Influence of the seagrass Thalassia hemprichii on coral reef mesocosms exposed to ocean acidification and experimentally elevated temperatures

Journal Pre-proofs Influence of the seagrass Thalassia hemprichii on coral reef mesocosms exposed to ocean acidification and experimentally elevated temperatures Pi-Jen Liu, Shin-Jing Ang, Anderson B. Mayfield, Hsing-Juh Lin PII: DOI: Reference:

S0048-9697(19)34455-9 https://doi.org/10.1016/j.scitotenv.2019.134464 STOTEN 134464

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Science of the Total Environment

Received Date: Revised Date: Accepted Date:

8 April 2019 25 July 2019 13 September 2019

Please cite this article as: P-J. Liu, S-J. Ang, A.B. Mayfield, H-J. Lin, Influence of the seagrass Thalassia hemprichii on coral reef mesocosms exposed to ocean acidification and experimentally elevated temperatures, Science of the Total Environment (2019), doi: https://doi.org/10.1016/j.scitotenv.2019.134464

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Title: Influence of the seagrass Thalassia hemprichii on coral reef mesocosms exposed to ocean acidification and experimentally elevated temperatures Running head: Seagrass influence on climate change-challenged coral reefs List of authors: Pi-Jen Liu1,2, Shin-Jing Ang3, Anderson B. Mayfield2,^, Hsing-Juh Lin3* Affiliation 1Graduate

Institute of Marine Biology, National Dong-Hwa University, Pingtung

94450, Taiwan 2National

Museum of Marine Biology and Aquarium, Pingtung 94450, Taiwan

3Department

of Life Sciences and Innovation and Development Center of Sustainable

Agriculture, National Chung Hsing University, Taichung 40227, Taiwan *Corresponding author, tel: +886-4-22840416, email: [email protected] ^present address: Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Association, Miami, FL 33149 USA *Corresponding author, tel: +886-4-22840416, email: [email protected] Keywords: climate change, coral reefs, ecosystem metabolism, ecosystem production, ocean acidification, seagrass Paper type: Primary research article

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1 2

Abstract Ocean acidification (OA) and warming currently threaten coastal ecosystems

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across the globe. However, it is possible that the former process could actually benefit

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marine plants, such as seagrasses. The purpose of this study was to examine whether

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the effects of the seagrass Thalassia hemprichii can increase the resilience of

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OA-challenged coral reef mesocosms whose temperatures were gradually elevated. It

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was found that shoot density, photosynthetic efficiency, and leaf growth rate of the

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seagrass actually increased with rising temperatures under OA. Macroalgal growth

9

rates were higher in the seagrass-free mesocosms, but the calcification rate of the

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model reef coral Pocillopora damicornis was higher in coral reef mesocosms

11

featuring seagrasses under OA condition at 25 and 28°C. Both the macroalgal growth

12

rate and the coral calcification rate decreased in all mesocosms when the temperature

13

was raised to 31°C under OA conditions. However, the variation in gross primary

14

production, ecosystem respiration, and net ecosystem production in the seagrass

15

mesocosms was lower than in seagrass-free controls, suggesting that the presence of

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seagrass in the mesocosms helped to stabilize the metabolism of the system in

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response to simulated climate change.

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18 19

1. Introduction The CO2 partial pressure (pCO2) in the atmosphere reached 411 μatm in the spring

20

of 2019 (https://www.esrl.noaa.gov/gmd/ccgg/trends/global.html), and representative

21

concentration pathway (RCP) scenarios 2.6 (“controlled warming”) and 8.5 (“business

22

as usual”) predict it to rise to 490 and 1370 μatm, respectively, by 2100 (van Vuuren

23

et al., 2011). According to the IPCC’s “Coupled Model Intercomparison Project”

24

(phase 5), the sea surface temperature (SST) will increase by 0.3-1.7°C (RCP2.6) to

25

2.6-4.8°C (RCP8.5) by 2081-2100 (Stocker et al., 2013). These temperature and pCO2

26

increases will cause the ocean’s pH to decline by 0.13-0.42, resulting in ocean

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acidification (OA).

28

Since 1970, the ocean has absorbed approximately 93% of the additional heat due

29

to global warming (Flato et al., 2013), leading to rising seawater temperatures. In

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general, when seawater temperatures rise above certain thermotolerance thresholds,

31

species richness declines (Katsikatsou et al., 2012) and corals bleach (Diaz-Pulido et

32

al., 2012). The differential responses of organisms to rising temperatures is expected

33

to affect their interspecific interactions (Poloczanska et al., 2013). However, prior

34

studies have tended to focus more on climate change-mediated effects on the

35

distribution (Shalders et al., 2018) or physiology of individual species (Helmuth et al.,

36

2013); the effect of rising temperatures on interspecific interactions is less commonly 3

37

addressed (but see Lord et al., 2017, García et al., 2018).

38

With increasing pCO2 (and declining pH), the concentration of HCO3- will

39

increase relative to that of CO32-, the latter being vital for the calcification of many

40

marine organisms. The increase in HCO3- concentration, in contrast, is expected to

41

stimulate the photosynthetic output of seagrasses and algae, which can use carbonic

42

anhydrase to convert HCO3- to CO2. Indeed, the productivity, shoot density,

43

belowground biomass and carbon reserves of seagrasses have all been reported to

44

increase in response to increased seawater pCO2 (Palacios and Zimmerman, 2007,

45

Andersson et al., 2011, Egea et al., 2018). The productivity and growth rate of

46

non-calcareous algae also increased at pCO2 levels ranging from 700 to 900 μatm

47

(Porzio et al., 2011, Kroeker et al., 2013). However, the calcification rate of corals

48

(Hoegh-Guldberg et al., 2007, Albright et al., 2016), sea urchins (Kurihara and

49

Shirayama, 2004), shelled molluscs (Gazeau et al., 2013), and spider crabs (Walther

50

et al., 2009) all decrease with increasing pCO2, leading to weakened calcified

51

structures.

52

Coral reefs are among the most biodiverse ecosystems on Earth and offer valuable

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ecosystem services to a plethora of organisms (as well as humankind; Knowlton, 2001;

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Costanza et al., 2014). However, over the past 20 years, phase shifts from coral- to

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macroalgal-dominated communities have occurred (Bellwood et al., 2004; Bruno and 4

56

Valdivia, 2016). In 1980-1983, coral cover ranged from 20 to 50%, even reaching

57

100% on some reefs in the Indo-Pacific. However, it is uncommon to find reefs with

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>70% live coral cover today, with most less than 30% even 15 years ago (Bruno and

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Selig, 2007). Commensurate decreases in coral cover in the Caribbean have also been

60

documented over the past 30 years: 50% in 1977 to 10% in 2002 (Gardner et al.,

61

2003). Disease, overfishing, eutrophication, rising temperatures, and OA have all

62

contributed to the demise of corals (Bruno and Valdivia, 2016), and the latter has been

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hypothesized to result in a shift from net calcium carbonate (CaCO3) precipitating

64

states to net dissolving ones (Baker et al., 2008). Furthermore, elevated temperatures

65

are hypothesized to elicit bleaching events on an annual basis, which will result in

66

dramatic community shifts given the wide variation in bleaching sensitivity across

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coral species (Donner et al., 2017).

68

Seagrasses are marine flowering plants that are widely distributed in shallow

69

waters except in the Antarctic Ocean (den Hartog and Kuo, 2007). Seagrass beds are

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“blue carbon” sinks (Gillanders, 2007; Huang et al., 2015) that provide a number of

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ecosystem services such as serving as food sources for mega-herbivores and as

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nursery grounds for a plethora of fish and invertebrates (Lee et al., 2015, 2016).

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Seagrasses are ecosystem engineers that can change the physical and chemical

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properties of seawater in a way that may affect nearby organisms, such as corals (van 5

75

de Koppel et al., 2015). For example, the rhizomes of seagrasses can stabilize the

76

sediments and filter seawater (Nordlund et al., 2017); the improved seawater clarity

77

resulting from the latter process can lead to higher irradiance, which benefits the

78

growth of corals and other photosynthetic organisms (Christianen et al., 2013).

