Dataset: Field measurements of periostracum cover of mussels (Mytilus californianus) from focal population at Marshall Gulch Beach, CA in July and August 2022

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.935484.1Version 1 (2024-12-26)Dataset Type:Other Field Results

Principal Investigator: Brian Gaylord (University of California - Davis: Bodega Marine Laboratory)

Student: Alisha Saley (University of California - Davis: Bodega Marine Laboratory)

BCO-DMO Data Manager: Lynne M. Merchant (Woods Hole Oceanographic Institution)


Project: Invertebrate calcification and behavior in seawater of decoupled carbonate chemistry (OA decoupling)


Abstract

These data build off of experimental incubations described in Dataset 1 and 2. To contextualize laboratory incubations, we measured periostracum cover of live California mussels from multiple microhabitats (relative tidal height and degree of sun exposure) in our focal sample population. This dataset represents periostracum cover measurements of California Mussels, Mytilus californianus, conducted at Marshall Gulch Beach, CA in July and August 2022. Dataset 1: Lab incubations of mussels (Myti...

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To provide ecological context for the laboratory dissolution experiments, we also measured the percent cover of periostracum of living California Mytilus californianus mussels in the field, focusing on mussels inhabiting different microhabitats within the intertidal zone. We sampled mussels across two tidal heights and three levels of sun exposure on 17 July and 18 August 2022 from the same population (Marshall Gulch Beach, California) where we had collected mussels for the laboratory trials (see the related BCO-DMO datasets). We sampled from the topmost layer of mussels within a 20 cm x 20 cm quadrat positioned within the center of each of 8 mussel beds at each tidal height (characterized as ‘high’ or low’, -0.3 – +0 m sea level height (SLH) and  +0.3 - +1 m SLH), haphazardly choosing the first 20 adult individuals within a pre-selected size range (n = 113 mussels total, 54 mm + 4 mm SD). We characterized sun exposure based on the cardinal direction of the mussel bed orientation, which included mussels oriented 200° – 240° SW (termed ‘intense’), 30° – 70° NE (termed ‘average’), and 300° – 340° NW (termed ‘shade’). We photographed both valves of each mussel, ensuring a scale bar was visible in the field of view for use in ImageJ, and averaged the coverage of periostracum across the two valves as the metric of percent cover for a given individual.


Related Datasets

IsRelatedTo

Dataset: Mussel lab incubations: periostracum and pH (effect on shell dissolution)
Relationship Description: Mussels from the same population as Dataset 2 & Dataset 3 examining the influence of periostracum cover and pH on external shell dissolution
Saley, A., Gaylord, B. (2024) Lab incubations of mussels (Mytilus californianus) examining the influence of periostracum cover and pH on external shell dissolution at Marshall Gulch Beach, CA from August 2021 to March 2022. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-12-28 doi:10.26008/1912/bco-dmo.935476.1
IsRelatedTo

Dataset: Mussel lab incubations: simulated periostracum abrasion (effect on shell dissolution)
Relationship Description: Mussels from the same population as Dataset 1 and Dataset 3 examining the influence of simulated abrasion of periostracum on external shell dissolution
Saley, A., Gaylord, B. (2024) Lab incubations of mussels (Mytilus californianus) examining the influence of simulated abrasion of periostracum on external shell dissolution at Marshall Gulch Beach, CA from August 2021 to March 2022. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-12-28 doi:10.26008/1912/bco-dmo.935480.1

Related Publications

Software

R Core Team (2023). R: A language and environment for statistical computing. R v4.3.1 (2023-06-01). R Foundation for Statistical Computing, Vienna, Austria. URL https://www.r-project.org/
Software

Schneider, C. A., Rasband, W. S., & Eliceiri, K. W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nature Methods, 9(7), 671–675. https://doi.org/10.1038/nmeth.2089