Zooplankton network conditioned by turbidity gradient in small anthropogenic reservoirs

Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient significantly differentiates the dynamics, significance and type of relationships in the structure of zooplankton communities colonizing mine pit reservo...

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Published inScientific reports Vol. 12; no. 1; pp. 3938 - 12
Main Authors Goździejewska, Anna Maria, Kruk, Marek
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 10.03.2022
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ISSN2045-2322
2045-2322
DOI10.1038/s41598-022-08045-y

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Abstract Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient significantly differentiates the dynamics, significance and type of relationships in the structure of zooplankton communities colonizing mine pit reservoirs. The interactions between zooplankton species were evaluated by network graph analysis for three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT). The HT network was most cohesive, and it was controlled by taxa grazing on various food sources within one ecological niche ( Polyarthra longiremis , Brachionus angularis , Cyclops vicinus , Codonella cratera ) and the positive and negative relationships between them were balanced. The MT biocenotic network was composed of three sub-networks connected by nodes with high communication attributes ( Polyarthra vulgaris , Bosmina longirostris , C. vicinus ), and antagonistic interactions (predation and competition) were less important. The LT network was most heterogeneous, and Daphnia cuculllata exerted the strongest influence on the network’s structure by forming numerous positive (coexistence with predators) and negative (interference competition with microphagous rotifers) interspecific relationships. The study provides new information about the ecology of aquatic ecosystems, that are disturbed by changes in water turbidity.
AbstractList Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient significantly differentiates the dynamics, significance and type of relationships in the structure of zooplankton communities colonizing mine pit reservoirs. The interactions between zooplankton species were evaluated by network graph analysis for three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT). The HT network was most cohesive, and it was controlled by taxa grazing on various food sources within one ecological niche ( Polyarthra longiremis , Brachionus angularis , Cyclops vicinus , Codonella cratera ) and the positive and negative relationships between them were balanced. The MT biocenotic network was composed of three sub-networks connected by nodes with high communication attributes ( Polyarthra vulgaris , Bosmina longirostris , C. vicinus ), and antagonistic interactions (predation and competition) were less important. The LT network was most heterogeneous, and Daphnia cuculllata exerted the strongest influence on the network’s structure by forming numerous positive (coexistence with predators) and negative (interference competition with microphagous rotifers) interspecific relationships. The study provides new information about the ecology of aquatic ecosystems, that are disturbed by changes in water turbidity.
Abstract Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient significantly differentiates the dynamics, significance and type of relationships in the structure of zooplankton communities colonizing mine pit reservoirs. The interactions between zooplankton species were evaluated by network graph analysis for three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT). The HT network was most cohesive, and it was controlled by taxa grazing on various food sources within one ecological niche (Polyarthra longiremis, Brachionus angularis, Cyclops vicinus, Codonella cratera) and the positive and negative relationships between them were balanced. The MT biocenotic network was composed of three sub-networks connected by nodes with high communication attributes (Polyarthra vulgaris, Bosmina longirostris, C. vicinus), and antagonistic interactions (predation and competition) were less important. The LT network was most heterogeneous, and Daphnia cuculllata exerted the strongest influence on the network’s structure by forming numerous positive (coexistence with predators) and negative (interference competition with microphagous rotifers) interspecific relationships. The study provides new information about the ecology of aquatic ecosystems, that are disturbed by changes in water turbidity.
Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient significantly differentiates the dynamics, significance and type of relationships in the structure of zooplankton communities colonizing mine pit reservoirs. The interactions between zooplankton species were evaluated by network graph analysis for three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT). The HT network was most cohesive, and it was controlled by taxa grazing on various food sources within one ecological niche (Polyarthra longiremis, Brachionus angularis, Cyclops vicinus, Codonella cratera) and the positive and negative relationships between them were balanced. The MT biocenotic network was composed of three sub-networks connected by nodes with high communication attributes (Polyarthra vulgaris, Bosmina longirostris, C. vicinus), and antagonistic interactions (predation and competition) were less important. The LT network was most heterogeneous, and Daphnia cuculllata exerted the strongest influence on the network's structure by forming numerous positive (coexistence with predators) and negative (interference competition with microphagous rotifers) interspecific relationships. The study provides new information about the ecology of aquatic ecosystems, that are disturbed by changes in water turbidity.
Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient significantly differentiates the dynamics, significance and type of relationships in the structure of zooplankton communities colonizing mine pit reservoirs. The interactions between zooplankton species were evaluated by network graph analysis for three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT). The HT network was most cohesive, and it was controlled by taxa grazing on various food sources within one ecological niche (Polyarthra longiremis, Brachionus angularis, Cyclops vicinus, Codonella cratera) and the positive and negative relationships between them were balanced. The MT biocenotic network was composed of three sub-networks connected by nodes with high communication attributes (Polyarthra vulgaris, Bosmina longirostris, C. vicinus), and antagonistic interactions (predation and competition) were less important. The LT network was most heterogeneous, and Daphnia cuculllata exerted the strongest influence on the network's structure by forming numerous positive (coexistence with predators) and negative (interference competition with microphagous rotifers) interspecific relationships. The study provides new information about the ecology of aquatic ecosystems, that are disturbed by changes in water turbidity.Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient significantly differentiates the dynamics, significance and type of relationships in the structure of zooplankton communities colonizing mine pit reservoirs. The interactions between zooplankton species were evaluated by network graph analysis for three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT). The HT network was most cohesive, and it was controlled by taxa grazing on various food sources within one ecological niche (Polyarthra longiremis, Brachionus angularis, Cyclops vicinus, Codonella cratera) and the positive and negative relationships between them were balanced. The MT biocenotic network was composed of three sub-networks connected by nodes with high communication attributes (Polyarthra vulgaris, Bosmina longirostris, C. vicinus), and antagonistic interactions (predation and competition) were less important. The LT network was most heterogeneous, and Daphnia cuculllata exerted the strongest influence on the network's structure by forming numerous positive (coexistence with predators) and negative (interference competition with microphagous rotifers) interspecific relationships. The study provides new information about the ecology of aquatic ecosystems, that are disturbed by changes in water turbidity.
ArticleNumber 3938
Author Kruk, Marek
Goździejewska, Anna Maria
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/35273316$$D View this record in MEDLINE/PubMed
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– reference: 35428864 - Sci Rep. 2022 Apr 15;12(1):6329
SSID ssj0000529419
Score 2.4391801
Snippet Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient...
Abstract Water turbidity can significantly influence interspecific interactions in aquatic ecosystems. We tested the hypothesis that the turbidity gradient...
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StartPage 3938
SubjectTerms 704/158
704/172
704/286
Anthropogenic factors
Aquatic ecosystems
Coexistence
Competition
Food sources
Humanities and Social Sciences
Interspecific relationships
multidisciplinary
Predation
Predators
Reservoirs
Science
Science (multidisciplinary)
Turbidity
Zooplankton
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Title Zooplankton network conditioned by turbidity gradient in small anthropogenic reservoirs
URI https://link.springer.com/article/10.1038/s41598-022-08045-y
https://www.ncbi.nlm.nih.gov/pubmed/35273316
https://www.proquest.com/docview/2637832406
https://www.proquest.com/docview/2638727348
https://pubmed.ncbi.nlm.nih.gov/PMC8913641
https://doaj.org/article/7ae84a6a15934d35883baaad39b8f1a4
Volume 12
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