Corals are a foundational species of an ecosystem upon which hundreds of thousands of people depend for food, coastal protection, and jobs (Brander et al., 2007; Ferrario et al., 2014; Fisher et al., 2015). Some in the coral science community argue that innovative restoration interventions are needed in response to coral reef decline due to climate change (Randall et al., 2020; van Oppen et al., 2015, 2017). Although there are other environmental factors that stress corals, the main stressor driving coral reef degradation is rising ocean temperatures due to climate change (Hutchings et al., 2019). Rising ocean temperatures have already resulted in an increase in global and local bleaching events (Hutchings et al., 2019). During a bleaching event, corals lose their symbiotic dinoflagellate partners which give them 95-99% of their energy thus increasing risk of coral mortality (Hoegh-Guldberg, 1999; Muscatine et al., 1981). Most coral populations are projected to experience temperatures above their current bleaching thresholds annually by 2050 (van Hooidonk et al., 2013; van Hooidonk et al., 2014). Adaptation to higher temperatures is therefore necessary if corals are to persist in a warming future. While restoration initiatives are useless if we do not aggressively mitigate and ultimately stop climate change, it is increasingly likely that we will need conservation and restoration initiatives to maintain coral reefs and their ecological and economic functions during climate change mitigation.

For the duration of this post, restoration efforts are those initiatives that plant adult coral fragments, coral larvae, or juvenile corals to degraded reefs to increase the number of corals on that degraded reef over time rebuilding the reef structure. There are two methods of restoration that are in development for coral: selective breeding and assisted gene flow (van Oppen et al., 2017). Selective breeding is the breeding of corals with a desired trait to produce offspring with that desired trait and plant those offspring on the reef (van Oppen et al., 2017). The process of relocating larvae or many coral juveniles from a heat tolerant population to a restoration site is called Assisted Gene Flow (AGF) (Randall et al., 2020). A key knowledge gap needed to use these methods is an understanding of the cross generational responses to heat stress and local stressors in coral populations. Quantifying adaptive capacity of coral populations or the direction and speed of trait evolution will be important to implement and evaluate the effectiveness of these restoration interventions. I would argue that genomics and quantitative genetics can play a role in selecting reefs and coral populations for these programs. Recent work from my Ph.D. thesis shows the potential for using genomics and quantitative genetics to find genetic markers of a trait and estimate heritability of a trait and then estimate the selection on that trait. These methods can assess the adaptive capacity of coral populations.

My Ph.D. thesis study quantified the heritability and genetic variation associated with heat tolerance in Platygyra daedalea from the Great Barrier Reef (GBR). We tracked the survival of replicate quantitative genetic crosses (or families) of coral larvae from six parents in a heat stress selection experiment. We also identified allelic shifts in heat-selected survivors versus paired, non-selected controls of the same coral crosses.

In my thesis study, I detected a total of 1,069 genomic markers associated with heat tolerance. An overlap of 148 unique markers shared between experimental crosses indicates that specific genomic regions are responsible for heat tolerance of P. daedalea and some of these markers fall in coding regions. The overlap of the genetic markers indicates that having these markers may indicate a heat-tolerant coral. While the role of these markers in heat tolerance mechanism is unknown, another study mined markers from similar studies and using lab experiments and population surveys found that a specific single nucleotide polymorphism (SNP) in a marker did predict that the coral was more heat tolerant (Jin et al., 2016). Furthermore the frequencies of this marker ranged from 0.48 to 0.92 in different populations (Jin et al., 2016). This shows that markers can identify populations that are more heat-tolerant than others. Adult coral fragments or larvae could be collected from the coral populations with a high frequency of this allele and used in restoration.

While genomic markers can play a role in selecting heat-tolerant populations, they do not tell us about the genetic variation contributing to a trait or the direction and speed of selection on a given trait. However, quantitative genetics methods can. If variation in a fitness-related phenotype has a genetic basis and is heritable and not otherwise constrained, then selection can act to further propagate it within populations (Charmantier & Garant, 2005). Narrow sense heritability (h2) describes the total phenotypic variance (VP) in a trait that can be attributed to parental or additive genetics (VA) and is used to determine the genetic contribution to traits such as heat tolerance (Falconer & Mackay, 1996; Lynch & Walsh, 1998).

h2 = VA/VP

In my thesis study, we estimated narrow sense heritability of survival in a heat stress to be 0.66. This high value indicates that heat tolerance is highly heritable and there is substantial genetic variation within the population to support adaptation to warmer temperatures. Estimates of h2 are essential for calculating selection differentials and using the breeder’s equation to predict the number surviving (R) in a population in the next generation given the same selection (S) (Falconer & Mackay, 1996; Lynch & Walsh, 1998).

