00)00681-1
Vermote E. F., Tanré D., Deuzé J. L., Herman M., Morcrette J. J., 1997, Second Simulation of the satellite signal in the solar spectrum, 6S: An overview, IEEE Geosci. Remote, 35 (3), 675-686.
http://dx.doi.org/10.1109/36.581987
Zemlys P., Ertürk A., Razinkovas A., 2008, 2D finite element ecological model for the Curonian lagoon, Hydrobiologia, 611 (1), 167-179.
http://dx.doi.org/10.1007/s10750-008-9452-7
Improvement of MERIS level 2 products in Baltic Sea coastal areas by applying the Improved Contrast between Ocean and Land processor (ICOL) - data analysis and validation
Oceanologia 2010, 52(2), 211-236
http://dx.doi.org/10.5697/oc.52-2.211
Susanne Kratzer1, Christian Vinterhav2
1Department of Systems Ecology, Stockholm University,
Svante Arrheniusvägen 21 A, SE-106 91 Stockholm, Sweden
2Department of Physical Geography and Quaternary Geology, Stockholm University,
Svante Arrheniusvägen 21 A, SE-106 91 Stockholm, Sweden
keywords:
MERIS full resolution data, optical case 2 waters, adjacency effect, algorithm development, MERIS standard processor, FUB processor, C2R processor
Received 5 October 2009, revised 3 February 2010, accepted 22 April 2010.
This paper was presented at the Remote Sensing and Water Optics Workshop of the 7th Baltic Sea Science Congress, August 2009, Tallinn, Estonia.
Abstract
In this paper we compare the following
MERIS processors against sea-truthing data:
the standard MERIS processor (MEGS 7.4.1), the Case 2
Regional processor (C2R) of the German Institute
for Coastal Research (GKSS), and the Case 2
Water Properties processor developed at the Freie
Universität Berlin (FUB). Furthermore, the Improved
Contrast between Ocean and Land processor (ICOL), a prototype
processor for the correction of adjacency effects from land,
was tested on all three processors, and the retrieval of level 2
data was evaluated against sea-truthing data before and after
ICOL processing.
The results show that by using ICOL the retrieval of
spectral reflectance in the open sea was improved for all processors.
After ICOL processing, the FUB showed rather small errors in
the blue, but underestimated in the red -34% Mean Normalised
Bias (MNB) and 37% Root Mean Square (RMS). For MEGS the reflectance
in the red was underestimated by about -20% MNB and 23% RMS,
whereas the reflectance in the other channels was well predicted,
even without any ICOL processing. The C2R underestimated the
red with about -27% MNB and 29% RMS and at 412 nm it overestimated
the reflectance with about 23% MNB and 29% RMS. At the outer
open sea stations ICOL processing did not have a strong effect:
the effect of the processor diminishes progressively up to
30 km from land.
At the open sea stations the ICOL processor improved
chlorophyll retrieval using MEGS from -74% to about 34% MNB,
and TSM retrieval from -63% to about 22% MNB. Using FUB in combination
with ICOL gave even better results for both chlorophyll (25%
MNB and 45% RMS) and TSM (-4% MNB and 36% RMS) in the open
Baltic Sea. All three processors
predicted TSM rather well, but the standard processor gave
the best results (-12% MNB and 17% RMS). The C2R had
a very low MNB for TSM (1%), but a rather high RMS (54%). The
FUB was intermediate with -16% MNB and 31% RMS.
In coastal waters, the spectral diffuse attenuation
coefficient Kd(490) was well predicted using
FUB or MEGS in combination with ICOL (MNB about 12% for FUB
and 0.4% for MEGS). Chlorophyll was rather well predicted in
the open Baltic Sea using FUB with
ICOL (MNB 25%) and even without ICOL processing (MNB about 15%).
ICOL-processed MEGS data also gave rather good retrieval of chlorophyll
in the coastal areas (MNB of 19% and RMS of 28%). In the open
Baltic Sea chlorophyll retrieval
gave a MNB of 34% and RMS of 70%, which may be due to the considerable
patchiness caused by cyanobacterial blooms.
The results presented here indicate that with the MERIS
mission, ESA and co-workers are in the process of solving some
of the main issues regarding the remote sensing of coastal waters:
spatial resolution; land-water adjacency effects; improved level 2
product retrieval in the Baltic Sea, i.e. the retrieval of spectral
reflectance and of the water quality products TSM and chlorophyll.
References
Andréfouët S., Costello M. J., Rast M., Sathyendranath S., 2008, Earth observations for marine and coastal biodiversity and ecosystems Remote Sens. Environ., 112 (8), 3297-3299.
http://dx.doi.org/10.1016/j.rse.2008.04.006
Bukata R. P., 2005, Satellite monitoring of inland and coastal water quality: Restrospection, introspection, future directions CRC Press, Taylor & Francis Group, Boca Raton, Fl, 246 pp.
Carlund T., Hakansson B., Land P., 2005, Aerosol optical depth over the Baltic Sea derived from AERONET and SeaWiFS measurements, Int. J. Remote Sens., 26 (2), 233-245.
http://dx.doi.org/10.1080/01431160410001720306
Cristina S. V., Goela P., Icely J. D., Newton A., Fragoso B., 2008, Assessment of water-leaving reflectance of the oceanic and coastal waters using MERIS satellite products off the southwest coast of Portugal, J. Coastal Res.,56 (Spec. Iss.), 1479-1483.
Doerffer R., 2002, Protocols for the validation of MERIS water products European Space Agency, Doc. No. PO TN MEL GS 0043.
Doerffer R., Schiller H., 2006, The MERIS neural network algorithm [in:] Remote sensing of inherent optical properties: Fundamentals, tests of algorithms, and applications, Z. P. Lee (ed.), IOCCG Rep. No.5, Dartmouth, 43-47.
Doerffer R., Schiller H.,2008,MERIS regional coastal and lake case 2 water project - Atmospheric Correction ATBD v.1.0, 18 May 2008, GKSS Res. Centre,
Geesthacht.
Fischer J., Fell F., 2001, Numerical simulation of the light field in the atmosphere-ocean system using the matrix-operator method, J. Quant. Spectrosc. Ra., 69 (3),351-388.
http://dx.doi.org/10.1016/S0022-4073(00)00089-3
Jansson B. O., 2003, The Baltic Sea [in:] Large marine ecosystems of the world G. Hempel & K. Sherma (eds.), Elsevier Sci., Amsterdam, 145-170.
