Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
• Related Datasets
• Parameters
• Instruments
• Project Information
• Funding

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), Pro Series temperature and conductivity sensor. The coral health chart/ color index card was provided by CoralWatch.

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

• Acer Aquaria water quality PAR, https://www.bco-dmo.org/dataset/873446
• Acer Aquaria water quality TA, DIC, and CO2, https://www.bco-dmo.org/dataset/873459

NSF Award Abstract:
Caribbean staghorn coral was one of the most common corals within reefs of the Florida Keys several decades ago. Over the last 40 years disease, bleaching, overfishing and habitat degradation caused a 95% reduction of the population. Staghorn coral is now listed as threatened under the U.S. Endangered Species Act of 1973. Within the past few years, millions of dollars have been invested for the purpose of restoring the population of staghorn coral within Florida and the U.S. Virgin Islands. Significant effort has been placed on maintaining and propagating corals of known genotypes within coral nurseries for the purpose of outplanting. However, little is known about the individual genotypes that are currently being outplanted from nurseries onto coral reefs. Are the genotypes being used for outplanting resilient enough to survive the three major stressors affecting the population in the Florida Keys: disease, high water temperatures, and ocean acidification? The research within the present study will be the first step in answering this critically important question. The funded project will additionally develop a research-based afterschool program with K-12 students in the Florida Keys and U.S. Virgin Islands that emphasizes an inquiry-based curriculum, STEM research activities, and peer-to-peer mentoring. The information from the present study will help scientists predict the likelihood of species persistence within the lower Florida Keys under future climate-change and ocean-acidification scenarios. Results of this research will also help guide restoration efforts throughout Florida and the Caribbean, and lead to more informative, science-based restoration activities.

Acropora cervicornis dominated shallow-water reefs within the Florida Keys for at least the last half a million years, but the population has recently declined due to multiple stressors. Understanding the current population level of resilience to three major threats - disease outbreaks, high water temperatures, and ocean acidification conditions - is critical for the preservation of this threatened species. Results from the present study will answer the primary research question: will representative genotypes from the lower Florida Keys provide enough phenotypic variation for this threatened species to survive in the future? The present proposal will couple controlled laboratory challenge experiments with field data and modeling applications, and collaborate with local educators to fulfill five objectives: 1) identify A. cervicornis genotypes resistant to disease, 2) identify A. cervicornis genotypes resilient to high water temperature and ocean acidification conditions, 3) quantify how high water temperature and ocean acidification conditions impact disease dynamics on A. cervicornis; 4) determine tradeoffs in life-history traits because of resilience factors; and 5) apply a trait-based model, which will predict genotypic structure of a population under different environmental scenarios.