Survey of environmental complex systems: pattern recognition of physicochemical data describing coastal water quality in the Gulf of Trieste.

A data set reporting temperature, salinity, dissolved oxygen, nitrogen as ammonia, nitrite and nitrate, silicate, chlorophyll a and phaeopigment values, determined in seawaters sampled during two years with a monthly frequency in 16 stations in the Gulf of Trieste, and at different depths of the water column, has been studied. In order to find synthetic descriptors useful for following the spatial and temporal variations of biogeochemical phenomena occurring in the considered ecosystem, the data set has been factorized using principal component analysis. A graphical display of scores, by means of boxplots and biplots, helped in the interpretation of the data set. The first factor conditioning the system is related to the input of freshwater from the estuary of the Isonzo River and to the stratification of the seawater (thermohaline discontinuity), while the second and third components describe interactions between biological activity, nutrients and physicochemical parameters; typical spring and autumn phytoplankton blooms were identified, in addition to an exceptional winter bloom conditioned by anomalous meteorological/climatic conditions. The fourth principal component explains the reducing activity of seawaters, which often increases when the decomposition of organic matter is relevant. The simple linear model proposed, and the related graphs, are shown to be useful tools for monitoring the main features of such a complex dynamic environmental system. The outlined approach to the considered complex data structure presents in a cognitive easy way (graphical outputs) the significant variations of the data, and allows for a detailed interpretation of the results of the monitoring campaign. Temporal and spatial effects are outlined, as well as those related to the depth in the water column.