Effects of elevated CO2 and temperature on an intertidal meiobenthic community

Journal of Experimental Marine Biology and Ecology 469 (2015) 44–56

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Effects of elevated CO2 and temperature on an intertidal meiobenthic community A.S. Meadows a, J. Ingels b,⁎, S. Widdicombe b, R. Hale c, S.D. Rundle a a b c

Marine Biology and Ecology Research Centre, School of Marine Science and Engineering, University of Plymouth, PL4 8AA Plymouth, UK Plymouth Marine Laboratory, Prospect Place, West Hoe, PL1 3DH Plymouth, UK Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, SO14 3ZH Southampton, UK

a r t i c l e

i n f o

Article history: Received 17 December 2014 Received in revised form 1 April 2015 Accepted 2 April 2015 Keywords: Intertidal meiofauna Nematodes Copepods Ocean acidification pH Ocean warming

a b s t r a c t In the near future, the marine environment is likely to be subjected to simultaneous increases in temperature and decreased pH. The potential effects of these changes on intertidal, meiofaunal assemblages were investigated using a mesocosm experiment. Artificial Substrate Units containing meiofauna from the extreme low intertidal zone were exposed for 60 days to eight experimental treatments (four replicates for each treatment) comprising four pH levels: 8.0 (ambient control), 7.7 & 7.3 (predicted changes associated with ocean acidification), and 6.7 (CO2 point-source leakage from geological storage), crossed with two temperatures: 12 °C (ambient control) and 16 °C (predicted). Community structure, measured using major meiofauna taxa was significantly affected by pH and temperature. Copepods and copepodites showed the greatest decline in abundance in response to low pH and elevated temperature. Nematodes increased in abundance in response to low pH and temperature rise, possibly caused by decreased predation and competition for food owing to the declining macrofauna density. Nematode species composition changed significantly between the different treatments, and was affected by both seawater acidification and warming. Estimated nematode species diversity, species evenness, and the maturity index, were substantially lower at 16 °C, whereas trophic diversity was slightly higher at 16 °C except at pH 6.7. This study has demonstrated that the combination of elevated levels of CO2 and ocean warming may have substantial effects on structural and functional characteristics of meiofaunal and nematode communities, and that single stressor experiments are unlikely to encompass the complexity of abiotic and biotic interactions. At the same time, ecological interactions may lead to complex community responses to pH and temperature changes in the interstitial environment. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Since the start of the industrial revolution, anthropogenic activities have led to a significant increase in carbon dioxide (CO2) emissions (Feely et al., 2009). It is estimated that over the past 250 years atmospheric CO2 concentrations have increased from 280 ppm prior to ca. 1750 (Caldeira and Wickett, 2003), to 390.5 ppm in 2011 (Rhein et al., 2013) and, in some places, to more than 400 ppm in 2014. The subsequent oceanic uptake of this CO2 has already caused an average decrease in the global surface water pH by approximately 0.1 units since the preindustrial era, whilst the greenhouse gas CO2 in the atmosphere has increased surface ocean temperature by nearly one degree in the last century (Rhein et al., 2013). It is predicted that continuing CO2 emissions could potentially lead to a pH reduction of 0.3 units by the year 2100, and 0.7 units by 2250 (Caldeira and Wickett, 2003) whilst

⁎ Corresponding author. E-mail address: [email protected] (J. Ingels).

http://dx.doi.org/10.1016/j.jembe.2015.04.001 0022-0981/© 2015 Elsevier B.V. All rights reserved.

temperature in the top 100 m of the ocean is expected to increase by 0.6 to 2.0 °C by 2100 (Collins et al., 2013). In addition to the global threat of ocean acidification, shelf sea ecosystems could potentially be exposed to elevated levels of CO2 from other, more localised sources. With the realisation that increasing levels of atmospheric CO2 are having a significant impact on marine and terrestrial ecosystems comes public acceptance that anthropogenic CO2 emissions need to be reduced significantly. However, current technical and political factors make the achievement of this reduction through increased energy efficiency and reduced energy generation alone highly unlikely and a number of additional, engineering based mitigation techniques are now being considered (Blackstock and Long, 2009). One such technique is geological Carbon Capture and Storage (CCS), which involves the capturing of waste CO2 at the source (mainly from large industries such as coal and natural gas fired power plants) and its injection into deep geological formations, such as depleted oil and gas fields or deep saline aquifers (Gibbins et al., 2006; Holloway, 2007). However, the leakage of CO2 from these geological storage sites remains a possibility (albeit a low one) so data are urgently needed to determine the

A.S. Meadows et al. / Journal of Experimental Marine Biology and Ecology 469 (2015) 44–56

consequences for benthic ecosystems should leakage occur (Widdicombe et al., 2013). In the natural environment, marine organisms and ecosystems will often be subjected to elevated CO2 levels across a range of different temperatures and so investigations into the effects of this type of environmental change need to address potential synergies and interactions between pH and temperature. However, most published laboratory studies to date have focussed on either ocean acidification or temperature (Doney et al., 2009; Kroeker et al., 2010), and only on a limited number of species. At the same time, observational studies on naturally acidified ecosystems such as vents and seeps have their own limitations since these may under- or overestimate the effects owing to spatial variability in pH and the spatial proximity of organisms and populations unaffected by acidification (Hall-Spencer et al., 2008). This natural variability and heterogeneity inherent to vent and seep systems do not reconcile with the knowledge that ocean acidification and warming will be widespread and affect most if not all habitats and ecosystems in current global climate change scenarios (Mora et al., 2013). The growing number of studies that have examined both the individual and combined effects of predicted ocean acidification and warming scenarios still tends to focus on a single species (Mayor et al., 2012; Melatunan et al., 2013), with little being known on the community response to these two major stressors. Yet, we understand that changes in multispecies communities will be the result of both direct (Barry et al., 2004; Fitzer et al., 2012; Kurihara et al., 2007) and indirect effects arising from species interactions that may amplify or attenuate the direct effects of lowered pH and elevated temperature, such as changes in relative physiological performance (Pörtner et al., 2004), altered competitive interactions (Kroeker et al., 2012), and predator– prey dynamics (Ferrari et al., 2011). Currently, our understanding of the magnitude and mechanisms that drive these changes is still very limited. Meiofauna (32–1000 μm) are a heterogeneous ecological group, comprising over 24 phyla and occurring in very high numbers in sedimentary ecosystems (Balsamo et al., 2010). Nematodes in particular inhabit every marine (and terrestrial) habitat, display high species richness and abundance (Giere, 2009) and are the most dominant and diverse meiofaunal group (Pereira et al., 2010). Meiofauna have been shown to enhance the mineralisation of organic matter in soft sediment ecosystems (Nascimento et al., 2012) and regulate biogeochemical processes in the sediment (Bonaglia et al., 2014), and a positive link has been found between meiofauna biodiversity and high rates and efficiency of ecosystem processes (Danovaro et al., 2008). Considering the important roles that meiofauna play in sedimentary ecosystems, very little is known on how their communities will respond to global environmental changes (e.g., Danovaro et al., 2001), particularly ocean acidification. Yet, it is generally acknowledged that meiofauna, and nematodes in particular, can be used as bio-indicators for environmental changes (Balsamo et al., 2012; Moreno et al., 2011). Barry et al. (2004) demonstrated high rates of mortality for deep-sea meiofauna (including nematodes) in response to a pH reduction of 0.5 to 1.0 units. However, in comparison with the stable environmental conditions of the deep sea, intertidal meiofauna are regularly exposed to seasonal and tidal environmental fluctuations, suggesting that they may be more resilient to environmental changes, or that their response may be altered by seasonal variation in species responses (Barry et al., 2004; Godbold and Solan, 2013). In shallow water conditions, Dashfield et al. (2008) demonstrated significant differences in nematode community structure in response to altered pH and the presence/absence of the burrowing sea urchin Echinocardium cordatum. Their study demonstrated that species responses to environmental stressors in a multispecies community are a combination of direct effects on physiology and function, and indirect effects from altered intensity of ecological constraints (e.g., food source variability, predation, competition) (Ferrari et al., 2011; Hale et al., 2011; Kroeker et al., 2010), including the interaction between macrofauna and meiofauna. Whilst available knowledge