79

Seagrasses and macroalgae can also absorb nutrients, which may suppress the

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growth of other macroalgae and/or seagrass in the near vicinity (Alexandre et al.,

81

2017); however, others (Moreno-Marín et al., 2016) have shown that macroalgae can

82

actually benefit the growth of seagrasses. As a specific example, both seagrasses and

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macroalgae can remove CO2 and increase local pH and ΩAr of the surrounding

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seawater via their high photosynthetic rates (Lai et al., 2013); this East Asia finding

85

has been observed elsewhere in the Pacific Ocean (Anthony et al., 2013), as well as in

86

the Mediterranean (Hendriks et al., 2014) and the Caribbean (Manzello et al., 2012).

87

Seagrass beds may consequently reduce the potential impact of OA on calcareous

88

organisms (Keppel and Wardell‐Johnson, 2012).

89

However, if both pCO2 and temperature were to rise, it is less clear how seagrass

90

beds may respond, nor do we know how coral reef+seagrass bed “mosaic habitats,” in

91

which corals and seagrass-based communities overlap (prevalent in Southern Taiwan,

92

as well as in the South China Sea; Lee et al., 2019) would be affected. Rising

93

temperatures might impose detrimental impacts on seagrasses, and shallow intertidal 6

94

seagrass beds are considered to be at the greatest risk (George et al., 2018); their

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relatively high respiration demands are expected to exceed their capacity for

96

synthesizing organic carbon through photosynthesis upon prolonged exposure to

97

elevated temperatures. Short-term high-temperature exposures, however, can actually

98

stimulate seagrass autotrophy (Egea et al., 2019).

99

In this multi-factorial study, coral reef mesocosms in Southern Taiwan were

100

cultured with and without seagrasses and exposed to both OA and gradually elevated

101

temperatures. There were four questions aimed to be answered/addressed in this

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integrated mesocosm study: 1. Can seagrass increase the resilience of coral reef

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mesocosms under OA alone, as well as OA plus elevated seawater temperatures?

104

2. How are net ecosystem calcification and production influenced by OA and

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elevated seawater temperatures? 3. Can seagrasses help calcifying macroalgae and

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corals resist elevated seawater temperatures under OA? 4. How do phytoplankton and

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benthic microalgae respond to elevated seawater temperatures under OA? Given the

108

aforementioned ability of seagrasses to modify local pH, it was hypothesized that reef

109

corals co-cultured with seagrasses would maintain higher growth rates under OA

110

conditions than those corals cultured in the absence of seagrasses. We also

111

hypothesized that elevated pCO2 exposure, but not elevated temperatures, would

112

enhance seagrass performance. 7

113

114

2. Materials and methods

115

2.1 Coral reef mesocosm facility

116

The coral reef mesocosm facility, which is located at the National Museum of

117

Marine Biology and Aquarium (NMMBA), is approximately 10 km northwest of

118

Taiwan’s Nanwan Bay (21°57’N, 120°45’E). Six tanks (5.14 m2 x 1 m depth; Fig. 1A)

119

were designed to serve as models of the reefs of Nanwan Bay (Liu et al., 2009). The

120

bottom of each tank was covered by a 3-cm layer of sand, and a few rocks were

121

distributed across the benthos. A plastic plate (180 x 120 cm) was placed on the rocks,

122

and two square baskets (81.5 x 81.5 x 6.5 cm [height]) covered with coral sand were

123

placed on the sand to simulate a reef flat. There were two pumps in each tank: one

124

was set up in the front side at 15 cm deep to produce wave simulations (1 Hz, 2–3 cm

125

wave height, SE200, Wavemaker, Taiwan) and another was set up along the back side

126

to produce a disturbance current of flow-through seawater (250 W, 7200 L h-1,

127

Trundean, Taiwan). Sand-filtered seawater pumped directly from adjacent Houwan

128

Bay (22°02’N, 120°41’E) was added to each tank at an exchange rate of 10% d-1 of

129

the total volume.

130

Seawater temperature in each tank was initially maintained at 25.0°C (±0.3°C [SD

131

for this and all other error terms in this section]) using a heat-exchanger (Great Helper 8

132

System & XT130C, Dixell, Italy) to simulate the field temperature in the spring (Liu

133

et al., 2009, 2015). During the experimental period, the photosynthetically active

134

radiation (PAR) at 0.5-m tank depth was maintained at 258±16.7 μmol photons m-2 s-1

135

from 0700 to 1700 hr (a 10:14-h light: dark photoperiod) by LED lamps (XLamp

136

XT-E LEDs, Cree, Taiwan).

9

137

138 139

A

B

C

140 141

Fig. 1. (A) The coral reef mesocosm facility. (B) The front side of the mesocosm, which

142

featured corals and giant clams and (C) the rear side of the mesocosm, which housed the

143

seagrasses. The black plastic mesh screen evident (~1 m2) in (B)-(C) (between the front

144

and rear sides) prevented seagrass grazing by sea urchins and served, additionally, as

145

settlement material for macroalgae (see below for details).

10

146

The biological components of these mesocosms were cultured at NMMBA for

147

several years prior to the experiment, and a detailed list of the organisms added can be

148

found in Table 1. There were some coral reef organisms already living in the tanks,

149

including soft corals, sea anemones, hydroids, sponges, polychaetes, isopods,

150

amphipods, symbiotic coral crabs, and macroalgae. At the location at which the wave

151

maker was set up to simulate the reef crest, the corals Montipora sp., Turbinaria sp.,

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Fungia sp., and Millepora sp. were deposited (Fig. 1B). On the front side of the “reef

153

flat,” the giant clam Tridacna maxima and the corals Turbinaria sp. and Pavona cactus

154

were placed. The corals Porites sp., Favia sp., and Heliopora coerulea (blue coral) were

155

deposited on the sand of each mesocosm, whereas nubbins were made from multiple

156

colonies of the coral Pocillopora damicornis several weeks prior to experimentation

157

(see timeline in Table 2.) and suspended on fishing line (9/mesocosm). Plants of the

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dominant seagrass species of Southern Taiwan, Thalassia hemprichii, were collected

159

with a shovel (along with the sediment into which their roots permeated) from seagrass

160

beds of Nanwan Bay. Approximately 3-4 seagrass shoots were transplanted to each of

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324 flower pots (8.1 cm diameter x 6.7 cm depth), and each seagrass mesocosm (n=3)

162

received a total of 108 pots (equivalent to 681±7 shoots m-2) positioned within a 1.08 m2

163

fenced-in enclosure to prevent grazing by sea urchins (Fig. 1C).

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Table 1. The number and total fresh weight (g) of the fish, mollusks, echinoderms, and corals present in the six mesocosms. Taxon

Common name

Scientific name

Fish

Bowtie damselfish

Control mesocosms (without seagrass)

Seagrass mesocosms

T2

T4

T6

T1

T3

T5

Neoglyphidodon melas

2

1

2

2

2

2

Blackspot sergeant

Abudefduf sordidus

0

1

0

0

0

0

Silver moony

Monodactylus argenteus

8(15.7)

8(18.7)

8(21.7)

8(15.4)

8(13.2)

8(22.3)

1(550.8)

1(270.4)

1(394.6)

1(270.4)

1(349.9)

1(270.4)

Eyestripe surgeonfish Acanthurus dussumieri Two-tone tang

Zebrasoma scopas

1(8.5)

1(8.5)

1(8.5)

1(15.8)

1(13.0)

1(10.6)

Jeweled blenny

Salarias fasciatus

3(24.0)

3(16.3)

3(27.6)

3(21.4)

3(20.1)

2(17.8)

Decorated goby

Istigobius decoratus

1

1

1

1

1

1

Giant clam (large)

Tridacna maxima

2

2

1

2

1

1

Giant clam (small)

Tridacna maxima

12

12

17

12

16

17

Black-spotted topshell Trochus hanleyanus

20(276)

20(284)

20(277)

20(285)

20(284)

20(274)

Hawaiian sea urchin

Tripneustes gratilla

2(340)

2(339)

2(363)

2(358)

2(358)

2(335)

Black sea cucumber

Holothuria leucospilota

5(1048)

5(1005)

5(1044)

5(1069)

5(1035)

4(1006)

Hydrozoans

Fire coral

Millepora sp.

1

1

1

1

1

1

Zoantharians

Cup coral

Turbinaria spp.

8

7

8

9

8

9

Mushroom coral

Fungiidae

1

2

1

1

1

1

Faviid coral

Faviid spp.

