Coral Reefs

, Volume 34, Issue 3, pp 955–966 | Cite as

Effects of seawater acidification on a coral reef meiofauna community

  • V. C. Sarmento
  • T. P. Souza
  • A. M. Esteves
  • P. J. P. Santos
Report

Abstract

Despite the increasing risk that ocean acidification will modify benthic communities, great uncertainty remains about how this impact will affect the lower trophic levels, such as members of the meiofauna. A mesocosm experiment was conducted to investigate the effects of water acidification on a phytal meiofauna community from a coral reef. Community samples collected from the coral reef subtidal zone (Recife de Fora Municipal Marine Park, Porto Seguro, Bahia, Brazil), using artificial substrate units, were exposed to a control pH (ambient seawater) and to three levels of seawater acidification (pH reductions of 0.3, 0.6, and 0.9 units below ambient) and collected after 15 and 30 d. After 30 d of exposure, major changes in the structure of the meiofauna community were observed in response to reduced pH. The major meiofauna groups showed divergent responses to acidification. Harpacticoida and Polychaeta densities did not show significant differences due to pH. Nematoda, Ostracoda, Turbellaria, and Tardigrada exhibited their highest densities in low-pH treatments (especially at the pH reduction of 0.6 units, pH 7.5), while harpacticoid nauplii were strongly negatively affected by low pH. This community-based mesocosm study supports previous suggestions that ocean acidification induces important changes in the structure of marine benthic communities. Considering the importance of meiofauna in the food web of coral reef ecosystems, the results presented here demonstrate that the trophic functioning of coral reefs is seriously threatened by ocean acidification.

Keywords

Coral reefs Ocean acidification Climate change Benthos Marine Park 

Introduction

Approximately 30 % of all anthropogenic CO2 emitted has been absorbed by the ocean surface (Sabine et al. 2004). Ocean uptake of CO2 will help to moderate future climate change, but when carbon dioxide dissolves in the ocean, it lowers the pH and causes changes in the ocean’s CaCO3 system (Feely et al. 2004, 2009). These changes, often referred to as ‘ocean acidification,’ are already occurring and are expected to intensify in the future. Surface ocean pH is already 0.1 units lower than pre-industrial levels (Caldeira and Wickett 2003). However, estimates of future atmospheric and oceanic CO2 concentrations based on the Intergovernmental Panel on Climate Change emission scenarios of human activities suggest that by the end of this century, CO2 levels could reach from 500 to 1400 ppm, and even exceed 1900 ppm by around the year 2300 (Caldeira and Wickett 2003; IPCC 2013). The corresponding decrease in pH would be about 0.3–0.5 pH units in surface waters relative to pre-industrial levels by the year 2100 (Caldeira and Wickett 2003; Feely et al. 2009; IPCC 2013) and about 0.8 units by 2300 (Caldeira and Wickett 2003, 2005).

Ocean acidification poses risks to all marine ecosystems, but coral reefs are widely recognized as the ecosystem that is most threatened by ocean acidification (Hoegh-Guldberg et al. 2007; Kleypas and Yates 2009; Fabricius et al. 2011; IPCC 2014; van Hooidonk et al. 2014). Coral reefs constitute about one-sixth of the world’s coastline and are the most biologically diverse habitats in the oceans. They also have an important role in shoreline protection and support a complex food web (Birkeland 1997; Roberts et al. 2002; Castro and Huber 2010; Gutiérrez et al. 2011). These features indicate that coral reefs provide essential ecosystem services and also provide direct and indirect economic benefits related to fisheries and ecotourism (Wilkinson 1996; Maida and Ferreira 1997; White et al. 2000; Hoegh-Guldberg et al. 2007).

Our present understanding of the impacts of ocean acidification on coral reef ecosystems is almost entirely limited to single-species studies of highly calcifying organisms, particularly those that are critical to the formation of habitats (e.g., coral species) or their maintenance (e.g., grazing echinoderms; e.g., Jokiel et al. 2008; Kleypas and Yates 2009; Morita et al. 2009; Byrne et al. 2013; De’ath et al. 2013; Uthicke et al. 2014). On the other hand, studies at the community level are still incipient. Fabricius et al. (2011, 2014) investigated the consequences of exposure to high CO2 on coral reef-associated macroorganism communities around three shallow volcanic CO2 seeps in Papua New Guinea. However, to our knowledge, no investigation on coral reef meiofauna communities has been conducted to date.

On coral reefs, a major source of primary productivity is derived from the phytal. This environment is often the dominant microhabitat on coral reefs, where algal turfs can cover 30–80 % of the total surface area (Maida and Ferreira 1997; Fabricius and De’ath 2001; Wismer et al. 2009; Hoey and Bellwood 2010). Meiofauna is one of the assemblages inhabiting this reef phytal environment. These organisms are likely to be more abundant than macrofauna by at least an order of magnitude (Gibbons and Griffiths 1986) and include representatives from almost all metazoan phyla. Meiofauna densities of up to 106 individuals m−2 of turf coverage are not uncommon, and some phytal environments are considered ‘hot spots of meiofauna production,’ reaching levels of around 10 g C m−2 yr−1 (Giere 2009). Meiofauna organisms are a biologically and ecologically distinct group of metazoans, operationally defined by their small size (Giere 2009). The metazoan meiofauna is a key component of the coastal benthos, contributing significantly to energy transfer to higher trophic levels (Danovaro et al. 2007; Kramer et al. 2013). Furthermore, members of the meiofauna community can be a useful tool for studies of human impacts (Kennedy and Jacoby 1999; Giere 2009).

Benthic community variations are strongly influenced by the type of substrate (Snelgrove and Butman 1994; Underwood and Chapman 2006). Furthermore, the wide variability in community structure and diversity caused by habitat heterogeneity can often complicate experiments on natural communities (Underwood and Chapman 1996), and it hampers efforts to separate the changes caused by anthropogenic disturbance from those arising from natural variations (Bishop 2005). Artificial substrate units (ASUs) have been used to overcome these problems, allowing the collection of a standardized community (Mirto and Danovaro 2004; Bishop 2005; Gobin and Warwick 2006) and have proved to be an effective method to represent natural communities (Mirto and Danovaro 2004; De Troch et al. 2005). ASUs have been widely applied in recent studies to assess the effects of climate change on benthic communities (Cigliano et al. 2010; Hale et al. 2011; Christen et al. 2013).

Together with the risk that ocean acidification will modify benthic communities, we must consider the great uncertainty about how the impacts of ocean acidification will affect the lower trophic levels, such as the meiofauna. The present study tested the hypothesis that exposure to different levels of seawater acidification that could be caused by global climate change will lead to strong modifications of the phytal meiofauna community from a coral reef, in a mesocosm experiment.

