Spatial dynamics of eukaryotic microbial communities in the German Bight

Sprong, Pim; Fofonova, Vera; Wiltshire, Karen Helen; Neuhaus, Stefan; Ludwichowski, Kai‐Uwe; Käse, Laura; Androsov, Alexey; Metfies, Katja

doi:10.1016/j.seares.2020.101914

Cited by 15 publications

(7 citation statements)

References 63 publications

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“…With a reduction in grid cell size, the model output can result in a completely different local circulation pattern. Concomitantly, different possible connections may be predicted between the considered positions (Sprong et al, 2020). Obviously, there is no universal answer for the optimal horizontal and vertical resolutions across all water bodies and coastal realms.…”

Section: Discussion Toward Seamless Coupling Between Food Web and Physical Ocean Modelsmentioning

confidence: 99%

“…There is a rich diversity of models available to conduct climate change projections in coastal areas, such as GETM, FESOM-C, SCHISM/SELFE, NEMO, DELFT3D, ROMS, FVCOM, and others (Burchard and Bolding, 2002;Shchepetkin and McWilliams, 2005;Chen et al, 2006;Zhang and Baptista, 2008;Zhang et al, 2016;Madec et al, 2017;Androsov et al, 2019). The role of the physical models can be divided into four pieces: (1) predictions of the abiotic parameters' distribution in space and time to supply the biogeochemical and food-web models (Hofmeister et al, 2017;Kerimoglu et al, 2017;Lemmen et al, 2018), (2) prediction of pathways of water parcels, passive and active tracers (van der Molen et al, 2018;Ricker and Stanev, 2020;Sprong et al, 2020), (3) predictions of the future "hotspots" in a sense of largest changes in the abiotic parameters' behavior (sensitivity studies) (Delworth et al, 2012;Yin, 2012;Schrum et al, 2016), and (4) evaluation of the representativeness of long-term observational stations for larger areas.…”

Section: Ocean Models In Relation To Climate Change Pressurementioning

confidence: 99%

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Toward Improved Model Capacities for Assessment of Climate Impacts on Coastal Bentho-Pelagic Food Webs and Ecosystem Services

et al. 2021

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Global climate change is a key driver of change in coastal waters with clear effects on biological communities and marine ecosystems. Human activities in combination with climate change exert a tremendous pressure on marine ecosystems and threaten their integrity, structure, and functioning. The protection of these ecosystems is a major target of the 14th United Nations sustainable development goal “Conserve and sustainably use the oceans, seas and marine resources for sustainable development.” However, due to the complexity of processes and interactions of stressors, the status assessment of ecosystems remains a challenge. Holistic food web models, including biological and environmental data, could provide a suitable basis to assess ecosystem health. Here, we review climate change impacts on different trophic levels of coastal ecosystems ranging from plankton to ecologically and economically important fish and shellfish species. Furthermore, we show different food web model approaches, their advantages and limitations. To effectively manage coastal ecosystems, we need both a detailed knowledge base of each trophic level and a holistic modeling approach for assessment and prediction of future scenarios on food web-scales. A new model approach with a seamless coupling of physical ocean models and food web models could provide a future tool for guiding ecosystem-based management.

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Section: Discussion Toward Seamless Coupling Between Food Web and Physical Ocean Modelsmentioning

confidence: 99%

Section: Ocean Models In Relation To Climate Change Pressurementioning

confidence: 99%

Toward Improved Model Capacities for Assessment of Climate Impacts on Coastal Bentho-Pelagic Food Webs and Ecosystem Services

et al. 2021

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“…In short, the first sampling phase was conducted from March 2016 to May 2016 (work-daily sampling) [ 47 ]. The second phase included samples from June to October 2016 (in total 6 samples, irregular sampling) [ 48 ]. The third phase was conducted from December 2016 until March 2019, where samples were taken twice a week.…”

Section: Methodsmentioning

confidence: 99%

Host-parasitoid associations in marine planktonic time series: Can metabarcoding help reveal them?

et al. 2021

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In this study, we created a dataset of a continuous three-year 18S metabarcoding survey to identify eukaryotic parasitoids, and potential connections to hosts at the Long-Term Ecological Research station Helgoland Roads. The importance of parasites and parasitoids for food web dynamics has previously been recognized mostly in terrestrial and freshwater systems, while marine planktonic parasitoids have been understudied in comparison to those. Therefore, the occurrence and role of parasites and parasitoids remains mostly unconsidered in the marine environment. We observed high abundances and diversity of parasitoid operational taxonomic units in our dataset all year round. While some parasitoid groups were present throughout the year and merely fluctuated in abundances, we also detected a succession of parasitoid groups with peaks of individual species only during certain seasons. Using co-occurrence and patterns of seasonal occurrence, we were able to identify known host-parasitoid dynamics, however identification of new potential host-parasitoid interactions was not possible due to their high dynamics and variability in the dataset.

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“…Nevertheless, this method still tends to overestimate the abundance of dino agellates, because their genome usually displays a high copy number of ribosomal operons [56]. After sequencing 300 bp paired-end with a MiSeq System (Illumina, California, USA), amplicon sequence variants (ASVs) were generated and annotated (as described in [57] and with the PR 2 -database; version 4.11.1; [58]). The species were marked with their respective trophic mode, if known, by manual curation (see table in supplementary data for applied criteria).…”

Section: Sample Preparation and Analysismentioning

confidence: 99%

Transition from a Mixotroph/Heterotroph Protist Community During the Dark Winter to a Photoautotrophic Spring Community in Arctic Surface Waters

Bruhn

Lundholm

Hansen

et al. 2021

Preprint

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Unicellular plankton communities (protists) are the basis of the marine food web. The spring bloom is especially important, because of its high biomass. However, it is poorly described how the protist community structure in Arctic surface waters develops from winter to spring. We show that mixotrophy and parasitism are the prominent trophic modes in the dark winter period. The transition period was characterized by a high relative abundance of mixotrophic dinoflagellates, while centric diatoms and the haptophyte Phaeocystis pouchetii dominated the successive phototrophic spring bloom event. Our observations indicate the presence of a characteristic winter community and a community shift from winter to spring, and not just a dormant spring community waiting for better circumstances. The spring bloom initiation commenced while sea ice was still obstructing the light penetration into the water column. The initiation coincided with a change in day length and spectral composition of the light, rather than with an increased light intensity. The initial increase in fluorescence, and therefore photosynthetic activity, was detected relatively deep in the water column, at ~55 m depth. This suggests that water column stratification and a complex interplay of abiotic factors eventually promote the spring bloom initiation.

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Spatial dynamics of eukaryotic microbial communities in the German Bight

Cited by 15 publications

References 63 publications

Toward Improved Model Capacities for Assessment of Climate Impacts on Coastal Bentho-Pelagic Food Webs and Ecosystem Services

Toward Improved Model Capacities for Assessment of Climate Impacts on Coastal Bentho-Pelagic Food Webs and Ecosystem Services

Host-parasitoid associations in marine planktonic time series: Can metabarcoding help reveal them?

Transition from a Mixotroph/Heterotroph Protist Community During the Dark Winter to a Photoautotrophic Spring Community in Arctic Surface Waters

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