Vistula Lagoon (southern Baltic) ecosystem presented in a

1

“Not to be cited without prior reference to the authors”

International Council for the Exploration of the Sea

ICES CM 2008/L:05

Vistula Lagoon (southern Baltic) ecosystem presented in a regionally scaled biogeochemical model

Mariusz Zalewski1*, Zbigniew Witek2 & Magdalena Wielgat-Rychert2

1Sea Fisheries Institute, Gdynia, Poland 2Pomeranian Academy, Słupsk, Poland

1. Abstract

Extensiveness of environmental observations, some occasional problems with in situ measurements, and at the same time willingness to understand ecosystem processes lead to mathematical mapping of the environment. In this paper we present our latest version of the biogeochemical model of the shallow coastal lagoon situated in the southern Baltic Sea. In order to describe the Vistula Lagoon ecosystem we used a 3-dimensional, water-quality part of the Delft3D software developed by Delft Hydraulics, the Netherlands, and its 0-dimensional version constructed with use of STELLA software. We have modified our first assumptions which had been made during the MANTRA-East project and the outcome provides better understanding of the Vistula Lagoon ecosystem functioning.

Our model covers cycles of nitrogen, phosphorous, silicate, carbon, and oxygen in water column and sediment. Model calibrations were based on the field data collected by various institutions carrying studies in the Vistula Lagoon over the years 1998–2000. Monitoring data covered only vegetation periods, mostly form April to November.

The obtained modeling results allowed to specify the most important processes controlling functioning of Vistula Lagoon ecosystem, and gave the opportunity to check the data quality, and to supplement the data base. Our modeling results give also a chance to estimate seasonal and spatial variability in nutrient and chlorophyll concentrations, and primary production. Based on modeling it was possible (i) to quantify roughly main fluxes of substances (inflow, outflow, primary production, mineralization, release from sediments, oxygen consumption, nitrification, denitrification, nitrogen fixation, net accumulation etc.), (ii) to investigate the relationship between pelagic and benthic subsystems, and finally to describe the functioning of the Vistula Lagoon ecosystem.

Keywords: southern Baltic, Vistula Lagoon, biogeochemical model, nutrient cycling, eutrophication

* Contact author: Mariusz Zalewski: Sea Fisheries Institute in Gdynia, ul. Kollataja 1, 81-332 Gdynia, Poland [phone: +4858 7356141, fax: +4858 7356110, e-mail: [email protected]]

M.Zalewski et al. / Vistula Lagoon (southern Baltic) ecosystem presented in a regionally scaled biogeochemical model

__________________________________________________________________________

2

2. Introduction

Lagoons located in the southern part of the Baltic Sea are shallow, brackish, and

highly productive (Łazarienko & Majewski, 1975; Mudryk et al., 1999; Olenina & Olenin,

2002; Schiewer, 2002; Wielgat & Witek, 2004; Wiktor, 1976). The largest among such water

bodies: the Szczecin Lagoon, the Vistula Lagoon, and the Curonian Lagoon were formed

through interactions between the sea and large rivers entering the sea: the Oder, Vistula, and

Nemunas rivers. As estuarine waters, these lagoons have relatively high drainage basin

surface to water volume ratio, and as a consequence, they receive high loads of nutrients and

organic matter per unit of volume from their drainage basin and are, therefore, highly

productive. Moreover, their biological productivity is enhanced by the polimictic character.

Fish catches in lagoons belong to the highest within the whole Baltic Sea basin (Borowski et

al., 1995; Draganik, 1998; Olenina & Olenin, 2002; Schiewer, 2002; Wolnomiejski, 1994).

Coastal lagoons have undergone significant changes resulting from anthropogenic

pressure. Important changes were caused by eutrophication due to severalfold increase in

discharges of allochthonous nutrients as a consequence of intensified application of fertilizers

in agriculture and increase in municipal wastewater discharges (Humborg et al., 2000;

Olenina & Olenin, 2002; RóŜańska & Wiktor, 1978; Wielgat & Witek, 2004; Wiktor, 1976).

The Vistula Lagoon is a good example of such changes. Recently, besides biological

production, another aspect of lagoon ecosystem functioning has been of great scientific

interest. Coastal water bodies retain and modify part of the nutrient loads transported towards

the Baltic Sea by rivers. The Vistula Lagoon modifies loads received from the drainage basin

covering about 24000 km2 and populated by around 1 million inhabitants. Range of nutrient

loads modification and retention in the Vistula Lagoon has not yet been determined because

of the insufficient knowledge of the lagoon system functioning, especially with respect to

biogeochemical processes.

