A multivariate assessment of coastal eutrophication. Examples from the Gulf of Finland, northern Baltic Sea

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Marine Pollution Bulletin 50 (2005) 1185–1196

A multivariate assessment of coastal eutrophication.Examples from the Gulf of Finland, northern Baltic Sea

Cecilia Lundberg *, Malin Lonnroth, Mikael von Numers, Erik Bonsdorff

Environmental and Marine Biology, Abo Akademi University, Akademigatan 1, FI-20500 Abo, Finland

Abstract

The Gulf of Finland is the sub-basin of the Baltic Sea that is most seriously affected by the effects and consequences of eutro-

phication. In this study, physical, chemical and biological long-term data (1980–2002) from the Finnish environmental monitoring

programme is used to detect possible gradients of eutrophication in the Gulf. The Finnish coastal area of the Gulf of Finland is

divided into three parts in an east–west direction, and into three zones (inner, middle, outer) according to differences in descriptive

parameters. We use principal component analysis (PCA) to study spatial and temporal differences in relation to eutrophication.

Clear differences between coastal and offshore areas are seen. Differences between eastern and western Gulf are not as evident.

The changes due to eutrophication are larger for the inner archipelago, whereas the outer areas have been more stable over time.

The concentration of oxygen is the strongest driving factor for eutrophication in the region.

� 2005 Elsevier Ltd. All rights reserved.

Keywords: Eutrophication; Long-term trends; Coastal areas; Gulf of Finland; Baltic Sea

1. Introduction

The Baltic Sea is one of the largest brackish water

areas on Earth, with a drainage basin that is four times

larger than its surface area (Elmgren and Larsson,

2001). One of the most serious threats to the Baltic iseutrophication. The large input of nutrients, especially

during the last five decades, has resulted in increased

concentrations of nitrogen and phosphorus in all sub-

basins (Kautsky and Kautsky, 2000). Increased input

of nutrients to the Baltic Sea has changed the biological

structure and ecological processes in both coastal and

open sea areas (Bonsdorff et al., 2002). The processes

of eutrophication include a rise in the concentration oforganic material in the water column and an increase

in the rate of sedimented matter. The amount of nutri-

0025-326X/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.doi:10.1016/j.marpolbul.2005.04.029

* Corresponding author. Tel.: +358 2 215 3416; fax: +358 2 215 3428.

E-mail address: [email protected] (C. Lundberg).

ents in the water is mainly governed by external input,

while the degree of sedimentation is ruled by factors in

the ecosystem, such as production, mineralization and

stratification (Gray et al., 2002).

The Gulf of Finland is known to be one of the most

polluted and eutrophied parts of the Baltic Sea (e.g.HELCOM, 2002). The Gulf, situated in the northern

Baltic Sea, is a direct extension of the Baltic proper

(Fig. 1). Geographically and hydrographically the Gulf

of Finland can be divided into a deeper, marine wes-

tern part and a shallower, more freshwater-influenced

eastern part, where the innermost Neva Bay has a lim-

nic character (Pitkanen et al., 2001). The horizontal

and vertical salinity gradients are strong, due to a com-bination of large fresh water inflow and the water ex-

change with the Baltic proper (Perttila et al., 1995;

HELCOM, 1996). The overall water circulation in

the Gulf of Finland is counter-clockwise, with an east-

ward transport along the Estonian north coast and a

westward transport along the Finnish south coast

mailto:[email protected]

Fig. 1. The Gulf of Finland with the location of the stations A–W. The vertical lines show the division for the geographical zonation. The symbols of

the stations indicate the division into the vertical parts (inner–middle–outer).

1186 C. Lundberg et al. / Marine Pollution Bulletin 50 (2005) 1185–1196

(HELCOM, 1996). The average calculated residence

time of the water is five years for the entire Gulf.

The Finnish coastline and the south-eastern part of

the Gulf have the slowest water exchange due to small

circulation patterns (Myrberg et al., 2004). Accordingto Stalnacke et al. (1999), the Gulf of Finland has an

annual runoff of 122.2 · 109 m3, which corresponds to24% of the total riverine transport to the Baltic Sea.

The total load to the Gulf in the year 2000 was

120,000 tons of nitrogen and 6400 tons of phosphorus

(Kiirikki et al., 2003). The largest load of nutrients and

organic matter are discharges from the River Neva and

the St. Petersburg area, with about 5 million inhabit-ants (Pitkanen et al., 1993, 1997; Stalnacke et al.,

1999). Considering a time period of 20 years, from

1980–2000, the reductions in nutrient loads were largest

for Russia but only minor for Estonia. The loads from

Finland have been constant and even increased some-

what during the last years (Kiirikki et al., 2003). The

amount of the atmospheric deposition of nitrogen has

increased from 1996 to 2000, when it was calculatedto 200,000–400,000 mg m�2 yr�1 for the Gulf of Fin-

land (HELCOM, 2005).