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suggests that it is unlikely that the predicted ocean acidification and temperature scenarios will directly affect nematode mortality, it is likely that community, structural and functional diversity changes will occur owing to species-specific responses (Takeuchi et al., 1997) and through ecological interactions with other, affected sedimentary organisms. Hale et al. (2011) demonstrated significant changes in macrofauna community structure and diversity in response to low pH and elevated temperature. Nematode abundance increased in response to low pH and elevated temperature, most likely due to reduced ecological pressures with reduced abundance of more vulnerable taxa (Hale et al., 2011). The present study builds on the mesocosm experiment performed by Hale et al. (2011) who investigated the combined effects of elevated CO2 and temperature elevation on macrofauna recruited from the intertidal zone using Artificial Substrate Units (ASUs). Here, we examined the potential impact of elevated CO2 and temperature on meiofauna and nematode community structure, biomass, and structural and functional diversity to shed light on how the microscopic sedimentary fauna will respond to global change scenarios. 2. Materials and methods The material collection and mesocosm experimental set-up is described in detail by Hale et al. (2011), and is summarised here. 2.1. Material collection Fifty Artificial Substrate Units (ASU, each one made from 4 nylon mesh pan scourers tied together) were attached to a sheltered area of a rocky shore at Mount Batten, Plymouth, UK (50°35′67″N, 4°12′77″W) on 14 January 2009 (Fig. 1A). They were left for a period of twelve weeks to allow colonisation, and collected on 8 April 2009. The ASUs were retrieved and transported in plastic bags to the mesocosm facility at the Plymouth Marine Laboratory (PML) 1 h after collection. Five ASUs were taken and preserved in 10% formaldehyde solution on arrival, to represent the standard invertebrate communities, and compare with the forty ASUs that underwent exposure in the mesocosm. 2.2. Mesocosm experiment Each ASU was placed in separate food-grade plastic buckets (vol. 6 l) containing ambient pH and temperature natural seawater (Fig. 1B). Each bucket was randomly allocated to one of eight treatments (four pH levels crossed with two temperature levels). The control treatment (pH 8.0, 12 °C) represented the ambient pH and temperature measured at the fauna collection site. Seawater was acidified to pH 7.7 and 7.3, mimicking the predicted drops (0.3 and 0.7 units) by Caldeira and Wickett (2003), and 6.7 (mimicking a continuous point source leakage of CO2) by bubbling 100% CO2. Artificial manipulation of temperature was achieved by placing the treatment buckets in water baths containing heaters. The experiment ran for 60 days, with little variation in the treatment levels (Table 1). During that time, each bucket received 1.68 ml of shellfish feed once a week to simulate the food availability at the Mount Batten collection site. Daylight simulation lights were also used. No tidal simulation was applied during the experiment. At the end of the mesocosm experiment, the material was passed through two sieves (0.5 mm and 63 μm) to separate the macrofauna fraction from the meiofauna fraction (Somerfield et al., 2007). Results from the macrofauna fraction are published in Hale et al. (2011). 2.3. Meiofauna sampling and identification Finer sediment components and formalin were removed by gently washing the meiofauna samples with tap water over a 63 μm sieve, in a fume cupboard. Following this initial washing, the meiofauna were

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A.S. Meadows et al. / Journal of Experimental Marine Biology and Ecology 469 (2015) 44–56

Fig. 1. (A) image of one of the Artificial Substrate Units (ASUs) attached to rocks in the intertidal, these were left for colonisation of meiofauna for a period of 12 weeks; (B) image of the mesocosm experiment setup.

