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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mar. Sci.</journal-id>
<journal-title>Frontiers in Marine Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mar. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-7745</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmars.2016.00239</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Marine Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The Influence of CO<sub>2</sub> Enrichment on Net Photosynthesis of Seagrass <italic>Zostera marina</italic> in a Brackish Water Environment</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Pajusalu</surname> <given-names>Liina</given-names></name>
<xref ref-type="author-notes" rid="fn001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/351801/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Martin</surname> <given-names>Georg</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/391100/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>P&#x000F5;llum&#x000E4;e</surname> <given-names>Arno</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/391072/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Paalme</surname> <given-names>Tiina</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/377789/overview"/>
</contrib>
</contrib-group>
<aff><institution>Department of Marine Biology, Estonian Marine Institute, University of Tartu</institution> <country>Tallinn, Estonia</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Fr&#x000E9;d&#x000E9;ric Gazeau, Laboratoire d&#x00027;Oc&#x000E9;anographie de Villefranche (CNRS/UPMC, UMR7093), France</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Jason Michael Hall-Spencer, Plymouth University, UK; Iris Eline Hendriks, University of the Balearic Islands, Spain; Traci Erin Cox, Dauphin Island Sea Laboratory, France</p></fn>
<fn fn-type="corresp" id="fn001"><p>&#x0002A;Correspondence: Liina Pajusalu <email>liina.pajusalu&#x00040;ut.ee</email></p></fn>
<fn fn-type="other" id="fn002"><p>This article was submitted to Global Change and the Future Ocean, a section of the journal Frontiers in Marine Science</p></fn></author-notes>
<pub-date pub-type="epub">
<day>18</day>
<month>11</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="collection">
<year>2016</year>
</pub-date>
<volume>3</volume>
<elocation-id>239</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>06</month>
<year>2016</year>
</date>
<date date-type="accepted">
<day>03</day>
<month>11</month>
<year>2016</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2016 Pajusalu, Martin, P&#x000F5;llum&#x000E4;e and Paalme.</copyright-statement>
<copyright-year>2016</copyright-year>
<copyright-holder>Pajusalu, Martin, P&#x000F5;llum&#x000E4;e and Paalme</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract><p>Seagrasses are distributed across the globe and their communities may play key roles in the coastal ecosystems. Seagrass meadows are expected to benefit from the increased carbon availability which might be used in photosynthesis in a future high CO<sub>2</sub> world. The main aim of this study was to examine the effect of elevated pCO<sub>2</sub> on the net photosynthesis of seagrass <italic>Zostera marina</italic> in a brackish water environment. The short-term mesocosm experiments were conducted in K&#x000F5;iguste Bay (northern part of Gulf of Riga, the Baltic Sea) in June&#x02013;July 2013 and 2014. As the levels of pCO<sub>2</sub> naturally range from ca. 150 &#x003BC;atm to well above 1000 &#x003BC;atm under summer conditions in K&#x000F5;iguste Bay we chose to operate in mesocosms with the pCO<sub>2</sub> levels of ca. 2000, ca. 1000, and ca. 200 &#x003BC;atm. Additionally, in 2014 the photosynthesis of <italic>Z. marina</italic> was measured outside of the mesocosm in the natural conditions. In the shallow coastal Baltic Sea seagrass <italic>Z. marina</italic> lives in a highly variable environment due to seasonality and rapid changes in meteorological conditions. This was demonstrated by the remarkable differences in water temperatures between experimental years of ca. 8&#x000B0;C. Thus, the current study also investigated the effect of elevated pCO<sub>2</sub> in combination with short-term natural fluctuations of environmental factors, i.e., temperature and PAR on the photosynthesis of <italic>Z. marina</italic>. Our results show that elevated pCO<sub>2</sub> alone did not enhance the photosynthesis of the seagrass. The photosynthetic response of <italic>Z. marina</italic> to CO<sub>2</sub> enrichment was affected by changes in water temperature and light availability.</p></abstract>