The three-dimensional (3D) water-quality part of the Delft3D software (Delft3D

WAQ) developed by Delft Hydraulics, the Netherlands (WL|Delft Hydraulics, 2001;

http://www.wldelft.nl) and its 0-dimensional (0D) version constructed with STELLA software

was used to describe the Vistula Lagoon ecosystem. Our present work is partly based on our

first assumptions which had been made during the MANTRA-East project (MANTRA-East,

http://www.ibwpan.gda.pl/mantraeast/vistulalagoon.php), but here we present the last

outcome of our work which provides better understanding of the Vistula Lagoon ecosystem

functioning.


__________________________________________________________________________

3

In the 1990s, the first approach of mathematical description of the Vistula Lagoon

functioning was done by Kwiatkowski et al. (1997), who constructed 2-dimentional, dynamic,

biogeochemical model. The project was carried out within the frame of Polish-Russian-

Danish cooperation. Seasonal changes of salinity, chlorophyll concentrations, oxygen, and

nutrients (nitrogen and phosphorus) were modeled for 1994.

3. Material and methods

Description of the study area

The Vistula Lagoon is located in the south-eastern part of the Baltic Sea (Fig. 1). The

lagoon is about 90 km long (in the south-west–north-east direction) and 13-km wide on

average (in the north-west–south-east direction) (Łomniewski, 1958). Main features

describing the lagoon are presented in Table 1.

Baltic Sea

Vistula Lagoon

Fig. 1. The Vistula Lagoon drainage basin.


__________________________________________________________________________

4

Table 1. Morphometry of the Vistula Lagoon (Łomniewski, 1958).

Surface area 838 km2 Length 90.7 km Min., mean, max. width 6.8; 8.9; 11.0 km Average depth 2.7 m Maximum depth 5.1 m Volume 2.3 km3

The lagoon is divided between Poland and Russia. About 56% of the total area—

473 km2 belongs to Russia and the remaining part to Poland (Łomniewski, 1958). The Vistula

Lagoon is separated from the Baltic Sea by a sandy spit, which is about 55 km long. The only

connection of the lagoon to the Baltic Sea is the Baltiysk Strait, approximately 400 m wide

and 2 km long, with the average depth of 8.8 m. The cross-section area of the strait is about

4000 m2.

Biogeochemical (water quality) model description

We used a 3D biogeochemical (water quality) part of the Delft 3D software developed

by Delft Hydraulics, the Netherlands (WL|Delft Hydraulics, 2001; http://www.wldelft.nl).

This software consists of two parts: hydrodynamic module Delft 3D FLOW and water quality

module Delft 3D WAQ. The water quality (WAQ) module uses output from hydrodynamic

module Delft 3D FLOW (calculations of water transport). In the work presented here

hydrodynamic part was done by Bielecka et al. (2003).

Model covers cycles of nitrogen, phosphorus, silicate, carbon, and oxygen in water

column and sediment. The processes include: algae growth, respiration, and mortality;

mineralization of particulate and dissolved organic matter; sedimentation and resuspension of

algae and particulate matter; adsorption and desorption of phosphorus onto inorganic matter;

nitrification; denitrification; reaeration with oxygen.

An example of the nitrogen cycle (applied in the biogeochemical model) is shown in

Fig. 2. There is no zooplankton as a state variable in the model. Zooplankton grazing pressure

on phytoplankton is expressed only by algal mortality.

The following forcing functions in the biogeochemical module were considered:

temperature, wind speed, irradiance at the water surface, day length, riverine loads,

atmospheric deposition of dissolved inorganic nitrogen (DIN) and particulate inorganic

matter.


__________________________________________________________________________

5

Algae(2)

Algae(2)

Uptak

e

MortalityAlgae(1)

Algae(1)

MortalityBurialBurial

Mineralization

NH4

DetNS1

Sedimentation/Resuspension

Min

eral

izatio

n

SEDIMENT

WATER


NO3

Denitrification

N2

Nitrif.

DetN

DON

Algae(2)

Algae(2)

Uptak

e

MortalityAlgae(1)

Algae(1)

MortalityBurialBurial

Mineralization

NH4

DetNS1


Min

eral

izatio

n

SEDIMENT

WATER


NO3

Denitrification

N2

Nitrif.

DetN

DON

Fig. 2. Nitrogen cycle in the Delft3D-WAQ model.

Simultaneously, a 0-dimentional (0D) model of the Vistula Lagoon ecosystem was

developed with use of STELLA software. The implementation of identical mathematical

formula in both models created an additional tool facilitating modeling. Simplified spatial

structure of the 0D model allowed modeling in much shorter calculation time and even testing

(calibrating) values of parameters needed for the 3D Delft3D-WAQ model. In the 0D model

no silicon cycle was developed, therefore diatoms were not a separate state variable.

