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Predicting zooplankton response to environmental changes in a temperate estuarine ecosystem

2008Journal article Restricted access
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dc.contributor.authorMarques, Sónia Cotrim
dc.contributor.authorAzeiteiro, Ulisses Miranda
dc.contributor.authorLeandro, Sérgio Miguel
dc.contributor.authorQueiroga, Henrique
dc.contributor.authorPrimo, Ana Ligia
dc.contributor.authorMartinho, Filipe
dc.contributor.authorViegas, Ivan
dc.contributor.authorPardal, Miguel Ângelo
dc.date.accessioned2022-09-06T12:03:01Z
dc.date.available2022-09-06T12:03:01Z
dc.date.issued2008
dc.descriptionThe present work was supported by I.I.I. (Instituto de Investigacao Interdisciplinar of the University of Coimbra) through a Ph.D grant awarded to S. C. Marques (III/AMB/28/2005).
dc.description.abstractA 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 (2003–2006). 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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMarques, S.C., Azeiteiro, U.M., Leandro, S.M. et al. Predicting zooplankton response to environmental changes in a temperate estuarine ecosystem. Mar Biol 155, 531–541 (2008). https://doi.org/10.1007/s00227-008-1052-6pt_PT
dc.identifier.doi10.1007/s00227-008-1052-6pt_PT
dc.identifier.issn0025-3162
dc.identifier.issn1432-1793
dc.identifier.urihttp://hdl.handle.net/10400.8/7614
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s00227-008-1052-6#citeaspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.titlePredicting zooplankton response to environmental changes in a temperate estuarine ecosystempt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage541pt_PT
oaire.citation.startPage531pt_PT
oaire.citation.titleMarine Biologypt_PT
oaire.citation.volume155pt_PT
person.familyNameCotrim Marques
person.familyNameAzeiteiro
person.familyNameLeandro
person.familyNameQueiroga
person.familyNamePrimo
person.givenNameSónia
person.givenNameUlisses Manuel de Miranda
person.givenNameSergio Miguel
person.givenNameHenrique
person.givenNameAna Ligia
person.identifierC-5933-2008
person.identifier156067
person.identifier245308
person.identifier.ciencia-id1C13-105A-FF3A
person.identifier.ciencia-id4010-5225-08DD
person.identifier.ciencia-id5C15-5F50-E5B6
person.identifier.ciencia-idB015-74A3-0F7A
person.identifier.orcid0000-0002-9467-3825
person.identifier.orcid0000-0002-5252-1700
person.identifier.orcid0000-0001-5005-3598
person.identifier.orcid0000-0002-2338-0013
person.identifier.orcid0000-0002-8632-2929
person.identifier.ridM-4254-2013
person.identifier.ridC-5134-2008
person.identifier.scopus-author-id9271998100
person.identifier.scopus-author-id6603109821
person.identifier.scopus-author-id6603233719
person.identifier.scopus-author-id6602694507
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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