<kwd-group>
<kwd>carbon dioxide</kwd>
<kwd><italic>Zostera marina</italic></kwd>
<kwd>Baltic Sea</kwd>
<kwd>marine acidification</kwd>
<kwd>net photosynthesis</kwd>
<kwd>seagrass</kwd>
<kwd>brackish water</kwd>
</kwd-group>
<counts>
<fig-count count="3"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="55"/>
<page-count count="10"/>
<word-count count="7075"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>Over the last 20 years, it has been established that the pH of the world&#x00027;s oceans is decreasing which is caused primarily by the uptake of carbon dioxide (CO<sub>2</sub>) from the atmosphere, also known as ocean acidification (OA). Since the start of the Industrial Revolution in the late eighteenth century, atmospheric carbon dioxide concentration has increased by &#x0007E;40% primarily due to the burning of fossil fuels (Raven et al., <xref ref-type="bibr" rid="B46">2005</xref>). The surface-ocean has absorbed &#x0007E;30% of anthropogenic CO<sub>2</sub> released from the atmosphere, which causes fundamental changes in seawater carbonate chemistry (Sabine et al., <xref ref-type="bibr" rid="B48">2004</xref>). The mean surface ocean pH has already fallen by &#x0007E;0.1 units and if global emissions of CO<sub>2</sub> continue to rise, the pH may decrease 0.3&#x02013;0.4 units by the year 2100 (IPCC, <xref ref-type="bibr" rid="B26">2013</xref>).</p>
<p>The projected range of pH changes are not uniform across the globe and there are regional differences. Models project that the surface water pH in the central Baltic Sea may decrease 0.3&#x02013;0.4 units by 2100 (Omstedt et al., <xref ref-type="bibr" rid="B35">2012</xref>; Schneider et al., <xref ref-type="bibr" rid="B50">2015</xref>). Moreover, the brackish Baltic Sea is sensitive to a future increase in acidity due to low carbonate buffering capacity, which is related to its low salinity, particularly in the northern parts (Hjalmarsson et al., <xref ref-type="bibr" rid="B23">2008</xref>; Omstedt et al., <xref ref-type="bibr" rid="B36">2015</xref>). However, Hjalmarsson et al. (<xref ref-type="bibr" rid="B23">2008</xref>) found high alkalinity in the Gulf of Riga caused by extensive inputs of freshwater from the river runoff. In contrast to the open sea, the shallow coastal waters of the Baltic Sea are characterized by high temporal (diurnal and seasonal) and spatial variation of environmental factors (Feistel et al., <xref ref-type="bibr" rid="B18">2008</xref>). Besides light and water temperature, pH and partial pressure of carbon dioxide (pCO<sub>2</sub>) show a substantial amplitude of natural variability, especially under summer conditions. These daily pH changes may be of a larger magnitude than the scenario modeling suggests for the surface-water pH decrease in the Baltic Sea by the end of this century (personal measurements, 2013, 2014). However, biological responses to the elevated water CO<sub>2</sub> concentrations in combination with these short-term natural fluctuations of environmental factors have generally received little attention.</p>
<p>Seagrass communities play a key role in the coastal ecosystems. They are important primary producers on soft bottoms (Larkum et al., <xref ref-type="bibr" rid="B29">2006</xref>), contribute to sediment stabilization (Duarte, <xref ref-type="bibr" rid="B12">2002</xref>; Orth et al., <xref ref-type="bibr" rid="B37">2006</xref>), carbon sequestration (Duarte et al., <xref ref-type="bibr" rid="B15">2005</xref>), cycling of nutrients and providing shelter and food for the coastal food webs (Duarte, <xref ref-type="bibr" rid="B12">2002</xref>). Seagrasses are distributed across the globe and there are &#x0007E;60 seagrass species (Orth et al., <xref ref-type="bibr" rid="B37">2006</xref>). Unfortunately, seagrass communities are globally in serious decline (Orth et al., <xref ref-type="bibr" rid="B37">2006</xref>; Waycott et al., <xref ref-type="bibr" rid="B53">2009</xref>) mainly due to eutrophication, habitat destruction and climate change (Duarte, <xref ref-type="bibr" rid="B12">2002</xref>).</p>