However, nitrogen fixing cynaobacteria were included in the model. Water exchange between

the Vistula Lagoon and the Gulf of Gdańsk was estimated on the basis of the salt budget.

Spatial and temporal resolution

In order to shorten simulation time 3D model grid used in hydrodynamic module (11

layers and 912 cells) was aggregated in water quality module vertically and horizontally to 8

layers and 100 cells grid net (Fig. 3). Additionally, a coarser calculation time step

(10 minutes) was used.

a) b)

Fig. 3. Surface aggregation of model grid in Delft3D-WAQ; (a) hydrodynamic grid, (b) water quality grid.


__________________________________________________________________________

6

Model calibration

Model calibrations were based on the field data from the Vistula Lagoon region

collected on the Polish side by WIOŚ (The Pomeranian Voivodship Inspectorate for

Environmental Protection, Branch in Elbląg), MIR (Sea Fisheries Institute in Gdynia; Renk et

al., 2001), and IMGW (Institute of Meteorology and Water Management in Gdynia). On the

Russian side data from HYDROMET (Institute of Hydrometeorology, Russia), AtlantNIRO

(Atlantic Scientific Research Institute of Marine Fisheries and Oceanography) and IO RAN

Kaliningrad (Russian Academy of Sciences P.P.Shirshov Institute of Oceanology Atlantic

Branch) were used. Monitoring data from the lagoon covered only vegetation period, mostly

form April to November. There were no winter measurements and no data for the early spring

when usually the first algal bloom in lakes is noted. Altogether measurements were carried

out at over 20 locations (Fig. 4).

19.2° 19.4° 19.6° 19.8° 20.0° 20.2° 20.4°54.2°

54.3°

54.4°

54.5°

54.6°

54.7°

54.8°

Nogat Elbląg

Bauda

Pasłęka

Mamonovka

Prokhladnaya

Pregola

Nelma

BaltiyskStrait

Baltic Sea

Kaliningradcollector

Fig. 4. Sources of nutrients entering the Vistula Lagoon and location of the measurements used for model calibration.

Modeling experiments indicated that in the case of concentrations the same good

model fit to empirical data could be achieved at different rates of modeled processes, e.g.

good fit can be achieved:

o at high rates of primary production and organic matter mineralization, and also at low

rates of these processes;


__________________________________________________________________________

7

o when organic matter mineralization takes place primarily in the pelagic zone with

small contribution of the sediment mineralization, and also in opposite situation when

organic matter mineralization takes place primarily in the sediment;

o at stable nutrient concentrations, and at increasing or decreasing nutrient

concentrations in the sediment.

As a consequence, substance concentrations could not be the only indicators used for

model calibration. In addition, some functional characteristics should be taken into account.

On the basis of the overall knowledge of the system, the following additional assumptions

were made:

o mean annual gross primary production (GPP) in the Vistula Lagoon should reach the

level of 300 gC m-2 yr-1 (Renk et al., 2001);

o production to respiration ratio in the water column should approach 1.5 (according to

measurements by Aleksandrov, 2005), with the rest of respiration occurring in the

bottom sediments;

o no matter accumulation in bottom sediments should occur, on the contrary, a weak

erosion process should be observed (Chubarenko & Chubarenko, 2002).

Initial conditions

The model run for the period 1998–2000 was preceded by a preparatory run in order to

set spatially differentiated initial conditions in the water column and in the sediments. Since

no winter measurement data for the lagoon were available, the preparatory run started on the

1st of April, of the ‘virtual’ year one, and ended after 33 months simulation, on the 31st of

December, of the ‘virtual’ year three. Simulations were done on the basis of hydrodynamic

field and forcing functions from the 1998–2000 period. Initial concentrations of substances in

the water column were set on the basis of spatially averaged monitoring data from April 1998,

while initial concentrations of C, N, and P in the sediment were set on the basis of spatially

averaged data after Uścinowicz & Zachowicz (1996) and Emelyanov (2002). Division of

phosphorus into organic (DetPS1) and adsorbed (AAPS1) pools was done on the basis of

findings by Graca & Bolałek (1998) from the Puck Lagoon.

For the inorganic matter in sediment (IM1S1) content, 12500 g m-2 was used in the

model as a starting value. The number represents an average dry matter mass minus organic

matter content (1–6%) in the 2-cm layer of the sediment in the lagoon. The organic matter

content was calculated on the basis of share of each sediment type in overall coverage of the

bottom in the lagoon.


__________________________________________________________________________

8

No data on biogenic silicon concentration in the sediment of the Vistula Lagoon was

available. In order to make at least a rough estimation of biogenic silicon concentration in the

sediment, data from other water body, namely the Szczecin Lagoon, were used (Pastuszak et

al., 2008).