1

1

1

1

1

1

Cactus coral

Pavona cactus

1

1

1

2

1

1

Plating coral

Montipora sp.

1

3

3

1

1

1

Massive coral

Porites spp.

1

1

1

2

1

1

Cauliflower coral

Pocillopora damicornis

9

9

9

9

9

9

Blue coral

Heliopora coerulea

1

1

1

1

2

1

Mollusks

Echinoderms

Alcyonarians

165

12

166 167 168 169 170

Table 2. The experimental design, including dates, duration, temperature, and pCO2 of each experimental stage. Readers are referred to prior works for details on annual temperature variation in Nanwan Bay’s coral reefs (Mayfield et al., 2012) and seagrass beds (Liu et al., 2012, Lin et al., 2018). Stage

Duration

# days

I II III IV

27 March-9 April 2017 10 April-7 May 2017 8 May-4 June 2017 16 June-28 June 2017

14 28 28 13

Temperatur e (°C) 25 25 28 31

pCO2 (μatm) 400 800 800 800

171 172

An Apex AquaController (USA) system (Supplementary fig. 1) featuring the Apex

173

base, the Energy Bar 8, the Apex display, a thermometer, a pH meter, and an ORP

174

probe was used to control seawater temperature and pH; the latter was achieved by

175

opening and closing a CO2 tank (100%) connected to four tubes with free air stones at

176

the end. The tubes were evenly distributed across each mesocosm to release CO2, which

177

quickly dissolved into the water. During OA treatments (described below), the release

178

of CO2 was initiated when the pH meter sensed a pH value >7.90 (10-min logging

179

interval) and stopped when the pH value was <7.80; the target value sought to match the

180

RCP6.0-projected pH of 7.85 (by the end of the 21st century). The total alkalinity (TA)

181

remained relatively constant (2207±45 μmol kg-1) over the duration of the OA

182

experiment (Supplementary table 1), resulting in a pCO2 of ~800 μatm at a pH of 7.85.

183

Three tanks featured seagrasses, while the other three were seagrass-free controls.

184

The maximum, dark-adapted yield of photosystem II (Fv/Fm) of random seagrass

185

shoots was assessed periodically (described in more detail below) after the shoots were

186

transported from the ocean into the mesocosms in order to determine whether they had

187

acclimated to their new environments (Supplementary table 1). After 10 days of

188

acclimation, the experiment began on 27 March 2017 (Table 2). Stage I was conducted

189

for 14 days under a constant seawater temperature of 25°C (the mean seawater 13

190

temperature of Nanwan Bay in the spring); all tanks were maintained at ambient pCO2

191

(~400 μatm), and we sought to document the effects of seagrass only in this stage. It

192

was hypothesized that a 2-week duration would be sufficient to observe seagrass effects

193

on corals given 1) prior work on coral+seagrass mosaic habitats in Southern Taiwan

194

(Lin et al., 2018) and the South China Sea (Lee et al., 2019) and 2) the close proximity

195

in which these fauna were cultured.

196

Stage II was conducted to examine the effect of OA (800 μatm) and seagrass

197

presence for 28 days at 25°C. A longer duration was chosen for this stage because the

198

effects of OA on reef corals in particular have been found to be subtle (Comeau et al.,

199

2014), or else not documented at all (Putnam et al., 2013) and so we hypothesized that

200

more time would be required to elicit a detectable physiological response. Similarly,

201

Stage III examined the combined effect of rising temperature (28°C; the mean

202

temperature of Nanwan Bay in the summer) and OA (800 μatm) for 28 days; since this

203

“high” temperature is still well under the maximum experienced by coral reefs in

204

Southern Taiwan (~30-30.5°C in the summer; Mayfield et al., 2013), a longer duration

205

was hypothesized to be needed to detect a shift in coral and/or seagrass behavior. Given

206

that the SST is predicted to increase by 1.4-3.1°C by the end of 21st century (RCP 6.0,

207

Stocker et al., 2013), the seawater temperature was increased to 31°C for 13 days at 800

208

μatm during Stage IV of the experiment. In contrast to Stages II and III, exposure to OA

209

at 31°C was hypothesized to elicit a stress response in the coral after only several days

210

of treatment; therefore, the duration of this experimental stage was relatively short.

211 212 213

2.2 Biological response The shoot density (shoots m-2) of T. hemprichii was determined every two weeks by

14

214

counting the number of shoots in each tank and dividing by the seagrass area (0.507 m2).

215

The leaf growth rate was also determined biweekly in each tank using the leaf marking

216

method (Short and Duarte, 2001). Briefly, approximately five plants were randomly

217

selected and marked in each tank at each measurement time. A small hole was punched

218

through all of the leaves at the base of each shoot to provide a reference level.

219

Approximately seven days after initial marking, the new growth increments of the

220

leaves were measured. Using these measurements, the leaf growth rate was then

221

expressed as mm shoot−1 day−1.

222

A submersible pulse amplitude-modulated (Diving-PAM) fluorometer (Waltz) was

223

used to measure three fluorescence parameters from both coral nubbins (P. damicornis)

224

and seagrass shoots (mentioned above): Fo (initial chlorophyll fluorescence after

225

acclimating samples in darkness for 20 min when all reaction centers were open), Fm

226

(maximum chlorophyll fluorescence after dark acclimation for 20 min when all reaction

227

centers were closed following a saturating flash of light), and Fv/Fm (maximum

228

quantum yield of photosystem II, where Fv=Fm-Fo). The calcification rate (mg CaCO3

229

d-1) of the coral P. damicornis was determined by the buoyant weighing technique

230

(Davies, 1989), and mass increase per day was normalized to nubbin surface area using

231

the modified wax dipping method of Mayfield et al. (2013).

232

Macroalgae began to proliferate rapidly in Stage II (OA). To assess algal growth, we

233

scraped all algae off the plastic urchin exclusion screen (Fig. 1B-C; one side of the

234

fence only) located close to the wave pump of each tank (size: 120 cm x 50 cm, but only

235

0.42 m2 surface area under the water) with a toothbrush. The plastic mesh was only

236

briefly removed from each mesocosm before being returned to ensure that urchins did

237

not graze seagrass blades during that time. The collected macroalgae were then weighed

15

238

(wet weight), and the growth rate was determined by collecting all macroalgae that had

239

accumulated each week in each tank, then normalizing to day (g wet weight d-1).

240

Assessment of ecosystem metabolism can aid in understanding the interactions

241

between organisms and their environments (Thorp and Delong, 2002; Marcarelli et al.,

242

2011). Diel variation in dissolved oxygen (DO) concentration was used to determine the

243

gross primary production (GPP), ecosystem respiration (ER), and net ecosystem

244

metabolism (NEP) of each mesocosm herein (sensu Odum, 1956). A DO data logger

245

(HOBO U-26, Onset, USA) was used to measure the changes in DO concentration

246

(ΔDO; g O2 m-2) in each tank at a 30-minute logging interval over the duration of the

247

experiment. In general, the ΔDO was driven by oxygen produced via photosynthesis

248

during the day, the oxygen respired, and the air-seawater exchange of oxygen (Kemp

249

and Boynton, 1980; see details below.). The ΔDO during the night was assumed to be

250

driven by 1) respiration and 2) the air-seawater exchange of oxygen. Therefore, the

251

hourly oxygen respiration rate during the night was calculated by correcting for the

252

air-seawater exchange of oxygen and dividing by the time (hr). The air-sea exchange

253

calculation followed Kemp and Boynton (1980): (1-(DO sat, t2 + DO sat, t1)/200)*k*dt,

254

where DO sat, t1 and DO sat, t2 are the relative percent oxygen saturations (%) at times t1

255

and t2, respectively, k is the air-sea exchange coefficient, and dt is the time difference

256

(in hours) between t2 and t1. DOTABLES

257

(http://water.usgs.gov/software/DOTABLES/) was used to calculate oxygen saturations

258

given the measured conditions in the tank. The wind and tide account for about the 50%

259

of the total DO; therefore, when DO is 0, k is assumed to be 0.5 g O2 m-2 hr-1 when

260

estimating the sea-air exchange.

