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Dryad

Data from: Heritable variation and lack of tradeoffs suggest adaptive capacity in Acropora cervicornis despite negative synergism under climate change scenarios

Cite this dataset

Muller, Erinn et al. (2021). Data from: Heritable variation and lack of tradeoffs suggest adaptive capacity in Acropora cervicornis despite negative synergism under climate change scenarios [Dataset]. Dryad. https://doi.org/10.5061/dryad.mcvdnck1w

Abstract

Knowledge of multi-stressor interactions and the potential for trade-offs among tolerance traits is essential for developing intervention strategies for the conservation and restoration of reef ecosystems in a changing climate. Thermal extremes and acidification are two major co-occurring stresses predicted to limit the recovery of vital Caribbean reef-building corals. Here we conducted an aquaria-based experiment to quantify the effects of increased water temperatures and pCO2 individually and in concert on 12 genotypes of the endangered branching coral, Acropora cervicornis, currently being reared and outplanted for large-scale coral restoration. Quantification of 11 host, symbiont, and holobiont traits throughout the 2-month long experiment showed several synergistic negative effects, where the combined stress treatment often caused greater reduction in physiological function than the individual stressors alone. However, we found significant genetic variation for most traits and positive trait correlations among treatments indicating an apparent lack of tradeoffs, suggesting that adaptive evolution will not be constrained. Our results suggest that it may be possible to incorporate climate-resistant coral genotypes into restoration and selective breeding programs, potentially accelerating adaptation.  

Methods

This data comes from an aquaria-based experiment.

First dataset ("Phenotype_metrics_measured.csv") -phenotype metrics measured throughout the study: skeletal growth, calcification (light and dark), P:R ratio, symbiont density, total chlorphyll, protein concentration, phenoloxidase (PO), prophenoloxidase (PPO), peroxidase (POX), change in maximal quantum yield of PS II (Δ Yield) and the change in maximum electron transport rate (ΔETRm). These data were collected using buoyant weight, respirometry, the alkalinity anomaly method, and PAM fluorometry.

Second dataset (Water quality_alkalinity.csv") - Water quality and alkalinity metrics collected throughout the study.

Water quality measurements were collected daily: temperature, salinity, pH, dissolved oxygen (DO).

PAR readings were recorded at noon daily. PAR readings reported in the manuscript were averaged across all treatments over the course of experiment, since the measurements were not stratified by treatment (only randomly within the system).

Alkalinity metrics: samples were collected weekly in duplicate from three concurrent aquariums per treatment for total alkalinity (TA) and spectrophotometric pHT analysis. Parameters of the carbonate system (pCO2, CO32-, HCO3-, and Ωar) for each experimental treatment was calculated in CO2SYS v2.2 (Pierrot et al. 2006)  from the measured parameters pHT, TA, temperature, and salinity (Table 1). CO2SYS was run using the K1K2 apparent equilibrium constants from Mehrbach (1973) and refit by Dickson and Millero (1987), HSO4- dissociation constants were taken from Lee et al. (2010) and Dickson (1990), and pH was calculated on the total scale.

Usage notes

Please see the readme file for more details on the two data files.