Unfortunately, up to the present no research was carried out in the Vistula Lagoon on

biogeochemical processes in sediments, therefore there was no possibility to compare

intensity of such processes calculated by the model with empirical measurements.

Thus, in our model, the ‘active’ layer (2-cm layer) of sediment contained the following

amounts of substances:

organic carbon (DetCS1) = 160 g m-2

organic nitrogen (DetNS1) = 26 g m-2

organic phosphorus (DetPS1) = 4 g m-2

adsorbed phosphorus (AAPS1) = 4 g m-2

organic silicon (DetSiS1) = 125 g m-2

inorganic matter (IM1S1) = 12500 g m-2

Results from the last day of the preparatory run were used as initial conditions (in

water column and sediment) for the 1998–2000 regular simulation.

4. Results and discussion

Model fit

Field data for model calibration were obtained from several Polish and Russian

institutions. Data available for model calibration covered a period from April to November

(no winter data were available). Comparison of measured and model-calculated data showed

the best fit in the case of substances characterized by low seasonal variability (e.g. oxygen,

Corg, Ntot), while for some highly variable substances (e.g. P-PO4) average relative

deviations may reach more then 50%. The highest deviation of the average value did not

exceed 10% with the exception of N-NH4 and Si, whereas average relative deviation was

higher, with the highest value for chlorophyll a (76.7%). Deviation of maximum value did not

exceed the 30% level (with the exception of Ntot; Table 2). Positive values of deviations of

average and maximum values indicate that model generates values higher then empirical data,

and negative values indicate that the model generates values lower then empirical data.


__________________________________________________________________________

9

Table 2. Average relative deviation, average value deviation and maximum value deviation between modeled and measured data, calculated for the Vistula Lagoon.

Deviation [%] N-NH4 N-NO3 P-PO4 Si N tot P tot C org OXY Chl_aSecchi Depth

average relative deviation 10,9 36,6 54,0 25,6 29,4 37,9 12,9 14,1 76,7 33,0average value deviation -12,9 1,7 -5,4 -11,1 -4,7 2,7 -9,2 -0,8 -0,8 -6,7maximum value deviation -19,5 -7,3 -22,0 -12,0 31,2 -29,6 -18,5 -3,2 -15,0 -17,3

Water column

Phytoplankton and primary production

Model results allow getting insight into the factors controlling primary production in

the lagoon. Very important factor governing the primary production was light availability in

the water column. Light penetration depends strongly on the amounts of suspended matter. Its

concentrations usually ranged from 20 to 100 g m-3. These were very high values, several

times higher than values noted in rivers. Such large amounts of suspended solids resulted

from frequent resuspension of the bottom sediment, which is a typical feature for water bodies

that are shallow and exposed to wind induced mixing, like the Vistula Lagoon.

The Secchi disc visibility was very low (most often 0.2–1 m) and did not vary

substantially over the entire vegetation period. Model results suggest that in winter periods,

when the lagoon is covered with ice and no resuspension occurs, particles suspended in water

column may sediment to the bottom and water transparency may increase. However, as ice

cover reduces light penetration, phytoplankton growth is still inhibited by light deficiency

(Fig. 5).

Chlorophyll a values ranged typically from 10 to 60 mg m-3 through the vegetation

season and this level appears to be determined by the availability of inorganic nutrients.

Phosphorus limitation occurred in early spring, when phosphates became exhausted and

nitrogen was still available (Fig. 5). During late spring there was a change of limiting nutrient.

N-NO3 and N-NH4 concentrations dropped to very low values while P-PO4 concentrations

increased (Fig. 5). Nitrogen limitation of eukaryotic phytoplankton lasted through the whole

summer season, giving possibility for the development of nitrogen-fixing cyanobacteria. In

general, phosphorus concentrations were more stable throughout the summer and autumn

showing no strong limitation during vegetation season. No limitation by silicon was observed

in the lagoon, even during spring diatom bloom.


__________________________________________________________________________

10

0,0

0,2

0,4

0,6

0,8

1,0

Jan-98 Jul-98 Jan-99 Jul-99 Jan-00 Jul-00 Jan-01

nutri

ent,

light

lim

itatio

ni

nitrogen phosphorus light

Fig. 5. Seasonal changes in limitation of phytoplankton primary production in the Vistula Lagoon (1-indicates no limitation, 0-indicates maximum limitation).

