Paper Review

Journal of Experimental Marine Biology and Ecology 534 (2021) 151477

Available online 6 November 2020 0022-0981/© 2020 Elsevier B.V. All rights reserved.

Coral-macroalgal competition under ocean warming and acidification

Lena Rölfer a, b, *, 1, Hauke Reuter a, b, Sebastian C.A. Ferse a, b, Andreas Kubicek c, Sophie Dove c, Ove Hoegh-Guldberg c, Dorothea Bender-Champ c

a Leibniz Centre for Tropical Marine Research (ZMT), Fahrenheitstraße 6, D-28359 Bremen, Germany b Faculty of Biology & Chemistry (FB2), University of Bremen, D-28359 Bremen, Germany c Global Change Institute and School for Biological Sciences, University of Queensland, 4072 Brisbane, Australia

A R T I C L E I N F O

Keywords: Coral-macroalgal interaction Ocean acidification Representative concentration pathways Porites lobata Chlorodesmis fastigiata Climate change

A B S T R A C T

Competition between corals and macroalgae is frequently observed on reefs with the outcome of these in- teractions affecting the relative abundance of reef organisms and therefore reef health. Anthropogenic activities have resulted in increased atmospheric CO2 levels and a subsequent rise in ocean temperatures. In addition to increasing water temperature, elevated CO2 levels are leading to a decrease in oceanic pH (ocean acidification). These two changes have the potential to alter ecological processes within the oceans, including the outcome of competitive coral-macroalgal interactions. In our study, we explored the combined effect of temperature increase and ocean acidification on the competition between the coral Porites lobata and on the Great Barrier Reef abundant macroalga Chlorodesmis fastigiata. A temperature increase of +1 ◦C above present temperatures and CO2 increase of +85 ppm were used to simulate a low end emission scenario for the mid- to late 21st century, according to the Representative Concentration Pathway 2.6 (RCP2.6). Our results revealed that the net photo- synthesis of P. lobata decreased when it was in contact with C. fastigiata under ambient conditions, and that dark respiration increased under RCP2.6 conditions. The Photosynthesis to Respiration (P:R) ratios of corals as they interacted with macroalgal competitors were not significantly different between scenarios. Dark calcification rates of corals under RCP2.6 conditions, however, were negative and significantly decreased compared to ambient conditions. Light calcification rates were negatively affected by the interaction of macroalgal contact in the RCP2.6 scenario, compared to algal mimics and to coral under ambient conditions. Chlorophyll a, and protein content increased in the RCP2.6 scenario, but were not influenced by contact with the macroalga. We conclude that the coral host was negatively affected by RCP2.6 conditions, whereas the productivity of its symbionts (zooxanthellae) was enhanced. While a negative effect of the macroalga (C. fastigiata) on the coral (P. lobata) was observed for the P:R ratio under control conditions, it was not enhanced under RCP2.6 conditions.

1. Introduction

Macroalgae are important organisms on coral reefs, contributing significantly to primary production (Gattuso et al., 1998) and nitrogen fixation (Heil et al., 2004). On a healthy reef, corals generally pre- dominate the benthic community and are generally competitively su- perior to macroalgae (Chadwick and Morrow, 2011). However, in recent years reef ecosystems experienced dramatic declines in coral cover due to anthropogenic impacts such as global climate change, ocean acidifi- cation, eutrophication, sedimentation and overfishing as well as disease

outbreaks (Hoegh-Guldberg et al., 2007; Hughes et al., 2010, 2007). Between 2014 and 2017 a 36 month global heatwave led to multiple bleaching events on coral reefs and on the Great Barrier Reef to a loss of shallow water corals of 22–30% with even 50% in the northern parts (Hughes et al., 2017; Eakin et al., 2018).

The free space on the reef created by high coral mortality can be taken up by other sessile benthic organisms such as macroalgae, cor- allimorpharians and sponges (Aronson and Precht, 2001; Norström et al., 2009). Competition between benthic, sessile organisms is one of the main factors shaping the community composition on reefs (Dayton,

Abbreviations: RCP2.6, Representative Concentration Pathway 2.6; Pnet, net oxygen production (net photosynthesis); Rdark, dark respiration rate; P:R, Photo- synthesis per Respiration ratio.

* Corresponding author at: Leibniz Centre for Tropical Marine Research (ZMT), Fahrenheitstraße 6, D-28359 Bremen, Germany. E-mail address: [email protected] (L. Rölfer).

1 Present address: Climate Service Center Germany (GERICS), Helmholtz-Zentrum Geesthacht, Fischertwiete 1, D-20095 Hamburg, Germany.