Je-rey S. W., Humphrey G. F., 1975, New spectrophotometric equation for determining chlorophyll a, b, c1 and c2 Biochem. Physiol. P-, 167, 194-204.
Je-rey S. W., Welschmeyer N. A., 1997, Appendix F: Spectrophotometric and uorometric equations in common use in oceanography [in:] Phytoplankton pigments in oceanography S. W. Je-rey, R. F. C. Mantoura & S. W. Wright (eds.), Monogr. Oceanographic Methodol., UNESCO, Paris, 597-615.
Kirk J. T. O., 1994, Light and photosynthesis in aquatic ecosystems 2nd edn., Cambridge Univ. Press, Cambridge, 528 pp.
http://dx.doi.org/10.1017/CBO9780511623370
Kowalczuk P., Olszewski J., Darecki M., Kaczmarek S., 2005, Empirical relationships between coloured dissolved organic matter (CDOM) absorption and apparent optical properties in Baltic Sea waters, Int. J. Remote Sens., 26 (2), 345-370.
http://dx.doi.org/10.1080/01431160410001720270
Kratzer S., 2000, Bio-optical studies of coastal waters, Ph. D. thesis, School of Ocean Sciences, Univ. Wales, Bangor.
Kratzer S., Håkansson B., Sahlin C., 2003, Assessing Secchi and photic zone depth in the Baltic Sea from space, Ambio, 32 (8), 577-585.
Kratzer S., Brockmann C., Moore G., 2008, Using MERIS full resolution data (300 m spatial resolution) to monitor coastal waters - A case study from Himmerfjärden, a fjord-like bay in the north-western Baltic Sea Remote Sens. Environ., 112 (5), 2284-2300.
http://dx.doi.org/10.1016/j.rse.2007.10.006
Kratzer S., Tett P., 2009, Using bio-optics to investigate the extent of coastal waters: A Swedish case study Hydrobiologia, 629 (1), 169-186.
http://dx.doi.org/10.1007/s10750-009-9769-x
Morel A., Prieur L., 1977, Analysis of variations in ocean colour Limnol. Oceanogr., 22 (4), 709-722.
http://dx.doi.org/10.4319/lo.1977.22.4.0709
Mueller J. L., ustin R. W., 1995, Ocean optics protocols for SeaWiFS validation Rev.1 ., NASA Tech. Memo. 104566, Vol. 25, NASA Goddard Space Flight Center, Greenbelt, MD, 66 pp.
Parsons T. R., Maita Y., Lalli C. M., 1984, A manual of chemical and biological methods for seawater analysis Pergamon Press, Michigan, 173 pp.
Pierson D., Kratzer S., Strömbeck N., Håkansson B.,2008,Relationship between the attenuation of downwelling irradiance at 490 nm with the attenuation of PAR (400 nm-700 nm) in the Baltic Sea Remote Sens.Environ., 112 (3), 668-680.
Santer R., Zagolski F., Gilson M., 2007, ICOL ATBD v. 0.1, 28 February 2007, Univ. Littoral, France.
Santer R., Zagolski F., 2009, ICOL. Improve contrast between ocean and land. ATBD-MERIS level-1C Rev. 1, Rep. D6 (1), 6 January 2009, Univ. Littoral, France.
Schroeder T., Behnert I., Schaale M., Fischer J., Doer-er R., 2007a, Atmospheric correction for MERIS above Case-2 waters Int. J. Remote Sens., 28 (7), 1469-1486.
http://dx.doi.org/10.1080/01431160600962574
Schroeder T., Schaale M., Fischer J., 2007b, Retrieval of atmospheric and oceanic properties from MERIS measurements: A new Case-2 water processor for BEAM, Int. J. Remote Sens., 28 (24), 5627-5632.
http://dx.doi.org/10.1080/01431160701601774
Sørensen K., Grung M., Röttgers R., 2003, An intercomparison of in vitro chlorophyll-a determinations, Proc.MERIS cal/val meeting at ESRIN, Frascati, Italy, 10-11 December.
Strickland J. H. D., Parsons T. R., 1972, A practical handbook of sea-water analysis, B. Fish. Res. Board Can., 167, 185-203.
Vinterhav C., 2008, Remote sensing of Baltic coastal waters using MERIS - a comparison of three Case-2 water processors Final degree project (examensarbete, 30 ECTS), Dept. Phys. Geogr. Quatern. Geol., SU.
Zieliński T., Petelski T., 2006, Studies of aerosol physical properties in the coastal area, Opt. Appl., 36 (4), 629-634.
Detecting cyanobacterial blooms in large North European lakes using the Maximum Chlorophyll Index
Oceanologia 2010, 52(2), 237-257
http://dx.doi.org/10.5697/oc.52-2.237
Krista Alikas1,*, Kersti Kangro2, Anu Reinart1
1Tartu Observatory,
EE-61602, Tõravere, Tartumaa, Estonia;
e-mail: alikas@ut.ee
*corresponding author
2Centre for Limnology,
Institute of Agricultural and Environmental Sciences,
Estonian University of Life Sciences,
EE-61117 Rannu, Tartumaa, Estonia
keywords:
MERIS, Maximum Chlorophyll Index, phytoplankton, cyanobacteria, chlorophyll a
Received 8 October 2009, revised 16 April 2010, accepted 17 April 2010.
This paper was presented at the Remote Sensing and Water Optics Workshop of the 7th Baltic Sea Science Congress, August 2009, Tallinn, Estonia.
Abstract
The Maximum Chlorophyll Index (MCI), developed for the MERIS sensor processing scheme, is used to investigate the seasonal
dynamics, spatial distribution, and coverage of cyanobacterial blooms over Lake Peipsi (Estonia/Russia) and Lake Võrtsjärv
(Estonia). In these optically complex waters, the amounts of suspended matter and dissolved organic matter vary greatly and
independently of the phytoplankton biomass. We demonstrate that MCI is a useful, new tool for detecting and estimating cyanobacterial
biomass (R2 = 0.73), phytoplankton biomass (R2 = 0.70) and chlorophyll a concentration (R2 = 0.64). The MCI-derived
results are consistent with known patterns of phytoplankton dynamics in these lakes, whose optical properties are in the same range as in many coastal
regions of the Baltic Sea.
