Identification of Factors Affecting Environmental Contamination Represented by Post-Hatching Eggshells of a Common Colonial Waterbird with Usage of Artificial Neural Networks

cris.virtual.author-orcid0000-0001-5616-3827
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cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid0000-0002-9239-4072
cris.virtualsource.author-orcida2f42993-2b76-4d53-acc8-61c1b5b10c4e
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
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cris.virtualsource.author-orcid85dd240b-a6d1-4110-ab08-361ff2720cb6
dc.abstract.enArtificial Neural Networks are used to find the influence of habitat types on the quality of the environment expressed by the concentrations of toxic and harmful elements in avian tissue. The main habitat types were described according to the Corine Land Cover CLC2012 model. Eggs of free-living species of a colonial waterbird, the grey heron Ardea cinerea, were used as a biological data storing media for biomonitoring. For modeling purposes, pollution indices expressing the sum of the concentration of harmful and toxic elements (multi-contamination rank index) and indices for single elements were created. In the case of all the examined indices apart from Cd, the generated topologies were a multi-layer perceptron (MLP) with 1 hidden layer. Interestingly, in the case of Cd, the generated optimal topology was a network with a radial basis function (RBF). The data analysis showed that the increase in environmental pollution was mainly influenced by human industrial activity. The increase in Hg, Cd, and Pb content correlated mainly with the increase in the areas characterized by human activity (industrial, commercial, and transport units) in the vicinity of a grey heron breeding colony. The decrease in the above elements was conditioned by relative areas of farmland and inland waters. Pollution with Fe, Mn, Zn, and As was associated mainly with areas affected by industrial activities. As the location variable did not affect the quality of the obtained networks, it was removed from the models making them more universal.
dc.affiliationWydział Inżynierii Środowiska i Inżynierii Mechanicznej
dc.affiliation.instituteKatedra Inżynierii Biosystemów
dc.contributor.authorSujak, Agnieszka
dc.contributor.authorJakubas, Dariusz
dc.contributor.authorKitowski, Ignacy
dc.contributor.authorBoniecki, Piotr
dc.date.access2026-01-30
dc.date.accessioned2026-02-10T08:52:16Z
dc.date.available2026-02-10T08:52:16Z
dc.date.copyright2022-05-13
dc.date.issued2022
dc.description.abstract<jats:p>Artificial Neural Networks are used to find the influence of habitat types on the quality of the environment expressed by the concentrations of toxic and harmful elements in avian tissue. The main habitat types were described according to the Corine Land Cover CLC2012 model. Eggs of free-living species of a colonial waterbird, the grey heron Ardea cinerea, were used as a biological data storing media for biomonitoring. For modeling purposes, pollution indices expressing the sum of the concentration of harmful and toxic elements (multi-contamination rank index) and indices for single elements were created. In the case of all the examined indices apart from Cd, the generated topologies were a multi-layer perceptron (MLP) with 1 hidden layer. Interestingly, in the case of Cd, the generated optimal topology was a network with a radial basis function (RBF). The data analysis showed that the increase in environmental pollution was mainly influenced by human industrial activity. The increase in Hg, Cd, and Pb content correlated mainly with the increase in the areas characterized by human activity (industrial, commercial, and transport units) in the vicinity of a grey heron breeding colony. The decrease in the above elements was conditioned by relative areas of farmland and inland waters. Pollution with Fe, Mn, Zn, and As was associated mainly with areas affected by industrial activities. As the location variable did not affect the quality of the obtained networks, it was removed from the models making them more universal.</jats:p>
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_nocost
dc.description.financecost0,00
dc.description.if3,9
dc.description.number10
dc.description.points100
dc.description.versionfinal_published
dc.description.volume22
dc.identifier.doi10.3390/s22103723
dc.identifier.issn1424-8220
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/7277
dc.identifier.weblinkhttps://www.mdpi.com/1424-8220/22/10/3723
dc.languageen
dc.relation.ispartofSensors
dc.relation.pagesart. 3723
dc.rightsCC-BY
dc.sciencecloudnosend
dc.share.typeOPEN_JOURNAL
dc.subject.enbiomaterial
dc.subject.enbiomonitoring
dc.subject.engrey heron
dc.subject.enelemental analysis
dc.subject.enartificial neural networks
dc.titleIdentification of Factors Affecting Environmental Contamination Represented by Post-Hatching Eggshells of a Common Colonial Waterbird with Usage of Artificial Neural Networks
dc.typeJournalArticle
dspace.entity.typePublication
oaire.citation.issue10
oaire.citation.volume22