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https://doi.org/10.1016/j.jembe.2020.151477 Received 4 June 2020; Received in revised form 2 October 2020; Accepted 29 October 2020

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1971). Macroalgae are competing for space in different ways, including physical abrasion of coral tissue (Coyer et al., 1993), shading (Hughes, 1994) or allelochemicals (i.e. harmful chemicals) to induce bleaching or death in corals (Longo and Hay, 2017; McCook, 2001; Nugues et al., 2004). Furthermore, macroalgal exudates can lead to microbe-induced mortality of adjacent corals (Clements et al., 2020; Smith et al., 2006). Corals that are weakened by anthropogenic impacts are not able to invest energy in spatial competition as their energy is needed for various maintenance functions (Diaz-Pulido et al., 2011; Foster et al., 2008; Rinkevich and Loya, 1985). Additionally, changes in the reef environ- ment such as high nutrient availability (eutrophication) and overfishing of herbivores can result in enhanced growth rates of macroalgae as well as their release from predation pressure (Hughes et al., 2007, 1987; Shenkar et al., 2008). As a consequence, macroalgae become the stronger competitor and proliferate over the reef environment (Done, 1992; McCook, 1999), which may lead to a phase shift from a coral to an algal dominated state (Anton et al., 2020; Done, 1992; Hughes et al., 2010; Norström et al., 2009).

Ocean warming and acidification, combined with disturbances such as overfishing and nutrient enrichment, have a high potential to also decrease resilience of coral reefs (Anthony et al., 2011; Dove et al., 2013) and may change the outcome of competition (Chadwick and Morrow, 2011; Diaz-Pulido et al., 2011; Hoegh-Guldberg et al., 2007). Thus, on many reefs worldwide macroalgae are the winners in the competition for space on coral reefs (Gardner, 2003; McCook, 1999; Mumby et al., 2013; Scheffer et al., 2001).

Corals are particularly vulnerable to ocean acidification (Pörtner et al., 2019), resulting in a significant reduction in calcification rate through a decreased aragonite saturation, which controls coral calcifi- cation (Doney et al., 2009; Kleypas and Langdon, 2006; Langdon, 2002). With an increase of dissolved CO2, however, productivity may be enhanced, as CO2 is often a limiting factor in the marine realm. Enhanced productivity under elevated CO2 levels has been shown for both, macroalgae (Gao et al., 1993, 1991; Wu et al., 2008) and zooxanthellae (Al-Moghrabi et al., 1996; Leggat et al., 1999).

Under current conditions, corals are already at their thermal limits, and with temperatures continuing to rise, corals will be pushed more frequently beyond their thermal tolerance threshold, as oceans warm (Hoegh-Guldberg, 1999; Hoegh-Guldberg et al., 2007; Anton et al., 2020). This was last observed in the longest and most severe coral bleaching event 2014–2017, when global monthly sea surface temper- ature maxima increased to 30–31 ◦C (Lough et al., 2018), which led to a mass mortality of shallow water corals (Heron et al., 2016; Hughes et al., 2017).

Investigations about coral-algal interactions have strongly increased during the last decade, monitoring interactions both in situ and in tank experiments (Bender et al., 2012; Birrell et al., 2008; Brown et al., 2019; Del Monaco et al., 2017; Diaz-Pulido et al., 2010; Diaz-Pulido and Barrón, 2020; Jompa and McCook, 2003; McCook, 2001; Rasher et al., 2011; Rasher and Hay, 2010; Vieira et al., 2016)However, information on the impacts of global and climate change on ecological interactions are still underrepresented in the literatura.

In order to explore the interaction of the macroalgae and corals under climate change, we used the macroalgae Chlorodesmis fastigiata (C. Agardh) S.C.Ducker and the coral Porites lobata (Dana, 1846) from Heron Island on the southern Great Barrier Reef. Both species are abundant and interactions between each are frequently observed (Jompa and McCook, 2003). C. fastigiata, a siphonous green macroalga, has been shown to have mostly negative impacts on corals, such as inducing bleaching (Bonaldo and Hay, 2014), decreased photosynthesis (Rasher et al., 2011; Rasher and Hay, 2010), polyp retraction by abra- sion (Jompa and McCook, 2003), reduced tissue recovery (Bender et al., 2012), and reduced coral settlement (Birrell et al., 2008). P. lobata is a massive, colonial coral from the order Scleractinia and constitutes one of the most important and occurring reef-building corals on Pacific coral reefs (Budd, 1986).

The combined effect of elevated CO2 and temperature on the inter- action between P. lobata and C. fastigiata was tested against ambient seawater as control, to provide further insights into coral-algal in- teractions under changing environmental conditions. Temperature of the treatment water was increased by 1 ◦C (compared to today; +2 ◦C compared to preindustrial times) and the CO2-concentration by +85 ppm according to the RCP2.6 scenario for the mid- to late 21st century (IPCC, 2013). We hypothesized that the coral would be nega- tively affected by both, the interaction with macroalgae and RCP2.6 conditions, and that the interaction with live algae would induce stronger effects than mimics because of biological/chemical in addition to mechanical effects (e.g. shading or abrasion).