References
Alikas K., Reinart A., 2008, Validation of the MERIS products on large European lakes: Peipsi, Vänern and Vättern, Hydrobiologia, 599 (1), 161-168.
http://dx.doi.org/10.1007/s10750-007-9212-0
Carvalho L., Solimini A. G., Phillips G., Pietiläinen O.-P., Moe J., Cardoso A. C., Solheim A. L., Ott I., S?ndergaard M., Tartari G., Rekolainen S., 2009, Site-specific chlorophyll reference conditions for lakes in Northern and Western Europe, Hydrobiologia, 633 (1), 59-66.
http://dx.doi.org/10.1007/s10750-009-9876-8
Clarke R., Carvalho L., Maberly S., 2006., Uncertainty in chlorophyll and total phosphorus classifications, [in:] Chlorophyll and phosphorus classifications for UK lakes, L. Carvalho, G. Phillips, S. Maberly & R. Clarke, Fin. Rep.SNIFFER (Proj. WFD38), Edinburgh, [available at http://www.sniffer.org.uk/].
Doerffer R., Schiller H., 2008, MERIS lake water algorithm for BEAM, algorithm theoretical basis document, http://www.brockmann-consult.de/beam-wiki/download/attachments/1900548/ATBDlakewaterRD20080610.pdf?version=1
Doerffer R., Schiller H., 2007, The MERIS Case 2 water algorithm, J. Remote Sens., 28 (3-4), 517-535.
http://dx.doi.org/10.1080/01431160600821127
Feldmann T., Nõges P., 2007, Factors controlling macrophyte distribution in large shallow Lake Võrtsjärv, Aquat. Bot., 87 (1), 15-21.
http://dx.doi.org/10.1016/j.aquabot.2007.01.004
Frisk T., Bilaletdin ä., Kaipainen H., Malve O., Möls M., 1999, Modelling phytoplankton dynamics of the eutrophic Lake Võrtsjärv, Estonia, Hydrobiologia, 414 (0), 59-69.
http://dx.doi.org/10.1023/A:1003802912687
Gons H. J., Auer M. T., Effler S. W., 2008, MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes, Remote Sens. Environ., 112 (11), 4098-4106.
http://dx.doi.org/10.1016/j.rse.2007.06.029
Gons H. J., Rijkeboer M., Ruddick K. G., 2002, A chlorophyll-retrieval algorithm for satellite imagery (Medium Resolution Imaging Spectrometer) of inland and coastal waters, J. Plankton Res., 24 (9), 947-951.
http://dx.doi.org/10.1093/plankt/24.9.947
Gower J. F. R., Hu C., Borstad G. A, King S., 2006, Ocean color satellites show extensive lines of oating Sargassum in the Gulf of Mexico, IEEE T. Geosci. Remote, 44 (12), 3619-3625.
http://dx.doi.org/10.1109/TGRS.2006.882258
Gower J. F. R., King S., 2007, An Antarctic ice-related 'superbloom' observed with the MERIS satellite imager, Geophys. Res. Lett., 34, L15501, doi:10.1029/2007GL029638.
http://dx.doi.org/10.1029/2007GL029638
Gower J. F. R., King S., Borstad G. A., Brown L., 2005, Use of the 709 nm band of MERIS to detect intense plankton blooms and other conditions in coastal waters, Proc. 2004 Envisat & ERS Symp., Salzburg, ESA SP-572.
Gower J. F. R., King S., Borstad G. A., Brown L., 2008a, The importance of a band at 709 nm for interpreting water-leaving spectral radiance, Can. J. Remote Sens., 34 (3), 287-295.
Gower J. F. R., King S., Goncalves P., 2008b, Global monitoring of plankton blooms using MERIS MCI, Int. J. Remote Sens., 29 (21), 6209-6216.
http://dx.doi.org/10.1080/01431160802178110
Huttula T., Nõges T. (eds.), 1998, Present state and future fate of Lake Võrtsjärv. Results from Finnish-Estonian joint project in 1993-1997, The Finnish Environment 209, Pirkanmaa Regional Environment Centre, Tampere, 150 pp.
Härmä P., Vepsäläinen J., Hannonen T., Pyhälahti T., Kämäri J., Kallio K., Eloheimo K., Koponen S., 2001, Detection of water quality using simulated satellite data and semi-empirical algorithms in Finland, Sci. Total Environ., 268 (1-3), 107-121.
http://dx.doi.org/10.1016/S0048-9697(00)00688-4
ISO 10260, 1996, (E), Water quality. Measurement of biochemical parameters-Spectrophotometric determination of chlorophyll-a concentration, ISO, Geneva, 1-6.
Jaanus A., Toming K., Hällförs S., Kaljurand K., Lips I., 2009, Potential phytoplankton indicator species for monitoring Baltic coastal waters in the summer period, Hydrobiologia, 629 (1), 157-168.
http://dx.doi.org/10.1007/s10750-009-9768-y
Jeffrey S. W., Humphrey G. F., 1975, New spectrophotometric equations for determining chlorophylls a, b, c and c2 in higher plants, algae and natural phytoplankton, Biochem. Physiol. P ., 167, 191-194.
Kahru M., Savchuk O. P., Elmgren R., 2007, Satellite measurements of cyanobacterial bloom frequency in the Baltic Sea: interannual and spatial variability, Mar. Ecol.-Prog. Ser., 343, 15-23.
http://dx.doi.org/10.3354/meps06943
Karlsson-Elfgren I., Hyenstrand P., Riydin E., 2005, Pelagic growth and colony division of Gloeotrichia echinulata in Lake Erken, J. Plankton Res., 27 (2), 145-151.
http://dx.doi.org/10.1093/plankt/fbh165
Koponen S., Pulliainen J., Kallio K., Hallikainen M., 2002, Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data, Remote Sens. Environ., 79 (1), 51-59.
http://dx.doi.org/10.1016/S0034-4257(01)00238-3
Koponen S., Ruiz-Verdu A., Heege T., Heblinski J., Sorensen K., Kallio K., Pyhälahti T., Doerffer R., Brockmann C., Peters M., 2008, Development of MERIS lake water algorithms, Validation Rep., http://www.brockmann-consult.de/beamwiki/download/attachments/
Kratzer S., Brockmann C., Moore G., 2008, Using MERIS full resolution data to monitor coastal waters - A case study from Himmerfjärden, a fjord-like bay in the northwestern Baltic Sea, Remote Sens. Environ., 112 (5), 2284-2300.
http://dx.doi.org/10.1016/j.rse.2007.10.006
Kullus L., 1964, Peipsi-Pihkva järve uurimisest ajavahemikul 1850-1917, Eesti Geografia Seltsi Aastaraamat 1963, Tartu, 148-158.