Spatial differentiation of subjected parameters was rather weak and that is typical for

shallow and well mixed water bodies. The main sources of horizontal variability in the lagoon

were the Baltiysk Strait (connection to the Baltic Sea) and the mouth of the Pregola, Elbląg,

and Nogat rivers. In addition, model results suggest that the outlet of the Kaliningrad collector

to the Primorskaya Bay in the north part of the lagoon may generate high gradients of nutrient

concentrations. Areas where higher nutrient inputs were noted (as compared to other parts of

the Vistula Lagoon) were also characterized by higher primary production rates, as indicated

by higher chlorophyll a concentrations (Fig. 6). Spatial chlorophyll a distribution calculated

by the model was more homogenous than the measured concentrations.

19August1999 _

C = 53

date measurements model

_C = 67

10 20 30 40 50 60 70[ mg m ]-3

Fig. 6. Exemplary surface concentrations of chlorophyll a [mg m-3] in the Vistula Lagoon based on in situ measurements and modeled data; the numbers next to graphs represent average values for the whole region.


__________________________________________________________________________

11

Phytoplankton primary production was the only flux measured in the Vistula Lagoon

in the 1998–2000 period. Measurements were conducted in 1999 in the Polish part of the

lagoon (Renk et al., 2001). In the first part of the vegetation season (until June) gross primary

production did not exceed 1 gC m-2 d-1 (with exception of one case at the beginning of

measurements). In July and August 1999, primary production was very intensive, and from

September to November gradually decreased. Annual primary production in the Polish part of

the lagoon was estimated at 303.8 gC m-2 yr-1 in 1999 (Renk et al., 2001; Fig. 7). Very high

values of production, exceeding 3 gC m-2 d-1, were noted in summer. These values were

always measured at the same time as maximum chlorophyll a concentrations.

Dec-97

Mar-98

Jun-98

Sep-98

Dec-98

Mar-99

Jun-99

Sep-99

Dec-99

Mar-00

Jun-00

Sep-00

Dec-00

[gC

md

]-2

-1

0

1

2

3

4

5

6

7MIRmodel

GPP

Fig. 7. Gross primary production [gC m-2 d-1] into Vistula Lagoon. Data from 0D model against a background of environmental observations from the Polish part of Vistula Lagoon (after Renk et al., 2001).

Summer 1999 was the warmest among all three summer seasons in the 1998–2000

period. During that season chlorophyll a concentrations were higher than in the remaining

years. According to model results, gross primary production (GPP) in 1999 in the whole

lagoon amounted to 298 (3D model) and 354 gC m-2 yr-1 (0D model), and it was the highest

value among all three years studied. In 1998 annual GPP amounted to 226 (3D model) and

254 gC m-2 yr-1 (0D model), and in 2000 amounted to 272 (3D model) and 314 gC m-2 yr-1

(0D model). Rate of primary production showed positive correlation with summer

temperature. At the same time, spatial distribution of primary production indicated that higher

production rates were measured in the area of the Pregola River mouth, Primorskaya Bay

(northern part of the lagoon) where wastewaters from the Kaliningrad Collector were

discharged, as well as in the mouths of the Nogat and Elbląg rivers (southwestern part of the

lagoon) (Fig. 8). Thus, spatial distribution of the annual GPP values corresponded to locations

of the main nutrient sources discharged to the Vistula Lagoon.


__________________________________________________________________________

12

Year 1998GPP226

(254)

Year 1999GPP298

(354)

Year 2000GPP272

(314)

year model - GPP [gC m yr ]-2 -1

Fig. 8. Spatial distribution of annual gross primary production (GPP, gC m-2 yr -1) in the Vistula Lagoon calculated with the 3D model; number without brackets – from 3D model; number in brackets – from 0D model.


__________________________________________________________________________

13

Mass budget

Substance fluxes were estimated with use of the 0-dimentional model. Annual values

were averaged to one value for the whole 1998–2000 period. Due to a relatively long fresh

water residence time in the lagoon (about 6 months) remineralization was the main source of

nitrogen and phosphorus for primary production process. Inputs of total nitrogen and total

phosphorus from the drainage basin were 2 and 5 times lower, respectively, than the

remineralization fluxes. Atmospheric deposition of nitrogen was of minor importance,

because it constituted up to 5% (670 tons year-1) of the input from the drainage basin (Fig. 9).

However, on annual basis, the respective discharges of allochthonous nitrogen and

phosphorus from the drainage basin were 6 and 4 times higher than the amounts of these

elements present in the water column (Fig. 9).

According to our estimation, the respective inputs of the dissolved inorganic nitrogen

(DIN) and dissolved inorganic phosphorus (DIP) from the Baltic Sea constituted ca. 2%

(about 207 tons year-1) and ca. 8% (about 36 tons year-1) of the inputs discharged by the

rivers. Input of organic forms of nitrogen and phosphorus from marine waters was relatively

higher and amounted to 23% for nitrogen (about 1114 tons year-1) and for phosphorus 13%

(about 50 tons year-1). Organic carbon input constituted up to 40% of the riverine input.