261

Assuming the hourly respiration rate during the night was similar to that of the day,

16

262

the 24-hr (daily) respiration rate (also known as the ER rate) was calculated by

263

multiplying the hourly night respiration rate by 24 hr. The GPP rate was then calculated

264

by adding the ΔDO rate to the respiration rate during the day, and the NEP rate was

265

calculated by deducting the ER rate from the GPP rate. These DO data were also used to

266

calculate a GPP:ER (i.e., photosynthesis [P]:respiration [R]) ratio to serve as a system

267

trophic index (sensu Odum, 1956).

268 269 270

2.3 Seawater quality data The AquaController system automatically monitored water temperature and pH

271

every 10 min. DO (mg L-1) and salinity were monitored daily at 9:30 am in each tank

272

using a portable “Professional Plus” meter from YSI (USA). A HOBO® Pendant data

273

logger (UA-002-64) was placed on the reef flat area of each mesocosm to measure

274

underwater light and temperature at 30-min intervals during the experimental period.

275

Light intensity (Lux) was transformed to photosynthetic photon flux density (PPFD)

276

and expressed as µmol m-2 s-1 (Riddle, 2013).

277

Every week, seawater samples were collected from the middle layer (~0.5 m depth)

278

of each tank for determination of total alkalinity (TA; sensu Strickland and Parsons,

279

1972). TA, pH, seawater temperature, and salinity were then used to determine the

280

pCO2 and aragonite saturation state (ΩAr; sensu Lewis et al., 1998). Seawater samples

281

were also collected from each tank at 10:00 am on a randomly selected day every week.

282

These water samples were filtered through 0.45-μm filters (Pall Corporation) and then

283

analyzed colorimetrically for phosphate (Hach, USA), ammonium (Hach), nitrite (Pai

284

and Riley, 1994), and nitrate (Pai and Riley, 1994).

285

17

286

2.4 Statistical analyses

287

Before statistical analyses, data were examined to determine whether residuals

288

conformed to assumptions of normality and homogeneity of variance. If not, they were

289

transformed (Clarke and Warwick, 2001) or analyzed using non-parametric statistical

290

methods. After the mean value of each change was compared with the standard

291

deviation, the slope (β) between the two was obtained by linear regression. When β

292

=0, no transformation was needed; when β≧0.5 and ≧0.75, data were square and

293

fourth root- transformed, respectively. If β≧1, the data were log transformed. If the

294

transformed data still did not meet the assumptions for parametrical statistical analyses,

295

the appropriate non-parametric analysis was chosen according to the independence of

296

the data. The four-stage experiment was separated into three parts (Table 2): Stage 1)

297

effect of seagrass alone (25°C and ambient pCO2), Stage 2) the effect of seagrass

298

presence under OA only, and Stages 3 and 4) the effect of seagrass presence under the

299

combined effects of OA and warming to 28°C and 31°C, respectively. One-way

300

repeated measures ANOVAs were used to determine the effect of OA (from Stage 1 to

301

2) or combined effects of OA and warming (from Stage 2 to 4) on seagrass responses.

302

Two-way repeated-measures ANOVAs were applied to determine the effect of seagrass

303

presence and OA only (from Stage 1 to 2) on seawater quality, other biological response

304

variables (coral Fv/Fm, coral calcification rate, and macroalgal growth rate), and system

305

metabolism. Two-way repeated-measure ANOVAs were also carried out to determine

306

the effect of seagrass presence and the combined effects of OA and warming (from

307

Stage 2 to 4) on seawater quality, biological responses, and system metabolism.

308

SigmaPlot 12.5 (SigmaStat, Systat Software GmbH, Germany) was used for the

309

statistical analyses described above. Unless stated otherwise, all error terms presented 18

310

below represent standard error (SE) of the mean, and an alpha level of 0.05 was

311

established a priori.

312 313

3. Results

314

3.1 Seawater quality response to OA and rising temperatures

315

In Stages I and II, the effect of OA alone on seawater quality was more pronounced

316

than the effect of seagrass presence (Table 3). For all mesocosms, the pH was

317

effectively dropped to its target value of ~7.85, and DO concentration decreased in

318

concert (Supplementary table 2). There were no significant differences in pCO2, DIC

319

concentration, ΩAr, and TA between the seagrass mesocosms and the controls; upon OA

320

alone in Stage II, pCO2 and DIC concentration in all mesocosms increased 91 and 6%,

321

respectively (Table 3). However, ΩAr decreased 37% upon acidifying the seawater. OA

322

did not affect TA, but it did result in significant changes in concentrations of various

323

seawater carbon species in all mesocosms (Supplementary table 2). The concentrations

324

of HCO3- and CO2 increased 10 and 85%, respectively, in response to OA alone in

325

Stage II, whereas the concentration of CO32- decreased by 37%.

326

All mesocosms were oligotrophic in Stage I (Table 3). After OA alone (Stage II),

327

the phosphate concentration increased 18% in the seagrass mesocosms though

328

decreased 73% in the controls. The concentrations of ammonium, nitrite, and nitrate

329

increased 95, 55, and 61%, respectively, after OA alone (Supplementary table 2). While

330

seawater temperature was programmed to increase from stage II (25°C) to stage IV

331

(31°C), DO decreased only 4% over this period (Table 3). There were significant

332

differences in seawater carbon species concentrations in response to the combined effect

333

of OA and warming for all mesocosms (Supplementary table 3). The concentrations of

19

334

both pCO2 and CO2 were slightly higher (7 and 8%, respectively) in all mesocosms at

335

28°C than at 25°C and 31°C (Table 3). Rising temperatures slightly reduced TA and

336

ΩAr, as well as the concentrations of DIC, HCO3-, and CO32- for all mesocosms. TA, ΩAr,

337

DIC, and concentrations of HCO3- and CO32- decreased 3, 8, 2, 2, and 9%, respectively,

338

from 25°C to 31°C.

339

The combined effect of OA and warming resulted in a significantly higher

340

phosphate concentration in the seagrass mesocosms than in the controls (Supplementary

341

table 3). The concentrations of nitrite and nitrate in all mesocosms at 31°C were 1.22

342

and 3.49-fold higher, respectively, than at 25°C and 28°C (Table 3). The concentrations

343

of nitrite and nitrate in the seagrass mesocosms tended to be higher (35 and 72%,

344

respectively) than in the controls at higher temperatures under OA, though the

345

differences were only marginally significant (Supplementary table 3).

346 347 348

3.2 Seagrass response to OA and rising temperatures OA led to a significant increase in both T. hemprichii shoot density (Fig. 2A) and

349

leaf growth rate (Fig. 2B) at 25°C (Stage II): increasing 4 and 25%, respectively

350

(Supplementary table 4). In contrast, Fv/Fm decreased slightly from 0.813±0.003 (Stage

351

I) to 0.799±0.005 upon OA treatment (Stage II), though later recovered (even as

352

temperatures rose; Fig. 2C). Further rising of the temperature (Stage II to Stages III and

353

IV) also led to significant increases in shoot density (18%) and leaf growth rate (35%)

354

at 31°C (Supplementary table 5). Fv/Fm also increased to 0.822±0.004 at 31°C.

20

355 356

Table 3. Seawater quality (mean±SE; n=3) in the four stages of the experiment in both seagrass and control (i.e., seagrass-free) mesocosms. 25˚C (ambient pCO2)

25˚C (acidification)

28˚C (acidification)

31˚C (acidification)

　

Control

Seagrass

Control

Seagrass

Control

Seagrass

Control

Seagrass

pH

8.06±0.01

8.10±0.04

7.86±0.00

7.86±0.01

7.85±0.00

7.86±0.01

7.85±0.00

7.86±0.00

Temperature (˚C) Photosynthetically active radiation (PAR, µmol m-2 s-1) DO (mg L-1)

25.0±0.0

25.0±0.1

25.1±0.0

25.1±0.1

27.9±0.0

27.9±0.0

30.8±0.1

30.8±0.0

274.0±2.4

267.7±10.8

242.0±20.4

281.4±9.5

256.1±13.6

248.7±20.0

251.2±14.1

247.4±33.3

6.84±0.00

6.84±0.01

6.78±0.00

6.79±0.01

6.49±0.00

6.49±0.00

6.24±0.00

6.24±0.00

Salinity

35.07±0.06

35.09±0.04

34.99±0.01

35.03±0.01

34.67±0.07

34.77±0.04

33.80±0.10

33.86±0.06

449±4

418±20

818±7

837±19

891±12

906±13

853±21

825±10

TA (μmol kg-1)