Kutser T., 2004, Quantitative detection of chlorophyll in cyanobacterial blooms by satellite remote sensing, Limnol. Oceanogr., 49 (6), 2179-2189.
http://dx.doi.org/10.4319/lo.2004.49.6.2179
Laugaste R., Haberman J., Krause T., Salujõe J., 2007, Significant changes in phyto- and zooplankton in Lake Peipsi in recent years: what is the underlying reason?, Proc. Estonian Acad. Sci. Biol. Ecol., 56 (2), 106-123.
Laugaste R., Jastremskij V. V., Ott I., 1996, Phytoplankton of Lake Peipsi-Pihkva: Species composition, biomass and seasonal dynamics, Hydrobiologia, 338 (1-3), 49-62.
http://dx.doi.org/10.1007/BF00031710
Laugaste R., Nõges T., Tõnno I., 2008, Vetikad, [in:] Peipsi, J. Haberman, T. Timm & A. Raukas (eds.), Eesti Loodusfoto, Tartu, 251-270.
McClain C. R., 2009, A decade of satellite ocean color observations, Annu. Rev. Mar. Sci., 1, 19-42.
http://dx.doi.org/10.1146/annurev.marine.010908.163650
Morel A., Huot Y., Gentili B., Werdell P. J., Hooker S. B., Franz B. A., 2007, Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach, Remote Sens. Environ., 111 (1), 69-88.
http://dx.doi.org/10.1016/j.rse.2007.03.012
Nixdorf B., Mischke U., Rücker J., 2003, Phytoplankton assemblages and steady state in deep and shallow eutrophic lakes - an approach to differentiate the habitat properties of Oscillatoriales, Hydrobiologia, 502 (1-3), 111-121.
http://dx.doi.org/10.1023/B:HYDR.0000004274.65831.e5
Nõges T., Haberman J., Jaani A., Laugaste R., Lokk S., Mäemets A., Nõges P., Starast H., Timm T., Virro T., 1996, General description of Lake Peipsi-Pihkva, Hydrobiologia, 338 (1-3), 1-9.
http://dx.doi.org/10.1007/BF00031706
Nõges T., Laugaste R., Nõges P., Tõnno I., 2008, Critical N:P ratio for cyanobacteria and N2-fixing species in large shallow temperate lakes Peipsi and Võrtsjärv, North-East Europe, Hydrobiologia, 599 (1), 77-86.
Oliver R. L., Ganf G. C., 2002, Freshwater blooms, [in:] The ecology of cyanobacteria. Their diversity in time and in space, B. A. Whitton & M. Potts (eds.), Kluwer Acad. Publ., New York, Boston, Dordrecht, London, Moscow, 149-194.
Paerl H. W., 2002, Marine plankton, [in:] The ecology of cyanobacteria. Their diversity in time and space, B. A. Whitton & M. Potts (eds.), Kluwer Acad. Publ., New York, Boston, Dordrecht, London, Moscow, 121-148.
Reinart A., Nõges P., 2004, Light conditions in Lake Võrtsjärv, [in:] Lake Võrtsjärv, J. Haberman, E. Pihu & A. Raukas (eds.), Estonian Encyclopaedia Publ., 141-149.
Reinart A., Valdmets K., 2007, Variability of optical water types in Lake Peipsi, Proc. Estonian Acad. Sci. Biol. Ecol., 56 (1), 33-46.
Reynolds C. S., 2006, Ecology of phytoplankton, Cambridge Univ. Press, Cambridge, 535 pp.
http://dx.doi.org/10.1017/CBO9780511542145
Ruddick K. G., Gons H. J., Rijkeboer M., Tilstone G., 2001, Optical remote sensing of chlorophyll a in case 2 waters by use of an adaptive two-band algorithm with optimal error properties, Appl. Optics, 40 (21), 3575-3585.
http://dx.doi.org/10.1364/AO.40.003575
Rundquist D. C., Han L., Schalles J. F., Peake J. S., 1996, Remote measurement of algal chlorophyll in surface waters: The case for the first derivative of re ectance near 690 nm, Photogramm. Eng. Rem. S., 62 (2), 195-200.
Sarmento H., Descy J.-P., 2008, Use of marker pigments and functional groups for assessing the status of phytoplankton assemblages in lakes, J. Appl. Phycol., 20 (6), 1001-1011.
http://dx.doi.org/10.1007/s10811-007-9294-0
Schalles J. F., Yacobi Y. Z., 2000, Remote detection and seasonal patterns of phycocyanin, carotenoid and chlorophyll pigments in eutrophic waters, Arch. Hydrobiol., 55 (Spec. Iss.), 153-168.
Schroeder T., Schaale M., 2005, MERIS case-2 water properties processor, version 1.0.1, Inst. Space Sci., Freie Univ., Berlin (FUB), [http://www.brockmann-consult.de/beam/software/plugins/FUB-WeW-Water-1.0.1.zip].
Sellner K. G., 1997, Physiology, ecology and toxic properties of marine cyanobacteria blooms, Limnol. Oceanogr., 42 (5 pt. 2), 1089-1104.
http://dx.doi.org/10.4319/lo.1997.42.5_part_2.1089
Simis S. G. H., Peters S. W. M., Gons H. J., 2005, Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water, Limnol. Oceanogr., 50 (1), 237-245.
http://dx.doi.org/10.4319/lo.2005.50.1.0237
Smith V. H., Willén E., Karlsson B., 1987, Predicting the summer peak biomass of four species of blue-green algae (cyanophyta/cyanobacteria) in Swedish lakes, Water Resour. Bull., 23 (3), 397-402.
Sørensen K., Aas E., Høkedal J., 2004, Validation of MERIS water products and bio-optical relationships in the Skagerrak, Int. J. Remote Sens., 28 (3 & 4), 555-568.
Utermöhl H., 1958, Zur Vervollkommnung der quantitativen Phytoplankton-Methodik, Mitt. Int. Ver. Limnol., 9, 1-38.
Water Framework Directive, Directive 2000/60/EC, Offic. J. Eur. Comm., L327, 1-27.
Webster I. T., Hutchinson P. A., 1994, Effect of the wind on the distribution of phytoplankton cells in lakes revisited, Limnol. Oceanogr., 39 (2), 365-373.
http://dx.doi.org/10.4319/lo.1994.39.2.0365
Can fluctuating asymmetry in Talitrus saltator (Montagu, 1808) (Crustacea, Amphipoda) populations be used as a bioindicator of stress on sandy beach ecosystems?