The Gulf of Finland is well studied and the ap-

proaches vary. Most of the work is done in the open

sea areas (e.g. Perttila et al., 1995; Conley et al., 1997;

HELCOM, 2002). Along the Finnish coastline national

monitoring has been carried out from the 1960s on-

wards. However, the monitoring data has mainly beenused for analysing local trends and linear relationships

(e.g. HELCOM, 1990, 1996, 2002; Kauppila and Back,

2001). In Meeuwig et al. (2000), hydrological data from

small estuaries associated to minor river mouths on the

whole Finnish coastline are used for predictions of

eutrophication, taking also the innermost coastal locali-ties into consideration. Weckstrom et al. (2004) have

used paleolimnological methods for reconstruction of

long-term trends in nutrients in Finnish coastal waters

of the Gulf of Finland. The combination of monitoring

and historic data is valuable in quality assessment, e.g.

in the work with the European Union Water Frame-

work Directive (Andersen et al., 2004; Rosenberg

et al., 2004).In this paper we assess long-term trends and differ-

ences in gradients along the Finnish south coast using

a multivariate approach, similar to that used in Appel-

gren and Mattila (2002). We use monitoring data and

our aim is to analyse if spatial and temporal trends exist

among biological and chemical data in the Gulf of Fin-

land. Do time series of nutrients, chlorophyll, oxygen

and transparency differ between the geographical re-gions in the Finnish archipelago in the Gulf of Finland?

We consider both the gradient from inshore to offshore

archipelago areas along the whole study area, and com-

parisons between the eastern, middle and western part

of the Finnish part of the Gulf. We are also analysing

if any single eutrophication-related parameter acts as a

dominating driver for these processes. In this effort we

focus on the productive season, and therefore only usesummer values.

Fig. 2. The principal component ordination that divides the stations

into the categories inner (stations A, B, G, H, O, P, Q, R, S, T), middle

(stations C, I, J, K, L, U) and outer (stations D, E, F, M, N, V, W)

archipelago areas. The eigenvalue for axis 1 explains 70.2% and 16.3%

for axis 2, which mean that these axes explain 86.5% of the variability

in the material. The vectors represent the correlations between the

PCA scores and the descriptive variables. (t �C = temperature,Exp. = exposure, W.e.r = water exchange rate).

C. Lundberg et al. / Marine Pollution Bulletin 50 (2005) 1185–1196 1187

2. Material and methods

2.1. Study area

The data used in this study originates from the Fin-

nish coastal areas along the Gulf of Finland, and is in-cluded in the environmental monitoring, collected by

the Uusimaa and Southeast Finland Regional Environ-

ment Centers. The material is based on data from 23

localities in this area, in order to cover (1) a geographi-

cal gradient from east to west in the Gulf (60� 15 0 N 27�15 0 E 59� 52 0 N 22� 52 0 E), and (2) a vertical gradient inthe coastal zone from inshore to offshore conditions

(Fig. 1). All these localities have regular long-term datasince at least the beginning of the 1990s with sampling

occasions between 2 and 23 times a year (Table 1).

Along the coastline, the localities were divided in an

eastern, middle and a western part of the Gulf of Fin-

land, forming three geographical classes. The geographi-

cal division is following the cultural geographic regions

of the county of Uusimaa (Nyland). The stations were

further grouped into three classes along the vertical gra-dient to inshore, middle shore and offshore (Fig. 2). This

was done using principal component analysis (PCA)

based on descriptive parameters for each station, namely

the rate of water exchange, level of exposure, depth and

temperature. As temperature is the only parameter that

changes between years, the average temperature in the

water column, from August 2000 was selected for this

Table 1

The locations, depths and length of existing time series for the 23 study stat

Station Location W-M-E

A 60� 24 03200N, 26� 29 03500E E

B 60� 20 01400N, 26� 08 05600E E

C 60� 20 03500N, 26� 35 03600E E

D 60� 15 00000N, 27� 15 00000E E

E 60� 16 05400N, 26� 53 04700E E

F 60� 16 01800N, 26� 38 00000E E

G 60� 17 05800N, 25� 55 01000E M

H 60� 13 04200N, 25� 28 04500E M

I 59� 59 01600N, 24� 17 03500E M

J 60� 08 05800N, 25� 08 03900E M

K 59� 56 03700N, 24� 02 00400E M

L 60� 12 00000N, 25� 20 01600E M

M 60� 04 05900N, 25� 07 03400E M

N 60� 10 05700N, 25� 38 01800E M

O 59� 54 05800N, 23� 04 00000E W

P 59� 53 04700N, 23� 36 02300E W

Q 59� 57 01700N, 23� 48 02200E W

R 59� 59 04900N, 22� 55 02900E W

S 59� 51 02700N, 23� 22 05000E W

T 59� 53 02600N, 23� 41 00600E W

U 59� 52 02900N, 22� 52 01200E W

V 59� 49 00100N, 23� 16 04400E W

W 59� 46 03500N, 23� 15 05800E W

W = western, M = middle, E = eastern Gulf of Finland, i = inner, m = midd

analysis. The water exchange rate is measured according

to Anon (1999), and the exposure due to the methods in

von Numers (1995).