2093±10

2157±25

2114±22

2148±42

2090±2

2096±32

2073±15

2066±19

ΩAr

2.72±0.02

2.99±0.15

1.78±0.02

1.80±0.05

1.61±0.02

1.60±0.03

1.64±0.03

1.67±0.04

1849±9

1889±13

1971±21

2004±39

1963±3

1971±30

1945±15

1934±15

1665±8

1689±8

1836±19

1867±36

1837±4

1844±28

1819±15

1807±12

CO32- (μmol kg-1)

171±1

188±9

112±2

113±3

101±1

101±2

102±2

104±3

CO2 (μmol kg-1)

13±0

12±1

23±0

24±1

25±0

26±0

24±1

23±0

PO43- (μmol L-1)

0.085±0.027

0.117±0.045

0.034±0.010

0.142±0.067

0.058±0.016

0.082±0.018

0.079±0.042

0.158±0.073

NH4+ (μmol L-1)

0.520±0.044

0.621±0.120

0.958±0.035

1.215±0.113

0.757±0.054

0.879±0.015

0.924±0.136

1.007±0.170

NO2- (μmol L-1)

0.086±0.012

0.099±0.023

0.125±0.012

0.172±0.007

0.141±0.015

0.154±0.019

0.246±0.044

0.402±0.044

NO3- (μmol L-1)

0.262±0.040

0.576±0.287

0.466±0.029

0.889±0.256

0.229±0.094

1.142±0.269

1.204±0.190

4.922±1.765

pCO2 (μatm)

DIC (μmol HCO3

kg-1)

- (μmol

kg-1)

357

21

358

359 360 361 362

363 364 365 366 367 368 369 370 371 372 373

A

B

C

Fig. 2. Seagrass (A) shoot density, (B) leaf growth rate, and (C) maximum quantum yield of photosystem II (Fv/Fm) across the four stages (denoted by shading) of the experiment (mean±SE; n=3). Lowercase letters adjacent to experimental stage at the top of each panel signify significant differences (Tukey’s p<0.05) between the means for each experimental stage, as repeated measures ANOVAs detected significant overall effects of ocean acidification [OA] (from Stage I to II) and combined effects of OA and warming (from Stage II to IV) for each response variable (Supplementary tables 4 and 5). In all cases, the group labeled “a” possessed the lowest value of the respective response variable.

22

374 375

3.3 Macroalgae response to OA and rising temperatures OA and rising temperatures stimulated the growth of macroalgae (Fig. 3); after OA,

376

the macroalga Dictyota bartayresiana started to grow rapidly in all mesocosms

377

(Supplementary fig. 2), and its growth rate was 2-fold higher in the controls than in the

378

seagrass mesocosms at 25°C and 28°C. However, its growth slowed at 31°C in all

379

mesocosms (Fig. 3).

380 381 382

3.4 Coral response to OA and rising temperatures OA did not significantly affect coral Fv/Fm, which ranged from 0.737 to 0.750 (Fig.

383

4A). However, coral Fv/Fm decreased gradually with rising temperatures under OA

384

conditions for all mesocosms. There was no significant difference in coral Fv/Fm

385

between the seagrass mesocosms and the controls (Supplementary tables 6 and 7). The

386

coral calcification rate was significantly higher in the seagrass mesocosms than in the

387

controls at 25°C and 28°C under OA (Fig. 4B). However, the coral calcification rate

388

was significantly lower at 31°C+OA for all mesocosms (Supplementary table 7).

389 390 391

3.5 System metabolic response to OA and rising temperatures In Stages I and II, there were no significant differences in the ER rates between the

392

control and seagrass mesocosms (Supplementary table 6). For all mesocosms, the ER

393

increased gradually with rising temperatures from Stage II to IV under OA conditions

394

(Fig. 5A). Moreover, the ER was significantly higher in the controls than in the seagrass

395

mesocosms at 28°C and 31°C under OA (Supplementary table 7). In Stages I and II,

396

there was no significant difference in the GPP between the control and seagrass

397

mesocosms, nor did OA affect GPP (Supplementary table 6). However, the GPP in all

23

398

mesocosms increased from the lowest values at 25°C to the highest values at 28°C (Fig.

399

5B). GPP was similar at 28°C and 31°C. The GPP was also significantly higher in the

400

controls than in the seagrass mesocosms when pooling the data across all sampling

401

times from Stage II to IV (Supplementary table 7).

402

In Stage II, OA did not affect the NEP in the seagrass mesocosms (Fig. 5C).

403

However, the NEP in the controls increased significantly after OA (Supplementary table

404

6). The NEP in all mesocosms decreased significantly with rising temperatures and

405

reached the lowest value at 31°C under OA (Supplementary table 7). The NEP in the

406

seagrass mesocosms tended to be lower than in the controls for all temperature

407

treatments (Fig. 5C), though no significant difference was detected.

408

In Stage II, the P:R ratio was not affected by OA alone (Fig. 5D). However, rising

409

temperatures significantly decreased the P:R ratio in all mesocosms, and lowest values

410

were measured at 31°C under OA (Supplementary tables 6 and 7). No significant

411

difference in the P:R ratio was detected between the control and seagrass mesocosms.

24

412 413 414 415 416 417 418

Fig. 3. The growth rate of macroalgae in control and seagrass mesocosms (mean±SE; n=3) for the latter three stages of the experiment. No macroalgae were observed during Stage I (prior to ocean acidification [OA]). Lowercase letters at the top of the figure signify significant differences (Tukey’s p<0.05) across stages.

25

419

420 421

422 423 424 425 426 427 428 429 430

A

B

Fig. 4. (A) Maximum, dark-adapted yield of photosystem II (Fv/Fm) and (B) calcification rates of corals in response to ocean acidification (OA) and warming (mean±SE; n=3) in all four and the latter three experimental stages, respectively. Lowercase letters adjacent to experimental stage or treatment names at the top of each panel signify significant differences (Tukey’s p<0.05) between experimental stages and seagrass (Sg) and control (Con) mesocosms when the repeated measures ANOVAs (Supplemental tables 6 and 7) detected a significant overall effect of stage alone (a) or 26

431 432

stage x treatment (b), respectively. In all cases, the group labeled “a” possessed the lowest value of the respective response variable.

27

433

A

B

434 435 436

C

D

437 438 439 440 441 442 443 444 445 446 447

Fig. 5. Community metabolism parameters in control (Con) and seagrass (Sg) mesocosms (n=3) at each of four experimental stages (mean±SE). (A) ecosystem respiration (ER), (B) gross primary production (GPP), (C) net ecosystem metabolism (NEP), and (D) P/R ratio. Lowercase letters adjacent to experimental stage or treatment names at the top of each panel signify significant differences (Tukey’s p<0.05) between experimental stages (b-d), treatment (b), and/or the interaction of stage and treatment (a, c) when the repeated measures ANOVAs (Supplemental tables 6 and 7) detected significant overall effects in the respective comparisons. In all cases, the group labeled “a” possessed the lowest value of the respective response variable.

28

448

4. Discussion

449

Effects of OA on different primary producers. Upon pumping CO2 into the seawater,

450

all mesocosms underwent increases in the concentrations of H2CO3, HCO3-, and H+; the

451

CO32- concentration and pH both decreased, as was hypothesized. Importantly, the

452

concentration of HCO3- was higher than CO2. Since the K0.5 of CO2 is 2-3 times lower

453

than that of HCO3-, CO2 is the preferred carbon source for seagrasses and macroalgae

454

(Sand-Jensen and Gordon, 1984). However, due to the slow dispersion rate and low

455

concentration of CO2 in seawater, most marine producers are C3 plants and use HCO3-

456

as their primary carbon source (Koch et al., 2013). Particularly, the lower utilization

457

efficiency of HCO3- by seagrasses than by macroalgae (Beer, 1989) suggests that

458

seagrasses are often limited by DIC in marine ecosystems (Invers et al., 2001). Some

459

seagrass species have been reported to demonstrate higher photosynthetic efficiency

460

(Fv/Fm), elevated leaf productivity, higher belowground biomass, and lower leaf

461

nitrogen and chl-a content in response to the higher DIC concentrations associated with

462

OA (Jiang et al., 2010, Repolho et al., 2017). Herein, although the Fv/Fm of T.