Oceanologia 2010, 52(2), 259-280
http://dx.doi.org/10.5697/oc.52-2.259
Ottavio Ottaviano, Felicita Scapini
Department of Evolutionary Biology "Leo Pardi", University of Florence,
Via Romana 17, IT-50125 Florence, Italy;
e-mail: ottavio.ottaviano@unifi.it
e-mail: scapini@unifi.it
keywords:
Amphipoda, Talitrus saltator, development, fluctuating asymmetry, sandy beaches
Received 21 December 2009, revised 6 May 2010, accepted 11 May 2010.
Abstract
This study focused on verifying the fluctuating asymmetry hypothesis
in the crustacean Talitrus saltator, which lives in sandy beaches.
We analysed three populations, one from an unpolluted Tuscan
beach relatively free of tourism, and two from Sicilian beaches,
which have been increasingly used for tourism and have been exposed
to hydrocarbon/pesticide pollution. Results confirmed the sexual
dimorphism in the second antennae flagella, which in the Tuscan
population presented directional asymmetry. This population had
a significant level of fluctuating asymmetry in the P6 and P3 meri.
The results showed the importance of the developmental stage
during which environmental mechanical stresses act.
References
Barca Bravo S., Servia M. J., Cobo F., Gonzalez M.A., 2008, The effect of human use of sandy beaches on developmental stability of Talitrus saltator (Montagu, 1808) (Crustacea, Amphipoda). A study on uctuating asymmetry, Mar. Ecol., 29 (1) ,91-98.
http://dx.doi.org/10.1111/j.1439-0485.2007.00208.x
De Matthaeis E., Davolos D., Cobolli M., Ketmaier V., 2000, Isolation by distance in equilibrium and non-equilibrium populations of four talitrid species in the Mediterranean Sea Evolution, 54 (5), 1606-1613.
Fanini L., Martín Cantarino C., Scapini F., 2005, Relationships between the dynamics of two Talitrus saltator populations and the impacts of activities linked to tourism, Oceanologia, 47 (1), 93-112.
Fanini L., Marchetti G. M., Scapini F., Defeo O., 2007, Abundance and orientation responses of the sandhopper Talitrus saltator to beach nourishment and groynes building at San Rossore natural park, Tuscany, Italy Mar. Biol., 152 (5), 1169-1179.
http://dx.doi.org/10.1007/s00227-007-0764-3
Jędrzejczak M. F., 2004, Sandy coastline ecosystem management- Bridging sustainability and productivity of sandy beaches The 3rd IUCN World Conservation Congr., Bangkok, Thailand,17-25 November 2004, Knowledge Marketplace Rep., 9 pp.
Karaman G. S.,1993, Crustacea Amphipoda of freshwaters (in Italian). Fauna d'Italia Ediz. Calderoni, Bologna, XXXI, 337 pp.
Ketmaier V., De Matthaeis E., Fanini L., Rossano C., Scapini F., 2010,Variation of genetic and behavioural traits in the sandhopper Talitrus saltator (Crustacea, Amphipoda) along a dynamic sand beach, Ethol. Ecol. Evol., 22 (1), 17-35.
http://dx.doi.org/10.1080/03949370903515919
Ketmaier V., Iuri V., De Matthaeis E., 2005, Genetic resources and molecular markers in Talitrus saltator (Amphipoda, Talitridae) from the beach of Smir Trav. Inst. Scient., Rabat Sér. Gén. 4, 55-59.
Lerner I. M., 1954, Genetic homeostasis Oliver and Boyd, Edinburgh, 134 pp.
Marques J. C., Gonçalves S. C., Pardal M. Â., Chelazzi L., Colombini I., Fallaci M., Bouslama M. F., El Gtari M., Charfi-Cheikhrouha F., Scapini F., 2003, Comparison of Talitrus saltator (Amphipoda, Talitridae) biology, dynamics, and secondary production in Atlantic (Portugal) and Mediterranean (Italy and Tunisia) populations, Estuar. Coast. Shelf Sci., 58 (S), 127-148.
Møller A. P., Swaddle J. P., 1997, Asymmetry, development stability and evolution, Oxford Univ. Press, Oxford, 291 pp.
Palmer A. R., 1994, Fluctuating asymmetry analyses: a primer [in:] Developmental instability: its origins and evolutionary implications, T. A. Markow (ed.), Kluwer Acad. Publ., Dordrecht, 335-364.
http://dx.doi.org/10.1146/annurev.es.17.110186.002135
Palmer A. R., Strobeck C., 1986, Fluctuating asymmetry: measurements, analysis, patterns, Ann. Rev. Ecol. Syst., 17, 391-421.
Ruffo S. (ed.), 1993, The Amphipoda of the Mediterranean. Part 3 Mém.Inst. Océanogr., Monaco, 577-813.
Scapini F., 2006, Keynote papers on sandhoppers orientation and navigation, Mar. Freshw. Behav. Phy., 39 (1), 73-85.
http://dx.doi.org/10.1080/10236240600563412
Scapini F., Buiatti M., De Matthaeis E., Mattoccia M., 1995, Orientation behaviour and heterozygosity of sandhopper populations in relation to stability of beach environments, J. Evolution. Biol., 8 (1), 43-52.
http://dx.doi.org/10.1046/j.1420-9101.1995.8010043.x
Scapini F., Morgan E., 2002, Bioassays for estimation of beach stability and ecosystem quality [in:] Baseline research for the integrated sustainable management of Mediterranean sensitive coastal ecosystems. A manual for coastal managers, scientists
and all those studying coastal processes and management in the Mediterranean, F. Scapini (ed.), Inst. Agronom. Oltremare, Florence, 120-122.
Schellenberg A., 1942, Flohkrebse oder Amphipoda Tierw. Deutschlands, 40 (I-IV), 252 pp.
Ugolini A. ,Borghini F., Calosi P., Bazzicalupo M., Chelazzi G., Focardi S., 2004, Mediterranean Talitrus saltator (Crustacea, Amphipoda) as a biomonitor of heavy metals contamination, Mar. Pollut. Bull., 48 (5-6), 526-532.
http://dx.doi.org/10.1016/j.marpolbul.2003.10.002
Węsławski J. M., Stanek A., Siewert A., Beer N., 2000, The sandhopper (Talitrus saltator, Montagu 1808) on the Polish Baltic coast. Is it a victim of increased tourism?, Oceanol. Stud., 29 (1),77-87.
