A FOURTEEN YEAR STUDY OF THE CHEMICAL-PHYSICAL CHARACTERISTICS
OF THE TARANTO SEA SYSTEMS. (NORTHERN IONIAN SEA)
Giorgio Alabiso1, Mauro Giacomini2, Milillo Matteo1, Patrizia Ricci1
1 CNRCNR-IAMC - U.O.S. di Taranto - via Roma, 3 - 74100 Taranto,
2 DIST, Università di Genova, Via Opera Pia, 13 - 16145 Genova
The present paper is part of a project which aims to construct a mathematical model for both the
seasonal and spatial variations of the chemical-physical characteristics of seawater from the
basins forming the system of the Taranto Seas: the Mar Grande basin (MG) and the Mar Piccolo
basin (MP), which is divided into two smaller inlets: Primo Seno (PS) and Secondo Seno (SS).
The model purpose is to detect their changes caused by the anthropogenic impact. The main
goal of the present study is to highlight, by several years of observations, both possible
seasonal trends of the considered variables and zones with similar features.
Since 1996 till now the area was continuously monitored.
Measurements of seawater chemical-physical variables by
multiparametric probe and samplings of seawater were carried out
twice a month at seven stations in the Mar Piccolo (four in the Primo
Seno and three in the Secondo Seno), three stations in the Mar
Grande and one station outside the Mar Grande that is in the Gulf of
Taranto (GT) (Fig. 1). The variables examined were the followings:
temperature, salinity, chlorophyll “a”, transparency, ammonia, nitrite,
nitrate, phosphate, silicate, total nitrogen, total phosphorous. The
collected data have been organized into a web-based relational data
base. The site address is http://www.medinfodist.it/taranto
http://www.medinfodist.it/taranto//. The
relational structure will allow the users to perform datamining
operations with several statistical tools.
Fig. 1 – Geographic location of the sampling stations.
Secchi (m)
Temperatura (°C)
PS
SS
12
GT
PS
MG
SS
22
10
21
8
20
6
19
4
18
2
17
0
MG
PS
40
0.6
30
0.4
20
St13
St4
St13
St13
St12
St10
St7
St5
St4
St2
St14
St17
St18
St19
St13
St12
St10
St7
St5
St4
St2
St14
St17
St18
St19
St13
St12
St10
St7
St5
St4
St2
St14
St17
St18
St19
St4
St7
St13
St5
St2
St10
St12
St14
St17
St18
St19
St12
St13
St10
St5
St7
St4
St2
St14
St17
St18
St19
St12
St13
St10
St5
St7
St4
St2
St14
St17
St18
St19
St12
St13
St10
St5
St7
St4
St2
St14
St17
St18
St19
St12
St13
St10
St5
St7
St4
St2
St14
St17
St18
St19
P tot
Si-SiO2
Fig. 2 – Cluster of homogeneous stations for
each examined variables.
Fig. 3 – Station 7: trend analysis for Ntot
Fig. 4 – Station 7: trend analysis for transparency
Chl a (µg/L)
SS
N-NH4 (µM)
38
4
37
3
36
2
35
1
N-NO3 (µM)
12
10
GT
5
MG
PS
GT
SS
MG
PS
MG
PS
SS
6
4
2
St St St St St St
4 7 5 10 12 13
MG
PS
0
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
Ptot (µM)
Si-SiO2 (µM)
1.2
0.40
GT
2
0
St St St St St
19 18 17 14 2
18
GT
SS
MG
PS
SS
GT
1.0
15
0.8
12
0.6
9
0.4
6
MG
PS
SS
0.10
10
0.2
0
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
PS
8
P-PO4 (µM)
SS
0.20
0.0
MG
10
0.30
0.2
GT
SS
8
0
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
Ntot (µM)
0.8
St12
St12
N tot
34
GT
SS
St10
St2
N-NO2
39
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
50
GT
St5
St7
4
N-NO2 (µM)
1.0
St17
St10
6
16
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
PS
St14
St5
N-NO3
6
MG
St7
St14
P-PO4
40
GT
St4
St17
N-NH4
Sal (psu)
23
MG
St2
St18
Sal.
The results obtained showed that these basins are characterized by
different levels of confinement (Fig. 5). Such a confinement is evident
for some variables (silicate, nitrate, phosphate and total nitrogen) and
let to immediately single out the four basins (i.e. GT, MG, PS, SS), as
the variables values change abruptly moving from the GT to the SS.
Concerning transparency, chlorophyll “a”, ammonia, nitrite,
confinement is less clear, since their values progressively change.
Along the same direction, besides the confinement, an evident
progressive increase of all the variables fluctuations is observable
(except for total P), which points out a noticeable instability of the
most confined basins. This probably depends not only on their
morphological characteristics but also on human activities, such as
mussel culture and agriculture carried out in the surrounding lands.
GT
St18
St19
chl a
A statistical elaboration was performed on the data of each variable
at every station to detect possible seasonal trends. To single out
probable homogeneous station clusters, after eliminating the factor
seasonality from the data series, these were compared by the
ANOVA followed by the Duncan test (Fig. 2).
The trend analyses were performed with the Cox-Stuart test.
Seasonal trends were detected for temperature, transparency,
salinity and for ammonia only in the Mar Piccolo basins; for nitrate,
nitrite and silicate only in the Secondo Seno. No trend was observed
for chl “a”, P-PO4, Ptot in all the stations. The ammonia showed a not
seasonal trend probably due to the different growth phases of the
cultivated mussels.
In the Primo Seno, from 2000 up to date, analyses showed a
negative trend for the Ntot concentration and a positive trend for
transparency, pH and silicate probably due to the closure of some
sewage outfalls (see, as an example, the station 7 in Figs 3 and 4).
14
St19
Trasp.
0.00
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
3
0.0
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
0
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13
Fig. 5 - Mean values (± S.D., as a variability index) of the studied variables.
Final workshop V.E.C.T.O.R. - Rome - October 1818-19, 2010
St St St St St St St St St St St
19 18 17 14 2 4 7 5 10 12 13