then extracted from the remaining sediment components via floatation extraction in Ludox TM colloidal solution with a specific gravity of 1.15 and collected with a 63 μm sieve following the protocol by Somerfield and Warwick (1996). This process was repeated four times, leaving the sediment to settle for approximately 40 min between extractions. Two samples (1 initial, and 1 treatment) were examined in full under a stereo microscope to obtain approximate abundance of meiofauna in the samples. Due to the high number and range of meiofauna organisms, thirty-two samples (four replicates per treatment) selected for analysis were subsampled (5% of each entire sample). Freshwater was used to wash the entire sample into a wide-mouthed plastic container (flat bottom and vertical sides) marked with a volume corresponding to 20 ladle volumes (1 ladle = 40 ml). Additional freshwater was then added to the sample until the total volume was equivalent to 20 times that of the ladle (800 ml) and the sample was agitated using the ladle with an up and down motion for 20–30 s to homogenously distribute the meiofauna (Somerfield and Warwick, 1996). One ladle of the mixture was carefully removed and washed into a 63 μm sieve. The subsample was stored in a glass vial whilst the remaining meiofauna from the mixture was returned to the plastic pot and preserved. Both were preserved in 75% Industrial Methylated Spirit (IMS). Light staining of the specimens was carried out by adding a few drops of 1% Rose Bengal to each of the meiofauna samples stored in IMS (Higgins and Thiel, 1988). The meiofauna subsamples were then examined under the stereo microscope in small portions on a counting tray. All organisms observed were identified down to major taxonomic groups using Higgins and Thiel (1988), and taxonomic literature. 2.4. Nematode sampling and identification If up to 200 individuals were found within the subsample, all were extracted for identification to the genus level. If more than 200 individuals were found then a percentage was extracted (201–500, 50%; 501–999, 20%; ≥1000, 10%) randomly, resulting in a minimum of 100 individuals extracted. The extracted nematodes were placed in an embryo dish, suspended in a dilute glycerol (5% glycerol, 10% ethanol and water) and left to evaporate overnight on a heater, leaving the nematodes in pure glycerol (Somerfield et al., 2007). Subsequently they were processed to permanent slides (10 nematodes per slide) following the standard technique for permanent glycerine collection slides described by Somerfield and Warwick (1996). The nematodes were examined under a compound microscope (1000 × magnification) and identified to putative species level where possible using pictorial keys and taxonomic literature (Platt and Warwick, 1988; Schmidt-Rhaesa, 2013). Two nematode sample replicates from each treatment were selected to assess change in nematode biomass. The length (μm) (excluding the

filiform tails, if present) and maximum body width (μm) of the fully intact nematodes were measured using the compound microscope and its interactive measurement software Leica LAS. 2.5. Data analysis All statistical analyses were performed using the PRIMER v6.1.11 software (Clarke and Gorley, 2006) and the PERMANOVA + add-on (Anderson et al., 2008). Meiofauna community structure analysis was performed on squareroot-transformed data (to down-weight the contributions of the highly abundant nematode taxon; Clarke and Gorley, 2006) using the Bray–Curtis similarity measure. The nematode community data were standardised but no transformation was needed (Clarke and Gorley, 2006); Bray–Curtis similarity was used to calculate resemblance measures. To visualise the similarities between samples, non-metric multi-dimensional scaling (MDS) was used. Analysis of variation by means of permutation (PERMANOVA) was conducted to test the effects of low pH and temperature rise, and their potential interaction. Pairwise tests were performed in the case of a significant (P b 0.05) pH × temperature interaction. Separate tests for homogeneity of multivariate dispersions (PERMDISP) were carried out using 999 permutations. Similarity percentage (SIMPER) analysis revealed which nematode species were most responsible for the (dis)similarity between treatment groups. To measure statistically significant similarities in abundance patterns among treatments between groups of nematode species, CLUSTER analyses were performed on the species matrix, based on a D9 Index of Association (Somerfield and Clarke, 2013) along with the permutation test SIMPROF (at the 5% level) to determine which species clusters had significant internal structure. A range of structural diversity measures were calculated (DIVERSE analysis) on the nematode community data and included the functional diversity measures Trophic Diversity (TD; Heip et al., 1998) and Maturity Index (MI; Bongers, 1990), as well as biomass, to obtain a comprehensive suite of community descriptors. Trophic Diversity (TD) was calculated as TD = 1 / Σθ2ι, where θι is the relative abundance of the ith trophic group. Four trophic groups were assigned: selective feeders (1A), opportunistic feeders (1B), epistrate feeders (2A) and predators/omnivores (2B) (Wieser, 1953). The Maturity Index (MI) was calculated as MI = Σv(i)xf(i), where v(i) is the c–p value of the taxon i, f(i) is the frequency of the taxon i in the subsample (Bongers, 1990). Based on an MDS analysis (normalised, Euclidean Distance) of all descriptors, we omitted those that were redundant based on their proximity in Euclidean space and hence similarity in the way that they contain information on the sampled community (Fig. 2). The sub-set of measures eventually used for the analyses was number of species (S),

A.S. Meadows et al. / Journal of Experimental Marine Biology and Ecology 469 (2015) 44–56

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Table 1 Seawater chemistry within a) buckets and b) reservoir tanks during the experimental exposure period. Hale et al. (2011).

a) 12 °C

Nominal

Temp

pH

(°C)

pH

Sal

TCO2

TA

(μatm)

ΩCa

ΩAr

HCO− 3

CO2− 3

8

11.78 0.35 0.07 11.93 0.35 0.07 11.66 0.41 0.09 11.53 0.38 0.08 16.04 0.40 0.08 16.01 0.63 0.13 15.76 0.31 0.07 15.48 1.52 0.32

7.86 0.09 0.02 7.66 0.08 0.01 7.35 0.07 0.01 6.81 0.23 0.04 7.85 0.13 0.02 7.61 0.15 0.03 7.37 0.1 0.02 6.66 0.19 0.04

34.88 0.19 0.05 34.89 0.24 0.06 34.94 0.13 0.03 34.82 0.14 0.04 35.31 0.26 0.07 35.13 0.21 0.05 35.06 0.15 0.04 34.99 0.18 0.04

1358.80 314.04 72.54 2084.49 331.50 76.57 2181.94 227.68 52.59 2409.95 313.33 72.37 1915.97 216.12 49.92 2046.30 241.83 55.86 2105.32 254.15 58.70 2423.61 284.04 65.60

1956.61 293.36 74.23 2155.52 303.58 76.81 2098.44 228.21 57.74 1942.01 221.04 55.93 1984.25 226.77 57.38 2072.27 246.16 62.29 2051.74 232.74 58.89 1957.02 25.08 54.42

729.23 160.4 40.59 1295.53 244.51 61.87 2729.23 499.36 126.35 2268.73 3127.42 791.33 822.18 743.4 188.1 1422.98 388.9 98.4 2611.66 547.02 138.41 3010.36 4141.2 1047.85

1.59 0.3 0.08 1.17 0.24 0.06 0.55 0.11 0.03 0.16 0.11 0.03 1.91 0.38 0.1 1.21 0.29 0.07 0.67 0.15 0.04 0.15 0.08 0.02

1.01 0.19 0.05 0.75 0.15 0.04 0.35 0.07 0.02 0.1 0.07 0.02 1.23 0.27 0.06 0.78 0.19 0.05 0.43 0.1 0.02 0.1 0.05 0.01

1784.99 275.4 69.68 2031.97 286.88 72.59 2039.57 222.75 56.36 1925.14 220.99 55.92 1779.26 204.34 51.7 1943.53 233.63 59.12 1980.85 225.48 57.05 1940.63 212.54 53.78