Energy values and energy resources of two prawns in Baltic coastal waters: the indigenous Palaemon adspersus and the non-indigenous Palaemon elegans
Oceanologia 2010, 52(2), 281-297
http://dx.doi.org/10.5697/oc.52-2.281
Urszula Janas*, Olimpia Bruska
Institute of Oceanography, University of Gdańsk,
al. Marszałka J. Piłsudskiego 46, PL-81-378 Gdynia, Poland;
e-mail: oceuj@ug.gda.pl
*corresponding author
keywords:
Palaemon elegans, Palaemon adspersus, non-indigenous species, energy value, energy resources, food item, Baltic Sea
Received 6 October 2009, revised 19 April 2010, accepted 22 April 2010.
Abstract
Until recently only two palaemonid species inhabited the southern Baltic: Palaemon adspersus and Palaemonetes varians. Soon
after the year 2000 a new species - Palaemon elegans - arrived and quickly established itself as a new component in the trophic
web. The objects of this research were to define the energy value and energy resources of P. elegans and to compare them with
the corresponding values for the native P. adspersus. These parameters will supply information about this new link in the
trophic web and may help to explain the part played by the new prawn and its population in the energy flow. This work demonstrated
that the energy values of both prawn species were very much the same: the average energy value of P. elegans was
16.5±2.1 J mg-1 DW (19.3±2.5 J mg-1AFDW) (N = 150), that of P. adspersus was 16.7±2.1 J mg-1 DW
(19.5± 2.5 J mg-1 AFDW) (N = 71). No statistically significant differences in energy value were found between the two species with respect
to sex, size or season. The results show that P. elegans is an energetically valuable food item for predators.
Its energy resources in Polish brackish coastal waters can be as high as 150 kJ m-2; the highest among the palaemonid species
in this habitat, they constitute a rich supply of food for other organisms.
References
Barańska A., Janas U., Rzemykowska H., 2009, Is there competition for habitat and food between two prawns,native Palaemon adspersus and alien Palaemon elegans in the Gulf of Gdańsk?, 7th Baltic Sea Congress 2009 - Towards better understanding and improved technology for serving the society, 17-21 August, Tallin, Estonia, p. 253.
Barnes R. S. K., 1994, The brackish water fauna of northwestern Europe, Cambridge Univ. Press., Cambridge, 106 pp.
Berglund A., Bengtsson J., 1981, Biotic and abiotic factors determining the distribution of two prawn species: Palaemon adspersus and P. squilla, Oecologia, 49 (3), 300-304.
http://dx.doi.org/10.1007/BF00347589
Company J. B., Sardà F., 1998, Metabolic rates and energy content of deep sea benthic decapod crustaceans in the western Mediterranean Sea, Deep Sea Res. Pt. I, 45 (11), 1861-1880.
http://dx.doi.org/10.1016/S0967-0637(98)00034-X
Cummins K. W., Wuycheck L. C., 1971, Caloric equivalents for investigations in ecological energetics, Mitt. Internat. Ver. Limnol., 18, 158 pp.
Dobrzycka A., Szaniawska A., 1993, Seasonal changes in energy value and lipid content in a population of Corophium volutator (Pallas,1766)from the Gulf of Gdańsk, Oceanologia, 35, 61-71.
Dobrzycka A., Szaniawska A., 1995, Energy strategy of Corophium volutator (Pallas, 1766)(Amphipoda)population from the Gulf of Gdańsk , Termochim. Acta, 251, 11-20.
http://dx.doi.org/10.1016/0040-6031(94)02073-W
Gorokhova E., Hansson S., 2000, Elemental composition of Mysis mixta (Crustacea, Mysidacea)and energy costs of reproduction and embryogenesis under laboratory conditions, J. Exp. Mar. Biol. Ecol., 246 (1), 103-123.
http://dx.doi.org/10.1016/S0022-0981(99)00173-2
Grabowski M., 2006, Rapid colonization of the Polish Baltic coast by an Atlantic palaemonid shrimp Palaemon elegans Rathke, 1837 ,Aquat.Invas., 1 (3), 116–123.
http://dx.doi.org/10.3391/ai.2006.1.3.3
Grabowski M., Jażdżewski K., Konopacka A., 2005, Alien Crustacea in Polish waters-Introduction and Decapoda, Oceanol. Hydrobiol. Stud., 34 (Suppl. 1), 43-61.
Gruszka P., Więcaszek B., Palaemon elegans Rathke, 1837 in the food of Baltic cod (Gadus morhua callarias L., 1758)from the Gulf of Gdańsk, Mar. Biol. Res., in press.
Hayward P. J., Ryland J. S., 1996, Handbook of the marine fauna of North West Europe, Oxford Univ. Press, New York, 800 pp.
Hill C., Quigley M. A., Cavaletto J. F., Gordon W., 1992, Seasonal changes in lipid content and composition in the benthic amphipods Monoporeia affinis and Pontoporeia femorata, Limnol. Oceanogr., 37 (6), 1280-1289.
http://dx.doi.org/10.4319/lo.1992.37.6.1280
Holthuis L. B., 1980, FAO Species catalogue. Vol. 1. Shrimps and prawns of the world.An annotated catalogue of species of interest to-sheries, Food Agr. Org. UN, Rome, 271 pp.
Janas U., Barańska A., 2008, What is the diet of Palaemon elegans Rathke, 1837 (Crustacea,Decapoda) a non indigenous species in the Gulf of Gdańsk (southern Baltic Sea?), Oceanologia, 50 (2), 221-237.
Janas U., Zarzycki T., Kozik P., 2004, Palaemon elegans-a new component of the Gulf of Gdańsk, Oceanologia, 46 (1), 143-146.
Jażdżewski K., Konopacka A., 1995,Pancerzowce oprócz równonogó w lądowych (Malcostraca excl. Oniscoidea), Vol. 13, pt. 1, [in:] Katalog fauny Polski, Dz. Wyd. Muz. Inst. Zool. PAN, Warszawa, 165 pp.
Klekowski R. Z., Bęczkowski J., 1973, A new modi-cation of micro bomb calorimeter, Ecol. Pol., 21 (16), 229-238.