463

hemprichii was not greatly affected by OA, shoot density and leaf growth rate both

464

increased, which is consistent with results of prior studies (Palacios and Zimmerman,

465

2007; Andersson et al., 2011). Increasing the temperature to 28°C or 31°C under OA

466

conditions further increased the shoot density, photosynthetic efficiency, and leaf

467

growth rate of T. hemprichii. Higher leaf productivity of the seagrass Zostera marina in

468

response to acidification was also observed (Palacios and Zimmerman, 2007). It is

469

worth noting here that the faster decomposition rates of old and senesced seagrass

470

leaves under higher temperatures (Huang et al., 2015) may have accounted for the

471

higher concentrations of nitrite and nitrate in the seagrass mesocosms at 31°C.

29

472

Upon acidification, the macroalga D. bartayresiana proliferated in all mesocosms.

473

The congeneric Dictyota dichotoma was also dominant in high-pCO2 vents off Castello

474

Aragonese (Ischia Island, Italy) (Porzio et al., 2011). Many macroalgae can dampen the

475

activity of HCO3--based carbon concentrating mechanisms (CCMs) and shift from use

476

of HCO3- to CO2 as their preferred carbon source in response to elevated CO2 levels

477

(Young and Gobler, 2016). Such a shift could explain why D. bartayresiana thrived

478

under OA conditions in our mesocosms. Furthermore, the significantly lower phosphate

479

concentrations in the controls relative to the seagrass mesocosms after increasing the

480

pCO2 and temperature may have been due to uptake by these macroalgae. Although the

481

growth of D. dichotoma was presumably stimulated by OA herein, its growth rate

482

sharply declined at 31 ̊C , and mortality was actually prevalent. Biber (2002) also found

483

that macroalgal biomass decreases at this temperature in South Florida (similar latitude

484

as Southern Taiwan).

485

The Fv/Fm of the coral P. damicornis did not decrease in response to OA, and its

486

calcification rate was similar to that measured in the South China Sea at 29°C (Jiang et

487

al., 2017). P. damicornis is clearly not vulnerable to OA (as observed previously,

488

Comeau et al., 2014), nor are the larvae (Putnam et al., 2013). However, upon

489

increasing the temperature to 28°C under OA conditions, Fv/Fm declined; the

490

calcification rate, however, was unaffected until the temperature was raised to 31°C for

491

13 days. In another mesocosm study carried out at the same facility, P. damicornis was

492

found to actually bleach at 31.5°C (Mayfield et al., 2013); our finding of diminished

493

calcification at 31°C under OA conditions herein is therefore unsurprising.

494

The calcification rate of P. damicornis in the seagrass mesocosms was significantly

495

higher than in the controls at 25°C and 28°C under OA conditions. Prior studies (Lai et

30

496

al., 2013, Hendriks et al., 2014) indicated that seagrasses may regulate local pH values

497

and raise ΩAr, which could thereby enhance the calcification rates of nearby corals.

498

However, pH and ΩAr were similar in the control and seagrass mesocosms. It is

499

nevertheless possible that the seagrasses influenced coral calcification rates by other

500

means, as discussed below.

501

Seagrasses compete with macroalgae for nutrients (Alexandre et al., 2017), which

502

likely accounts for why macroalgal growth was lower in the seagrass mesocosms.

503

Seagrass could also have reduced the degree of nutrient competition between

504

macroalgae and P. damicornis, thereby accounting for (indirectly) the elevated coral

505

calcification rates in the seagrass mesocosms. Corals can survive in oligotrophic

506

systems because they can obtain nutrients from diverse sources, namely via the

507

photosynthetic algae (family Symbiodinaceae) living in their tissues (Yonge, 1931;

508

Jackson & Yellowlees, 1990; Ceh et al., 2013). However, autotrophic corals still rely on

509

exogenous nutrients and therefore compete with primary producers such as macroalgae,

510

periphyton, and seagrasses for nutrients in oligotrophic coral reef ecosystems. Our

511

results showed that macroalgae are likely to bloom and rapidly consume nutrients in the

512

water in response to elevated pCO2 levels; this may account for why phosphate

513

concentrations were barely detectable in the control, algae-enriched mesocosms. We

514

surmise that this lack of phosphate could be another driver of the observed reduction in

515

coral calcification in the seagrass-free control mesocosms given the importance of

516

phosphate in coral photosynthesis (Annis and Cook, 2002). That being said,

517

Symbiodinaceae dinoflagellates can obtain phosphate from dissolved organic sources,

518

as well (Jackson and Yellowlees, 1990), and so this phosphate limitation hypothesis

519

remains speculative.

31

520

The overall effects of seagrass on coral reef mesocosms can be further examined via

521

assessment of the community metabolism data. In general, there is a positive

522

relationship between algal biomass and GPP (Mulholland et al., 2001). Herein the GPP,

523

NEP, and ER were all higher in the high-algal biomass controls under OA conditions,

524

and the differences in GPP, NEP, and ER between the seagrass mesocosms and the

525

controls became greater when the seawater temperature was increased to 28°C. When

526

the temperature reached 31°C, the NEP in all mesocosms declined, although the NEP in

527

the controls was still higher than in the seagrass mesocosms. The decline in NEP at

528

31°C is likely due to reduced macroalgal biomass at this temperature, as has been

529

documented in other studies of subtropical algae (Koch et al., 2013) (including the

530

macroalga Codium edule in Nanwan Bay, Taiwan (Lin et al., 2007). Macroalgal

531

degradation in our controls at 31°C could also account for the increase in ER at this

532

temperature.

533 534 535

5. Conclusions The increase in DIC concentration in the seawater as a combined effect of OA and

536

rising temperatures stimulated the growth of macroalgae, which may have preferentially

537

exploited CO2 as their major carbon source. However, the growth of macroalgae was

538

less in the seagrass mesocosms than in the controls. OA did not have a significant effect

539

on the coral P. damicornis. However, the calcification rates of the corals were higher in

540

the seagrass mesocosms than in the controls, potentially as a result of competitive

541

interactions between the seagrass and macroalgae. Macroalgal and coral growth both

542

suffered at 31°C under OA conditions. In contrast, seagrass shoot density, Fv/Fm, and

543

leaf growth rate all increased with temperature. Consequently, the climate change

32

544

factor-associated decline in NEP and ER in the seagrass mesocosms was less than in the

545

controls, indicating that the presence of seagrass in the mesocosms can help stabilize

546

(i.e., buffer) the system’s metabolism in response to projected climate change stressors.

547 548

Acknowledgments

549

This work was funded by 1) a research grant from the Ministry of Science and

550

Technology (MOST) of Taiwan (MOST 105-2621-B-259-001 to PJL and HJL) and 2)

551

the “Innovation and Development Center of Sustainable Agriculture” project

552

administered by the “Featured Areas Research Center Program” within the framework

553

of Taiwanese Ministry of Education’s “Higher Education Sprout Project.” ABM was

554

supported by a postdoctoral research fellowship from the Khaled bin Sultan Living

555

Oceans Foundation during the time at which the research project was undertaken.

556 557

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Author contributions

43

808

PJL and HJL conceived the ideas and designed the experiments; SJA collected and

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analyzed the data; HJL and ABM drafted the manuscript. All authors read and approved

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the final manuscript.

811 812

Competing interests: The authors declare no competing interests.