<p>Seagrass meadows are expected to be influenced by the increase in seawater acidity in the future. However, the response of seagrasses to elevated pCO<sub>2</sub> can vary depending on the seagrass species as well as the habitat (Koch et al., <xref ref-type="bibr" rid="B27">2013</xref> and references therein). Besides, observed seagrass responses to CO<sub>2</sub> enrichment can be affected by the methods used. Numerous studies have been conducted near natural CO<sub>2</sub> vents, which allow assessment of the long-term effects of ocean acidification (Hall-Spencer et al., <xref ref-type="bibr" rid="B19">2008</xref>; Fabricius et al., <xref ref-type="bibr" rid="B17">2011</xref>; Porzio et al., <xref ref-type="bibr" rid="B45">2011</xref>; Russell et al., <xref ref-type="bibr" rid="B47">2013</xref>; Takahashi et al., <xref ref-type="bibr" rid="B51">2015</xref>), although it is not always clear in these studies whether observed responses are exclusively driven by changes in CO<sub>2</sub> concentration. There are no underwater CO<sub>2</sub> vents in the Baltic Sea, so we used mesocosms to investigate the effects of OA in the field.</p>
<p>This study focuses on the seagrass <italic>Zostera marina</italic>, which is a widely distributed seagrass of the temperate coastal waters in the northern hemisphere (den Hartog, <xref ref-type="bibr" rid="B11">1970</xref>; Moore and Short, <xref ref-type="bibr" rid="B34">2006</xref>). Seagrass <italic>Z. marina</italic> is one of the most common macrophytes on the species-poor sandy bottoms and is regarded as a key species of this habitat found throughout the Baltic Sea. These plants provide a secondary substrate for a diverse epiflora and fauna (Bostr&#x000F6;m et al., <xref ref-type="bibr" rid="B6">2014</xref> and references therein). The majority of investigations on the distribution of <italic>Z. marina</italic> have shown a significant decline of their meadows mainly due to eutrophication in Danish, Swedish, and Polish coastal ecosystems (Bostr&#x000F6;m et al., <xref ref-type="bibr" rid="B6">2014</xref> and references therein). However, in the Estonian coastal waters (NE Baltic Sea), the effect of eutrophication on their communities is less obvious compared to the other parts of the Baltic Sea (M&#x000F6;ller and Martin, <xref ref-type="bibr" rid="B33">2007</xref>).</p>
<p>While the effects of eutrophication on seagrass meadows in the Baltic Sea are well documented, the impacts of the increasing water CO<sub>2</sub> concentrations on <italic>Z. marina</italic> in the Baltic Sea are still mainly unknown. Previous research has shown substantial effect of warming and small positive effect of elevated CO<sub>2</sub> on the growth of <italic>Z. marina</italic> from the Kattegat region of the Baltic (Ekl&#x000F6;f et al., <xref ref-type="bibr" rid="B16">2012</xref>). Outside of the Baltic Sea, there are several studies describing the effects of elevated pCO<sub>2</sub> on the temperate seagrass species <italic>Z. marina</italic>. These studies have shown increased growth rate, enhanced photosynthesis, increased reproduction and below-ground biomass of <italic>Z. marina</italic> under elevated pCO<sub>2</sub> (Thom, <xref ref-type="bibr" rid="B52">1996</xref>; Zimmerman et al., <xref ref-type="bibr" rid="B55">1997</xref>; Palacios and Zimmerman, <xref ref-type="bibr" rid="B43">2007</xref>). Brodie et al. (<xref ref-type="bibr" rid="B7">2014</xref>) pointed out that <italic>Z. marina</italic> is likely to thrive at high latitudes although the habitat will be altered considerably due to carbonate undersaturation.</p>
<p>The main goal of this study was to examine the effect of elevated pCO<sub>2</sub> on the net photosynthesis of seagrass <italic>Z. marina</italic> in the brackish water conditions. The second goal of this study was to determine whether elevated pCO<sub>2</sub> in combination with short-term natural fluctuations of environmental factors exerts interactive effects on the photosynthetic rate of <italic>Z. marina</italic>. Our hypotheses were that the photosynthetic rate of <italic>Z. marina</italic> increases with the elevated pCO<sub>2</sub> levels and that the response would vary depending on the surrounding meteorological conditions. We tested these hypotheses <italic>in situ</italic> in short-term mesocosm experiments during two different experimental years under summer conditions in the north-eastern Baltic Sea.</p>