Kobyakova Z. I., Dolgopol’skaya M. A., 1969, Order Decapoda, [in:] Determination keys to the fauna of Black and Azov Seas, Vol. 2, F. D. Mordukhai Boltovskoi (ed.), Naukova Dumka, Kiev, 270-306, (in Russian).
Kube J., Gosselck F., Powilleit M., Warzocha J., 1997, Long term changes in benthic communities of the Pomeranian Bay (Southern Baltic Sea), Helgol. Meer., 51 (4), 399-416.
http://dx.doi.org/10.1007/BF02908723
McClintock J. B., 1986, On estimating energetic values of prey:implications in optimal diet models, Oecologia, 70 (1), 161-162.
http://dx.doi.org/10.1007/BF00377127
Normant M., Chrobak M., Szaniawska A., 2002, Energy value and chemical composition (CHN)of the Chinese mitten crab Eriocheir sinensis (Decapoda:Grapsidae) from the Baltic Sea, Termochim. Acta, 394 (1-2), 233-237.
http://dx.doi.org/10.1016/S0040-6031(02)00259-9
Normant M., Szaniawska A., 1993, Energy accumulation in the carapace, tissue and limbs of Saduria (Mesidotea)entomon from the Gulf of Gdańsk, Stud. Mater. Oceanol., 64 (3), 265-271.
Norrbin F., Bamstedt U., 1984, Energy contents in benthic and planktonic invertebrates of Kosterfjorden, Sweden. A comparison of energetic strategies in marine organism groups, Ophelia, 23 (1), 47-64.
Prus T., 1970, Calorific value of animals as an element of bioenergetical investigations, Pol. Arch. Hydrobiol., 17 (1/2), 183-199.
Prus T., 1993, Zawartość energii w materiałach biologicznych, [in:] Bioenergetyka ekologiczna zwierząt zmiennocieplnych, R. Z. Klekowski & Z. Fischer (eds.), Wydz. II Nauk Biol. PAN, Warszawa, 203-229.
Quigley M. A., Cavaletto J. F., Gardner W. S., 1989, Lipid composition related to size and maturity of the amphipod Pontoporeia hoyi, J. Great Lakes Res., 15 (4), 601-610.
http://dx.doi.org/10.1016/S0380-1330(89)71514-8
Rasmussen E., 1973, Systematics and ecology of the Isefjord marine fauna (Denmark), Ophelia, 11, 1-507.
Salama A. J., Hartnoll R. G., 1992, Effects of food and feeding regime on the growth and survival of the prawn Palaemon elegans Rathke, 1837 (Decapoda,Caridea), Crustaceana,63 (1), 11-22.
http://dx.doi.org/10.1163/156854092X00235
Salonen K., Sarvala J., Hakala I., Viljanen M. L., 1976, The relation of energy and organic carbon in aquatic invertebrates, Limnol. Oceanogr., 21 (5), 724-730.
http://dx.doi.org/10.4319/lo.1976.21.5.0724
Szaniawska A., 1983, Seasonal changes in energy content of Crangon crangon L. (Crustacea, Decapoda), Pol. Arch. Hydrobiol., 30 (1), 45-56.
Szaniawska A., 1984a, Calori-c value of Palaemon adspersus (Rathke, 1837) as an element of ecological investigations, Limnologica, 15 (2), 547-553.
Szaniawska A., 1984b, Seasonal changes in weight and energy content in the Crangon crangon population of Gdańsk Bay, Ophelia, Suppl. 3, 247-251.
Szaniawska A., 1991, Gospodarka energetyczna bezkr.gowcow bentosowych występujących w Zatoce Gdańskiej, Uniw. Gd., 121 pp.
Townend J., 2002, Practical statistics for environmental and biological scientists, John Wiley & Sons LTD, Chichester, 276 pp.
Wiktor K., 1979, Skąd pokarmu Palaemon adspersus (Rathke) z Zatoki Puckiej, Zesz. Nauk. BINOZ UG, 6, 147-154.
Wiktor K., 1993, Makrozoobentos, [in:] Zatoka Pucka, K. Korzeniewski (ed.), Inst. Oceanogr. Uniw. Gd., Gdańsk, 442-454.
Wiktor K., Szaniawska A., 1989, The energy content in relation to the population dynamic of Mysis mixta (Crustacea), Kiel. Meer. Sonderh. 6, 154-161.
Wiszniewska A., Rychter A., Szaniawska A.,1998,Energy value of the mud crab Rhithropanopeus harrisii spp.tridentatus (Crustacea,Decapoda)in relation to season,sex and size, Oceanologia, 40 (3), 231-241.
Yiğit M., Ergün S., Türker A., Karaali B., Bilgin S., 2005, Using ammonia nitrogen excretion rates as an index for evaluating protein quality of prawns in turbot (Psetta maeotica)nutrition, Turk. J. Vet. Anim. Sci., 29 (6), 1343-1349.
Załachowski W., 1986, An attempt to estimate food biomass eliminated annually by the cod (Gadus morhua L.) population in the Baltic, based on studies in 1977-1982, Acta Ichthyol. Piscat., 16 (1), 3-23.
Geostrophic current patterns off the Egyptian Mediterranean coast
Oceanologia 2010, 52(2), 299-310
http://dx.doi.org/10.5697/oc.52-2.299
Mohamed Salama Kamel
National Institute of Oceanography and Fisheries,
Kayt-Bay, Alexandria, Egypt;
e-mail: mskamela@yahoo.com
keywords:
Egypt, Mediterranean, geostrophic current circulation
Received 4 January 2010, revised 7 May 2010, accepted 13 May 2010.
Abstract
Using objectively analysed hydrographic data,
currents have been calculated off the Egyptian Mediterranean
coast at the surface and at 30, 50, 75, 100, 200 and 300 m
depths for the four seasons.
The surface circulation is dominated by an anticyclonic circulation
off Salum Bay in winter, spring and summer. In nearshore areas,
the current flows eastwards at the shallower levels but westwards
at the deeper levels.
Off the Nile Delta, the current is almost eastward with a higher
velocity in summer and autumn, while in spring it is very weak.
Off the area between Port Said and Rafah, there is a clear cyclonic
circulation appearing in all seasons except winter. At 50 and
75 m depth, the velocity of the circulation is weak. At 100 m depth,
the circulation that appeared between Matruh and Alamen in summer decreases
in area and magnitude at the former depths.