2. Materials and methods

2.1. Study site and collection of corals and macroalgae

This study was done between October and December 2016 (late spring/Australian summer) at Heron Island Research Station (HIRS), located in the southern section of the Great Barrier Reef. Organisms were collected with permission from the Great Barrier Reef Marine Park Authority (permit number G16/38942.1). Colonies of P. lobata (approximately 30 cm in diameter) were collected at the reef flat of Heron Reef (four colonies, 23◦26′S, 151◦54′E) and the adjacent Wistari Reef (two colonies, 23◦27′S, 151◦52′E). From the colonies, 90 coral cores (further referred to as corals) of 5 cm diameter were drilled using a core saw, cut to a height of 1.5 cm and put into tanks with constant flow- through of seawater for a recovery time of 5 days.

Thirty specimens of C. fastigiata of approximately the same size as coral cores were collected with a small amount of substrate (Bonaldo and Hay, 2014) at the reef flat of Heron Reef. Care was taken not to injure holdfast or other tissue to avoid leaking of chemical compounds. Macroalgal substrate was cleaned of crabs and other organisms that lived and fed on the macroalgae were removed. Macroalgae were put into tanks with corals, with care not to touch the corals (or other mac- roalgae). After the recovery time of five days, seawater in all tanks was slowly switched to treatment water over another five days in order to let corals and algae acclimatize to the new conditions. Macroalgae mimics were made from 13 cm long pieces of fibre rope (0.7 cm in diameter), which were bent once in the middle, tied at the base and separated into its fibres (Edgar and Klumpp, 2003), and pieces of substrate were attached to the bottom. After the acclimatization time, mimics and specimens of C. fastigiata were tied to coral cores using rubber bands (without touching coral tissue) (Bonaldo and Hay, 2014) to avoid mimics from floating and to assure that macroalgae stayed with the same coral for the time of the experiment.

2.2. Experimental set-up, maintenance and monitoring

To assess the effect of elevated temperature and ocean acidification on a coral-algal interaction, organisms were subjected to ambient con- ditions and the Intergovernmental Panel on Climate Change (IPCC) scenario RCP2.6 conditions (Dove et al., 2013). Data collected at a reference site in the Wistari Channel (adjacent to Heron Reef) was used as a baseline for ambient temperature and CO2. Sea water was pumped from the reef flat to a holding tower at Heron Island Research Station and redistributed into two sumps, in which CO2 and temperature treatment conditions were established (as described by Dove et al., 2013). From these sumps the experimental tanks were supplied with the respective treatment water. Temperature and pH feedback sensors in experimental tanks were connected to a system controller, which then adjusted the conditions in the sumps at intervals of two hours to guar- antee exact diurnal and seasonal conditions within the experimental tanks (Fig. 1). See Dove et al. (2013) for details. Both water treatments (ambient and RCP2.6) were applied to nine tanks each (18 tanks in total). Per treatment condition, three tanks each contained five

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replicates of either a) only corals, b) corals with interacting macroalgae, or c) corals with macroalgal mimics (Fig. 2), summing up to 15 coral replicates per contact treatment. Organisms were kept under treatment conditions for a period of 22 days and physiological measurements were performed subsequently.

Experimental tanks (60*20*38 cm; ~ 35 l) containing corals and macroalgae were covered with Lee-filters (Old Steel Blue, 725) on the sides and lids to imitate light intensity at a water depth of 3–6 m on the reef flat. They were exposed to natural sun irradiance with a constant flow-through of seawater (0.8–1 l*min− 1). Pumps (Clearpond Infiniti 800) were installed to agitate seawater in order to avoid the forming of a boundary layer. Tanks were cleaned from fouling organisms every three days, with macroalgal mimics being washed in freshwater to remove biofouling, and settled substrate was carefully cleaned off corals with toothbrushes. At the same time, tanks were rotated to avoid confounding of light and temperature differences.

To monitor the abiotic conditions within tanks (Table 1), we installed four light loggers (PAR Sensor, Odyssey, Dataflow Systems, New Zealand) and five temperature loggers (HOBO Data Loggers, Onset) as well as four pH-probes (Mettler Toledo, Port Melbourne, Victoria,

Australia, InPro4501VP X connected to an Aquatronica Aquarium Controller ACQ110). pH was measured on the scale pHsw and the pH probes were calibrated every second to third day by a two point cali- bration. The loggers and probes were randomly swapped between tanks every three days to monitor every tank throughout the experiment. Temperature and pCO2 contents of sumps were recorded additionally (Table 1). pCO2 was measured in the sumps (logged continuously every 3 min) and calculated in CO2SYS (developed by E. Lewis and W.R. Wallace) based on twice daily alkalinity and salinity sampling, and continuous temperature and pH monitoring at 10 min intervals (see Dove et al. (2013) for more detail). The total alkalinity of each tank was sampled once a week at midday and midnight (Table 1) and measured using a Mettler Toledo titrating system (T50) by Gran titration after Dickson et al. (2003) using the method with a precision of ±3 μmol Kg− 1 or better as described in Kline et al. (2012). RCP2.6 conditions of ~1 ◦C increase and a CO2 level of +85 ppm compared to ambient conditions could be maintained during the experimental period.