44

Figure captions Fig. 1. (A) The coral reef mesocosm facility. (B) The front side of the mesocosm, which featured corals and giant clams and (C) the rear side of the mesocosm, which housed the seagrasses. The black plastic mesh screen evident (~1 m2) in (B)-(C) (between the front and rear sides) prevented seagrass grazing by sea urchins and served, additionally, as settlement material for macroalgae (see below for details). Fig. 2. Seagrass (A) shoot density, (B) leaf growth rate, and (C) maximum quantum yield of photosystem II (Fv/Fm) across the four stages (denoted by shading) of the experiment (mean±SE; n=3). Lowercase letters adjacent to experimental stage at the top of each panel signify significant differences (Tukey’s p<0.05) between the means for each experimental stage, as repeated measures ANOVAs detected significant overall effects of ocean acidification [OA] (from Stage I to II) and combined effects of OA and warming (from Stage II to IV) for each response variable (Supplementary tables 4 and 5). In all cases, the group labeled “a” possessed the lowest value of the respective response variable. Fig. 3. The growth rate of macroalgae in control and seagrass mesocosms (mean±SE; n=3) for the latter three stages of the experiment. No macroalgae were observed during Stage I (prior to ocean acidification [OA]). Lowercase letters at the top of the figure signify significant differences (Tukey’s p<0.05) across stages. Fig. 4. (A) Maximum, dark-adapted yield of photosystem II (Fv/Fm) and (B) calcification rates of corals in response to ocean acidification (OA) and warming (mean±SE; n=3) in all four and the latter three experimental stages, respectively. Lowercase letters adjacent to experimental stage or treatment names at the top of

45

each panel signify significant differences (Tukey’s p<0.05) between experimental stages and seagrass (Sg) and control (Con) mesocosms when the repeated measures ANOVAs (Supplemental tables 6 and 7) detected a significant overall effect of stage alone (a) or stage x treatment (b), respectively. In all cases, the group labeled “a” possessed the lowest value of the respective response variable. Fig. 5. Community metabolism parameters in control (Con ) and seagrass (Sg) mesocosms (n=3) at each of four experimental stages (mean±SE). (A) ecosystem respiration (ER), (B) gross primary production (GPP), (C) net ecosystem metabolism (NEP), and (D) P/R ratio. Lowercase letters adjacent to experimental stage or treatment names at the top of each panel signify significant differences (Tukey’s p<0.05) between experimental stages (b-d), treatment (b), and/or the interaction of stage and treatment (a, c) when the repeated measures ANOVAs (Supplemental tables 6 and 7) detected significant overall effects in the respective comparisons. In all cases, the group labeled “a” possessed the lowest value of the respective response variable.

46

Supplementary information Apex display

Network cable

Apex base

Temperature probe

Energy Bar 8

pH probe

ORP probe

Supplementary fig. 1. The Apex AquaController™ system used to regulate the temperature and pH of the six mesocosms.

47

Supplementary table 1. Physical and chemical characteristics of the seawater in the control (T2, T4, and T6) and seagrass mesocosms (T1, T3, and T5) and the photosynthetic efficiency (Fv/Fm; i.e., maximum, dark-adapted yield of photosystem II) of the seagrass Thalassia hemprichii before the experiment. Values in cell represent means. DIC=dissolved inorganic carbon. DO=dissolved oxygen. NA=not assessed. TA=total alkalinity.

pH Temperature (˚C) DO (mg L-1) Salinity pCO2 (μatm) TA (μmol kg-1) ΩAr DIC (μmol kg-1) HCO3- (μmol kg-1) CO32- (μmol kg-1) CO2 (μmol kg-1) PO43- (μmol L-1) NH4+ (μmol L-1) NO2- (μmol L-1) NO3- (μmol L-1) Seagrass Fv/Fm

T1

T2

T3

T4

T5

T6

7.92 26.1 6.70 35.30 462 2189 2.88 1933 1738 182 13 0.016 0.077 0.011 0.020 0.790

7.92 26.4 6.65 35.30 589 2182 2.43 1972 1802 153 16 0 0.024 0.014 0.004 NA

7.92 26.0 6.70 35.10 450 2189 2.93 1929 1732 184 13 0.030 0.026 0.009 0.056 0.794

7.95 26.0 6.70 35.03 449 2182 2.92 1923 1727 183 13 0.009 0.028 0.005 0.029 NA

7.97 25.9 6.71 35.07 448 2299 3.22 2017 1803 202 12 0.009 0.018 0.007 0.033 0.791

7.91 26.1 6.68 35.15 465 2202 2.90 1946 1750 182 13 0 0.009 0.006 0.012 NA

48

Supplementary table 2. Two-way repeated measures ANOVA results of seagrass presence and ocean acidification (OA) (i.e., from experimental stage I to II) on seawater quality and irradiance. Statistically significant findings (p<0.05) have been highlighted in bold font. DIC=dissolved inorganic carbon. DO=dissolved oxygen. PAR=photosynthetically active radiation. TA=total alkalinity.

pH Temperature (˚C) PAR (µmol m-2 s-1) DO (mg L-1) Salinity pCO2 (μatm) TA (μmol kg-1) ΩAr DIC (μmol kg-1) HCO3- (μmol kg-1) CO32- (μmol kg-1)† CO2 (μmol kg-1)

Seagrass presence F(1, 4)=1.015, p=0.371 F(1, 4)=0.020, p=0.894 F(1, 4)=1.367, p=0.307 F(1, 4)=0.072, p=0.802 F(1, 4)=0.477, p=0.528 F(1, 4)=0.305, p=0.610 F(1, 4)=2.373, p=0.198 F(1, 4)=2.286, p=0.205 F(1, 4)=2.340, p=0.201 F(1, 4)=2.229, p=0.210 F(1, 4)=2.181, p=0.214 F(1, 4)=0.471, p=0.530

OA F(1, 4)=171.202, p<0.001 F(1, 4)=1.780, p=0.253 F(1, 4)=0.716, p=0.445 F(1, 4)=57.316, p=0.002 F(1, 4)=4.863, p=0.092 F(1, 4)=508.342, p<0.001 F(1, 4)=0.092, p=0.777 F(1, 4)=388.042, p<0.001 F(1, 4)=26.830, p=0.007 F(1, 4)=55.032, p=0.002 F(1, 4)=627.699, p<0.001 F(1, 4)=482.845, p<0.001

Interaction F(1, 4)=0.820, p=0.416 F(1, 4)=0.081, p=0.790 F(1, 4)=4.465, p=0.102 F(1, 4)=0.207, p=0.673 F(1, 4)=0.155, p=0.714 F(1, 4)=2.023, p=0.228 F(1, 4)=0.526, p=0.509 F(1, 4)=5.282, p=0.083 F(1, 4)=0.025, p=0.883 F(1, 4)=0.024, p=0.886 F(1, 4)=6.441, p=0.064 F(1, 4)=1.980, p=0.232

PO43- (μmol L-1)

F(1, 4)=1.907, p=0.239

F(1, 4)=0.152, p=0.716

F(1, 4)=1.273, p=0.322

NH4+ (μmol L-1)

F(1, 4)=2.688, p=0.176

F(1, 4)=80.646, p<0.001

F(1, 4)=1.837, p=0.247

F(1, 4)=2.522, p=0.187

F(1, 4)=40.752, p=0.003

F(1, 4)=3.625, p=0.130

F(1, 4)=1.954, p=0.235

F(1, 4)=11.659, p=0.027

F(1, 4)=0.515, p=0.513

-

NO2 (μmol

L-1)

NO3- (μmol L-1) †square-root transformed data.

49

Supplementary table 3. Two-way repeated measures ANOVA results of seagrass (Sg) presence and the combined treatment of ocean acidification (OA) and warming (i.e., from experimental stage II to IV) on seawater quality and irradiance; statistically significant findings (p<0.05) have been highlighted in bold, and lowercase letters in the “Tukey’s test” column signify significant differences (p<0.05) across combined treatment of OA and warming. In all cases, the group labeled “a” possessed the lowest value of the respective response variable. Con=control. DIC=dissolved inorganic carbon. DO=dissolved oxygen. PAR=photosynthetically active radiation. TA=total alkalinity.

