Estuarine Environmental Monitoring Programs: Long-Term Studies.

JORGE MARCOVECCHIO; BOTTÉ, S.E.; DE MARCO, S.G.; ANDREA LOPEZ CAZORLA; ARIAS A.; BALDINI M; CUBITTO MA; FIORI SADRA; OLIVA A; LA COLLA N; BLASINA, G.E.; MOLINA J. M.; SIMONETTI P; SERRA A; NEGRIN V; RONDA, A.C.; PEREYRA M

The Bahía Blanca Estuary

Springer

Año: 2021; p. 521 - 548

A continuous observation and control system of measures and evaluations for a defned purpose is called “monitoring.” This is an important tool within the impact assessment process and in any vigilance and control program (Pali and Swaans 2013; Valle Junior et al. 2015). There is currently a strong consensus that environmental monitoring is not an end-point in itself but an essential step in environmental management processes (Stelzenmüller et al. 2013). Taking into account the previously mentioned concepts, the importance of monitoring within different processesof human activity can be observed. In addition, and as it is rightly mentioned, it is a fundamental tool within all that development or procedure that is desired to be carried out in a controlled and safe way (Collins et al. 2012).The monitoring programs consist of carrying out a permanent surveillance of a natural system, controlling the state and evolution of its variables, quantifying the variations that occur, and identifying the reasons that generated them. There are different work strategies, both spatial and temporal, and can be developed either exclusively based on feld data or based on experimental data and even combining both (Lindenmayer and Likens 2010). When these programs are carried out for a long period of time (e.g., decades), the set of information they provide supports a solid basis on which it is possible to accurately characterize the structure and operation of the system under study (Biber 2013). As long as the continuity of monitoring is maintained, it can be argued that as the program has more seniority (therefore more information), it is easier to identify a signifcant anomaly or variation in any of the parameters studied, taking into account that the distribution of “normal” values will be very dense, and therefore those that move away from that model will be easily distinguishable (Gray and Shimshack 2011).