Zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach

The main purpose of the research was to determine the differences in the network relationships among zooplankton predator and prey taxa biomasses as a premise for dividing coastal lakes according to the brackish-freshwater gradient. Furthermore, the significance of these divisions in the overall int...

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Autores principales:	Marek Kruk, Ewa Paturej, Krystian Obolewski
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Coastal lakes Zooplankton Predator–prey web Support vector machines Structural equation modeling Graph meta-network Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/67fc8def3f304049970c0885cf9522eb
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spelling	oai:doaj.org-article:67fc8def3f304049970c0885cf9522eb2021-12-01T04:48:01ZZooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach1470-160X10.1016/j.ecolind.2021.107550https://doaj.org/article/67fc8def3f304049970c0885cf9522eb2021-06-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21002156https://doaj.org/toc/1470-160XThe main purpose of the research was to determine the differences in the network relationships among zooplankton predator and prey taxa biomasses as a premise for dividing coastal lakes according to the brackish-freshwater gradient. Furthermore, the significance of these divisions in the overall interspecies interactions of the zooplankton networks of these waters was demonstrated. To solve problems with multidimensional and highly interactive character of the data, we used machine learning and meta-network analysis models. The data analysis methods comprised the support vector machines (SVM) multidimensional modelling, structural equation modelling (SEM), and graph network analysis. The zooplankton taxa biomasses showed high accuracy with lake classification on mesohaline, oligohaline and freshwater classes. We showed two interspecies relationships in coastal lakes in the zooplankton taxa predator–prey Cladocera and Copepoda - Rotifera assemblage, which variability of taxa biomass indicated more saline or more freshwater lake classes. Biomass increases in the predators Cyclopoida copepodites, B. longirostris, D. cucullata, and the prey K. cochlearis were associated with the freshwater class. However, increased Calanoida nauplii and his prey K. cochlearis tecta biomasses suggested that they belong to the more saline lake class. In the case of decreases in the biomass of these taxa, the preference would shift to the opposite of the above. Lake salinity classes differed in the role they had on the connections of the zooplankton taxa generalized meta-network of the South Baltic coastal lakes. The freshwater and mesohaline classes were the most important for the organization of the interspecies network, while the oligohaline class had the poorest connections among taxa and showed a marginal role in the integrity of the coastal lakes’ zooplankton meta-network.Marek KrukEwa PaturejKrystian ObolewskiElsevierarticleCoastal lakesZooplanktonPredator–prey webSupport vector machinesStructural equation modelingGraph meta-networkEcologyQH540-549.5ENEcological Indicators, Vol 125, Iss , Pp 107550- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Coastal lakes Zooplankton Predator–prey web Support vector machines Structural equation modeling Graph meta-network Ecology QH540-549.5
spellingShingle	Coastal lakes Zooplankton Predator–prey web Support vector machines Structural equation modeling Graph meta-network Ecology QH540-549.5 Marek Kruk Ewa Paturej Krystian Obolewski Zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach
description	The main purpose of the research was to determine the differences in the network relationships among zooplankton predator and prey taxa biomasses as a premise for dividing coastal lakes according to the brackish-freshwater gradient. Furthermore, the significance of these divisions in the overall interspecies interactions of the zooplankton networks of these waters was demonstrated. To solve problems with multidimensional and highly interactive character of the data, we used machine learning and meta-network analysis models. The data analysis methods comprised the support vector machines (SVM) multidimensional modelling, structural equation modelling (SEM), and graph network analysis. The zooplankton taxa biomasses showed high accuracy with lake classification on mesohaline, oligohaline and freshwater classes. We showed two interspecies relationships in coastal lakes in the zooplankton taxa predator–prey Cladocera and Copepoda - Rotifera assemblage, which variability of taxa biomass indicated more saline or more freshwater lake classes. Biomass increases in the predators Cyclopoida copepodites, B. longirostris, D. cucullata, and the prey K. cochlearis were associated with the freshwater class. However, increased Calanoida nauplii and his prey K. cochlearis tecta biomasses suggested that they belong to the more saline lake class. In the case of decreases in the biomass of these taxa, the preference would shift to the opposite of the above. Lake salinity classes differed in the role they had on the connections of the zooplankton taxa generalized meta-network of the South Baltic coastal lakes. The freshwater and mesohaline classes were the most important for the organization of the interspecies network, while the oligohaline class had the poorest connections among taxa and showed a marginal role in the integrity of the coastal lakes’ zooplankton meta-network.
format	article
author	Marek Kruk Ewa Paturej Krystian Obolewski
author_facet	Marek Kruk Ewa Paturej Krystian Obolewski
author_sort	Marek Kruk
title	Zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach
title_short	Zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach
title_full	Zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach
title_fullStr	Zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach
title_full_unstemmed	Zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach
title_sort	zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. machine learning and meta-network approach
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/67fc8def3f304049970c0885cf9522eb
work_keys_str_mv	AT marekkruk zooplanktonpredatorpreynetworkrelationshipsindicatesthesalinegradientofcoastallakesmachinelearningandmetanetworkapproach AT ewapaturej zooplanktonpredatorpreynetworkrelationshipsindicatesthesalinegradientofcoastallakesmachinelearningandmetanetworkapproach AT krystianobolewski zooplanktonpredatorpreynetworkrelationshipsindicatesthesalinegradientofcoastallakesmachinelearningandmetanetworkapproach
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Zooplankton predator–prey network relationships indicates the saline gradient of coastal lakes. Machine learning and meta-network approach

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