Materials and methods

Artificial substrate units (ASUs) colonized by coral reef phytal meiofauna were used in order to collect a standardized and diverse community. Artificial turf (synthetic grass consisting of polyethylene strips 10 mm in height) was used as the ASU, as it mimics the turf algae that cover coral reefs (Kelaher 2003; Matias et al. 2007). Thirty-six ASUs (6 × 6 cm each) were tied up between two nylon ropes what give an appearance of a ‘belt.’ Five belts were set up (six ASUs per belt, distant from each other by 5 cm). Then, each belt was attached on the side of the reef formation called Recife de Fora (S 16°24′37.3″, W 38°59′02.2″). Recife de Fora is located about 9 km off of Porto Seguro city, on the southern coast of Bahia, Brazil. This reef formation is part of the Recife de Fora Municipal Marine Park created in 1998 (Leão and Dominguez 2000). All ASUs were placed in the same location, approximately 4 m deep in a sheltered area (Enseada do Morão), and were therefore exposed to similar conditions (temperature, sunlight, wave exposure; Fig. 1). The ASUs were left in the field for 30 d to allow colonization by a suitable meiofauna community (Mirto and Danovaro 2004; De Troch et al. 2005). Upon collection, each ASU was placed in a small plastic container and then transported for 1 h to the mesocosm facility located at Arraial d’Ajuda (Santos et al. 2014; Fig. 1).
Fig. 1

a Brazil coastline showing the state of Bahia, b Porto Seguro and Arraial d’Ajuda, and c Recife de Fora Municipal Marine Park

Four pH treatments were established with four replicates each. The control was the local/ambient seawater without manipulation, and the decreased pH levels used were 0.3, 0.6, and 0.9 units below the ambient seawater, corresponding to the three levels of acidification. These levels of decrease in the ambient seawater pH are based on predictions of ocean chemistry changes by the years 2100 and 2300, made by a range of models of atmospheric CO2 emissions (Caldeira and Wickett 2003, 2005; IPCC 2013).

The experimental setup consisted of 16 tanks that were continuously supplied with seawater at a rate of 8.33 L min−1. In this system, seawater is captured 500 m from the shore at an adjacent fringe reef and is pumped to four cisterns of 5000 L each. In each cistern, the seawater received one of the four pH treatments. CO2 gas was bubbled through the natural seawater in each cistern, lowering the pH level. Once the pH had fallen to the required level, the supply of CO2 was stopped. The control and the CO2-enriched seawater from each cistern supplied four tanks. The acidification process was controlled by a computerized system, Reef Angel© Controller, coupled to pH electrodes (Gehaka 09RBCN). Reef Angel© Controller is an open-source aquarium controller that allows the level of acidification to follow environmental variations of the pH of seawater collected in the field. Thus, daily and/or seasonal variations are replicated in the tanks. The mesocosm tanks received only natural sunlight and therefore followed natural day/night cycles. To mimic the amount of incident light on the reefs, the tanks were covered with a 70 % shade screen, which is equivalent to the mean parameters measured in situ at 2.5 m depth on the Recife de Fora reef (about 250 µmol photons m−2 s−1).

At the mesocosm facility, four ASUs were randomly selected and preserved in 4 % formalin. These ASUs were used to characterize the community structure before the start of the exposure. The 32 remaining ASUs were randomly allocated to the four treatments. Two ASUs were placed in each of the 16 tanks. No food was supplied. The ASUs remained in the tanks for 3 d before the exposure started on October 30, 2012. From each tank, one ASU was collected after 15 d (14 November 2012) and another after 30 d (29 November 2012). Each sample was preserved in 4 % formalin. During the exposure period, the pH and temperature of the water from each cistern were monitored daily, every 15 min by the Reef Angel© Controller. Measurements of salinity (Instrutemp ITREF 10 optical refractometer), nutrients (Hach DR 890 colorimeter with the reagents NitraVer X and PhosVer 3 for nitrate and phosphate, respectively), and light intensity (LI-COR, LI 250A Light Meter, LI-193 Underwater Spherical Quantum Sensor) were taken weekly. Temperature data from the strongest level of acidification (reduction by 0.9 from the seawater control pH) are not presented because the sensor malfunctioned. Precipitation data were obtained from the National Institute of Meteorology, Brazil (INMET). Nine samples for total alkalinity (TA) of the seawater supplying the mesocosm system were analyzed only in February 2015. An alkalinity titrator (AS-ALK2, Apollo SciTech Inc., Bogart, GA, USA) was used following Dickson et al. (2007), and certified reference materials were obtained from the laboratory of A. G. Dickson, Scripps Institution of Oceanography. Because of the open mesocosm system, which continuously supplied all treatments, it is expected that the TA of the seawater will not change when bubbled with CO2 gas (Dickson et al. 2007; Riebesell et al. 2010). The pCO2s, Ωca, and Ωar for each treatment were calculated from the TA and mean pH using CO2calc version 1.2.9 (Robbins et al. 2010).

In the laboratory, the fauna was extracted by manual elutriation with filtered water through geological sieves. Samples were sieved through a 300-μm mesh, and a 45-μm mesh was used to retain the meiobenthic organisms. The fraction remaining on the 45-μm mesh was extracted six times with colloidal silica (diluted with distilled water to a final density of 1.18 g cm−3) flotation. The meiofauna retained were analyzed under a Leica EZ4 stereomicroscope to evaluate the densities of the major groups.

Statistical analysis

Permutational multivariate analyses of variance (PERMANOVA; Anderson 2001; McArdle and Anderson 2001) based on Bray–Curtis dissimilarities on meiofauna log (x + 1)-transformed data were used to evaluate the impact of seawater acidification (factor pH) on the structure of communities, considering the two exposure periods, 15 and 30 d (factor Time). For all analyses, 9999 random permutations were used. Pairwise a posteriori comparisons (the multivariate version of the t statistic) were made when the interaction between factors was significant. A similarity percentage (SIMPER) analysis was applied to determine which groups were responsible for the dissimilarities among the pH treatments for the samples collected after 15 and 30 d. Multi-dimensional scaling (MDS) was used to represent the Bray–Curtis matrix graphically in a two-axis space. The relationship between the density of the major meiofauna groups and the four pH levels was assessed by linear replicated regression analyses, separately for samples collected after 15 and 30 d of exposure.

PERMANOVA, SIMPER, and MDS were applied using the software Primer® 6 with add-on PERMANOVA+ (Plymouth Routines in Multivariate Ecological Researches). The linear regression analyses were performed using the software BioEstat 5.0. The level of significance was set at p < 0.05 for all analyses. Confidence intervals of 95 % (CI) were used to express the variation of the calculated means. Parametric statistical analysis followed Zar (1996).

Results

Experimental conditions

Figure 2 illustrates the pH levels monitored during the course of the experiment. Nominal pH treatments were successfully maintained throughout the 30-d exposure period (Table 1). The mean (±confidence interval, CI) daily total rainfall for the Porto Seguro region during November 2012 was 7.49 mm (±4.27 CI). However, precipitation was lower (4.84 mm, ±6.26 CI) in the first half of November than in the second (10.14 mm, ±5.73 CI). The mean temperature was also lower in the first half of the month (24.65, 24.45, and 24.62 °C) than in the second (25.7, 25.5, and 25.65 °C for pH treatments 8.1, 7.8, and 7.5, respectively). This pattern was also observed for pH. On average, pH levels were lower in the first half of the month (8.05, 7.70, 7.48, and 7.19) than in the second (8.14, 7.77, 7.54, and 7.23). Total alkalinity of the seawater supplying the mesocosm system was 2379.14 (±2.85 CI) µmol kg−1. The pCO2 values for the treatments were 351.8 (pH 8.1), 939.0 (pH 7.8), 1683.4 (pH 7.5), and 3494.3 µatm (pH 7.2). The Ωca and Ωar values were 5.89 and 3.89 (pH 8.1), 2.98 and 1.96 (pH 7.8), 1.86 and 1.23 (pH 7.5), and 0.97 and 0.64 (pH 7.2).
Fig. 2