Fig. 1. Schematic of sumps and wet table set up with partial pressure of CO2(pCO2)/ temperature control system. Seawater from the tower (light blue) is pumped into sumps (dark blue, red), treatment conditions are applied and tanks (n = 3 per interaction treatment) on wet table are connected to sumps. System controller (grey) with feed- back loop (dotted line) to adjust conditions in a two hour interval. AMB: ambient seawater; RCP2.6: treatment seawater with increased temperature and pCO2. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 2. Pictures of interaction treatments: a) coral P. lobata, b) coral P. lobata with interacting alga C. fastigiata, and c) coral P. lobata with algal mimic (made out of plastic fibre rope). Ambient and RCP2.6 water treatments were applied to each 3 tanks with 5 replicates each per interaction treatment.

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2.3. Measurement of respiration and calcification rates

In order to investigate treatment effects on the metabolism of corals and macroalgae, the net oxygen production (Pnet) and dark respiration rates (Rdark) were measured following the methodology of Crawley et al. (2010) at the end of the experiment (i.e. after 22 days in treatment conditions). Organisms (ncoral = 12 per treatment, nmacroalgae = 6 for RCP2.6 and 8 for ambient) were dark adapted for 45 min prior to dark respiration measurements. For Pnet measurements the light intensity was adjusted by modifying the distance of a metal halide lamp (Ocean Light T5 MH combo 150 W, with 2 × 24 Ocean Blue Actinic, Aqua-Medic of North America, LLC) from the specimens. The average light intensity within the experimental tanks matched that measured at midday of the previous week (694.5 μmol photons m− 2 s− 1 ≈ h = 32.5 cm). Oxygen flux was recorded using high-precision optical oxygen sensors (optodes) connected to a logging system (Oxy-10, PreSens, Germany) for 12 and 20 min for macroalgae and corals, respectively, and was normalized to the surface area of corals (see below) and fresh weight of macroalgae. All measurements were conducted in the respective treatment water (tam- bient = 25.9 ◦C, tRCP2.6 = 26.9 ◦C) calculated as a mean for the previous week. The photosynthesis per respiration (P:R) ratio was calculated by dividing Pnet by -Rdark.

The light and dark calcification rates were measured in addition to the photosynthetic/respiratory rates of the corals. To do this, alkalinity samples (n = 5 per treatment) were taken from respirometry incubations and the changes in the calcification of corals measured using the alka- linity anomaly technique using bulk water samples as blanks. Alkalinity samples were stored in a fridge at 4 ◦C, and within eight weeks after collection (Huang et al., 2012), were measured using a Mettler Toledo titrating system (T50) by Gran titration after Dickson et al. (2003) with a precision of ±3 μmol Kg− 1 or better using the method described in Kline et al. (2012). The calcification rate was then calculated from the total alkalinity after Zundelevich et al. (2007), corrected by 10− 3 for unit conversion and divided by two as molar amount of dissolved CaCO3 equals only half of observed AT increase (Chisholm and Gattuso, 1991). Calcification rates were normalized to time and surface area and expressed in μg CaCO3 cm− 2 h− 1.

2.4. Growth measurements

To examine possible differences in growth rates of organisms be- tween treatments, buoyant weight of corals (Jokiel and Maragos, 1978) (n = 15 per treatment) and fresh weight of macroalgae (n = 15 per treatment) were measured before the tank period and after respirometry measurements were conducted (i.e after 26 days). Fresh weight of macroalgae was calculated by subtracting the weight of the substrate (measured by buoyant weight) from the total weight. To minimize in- accuracy of measurements, macroalgae were blotted with paper tissue prior to weighing. Weight differences were calculated as percentage change of buoyant weight and fresh weight for corals and macroalgae, respectively. After weighing, all samples were frozen at − 20 ◦C pending further analysis.

2.5. Tissue analysis of corals

Tissue samples were taken from same corals used for respirometry measurements (n = 12 per treatment), by removal with a seawater jet (Johannes and Wiebe, 1970). Samples were poured into a Falcon tube and then vortexed and centrifuged at 4500 rpm for 5 min at 4 ◦C. The supernatant was poured into a 2 ml Eppendorf tube for protein analysis. To dilute the pellet left in the tube, 10 ml of filtered seawater was added and vortexed. From this dilution, 1 ml was pipetted into two tubes for zooxanthellae count and chlorophyll a analysis.

