Effects of temperature and pCO 2 on lipid use and biological parameters of planulae of Pocillopora damicornis

Abstract

Keywords:Ocean acidification Ocean warming Coral larvae Lipid Wax esterThe successful dispersal and recruitment of coral larvae depend on endogenous energy stores that fuel swimming, the search for optimal habitat, and metamorphosis. Ocean acidification and warming threaten to disrupt this critical process within the life cycle of reef-building corals by increasing maintenance costs in the energy budgets of larvae. In this study, lipid utilization and biological parameters of planula larvae of the cauliflower coral Pocillopora damicornis under future ocean conditions were examined using manipulative CO 2 experiments. For the first 24 h following their release, planulae were cultured in seawater controlled to mimic a future ocean scenario (1030 μatm pCO 2 , 30.7°C) as well as present-day, ambient ocean conditions (475 μatm pCO 2 , 28.1°C; confirmed by autonomous sensors deployed at our study site). Abundance of wax ester, triacylglycerol, and phospholipids as well as traits of physiological status were measured before and after incubations. High temperature and pCO 2 conditions did not elicit changes in wax ester composition of larvae. Triacylglycerol content increased with temperature but was not sensitive to pCO 2 . In general, larvae consumed more total lipid and protein in response to conditions of warming but not high pCO 2 , and the day the larvae were released often played a large role in the biological patterns observed. Our results suggest that future ocean warming may influence some organismal properties of coral larvae. High pCO 2 may not have a strong effect on the physiology of this early life history stage.

Host and Symbionts in Pocillopora damicornis Larvae Display Different Transcriptomic Responses to Ocean Acidification and Warming

“…The control (ambient) treatment approximated the present-day environmental conditions for the adult coral (verified by environmental data; Rivest and Hofmann, 2015), while the high treatment represents a level of pCO 2 expected in the surface ocean by year 2100 (RCP8.5 scenario; IPCC, 2013). Two experimental temperatures (T) were crossed with the pCO 2 levels: 28 and 31 • C. The control (ambient) temperature approximated the multi-year average temperature (20-min sampling frequency) for the fringing reefs close to the collection sites for adult P. damicornis (Leichter, 2015).…”

“…Treatment conditions were generated in a Moorea Coral Reef Long-Term Ecological Research program (MCR LTER) facility as described previously (Rivest and Hofmann, 2015), with two aquaria for each combination of pCO 2 and temperature treatment levels (8 aquaria total). Photosynthetically-active radiation (PAR) was provided at 1,800 ± 140 µmol m −2 s −1 on a 13h:11h: light:dark cycle (Sol LED Module, Aquaillumination, 75 W, Ames, IA, USA), an ecologically relevant level for shallow reef environments studied by MCR LTER (Carpenter, 2016).…”

“…To verify and monitor the physical parameters of the pCO 2 × temperature treatments, the carbonate chemistry (pH and total alkalinity), salinity, and temperature of the seawater in the aquaria was measured during the incubations. For a description of the methods, see Rivest and Hofmann (2015). pH and pCO 2 of the treatments were calculated from pH at 25 • C, total alkalinity (A T ), temperature, and salinity using CO 2 calc (Robbins et al, 2010).…”

“…Larval size, protein content, and Symbiodinium density were measured as described in Rivest and Hofmann (2015). Briefly, larval size was quantified through image analysis using ImageJ (Rasband, 1997).…”

“…Effects of pCO 2 and temperature on tank conditions and larval quality response variables were estimated using linear mixedeffect models (nlme package in R; Pinheiro and Bates, 2000) with pCO 2 and temperature treatments as fixed factors and "tank" as a random factor (following Rivest and Hofmann, 2015). Statistical assumptions of normality and homogeneity of variance were met, sometimes following a power-based transformation of the response variable.…”