Levels of pH in the tanks monitored during the 30-d exposure period

Table 1

Seawater physical and chemical conditions maintained in the tanks during the 30-d exposure period

 

pH

8.1

7.8

7.5

7.2

pH

8.10

7.74

7.51

7.21

0.004

0.008

0.006

0.007

Temperature (°C)

25.19

25.00

25.16

0.03

0.03

0.03

Salinity

35

35

35

35

0.39

0.41

0.37

0.34

Light (μmol photons m−2 s−1)

284.97

296.37

285.46

276.98

41.34

41.51

33.91

39.77

Nitrate (mg L−1)

0.98

0.98

0.88

0.85

0.20

0.15

0.05

0.06

Phosphate (mg L−1)

0.06

0.06

0.06

0.06

0.01

0.01

0.01

0.01

Values: mean ± 95 % CI

Effect of acidification on community

A total of 20,371 meiofauna organisms were counted. Meiofauna was composed of Copepoda harpacticoids (38.21 %), Polychaeta (21.45 %), Nematoda (15.86 %), Chironomidae larvae (13.56 %), Harpacticoid nauplii (3.48 %), Ostracoda (2.72 %), Turbellaria (2.68 %), Tardigrada (1.43 %), with Acari, Gastrotricha, and Oligochaeta (<1 %).

The MDS analysis representing the similarity matrix of meiofauna samples from the four pH treatments at the two sampling times (Fig. 3) showed a clear pattern of differentiation between samples collected after 15 and 30 d. However, for the 15-d samples, there was no pattern of difference among the different pH levels. On the other hand, after 30 d of exposure, there was a clear separation of both the control (pH 8.1) and pH 7.8 samples from the pH 7.5 and 7.2 samples. The PERMANOVA results confirmed the pattern shown in MDS and detected significant differences in the structure of the meiofauna community between samples collected after 15 and 30 d (factor time), among the four levels of pH (factor pH), and also for the interaction between the two factors (Table 2).
Fig. 3

Non-metric multi-dimensional scaling ordination plots for the Bray–Curtis similarity for the meiofauna community structure. (closed square) 8.1, (closed invertedtriangle) 7.8, (closed diamond) 7.5, (closed circle) 7.2. Closed symbols represent samples collected after 15 d, and open symbols after 30 d

Table 2

PERMANOVA results for the meiofauna communities exposed to different pH levels and collected after 15 and 30 d

Source

df

MS

F

p

Time (Ti)

1

566.04

8.67

<0.001

pH

3

126.23

1.93

0.020

Ti × pH

3

119.99

1.84

0.027

Residual

24

65.28

  

Significant values are highlighted in bold

Pairwise tests for samples collected after 15 d of exposure did not detect significant differences in the meiofauna community structure among the control and the acidification levels (p > 0.42 for all) or among the three levels of acidification (p > 0.25 for all). However, samples collected after 30 d of exposure showed a clear pattern of response to seawater acidification. Pairwise tests detected significant differences between the control and the pH 7.5 samples (t = 1.99, p = 0.029), and between the control and the pH 7.2 samples (t = 1.85, p = 0.028). No significant difference was detected between the control and pH 7.8 (t = 1.20, p = 0.18) or among the three levels of acidification (p > 0.06 for all).

SIMPER analyses showed that the dissimilarities among treatments were greater after 30 d, especially for comparisons between 8.1 and 7.5, and between 8.1 and 7.2; Nauplii was the group that contributed most to these dissimilarities (Table 3).
Table 3

Percent contribution (Contrib.  %) of meiofauna groups to average dissimilarity (Diss.) between different pH levels for samples collected after 15 and 30 d

8.1 versus 7.8

8.1 versus 7.5

8.1 versus 7.2

Diss. = 11.53

Contrib. %

Diss. = 10.53

Contrib. %

Diss. = 11.33

Contrib. %

Day 15

Nauplii

23.49

Tardigrada

22.77

Tardigrada

18.50

Tardigrada

19.70

Turbellaria

18.49

Acari

14.19

Acari

10.89

Nauplii

12.29

Nauplii

13.38

Ostracoda

9.53

Acari

11.89

Ostracoda

12.93

Turbellaria

8.98

Ostracoda

9.38

Turbellaria

10.09

Harpacticoida

7.58

Chiron. larvae

8.66

Chiron. larvae

8.41

Nematoda

5.99

Nematoda

6.64

Nematoda

6.08

Polychaeta

5.60

  

Oligocheta

5.65

    

Harpacticoida

4.79

8.1 versus 7.8

8.1 versus 7.5

8.1 versus 7.2

Diss. = 10.51

Contrib. %

Diss. = 16.36

Contrib. %

Diss. = 14.70

Contrib. %

Day 30

Turbellaria

14.02

Nauplii

21.58

Nauplii

16.53

Ostracoda

13.54

Ostracoda

12.66

Tardigrada

12.99

Tardigrada

13.30

Gastroticha

12.34

Ostracoda

10.70

Polychaeta

10.96

Nematoda

10.14

Turbellaria

10.39

Nematoda

10.09

Polychaeta

9.48

Polychaeta

10.07

Acari

9.45

Tardigrada

7.65

Nematoda

9.47

Nauplii

7.72

Acari

6.74

Acari

8.58

Chiron. larvae

7.71

Turbellaria

5.96

Gastroticha

8.21

Oligocheta

7.49

Chiron. larvae

4.59

Harpacticoida

5.10

Chiron. larvae Chironomidae larvae

Fluctuations in the density of total meiofauna and of dominant groups were observed between the field and control samples. However, at the end of the experiment, the density of total meiofauna and of the dominant groups increased in the control tanks (Fig. 4).
Fig. 4

Mean density (±95 % confidence intervals) of the main groups of meiofauna at different pH levels (8.1, 7.8, 7.5, and 7.2) and sampling times (15 and 30 d)

The results of the linear regression analyses indicated that many groups showed significant relationships between density and the different levels of acidification (Table 4). For samples collected after 15 d, only Turbellaria showed a positive relationship to acidification. On the other hand, for samples collected after 30 d, Nematoda, Ostracoda, Turbellaria, and Tardigrada showed a positive relationship between their densities and acidification. Harpacticoid nauplii was the only group that showed a negative relationship between density and acidification after 30 d of exposure (Fig. 4). However, adult harpacticoid density did not show a significant relationship to the different pH levels.
Table 4

Results of linear replicated regression analyses for the major groups of meiofauna (data transformation), degrees of freedom = 1;14

Group

Day 15

Day 30

F

p

f

p

Harpacticoida (untransf.)

0.556

0.526

0.285

0.607

Polychaeta (fourth root)

0.013

0.909

4.114

0.059

Nematoda (untransf.)

0.875

0.632

6.002

0.027

Chiron. larvae (untransf.)

2.974

0.104

0.104

0.749

Nauplii (untransf.)

2.405

0.140

6.470

0.022

Ostracoda (fourth root)

0.688

0.574

5.210

0.037

Turbellaria (ln(X+1))

4.538

0.049

4.603

0.048

Tardigrada (untransf.)

0.205

0.661

10.133

0.007

Total meiofauna (untransf.)