The population density of zooxanthellae was measured using a Neubauer hemocytometer (Neubauer-improved, Marienfeld GmbH), counting cells within three squares of four replicate grids. Chlorophyll a was measured by adding 2 ml of 100% acetone to the 1 ml pellet dilu- tion. Samples were sonicated in an ice bath for 10 min to extract the pigments and then centrifuged at 4500 rpm for 5 min at 4 ◦C to separate the pellet from the pigment solution. The supernatant was poured into a new Falcon tube and frozen and the extraction was repeated twice until supernatant was clear. After the extraction, tubes with supernatants were centrifuged again to remove debris (Hellebust and Craigie, 1978). Samples were measured in a spectrophotometer (SpectrostarNano) at wavelengths of 663 nm and 645 nm and blanks of acetone were measured after every ten samples and subtracted directly. The amount of chlorophyll a was then calculated after Arnon (1949) and expressed in g l− 1. As a quantitative indicator for the thickness of the tissue, the protein content was measured. Subsamples were measured as triplicates in the spectrophotometer at wavelengths of 235 nm and 280 nm. Protein content was calculated after Whitaker and Granum (1980) and expressed in g l− 1. To normalize tissue properties, respirometry mea- surements and calcification rates, the corals’ surface area was measured using the paraffin wax technique (Stimson and Kinzie III, 1991).

2.6. Data analysis

Before statistical analysis of data was performed, all variables were tested for a possible tank effect by using the lmne package in R Studio, which compares Gaussian linear and nonlinear mixed-effect models. The test was performed for models with and without tank as a random factor. Since the tank factor was non-significant for all variables (p > 0.25) (results in supplementary table S2), specimens were used as replicates (Underwood, 1997), hence increasing the power of the analysis.

All response data of corals were tested using a two-factor analysis of variance (ANOVA) with “scenario” (ambient; RCP2.6) and “contact” (coral; coral-algal interaction; coral with algal mimic) as fixed factors, including the interaction term. Response data of macroalgae were tested using a one-way ANOVA with “scenario” as factor. To account for multiple comparisons of physiological parameters for P. lobata a Bon- ferroni correction was applied reducing the α-level of significance to 0.005. When significant effects of factors occurred, ANOVAs were fol- lowed by a Tukey multiple comparisons test to identify significant groups. Data were tested for homogeneity of variance (visual inspection

Table 1 Summary of values of water chemistry data for scenario conditions.

Ambient RCP2.6

Temperature [◦C] tanks 25.95 ± 0.65 26.88 ± 0.75 pHSW tanks 8.07 ± 0.03 7.96 ± 0.03 Temperature [◦C] sumps 25.38 ± 0.44 26.29 ± 0.57 pCO2 [ppm] sumps 465.27 ± 53.48 550.58 ± 49.52 Total alkalinity day [μmol Eq. L− 1]

Day 2289.65 ± 12.23 2287.18 ± 11.86 Night 2269.11 ± 26.18 2271.64 ± 25.18

pCO2 [μppm] CO2Sys Day 268.17 ± 30.32 282.13 ± 25.32 Night 311.26 ± 26.52 331.45 ± 21.68

HCO3 − [μmol Kg SW− 1]

Day 1706.37 ± 43.74 1723.38 ± 36.09 Night 1744.8 ± 35.13 1767.53 ± 31.80

CO3 2− [μmol Kg SW− 1]

Day 234.64 ± 15.85 226.79 ± 11.60 Night 210.61 ± 10.87 202.61 ± 7.98

ΩAragonite Day 3.66 ± 0.25 3.54 ± 0.18 Night 3.28 ± 0.17 3.16 ± 0.12

Temperature, pH, pCO2 values are means over experimental period, continu- ously measured over the experimental period (22 days). High standard deviation is due to daily variability. Total alkalinity, pCO2, HCO3

− , CO3 and ΩAragonite of treatments are given as means over experimental period, measured once a week at midday and midnight in tanks and were estimated using CO2SYS software. Kg SW, kilogram of seawater.

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of residuals vs. fitted values), and normality of residuals was tested using Shapiro-Wilk normality test. Non-normally distributed data were log or power transformed to correct for right- or left skew, respectively. Sta- tistical analysis of data was performed using R Studio Version 1.0.143 (R Core Team, 2015) and results were expressed as boxplots using the ggplot package. Some samples of chlorophyll a and protein content of corals were lost throughout the analysis, reducing the degrees of freedom in the analysis.

3. Results

3.1. Corals

Coral growth, reported as percentage change in buoyant weight, was not significantly affected by the RCP2.6 or macroalgae treatment, or a combination of both. However, slightly negative growth was observed in the RCP2.6 coral treatment with an average of − 0.34% change in buoyant weight (see supplementary TableS1).

The technique used for the respirometry measurements allowed the quantification of calcification rates under treatment conditions in the presence and absence of light for a particular point in time. The response of light calcification was dominated by an interaction of “scenario” and “contact”. In the absence of macroalgae or mimics, corals showed significantly higher light calcification under ambient conditions with 48.7 ± 10.3 CaCO3 [μg h− 1 cm− 2] as compared to 15.1 ± 5.9 CaCO3 [μg h− 1 cm− 2] in the RCP2.6 scenario (Table 2, Fig. 3a). Corals in the ambient treatment also performed significantly different compared to corals in interaction with macroalgae in the RCP2.6 treatment. Dark calcification was significantly greater in the ambient scenario, with

negative dark calcification in the RCP2.6 scenario for all contact treat- ments (Table 2, Fig. 3b).