2.2. Study parameters

The physical–chemical and biological parameters used

in this study are: nitrogen, phosphorus, transparency

ions

i-m-o Depth (m) Time series

i 17 1972

i 31 1987–2001

m 28 1979

o 69 1966

o 44 1979

o 42 1987

i 15 1987

i 19 1975–1976,

1983–1984, 1994

m 31 1979

m 33 1969

m 26 1994

m 23 1994

o 49 1971

o 57 1971

i 32 1983

i 29 1984

i 10 1984–2000

i 33 1971–1975, 1994

i 26 1994

i 27 1994

m 37 1994

o 43 1979

o 60 1994

le, o = outer archipelago areas.


(measured as Secchi depth), oxygen concentration and

chlorophyll a. All the parameters are analysed according

to Finnish Standards Association (for oxygen SFS 3040

(1990), for nitrogen SFS-EN ISO 13395 (1997), for phos-

phorus SFS 3026 (1986), and for chlorophyll a SFS 5772

(1993). For long time series the methods have changedand developed over time.

For nutrients total nitrogen (tot-N) and phosphorus

(tot-P) are used. Year to year variation is great, but gen-

erally the highest concentrations are found near the

mouths of large rivers (HELCOM, 2003). The decay

of organic material consumes oxygen in the bottom

waters (Richardsen and Jørgensen, 1996) and the dura-

tion of hypoxia has serious consequences for the ben-thos and bottom living fishes (e.g. Karlson et al.,

2002). Hence, we have used oxygen content in the bot-

tom water (0.5–1 m above the bottom surface). Chloro-

phyll a is a good measure of phytoplankton in the water

column and is an important effect parameter of both the

nutrient concentration and the rate of eutrophication in

the water (Anon, 1999). Secchi depth also measures the

biological production by indicating the amount of par-ticulate material in the surface layer (Sanden and

Hakansson, 1996). We have used summer values defined

as July 15th–September 15th.

2.3. Statistical parameters and methods

To analyse the level of eutrophication, and which

parameters act as driving forces, principal componentanalysis (PCA) was used (PRIMER version 5 and SPSS

version 12 software). Normally distributed variables are

required for PCA. The analysis reduces the dimensiona-

lity of the variable space by identifying correlation struc-

tures within a data matrix and includes the reduction of

many variables into few components (Jenerette et al.,

2002). PCA is a useful tool for analysing environmental

data, as it can handle a mixture of parameters and mea-surement scales. A correlation-based PCA normalises all

axes into comparable, i.e. dimensionless, scales (Clarke

and Warwick, 1994). The tested parameters were on

the one hand descriptive (depth, exposure, rate of water

exchange and temperature) and on the other hand eutro-

phication-related (tot-N, tot-P, oxygen, chlorophyll a

and Secchi depth).

The descriptive parameters were first analysed foreach station, in order to get the classes for the inner,

middle and outer archipelago areas, which already are

described in Section 2.1 and Fig. 2. The eutrophica-

tion-related parameters were then analysed to detect

spatial and temporal changes in the eutrophication

situation.

The dataset was divided into five time periods (1980–

1984, 1985–1989, 1990–1994, 1995–1999, 2000–2002).Each parameter is given as an average for each time pe-

riod and thereby the problem with missing values are

minimised. However, only information with values from

more than three (of five) years for each period are in-

cluded in the analysis (2000–2002: all data). Different

PCA�s are not comparable with each other (Chatfieldand Collins, 1980), but the division of the data material

in time periods allows assessment of the state of a givenstation, and how the situation changes over time in rela-

tion to the other study localities. The grouping of the

stations is based on a similarity matrix according to

normalised Euclidian distance and dendrogram. The

clusters are here expressed from the third level of dicho-

tomisation. The principal component scores and the

eigenvectors for the original variables for PC axes 1

and 2 are correlated using Spearman�s test. The correla-tion coefficients are expressed as vectors for each

analysis.

The PCA for the detection of spatial changes was

done on the basis of the eutrophication related parame-

ters (tot-N, tot-P, oxygen, chlorophyll a and Secchi

depth) where data from each time period is analysed

separately. The temporal change is analysed in a PCA

when data from all localities and all five time periodswere included in the same analysis. The purpose was

to observe the changes related to eutrophication that

may have occurred during the time period from 1980

to 2002.

3. Results

3.1. Zonation

The PC-analysis based on the descriptive parameters

divided the stations into three classes according to dis-

tance from the coast. The two first axes of the analysis

explain over 85% of the variation in the material

(70.2% for axis 1, 16.3% for axis 2). The PCA score-

values were clustered using Euclidian distance into threegroups, hereafter called the inner, middle and outer

archipelago areas (Fig. 1). In Fig. 2, depth, water ex-

change rate and exposure increase towards the outer

archipelago, whereas temperature decreases. The corre-

lation analysis between the PC scores and the variable

values (Table 2) show that the strongest correlations

are due to the level of exposure.