Oxygen inputs from the sea and from the rivers had similar values (Fig. 10).

[tons year ]-1

[tons]

precipitation

mineralization

rivers

local

Fig. 9. Main sources of nitrogen and phosphorus [tons year-1] for primary production compared to the average amount of these elements [tons] in the Vistula Lagoon.


__________________________________________________________________________

14

[tons year ]-1

Fig. 10. Inflow of phosphorus and nitrogen (organic and inorganic), dissolved oxygen, and organic carbon to the Vistula Lagoon from rivers and the Baltic Sea.

According to model calculations about 20% of the total nitrogen and phosphorus

mineralization, and about 30% of organic carbon mineralization occurred in sediment. This

indicates that processes in the water column dominated over those in sediments. Also oxygen

consumption was higher in the water column (above 70%) then in sediment (less then 30%;

Fig. 11). Nitrogen and phosphorus turn-over rates, calculated as ratios of annual

mineralization fluxes (summed pelagic and benthic values) to the mean annual concentrations

in the water column in the lagoon, amounted to about 15.

Porgmineralization

watercolumn

sedim

ent20%

80%

Norgmineralization

watercolumn

sedim

ent17%

83%

Corgmineralization

29%

71%

sedim

ent

watercolumn

Oxygenconsumption

27%

73%

sedim

ent

watercolumn

Fig. 11. Contribution of pelagic and sediment mineralization of organic nitrogen, phosphorus, carbon, and oxygen consumption.

Due to shallowness and large surface of the water body, resuspension of bottom

sediments was quite often noted in the lagoon. Resuspension was the main source of the

inorganic suspended matter in the pelagic zone of the lagoon, much higher than the input from

the drainage basin and atmosphere. On annual basis resuspension of inorganic matter was two

times higher than sedimentation. Outflow of the inorganic matter to the Baltic Sea calculated


__________________________________________________________________________

15

by the model exceeded the inflow form the drainage basin and atmosphere 5 times. It

indicates bottom erosion of about 0.4 mm per year. It is possible, that inflow of inorganic

matter to the lagoon was not fully taken into account in this work, because riverine input was

based on suspended matter concentration in the surface riverine water. At the river bottom,

suspended matter concentrations might be higher and thus the overall load discharged to the

lagoon might have been underestimated in the present work. Another unknown factor is a

contribution of inorganic matter from coastal erosion (abrasion). However, much higher

concentrations of suspended matter in the lagoon water than in riverine waters discharged to

the lagoon indicate negative budget of suspended matter in the lagoon (Fig. 12).

According to model simulations outflow of total phosphorus and organic carbon

exceeded the inflow. At the same time, mineralization of organic nitrogen, phosphorus and

carbon in sediment, together with resuspension, exceeded sedimentation. This indicates no

nitrogen, phosphorus, and organic carbon accumulation in the Vistula Lagoon. However, it

should be noted that differences in input and output of these elements in sediment were rather

small, within a range of estimation accuracy (Fig. 12).

per cent of inflow

Fig. 12. N, P, C and inorganic matter (IM) budget (per cent of inflow).

Comparison of nutrient outflow from the lagoon with loads discharged to the lagoon

may give an estimation of the nitrogen retention in the system. With the nutrient

concentrations in the model adjusted to the levels observed in field measurements, average

annual outflow of total nitrogen was lower than inputs while annual outflow of total

phosphorus was higher than annual inflow (Fig. 13 and Fig. 14).

Total nitrogen outflow constituted about 64 % of the inflow to the lagoon, so nitrogen

retention amounted to 36 % of the inflow. This retention resulted from denitrification process

which was estimated at about 8 gN m-2 y-1 (7156 tons year-1; Fig. 13).


__________________________________________________________________________

16

River loads = 13847

LANDBALTIC SEA

Inflow = 1322

SEDIMENT EROSION

Outflow = 10185

Vistula Lagoon

Net outflow of nitrogen = 64% of the input from the drainage basin

483D

enitr

ifica

tion

N-f

ixat

ion

Pre

cipi

tatio

n

7156

891

659

Fig. 13. Nitrogen budget for the Vistula Lagoon for the 1998–2000 period (tons yr-1).

Calculation of phosphorus budget indicates lack of phosphorus retention in the lagoon;

the outflow amounted to about 111 % of the inflow, so the model results indicate no

phosphorus retention (Fig. 14).

River loads = 991

LANDBALTIC SEA

Inflow = 87

SEDIMENT EROSION

Outflow = 1190

Vistula Lagoon

Net outflow of phosphorus = 111% of the input from the drainage basin

160

Fig. 14. Phosphorus budget for the Vistula Lagoon for the 1998–2000 period (tons yr-1).