0.497

0.502

2.469

0.136

Significant values in bold

untransf. untransformed data, Chiron. larvae Chironomidae larvae)

Discussion

In the present study, the acidification system was able to maintain the levels of decrease in the pH treatments following the natural variation of the ‘control’ seawater. Thus, the meiofauna community was exposed to seawater that showed daily and/or seasonal environmental variations of its parameters, with only the level of acidity varying among treatments due to the amount of CO2 injected. Furthermore, the total density of meiofauna and their dominant groups in the control conditions increased at the end of the experiment. These results indicate that the conditions in the tanks were suitable for maintaining natural communities with the purpose of conducting studies on anthropogenic impacts such as ocean acidification.

When left in the field, ASUs are colonized by a wide spectrum of organisms (e.g., bacteria, microphytobenthos, meiofauna, and vagile macrofauna). An entire ecosystem, albeit on a small scale, is taken and maintained in the mesocosm system. No interference with the organisms, such as food, maintenance, or handling, was required. Despite the small scale of ASUs (36 cm2), they constitute a meaningful sampling universe in terms of statistical power to detect biologically important effects on meiofauna due to the small size and high abundance of these animals.

Studies on the effects of acidification on multispecies benthic communities have received increasing attention recently. However, most studies of shallow benthic communities have focused on macrofauna or large and conspicuous organisms (Hall-Spencer et al. 2008; Widdicombe et al. 2009; Cigliano et al. 2010; Hale et al. 2011; Kroeker et al. 2011; Fabricius et al. 2011, 2014; Christen et al. 2013). Studies with meiofauna communities have focused almost exclusively on the effects of direct injection of CO2 into the deep seafloor (carbon sequestration), with most of them conducted off central California (Barry et al. 2004; Carman et al. 2004; Thistle et al. 2005; Fleeger et al. 2010; Ishida et al. 2013). All of the very few studies on shallow-water meiofauna communities were from sediment/unconsolidated substrate (Kurihara et al. 2007; Dashfield et al. 2008; Widdicombe et al. 2009), and none were from coral reef environments.

Studies on meiofauna communities from shallow areas indicate that they tolerate ocean acidification. In a 56-d microcosm experiment with a meiobenthic community from sediment, Kurihara et al. (2007) found no significant impact in the abundance of meiofauna in response to elevated CO2 concentrations (pH 7.4). Widdicombe et al. (2009) found that exposure to acidified seawater significantly altered the community structure and reduced diversity for nematode assemblages in a mesocosm experiment. However, the largest differences were observed for pH 5.6 after 20 weeks, and the sediment type (mud or sand) played an important role in the differentiation of the nematode community structure. In a mesocosm experiment, Dashfield et al. (2008) found that the presence of a burrowing urchin was a key factor determining the response of the nematode community to the impact of ocean acidification (pH 7.5) and suggested that any nematode mortality is unlikely to be directly due to differences in pH.

In the present study, acidified seawater caused major changes in the structure of the meiofauna community. These changes were the result of divergent biological responses to acidification. We found that among the numerically dominant meiofauna taxa, the densities of Harpacticoida and Polychaeta did not show significant differences due to pH after 15 or 30 d. On the other hand, Nematoda, Ostracoda, Turbellaria, and Tardigrada exhibited their highest densities in low-pH treatments (especially at 7.5), while only the harpacticoid nauplii were strongly negatively affected by low pH.

Ocean acidification has been shown to have drastic effects on macrobenthic organisms (e.g., Dupont et al. 2010; Findlay et al. 2010; Byrne et al. 2013; Fabricius et al. 2014). However, the divergent patterns of response exhibited by meiofauna in this study are not uncommon. It appears that nematodes are likely to be able to withstand short-term exposure to even severe seawater acidification (Wieser et al. 1974; Takeuchi et al. 1997; Ishida et al. 2005; Kurihara et al. 2007; Dashfield et al. 2008; Widdicombe et al. 2009) and also to increase their densities under low-pH conditions (Hale et al. 2011). Similarly, the abundance of polychaetes appears not to be greatly affected by low pH (Hale et al. 2011; Kroeker et al. 2011; Calosi et al. 2013; Christen et al. 2013; Fabricius et al. 2014), and some species even became more abundant at the lowest pH investigated (Cigliano et al. 2010; Hale et al. 2011).

Investigations on the impact of any stressor should consider that other factors/drivers may be involved in the response exhibited by multi-species assemblages (individual performance, species interactions, food supply, and so on; Gaylord et al. 2015). Experiments with macrofaunal species have demonstrated that these organisms are highly sensitive to ocean acidification, with negative impacts on their survival, calcification, growth, reproduction, metabolic rates, and physiology (Bibby et al. 2007; Dupont and Thorndyke 2009; Ellis et al. 2009; Byrne et al. 2013; Ceballos-Osuna et al. 2013; Cumbo et al. 2013; De’ath et al. 2013; Sung et al. 2014). Considering that many macrofaunal organisms are meiofauna predators or competitors, the negative impacts on macrofauna could generate a top-down, indirect positive effect on meiofauna due to the release of or reduction in ecological pressures (Cigliano et al. 2010; Hale et al. 2011; Kroeker et al. 2011).

Another indirect impact on meiofauna may occur through a bottom-up effect of ocean acidification on microphytobenthos/primary producer communities. Ocean acidification can alter net primary production due to species-specific sensitivities to increased CO2 that change the structure of macroalgae (Porzio et al. 2011), diatoms (Johnson et al. 2013), bacteria (Webster et al. 2013), and biofilm communities (Witt et al. 2011). These modifications are followed by increases in primary production (Hargrave et al. 2009), diatom abundance and biomass (Johnson et al. 2013), biofilm production (Lidbury et al. 2012), and the abundance of bacteria and nanobenthos (Ishida et al. 2005, 2013). Kroeker et al. (2011) suggested that certain indirect effects of low pH could drive the tolerance response of some animals. They suggested that, because of the association between small crustaceans and algal turfs and canopies, the increased abundance of small crustaceans in extreme low-pH zones could be caused by the increased availability of habitat and food. The results presented by Hargrave et al. (2009) show how acidification can have a positive bottom-up effect on primary production and on benthic invertebrate consumers. The potential for ocean acidification to influence bottom-up and top-down processes (Gaylord et al. 2015) concords with the increases in density observed for many meiofauna groups in this study.

Changes in primary producer communities in response to ocean acidification may have even more subtle consequences for the maintenance and development of benthic populations that depend on them. For instance, there is a consensus that harpacticoid species are able to develop and reproduce while feeding on different diatoms, but that some algal species are more suitable; so although the copepods can survive, the ingestion of some diatoms or bacteria can drastically impact their development and reproductive success (Araújo-Castro and Souza-Santos 2005; Wyckmans et al. 2007; Dahl et al. 2009). Furthermore, indirect effects of ocean acidification can be expected for consumers because of changes in the nutritional quality of their prey (Rossoll et al. 2012). Thus, a ‘bloom’ of some specific diatom or bacteria that benefited from a low-pH environment could serve as food, although could not sustain the full population development of many harpacticoid species for longer periods. These patterns of response are in accordance with the divergent results found for the total densities of harpacticoids and their nauplii.

The absence of a response of polychaetes and harpacticoids could be the consequence of compensatory response, where reductions in the density of sensitive species are compensated by the opportunistic behavior of others. Opportunistic behavior has been documented for harpacticoid species under stress situations in a coral reef environment. In an assessment of the impact of phytal trampling, Sarmento and Santos (2012) showed that together with the reduction in several more-susceptible species, Amphiascopsis cinctus benefited from trampling, which resulted in a lack of differences in the total harpacticoid density.