3.2. Overview of the state of eutrophication

The general patterns of the physical–chemical param-

eters are summarised in Table 3. Comparing the average

values from the time periods 1980–1985, 1990–1995 and

2000–2002, the state and rate/direction of change are de-

scribed for five parameters at each station. Differences

between the stations in the outer areas compared tothe inner and middle archipelago are evident. The defini-

tion of the state of eutrophication has followed (Anon,

Table 2

Spearman�s correlation coefficient between the descriptive parametersand the principal component scores for axes 1 and 2 in Fig. 2

PCA 1 PCA 2

Depth 0.791 0.335

0.000 0.118

Exposure �0.895 0.320

0.000 0.137

Water exchange rate �0.866 0.364

0.000 0.088

Temperature �0.758 �0.4730.000 0.023

Top numbers are correlations coefficients (rs) and bottom numbers

probabilities (p). Significant correlations are in bold.


1999). The inner archipelago shows, regardless of the

geographical gradient, the most serious situation. The

oxygen concentrations are low, the levels of chlorophyll

and nutrients are high and in many cases the situation

Table 3

Panel a: An overview of water quality trends for the study stations grouped in

M and L, which is based on Anon (1999)

Station n Secchi (m) Oxygen (mgl�1) Chl.a

Panel a

A 16 L! (1.4–2.5) L# (1.9–8.2) H"B 13 H! (1.1–4.5) H! (5.3–8.5) M"G 14 L# (1.0–2.5) L# (1.4–7.8) H"H 10 H! (1.6–4.1) H! (5.9–9.7) M!O 14 H! (1.7–4.8) M! (2.5–7.1) M"P 17 H! (1.5–4.8) L# (0.0–7.4) L#Q 14 L! (0.8–2.7) H! (5.2–8.6) M!R 8 M! (1.8–3.9) H! (5.2–9.8) L!S 9 H! (1.9–4.0) L# (0.0–7.1) L!T 8 M! (1.7–3.8) H! (3.9–7.9) M!C 23 M# (1.2–4.8) H! (5.4–9.6) M!I 24 M# (1.8–5.2) H# (2.1–10.9) M"J 17 H" (2.0–4.9) M# (0.0–9.8) M#K 9 M! (2.2–4.5) H! (1.5–8.4) M!L 8 M! (1.6–4.8) M! (3.0–8.8) M!U 14 L! (1.0–3.3) M! (1.4–7.8) M!D 20 H! (3.2–5.8) M# (1.0–8.9) M"E 18 H! (2.0–5.5) H! (3.4–9.2) H"F 16 H" (2.8–5.4) H! (4.8–10.1) M!M 23 H! (3.0–7,0) H! (5.4–9.3) M!N 18 H" (0.6–5.1) H! (5.3–9.0) M"V 13 H" (1.1–4.5) H# (5.3–8.5) M#W 9 H! (3.0–7.0) H! (6.6–9.0) M!

Anon, 1999 Secchi (m) Oxygen (mgl�1)

Panel b

H: very high 65.4 66

High 4.0–5.4 4–6

M: medium high 3.4–4.0 2–4

L: low 2.5–3.4 0–2

Very low <2.5 Presence of H2S

a For each station and parameter the mean value from the time periods 1

M = medium, H = high-very high values, ! = steady state, " = increasing, #and tot-P are summer values (15.7–15.9), oxygen concentration is based on

values are given in brackets.

has worsen over time. The only exception is transpar-

ency that seems to be relatively stable between years.

The same trend is seen for the middle archipelago areas,

though the starting points for the nutrients and chloro-

phyll a values were better compared to the coastal areas.

The oxygen concentration has a decreasing trend, as hastransparency. For the outermost areas, close to the open

Gulf of Finland, the trends for transparency and tot-N

seem to be slightly positive. However, the opposite is

true for oxygen, chlorophyll and phosphorus. For fur-

ther trends from the Gulf of Finland, see Kauppila

and Back, 2001) for coastal areas, and HELCOM

(2002) for the open sea.

3.3. Spatial trends

In the analyses from all time periods in Fig. 3a–e, the

first two axes explain approximately 80% of the varia-

tion (eigenvalues for the axis 1 between 50.2% and

60.3% and for axis 2 between 20.7% and 25.1%), which

to inner, middle and outer archipelago areas.a Panel b: The scale for H,

(lg l�1) Tot-N (lg l�1) Tot-P (lg l�1)

(2.3–17) H! (340–780) H! (33–180)

(2.9–15.0) H! (410–600) H! (26–175)

(3.1–28.0) H" (250–760) H" (33–200)

(2.0–10.2) M! (240–400) H! (19–55)

(1.8–6.0) H" (180–540) H" (20–83)

(2.1–14.0) H" (310–1200) H" (30–440)

(2.6–7.3) M! (220–470) H! (23–51)

(2.1–4.5) M! (330–610) L! (14–36)

(2.0–10.0) H! (210–870) H! (32–570)

(2.9–12.0) H! (220–750) H! (47–410)

(1.9–15.3) H" (320–590) H" (21–77)

(1.3–13.0) L# (190–560) M" (18–120)

(2.3–8.6) M# (310–1200) H! (25–440)

(2.8–11.0) H! (200–490) H! (21–137)

(2.3–12.0) H! (260–580) H! (36–155)

(3.1–28.0) M! (250–760) M! (33–200)