</sec>
<sec sec-type="materials and methods" id="s2">
<title>Materials and methods</title>
<sec>
<title>Collection of seagrass <italic>Zostera marina</italic></title>
<p>The specimens of <italic>Zostera marina</italic> were collected by SCUBA diving at a depth of 3.0 m from K&#x000FC;dema Bay (58.533&#x000B0;N, 22.238&#x000B0;E) in June 2013 and in June 2014. Whole shoots were carefully removed from the sandy sediment to keep shoots with connected bundles and horizontal rhizomes intact. All specimens were placed in coolers containing water collected at the site and transported to the experimental site immediately.</p>
</sec>
<sec>
<title>Experimental design</title>
<p>The mesocosm experiments were conducted in the shallow semi-enclosed K&#x000F5;iguste Bay, Gulf of Riga, northern Baltic Sea (58.371&#x000B0;N, 22.980&#x000B0;E). The study area is affected by nutrient inputs from the moderately eutrophic brackish Gulf of Riga (Astok et al., <xref ref-type="bibr" rid="B1">1999</xref>; Kotta et al., <xref ref-type="bibr" rid="B28">2008</xref>).</p>
<p>The experimental design used in the current study has been previously used in a number of studies targeting different macrophyte species (e.g., Pajusalu et al., <xref ref-type="bibr" rid="B41">2013</xref>, <xref ref-type="bibr" rid="B42">2015</xref>, <xref ref-type="bibr" rid="B40">2016</xref>). The mesocosm experiments were conducted during two experimental periods in 2013 and 2014 (18 July 2013&#x02013;27 July 2013 and 16 July 2014&#x02013;26 July 2014). The experimental design was identical during both years of incubation. Approximately 20 <italic>Z. marina</italic> specimens were transplanted to each plastic pot containing the mixture of fine gravel and sand (roughly 20:80). In the both experimental years, the plant material was acclimatized at the experimental site for 3 weeks prior the start of the net photosynthesis measurements. Four plastic pots with ca. 80 individual <italic>Z. marina</italic> specimens were incubated in each mesocosm with manipulated pCO<sub>2</sub> levels. In 2014 also four plastic pots were placed outside of the mesocosm in the sea. Open plastic bags (double wall of LDPE foil, 175 &#x003BC;m each) externally supported by metal frames were used as mesocosms. The bags were floating in the sea, fixed to the bottom by anchors at a depth of 0.8 m. The bags were open on the top, so there was free gas exchange with the atmosphere, but not with the surrounding water. Three plastic bag mesocosms, each with dimensions of 1.2 &#x000D7; 1.0 &#x000D7; 1.5 m, and a volume of 400 l were set up: two mesocosms with elevated pCO<sub>2</sub> levels ca. 1000 and 2000 &#x003BC;atm and one with the untreated level of ca. 200 &#x003BC;atm (control treatment). The levels of pCO<sub>2</sub> in the control treatment was ca. 200 &#x003BC;atm during the photosynthesis measurements. The pCO<sub>2</sub> level of 2000 &#x003BC;atm is much higher than the recommended maximum pCO<sub>2</sub> level of 1000 &#x003BC;atm predicted by 2100 for seawater (Barry et al., <xref ref-type="bibr" rid="B4">2010</xref>). In our experiment, the high target pCO<sub>2</sub> level ca. 2000 &#x003BC;atm was chosen because natural values of pCO<sub>2</sub> in K&#x000F5;iguste Bay were measured prior to the start of the mesocosm experiments, which turned out to be well above the concentration of 1000 &#x003BC;atm in the summer mornings. Water from the sea area adjacent to the mesocosms incubation site was sieved using a 0.25 mm mesh and used for mesocosms. Food grade pure carbon dioxide from CO<sub>2</sub> tanks was slowly bubbled into the water in the mesocosms. A custom-made controller was used to maintain elevated pCO<sub>2</sub> levels in the treatments. The controller switched on or off the CO<sub>2</sub> supply and treatment according to the CO<sub>2</sub> level measured by underwater (sensor) automatic CO<sub>2</sub> data logger (CONTROS DETECT 2.0, Germany). However, due to the response lag of the used CO<sub>2</sub> sensor (15&#x02013;20 min), the actual CO<sub>2</sub> level oscillated around the lower level present by the controller. The pH<sub>NBS</sub> (National Bureau of Standards scale) values of each treatment were measured during experiments. The measurements of photosynthesis were carried out between 10 a.m. and 4 p.m.</p>
</sec>
<sec>
<title>Environmental variables</title>
