The zooplankton adaptation patterns along turbidity gradient in shallow water reservoirs
•Water turbidity changes the hierarchy of zooplankton interspecific relations.•Random forest model shows zooplankton adaptation paths to various turbidity conditions.•Regression modeling shows the zooplankton occurrence patterns along turbidity gradient.•Variations of copepod nauplii biomass best re...
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Published in | Ecohydrology & Hydrobiology Vol. 24; no. 1; pp. 188 - 200 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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Elsevier B.V
01.01.2024
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Abstract | •Water turbidity changes the hierarchy of zooplankton interspecific relations.•Random forest model shows zooplankton adaptation paths to various turbidity conditions.•Regression modeling shows the zooplankton occurrence patterns along turbidity gradient.•Variations of copepod nauplii biomass best reflect the turbidity gradient conditions.•Zooplankton occurrence patterns indicate water conditions along turbidity gradient.
Turbidity is a precursor of several biotic phenomena in aquatic ecosystems, including differentiation of the zooplankton ensemble. We tested the hypothesis that the turbidity gradient in shallow artificial reservoirs can control the biomass of the most evenly distributed, i.e. the best adapted, population of a zooplankton species. This species can be sequentially linked to other zooplankton taxa to indicate a particular turbidity gradient. We assumed that each of the three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT) can be represented by the best adapted species that establishes relationships with other species. These networks can indicate adaptation to the higher and lower levels of turbidity in the class. Random forest classification and regression models were used. The classification of zooplankton adaptation showed that variation in copepod nauplii biomass best reflected the turbidity classifications. Patterns of species occurrence by Daphnia cucullata Sars, 1862, Difflugia spp. and Cephalodella spp. (LT), Keratella cochlearis (Gosse, 1851) (MT), and K. cochlearis and Filinia longiseta (Ehrenberg, 1834) (HT) were formed at successive levels of the network. The adaptation patterns in each of the three turbidity classes were based on an optimal set and sequence of zooplankton functional traits, the ability to satisfy food needs, and interspecific relationships. Random forest modelling supported a comprehensive interpretation of the results, innovatively expanding existing knowledge on the functioning of turbid water ecosystems. |
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AbstractList | Turbidity is a precursor of several biotic phenomena in aquatic ecosystems, including differentiation of the zooplankton ensemble. We tested the hypothesis that the turbidity gradient in shallow artificial reservoirs can control the biomass of the most evenly distributed, i.e. the best adapted, population of a zooplankton species. This species can be sequentially linked to other zooplankton taxa to indicate a particular turbidity gradient. We assumed that each of the three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT) can be represented by the best adapted species that establishes relationships with other species. These networks can indicate adaptation to the higher and lower levels of turbidity in the class. Random forest classification and regression models were used. The classification of zooplankton adaptation showed that variation in copepod nauplii biomass best reflected the turbidity classifications. Patterns of species occurrence by Daphnia cucullata Sars, 1862, Difflugia spp. and Cephalodella spp. (LT), Keratella cochlearis (Gosse, 1851) (MT), and K. cochlearis and Filinia longiseta (Ehrenberg, 1834) (HT) were formed at successive levels of the network. The adaptation patterns in each of the three turbidity classes were based on an optimal set and sequence of zooplankton functional traits, the ability to satisfy food needs, and interspecific relationships. Random forest modelling supported a comprehensive interpretation of the results, innovatively expanding existing knowledge on the functioning of turbid water ecosystems. •Water turbidity changes the hierarchy of zooplankton interspecific relations.•Random forest model shows zooplankton adaptation paths to various turbidity conditions.•Regression modeling shows the zooplankton occurrence patterns along turbidity gradient.•Variations of copepod nauplii biomass best reflect the turbidity gradient conditions.•Zooplankton occurrence patterns indicate water conditions along turbidity gradient. Turbidity is a precursor of several biotic phenomena in aquatic ecosystems, including differentiation of the zooplankton ensemble. We tested the hypothesis that the turbidity gradient in shallow artificial reservoirs can control the biomass of the most evenly distributed, i.e. the best adapted, population of a zooplankton species. This species can be sequentially linked to other zooplankton taxa to indicate a particular turbidity gradient. We assumed that each of the three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT) can be represented by the best adapted species that establishes relationships with other species. These networks can indicate adaptation to the higher and lower levels of turbidity in the class. Random forest classification and regression models were used. The classification of zooplankton adaptation showed that variation in copepod nauplii biomass best reflected the turbidity classifications. Patterns of species occurrence by Daphnia cucullata Sars, 1862, Difflugia spp. and Cephalodella spp. (LT), Keratella cochlearis (Gosse, 1851) (MT), and K. cochlearis and Filinia longiseta (Ehrenberg, 1834) (HT) were formed at successive levels of the network. The adaptation patterns in each of the three turbidity classes were based on an optimal set and sequence of zooplankton functional traits, the ability to satisfy food needs, and interspecific relationships. Random forest modelling supported a comprehensive interpretation of the results, innovatively expanding existing knowledge on the functioning of turbid water ecosystems. |
Author | Bláha, Martin Kruk, Marek Goździejewska, Anna Maria |
Author_xml | – sequence: 1 givenname: Anna Maria surname: Goździejewska fullname: Goździejewska, Anna Maria email: gozdzik@uwm.edu.pl organization: Faculty of Geoengineering, University of Warmia and Mazury, Oczapowskiego 5, 10-719, Olsztyn, Poland – sequence: 2 givenname: Marek surname: Kruk fullname: Kruk, Marek organization: Faculty of Mathematics and Computer Science, University of Warmia and Mazury in Olsztyn, Słoneczna 54, 10-710, Olsztyn, Poland – sequence: 3 givenname: Martin surname: Bláha fullname: Bláha, Martin organization: Faculty of Fisheries and Protection of Waters, University of South Bohemia in České Budějovice. Research Institute of Fish Culture and Hydrobiology, Zátiší 728/II, 389 25, Vodňany, Czech Republic |
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Keywords | Water turbidity Mine waters Zooplankton Random forest modelling Interspecific relationships |
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Snippet | •Water turbidity changes the hierarchy of zooplankton interspecific relations.•Random forest model shows zooplankton adaptation paths to various turbidity... Turbidity is a precursor of several biotic phenomena in aquatic ecosystems, including differentiation of the zooplankton ensemble. We tested the hypothesis... |
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SubjectTerms | biomass class Copepoda Daphnia hydrobiology Interspecific relationships Mine waters nauplii Random forest modelling species turbidity Water turbidity Zooplankton |
Title | The zooplankton adaptation patterns along turbidity gradient in shallow water reservoirs |
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