(2.4–9.0) M! (310–610) L" (35–140)

(3.2–6.8) M! (370–540) L" (37–140)

(2.7–7.4) M! (370–850) M" (23–82)

(1.9–7.1) M# (310–670) H# (25–130)

(1.5–8.2) M# (300–600) H" (14–89)

(2.9–15.0) H" (410–600) H" (26–175)

(2.3–7.1) L! (280–410) H! (45–100)

Chl. a (lg l�1) Tot-N (lgl�1) Tot-P (lg l�1)

>5.0 >450 >31

3.2–5.0 360–450 24–31

2.2–3.2 310–360 19–24

1.5–2.2 250–310 15–19

61.5 <250 <15

980–1984, 1990–1994 and 2000–2002 is compared. L = low-very low,

= decreasing trend. The values for Secchi depth, chlorophyll a, tot-N

an annual minimum. Besides the trends, the minimum and maximum

Fig. 3. Principal component ordination for the spatial trend analysis for five time periods: (a) 1980–1984, (b) 1985–1989, (c) 1990–1994, (d) 1995–

1999 and (e) 2000–2002. The level of eutrophication is increasing to the left in the graphs. The correlations between the PCA scores and the analysed

variables are indicated with vectors for each time period. When the variables and at least one of the axes correlate significantly, the vector and

parameter are given in bold.


means that the unprojected axes also include some of the

variance in the material. In Table 4 the coefficients and

significances for the correlations between PCA axes 1and 2 and the eutrophication-related parameters used

in the analysis are presented. The variables of the

parameters are correlated with the principal component

axes, which are seen as vectors in Fig. 3a–e. From the

directions of the vectors it is apparent that the rate of

eutrophication increases to the left in the graphs of

Fig. 3.

The PCA�s for spatial trends related to eutrophica-tion are divided into five time periods. Eight stations

had enough data for the first period 1980–1984 (Fig.

3a, Table 1). The degree of eutrophication increases to-

wards left along axis 1 in the graph. The stations are all

situated in the middle (C, I, J, V) archipelago or offshore

(D, E, M, N). Station J is in the worst condition duringthis period, but station V in the western Gulf of Finland

has comparatively good values. Correlation analysis

(Table 4) showed that chlorophyll and oxygen ac-

counted for most of the variation in the data.

In the following period, 1985–1989, the material is

larger, with 13 stations included, and arranged in four

groups (Fig. 3b, Table 1). The most eutrophied localities

are situated in inshore areas (A and Q). The high nitro-gen value has placed station A to a group of its own.

The group relatively unaffected by eutrophication (D,

E, I, M, N, V) consists of mainly offshore localities from

Table 4

Spearman�s correlation coefficient between the effect parameters and the principal component scores for axes 1 and 2 in Fig. 3

1980–1984 1985–1989 1990–1994 1995–1999 2000–2002

PCA 1 PCA 2 PCA 1 PCA 2 PCA 1 PCA 2 PCA 1 PCA 2 PCA 1 PCA 2

Secchi depth 0.452 0.333 0.877 0.317 0.892 �0.333 0.749 �0.046 0.763 0.011

0.260 0.420 0.000 0.291 0.000 0.225 0.000 0.835 0.000 0.966

Chlorophyll a �0.929 0.452 �0.582 0.247 �0.363 �0.616 �0.580 0.267 �0.341 �0.4500.001 0.260 0.037 0.415 0.183 0.014 0.004 0.218 0.181 0.070

Tot-P �0.452 �0.119 �0.705 0.138 �0.871 0.368 �0.610 0.118 �0.867 0.710

0.260 0.779 0.007 0.654 0.000 0.177 0.002 0.591 0.000 0.001

Tot-N �0.524 �0.262 �0.473 �0.044 �0.542 �0.513 �0.566 �0.426 �0.649 0.010

0.183 0.531 0.103 0.887 0.037 0.051 0.005 0.043 0.005 0.970

Oxygen 0.683 �0.755 0.545 0.748 0.562 �0.320 0.160 �0.718 0.757 �0.5510.062 0.031 0.054 0.003 0.029 0.245 0.465 0.000 0.000 0.022

Top numbers are correlations coefficients (rs) and bottom numbers probabilities (p). Significant correlations are in bold.


all three geographical zones. Stations J, O and P have

the worst oxygen conditions. According to the correla-

tions in Table 4 and the directions of the vectors in

Fig. 3b, the eastern Gulf is more affected of eutrophica-

tion in the end of the 1980s.

Data from 15 sites are analysed for the time period

1990–1994, seen in Fig. 3c. Compared to the previous

period, a number of stations have moved to the left,i.e. they have become more eutrophied. Station A is

again singled out due to its high nitrogen values. The

stations D, E, F and M have better transparency and

low phosphorus concentrations. Station V has especially

good phosphorus and oxygen values, which compen-

sates a high concentration of chlorophyll a. The outer

archipelago localities are placed more to the right in

the graph, indicating healthier conditions. Differencesbetween east and west in the study area are not detect-

able during 1990–1994.