Despite the apparent lack of total phosphorus retention in the system and 36%

retention of total nitrogen, there was a large retention of inorganic forms of nutrients. Only

35% of P-PO4 and 37% of DIN inflow to the lagoon was exported to the Baltic Sea.

However, large amounts of nutrients were taken up by phytoplankton in the lagoon and left

the system in organic form. According to the LOICZ stoichiometric interpretation (Gordon et


__________________________________________________________________________

17

al., 1996), all inorganic phosphorus retained in the lagoon may be considered as ‘net

ecosystem production’ (NEP). Assuming C/P (mass) ratio for incorporation of phosphorus

during primary production equal to 50:1, the retained P-PO4 flux was equivalent to NEP of

about 17000 tC yr-1 (or about 20 gC m-2 yr-1).

It should be noted that the above calculations were based on rather limited and

incomplete dataset on nutrient concentrations and discharges to the system. For many

elements quantitative data were not available and thus model inputs were based on

assumptions. With the increasing knowledge on the Vistula Lagoon ecosystem and its

watershed, more precise estimates of nutrient budget will be possible.

5. Conclusions

o Model results showed a moderate agreement with measured values. In most cases

deviations of average values were below 7%; there were, however, some cases when

subjected deviations were within a range 7 ÷ 13 %. Average relative deviation reached

values between 11% and 77%.

o Light availability was a very important factor governing the primary production in

water column. The light penetration depends on the amount of suspended matter. Its

concentrations were very high, several times higher than values noted in rivers. Such

large amounts of suspended solids resulted from frequent resuspension of the bottom

sediment, which is a typical feature for water bodies that are shallow and exposed to

wind induced mixing, like the Vistula Lagoon.

o Model indicated that phosphorus was the limiting factor for phytoplankton growth in

the Vistula Lagoon in spring. Nitrogen limitation was observed in summer and

autumn. No silicon limitation of diatom growth was noted throughout the whole

vegetation season.

o State variables in the model showed moderate spatial differentiation for the whole

Vistula Lagoon area. The main sources of horizontal inhomogenity were the riverine

inflows: the Pregola, Elbląg and Nogat rivers, the outlet of Kaliningrad sewage

collector and the Baltiysk Strait.

o Annual gross primary production (GPP) showed positive correlation with temperature,

so the highest GPP values were noted in 1999 (the warmest summer in the 1998-2000

period).


__________________________________________________________________________

18

o It was estimated that due to a relatively long time of water retention in the lagoon

remineralization of organic matter within the system was the main source of nitrogen

and phosphorus for primary production.

o Rivers were the main external source of nitrogen and phosphorus input to the lagoon.

o According to model calculations mineralization in the water column dominated over

mineralization in sediment.

o Nutrient budget calculations indicated that there was no retention of phosphorus in the

lagoon, while the retention of nitrogen (36%) was more substantial. The important

pathway in nitrogen cycle in the lagoon appears to be denitrification.

6. References

Aleksandrov S.V., 2005. Primary production of phytoplankton and chlorophyll concentration

in the Vistula and Curonian Lagoons of the Baltic Sea // The Baltic Sea a changing

ecosystem: 5th BSSC, Sopot, pp.192-193.

Bielecka M., Kaźmierski J., Jasińska E., Majewski W., Walkowiak A., Witek Z., Zalewski

M., Wielgat M., Staśkiewicz A., Lewandowski A., Olszewski T., 2003.

Hydrodynamic and water quality models of the Vistula Lagoon – description and

calibration results. MANTRA-East Deliverable D36cVL, 58 pp.

Borowski W., Dąbrowski H., Skólski J., 1995. The ichthiological studies of the state of fish

resources in the Vistula Lagoon in 1993. Reports of the Sea Fisheries Institute, 1993-

1994, Gdynia, pp. 72-91.

Chubarenko B.V., Chubarenko I.P., 2002. New way of natural geomorphological evolution of

the Vistula Lagoon due to crucial artificial influence. [In:] E.M. Emelyanov (ed.):

Geology of the Gdańsk Basin. Baltic Sea, Kaliningrad, Yantarny skaz, pp. 371-374.

Draganik B., 1998. Polish fishery research in the Szczecin and Vistula Lagoons. Proceedings

of thr Symposium on Freshwater fish and the herring populations in the coastal

lagoons. SFI Gdynia, pp. 60-95.

Emelyanov E.M. (ed.), 2002. Geology of the Gdańsk Basin. Baltic Sea, Kaliningrad,

Yantarny skaz, 496 pp.

Graca B., Bolałek J., 1998. Forms of phosphorus in sediments from the Gulf of Gdańsk.

