Title
Spatio-Temporal Symbiont Mosaics Influence on SCTLD Susceptibility in Orbicella faveolata
Start
2-25-2022 2:30 PM
End
2-25-2022 2:45 PM
Type of Presentation
Oral Presentation
Abstract
Stony Coral Tissue Loss Disease (SCTLD) has decimated vital reef-building corals along Florida’s Coral Reef over the last 7 years. Populations of Florida’s mountainous star coral (Orbicella faveolata) have been among the top priority corals for receiving direct intervention efforts to stop the spread of SCTLD. As a result, there have been notable differences in the susceptibility of individual Orbicella faveolata colonies. A characteristic of O. faveolata is their ability to harbor multiple genetically distinct species of agal symbionts (zooxanthellae), in the family Symbiodiniaceae, creating a mosaic of varying species. These algal associations have been observed to shift over time based on environmental factors such as light and temperature. A recent study at the University of Miami provided significant evidence of disease susceptibility based on the dominant symbiont type. The data established the following ranking from most susceptible to least susceptible: Breviolum >> Cladocopium > Durusdinium >> Symbiodinium.
The goal of this study is to assess and map seasonal spatio-temporal variation of the in-situ Orbicella faveolata Symbiodiniaceae communities in a select number of large colonies known to have variable communities. Three-dimensional models of five large O. faveolata colonies that have exhibited a wide variety of Symbiodiniaceae were created using structure from motion software. Repeatable sample grids will be established on each colony where small tissue biopsies will be collected at four time points throughout the year. Biopsies will be analyzed to determine the relative abundance of zooxanthellae communities for each timepoint. Results will be mapped via a spatial grid in GIS and spatial statistics will be performed to identify patterns. Resulting layers will be draped on the three-dimensional model to illustrate the spatio-temporal patterns. In addition, previous lesion locations will be identified to determine if specific zooxanthellae communities relate to lesion locations.
This innovative and novel approach will provide a greater understanding of zooxanthellae community spatial and temporal variability and possibly elucidate their associations with SCLTD disease lesion occurrence.
Spatio-Temporal Symbiont Mosaics Influence on SCTLD Susceptibility in Orbicella faveolata
Stony Coral Tissue Loss Disease (SCTLD) has decimated vital reef-building corals along Florida’s Coral Reef over the last 7 years. Populations of Florida’s mountainous star coral (Orbicella faveolata) have been among the top priority corals for receiving direct intervention efforts to stop the spread of SCTLD. As a result, there have been notable differences in the susceptibility of individual Orbicella faveolata colonies. A characteristic of O. faveolata is their ability to harbor multiple genetically distinct species of agal symbionts (zooxanthellae), in the family Symbiodiniaceae, creating a mosaic of varying species. These algal associations have been observed to shift over time based on environmental factors such as light and temperature. A recent study at the University of Miami provided significant evidence of disease susceptibility based on the dominant symbiont type. The data established the following ranking from most susceptible to least susceptible: Breviolum >> Cladocopium > Durusdinium >> Symbiodinium.
The goal of this study is to assess and map seasonal spatio-temporal variation of the in-situ Orbicella faveolata Symbiodiniaceae communities in a select number of large colonies known to have variable communities. Three-dimensional models of five large O. faveolata colonies that have exhibited a wide variety of Symbiodiniaceae were created using structure from motion software. Repeatable sample grids will be established on each colony where small tissue biopsies will be collected at four time points throughout the year. Biopsies will be analyzed to determine the relative abundance of zooxanthellae communities for each timepoint. Results will be mapped via a spatial grid in GIS and spatial statistics will be performed to identify patterns. Resulting layers will be draped on the three-dimensional model to illustrate the spatio-temporal patterns. In addition, previous lesion locations will be identified to determine if specific zooxanthellae communities relate to lesion locations.
This innovative and novel approach will provide a greater understanding of zooxanthellae community spatial and temporal variability and possibly elucidate their associations with SCLTD disease lesion occurrence.