The apparent higher tolerance observed for the benthic meiofauna in the present study may be related to physiological features of these animals. In contrast to the great vulnerability to high CO2 of calcifying organisms, marine invertebrate species that do not calcify in the larval stage or have poorly calcified exoskeletons (e.g., copepods, amphipods, and barnacles) appear to be resilient to near-future levels of pH/pCO2 (Kurihara et al. 2004; Ishida et al. 2005; Mayor et al. 2007; Kurihara 2008; Kurihara and Ishimatsu 2008; Dupont and Thorndyke 2009; Dupont et al. 2010; Findlay et al. 2010; Byrne 2012). Thus, it is probable that due to the poorly calcified cuticle of representatives of meiofauna such as the dominant crustaceans Copepoda Harpacticoida, but also Kinorhyncha, Tardigrada, and Nematoda (Ruppert et al. 2004; Giere 2009), the meiofauna community could withstand the effects of ocean acidification at the level tested in the present study.

Considering the direct impacts of ocean acidification on benthic organisms, tolerance to CO2 has been found to differ between life stages (e.g., larva and adult; (Kurihara 2008; Dupont et al. 2010; Hendriks and Duarte 2010). Adults exposed to hypercapnia could suffer physiological stress without showing high mortality rates. Such effects are expected to affect long-term growth and reproduction and may thus be harmful at population and species levels (Pörtner et al. 2004). In the present study, although acidification had no significant impact on harpacticoid density, their larval stages were negatively affected. The densities of nauplii were reduced, on average, by 29.2, 60.5, and 61.1 % in pH 7.8, 7.5, and 7.2, respectively, compared with the control after 30 d. Some studies with different copepod species (calanoids and harpacticoids) found that adult survival, body size, and growth were not affected by increased seawater acidity (Kurihara et al. 2004; Mayor et al. 2007; Kurihara and Ishimatsu 2008; Pascal et al. 2010), but others found large decreases in egg and naupliar production (Kurihara et al. 2004; Mayor et al. 2007; Fitzer et al. 2012, 2013). These sublethal effects of seawater acidification are in accordance with our results for the absence of response of total harpacticoid density and with the observed decreases in numbers of nauplii.

Some studies have exposed benthic communities to pH reductions >1 unit. In these studies, sharp decreases in density are not surprising, especially for calcifying animals, since such large changes in pH greatly exceed the range of natural environmental variability (Wieser et al. 1974; Widdicombe et al. 2009; Hale et al. 2011; Christen et al. 2013). Although most components of the meiobenthos are not lethally affected by elevated CO2, it is highly possible that increases in CO2 will have sublethal effects on reproduction, metabolism, and growth rate (Kurihara et al. 2004; Li and Gao 2012; Fitzer et al. 2012, 2013). The results presented also provide evidence of a negative effect on recruits (larval stages) of Harpacticoida, which may have serious consequences for the long-term population dynamics. It is very likely that the pattern of response shown by the major groups of meiofauna was due to changes in their species composition. Experiments with single meiofauna organisms at a lower taxonomic level are needed to more closely evaluate the impacts of increased CO2 and to provide a basis for evaluation of different sensitivities among meiofauna representatives.

Recent studies have revealed that benthic carnivorous fish are an abundant and important trophic link between a highly nutritious food source (harpacticoid copepods) and higher trophic levels (Kramer et al. 2012, 2013). Berkström et al. (2012) also showed that juveniles of many wrasses are highly dependent on a single food item (harpacticoid copepods) and warned of the potential risk to higher trophic levels if degradation of reefs extends to this resource (meiofauna). This evidence illustrates the important role of phytal environments, together with their associated meiofauna organisms (especially the diatom–harpacticoid–fish link), in the trophic structure and functioning of a coral reef ecosystem (Berkström et al. 2012; Kramer et al. 2012). It also highlights the fragility of this ecosystem if ocean acidification has major impacts on the meiofauna food base. Thus, our results help to demonstrate that the trophic functioning of coral reefs is seriously threatened by ocean acidification.

Notes

Acknowledgments

VC Sarmento gratefully acknowledges a PhD scholarship from the Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (FACEPE), and PJP Santos (CNPq 305417/2011-8) and AM Esteves (CNPq 312143/2013-3) acknowledge research fellowships from the Conselho Nacional de Ciência e Tecnologia (CNPq). We thank Alex M. Silva for help with meiofauna extraction and Dr. Janet W. Reid for English language revision. Special thanks are also due to the ‘Rede de Pesquisas Coral Vivo,’ to Petrobras and to the Arraial d’Ajuda Eco Parque, for all logistical assistance provided. We are grateful to the reviewers for their incisive and helpful comments on the manuscript.

