Embedding and slicing of intact in situ collected marine snow


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andreas.rogge [ at ] awi.de

Abstract

The biological carbon pump is largely driven by the formation and sinking of marine snow. Because of their high organic matter content, marine snow aggregates are hotspots for microbial activity, and microbial organic matter degradation plays an important role in the attenuation of carbon fluxes to the deep sea. Our inability to examine and characterize microscale distributions of compounds making up the aggregate matrix, and of possible niches inside marine snow, has hindered our understanding of the basic processes governing marine carbon export and sequestration. To address this issue, we have adapted soft‐embedding and sectioning to study the spatial structure and components of marine aggregates at high resolution. Soft‐embedding enables rapid quantitative sampling of undisturbed marine aggregates from the water column and from sediment traps, followed by spatially resolved staining and characterization of substrates of the aggregate matrix and the microorganisms attached to it. Particular strengths of the method include in situ embedding in sediment traps and successful fluorescence in situ hybridization (FISH)‐probe labeling, supporting studies of microbial diversity and ecology. The high spatial resolution achieved by thin‐sectioning of soft‐embedded aggregates offers the possibility for improved understanding of the composition and structure of marine snow, which directly influence settling velocity, microbial colonization and diversity, degradation rates, and carbon content. Our method will help to elucidate the small‐scale processes underlying large‐scale carbon cycling in the marine environment, which is especially relevant in the context of rising anthropogenic CO2 emissions and global change.



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Published
Eprint ID
48283
DOI 10.1002/lom3.10251

Cite as
Flintrop, C. M. , Rogge, A. , Miksch, S. , Thiele, S. , Waite, A. M. and Iversen, M. H. (2018): Embedding and slicing of intact in situ collected marine snow , Limnology and Oceanography: Methods, 16 (6), pp. 339-355 . doi: 10.1002/lom3.10251


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