Applied Geochemistry, Vol. 13, pp. 319-327.


__________________________________________________________________________

19

Gordon D.C. Jr., Boudreau P.R., Mann K.H., Ong J.-O., Silvert W.L., Smith S.V.,

Wattayakom G., Wulff F., Yanagi T., 1996. LOICZ Biogeochemical Modelling

Guidelines. LOICZ/R&S/95-5, vi+96pp. LOICZ, Texel, The Netherlands.

Humborg C., Fennel K., Pastuszak M., Fennel W., 2000. A Box Model Approach for a Long-

Term Assessment of Estuarine Eutrophication, Szczecin Lagoon, Southern Baltic.

Journal of Marine Systems, 25, pp. 387-403.

Kwiatkowski J., Rasmussen E.K., Ezhova E., Chubarenko B., 1997. The Eutrophication

Model of the Vistula Lagoon. Oceanological Studies No. 1, pp. 5-33.

Łazarenko N.N., Majewski A., 1975. The hydrometeorological system of the Vistula Lagoon.

[Hydrometeorologiczny ustrój Zalewu Wiślanego]. IMGW, Wydawnictwo

Komunikacji i Łączności, Warszawa, 1975, 518 pp.

Łomniewski K., 1958. The Vistula Lagoon (in Polish). Prace Geograficzne, Polska Akademia

Nauk, Instytut Geografii, PWN Warszawa, No.15. 106 pp.

MANTRA-East, http://www.ibwpan.gda.pl/mantraeast/vistulalagoon.php

Mudryk Z., Donderski W., Skorczewski P., Walczak M., 1999. Neustonic and planktonic

bacteria isolated from a brackish Lake Gardno. Polskie Archiwum

Hydrobiologii/Polish Archives of Hydrobiology [Pol. Arch. Hydrobiol./Pol. Arch.

Hydrobiol.]. Vol. 46, no. 2, pp. 121-129.

Olenina I., Olenin S., 2002. Environmental Problems of the South-Eastern Baltic Coast and

the Curonian lagoon. [In:] Schernewski & Schiewer (eds.): Baltic Coastal Ecosystems:

Structure, Function and Coastal Zone Management. CEEDES-Series, Springer Verlag

Berlin, Heidelberg, New York, pp. 149-156.

Pastuszak M., Conley D.J., Humborg C., Witek Z., Sitek S., 2008. Silicon dynamics in the

Oder estuary, Baltic Sea. J. Mar. Syst. (2008), doi:10.1016/j.jmarsys.2007.10.013.

Renk H., Ochocki S., Zalewski M., Chmielowski H., 2001. Environmental Factors

Controlling Primary Production on the Polish Part of the Vistula Lagoon. Bulletin of

the Sea Fisheris Institute 152(1), pp. 77-95.

RóŜańska Z., Wiktor K., 1978. Summary of investigations on the Vistula Lagoon in 1974-

1975. Studia i Materiały Oceanologiczne, Biologia Morza(4), No.21, pp. 197-204.

Schiewer U., 2002. Recent Changes in Northern German Lagoons with Special Reference to

Eutrophication. [In:] G. Schernewski & U. Schiewer (eds.): Baltic Coastal

Ecosystems: Structure, Function and Coastal Zone Management. CEEDES-Series,

Springer Verlag Berlin, Heidelberg, New York, pp. 19-30.


__________________________________________________________________________

20

Uścinowicz S., Zachowicz J., 1996. Geochemical Atlas of the Vistula Lagoon. PIG Warsaw,

pp. 14 (in Polish).

Wielgat M., Witek Z., 2004. A dynamic box model of the Szczecin Lagoon nutrient cycling

and its first application to the calculation of the nutrient budget. [In:] G. Schernewski

& T. Dolch (eds.): The Oder estuary, against the background of the Water Framework

Directive. Marine Science Reports No. 57, pp. 99-133.

Wiktor K., 1976. Changes in coastal and estuarine communities in the Baltic Sea as a

consequence of increase of pollution. Materiały Oceanologiczne, KBM PAN, 15, pp.

143-168 (in Polish).

WL | Delft Hydraulics, 2001. User Manual Delft3D-WAQ. Delft, The Netherlands.

Wolnomiejski N., 1994. Ekologiczne studium makrofauny dna mulistego Zalewu

Szczecińskiego (1982-1992). Studia i Materiały MIR, Seria A, 31, pp. 1-126 (in

Polish).

Wulff F., Sokolov A., Andrejev O., Rodriguez-Medina M., 1996. The Data Assimilation

System and the Baltic Environmental Database. http://nest.su.se/das/

Documents

Vistula Lagoon (southern Baltic) ecosystem presented in a