References

  1. Anderson MJ (2001) A new method for non-parametric multivariate analysis of variance. Austral Ecol 26:32–46Google Scholar
  2. Araújo-Castro CMV, Souza-Santos LP (2005) Are the diatoms Navicula sp. and Thalassiosira fluviatilis suitable to be fed to the benthic harpacticoid copepod Tisbe biminiensis? J Exp Mar Biol Ecol 327:58–69CrossRefGoogle Scholar
  3. Barry JP, Buck KR, Lovera CF, Kuhnz L, Whaling PJ, Peltzer ET, Walz P, Brewer PG (2004) Effects of direct ocean CO2 injection on deep-sea meiofauna. J Oceanogr 60:759–766CrossRefGoogle Scholar
  4. Berkström C, Jones GP, McCormick MI, Srinivasan M (2012) Ecological versatility and its importance for the distribution and abundance of coral reef wrasses. Mar Ecol Prog Ser 461:151–163CrossRefGoogle Scholar
  5. Bibby R, Cleall-Harding P, Rundle S, Widdicombe S, Spicer J (2007) Ocean acidification disrupts induced defences in the intertidal gastropod Littorina littorea. Biol Lett 3:699–701PubMedCentralPubMedCrossRefGoogle Scholar
  6. Birkeland C (1997) Life and death of coral reefs. Chapman and Hall, New YorkCrossRefGoogle Scholar
  7. Bishop MJ (2005) Artificial sampling units: a tool for increasing the sensitivity of tests for impact in soft sediments. Environ Monit Assess 107:203–220PubMedCrossRefGoogle Scholar
  8. Byrne M (2012) Global change ecotoxicology: Identification of early life history bottlenecks in marine invertebrates, variable species responses and variable experimental approaches. Mar Environ Res 76:3–15PubMedCrossRefGoogle Scholar
  9. Byrne M, Lamare M, Winter D, Dworjanyn SA, Uthicke S (2013) The stunting effect of a high CO2 ocean on calcification and development in sea urchin larvae, a synthesis from the tropics to the poles. Philos Trans R Soc Lond B Biol Sci 368:20120439PubMedCentralPubMedCrossRefGoogle Scholar
  10. Caldeira K, Wickett M (2003) Anthropogenic carbon and ocean pH. Nature 425:365PubMedCrossRefGoogle Scholar
  11. Caldeira K, Wickett M (2005) Ocean model predictions of chemistry changes from carbon dioxide emissions to the atmosphere and ocean. J Geophys Res 110:1–12Google Scholar
  12. Calosi P, Rastrick SPS, Lombardi C, Guzman HJ, Davidson L, Jahnke M, Giangrande A, Hardege JD, Schulze A, Spicer JI, Gambi MC (2013) Adaptation and acclimatization to ocean acidification in marine ectotherms: an in situ transplant experiment with polychaetes at a shallow CO2 vent system. Proc R Soc Lond B Biol Sci 368:20120444CrossRefGoogle Scholar
  13. Carman KR, Thistle D, Fleeger JW, Barry JP (2004) Influence of introduced CO2 on deep-sea metazoan meiofauna. J Oceanogr 60:767–772CrossRefGoogle Scholar
  14. Castro P, Huber ME (2010) Marine Biology, 8th edn. The McGraw-Hill Companies, New YorkGoogle Scholar
  15. Ceballos-Osuna L, Carter HA, Miller NA, Stillman JH (2013) Effects of ocean acidification on early life-history stages of the intertidal porcelain crab Petrolisthes cinctipes. J Exp Biol 216:1405–1411PubMedCrossRefGoogle Scholar
  16. Christen N, Calosi P, McNeill CL, Widdicombe S (2013) Structural and functional vulnerability to elevated pCO2 in marine benthic communities. Mar Biol 160:2113–2128CrossRefGoogle Scholar
  17. Cigliano M, Gambi MC, Rodolfo-Metalpa R, Patti FP, Hall-Spencer JM (2010) Effects of ocean acidification on invertebrate settlement at volcanic CO2 vents. Mar Biol 157:2489–2502CrossRefGoogle Scholar
  18. Cumbo VR, Fan TY, Edmunds PJ (2013) Effects of exposure duration on the response of Pocillopora damicornis larvae to elevated temperature and high pCO2. J Exp Mar Bio Ecol 439:100–107CrossRefGoogle Scholar
  19. Dahl U, Lind CR, Gorokhova E, Eklund B, Breitholtz M (2009) Food quality effects on copepod growth and development: Implications for bioassays in ecotoxicological testing. Ecotoxicol Environ Saf 72:351–357PubMedCrossRefGoogle Scholar
  20. Danovaro R, Scopa M, Gambi C, Franschetti S (2007) Trophic importance of subtidal metazoan meiofauna: evidence from in situ exclusion experiments on soft and rocky substrates. Mar Biol 152:339–350CrossRefGoogle Scholar
  21. Dashfield SL, Somerfield PJ, Widdicombe S, Austen MC, Nimmo M (2008) Impacts of ocean acidification and burrowing urchins on within-sediment pH profiles and subtidal nematode communities. J Exp Mar Bio Ecol 365:46–52CrossRefGoogle Scholar
  22. De Troch M, Vandepitte L, Raes M, Suárez-Morales E, Vincx M (2005) A field colonization experiment with meiofauna and seagrass mimics: effect of time, distance and leaf surface area. Mar Biol 148:73–86CrossRefGoogle Scholar
  23. De’ath G, Fabricius K, Lough J (2013) Yes – Coral calcification rates have decreased in the last twenty-five years! Mar Geol 346:400–402CrossRefGoogle Scholar
  24. Dickson AG, Sabine CL, Christian JR (2007) Guide to best practices for ocean CO2 measurements. PICES Special Publication 3, SidneyGoogle Scholar
  25. Dupont S, Thorndyke MC (2009) Impact of CO2-driven ocean acidification on invertebrates early life-history – What we know, what we need to know and what we can do. Biogeosci Discuss 6:3109–3131CrossRefGoogle Scholar
  26. Dupont S, Dorey N, Thorndyke MC (2010) What meta-analysis can tell us about vulnerability of marine biodiversity to ocean acidification? Estuar Coast Shelf Sci 89:182–185CrossRefGoogle Scholar
  27. Ellis RP, Bersey J, Rundle SD, Hall-Spencer JM, Spicer JI (2009) Subtle but significant effects of CO2 acidified seawater on embryos of the intertidal snail, Littorina obtusata. Aquat Biol 5:41–48CrossRefGoogle Scholar
  28. Fabricius K, De’ath G (2001) Environmental factors associated with the spatial distribution of crustose coralline algae on the Great Barrier Reef. Coral Reefs 19:303–309CrossRefGoogle Scholar
  29. Fabricius KE, De’ath G, Noonan S, Uthicke S (2014) Ecological effects of ocean acidification and habitat complexity on reef-associated macroinvertebrate communities. Proc R Soc Lond B Biol Sci 281:20132479CrossRefGoogle Scholar
  30. Fabricius KE, Langdon C, Uthicke S, Humphrey C, Noonan S, De’ath G, Okazaki R, Muehllehner N, Glas MS, Lough JM (2011) Losers and winners in coral reefs acclimatized to elevated carbon dioxide concentrations. Nat Clim Chang 1:165–169CrossRefGoogle Scholar
  31. Feely RA, Doney SC, Cooley SR (2009) Ocean acidification: present conditions and future changes in a high-CO2 world. Oceanography 22:36–47CrossRefGoogle Scholar
  32. Feely RA, Sabine CL, Lee K, Berelson W, Kleypas J, Fabry VJ, Millero FJ (2004) Impact of anthropogenic CO2 on the CaCO3 system in the oceans. Science 305:362–366PubMedCrossRefGoogle Scholar
  33. Findlay HS, Kendall MA, Spicer JI, Widdicombe S (2010) Post-larval development of two intertidal barnacles at elevated CO2 and temperature. Mar Biol 157:725–735CrossRefGoogle Scholar
  34. Fitzer SC, Caldwell GS, Clare AS, Upstill-Goddard RC, Bentley MG (2013) Response of copepods to elevated pCO2 and environmental copper as co-stressors – A multigenerational study. PLoS One 8:e71257PubMedCentralPubMedCrossRefGoogle Scholar