66.59 12.5 3.16 49.03 10.09 2.55 23.22 4.5 1.14 6.6 4.56 1.15 80.3 15.83 4.01 50.94 12.18 3.08 28.01 6.43 1.63 6.5 3.41 0.86

14.08 0.44 0.19 15.56 0.41 0.18 15.46 0.43 0.19 14.33 0.56 0.24 15.39 0.55 0.24 14.26 0.43 0.19 13.86 0.44 0.19 15.3 0.7 0.3

7.89 0.14 0.06 7.98 0.14 0.06 7.68 0.19 0.08 7.63 0.18 0.08 7.26 0.19 0.08 7.35 0.2 0.08 6.33 0.14 0.06 6.34 0.2 0.08

34.95 0.10 0.05 34.84 0.13 0.07 34.82 0.12 0.06 34.75 0.15 0.08 34.86 0.13 0.07 34.82 0.14 0.07 34.76 0.14 0.08 34.76 0.16 0.09

1930 273.13 138.22 1860 257.68 130.40 2086.67 206.13 104.31 2033.33 287.90 145.70 2156.67 130.21 65.90 2106.67 264.49 133.85 2686.67 311.7 157.74 2693.33 358.17 181.26

2018.97 307.01 166.89 1970.58 290.3 157.81 2116.32 225.18 122.41 2084.55 323.71 175.97 2066.85 141.82 77.09 2043.55 286.94 155.98 1770.66 247 134.27 1763.27 220.64 119.94

680.76 156.68 85.17 527.15 96.68 52.56 1211.65 243.27 132.24 1308.57 230.09 125.07 3279.5 584.35 317.65 2905.94 484.55 263.4 243.69 42.29 22.99 238.83 41.23 22.41

1.93 0.31 0.17 2.38 0.39 0.21 1.38 0.23 0.12 1.21 0.37 0.2 0.54 0.12 0.07 0.55 0.12 0.07 0.05 0.02 0.01 0.06 0.02 0.01

1.24 0.2 0.11 1.53 0.25 0.14 0.89 0.15 0.08 0.77 0.23 0.13 0.35 0.08 0.04 0.35 0.08 0.04 0.03 0.01 0.01 0.04 0.01 0.01

1811.93 287.81 156.45 1715.41 231.67 142.08 1970.45 216.55 117.71 1957.12 297.01 161.46 2010.12 135.28 73.54 1984.88 278.31 151.29 1765.47 245.84 133.64 1757.66 219.47 119.31

81.15 12.89 7.01 99.82 16.49 8.97 57.92 9.6 5.22 50.53 15.36 8.35 22.48 5.21 2.83 23.14 5.16 2.8 2.16 0.64 0.35 2.31 0.63 0.34

7.7

7.3

6.7

16 °C

8

7.7

7.3

6.7

pCO2

b) 8

7.7

7.3

6.7

Sal — salinity, TCO2 — total water carbon dioxide concentration, TA — total alkalinity, pCO2 — partial pressure of carbon dioxide, ΩCa — calcite saturation state, ΩAr — argon saturation state, HCO13 — bicarbonate concentration, CO2− — carbonate concentration. Values: mean, ±SD, and 95% Cl. 3

estimated number of species from 50 individuals (ES(50)) (Hurlbert, 1971), Pielou's evenness (J′), Trophic Diversity, Maturity Index, and biomass for each nematode subsample (Bongers, 1990; Bongers et al., 1991; Heip et al., 1998). Here, univariate PERMANOVA analyses were used to determine whether each of the nematode community descriptors was significantly affected by pH, temperature and/or their interaction (Anderson et al., 2008). Euclidean Distance was used as a similarity measure. 2.5.1. Biomass The nematode biomass was calculated with Andrassy's formula (Andrassy, 1956) adapted for marine nematodes (specific density of 1.13 (Heip et al., 1985) instead of 1.08 proposed by Andrassy (1956): Biomass (μg wet weight) = L × W2 / (1.5 × 106 )), and a

carbon weight at 12.4% of the wet weight was assumed (Heip et al., 1985). The average biomass of each species was extrapolated to total sample (ASU) values using species relative abundance data and total nematode abundance.

2.5.2. Macrofauna effects The RELATE routine was applied to assess whether there was an interaction response between the macrofauna and meiofauna datasets. The meiofauna and nematode similarity matrices (Bray–Curtis) were related to the macrofauna (Hale et al, 2011) similarity matrix by calculating the Spearman rank correlation (999 permutations) investigating the null hypothesis that there is no relationship between the matrices (i.e., Rho = 0).

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Fig. 2. MDS ordination for Euclidean Distance between nematode community diversity measures and biomass. Measures used for analysis: total species (S), estimated species per 50 individuals (ES(50)), Pielou's evenness (J′), Maturity Index (MI), Trophic Diversity (TD) and Biomass.

3. Results 3.1. Meiofauna Meiofauna densities in the initial subsamples (5%) were relatively similar, containing on average 1387 (±323) individuals with between 8 and 13 higher taxa. Meiofauna densities in the treatment subsamples contained on average 630 (±210) individuals from 6 to 12 higher taxa. Nematodes and copepods (including copepodites) dominated the assemblages. Other meiobenthic taxa were observed (e.g., Amphipoda, Ostracoda) in much lower numbers. Nematodes comprised between 50 and 62% of the total abundance in the initial subsamples, but between 10 and 90% in the treatment samples. Differences in meiofauna community structure in each treatment are shown using MDS plots (Fig. 3); illustrating a separation of assemblages exposed to pH 6.7 from those subjected to other pH treatments. Assemblages exposed to 16 °C are more tightly grouped in the Bray– Curtis space in comparison to those exposed to 12 °C (Fig. 3) indicating greater variability between subsample assemblages at lower (in situ) temperatures.

