Preprint volume - SIBM
Preprint volume - SIBM
Preprint volume - SIBM
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
Pre-print Volume - Oral presentations<br />
Topic 2: MARINE ORGANISMS AND ECOSYSTEMS AS MODEL SYSTEMS<br />
C. CAROPPO, L. GIORDANO * , F. RUBINO, A.P. BISCI, T.S. HOPKINS *<br />
Institute for Coastal Marine Environment, National Research Council (IAMC-CNR),<br />
Via Roma, 3 - 74100 Taranto, Italia.<br />
carmela.caroppo@iamc.cnr.it<br />
* IAMC-CNR, Calata Porta di Massa, Napoli, Italia.<br />
PHYTOPLANKTON COMMUNITIES AS INDICATORS<br />
OF ECOLOGICAL CHANGE IN THE ANTHROPOGENICALLY<br />
IMPACTED MAR PICCOLO OF TARANTO (IONIAN SEA)<br />
LE COMUNITÀ FITOPLANCTONICHE QUALI INDICATORI<br />
DELLE VARIAZIONI DI UN ECOSISTEMA SOGGETTO AD IMPATTO<br />
ANTROPICO: IL MAR PICCOLO DI TARANTO (MAR IONIO)<br />
Abstract – Preliminary results on phytoplankton community dynamics obtained by constructing a system<br />
based simulation model are here presented. This constitutes a component in a larger ecological model,<br />
which has been developed under the FP6 Integrated Project SPICOSA (Science and Policy Integration for<br />
Coastal Assessment). This model is aimed to quantify the main forcing due to human activities and<br />
environmental factors acting on the Mar Piccolo coastal system (Taranto, Italy) that is changing its<br />
response to these forcing. The succession of phytoplankton groups provides a useful indicator of system<br />
response to human perturbations, a calibration parameter for the species-specific growth, an indicator of<br />
trophic changes, and a control on the growth of mussels reared in Mar Piccolo.<br />
Key-words: coastal zone, indicators, model, phytoplankton, Ionian Sea.<br />
Introduction - Coastal lagoons and semi-enclosed seas have peculiar functional and<br />
structural characteristics due to their location at the interface between land and sea.<br />
They generally show large temporal and spatial variations in hydro-chemical<br />
characteristics and considerable biological diversity (Castel et al., 1996). By<br />
considering the dynamic nature of these ecosystems, there is an urgent need to develop<br />
sensitive and broadly applicable indicators for detecting water quality and ecosystem<br />
health. Phytoplankton, which conduct a bulk of primary production and can rapidly<br />
respond to a wide range of environmental perturbations, represent a sensitive and<br />
important indicator for detecting ecological change in coastal systems (Paerl et al.,<br />
2009), like Mar Piccolo in Taranto. In this ecosystem, in the last fifty years, urban<br />
expansion and intensive agricultures have caused an increase in nutrients and organic<br />
matter levels, which are higher than the self-depurating capacities of the basin. Since<br />
2000, to improve the water quality, a depuration plan has been implemented in Mar<br />
Piccolo. In the framework of the Integrated Project, SPICOSA (Science and Policy<br />
Integration for COastal Systems Assessment), system-based models are being<br />
developed to provide higher-level information and decision-support tools for solving<br />
problematic issues in coastal zones. In this paper, we refer about the phytoplankton<br />
sub-model that is included into a more complex ecological model developed under the<br />
SPICOSA Mar Piccolo experiment.<br />
Materials and methods –The simulation model was developed considering a System<br />
Approach Framework and the principles of the Systems Theory (von Bertalanffy,<br />
1968). Globally, the System Theory states that complex, non-linear systems function<br />
differently in vivo than a separate scrutiny of their component parts might indicate.<br />
41 st S.I.B.M. CONGRESS Rapallo (GE), 7-11 June 2010<br />
108