| Literature DB >> 26157627 |
Jahangir Vajed Samiei1, Abolfazl Saleh1, Ali Mehdinia1, Arash Shirvani1, Mohsen Kayal2.
Abstract
With on-going climate change, coral susceptibility to thermal stress constitutes a central concern in reefconservation. In the Persian Gulf, coral reefs are confronted with a high seasonal variability in water temperature, and both hot and cold extremes have been associated with episodes of coral bleaching and mortality. Using physiological performance as a measure of coral health, we investigated the thermal susceptibility of the common acroporid, Acropora downingi, near Hengam Island where the temperature oscillates seasonally in the range 20.2-34.2 °C. In a series of two short-term experiments comparing coral response in summer versus winter conditions, we exposed corals during each season (1) to the corresponding seasonal average and extreme temperature levels in a static thermal environment, and (2) to a progressive temperature deviation from the annual mean toward the corresponding extreme seasonal value and beyond in a dynamic thermal environment. We monitored four indictors of coral physiological performance: net photosynthesis (Pn), dark respiration (R), autotrophic capability (Pn/R), and survival. Corals exposed to warming during summer showed a decrease in net photosynthesis and ultimately died, while corals exposed to cooling during winter were not affected in their photosynthetic performance and survival. Coral autotrophic capability Pn/R was lower at the warmer thermal level within eachseason, and during summer compared to winter. Corals exposed to the maximum temperature of summer displayed Pn/R < 1, inferring that photosynthetic performance could not support basal metabolic needs under this environment. Our results suggest that the autotrophic performance of the Persian Gulf A. downingi is sensitive to the extreme temperatures endured in summer, and therefore its populations may be impacted by future increases in water temperature.Entities:
Keywords: Coral reefs; Global warming; Seasonal performance; Thermal tolerance
Year: 2015 PMID: 26157627 PMCID: PMC4493696 DOI: 10.7717/peerj.1062
Source DB: PubMed Journal: PeerJ ISSN: 2167-8359 Impact factor: 2.984
Figure 1The experimental set up.
Seawater collected from the study site was pumped from the source-water tank through the system at a constant rate of about 0.5 l. min−1. Oxygen concentration (mg. l−1) and pH were recorded upstream and downstream the coral chambers every 5 min. 6,500 lux light (i.e. about 120 µ mol. m−2 .s−1) was provided by an artificial sunlight lamp (Dymax Rex-2). Water temperature was controlled by heaters (Lauda E100, with accuracy of ± 0.1 ° C) and a chiller (Aqua medic Titan 1500, with accuracy of ±0.5 °C). Net photosynthesis or respiration rate of corals was calculated in light and dark conditions as the difference in O2 concentration between the upstream and downstream chamber multiplied by the flow rate. The measured metabolic fluxes were not affected by gas exchange with the atmosphere since the measurement and sample chambers were in a closed circuit and water was exposed to air only in the source tank.
Figure 2Metabolic performance of corals in constant seasonal temperature levels.
Net photosynthesis in light Pn (A), respiration in darkness R (B) and autotrophic capability Pn/R ratio (C) of corals exposed to a range of temperatures as observed on Hengam reefs. The mean ± SE values are indicated on graphs. Letters on top indicate statistically different groups within each season in (A) and (B), and among the four thermal environments in (C). The thermal levels correspond to the winter minimum of 20.2 °C, winter average of 23 °C, summer average of 32 °C, and summer maximum of 34.2 °C.
Figure 3Net photosynthesis of corals exposed to gradual temperature deviations.
Coral net photosynthesis Pn as a function of positive (black) versus negative (grey) temperature deviation |dT| from the annual mean value of 27.5 °C. Plot (A) shows raw data as recorded for each of the n = 5 replicate coral fragments within each treatment. The corresponding temperature ranges are indicated in italic on top of the plot. Plot (B) shows the fit from the Generalized Linear Mixed-effect Model (GLMM) in the linearized dimension (x = [dT]2). The equations of the linear regressions are provided in the form y = slope (±SE) x + intercept (±SE), and significant equation parameters are printed in bold character. Note the significant negative slope estimated for the summer heating treatment (p < 0.001) while the slope is not significantly different from zero in the winter cooling treatment (p = 0.171). Plot (C) illustrates results from the semi-parametric contrast curve (based on GLMM and penalized splines) identifying the domain of significant difference between the profiles obtained from the two treatments: the profiles are significantly different when the contrast curve ±CI (black-line ± shading) does not overlap with the y = 0 line (here for [dT]2 > 1. 6 ° C or dT = 1.3 °C; see vertical line in zoom insert). Black and grey dashed lines indicate the levels of the peak temperatures observed at the study site in summer (34.2 °C) and winter (20.2 °C), respectively.