The PERMANOVA analysis on meiofauna abundance data showed a significant effect of temperature (P b 0.05) and the temperature × pH interaction (P b 0.01) (Table S1). Significant differences were found between 12 °C and 16 °C at pH 7.3 (P b 0.05), and between pH groups 7.3 and 6.7 at 16 °C (P b 0.05). Meiofauna community structure, on the other hand, was significantly affected by pH (P b 0.01) and temperature (P b 0.01) separately (Table S1). Nematodes, copepods (and copepodites) were the most abundant taxa, and also displayed the greatest change in abundance in response to low pH and rising temperature (Fig. 4). PERMANOVA tests show that the abundances of nematodes (P b 0.05), polychaetes (larva) (P b 0.05), amphipods (P b 0.01), ostracods (P b 0.01), foraminiferans (P b 0.05) and kynorhynchs (P b 0.05) were significantly affected by single factor pH, but not by the factor temperature, nor their interaction (Table S1). A positive response in nematode abundance was observed in response to lowered pH at the 12 and 16 °C temperatures (Fig. 4A). The effects of temperature are only evident at pH 6.7, whereby nematode abundance is substantially higher at 12 °C. However, average nematode relative abundance is consistently higher at 12 °C across all pH treatments (Fig. 4B). PERMDISP analysis revealed significant differences in dispersion for temperature and the interaction of the two stressors (Table S1). Copepod abundance was significantly affected by pH (P b 0.01) and temperature (P b 0.01) separately, but the interaction of the two stressors did not evoke a significant effect (Table S1). Abundance initially increases in response to low pH and high temperature, followed by a drastic decline at pH 6.7 (Fig. 4C). Pairwise tests show that copepod abundance at pH 6.7 was significantly different from abundance at other pH levels, and that for both the 12 and 16 °C treatments (P b 0.05). At pH 7.3, the effect of temperature on copepod abundance was particularly noticeable (Fig. 4C). Average copepod relative abundance values were greater at 16 °C compared to 12 °C for all pH treatments lower than pH 8.0 (Fig. 4D). Copepodites were significantly affected by pH, temperature and their interaction (P b 0.01) (Table S1), with a significant difference between pH 7.7 and 8.0 at 16 °C (P b 0.05) and between 12 and 16 °C at pH 8.0 (P b 0.05) and 7.3 (P b 0.05). Copepodite abundance generally decreased in response to low pH, but the mean number of individuals was more varied at 16 °C (Fig. 4E). Copepodite abundance patterns were generally also reflected in their relative abundance patterns (Fig. 4F). PERMDISP analysis revealed significant differences in dispersion for pH only (Table S1). The other meiofauna taxa comprised very low numbers in all treatments, potentially reducing their importance in assessing pH and temperature effects, and should be treated with caution (Table S2). Polychaete larvae abundance was significantly affected by pH only (Table S1), with particularly low abundance and relative abundance at pH 6.7 for both the 12 and 16 °C treatments (Fig. 4G, H). Halacarid abundance was significantly affected by temperature only (P b 0.01) (Table S1), with substantially higher abundance and relative abundance at 16 °C for all pH levels apart from pH 7.7 (Fig. 4O, P). Changes in abundance and relative abundance observed in amphipods, ostracods, foraminiferans, and kynorhynchs varied (Fig. 4I–N, Q, R), but were not significantly affected by pH, temperature or their interaction (Table S1). Adult polychaetes, gastropods, isopods, turbellarians, and tanaidaceans were either extremely low in abundance or frequently absent in the subsample replicates.

3.2. Nematodes

Fig. 3. nMDS ordination for the Bray–Curtis similarity from square root transformed meiofauna major taxa abundance data. ●6.7 (red), ■7.3 (orange), ▲7.7 (green), and ▼8.0 (black). Solid symbols 16 °C and hollow symbols 12 °C.

3.2.1. Community structure One-hundred-and-one species (from 46 genera) were identified in the subsample fractions. Some specimens could only be identified down to family level (4612 extracted, 48 identified to family level).

A.S. Meadows et al. / Journal of Experimental Marine Biology and Ecology 469 (2015) 44–56

Nematode community structure was significantly affected by pH (P b 0.01) and temperature (P b 0.01) only (Table 2). MDS ordination plots for the nematode assemblages show the separation of assemblages

49

exposed to pH 6.7 from those subjected to other pH treatments (Fig. 5). Nematode assemblages exposed to 12 °C are more diffusely distributed compared to those exposed to 16 °C, indicating greater biological

Fig. 4. The effects of pH and temperature (○12 °C, ●16 °C) on the mean abundance and relative abundance of (A, B) Nematoda, (C, D) Copepoda, (E, F) copepodites, (G, H) polychaete larva, (I, J) Amphipoda, (K, L) Ostrocoda, (M, N) Foraminifera, (O, P) Halacaroidea and (Q, R) Kynorhyncha.

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A.S. Meadows et al. / Journal of Experimental Marine Biology and Ecology 469 (2015) 44–56

Fig. 4 (continued).

dissimilarity at lower temperatures. This was similar to the patterns of dispersion seen for the full meiofauna community (Fig. 3). SIMPER analysis (cut-off: 50%) identified species of the genera Neochromadora, Paracanthonchus, Halomonhystera and Euchromadora to be mainly responsible for the similarity among replicates in each treatment (Table S3). Three species of Chromadora were responsible for the similarity between the initial samples, yet were rare in the ambient control treatment. Eleven species from 7 genera were found to

contribute most to dissimilarity between pH treatment groups (average dissimilarity 52.42%), and 5 species from 4 genera responsible for dissimilarity between temperature groups (50.12%) (Table S4). One species of Paracanthonchus and Neochromadora contributed to the dissimilarity between all pH and temperature treatment groups. It is noteworthy that most of the species responsible for similarity and dissimilarity belong to the chromadorid group, often characterised by nematodes typified as epistrate feeders.

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Table 2 Nematode PERMANOVA and PERMDISP analyses of variance of the effects of two crossed, fixed factors, pH (8.0, 7.7, 7.3 and 6.7) and temperature (12 °C and 16 °C). Significant results (P b 0.05) are in bold. PERMANOVA

PERMDISP

Data

Factor

DF

MS

Community structure

pH Temp pHxTemp Res pH Temp pHxTemp Res pH Temp pHxTemp Res pH Temp pHxTemp Res pH Temp pHxTemp Res pH Temp pHxTemp Res pH Temp pHxTemp Res

3 1 3 24 3 1 3 24 3 1 3 24 3 1 3 24 3 1 3 24 3 1 3 24 3 1 3 8

2992.6 2513.4 1380.6 1142.6 32.417 b0.0001 7.4167 38.833 1.765 43.332 0.30651 5.2234 2.45E−03 2.24E−02 4.85E−04 3.92E−03 2.16E−01 3.13E−01 3.40E−02 9.92E−02 2.69E−02 2.16E−03 1.31E−02 1.27E−02 1.46E+06 1.79E+06 1.51E+06 3.98E+05

S

ES(50)

J′

TD

MI

Total sample biomass

CLUSTER and SIMPROF analyses on nematode species indicated that groups of species responded significantly similar in terms of their abundance to pH decline and temperature rise (Fig. S1). At the same time, some nematode species show clear abundance responses to induced pH and temperature changes (e.g., Fig. S2A–F, S3A–E), whilst other species responses were unclear (e.g., Fig. S2G, S3F).