For the period 1995–1999, the material is based on

data from all 23 stations (Fig. 3d, Table 1). A majority

of the stations has similar values and forms two large

groups, where the offshore areas have a better situation

enough for being an own group (Fig. 3d). The two clus-

ters with outliers, stations J, P and S, are due to theirlow oxygen concentration, and stations A and G, the

high nitrogen values, respectively. The stations from

inshore areas are generally placed to the left and the

offshore localities to the right, reflecting the eutrophica-

tion gradient from the coast towards the open sea.

The final time-period consists of data from only

three years, 2000–2002, and 17 stations (Fig. 3e,

Table 1). The highest concentrations of nitrogen andchlorophyll are found at stations A and G, which form

a group of their own. Hypoxic conditions pool P and S

into another group. All stations from offshore areas are

placed to the right in the graph together with station R

in the innermost areas in the western part of the Gulf,

showing that they are the least influenced by

eutrophication.

3.4. Comparisons between time periods

About 60% (41.3% for axis 1 and 22.5% for axis 2) of

the variation is explained by the two first axes in the

PCA in Fig. 4. The results from Spearman�s rank corre-lation in Table 5 show that all parameters correlated sig-

nificantly with axis 1, and more than half of the

parameters with axis 2.The development of eutrophication at any single sta-

tion is evident when the results from all time periods are

included in the same PCA. The material shown is di-

vided into three graphs, representing the development

for the localities in the inner, middle and outer archipel-

ago areas, respectively (Fig. 4a–c). By connecting the

position of the localities in the PCA-space in the differ-

ent time periods, the direction of development for thelocalities appears. A change towards left in the graph

indicates increased eutrophication over time, and a

change to the right stands for an improvement accord-

ing to the direction of the vectors in Fig. 4. The position

of localities in the inner archipelago fluctuate most com-

pared to the middle and outer areas and have the largest

variations between time periods. Especially localities A

and G have undergone a considerable negative develop-ment from an eutrophication perspective. The variations

in the middle and outer archipelagos are more homoge-

nous and not as drastic as in the inshore areas. Note that

station number J in Fig. 4b even shows a positive trend.

4. Discussion

4.1. Trends in eutrophication related parameters in the

Gulf of Finland

Remedial actions for eutrophication require knowl-

edge of the key physical, chemical and biological pro-

cesses involved in the ecosystem. Eutrophication as a

problem is extremely hard to reverse (Gray et al.,

Fig. 4. Principal component ordination for the temporal change analysis of the eutrophication-related parameters in the three archipelago zones. The

localities are divided into (a) inner (d: A 2-5,j: G 3-5, · : O 2-5,s: P 2-5,h: Q 2-4), (b) middle (·: C 1-5,d: I 1-4,h: J 1-4), and (c) outer (�: D 1-5,h: E 1-4,s: F 2-5, ·: M 1-5,j: N 1-4,d: V 1-5) archipelago areas. The numbers from 1 to 5 stand for the means of the time periods, 1 = 1980–1984,2 = 1985–1989, 3 = 1990–1994, 4 = 1995–1999, 5 = 2000–2002, and are connected for each station. The correlations between the PCA scores and the

analysed variables are expressed with vectors. When the variables and at least one of the axes correlate significantly, the vector and parameter are

given in bold. Note that the scales differ from each other.

Table 5

Spearman�s correlations coefficient between the effect parameters andthe principal component scores for axes 1 and 2 in Fig. 4

PCA 1 PCA 2

Secchi depth 0.772 0.219

0.000 0.057

Chlorophyll a �0.268 �0.7300.019 0.000

Tot-P �0.698 �0.1150.000 0.321

Tot-N �0.472 �0.4760.000 0.000

Oxygen 0.565 �0.2410.000 0.036

Top numbers are correlations coefficients (rs) and bottom numbers

probabilities (p). Significant correlations are in bold.


2002). In the Gulf of Finland, two factors are key-driv-

ers for changes in the nutrient concentrations and there-

by the whole status of the eutrophication; the net

transport of nitrogen and phosphorus from the Baltic

proper, and the net exchange of mainly phosphorus be-

tween sediment and water, the so called internal loading(Pitkanen et al., 2003). The nutrient discharges from the

catchment area of the Gulf of Finland decreased with

40% during the 1990s (Pitkanen et al., 2001). The reduc-

tions are especially valid for eastern and southern Gulf

of Finland, i.e. in Russian and Estonian waters. The

total load to the Gulf of Finland is still 2–3 times higher

compared to the rest of the Baltic Sea (Pitkanen et al.,

2001). However, as Conley et al. (2002) state, we mustbe able to distinguish which effects originate from

anthropogenic inputs and which are due to fluxes in cli-

mate. For example, the cycling of phosphorus is affected


by variations in salinity, which can be climatically dri-

ven, and thereby cause hypoxia (Conley et al., 2002).