R = h2 S

Assuming truncation selection, where all individuals with trait values above a threshold contribute offspring to the next generation, selection differentials are equal to the difference in mean trait values between the selected population and the original population (Falconer & Mackay, 1996; Lynch & Walsh, 1998) expressed as standard deviations of the population mean. If the selection differential equals one standard deviation, all parents with traits one standard deviation above the population mean contribute to the next generation. Based on the distribution of cumulative survival probabilities in heat stress from my experiment (0.57 ± 0.18) and the h2 of variation in heat tolerance (0.66), the Breeder’s Equation predicts a response to selection of 0.12. We would expect that if larvae of the next generation after selection were subjected to the same heat stress treatment, the average mortality would be 0.48 (0.59 - 0.12), a 20% reduction in overall mortality. If instead of the high h2 estimated in our study (0.66), we modeled the responses to selection using a low h2 value of 0.1, we would predict only a 3% reduction in mortality in the following generation. While the estimates above are underpinned by too many assumptions to predict responses in natural populations of corals, the comparison highlights how empirical estimations of h2 can be used to predict adaptive responses. However, understanding the adaptive potential of a population should be an important part of determining if a population or their offspring are good candidates for use in restoration programs.

These findings suggest that this P. daedalea population from the GBR has the genetic prerequisites for adaptation to increasing temperatures. It also provides a framework to screen for variation within and across populations. Using genomics and quantitative genetics can help us identify populations that are good candidates for restoration work. While my work only investigated the heat tolerance trait, this framework can be used for other traits. Perhaps there is a restoration site that also has high nutrient input because it is close to shore or another site has high recurrence of disease events. These traits can also be assessed using the same framework to identify candidates for restoration.


Holland Elder is a Postdoctoral Research Scholar at University of Southern California in the Cnidarian Evolutionary Ecology Lab with the direction of Dr. Carly Kenkel. Dr. Elder studies coral adaptation. The study this refers to will be on bioRxiv on October 15th 2020.

Works Cited

Brander, L. M., Van Beukering, P., & Cesar, H. S. J. (2007). The recreational value of coral reefs: A meta-analysis. Ecological Economics, 63(1), 209–218.

Charmantier, A., & Garant, D. (2005). Environmental quality and evolutionary potential : lessons from wild populations. Proceedings of the Royal Society, 272, 1415–1425.

Falconer, D. S., & Mackay, T. F. C. (1996). Introduction to Quantitative Genetics.

Ferrario, F., Beck, M. W., Storlazzi, C. D., Micheli, F., Shepard, C. C., & Airoldi, L. (2014). The effectiveness of coral reefs for coastal hazard risk reduction and adaptation. Nature Communications, 5(May), 1–9.

Fisher, R., O’Leary, R. A., Low-Choy, S., Mengersen, K., Knowlton, N., Brainard, R. E., & Caley, M. J. (2015). Species Richness on Coral Reefs and the Pursuit of Convergent Global Estimates. Current Biology, 25(4), 500–505.

Hoegh-Guldberg, O. (1999). Climate change, coral bleaching and the future of the world’s coral reefs. Marine and Freshwater Research, 50(8), 839–866.

Hutchings, P., Kingsford, M., & Hoegh-Guldberg, O. (2019). The Great Barrier Reef: Biology, Environment, and Management. Csiro Publishing.

Jin, Y. K., Lundgren, P., Lutz, A., Raina, J., Howells, E. J., Paley, A. S., Willis, B. L., & Oppen, M. J. H. Van. (2016). Genetic markers for antioxidant capacity in a reef-building coral. May.

Lynch, M., & Walsh, B. (1998). Genetics and Analysis of Quantitative Traits.

Muscatine, L., R. McCloskey, L., & E. Marian, R. (1981). Estimating the daily contribution of carbon from zooxanthellae to coral animal respiration. Limnology and Oceanography, 26(4), 601–611.

Randall, C. J., Negri, A. P., Quigley, K. M., Foster, T., Ricardo, G. F., Webster, N. S., Bay, L. K., Harrison, P. L., Babcock, R. C., & Heyward, A. J. (2020). Sexual production of corals for reef restoration in the Anthropocene. Marine Ecology Progress Series, 635(February), 203–232.

van Hooidonk, R., Maynard, J. A., & Planes, S. (2013). Temporary refugia for coral reefs in a warming world. Nature Climate Change, 3(5), 508–511.

van Hooidonk, Ruben, Maynard, J. A., Manzello, D., & Planes, S. (2014). Opposite latitudinal gradients in projected ocean acidification and bleaching impacts on coral reefs. Global Change Biology, 20(1), 103–112.

van Oppen, M. J. H., Gates, R. D., Blackall, L. L., Cantin, N., Chakravarti, L. J., Chan, W., Cormick, C., Crean, A., Damjanovic, K., Epstein, H., Harrison, P. L., Jones, T. A., Miller, M., Pears, R. J., Peplow, L. M., Raftos, D. A., Schaffelke, B., Stewart, K., Torda, G., … Putnam, H. M. (2017). Shifting paradigms in restoration of the world ’ s coral reefs. Global Change Biology, 1–12.

van Oppen, M. J. H., Oliver, J. K., Putnam, H. M., & Gates, R. D. (2015). Building coral reef resilience through assisted evolution. Proceedings of the National Academy of Sciences, 112(8), 2307–2313.