<p>In the mesocosm experiments water temperature, oxygen saturation, pH<sub>NBS</sub>, and salinity were measured continuously using a YSI 6600V2 environmental multiprobe (pH electrode YSI 6589FR). Measurements were performed during a full 24-h cycle with a frequency of 30 s. The irradiance at the incubation depths was measured as photosynthetically active radiation (PAR) using a spherical light sensor (Alec Electronics Co Ltd.). Additionally, in parallel with the photosynthesis measurements, the diurnal fluctuations of water pH, pCO<sub>2</sub>, and oxygen saturation were measured outside the mesocosms at a depth of 0.8 m in the natural shallow water macroalgal habitat. Water samples were taken from the experimental site daily and frozen immediately until further laboratory analyses. Nutrient concentrations: total nitrogen (TN), total phosphorus (TP), phosphates (P-PO<sub>4</sub>), and nitrites &#x0002B; nitrates (N-NOx) were measured in a laboratory with a continuous flow automated wet chemistry analyzer Skalar SAN<sup>plus</sup> (Skalar Analytic B.V., De Breda, The Netherlands) using the standard methods EN ISO 11905-1<xref ref-type="fn" rid="fn0001"><sup>1</sup></xref>, EN ISO 15681-2<xref ref-type="fn" rid="fn0002"><sup>2</sup></xref>, and EN ISO 13395<xref ref-type="fn" rid="fn0003"><sup>3</sup></xref>.</p>
</sec>
<sec>
<title>Measurements of net photosynthesis</title>
<p>The photosynthetic rate of <italic>Z. marina</italic> leaves at different pCO<sub>2</sub> levels (mesocosms) was measured once a day. For this procedure about 0.1 g (dry weight, dw) of plant material (one leaf) was incubated in 600 ml glass bottles. The glass bottles were filled with water from the inside of the mesocosm and placed horizontally on the transparent trays hanging at a depth of 0.5 m. All incubations with <italic>Z. marina</italic> were performed in six replicates per treatment. Bottles without plant material (in triplicate per treatment) served as controls. The dw of the plant material was determined after drying at 60&#x000B0;C for 48 h. Net primary productivity (NPP) (given as mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup>) was calculated from the differences in oxygen concentrations in incubation bottles with and without plant material, measured over the incubation period (ca. 1 h) (Paalme, <xref ref-type="bibr" rid="B39">2005</xref>). The dissolved oxygen concentrations were measured with a Marvet Junior dissolved oxygen meter (MJ2000, Elke Sensor, Estonia) using the standard method EN ISO 5814<xref ref-type="fn" rid="fn0004"><sup>4</sup></xref>.</p>
</sec>
<sec>
<title>Statistical analyses</title>
<p>A one-factor permutational multivariate analysis of variance (PERMANOVA) with 9999 permutations was used to statistically test single and interactive treatment effects on the net photosynthetic rates of <italic>Z. marina</italic>: pCO<sub>2</sub> was used as the fixed factor with 3 levels in 2013 and 4 levels in 2014; photosynthetic radiation (PAR) and water temperature were treated as covariates. Significant effects were explored when necessary with pairwise <italic>post-hoc</italic> tests (with 9999 permutations). Statistical analyses were performed using PERMANOVA (PRIMER, PRIMER-E Ltd., Plymouth, UK). For all statistical tests, a probability of 0.05 was used to determine statistical significance.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec>
<title>Environmental variables</title>
<p>The average values of PAR during the experimental period were 744 &#x000B1; 248.09 &#x003BC;mol m<sup>&#x02212;2</sup>s<sup>&#x02212;1</sup> (&#x000B1; standard deviation, SD) in 2013 and 642 &#x000B1; 179.13 &#x003BC;mol m<sup>&#x02212;2</sup>s<sup>&#x02212;1</sup> in 2014. Remarkable differences in water temperature between the two experimental periods were found: the average water temperature at the experimental site was 13.5 &#x000B1; 2.56&#x000B0;C in 2013 and 21.9 &#x000B1; 1.45&#x000B0;C in 2014 (Tables <xref ref-type="table" rid="T1">1</xref>, <xref ref-type="table" rid="T2">2</xref>). The average salinity measured during the experimental periods was 5.7 &#x000B1; 0 PSU in 2013 and 5.7 &#x000B1; 0 PSU in 2014 (Tables <xref ref-type="table" rid="T1">1</xref>, <xref ref-type="table" rid="T2">2</xref>). Carbonate parameters pCO<sub>2</sub> and pH<sub>NBS</sub> in mesocosms with different pCO<sub>2</sub> levels in 2013 and 2014 are presented in Tables <xref ref-type="table" rid="T1">1</xref>, <xref ref-type="table" rid="T2">2</xref>. Data on nutrient concentrations of the sampling sites for different experimental periods are presented in Table <xref ref-type="table" rid="T3">3</xref>.