At 200 and 300 m in winter, the current velocity is quite low. In
spring the current flows southwards off the area between Rafah
and Port Said. In summer, the current off the area between Port
Said and Rafah is quite strong and flows to the south. The situation
in autumn is quite similar to that in summer, except in the eastern
area, where the current is a westward one.
References
Gerin R., Poulain P.-M., Taupier-Letage I., Millot C., Ismail S. B., Sammari C., 2009, Surface circulation in the Eastern Mediterranean using drifters (2005-2007), Ocean Sci., 5, 559-574.
Gerges M. A., 1976, The damming of the Nile River and its effect on the hydrographic conditions and circulation pattern in the southern Mediterranean and the Suez Canal, Acta. Adriat., 18 (11), 179-191.
Hamad N., Millot C., Taupier-Letage I., 2006, The surface circulation in the eastern basin of the Mediterranean Sea, Sci. Mar., 70 (3), 457-505.
Kamel M. S., 1993, Wind driven water movement in the Eastern and Western basins of the Mediterranean Sea, M. Sc. thesis., Fac. Sci., Alex. Univ., Egypt, 109 pp.
Kamel M. S., 1998, Numerical assessments of salt content in the Mediterranean Sea, Ph. D. thesis., Fac. Sci., Alex. Univ., Egypt., 176 pp.
Kamel M. S., 1999, Seasonal variability of surface current in the eastern Mediterranean Sea, Bull. Nat. Inst. Ocean. Fish., 25, 51-67.
Millot C., Taupier-Letage I., 2005, Circulation in the Mediterranean Sea, Handb. Environ. Chem. Vol. 5, Part K, 29-66.
Morcos S. A., Hassan H. M., 1976, The water masses and circulation in the southeastern Mediterranean, Acta Adriat., 18 (12), 195-218.
Pond S., Pickard G. L., 1983, Introductory dynamical oceanography, Pergamon Press, Oxford, 329 pp.
Said M. A., Eid F. M., 1994, Circulation pattern of the Egyptian Mediterranean waters during winter and summer seasons, Pak. J. Mar. Sci., 3 (2), 91-100.
Said M. A., Karam A., 1990, On the formation of the intermediate water masses off the Egyptian Mediterranean coast, J. Arch. Hydrobiol., 120 (1), 111-122.
Said M. A., Rajkovic B., 1996, A study of water circulation along the Egyptian Mediterranean coast using a three dimensional numerical model, Int. J. Environ. Stud., 50 (3), 223-235.
Sharaf El-Din S. H., 1972, Some aspects of the hydrographic conditions of the eastern part of the Mediterranean Sea, Rapp. Comm. Int. Mer Medit., 20 (4), 619-621.
Sharaf El-Din S. H., Karam A., 1976, Geostrophic currents in the southern sector of the Mediterranean Sea, Acta Adriat., 18 (13), 221-235.
Reports
Report on the development of the Vistula river plume in the coastal waters of
the Gulf of Gdańsk during the May 2010 flood
Oceanologia 2010, 52(2), 311-317
http://dx.doi.org/10.5697/oc.52-2.311
Marek Zajączkowski1,*, Mirosław Darecki1, Witold Szczuciński2
1Institute of Oceanology, Polish Academy of Sciences,
Powstańców Warszawy 55, PL-81-712 Sopot, Poland;
e-mail: trapper@iopan.gda.pl
*corresponding author
2Institute of Geology, Adam Mickiewicz University,
Maków Polnych 16, PL-61-606 Poznań, Poland
keywords:
River Vistula, Gulf of Gdańsk, flood, river plume
Received 7 June 2010, revised 11 June 2010, accepted 14 June 2010.
Abstract
The hydrological conditions, suspended matter concentrations and vertical particulate matter flux were measured as the River Vistula
flood wave (maximum discharge) was flowing into the southern part of the Gulf of Gdańsk on 26 May 2010. Extending offshore for several tens
of kilometres, the river plume was well stratified, with the upper layer flowing away from the shore and the near-bottom water coastwards.
References
Cyberski J., Grześ M., Gurty-Korycka M., Nachlik E., Kundziewicz W. W., 2006, History of oods on the river Vistula, Hydrol. Sci. J., 51 (5), 799-817.
http://dx.doi.org/10.1623/hysj.51.5.799
Pruszak Z., van Ninh P., Szmytkiewicz M., Ostrowski R., 2005, Hydrology and morphology of two river mouth regions (temperate Vistula Delta and subtropical Red River Delta), Oceanologia, 47 (3), 365-385.
Zajączkowski M., 2002, On the use of sediment traps in sedimentation measurements in glaciated fjords, Pol. Polar Res., 23 (2), 161-174.
Chronicle
The SatBałtyk project: Satellite Monitoring of the Baltic Sea Environment
Oceanologia 2010, 52(2), 319-324
http://dx.doi.org/10.5697/oc.52-2.319
Jerzy Dera
Marine research in Poland has a long tradition. The first purpose-built laboratories were founded in the 1920s on the Hel
Peninsula and in Gdynia. After World War II a number of large, dynamically developing marine science
institutes came into existence (Dera et al. 2007).
One of these is the Institute of Oceanology of the Polish Academy of Sciences (Dera 2003),
where marine optics, one of several disciplines practised at the Institute,
has been able to flourish; today, it is of fundamental importance in remote sensing techniques for monitoring
the marine environment. The first research to be carried out in this field at the Institute investigated the optical properties
of the constituents of sea water, their influence on underwater visibility and the structure of the underwater light field. This
research was later extended to the various processes in the sea that are stimulated by sunlight, especially the photosynthesis
of organic matter in marine algae. Concurrently, more or less since the mid-1990s, great emphasis has been placed on the development
of bio-optical modelling and remote optical means of investigating the functioning of marine ecosystems, particularly those based
on satellite observations. The synthesis of these several branches of optical research led to the development, in 2001-2005, of
the comprehensive DESAMBEM8,9 algorithm, which enables Baltic ecosystems to be monitored from space. This will now be
discussed in greater detail.(...)
Dissertations
Atlantic Water in the Nordic Seas - properties, variability, climatic significance
Oceanologia 2010, 52(2), 325-327
http://dx.doi.org/10.5697/oc.52-2.325
Waldemar Walczowski
Physical Oceanography Department, Institute of Oceanology, Polish Academy of Sciences,
Powstańców Warszawy 55, PL-81-712 Sopot, Poland;
e-mail: walczows@iopan.gda.pl
Post-doctoral (habilitation) thesis in the Earth Sciences.