Pnet was significantly influenced by “contact” (Table 2, supplemen- tary material Fig.S1A) and lower in the coral-algal interaction treatment compared to only corals, while there was no difference of both treat- ments to the mimics treatment. Rdark was significantly affected by “scenario” (Table 2, supplementary material Fig.S1B), with higher respiration under RCP2.6 compared to ambient conditions. For the P:R ratio there was a highly significant effect of “contact” (Fig. 3c, Table 2), with differences among all treatments. P:R ratio was highest for the mimics treatment, followed by the coral treatment and lowest for the coral-algal interaction treatment. While the P:R ratio was higher under ambient conditions for only corals and corals with mimics compared to RCP2.6 scenario conditions, there was an opposite trend for the coral- algal interaction. However, the interaction term of “scenario” and “contact” was not significant (Anova, p = 0.03, Table 2).

Chlorophyll a (Fig. 4d and Protein content (Fig. 4a) were signifi- cantly different among “scenarios” (Table 2). The mean value of chlo- rophyll a content in the coral-algal interaction under RCP2.6 conditions was more than two times higher than for the interaction under ambient conditions (Fig. 4d). There was a slight trend of a higher zooxanthellae population density in the RCP2.6 compared to the ambient scenario, irrespective of the contact treatment (Table 2, Fig. 4b).

3.2. Macroalgae

The macroalga at the centre of this study was very sensitive, and began to die after eight days of exposure to treatment conditions. Macroalgae that died were replaced once by ‘back-up’ macroalgae, which were acclimated and kept in additional tanks with ambient and RCP2.6 conditions, respectively. However, due to permit limitations no more macroalgae could be replaced after that. Over the remainder of the experiment another 14 macroalgae died, some of which were ‘back-up’ macroalgae, summing up to a total of 30 dead macroalgae (n = 13 in ambient, n = 17 in RCP2.6). Only 16 macroalgae survived throughout the whole experimental time (n = 9 in ambient, n = 7 in RCP2.6), reducing the degrees of freedom in the analysis.

Due to differences in size of macroalgae, growth was expressed as percentage change in fresh weight. Growth of individuals was positive and negative in both of the scenarios, with negative values resulting from a loss of filaments, explaining a high standard deviation. However, total change in fresh weight was positive in both treatments, with no significant difference between treatments (Table 3). There was also no significant difference in Rnet between the scenarios (Table 3). Rdark was slightly higher in the RCP2.6 compared to the ambient scenario, resulting in a non-significant difference of P:R ratios between scenarios (Table 3).

4. Discussion

We investigated the important issues as to how ecological competi- tion may vary under climate change. To do so, we investigated the in- teractions between the coral P. lobata and the potential competitor, the fleshy alga C.fastigiate, under low rates of future ocean warming and acidification. Corals and macroalgae were exposed to a temperature increase of +1 ◦C and a CO2 increase of +85 ppm above ambient, which is close to the RCP2.6 scenario of the IPCC at mid- to late 21st century (IPCC, 2013). This corresponds to CO2 levels expected if action is taken globally in accordance with the Paris Agreement and refers to the best- case scenario. We found that both, interaction with macroalgae and the combined effect of temperature and CO2 affected the coral, whereas no significant impact of treatment conditions was detected for the macroalgae.

Table 2 ANOVA output of different variables for P. lobata with bold values indicating significant effects on the variable.

Variable Source of variation df F p

Bouyant weight Scenario 1 0.279 0.599 Contact 2 1.633 0.202 Scenario x Contact 2 1.587 0.211 Residuals 81

Light calcification Scenario 1 4.354 0.048 Contact 2 2.878 0.076 Scenario x Contact 2 7.480 0.003 Residuals 24

Dark calcification Scenario 1 36.792 <0.001 Contact 2 5.007 0.013 Scenario x Contact 2 2.843 0.078 Residuals 24

Zooxanthellae Scenario 1 7.031 0.010 Contact 2 0.821 0.445 Scenario x Contact 2 0.034 0.967 Residuals 66

Chlorophyll a Scenario 1 13.909 <0.001 Contact 2 0.068 0.934 Scenario x Contact 2 3.434 0.039 Residuals 54

Protein Scenario 1 12.448 <0.001 Contact 2 0.848 0.433 Scenario x Contact 2 2.228 0.117 Residuals 60

Pnet Scenario 1 2.390 0.127 Contact 2 5.893 0.004 Scenario x Contact 2 3.485 0.036 Residuals 66

Rdark Scenario 1 8.749 0.004 Contact 2 3.631 0.032 Scenario x Contact 2 0.156 0.856 Residuals 66

P:R Scenario 1 2.899 0.093 Contact 2 13.466 <0.001 Scenario x Contact 2 3.693 0.030 Residuals 66

df = degrees of freedom; F = F-value; p = p-value (significance <0.005).

