Grazing impact of microzooplankton upon phytoplankton

Alterations of freshwater flow regimes and increasing eutrophication can lead to alterations in phytoplankton biomass, composition, and growth in estuaries and adjacent coastal waters. Since phytoplankton is the first trophic level of most aquatic foodwebs, these changes can be propagated to other biological compartments, eventually impacting water quality and ecosystem services. However, phytoplankton responses to environmental changes in abiotic variables (e.g., light, nutrients) are additionally controlled by mortality or removal processes (e.g., grazing, horizontal advection and viral lysis). Grazing exerted by microzooplankton, usually dominated by phagotrophic protists, is considered the most relevant phytoplankton mortality factor in most aquatic systems (see Calbet, Landry 2004). In fact, grazing impact of microzooplankton can prevent phytoplankton accumulation in marine systems despite an overall increase in phytoplankton replication rate. By consequence, microzooplankton grazing may minimize problems associated to increased eutrophication and, ultimately, prevent the occurrence of harmful phytoplankton blooms. Thus, microzooplankton grazing on phytoplankton constitutes a key biological process required to understand and predict relationships between hydrological and biological processes in aquatic ecosystems and to use ecosystem properties to improve water quality and enhance ecosystem services, general principles of the Ecohydrology Concept (Zalewski 2000).

Patterns of distribution in intertidal rocky shores: the role of grazing and competition in structuring communities

Tese de doutoramento, Ciências do Mar, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2000

Combined disaggregation of agricultural land uses, livestock numbers and crops' production: an entropy approach

This paper presents several combined agricultural data disaggregation models in order to recover the farms' land uses, the livestock numbers and main crops' productions. The proposed approach estimates incomplete information at disaggregated level through entropy, using an information prior, and generating information for a combined calculation use of data in the estimation of other variables. The models were applied to the region of Algarve, to some rural pilot areas (Salir-Ameixial-Cachopo and Alcoutim) for livestock data, since this data in some Algarve's inland areas is needed for a European forest fire prevention project, and to the agrarian zones in a more complex framework. The results are promising. They were validated, in cross reference to real data, having proven to be valid and reliable. The total error was small and a considerable level of information heterogeneity was recovered. The total error was about 27,9% for the counties' land uses and 21% for the agrarian zones, and for the livestock it was also acceptable. The level of heterogeneity recovered was always higher than 50%, revealing some improvements regarding previous studies.