3.2.2. Structural diversity No significant effect of pH, temperature nor their interaction was found on total species number (S). Temperature was found to have a significant effect on ES(50) (P b 0.01) and J′ (P b 0.01) (Table 2); average ES(50) and Pielou's evenness (J′) values were consistently lower at 16 °C (Fig. 5a, b). Pairwise tests indicated that at pH 7.3 there was a

Pseudo-F

P(perm)

perms

F

P

2.6192 2.1997 1.2083

0.001 0.005 0.148

998 998 998

2.5366 11.061 5.9223

0.101 0.001 0.003

0.83476 b0 0.1910

0.49

999

0.897

999

0.7960 0.0383 1.2089

0.545 0.851 0.465

0.3379 8.2957 0.0587

0.783 0.008 0.981

998 999 998

0.85846 1.5781 2.2783

0.589 0.226 0.155

0.6239 5.7012 0.1238

0.627 0.024 0.938

999 997 999

0.2582 12.233 2.9213

0.929 0.002 0.11

2.1721 3.1525 0.3422

0.119 0.085 0.794

999 994 997

2.0993 1.0192 1.1212

0.151 0.472 0.747

2.1184 0.1702 1.0331

0.105 0.662 0.391

999 999 999

1.1695 2.7535 2.6922

0.445 0.112 0.14

3.6656 4.4969 3.8003

0.076 0.064 0.04

998 996 997

3.706 9.2051 –

0.123 0.013 –

significant difference (P(MC) b 0.05) between 12 °C and 16 °C for ES(50); the same was observed for J′ at pH 6.7 (P(MC) b 0.01). 3.2.3. Functional diversity (Trophic Diversity [TD] and Maturity Index [MI]) Average TD values are consistently higher at 16 °C apart from the pH 6.7 treatments (Fig. 7A). Average MI values are slightly lower at 16 °C apart from the pH 7.7 treatments (Fig. 7B). Generally, there was higher variability in MI at 12 °C, and MI decreased slightly in response to lowered pH, but there was no significant effect of pH, temperature nor their interaction in the PERMANOVA test (Table 2). 3.2.4. Biomass There was a significant pH × temperature interaction effect on biomass (P b 0.05), but no main effects (Table 2). Pairwise tests found significant differences between 12 and 16 °C for pH 7.7 and 8.0 (P(MC) b 0.05) and between pH 7.7 and 8.0 at 12 °C (P(MC) b 0.05). Graphical representation, however, indicates clear differences between 12 °C and 16 °C also at the pH 6.7 level; it is assumed that the statistical limitation to detect these differences is caused by insufficient replication (n = 2) (Fig. 7C). The highest mean total abundance was observed at pH 6.7 at 12 °C. The greatest difference in total biomass between replicates was observed at pH 7.3 at 12 °C (2118 and 3891 μg). 3.3. Mesocosm and macrofauna effects—procedural controls

Fig. 5. nMDS ordination for the Bray−Curtis similarity nematode species abundance data (standardised). ●6.7 (red), ■7.3 (orange), ▲7.7 (green), ▼8.0 (black). Solid symbols 16 °C, hollow symbols 12 °C.

The MDS ordinations for the meiofauna and nematode community structures show the segregation of the initial samples from those subjected to the control treatment (pH 8, 12 °C) and other treatments in the mesocosm (Fig. 8A, B) suggesting a mesocosm effect on all treatment samples. The fact that all “mesocosm” samples are grouped within the MDS (compared to the “initial” samples), however, supports the assumption that the mesocosm didn't have a differential effect on the different treatment samples. With the exception of amphipods, the control samples contained less of all the higher meiofauna taxonomic groups after 60 days in the mesocosm (Fig. 9A, B).

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Fig. 6. The effects of pH and temperature on (A) expected nematode species diversity per 50 individuals and (B) Pielou's evenness. (○12 °C, ●16 °C).

SIMPER results corroborated that the nematode species composition in the initial subsamples was different from the mesocosm control subsamples (pH 8, 12 °C) (Table S3). Abundances of the Chromadora species were significantly higher in the initial subsamples than the control

subsamples. Chromadora abundance was highest at pH 6.7 and 12 °C, but is still lower than that of the initial subsamples. Comparisons of the matrices derived from the RELATE meiofauna data indicate an interaction between the macrofauna and meiofauna

Fig. 7. The effects of pH and temperature on (A) nematode Trophic Diversity, (B) Maturity Index and (C) total nematode biomass. (○12 °C, ●16 °C).

Fig. 8. nMDS ordination for the Bray–Curtis similarity from square root transformed (A) meiofauna and (B) nematode species abundance data (standardised). control treatment (pH 8.0, 12 °C) subsamples. Solid symbols 16 °C and hollow symbols 12 °C.

initial subsamples and

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53

Fig. 9. Mean abundance of dominant meiofauna taxonomic groups in initial (grey) and control (white) subsamples; a) Nematoda, b) Copepoda, c) copepodites, d) polychaete larva, e) Amphipoda, f) Gastropoda and g) Halacaroidea.

(Rho = 0.549) (Fig. S4A), and between the macrofauna and nematode assemblage patterns (Rho = 0.463) (Fig. S4B). 4. Discussion The results presented here give an indication on the potential impacts to intertidal meiofauna that are likely to occur across a range of predicted pH and temperature levels (Caldeira and Wickett, 2003; Collins et al., 2013). They demonstrate that the predicted changes due to ocean acidification and warming could potentially alter meiofauna community structure, diversity and function. Since ocean acidification and warming are both caused by increased atmospheric CO2, the meiofauna organisms are being exposed to the two stressors simultaneously (Byrne, 2011; Hale et al., 2011; Melatunan et al., 2013). The impact of a single environmental stressor may be exacerbated due to other stressors occurring simultaneously rather than their interaction e.g., the resistance of individual species to a single environmental stressor may be reduced in the face of multiple stressors (Melatunan et al., 2013). In addition, the response of a multispecies intertidal community to ocean warming and acidification is strongly influenced by direct effects on taxa and indirect effects through ecological interactions (Hale et al., 2011; Melatunan et al., 2013). Species interactions may attenuate or amplify the direct effects on individual species (Kroeker et al., 2012). Therefore, the true impacts of ocean acidification and elevated temperature on a multispecies benthic community are more complex and varied than previously thought. There was a significant pH ∗ temperature interaction, with synergistic impacts on the meiofauna density. Meiofauna and nematode community structures were both significantly affected by pH and temperature only. All the major taxonomic groups found in the ASUs were significantly affected by one or both environmental factors without interaction effects, apart from gastropods (pH ∗ temperature interaction only), and isopods (no significant effects). We did not expect gastropod abundance to remain unaffected by ocean acidification since they have a calcium carbonate shell prone to acidification (Fabry et al., 2008) and Shirayama and Thornton (2005) reported reduced growth, but also mortality of shallow-water gastropods under only slightly elevated CO2 conditions (200 ppm) in laboratory experiments. Also isopods were expected to exhibit vulnerability to warming and ocean acidification (reviewed in Ingels et al., 2012), although the effects of these stressors may be limited to their reduced development and reproductive success rather than being expressed in greater mortality (e.g., Egilsdottir et al., 2009).