  35. Fitzer SC, Caldwell GS, Close AJ, Clare AS, Upstill-Goddard RC, Bentley MG (2012) Ocean acidification induces multi-generational decline in copepod naupliar production with possible conflict for reproductive resource allocation. J Exp Mar Bio Ecol 418–419:30–36CrossRefGoogle Scholar
  36. Fleeger JW, Johnson DS, Carman KR, Weisenhorn PB, Gabriele A, Thistle D, Barry JP (2010) The response of nematodes to deep-sea CO2 sequestration: A quantile regression approach. Deep Sea Res Part I Oceanogr Res Pap 57:696–707CrossRefGoogle Scholar
  37. Gaylord B, Kroeker KJ, Sunday JM, Anderson KM, Barry JP, Brown NE, Connell SD, Dupont S, Fabricius KE, Hall-Spencer JM, Klinger T, Milazzo M, Munday PI, Russell BD, Sanford E, Schreiber SJ, Thiyagarajan V, Vaughan MLH, Widdicombe S, Harley CDG (2015) Ocean acidification through the lens of ecological theory. Ecology 96:3–15PubMedCrossRefGoogle Scholar
  38. Gibbons MJ, Griffiths CL (1986) A comparison of macrofaunal and meiofaunal distribution and standing stock across a rocky shore, with an estimate of their productivities. Mar Biol 3:181–188CrossRefGoogle Scholar
  39. Giere O (2009) Meiobenthology: The microscopic motile fauna of aquatic sediments, 2nd edn. Springer-Verlag, BerlinGoogle Scholar
  40. Gobin JF, Warwick RM (2006) Geographical variation in species diversity: A comparison of marine polychaetes and nematodes. J Exp Mar Bio Ecol 330:234–244CrossRefGoogle Scholar
  41. Gutiérrez JL, Jones CG, Byers JE, Arkema KK, Berkenbusch K, Commito JA, Duarte CM, Hacker SD, Lambrinos JG, Hendriks IE, Hogarth PJ, Palomo MG, Wild C (2011) Physical ecosystem engineers and the functioning of estuaries and coasts. In: Wolanski E, McLusky DS (eds) Treatise on estuarine and coastal science. Waltham: Academic 7:53–81Google Scholar
  42. Hale R, Calosi P, McNeill L, Mieszkowska N, Widdicombe S (2011) Predicted levels of future ocean acidification and temperature rise could alter community structure and biodiversity in marine benthic communities. Oikos 120:661–674CrossRefGoogle Scholar
  43. Hall-Spencer JM, Rodolfo-Metalpa R, Martin S, Ransome E, Fine M, Turner SM, Rowley SJ, Tedesco D, Buia MC (2008) Volcanic carbon dioxide vents show ecosystem effects of ocean acidification. Nature 454:96–99PubMedCrossRefGoogle Scholar
  44. Hargrave CW, Gary KP, Rosado SK (2009) Potential effects of elevated atmospheric carbon dioxide on benthic autotrophs and consumers in stream ecosystems: a test using experimental stream mesocosms. Glob Chang Biol 15:2779–2790CrossRefGoogle Scholar
  45. Hendriks IE, Duarte CM (2010) Ocean acidification: Separating evidence from judgment – A reply to Dupont et al. Estuar Coast Shelf Sci 89:186–190CrossRefGoogle Scholar
  46. Hoegh-Guldberg O, Mumby PJ, Hooten AJ, Steneck RS, Greenfield P, Gomez E, Harvell CD, Sale PF, Edwards AJ, Caldeira K, Knowlton N, Eakin CM, Iglesias-Prieto R, Muthiga N, Bradbury RH, Dubi A, Hatziolos ME (2007) Coral reefs under rapid climate change and ocean acidification. Science 318:1737–1742PubMedCrossRefGoogle Scholar
  47. Hoey AS, Bellwood DR (2010) Cross-shelf variation in browsing intensity on the Great Barrier Reef. Coral Reefs 29:499–508CrossRefGoogle Scholar
  48. IPCC (2013) Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, New York, NY, USAGoogle Scholar
  49. IPCC (2014) Climate Change 2014: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, New York, NY, USAGoogle Scholar
  50. Ishida H, Watanabe Y, Fukuhara T, Kaneko S, Furusawa K, Shirayama Y (2005) In situ enclosure experiment using a benthic chamber system to assess the effect of high concentration of CO2 on deep-sea benthic communities. J Oceanogr 61:835–843CrossRefGoogle Scholar
  51. Ishida H, Golmen LG, West J, Krüger M, Coombs P, Berge JA, Fukuhara T, Magi M, Kita J (2013) Effects of CO2 on benthic biota: An in situ benthic chamber experiment in Storfjorden (Norway). Mar Pollut Bull 73:443–451PubMedCrossRefGoogle Scholar
  52. Johnson VR, Brownlee C, Rickaby REM, Graziano M, Milazzo M, Hall-Spencer JM (2013) Responses of marine benthic microalgae to elevated CO2. Mar Biol 160:1813–1824CrossRefGoogle Scholar
  53. Jokiel PL, Rodgers KS, Kuffner IB, Andersson AJ, Cox EF, Mackenzie FT (2008) Ocean acidification and calcifying reef organisms: a mesocosm investigation. Coral Reefs 27:473–483CrossRefGoogle Scholar
  54. Kelaher BP (2003) Changes in habitat complexity negatively affect diverse gastropod assemblages in coralline algal turf. Oecologia 135:431–441PubMedCrossRefGoogle Scholar
  55. Kennedy A, Jacoby C (1999) Biological indicators of marine environmental health: meiofauna–a neglected benthic component? Environ Monit Assess 54:47–68CrossRefGoogle Scholar
  56. Kleypas JA, Yates KK (2009) Coral reefs and ocean acidification. Oceanography 22:108–117CrossRefGoogle Scholar
  57. Kramer MJ, Bellwood O, Bellwood DR (2012) Cryptofauna of the epilithic algal matrix on an inshore coral reef, Great Barrier Reef. Coral Reefs 31:1007–1015CrossRefGoogle Scholar
  58. Kramer MJ, Bellwood O, Bellwood DR (2013) The trophic importance of algal turfs for coral reef fishes: the crustacean link. Coral Reefs 32:575–583CrossRefGoogle Scholar
  59. Kroeker KJ, Micheli F, Gambi MC, Martz TR (2011) Divergent ecosystem responses within a benthic marine community to ocean acidification. Proc Natl Acad Sci USA 108:14515–14520PubMedCentralPubMedCrossRefGoogle Scholar
  60. Kurihara H (2008) Effects of CO2-driven ocean acidification on the early developmental stages of invertebrates. Mar Ecol Prog Ser 373:275–284CrossRefGoogle Scholar
  61. Kurihara H, Ishimatsu A (2008) Effects of high CO2 seawater on the copepod (Acartia tsuensis) through all life stages and subsequent generations. Mar Pollut Bull 56:1086–1090PubMedCrossRefGoogle Scholar
  62. Kurihara H, Shimode S, Shirayama Y (2004) Sub-lethal effects of elevated concentration of CO2 on planktonic copepods and sea urchins. J Oceanogr 60:743–750CrossRefGoogle Scholar
  63. Kurihara H, Ishimatsu A, Shirayama Y (2007) Effects of elevated seawater CO2 concentration on the meiofauna. J Mar Sci Technol Special Issue:17–22Google Scholar
  64. Leão ZMAN, Dominguez JML (2000) Tropical coast of Brazil. Mar Pollut Bull 41:112–122CrossRefGoogle Scholar
  65. Li W, Gao K (2012) A marine secondary producer respires and feeds more in a high CO2 ocean. Mar Pollut Bull 64:699–703PubMedCrossRefGoogle Scholar
  66. Lidbury I, Johnson V, Hall-Spencer JM, Munn CB, Cunliffe M (2012) Community-level response of coastal microbial biofilms to ocean acidification in a natural carbon dioxide vent ecosystem. Mar Pollut Bull 64:1063–1066PubMedCrossRefGoogle Scholar
  67. Maida M, Ferreira BP (1997) Coral reefs of Brazil: an overview. Proc 8th Int Coral Reef Symp 1:263–274Google Scholar
  68. Matias MG, Underwood AJ, Coleman RA (2007) Interactions of components of habitat alter composition and variability of assemblages. J Anim Ecol 76:986–994PubMedCrossRefGoogle Scholar
