Predicting zooplankton response to environmental changes in a temperate estuarine ecosystem

Abstract

A novel strategy that allows to predict the responses of zooplanktonic species to environmental conditions in an estuarine temperate ecosystem (Mondego estuary) is presented. It uses 12 indicator species from the zooplanktonic Mondego database (102 species) that are common members of the different habitats, characterized by their specific hydrological conditions. Indicator-species analysis (ISA) was used to define and describe which species were typical of each of the five sampling stations in a 4-year study (2003)(2004)(2005)(2006). First, a canonical correspondence analysis (CCA) was carried out to objectively identify the species-habitat affinity based on the relationship between species, stations and environmental data. Response curves for each of the zooplanktonic species, generated by univariate logistic regression on each of the independent variables temperature and salinity, were generally in agreement with the descriptive statistics concerning the occurrence of those species in this particular estuarine ecosystem. Species-specific models that predict probability of occurrence relative to environmental parameters like salinity, water temperature, turbidity, chlorophyll a, total suspended solids and dissolved oxygen were then developed for the zooplanktonic species. The multiple logistic models used contained between 1 and 3 significant parameters and the percentage correctly predicted was moderate to high, ranging from 62 to 95%. The predictive accuracy of the model was assured by direct comparison of model predictions with the observed occurrence of species obtained in 2006 (validation) and from data collected in the early 2000s in another Portuguese estuary-Ria de Aveiro (Canal de Mira), a complex mesotidal shallow coastal lagoon. The regression logistic model here defined, correctly suggested that the distribution of zooplankton species was mainly dependent on salinity and water temperature. The logistic regression proved to be a useful approach for predicting the occurrence of species under varying environmental conditions at a local scale. Therefore, this model can be considered of reasonable application (and should be tested in other estuarine systems) due to its ability to predict the occurrence of individual zooplanktonic species associated with habitat changes.

Zooplankton diversity and distribution in a deep and anoxic Mediterranean coastal lake

“…Salinity stands out as one of the most important parameters in environments with strong zonation patterns (Gaudy et al, 1995;Marques et al, 2008), or in cases where man-made changes have altered the freshwater inputs in the ecosystem (Sei et al, 1996;Badosa et al, 2008). In this study, however, salinity presented very small seasonal variation and thus, it is not expected to influence zooplanktonic assemblages significantly.…”

Long-term variability of the siphonophores Muggiaea atlantica and M. kochi in the Western English Channel

“…Siphonophores are generally considered strictly oceanic (Pugh, 1999) and intolerant of low salinity waters (Mackie et al, 1987). However, the neritic M. atlantica can exploit both low salinity (Kitamura et al, 2003;Marques et al, 2008;Primo et al, 2012) and high salinity waters (Licandro et al, 2012). Salinity may however have an indirect effect, representing a proxy for physical processes.…”

Population ecology of Muggiaea atlantica (Cnidaria, Siphonophora) in the Western English Channel

“…Field studies have indicated an upper thermal limit of 24°C for the survival of M. atlantica (Marques et al 2008, Batistić et al 2013. Therefore high tem per ature was unlikely to be a limiting factor in the present study as the maximum average temperature in the Western English Channel is ~16.5 °C (Smyth et al 2010).…”