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Fig. 3. Calcification rates of P. lobata under a light (n = 5), and b dark conditions (n = 5), measured during respirometry incubations. Letters indicate significant differences between interactions (a) or among scenarios (b).

Fig. 4. a Protein content (n = 11), b Zooxanthellae density (n = 12), c Photosynthesis/Respiration (P:R) ratio (n = 12), d Chlorophyll a content (n = 10), protein content (n = 11) for P. lobata. Letters indicate significant differences among scenarios (a,d) or contact (c).

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4.1. Calcification under low rates of warming and acidification

The calcification of massive species such as P. lobata can be slow, as compared to faster growing corals such as branching species (Lough et al., 1999). In this study, percentage change in buoyant weight (~deposited calcium carbonate) was close to zero in all treatments. It is very likely, however, that the period of our tank experiment (22 days) was too short, as well as the increase of pCO2 too small, to lead to a detectable effect in buoyant weight. Anthony et al. (2008) measured growth of P. lobata over a period of eight weeks and reported slightly reduced growth rate at 520–700 ppm and a ~ 40% decrease at 1000–1300 ppm. Diaz-Pulido et al. (2011) found that the linear exten- sion of the fast growing coral Acropora intermedia, measured over eight weeks, was also strongly negatively affected by CO2 treatments, but showed no significant difference between treatments with or without competition with the seaweed Lobophora papenfussii.

While a change in buoyant weight was not detected, measurements of dark calcification rates were significantly decreased under conditions similar to RCP2.6 for all interaction treatments, as well as for the coral treatment under light conditions. This is in agreement with other studies on coral of the genus Porites, including P. lobata (Anthony et al., 2008); P. lutea (Ohde and Hossain, 2004); P. compressa (Marubini et al., 2003) and supports the sensitivity of corals to elevated CO2 (Kleypas and Langdon, 2006). In the present study, negative calcification (i.e. decal- cification) was observed in all treatments under RCP2.6 conditions in the dark. CaCO3 dissolution even exceeded light calcification in the coral and coral-algae interaction treatment which would lead to negative growth rates in these treatments if measured over a longer period. While the amount of energy available from photosynthesis (P:R) was stable among scenario conditions in the coral-algal interaction, dark calcifi- cation was reduced under RCP2.6 conditions. This suggests that re- sources were used for processes other than calcification that demanded higher energy expenditure under RCP2.6 conditions in the dark while in contact with the alga.

Calcification under illuminated conditions in the RCP2.6 scenario was significantly reduced in the interaction with the macroalgae compared to algal mimics and to coral under ambient conditions. Those results suggest that macroalgal mimics benefitted the light calcification of corals through shading by reducing irradiance and therefore light stress (Anthony et al., 2008), while this positive effect could not be detected for live algae.

4.2. Photosynthesis and respiration: evidence of a CO2 fertilization effect?

Contrary to the results for the calcification rates, we found that RCP2.6 conditions significantly increased chlorophyll a and protein content. The increase in chlorophyll a coincides with an increased net photosynthesis under RCP2.6 conditions and might be explained by a ‘CO2 fertilization effect’ due to the greater availability of CO2 to photosynthesize. An increase in chlorophyll an under future conditions was also found in the branching corals Stylophora pistillata under raised temperature (Reynaud et al., 2003) and Acropora formosa under elevated CO2 (Crawley et al., 2010). Crawley et al. (2010) used an increase of

>200 ppm, but interestingly, a CO2 increase of only +85 ppm in this study was sufficient to lead to an increase in chlorophyll a. This is comparable to another study, which found an increase in productivity at an intermediate CO2 scenario (520–705 ppm), while the positive effect was mitigated at high CO2 (1010–1350 ppm) (Anthony et al., 2008). The positive effect of CO2 on chlorophyll a found in this study facilitates the slight increase of zooxanthellae and therefore protein content, which is an indicator for the nutritional condition of the coral (Ferrier-Pagès et al., 2003). However, the positive effect of CO2 on the chlorophyll a content could be mitigated when CO2 concentrations reach a higher level, as more energy is needed to maintain base functions of the coral host. This negative effect may be further enhanced by other anthropo- genic stressors, which weaken the competitive strength of corals over macroalgae (Diaz-Pulido et al., 2011; Foster et al., 2008).

While a decrease in photosynthesis of corals in contact with various macroalgae is documented (Rasher et al., 2011; Rasher and Hay, 2010), the interacting effects of CO2 and temperature on the interaction have scarcely been considered yet. Our study showed that there was a sig- nificant decreased P:R ratio of corals in interaction with macroalgae compared to no contact and the mimics treatment irrespective of the temperature/CO2 regime the corals were under. RCP2.6 conditions had a lesser negative effect that was only visible as a trend in the coral only and mimics treatment. C. fastigiata caused a significant decrease of photosynthetic efficiency in the corals Montipora digitata, Acropora mil- lepora and Pocillopora damicornis under ambient conditions, which was more severe compared to the effect of seven other common macroalgae (Longo and Hay, 2017; Rasher et al., 2011). In our study, however, corals were not actually in contact with macroalgae during the physio- logical measurements, because each species’ metabolic rate was measured separately. Negative carry-over effects of macroalgae on the coral photosynthesis and respiration found in our study might be even more enhanced if measured whilst in contact.

