Dataset: Aquaria water quality PAR measurements from full factorial study of Acropora cervicornis at Mote Marine Laboratory in Nov-Dec 2019

This dataset has not been validatedData not availableVersion 1 (2022-04-22)Dataset Type:Other Field ResultsDataset Type:experimental

Principal Investigator: Erinn M. Muller (Mote Marine Laboratory)

Scientist: Chelsea Petrik (Mote Marine Laboratory)

BCO-DMO Data Manager: Dana Stuart Gerlach (Woods Hole Oceanographic Institution)

Project: CAREER: Applying phenotypic variability to identify resilient Acropora cervicornis genotypes in the Florida Keys (Resilient Acerv)

Abstract

** Please write an abstract to include here ** Water quality PAR was monitored as part of a full factorial experiment to determine the survival probability and photochemical efficiency of 25 unique genotypes of Acropora cervicornis in November and December 2019 at Mote Marine Laboratory.

Cite Dataset

Water quality was monitored as part of a full factorial experiment to determine the survival probability and photochemical efficiency of 25 unique genotypes of Acropora cervicornis in November and December 2019.  Coral fragments of A. cervicornis were exposed to high temperatures and/or high pCO2 treatments in flow-through tanks at Mote Marine Laboratory. 

During the exposure period, water quality for each tank was measured daily and color index of the coral fragments was assessed.  Treatment tank water quality was monitored using a YSI Professional Plus (Pro Plus) Multi-parameter handheld with a quarto containing a Pro Series Galvanic Dissolved Oxygen Sensor, a Pro Series pH Sensor (calibrated using 4, 7, and 10 buffers), and a Pro Series temperature and conductivity sensor. PAR was measured using the Licor handheld (Li-COR LI-1500) with an underwater quantum senor (Li-Cor LI-192).  Imaging-PAM Chlorophyll flurometer (Walz GmbH, Effeltrich, Germany) was used to measure photochemical efficiencies and the coral health chart/ color index card was provided by CoralWatch.

Details on additional water quality measurements can be found in these datasets:

Related Datasets

Continues
Dataset: Acer Aquaria water quality pH and DO
Relationship Description: First of three datasets on aquaria water quality from full-factorial study of Acropora cervicornis
Muller, E. M., Petrik, C. (2022) Aquaria water quality pH and dissolved oxygen measurements from full factorial study of Acropora cervicornis at Mote Marine Laboratory in Nov-Dec 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-04-22 http://lod.bco-dmo.org/id/dataset/873433
IsContinuedBy
Dataset: Acer Aquaria water quality TA, DIC, and CO2
Relationship Description: Third of three datasets on aquaria water quality from full-factorial study of Acropora cervicornis
Muller, E. M., Petrik, C. (2022) Aquaria water quality total alkalinity, DIC, and CO2 measurements from full factorial study of Acropora cervicornis at Mote Marine Laboratory in Nov-Dec 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-04-22 http://lod.bco-dmo.org/id/dataset/873459
IsSupplementTo
Dataset: Acer 25 genotype full factorial study
Relationship Description: Full-factorial study to which the aquaria water quality data relates
Muller, E. M., Petrik, C. (2022) Temperature and pCO2 effects on survivability of 25 genotypes of Acropora cervicornis coral at Mote Marine Laboratory in Nov-Dec 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-03-18 http://lod.bco-dmo.org/id/dataset/871765

Related Publications

No Related Publications

Muller, E. M., Petrik, C. (2022) Aquaria water quality PAR measurements from full factorial study of Acropora cervicornis at Mote Marine Laboratory in Nov-Dec 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-04-22 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/873446 [access date]

Terms of Use

This dataset is licensed under Creative Commons Attribution 4.0.


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