Dataset: Laboratory Skeletonema Grethae Disaggregation
View Data: Data not available yet
Data Citation:
Rau, M. (2024) Data from laboratory disaggregation experiments with Skeletonema grethae using a disaggregation roller tank that exposed aggregates to time-varying laminar shear in 2021. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-04-15 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/924936 [access date]
Terms of Use
This dataset is licensed under Creative Commons Attribution 4.0.
If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.
Temporal Extent: 2021-09-17 - 2021-10-14
Project:
Principal Investigator:
Matthew Rau (Pennsylvania State University, PSU)
Student:
Yixuan Song (Pennsylvania State University, PSU)
BCO-DMO Data Manager:
Amber D. York (Woods Hole Oceanographic Institution, WHOI BCO-DMO)
Version:
1
Version Date:
2024-04-15
Restricted:
No
Validated:
No
Current State:
Data not available
Data from laboratory disaggregation experiments with Skeletonema grethae using a disaggregation roller tank that exposed aggregates to time-varying laminar shear in 2021
Abstract:
These data include particle aggregate size, morphology, and fragmentation statistics obtained from laboratory experiments using a disaggregation roller tank that exposed aggregates to time-varying laminar shear. Particle aggregates were formed by rolling sterile cultures of Skeletonema grethae at a slow constant rate. Fragmentation was induced by oscillating the roller tank motion (following published methods) to create time-varying laminar shear with values relevant to turbulent shear in the open ocean. Aggregate sizes and morphologies were tracked in time using a bright side-illumination, a high-speed camera, and a particle tracking algorithm. Aggregates were tracked until they either left the camera's field of view or fragmented into two pieces. These data include capture of 75 fragmentation events. The fragmented aggregates ranged from 1 mm to 5 mm in major axis length, though deformed substantially prior to fragmentation due to shear exposure. Laboratory experiments were conducted at Penn State University in 2021.