Anna Maria Goździejewska , Marek Kruk , Martin Bláha
{"title":"The zooplankton adaptation patterns along turbidity gradient in shallow water reservoirs","authors":"Anna Maria Goździejewska , Marek Kruk , Martin Bláha","doi":"10.1016/j.ecohyd.2023.08.005","DOIUrl":null,"url":null,"abstract":"<div><p>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 <em>Daphnia cucullata</em> Sars, 1862, <em>Difflugia</em> spp. and <em>Cephalodella</em> spp. (LT), <em>Keratella cochlearis</em> (Gosse, 1851) (MT), and <em>K. cochlearis</em> and <em>Filinia longiseta</em> (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.</p></div>","PeriodicalId":56070,"journal":{"name":"Ecohydrology & Hydrobiology","volume":"24 1","pages":"Pages 188-200"},"PeriodicalIF":2.7000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecohydrology & Hydrobiology","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1642359323000903","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Ecohydrology & Hydrobiology is an international journal that aims to advance ecohydrology as the study of the interplay between ecological and hydrological processes from molecular to river basin scales, and to promote its implementation as an integrative management tool to harmonize societal needs with biosphere potential.