The positive response of nematode abundance to lowered pH and elevated temperature in the meiofauna fraction was previously observed in the macrofauna fraction (Hale et al., 2011). Kurihara et al. (2007) reported no significant changes in nematode abundance when increasing CO2 concentrations from 360 ppm to 2000 ppm (reflecting in a pH drop from 8.2 to about 7.4) and Takeuchi et al. (1997) observed drastic impacts only under pH 5.5–6.0 or less, although the latter study, unlike the current study, was limited to only a few nematode species. The observed changes in the density of macrofauna organisms (Hale et al., 2011), may have caused an increase in nematode abundance through altered intensities of competition for food resources (Frontalini et al., 2011; Ingels et al., 2014). In addition, the reduced ecological constraints may have affected nematode assemblages, shifting in favour of certain nematode species (e.g., Ingels et al., 2014). Widdicombe et al. (2009) noted that the impermeable proteinaceous cuticle may contribute to the nematodes short-term tolerance to ocean acidification. Increased biofilm growth and bacterial abundance (Russell et al., 2013) in response to increased CO2 is also a possibility. In Majdi et al. (2011) nematode diversity was positively correlated to biofilm density, and epistrate-feeders were the dominant feeding type in the nematode assemblages. The availability of potential prey in biofilms may be an important driver of nematode community patterns and prey availability may be positively affected by warming and ocean acidification as shown in Alsterberg et al. (2013). Most of the observed changes in this study occurred in epistrate feeders. The colonisation method (ASUs) may have contributed to their colonisation success. They may also have benefited from increased biofilm growth and bacterial abundance, depending on the availability of potential prey. Opportunistic feeders may also change feeding strategy in response to available food (Moens and Vincx, 1997; Schratzberger et al., 2004a,b; Semprucci et al., 2014). Copepod abundance was not predicted to increase at pH levels 7.7 and 7.3 at 16 °C (e.g., Kurihara et al., 2007 who reported no significant effects at pH ~ 7.4), but that is what was observed in the current study. Previous studies suggest copepod communities to be significantly negatively affected by ocean acidification and ocean warming (Fitzer et al., 2012; Mayor et al., 2012; Pascal et al., 2010). Fitzer et al. (2012) also concluded that the hatching success in marine copepods will not be affected under the predicted pH and temperature levels, suggesting that copepod vulnerability varies at different life history stages. One explanation for the apparently contradictory results is that the copepods, in response to pH stress, may have reallocated energy to reproductive

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output, to a point when it is no longer possible without compromising growth and health (Fitzer et al., 2012). Consequently, any abundance increase may be an initial response to stress before a more long-term decline in abundance. Species that enhance calcification in response to ocean acidification and climate change can still be impacted negatively by the decline of less tolerant species within their ecosystems (Ries et al., 2009). Our study has also demonstrated that the response of calcifying marine organisms to acidification and climate change is variable and complex. Some taxa, such as foraminifera, exhibited a positive response to the predicted ocean pH and temperature scenarios, but were greatly reduced at pH 6.7. Observational studies at CO2 vents have produced varying and contrasting results regarding resilience to low pH (Pettit et al., 2013). Although living foraminifera were found in all treatments, they were low in abundance compared to other taxonomic groups. The weekly supply of food (Hale et al., 2011) and increased availability owing to the reduced macrofauna density may enable some foraminifera to adapt to a low pH environment (Pettit et al., 2013). In addition, future temperature elevation could also lead to higher growth rate (Fabry et al., 2008). No food was provided for the larger or carnivorous macrofauna organisms (Hale et al., 2011). It is assumed that the meiofauna were being consumed by larger carnivorous organisms. Both pH and temperature are likely to have caused changes to the physiology and functionality of meiofauna organisms (e.g., gastropod shell properties), resulting in reduced protection from predation (Melatunan et al., 2013). It is currently unclear how ocean acidification and temperature elevation affects the physiology and behaviour of the predators. Research, on changes in predator–prey interaction is currently limited to larger marine organisms (Cripps et al., 2011; Manríquez et al., 2014). As predator and prey were exposed to the same treatments, it is not known whether the changes are the result of pH, temperature or both factors influencing predator, prey or both (Ferrari et al., 2011). In the intertidal zone, the gastropods will also be vulnerable to wave exposure, overheating and desiccation (Melatunan et al., 2013). Investigating the changes in species composition of nematode assemblages is a more sensitive means of assessing environmental impacts than is possible by referring to changes in abundance, diversity and evenness (Schratzberger et al., 2000) and this has proven to be the case in the present study for ocean acidification and temperature rise. SIMPROF analysis showed that some closely related species (e.g., Neochromadora genus) responded differently (Fig. S1–3) indicating that the change in nematode community structure is also dependant on species-specific tolerance (Takeuchi et al., 1997). It cannot be assumed that closely related taxa will have the same levels of sensitivity to acidification and warming. To understand multi-stressor impacts of warming and acidification on meiofauna, it is important to increase our understanding on the fundamental physiologies and life history traits of individual meiofauna and nematode species. Subsequently we may increase our knowledge on the potential use of meiofauna and nematode species as bio-indicators for pH and temperature changes. Previous work on the effects of elevated CO2 concentration on meiofauna has suggested that in spite of no observed change in abundance or biomass of nematodes (Kurihara et al., 2007), there could have been a change in species composition. Changes in species composition were observed in the nematode assemblages indicating differential responses to pH and temperature (Fig. S2, S3). Diversity indices should be used in combination with abundance data for all taxonomic groups in future studies. Nematode abundance was sufficient to differentiate pH treatments, but the effects of temperature on nematode abundance were only evident at pH 6.7 (Fig. 4A). The results of the structural and functional diversity analyses proved useful in distinguishing between temperature treatments, showing substantial differences between 12 and 16 °C in estimated species (ES(50)), species evenness (J′), Trophic Diversity (TD) and Maturity Index (MI) at all pH treatments.

