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Computed tomography reconstructions of burrow networks for the Opheliid polychaete, Armandia cirrhosa

Computed tomography reconstructions of burrow networks for the Opheliid polychaete, Armandia cirrhosa
Computed tomography reconstructions of burrow networks for the Opheliid polychaete, Armandia cirrhosa
The morphology and architecture of structures formed by sediment-dwelling invertebrates, such as excavations or burrows, are often assumed to be characteristic of a given species, consistent across a range of environmental conditions, and used to categorise species contributions to ecosystem functioning. However, very few investigations use non-invasive high-resolution techniques capable of determining fine scale variations in burrow form and complexity, or consider whether or not the form of the burrow is context dependent. Here, we provide replicate high-resolution micro-focus computed tomography data for the complete burrow systems of the Opheliid polychaete, Armandia cirrhosa, across a range of salinity and habitat conditions. These data provide reference models which can be used by ecologists investigating intraspecific variation in species traits and organism-sediment interactions and, more generally, by those tasked with pattern and shape recognition of objects that are morphologically highly variable and which adjust their architecture with changing circumstance or context.
Animals, Ecosystem, Geologic Sediments, Polychaeta/anatomy & histology, Salinity, Tomography, X-Ray Computed, X-Ray Microtomography
2052-4463
695
Howman, Rebecca M.
0c132d44-9552-4dbe-8d05-177a73aee240
Mavrogordato, Mark N.
f3e0879b-118a-463a-a130-1c890e9ab547
Alvarez-Borges, Fernando
5512cdfd-6ad3-475f-8aec-2fc767607314
Solan, Martin
c28b294a-1db6-4677-8eab-bd8d6221fecf
Howman, Rebecca M.
0c132d44-9552-4dbe-8d05-177a73aee240
Mavrogordato, Mark N.
f3e0879b-118a-463a-a130-1c890e9ab547
Alvarez-Borges, Fernando
5512cdfd-6ad3-475f-8aec-2fc767607314
Solan, Martin
c28b294a-1db6-4677-8eab-bd8d6221fecf

Howman, Rebecca M., Mavrogordato, Mark N., Alvarez-Borges, Fernando and Solan, Martin (2024) Computed tomography reconstructions of burrow networks for the Opheliid polychaete, Armandia cirrhosa. Scientific Data, 11 (1), 695, [695]. (doi:10.1038/s41597-024-03557-w).

Record type: Article

Abstract

The morphology and architecture of structures formed by sediment-dwelling invertebrates, such as excavations or burrows, are often assumed to be characteristic of a given species, consistent across a range of environmental conditions, and used to categorise species contributions to ecosystem functioning. However, very few investigations use non-invasive high-resolution techniques capable of determining fine scale variations in burrow form and complexity, or consider whether or not the form of the burrow is context dependent. Here, we provide replicate high-resolution micro-focus computed tomography data for the complete burrow systems of the Opheliid polychaete, Armandia cirrhosa, across a range of salinity and habitat conditions. These data provide reference models which can be used by ecologists investigating intraspecific variation in species traits and organism-sediment interactions and, more generally, by those tasked with pattern and shape recognition of objects that are morphologically highly variable and which adjust their architecture with changing circumstance or context.

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s41597-024-03557-w - Version of Record
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e-pub ahead of print date: 26 June 2024
Published date: 26 June 2024
Additional Information: Publisher Copyright: © The Author(s) 2024.
Keywords: Animals, Ecosystem, Geologic Sediments, Polychaeta/anatomy & histology, Salinity, Tomography, X-Ray Computed, X-Ray Microtomography

Identifiers

Local EPrints ID: 491767
URI: http://eprints.soton.ac.uk/id/eprint/491767
ISSN: 2052-4463
PURE UUID: d1e0e888-abbd-4063-9929-3a63cf0073c6
ORCID for Fernando Alvarez-Borges: ORCID iD orcid.org/0000-0002-6940-9918
ORCID for Martin Solan: ORCID iD orcid.org/0000-0001-9924-5574

Catalogue record

Date deposited: 03 Jul 2024 17:22
Last modified: 16 Jul 2024 02:02

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Contributors

Author: Rebecca M. Howman
Author: Fernando Alvarez-Borges ORCID iD
Author: Martin Solan ORCID iD

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