50

pH Temperature (˚C)

Seagrass presence F(1, 4)=1.731, p=0.259 F(1, 4)=0.054, p=0.828

OA and warming F(2, 8)=3.932, p=0.065 F(2, 8)=9132.432, p<0.001

Interaction F(2, 8)=0.433, p=0.663 F(2, 8)=0.331, p=0.728

PAR (µmol m-2 s-1)

F(1, 4)=0.158, p=0.712

F(2, 8)=0.448, p=0.654

F(2, 8)=1.828, p=0.222

DO (mg L-1)

F(1, 4)=0.458, p=0.536

F(2, 8)=9602.524, p<0.001

F(2, 8)=0.354, p=0.712

25a 28b 31c

Salinity

F(1, 4)=1.266, p=0.323

F(2, 8)=341.912, p<0.001

F(2, 8)=0.224, p=0.804

25a 28b 31c

pCO2 (μatm)

F(1, 4)=0.041, p=0.850

F(2, 8)=11.915, p=0.004

F(2, 8)=1.439, p=0.293

28a 25b 31b

TA (μmol kg-1)

F(1, 4)=0.114, p=0.752

F(2, 8)=12.746, p=0.003

F(2, 8)=1.441, p=0.292

25a 28b 31b

ΩAr

F(1, 4)=0.106, p=0.761

F(2, 8)=101.400, p<0.001

F(2, 8)=1.389, p=0.304

25a 31b 28c

DIC (μmol kg-1)

F(1, 4)=0.113, p=0.753

F(2, 8)=6.557, p=0.021

F(2, 8)=1.400, p=0.301

25a 28ab 31b

HCO3- (μmol kg-1)

F(1, 4)=0.111, p=0.755

F(2, 8)=4.760, p=0.043

F(2, 8)=1.373, p=0.307

25a 28ab 31b

CO32- (μmol kg-1)

F(1, 4)=0.111, p=0.755

F(2, 8)=103.039, p<0.001

F(2, 8)=1.416, p=0.298

25a 28b 31b

CO2 (μmol kg-1)

F(1, 4)=0.020, p=0.893

F(2, 8)=13.027, p=0.003

F(2, 8)=1.319, p=0.320

28a 25b 31b

PO43- (μmol L-1)

F(1, 4)=9.363, p=0.038

F(2, 8)=0.148, p=0.865

F(2, 8)=0.304, p=0.746

Sga Conb

NH4+ (μmol L-1)

F(1, 4)=3.716, p=0.126

F(2, 8)=3.182, p=0.096

F(2, 8)=0.367, p=0.704

NO2- (μmol L-1)

F(1, 4)=5.025, p=0.088

F(2, 8)=52.305, p<0.001

F(2, 8)=7.010, p=0.017

NO3- (μmol L-1)

F(1, 4)=4.935, p=0.090

F(2, 8)=9.605, p=0.007

F(2, 8)=4.014, p=0.062

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Tukey’s test 31a 28b 25c

31a 28b 25b

Supplementary table 4. One-way repeated measures ANOVA results of the effect of ocean acidification (OA) on the seagrass Thalassia hemprichii in seagrass mesocosms only from experimental stage I to II. Statistically significant findings (p<0.05) has been highlighted in bold. F(1,2) Shoot density (shoot m-2)

p

75.184 0.013 week-1)

Rate of shoot density increase (% Seagrass leaf Fv/Fm Seagrass leaf growth rate (mm shoot-1 day-1)

1.631 0.330 31.687 0.030 19.494 0.048

Seagrass leaf productivity (mg DW shoot-1 day-1)

5.726

0.139

Aboveground biomass (mg DW shoot-1)

0.942

0.434

Seagrass biomass (mg DW shoot-1) Belowground/aboveground (R/S) ratio

0.502 2.615

0.552 0.247

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Supplementary table 5. One-way repeated measures ANOVA results of the combined treatment of ocean acidification (OA) and warming (i.e., from experimental stage II to IV) on the seagrass Thalassia hemprichii. Statistically significant findings (p<0.05) have been highlighted in bold font. Lowercase letters in the “Tukey’s test” column signify significant differences (p<0.05) across combined treatment of OA and warming. In all cases, the group labeled “a” possessed the lowest value of the respective response variable.

Shoot density (shoot m-2)

63.393

Tukey's test a b c <0.001 31 28 25

Rate of shoot density increase (% week-1) Seagrass leaf Fv/Fm Seagrass leaf growth rate (mm shoot-1 day-1)

5.074 10.786 57.758

0.080 0.024 0.001

Seagrass leaf productivity (mg DW shoot-1 day-1)

3.401

0.137

Aboveground biomass (mg DW shoot-1)

3.975

0.112

Seagrass biomass (mg DW shoot-1) Belowground/aboveground (R/S) ratio

6.841 0.190

0.051 0.834

F(2,4)

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p

31a 28ab 25b 31a 28a 25b

Supplementary table 6. Two-way repeated measures ANOVA results of seagrass presence and ocean acidification (OA) on 1) Fv/Fm of the coral Pocillopora damicornis, 2) system metabolism parameters from Stage I (ambient pCO2 and temperature) to II (OA and ambient temperature). Statistically significant findings (p<0.05) have been highlighted in bold font.

Coral Fv/Fm

Seagrass presence F(1, 4)=0.322 , p=0.601

ER (g O2 m-2 d-1)

F(1, 4)=0.279, p=0.625

GPP (g O2 m-2 d-1)

F(1, 4)=2.037, p=0.227

NEP (g O2 m-2 d-1)

F(1, 4)=4.567, p=0.099

GPP/ ER (P/R) ratio

F(1, 4)=0.0194, p=0.896

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OA Interaction F(1, 4)=3.058 , p=0.155 F(1, 4)=0.030, p=0.871 F(1, 4)=0.0199, F(1, 4)=2.471, p=0.191 p=0.895 F(1, 4)=4.734, p=0.095 F(1, 4)=1.370, p=0.307 F(1, 4)=12.413, F(1, 4)=11.328, p=0.028 p=0.024 F(1, 4)=0.431, p=0.547 F(1, 4)=1.863, p=0.244

Supplementary table 7. Two-way repeated measures ANOVA results of seagrass (Sg) presence and the combined treatment of ocean acidification (OA) and warming (i.e., from experimental Stage II to IV) on the Fv/Fm and calcification rate of the coral Pocillopora damicornis, the macroalgal growth rate, and system metabolism parameters. Statistically significant findings (p<0.05) have been highlighted in bold font, and lowercase letters in the “Tukey’s test” column signify significant differences (p<0.05) across either seagrass (Sg) presence or combined treatment of OA and warming. In all cases, the group labeled “a” possessed the lowest value of the respective response variable. “Con” =control mesocosms. 　

Seagrass presence

OA and warming

Coral Fv/Fm

F(1, 4)=0.128, p=0.739

Coral calcification rate (mg CaCO3 d-1) Macroalgal growth rate (g d-1) ER (g O2 m-2 d-1) GPP (g O2 m-2 d-1) NEP (g O2 m-2 d-1) GPP/ER (P/R) ratio

F(1, 4)=4.767, p=0.094 F(2, 8)=57.146, p<0.001 F(1, 4)=1.473, p=0.292 F(2, 8)=5.347, p=0.034 F(1, 4)=8.335, p=0.045 F(2, 8)=57.679, p<0.001 F(1, 4)=74.113, p=0.001 F(2, 8)=6.662, p=0.020 F(1, 4)=3.542, p=0.133 F(2, 8)=26.118, p<0.001 F(1, 4)=0.074, p=0.799 F(2, 8)=173.840, p<0.001

Interaction

F(2, 8)=11.233, p=0.005 F(2, 8)=0133, p=0.877

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Tukey’s test 25a 28ab 31b

F(2, 8)=5.414, p=0.033 F(2, 8)=1.488, p=0.282 28a 25ab 31b F(2, 8)=7.503, p=0.015 F(2, 8)=2.712, p=0.126 Sga Conb, 28a 31ab 25b F(2, 8)=0.458, p=0.648 25a 28a 31b F(2, 8)=1.428, p=0.295 25a 28b 31c

Supplementary fig. 2. The growth of the macroalga Dictyota bartayresiana in the seagrass and control mesocosms in the first and second (“acidification”) experimental stages (both at 25°C). Tank No.

Control mesocosms First stage Acidification (stage II)

Tank No.

T2

T1

T4

T3

T6

T5

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Seagrass mesocosms First stage Acidification (stage II)

Conceptual model of climate change (ocean acidification [OA] and seawater warming) effects on coral reef mesocosms that either do (light blue) or do not (blue) feature seagrass beds. Solid lines denote abiotic effects (i.e., OA or OA+warming to 31C), whereas dotted lines depict effects of co-incubation with seagrass. CCM=carbon concentrating mechanism. ER=ecosystem respiration, GPP=gross primary production, NEP=net ecosystem metabolism, and P/R=photosynthesis/respiration ratio.

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Highlights 

The combined effect of OA and rising temperatures stimulated the growth of macroalgae.



OA resulted in higher coral calcification rates when corals were co-incubated with seagrass.



Macroalgal growth was lower in seagrass-containing mesocosms.



Coral and macroalgal, but not seagrass, growth suffered at 31°C under OA conditions.



Seagrass helped to stabilize the system’s metabolism in response to projected climate change stressors.

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