The Maturity Index (MI) has proven useful in investigating the disturbance of marine nematode assemblages (Bongers et al., 1991). Whilst it was not significantly affected in the present study, the mean MI values were consistently lower at 16 °C (apart from pH 7.7), indicating that the nematode assemblages were less disturbed at 12 °C (Fig. 6B). Decreasing MI values also indicate that the ASUs were increasingly dominated by “colonizers” (Gambi et al., 2003). The data suggests that the intertidal nematode community structure in the lowered pH and elevated temperature scenarios is characterised by a higher fraction of colonisers (opportunistic behaviour). An increase in quantity of food will favour fast reproducing species, resulting in a decreasing MI (Bongers et al., 1991; Ingels et al., 2014). Chromadora, Halomonhystera and Neochromadora species demonstrated a high colonisation ability and tolerance to lower pH and elevated temperature (Fig. S3), becoming the most dominant species at pH 6.7. The Chromadora species in particular demonstrated high colonisation ability to lower pH at 12 and 16 °C (Figs. S2 and S3). This observation may be biased through the type of substrate (ASUs) used for collecting the meiofauna and thus related to the complexity of the structure, but the high colonisation potential of chromadorids has also been reported by Schratzberger et al. (2004a,b) and Semprucci et al. (2014). PERMANOVA tests showed that total nematode biomass was significantly reduced by the pH ∗ temperature interaction only. No significant pH effects were observed. This is similar to the findings by Kurihara et al. (2007) who reported decreasing nematode biomass under acidified conditions, but no significant effects. The most likely explanatory scenario for this observation is that species exchange occurred; opportunistic nematode species tolerant to the new conditions may have replaced and outcompeted the more sensitive species. In addition, the lowest pH levels may have exceeded the tolerance levels of nonnematode meiofauna species competing with the nematodes, leading to an increase in nematode biomass of the resilient and opportunistic nematode species at the lowest pH level (Fig. 7C). The process of identifying nematodes to the lowest taxonomic level is difficult and time consuming, which may explain why studies on meiofauna at the species level are extremely scarce. Identification of the other higher taxa to genus level was not feasible owing to time constraints and limited taxonomic expertise. Whilst previous studies have shown that genus-level identification does not usually alter the interpretation and description of community patterns compared to species-level identification (Moore and Bett, 1989; Somerfield and Clarke, 1995), significant impacts on individual species or a group of species may go unnoticed if the assessment is undertaken at genus or a higher taxonomic level. The SIMPER and CLUSTER analyses of nematode assemblages showed the varied responses of species between and within different nematode genera (Tables S3 and S4; Figs. S1–3). The macrofauna extracted from the same ASUs (Hale et al., 2011) are diverse in taxonomy, making them a source of ecological constraints (e.g., predation, competition for food resources) and disturbance of varying intensities to meiofauna (Dashfield et al., 2008; Ingels et al., 2014; Olafsson, 2003). It is also worth considering that the meiofauna may be a source of ecological constraints on macrofauna communities as they are also structured by interactions that occur when they are in the meiofaunal size category as larvae and juveniles (e.g., meiofauna preying on macrofauna larvae, Watzin (1983, 1986), Dahms et al. (2004)). Kennedy (1994), for instance, found evidence of predaceous nematodes and turbellarians ingesting a range of meiofaunal sized organisms including copepods, annelids, ostracods, halacarids and nematodes, giving valuable information in terms of their role in intertidal meiofauna communities as well as their role in trophic interactions. Although the community samples were given approximately 12 h to acclimate to the treatment levels, the gradual changes occurring in nature are taking place on a scale of years or decades. However, intertidal organisms are subject to regular fluctuations in pH and temperature (Godbold and Solan, 2013). Meiofauna that pre-adapted to large

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fluctuations in environmental parameters may tolerate the long-term steady changes (Pörtner et al., 2004). The possibility of adaptive and selective processes taking place exists when looking at complex multispecies communities (Hendriks et al., 2009). Finally, the comparison between the initial and control subsamples suggests the possibility that ecological interactions are sensitive to variation in spatial scale. However, research data on the potential effects of mesocosm size as a driver of complex ecological interactions is extremely scarce (Spivak et al., 2011). The results presented here illustrate that complex impacts can occur and predicting more realistic changes in multispecies communities will require knowledge of key ecological interactions, as well as identifying key species and their direct responses to pH and temperature change.

5. Conclusion Future ocean acidification and temperature levels have the potential to alter the structure, diversity and function of intertidal marine meiobenthic communities. The experiment presented here suggests that the effects may be complex, with both positive and negative responses owing to differential vulnerability within and between taxonomic groups, particularly on the level of nematode species (even within the same genus). General differences in response occurred between higher taxonomic groups (e.g., nematodes, copepods, polychaete larva), but some higher taxa (e.g., adult polychaetes, gastropods) were of little relevance due to low abundance and frequent absence. Identifying nematodes to the lowest taxonomic level and investigating the impacts on diversity indices proved to be a more sensitive means of assessing the potential impact, and should be combined with abundance data in future meiofaunal studies to maximise information when investigating ocean acidification and temperature rise on multispecies communities. Significant similarities in abundance patterns between groups of nematode species and changes in species composition were also found. Care must be taken when making predictions based on single-stressor and single species studies, and changes in ecological interactions must be taken into consideration when examining community changes in response to ocean acidification and temperature rise. Species with mechanism(s) that enable adaptation physiologically can still be affected negatively through changes in ecological interactions within and between taxonomic groups. With the increasing interest in ocean acidification and temperature rise, the scientific community must move towards more holistic, ecologically realistic experiments that incorporate multiple stressors and ecological interactions.

Acknowledgements This paper is a contribution to the Plymouth Marine Laboratory science area “Marine Life Support Systems”. This study was partially funded by the NERC/Defra UK Ocean Acidification Research Programme grant “Impacts of ocean acidification on key benthic ecosystems, communities, habitats, species and life cycles” (NE/H01747X/1). We thank Sarah Dashfield and Christine Pascoe for their help. Jeroen Ingels is supported by a Marie-Curie Intra-European Fellowship within the 7th European Community Framework Programme (FP7-PEOPLE-2011-IEF Project No 300879, grant agreement number PIEF-GA-2011-300879). This study was undertaken whilst Alexander Meadows was completing a work placement in partial fulfilment of his MSc. [SS]

Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jembe.2015.04.001.

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