Large amounts of stored phosphorus in the sediments

is also indicated by high fluxes of DIP even during peri-

ods when oxygen conditions in the bottom water are

satisfactory (Conley et al., 1997).Earlier analysis of monitoring data and compilations

from the Finnish coast of the Gulf of Finland (e.g. Karj-

alainen, 1999; Pitkanen et al., 2001), as also the overview

of the trends of the temporal changes for different

parameters in Table 3, show that changes have occurred

over time. In general, the concentrations of nutrients

have increased, which give higher chlorophyll a values

and a decrease in oxygen concentrations. Very sharplocal differences are also seen in Table 3. For example,

the oxygen values vary markedly between localities close

to each other, which probably are due to topographic

and physical differences. Changes in physical and chem-

ical water parameters have occurred both during sum-

mer and winter seasons. During the past decade, there

has been an increase in phosphate, but a decrease in

inorganic nitrogen according to wintertime recordingsfrom the open Gulf (HELCOM, 2002). The concentra-

tions of chlorophyll a in the Gulf of Finland have also

increased over time. Along the western part of the Gulf

of Finland, the chlorophyll during the spring bloom in

the 1970s had values of around 20 lg l�1, compared toabout 100 lg l�1 in the late 1990s (Karjalainen, 1999).Declines in oxygen concentrations are also seen, espe-

cially in the inner and middle archipelago areas. A pe-riod with high deep-water salinity in the mid 1990s

improved the state of the oxygen conditions at the deep

bottoms. The conditions worsened again, and in 2001 a

new oxygen collapse took place. Over 80% of the inves-

tigated bottoms were reduced, which means that no

macrofauna was present (Pitkanen et al., 2003). The sit-

uation improved slightly after strong mixing during the

autumn of 2001, but during investigations made by theFinnish Environment Institute and the regional environ-

ment centers in August 2003, only approximately 25% of

the sampling stations in the near coastal areas had oxi-

dised sediments (Pentti Kangas, pers. comm.). Hypoxia

and conditions for the zoobenthos are tightly linked.

Laine et al. (1997), HELCOM (2002) and Pitkanen

et al. (2003) have reported serious hypoxia and anoxia

and deterioration for living organisms both on deepand shallow bottoms of the Gulf of Finland since the

mid 1990s, and Karlson et al. (2002) reviewed the situa-

tion for the entire Baltic Sea.

4.2. Spatial trends

In the open Gulf of Finland, the period from 1980 to

2002 can be divided into two stages: a period withdecreasing salinities in the deep water combined with

increasing oxygen conditions in the 1980s, and a period

with higher salinities and lower oxygen in the beginning

of the 1990s. The saline influx from the North Sea in

1993 reached the Gulf of Finland in 1995 and co-incided

with a decrease in oxygen and an increase in phosphate

(Kahru et al., 1994). Since the mid 1990s the variations

between years have been large, with high amplitudes inphysical and biogeochemical values as a consequence

(Pitkanen et al., 2003). In Sanden and Danielsson

(1995) nutrient concentrations from 1980 to 1989 in

the whole Baltic were analysed, and the Gulf of Finland

had significantly higher phosphate and nitrate concen-

trations during autumn and winter than the rest of the

Baltic Sea. A clear gradient in the open sea areas was de-

tected. The highest concentrations occurred in the east-ern part and declined towards the mouth of the Gulf

(Sanden and Danielsson, 1995).

The detection of spatial trends in the principal com-

ponent analyses between different time periods from

the beginning of the 1980s and two decades onwards

indicates that the outer archipelago areas were always

less eutrophied, and the coastal parts the most, irrespec-

tive of time period. The differences between eastern andwestern areas in the Gulf of Finland due to the eutrophi-

cation were not as clear as expected. The situation is

worse in the eastern part of the Gulf, which already is

shown in several earlier studies, with the highest nutrient

concentrations in the sediment and the highest interac-

tions between water and sediment (e.g. Conley et al.,

1997; Pitkanen et al., 2001). For example, the stations

A and G are the most seriously eutrophied. Station Ahas been an outlier since the period 1985–1989 (Fig.

3b), the degradation for G takes place during the follow-

ing period, 1990–1994 (Fig. 3c). These stations represent

the inner archipelago area in the eastern and middle

zones of the study area.

Even the state in the western Gulf has undergone

deterioration since the 1980s. These results from the

northern coastal areas of the Gulf are not comparablewith the state in the open sea, however. It must also

be remembered that the area called ‘‘the eastern Gulf

of Finland’’ in this study in fact is situated more than

92 nautical miles or 170 km from the easternmost part

of the Gulf, where St. Petersburg is situated. Local circu-

lation patterns together with the distance from the Neva

River impact the degree of seriousness of eutrophication

(Conley et al., 1997). The salinity stratification is brokenin the shallow Neva Estuary, which contributes to the

state of serious eutrophication in the eastern part of

the Gulf. The shallowness in the easternmost Gulf of

Finland also makes it sensitive for changes in oxygen

in the sediment–water interface (Pitkanen et al., 2001,

2003). The western part of the Gulf of Finland is deeper

and under direct influence of saline inflows from the Bal-

tic proper. Therefore, the entrance of the Gulf is sensi-tive to reduced conditions (Pitkanen et al., 2003). The

coastal areas are influenced by nutrient input from the


Finnish mainland, mainly agricultural runoff. Local

upwelling is common in shallow archipelago areas as

well (Hallfors et al., 1983). A negative structural and

functional development due to eutrophication in the

coastal areas in the western part of the Gulf is also evi-

dent from studies of Zostera marina communities off theHanko peninsula. Changes in faunal composition asso-

ciated to Z. marina are primarily a result of a more

eutrophic environment (Bostrom et al., 2002).

