Temporal variability and community composition of zooplankton at station L4 in the Western Channel: 20 years of sampling

Eloire, Damien; Somerfield, Paul J.; Conway, D. V. P.; Halsband, Claudia; Harris, Roger P.; Bonnet, Delphine

doi:10.1093/plankt/fbq009

Cited by 101 publications

(90 citation statements)

References 54 publications

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“…This is consistent with previous studies across the northern and central Red Sea that have reported similar findings in terms of copepod abundance (Khalil and El-Rakman, 1997;El-Sherbiny et al, 2007;Dorgham et al, 2012;Pearman et al, 2014) as well as with studies in other marine basins (e.g., Caribbean: Moore and Sander, 1976;Mediterranean: Pancucci-Papadopoulou et al, 1992; the Western Channel: Eloire et al, 2010). In our study, the majority of the reads corresponded to calanoid copepods, while poecilostomatoids and harpacticoids occurred only rarely (Table 2).…”

Section: Annual Zooplankton Succession and Assemblage Structure In Thsupporting

confidence: 93%

Metabarcoding Reveals Seasonal and Temperature-Dependent Succession of Zooplankton Communities in the Red Sea

2017

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Very little is known about the composition and the annual cycle of zooplankton assemblages in the Red Sea, a confined water body characterized by a high biodiversity and endemism but at the same time one of the most understudied areas in the world in terms of marine biodiversity. This high diversity together with the lack of references for several of the groups poses a problem in obtaining basic information on zooplankton seasonal patterns. In the present work, we used high throughput sequencing to examine the temporal and spatial distribution of the zooplankton communities inhabiting the epipelagic zone in the central Red Sea. The analysis of zooplankton assemblages collected at two sites-coastal and offshore-twice a month at several depth strata by using MANTA, Bongo and WP2 nets provides baseline information of the seasonal patterns of the zooplankton community over 1 year. We show that the seasonal fluctuation of zooplankton communities living in the upper 100 m of the water column is driven mainly by the annual changes in seawater temperature. The 18S rRNA gene was used for metabarcoding of zooplankton assemblages revealing 630 metazoan OTUs (97% similarity) in five phyla, highlighting the richness of the Red Sea community. During colder months, communities were characterized by lower richness and higher biomass than communities found during the hot season. Throughout the year the zooplankton communities were dominated by the class Maxillopoda, mainly represented by copepods and class Hydrozoa. The rise in the water temperature favors the appearance of classes Malacostraca, Cephalopoda, Gastropoda, and Saggitoidea. The present study provides essential baseline information for future monitoring and improves our knowledge of the marine ecosystem in the Red Sea while reporting the main environmental variable structuring zooplankton assemblages in this region.

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Section: Annual Zooplankton Succession and Assemblage Structure In Thsupporting

confidence: 93%

Metabarcoding Reveals Seasonal and Temperature-Dependent Succession of Zooplankton Communities in the Red Sea

2017

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“…To reduce inter-sample variability, duplicate samples were averaged and data represented as the number of individuals or colonies per cubic metre (see Eloire et al [2010] for a detailed description of the sampling methodology).…”

Section: Muggiaea and Other Zooplankton Datamentioning

confidence: 99%

Population ecology of Muggiaea atlantica (Cnidaria, Siphonophora) in the Western English Channel

Blackett¹,

Lucas²,

Harmer³

et al. 2015

Mar. Ecol. Prog. Ser.

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“…Eloire et al (2010) and Southward et al (2005) describe data collection methods for zooplankton and for phytoplankton, respectively. Timepoints including both zooplankton and phytoplankton abundance data from 1992-2007 were used for analysis in this study.…”

Section: English Channelmentioning

confidence: 99%

Inferring plankton community structure from marine and freshwater long‐term data using multivariate autoregressive models

Scheef

Hampton

Izmest'eva

2013

Limnology & Ocean Methods

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Multivariate autoregressive (MAR) models have been useful in elucidating food web dynamics and stability from freshwater plankton monitoring data, but their applicability to marine datasets has not been as well explored. Characteristics of marine systems, such as the movement of water masses by tides and currents, may present unique challenges to MAR modeling of data gathered in marine environments. To explore the behavior of MAR models with marine plankton data, in the context of what we know about applying MAR to freshwater data, we applied MARs to each of three freshwater and four marine long-term datasets and compared results among them. We generated sets of replicate MAR models for each dataset and used the consistency of models within each set of replicates as a measure of MAR performance. Overall, replicate MAR models generated from the marine datasets were less consistent than those generated from the freshwater datasets, suggesting that MAR methods need fundamental reconfigurations to be applied to standard marine plankton data. Higher variability observed within the marine MAR results may be attributable to weaker biotic interactions as represented by the data, and to overparameterization when the criteria for lumping freshwater plankton taxa into model variables are directly applied to marine plankton taxa. Adjustments to dataset preparation for MAR application and to the modeling framework itself may address these issues associated with analyzing data from highly dynamic systems.

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Temporal variability and community composition of zooplankton at station L4 in the Western Channel: 20 years of sampling

Cited by 101 publications

References 54 publications

Metabarcoding Reveals Seasonal and Temperature-Dependent Succession of Zooplankton Communities in the Red Sea

Metabarcoding Reveals Seasonal and Temperature-Dependent Succession of Zooplankton Communities in the Red Sea

Population ecology of Muggiaea atlantica (Cnidaria, Siphonophora) in the Western English Channel

Inferring plankton community structure from marine and freshwater long‐term data using multivariate autoregressive models

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