  69. Mayor DJ, Matthews C, Cook K, Zuur AF, Hay S (2007) CO2-induced acidification affects hatching success in Calanus finmarchicus. Mar Ecol Prog Ser 350:91–97CrossRefGoogle Scholar
  70. McArdle BH, Anderson MJ (2001) Fitting multivariate models to community data: a comment on distance based redundancy analysis. Ecology 82:290–297CrossRefGoogle Scholar
  71. Mirto S, Danovaro R (2004) Meiofaunal colonisation on artificial substrates: a tool for biomonitoring the environmental quality on coastal marine systems. Mar Pollut Bull 48:919–926PubMedCrossRefGoogle Scholar
  72. Morita M, Suwa R, Iguchi A, Nakamura M, Shimada K, Sakai K, Suzuki A (2009) Ocean acidification reduces sperm flagellar motility in broadcast spawning reef invertebrates. Zygote 18:103–107CrossRefGoogle Scholar
  73. Pascal PY, Fleeger JW, Galvez F, Carman KR (2010) The toxicological interaction between ocean acidity and metals in coastal meiobenthic copepods. Mar Pollut Bull 60:2201–2208PubMedCrossRefGoogle Scholar
  74. Pörtner HO, Langenbuch M, Reipschläger A (2004) Biological impact of elevated ocean CO2 concentrations: lessons from animal physiology and earth history. J Oceanogr 60:705–718CrossRefGoogle Scholar
  75. Porzio L, Buia MC, Hall-Spencer JM (2011) Effects of ocean acidification on macroalgal communities. J Exp Mar Bio Ecol 400:278–287CrossRefGoogle Scholar
  76. Riebesell U, Fabry VJ, Hansson L, Gattuso JP (2010) Guide to best practices for ocean acidification research and data reporting. Publications Office of the European Union, Luxembourg, p 260Google Scholar
  77. Robbins LL, Hansen ME, Kleypas JA, Meylan SC (2010) CO2calc—A user-friendly seawater carbon calculator for Windows, Max OS X, and iOS (iPhone): U.S. Geological Survey Open-File Report 2010–1280Google Scholar
  78. Roberts CM, McClean CJ, Veron JEN, Hawkins JP, Allen GR, McAllister DE, Mittermeier CG, Schueler FW, Spalding M, Wells F, Vynne C, Werner TB (2002) Marine biodiversity hotspots and conservation priorities for tropical reefs. Science 295:1280–1284PubMedCrossRefGoogle Scholar
  79. Rossoll D, Bermúdez R, Hauss H, Schulz KG, Riebesell U, Sommer U, Winder M (2012) Ocean acidification-induced food quality deterioration constrains trophic transfer. PLoS One 7:e34737PubMedCentralPubMedCrossRefGoogle Scholar
  80. Ruppert EE, Fox RS, Barnes RD (2004) Invertebrate zoology: A functional evolutionary approach, 7th edn. Brooks/Cole, Thomson Learning, BelmontGoogle Scholar
  81. Sabine CL, Feely RA, Gruber N, Key RM, Lee K, Bullister JL, Wanninkhof R, Wong CS, Wallace DWR, Tilbrook B, Millero FJ, Peng TH, Kozyr A, Ono T, Rios AF (2004) The oceanic sink for anthropogenic CO2. Science 305:367–371PubMedCrossRefGoogle Scholar
  82. Santos HF, Carmo FL, Duarte G, Dini-Andreote F, Castro CB, Rosado AS, Elsas JD, Peixoto RS (2014) Climate change affects key nitrogen-fixing bacterial populations on coral reefs. ISME J 8:2272–2279PubMedCrossRefGoogle Scholar
  83. Sarmento VC, Santos PJP (2012) Trampling on coral reefs: tourism effects on harpacticoid copepods. Coral Reefs 31:135–146CrossRefGoogle Scholar
  84. Snelgrove PVR, Butman CA (1994) Animal–sediment relationships revisited: cause versus effect. Oceanogr Mar Biol 32:111–177Google Scholar
  85. Sung CG, Kim TW, Park YG, Kang SG, Inaba K, Shiba K, Choi TS, Moon SD, Litvin S, Lee KT, Lee JS (2014) Species and gamete-specific fertilization success of two sea urchins under near future levels of pCO2. J Mar Syst 137:67–73CrossRefGoogle Scholar
  86. Takeuchi K, Fujioka Y, Kawasaki Y, Shirayama Y (1997) Impacts of high concentration of CO2 on marine organisms; a modification of CO2 ocean sequestration. Energy Convers Manag 38:337–341CrossRefGoogle Scholar
  87. Thistle D, Carman KR, Sedlacek L, Brewer PG, Fleeger JW, Barry JP (2005) Deep-ocean, sediment-dwelling animals are sensitive to sequestered carbon dioxide. Mar Ecol Prog Ser 289:1–4CrossRefGoogle Scholar
  88. Underwood AJ, Chapman MG (1996) Scales of spatial patterns of distribution of intertidal invertebrates. Oecologia 107:212–224CrossRefGoogle Scholar
  89. Underwood AJ, Chapman MG (2006) Early development of subtidal macrofaunal assemblages: relationships to period and timing of colonization. J Exp Mar Bio Ecol 330:221–233CrossRefGoogle Scholar
  90. Uthicke S, Liddy M, Nguyen HD, Byrne M (2014) Interactive effects of near-future temperature increase and ocean acidification on physiology and gonad development in adult Pacific sea urchin, Echinometra sp. A. Coral Reefs 33:831–845CrossRefGoogle Scholar
  91. van Hooidonk R, Maynard JA, Manzello D, Planes S (2014) Opposite latitudinal gradients in projected ocean acidification and bleaching impacts on coral reefs. Glob Chang Biol 20:103–112PubMedCrossRefGoogle Scholar
  92. Webster NS, Negri AP, Flores F, Humphrey C, Soo R, Botté ES, Vogel N, Uthicke S (2013) Near-future ocean acidification causes differences in microbial associations within diverse coral reef taxa. Environ Microbiol Rep 5:243–251PubMedCrossRefGoogle Scholar
  93. White AT, Vogt HP, Arin T (2000) Philippine coral reefs under threat: the economic losses caused by reef destruction. Mar Pollut Bull 40:598–605CrossRefGoogle Scholar
  94. Widdicombe S, Dashfield SL, McNeill CL, Needham HR, Beesley A, McEvoy A, Øxnevad S, Clarke KR, Berge JA (2009) Effects of CO2 induced seawater acidification on infaunal diversity and sediment nutrient fluxes. Mar Ecol Prog Ser 379:59–75CrossRefGoogle Scholar
  95. Wieser W, Ott J, Schiemer F, Gnaiger E (1974) An ecophysiological study of some meiofauna species inhabiting a sandy beach at Bermuda. Mar Biol 26:235–248CrossRefGoogle Scholar
  96. Wilkinson CR (1996) Global change and coral reefs: impacts on reefs, economies and human cultures. Glob Chang Biol 2:547–558CrossRefGoogle Scholar
  97. Wismer S, Hoey AS, Bellwood DR (2009) Cross-shelf benthic community structure on the Great Barrier Reef: relationships between macroalgal cover and herbivore biomass. Mar Ecol Prog Ser 376:45–54CrossRefGoogle Scholar
  98. Witt V, Wild C, Anthony KRN, Diaz-Pulido G, Uthicke S (2011) Effects of ocean acidification on microbial community composition of, and oxygen fluxes through, biofilms from the Great Barrier Reef. Environ Microbiol 13:2976–2989PubMedCrossRefGoogle Scholar
  99. Wyckmans M, Chepurnov VA, Vanreusel A, De Troch M (2007) Effects of food diversity on diatom selection by harpacticoid copepods. J Exp Mar Bio Ecol 345:119–128CrossRefGoogle Scholar
  100. Zar JH (1996) Biostatistical Analysis, 3rd edn. Prentice-Hall, New JerseyGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • V. C. Sarmento
    • 1
  • T. P. Souza
    • 1
  • A. M. Esteves
    • 1
  • P. J. P. Santos
    • 1
  1. 1.Departamento Zoologia, Centro de Ciências BiológicasUniversidade Federal de PernambucoRecifeBrazil

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