4.3. Temporal trends and driving elements

The concentration of oxygen seems to be the driving

element during the whole time spectrum from 1980 to2002. Secchi depth, chlorophyll a and nutrients also cor-

relate significantly with the PCA axes (Table 5). The

time period 1980–1984 is lacking data from the inner

archipelago, which unfortunately makes the first time

period hard to compare with the later ones. The general

trend during the 1980s shows relatively unaffected local-

ities in the western and middle part of the study area.

Comparing the 1980s with the following decade, theeutrophication situation had become more severe. Some

localities from the inner archipelago, irrespective of the

geographical zonation, are especially seriously affected.

The locations of stations A and G in the eastern and

middle Gulf in the PCA�s (Figs. 3 and 4) are exceptionaldue to their high concentrations of nitrogen. Station P in

the western Gulf has extremely low oxygen values. The

last analysed period, 2000–2002, is more or less similarto the one from the latter part of the 1990s.

The vertical gradient from inshore to offshore areas

due to the degree of eutrophication is more evident.

The difference between inshore to offshore areas is also

seen in Fig. 4 where the changes between years are illus-

trated. The comparisons between years for the same

locality show that the changes were most drastic for

the inner archipelago, whereas the changes in the middleand outer areas are minor. In Fig. 4(b) even an improve-

ment in the state of eutrophication is seen for station J,

east of Helsinki.

4.4. Geographical gradients

According to Hallfors et al. (1983) the entire water

mass in the outer archipelago consists of surface waterfrom the Baltic proper. Large upwelling and mixing of

water in the entrance to the Gulf together with minor

local upwelling in open areas in the outer archipelago,

results in water of high salinity, but also high phospho-

rus content (Hallfors et al., 1983). This stands in good

accordance with the trends in Table 3. The analyses have

not taken into consideration that the inner archipelago

naturally has higher nutrient concentrations comparedto regions off the coast. Therefore also the offshore

localities seem to be better off than they actually are,

even if the nutrient concentrations may be too high in

relation to what is normal in an area with a fast water

circulation pattern. The significant correlations for total

phosphorus and nitrogen, as well as for chlorophyll a

concentrations in all analyses indicate that the nutrient

levels are abnormal even in the outer archipelago re-gions (Appelgren and Mattila, 2002). Gradient studies

in archipelago zones are also done in the Archipelago

Sea, SW Finland. In Hanninen et al. (2000), nitrogen

concentrations declined with distance from the coast,

but phosphorus showed no gradient from inner to outer

archipelago areas. Phosphorus variated seasonally in-

stead, especially in the areas near the coastline. For

nitrogen, the seasonal fluctuations were largest in theouter areas (Hanninen et al., 2000).

Multivariate analysis and PCA have been used for

detection of long-term trends and overall assessments

of environmental data on a global scale (e.g. Zitko,

1994; Bizsel and Uslu, 2000; Park and Park, 2000).

The method may identify a pattern in water quality from

long-term data and problems with for example seasona-

lity and extreme values are minimised.The archipelago system, which in the Gulf of Finland

is concentrated along the coast and consists of several

smaller patterns of islands, is environmentally stressed

from several directions. The assessment of the environ-

mental state in this kind of areas is essential and proper

monitoring is important. An effective monitoring pro-

gram has to include not only data collection but analysis

and interpretation of results (Vos et al., 2000). Changesin trends and analysis may be masked by heterogeneity

and variability in the data material (Boesch, 2000).

Appelgren and Mattila (2002) state that the eutrophica-

tion indicating parameters now used are appropriate for

assessment of the environment. Total phosphorus and

nitrogen as well as chlorophyll a form clear zonation

patterns. Oxygen is best used if it can be linked to the

state of the benthos. Transparency should only be usedin combination with other parameters (Appelgren and

Mattila, 2002). The archipelago area acts as a transition

zone between the coast and the open sea. Topography,

circulation patterns and local anthropogenic inputs af-

fect the ecosystem on a smaller scale (Bonsdorff et al.,

1997), which indicate that the coastal zone is not compa-

rable with the open sea, but still of equal importance for

a complete understanding of a sea ecosystem.

Acknowledgement

We thank Uusimaa and Southeast Finland Regional

Environmental Centers for the supply of their long-term

monitoring data. Kajsa Appelgren kindly gave com-

ments on the manuscript. This study is done in collabo-ration of the Swedish research programme MARE

(Marine Research on Eutrophication), the Academy of


Finland�s IMAGINE (Interpreting Baltic Coastal Ma-rine Ecological Data for Environmental Decision Ma-

king), and the EU project CHARM (Characterisation

of the Baltic Sea Ecosystem: Dynamics and Function

of Coastal Types).

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