Dataset: Temperature and pCO2 effects on survivability of 25 genotypes of Acropora cervicornis coral at Mote Marine Laboratory in Nov-Dec 2019

Preliminary and in progressVersion 1 (2022-03-18)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 a dataset-specific abstract ** A full factorial experiment was completed at Mote Marine Laboratory in November and December 2019 to determine the survival probability and photochemical efficiency of 25 unique genotypes of Acropora cervicornis in high temperature, high pCO2 treatment, or the combination of high temperature and high pCO2.

A full factorial experiment was completed to determine the survival probability and photochemical efficiency of 25 unique genotypes of Acropora cervicornis in high temperature, high pCO2 treatment, or the combination of high temperature and high pCO2.

  • High temperature was 33 ± 0.6°C and 463 ± 31 µatm
  • High pCO2 treatment was 29 ± 0.2°C and 798 ± 78 µatm
  • Combination high temperature and high pCO2 was 33 ± 0.8°C and 823 ± 83 µatm 

Prior to exposure, dark-acclimated photochemical efficiency was measured in all fragments (n=600) using a pulse amplitude modulation chlorophyll fluorometer (I-PAM, Walz GmbH, Effeltrich, Germany). Photochemical efficiency factors include:

  • ETR (max)
  • Fv/Fm (max)
  • Initial slope of ETR v. PAR plot

Additionally, the starting color index was gathered for each fragment based on the coral health chart provided by CoralWatch.  The starting colors ranged from D1 for bleached to D5 for full color/healthy. During the exposure period, water quality for each tank was measured daily and color index was assessed daily for all fragments. Water samples were collected in acid-washed amber bottles (125 mL) for carbonate chemistry analysis bi-weekly and fixed with mercuric chloride (60 µL). Water samples were filtered (0.2 microns) prior to analysis on the dissolved inorganic carbon (DIC) machine (Apollo SciTech Analyzer).

As replicates started to show signs of stress (paling activity) and subsequent mortality, the following was recorded:

  • the date of mortality,
  • the time (days) till mortality,
  • the mechanism of mortality (i.e. showed signs of Tissue loss, Bleaching, or both occurring simultaneously)

Each replicate coral was categorized as a binomial rank, classified as either 0, no event/alive, or a 1, event occurred/dead, on each day of the study. As coral fragments reached mortality, they were removed from their treatment tank to limit negative effects on the remaining fragments in the tank. Once LD50 was reached for each genotype in each treatment, the dark-acclimated PAM Chlorophyll Fluorometry outputs (ETR (max), Fv/Fm (max), and initial slope of ETR v. PAR plot) was measured for the remaining fragments of that genotype in that same treatment to derive change of yield over time.

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), 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). Dissolved inorganic carbon (DIC) was analyzed using the Apollo SciTech DIC analyzer model AS-C151. Total Alkalinity (TA) was analyzed using the Metrohm 905 Titrando analyzer. Both DIC and TA were standardized each day with certified reference material (CRM) provided by A.G. Dickson. 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.


Related Datasets

IsSupplementedBy

Dataset: Acer Aquaria water quality PAR
Relationship Description: Water quality measurements of PAR for the full factorial study
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 http://lod.bco-dmo.org/id/dataset/873446
IsSupplementedBy

Dataset: Acer Aquaria water quality pH and DO
Relationship Description: Water quality measurements of pH and dissolved oxygen for the full factorial study
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
IsSupplementedBy

Dataset: Acer Aquaria water quality TA, DIC, and CO2
Relationship Description: Water quality measurements of total alkalinity, DIC, and CO2 for the full factorial study
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
IsSupplementedBy

Dataset: Acer Pilot Study
Relationship Description: Pilot study that preceded the full factorial experiment
Muller, E. M., Petrik, C. (2022) Pilot study with three unique genotypes of Acropora cervicornis coral to determine survival probability after exposure to temperature treatments at Mote Marine Laboratory in September and October 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-03-18 http://lod.bco-dmo.org/id/dataset/871719

Related Publications

Methods

Siebeck, U. E., Marshall, N. J., Klüter, A., & Hoegh-Guldberg, O. (2006). Monitoring coral bleaching using a colour reference card. Coral Reefs, 25(3), 453–460. doi:10.1007/s00338-006-0123-8
Software

R Core Team (2020). R: A language and environment for statistical computing. R v4.0.3. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/