4.3. Physical impacts of competitors

Impacts of macroalgae can harm corals by various mechanisms including shading and abrasion (McCook et al., 2001) as well as biochemical reactions, e.g. the induced bleaching due to harmful chemicals (Longo and Hay, 2017; McCook, 2001; Nugues et al., 2004). Indeed, C. fastigiata has been shown to produce allelochemicals that can suppress photosynthesis (Rasher et al., 2011) and cause bleaching (Rasher and Hay, 2010). A study by Del Monaco et al. (2017) investi- gated the impact of allelochemical extracts from C. fastigiata on corals over the same time scale as our project and Diaz-Pulido and Barrón (2020) tested the release of dissolved organic carbon, which can pro- mote bacterial metabolism on corals surface and subsequent mortality, under future CO2 conditions. Both studies conclude that the effects of C. fastigiata were not more harmful to corals under future climatic conditions (Del Monaco et al., 2017; Diaz-Pulido and Barrón, 2020).This is in agreement with our results, which show an effect of C. fastigiata on the P:R ratio, which however was not enhanced under RCP2.6 conditions.

A recent study by Brown et al. (2019) suggests that coral-algal in- teractions are temporally variable across seasons. Photosynthetic rates of the coral A. intermedia in contact with H. heteromorpha were reduced in winter and increased in summer, while calcification rates in summer reduced in contact with the algae. Even though photosynthetic activity was increased in contact with the algae, negative effects of a high-end ocean acidification and warming scenario (RCP8.5) reduced overall performance of corals (Brown et al., 2019), which is comparable to the results of our study.

The impacts of competitors can vary strongly among coral-algal in- teractions. C. fastigiata is a siphonous macroalga and therefore lacks discrete cell walls (Rasher et al., 2011). For that reason, handling such as collection or tank cleaning might have had a significant impact on the health of the organisms, resulting in a high mortality rate of the

Table 3 ANOVA output of different variables for C. fastigiata.

Variable Source of variation df F p

Fresh weight Scenario 1 1.470 0.244 Residuals 15

Pnet Scenario 1 1.852 0.197 Residuals 13

Rdark Scenario 1 0.336 0.572 Residuals 13

P:R Scenario 1 0.341 0.569 Residuals 13

df = degrees of freedom; F = F-value; p = p-value (significance >0.05).

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macroalgae. Additionally, cycles of periodic loss and reappearance are known to occur in C. fastigiata, but the timing is unknown (Jompa and McCook, 2003). As the mortality rate was higher in the RCP2.6 scenario, temperature and CO2 increase might have affected algal health and led to a die-off. However, measurements are hardly comparable between treatments, as time in treatment differed between minimum 13 days and maximum 22 days, due to the mortality. Furthermore, only 9 corals in the ambient and 7 corals in the RCP2.6 treatment had an algal partner at the end of the study. Despite the early die off of macroalgae, we still measured their effects on corals, which, however, might have been more visible in the absence of algal mortality, especially in the RCP2.6 sce- nario, where macroalgae died relatively early in the experiment.

5. Conclusions

P. lobata has a ‘massive ‘coral morphology, and has previously been shown to be less affected by the interaction with competing macroalgae compared to other coral species. The negative impact of C. fastigiata was only visible in the decrease of the P:R ratio, but the study shows no enhanced impact under RCP2.6 conditions. The energy budget of the coral in this study, however, was very likely negatively influenced by RCP2.6 scenario conditions. Calcification, which is directly linked to the aragonite saturation, was probably negatively affected by the increase in CO2 as shown in earlier studies. We hypothesize that the productivity of zooxanthellae might be enhanced under the RCP2.6 scenario due to elevated CO2 availability (CO2 fertilization effect), leading to an in- crease of chlorophyll a. The coral host, however, was rather stressed, resulting in higher respiration and decreased calcification.

C. fastigiata is known for its strong allelopathy, but also very sensitive under experimental conditions. While the impacts of the algae on the coral were small, a temperature and CO2 increase of more than 1 ◦C and 85 ppm respectively over longer periods, whether due to global warming or warm water periods (e.g. El Niño), might have significant impacts on coral-macroalgal interactions. Hence, further studies with less sensitive macroalgae are needed to investigate the likelihood of interaction shifts for P. lobata under future climatic regimes.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We would like to thank the University of Queensland and the Leibniz Centre for Tropical Marine Research (ZMT) for funding. LR was sup- ported by the ZMT ‘Student Research Grant’. DB-C and OHG were supported by the Australian Research Council Laureate Fellowship program. Thanks to the research assistants at Heron Island Research Station for technical support.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi. org/10.1016/j.jembe.2020.151477.

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