</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p><bold>Environmental variables (salinity and temperature) and carbonate parameters pCO<sub>2</sub> (<italic><bold>n</bold></italic> &#x0003D; 10) and pH<sub>NBS</sub> (<italic><bold>n</bold></italic> &#x0003D; 10) in different treatments measured during the experimental period in 2013</bold>.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="center"><bold>Treatment pCO<sub>2</sub></bold></th>
<th valign="top" align="center"><bold>Salinity</bold></th>
<th valign="top" align="center"><bold>T(&#x000B0;C)</bold></th>
<th valign="top" align="center"><bold>pH</bold></th>
<th valign="top" align="center"><bold>pCO<sub>2</sub> (&#x003BC;atm)</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">200 &#x003BC;atm</td>
<td valign="top" align="center">5.7&#x000B1;0</td>
<td valign="top" align="center">13.5&#x000B1;2.56</td>
<td valign="top" align="center">9.17&#x000B1;0.15</td>
<td valign="top" align="center">190&#x000B1;34</td>
</tr>
<tr>
<td valign="top" align="left">1000 &#x003BC;atm</td>
<td valign="top" align="center">5.7&#x000B1;0</td>
<td valign="top" align="center">13.5&#x000B1;2.56</td>
<td valign="top" align="center">7.99&#x000B1;0.17</td>
<td valign="top" align="center">1010&#x000B1;139</td>
</tr>
<tr>
<td valign="top" align="left">2000 &#x003BC;atm</td>
<td valign="top" align="center">5.7&#x000B1;0</td>
<td valign="top" align="center">13.5&#x000B1;2.56</td>
<td valign="top" align="center">7.54&#x000B1;0.16</td>
<td valign="top" align="center">2059&#x000B1;101</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>Carbonate parameters of each of the three different pCO<sub>2</sub> treatments sampled every day before net photosynthesis measurements over the experimental period. Data are the mean &#x000B1; standard deviation, SD</italic>.</p>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="T2">
<label>Table 2</label>
<caption><p><bold>Environmental variables (salinity and temperature) and carbonate parameters pCO<sub>2</sub> (<italic><bold>n</bold></italic> &#x0003D; 11) and pH<sub>NBS</sub> (<italic><bold>n</bold></italic> &#x0003D; 11) in different treatments measured during the experimental period in 2014</bold>.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="center"><bold>Treatment pCO<sub>2</sub></bold></th>
<th valign="top" align="center"><bold>Salinity</bold></th>
<th valign="top" align="center"><bold>T(&#x000B0;C)</bold></th>
<th valign="top" align="center"><bold>pH</bold></th>
<th valign="top" align="center"><bold>pCO<sub>2</sub> (&#x003BC;atm)</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">200 &#x003BC;atm</td>
<td valign="top" align="center">5.7&#x000B1;0</td>
<td valign="top" align="center">21.9&#x000B1;1.45</td>
<td valign="top" align="center">8.64&#x000B1;0.12</td>
<td valign="top" align="center">196&#x000B1;41</td>
</tr>
<tr>
<td valign="top" align="left">1000 &#x003BC;atm</td>
<td valign="top" align="center">5.7&#x000B1;0</td>
<td valign="top" align="center">21.9&#x000B1;1.45</td>
<td valign="top" align="center">7.94&#x000B1;0.11</td>
<td valign="top" align="center">1023&#x000B1;127</td>
</tr>
<tr>
<td valign="top" align="left">2000 &#x003BC;atm</td>
<td valign="top" align="center">5.7&#x000B1;0</td>
<td valign="top" align="center">21.9&#x000B1;1.45</td>
<td valign="top" align="center">7.47&#x000B1;0.09</td>
<td valign="top" align="center">2048&#x000B1;98</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="table-fn" rid="TN1"><sup>&#x0002A;</sup></xref>Natural conditions</td>
<td valign="top" align="center">5.7&#x000B1;0</td>
<td valign="top" align="center">21.9&#x000B1;1.45</td>
<td valign="top" align="center">8.40&#x000B1;0.13</td>
<td valign="top" align="center">349&#x000B1;118</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>Carbonate parameters of each of the three different pCO<sub>2</sub> treatments sampled every day before net photosynthesis measurements over the experimental period. Data are the mean &#x000B1; standard deviation, SD</italic>.</p>
<fn id="TN1">
<label>&#x0002A;</label>
<p><italic>Seawater carbonate chemistry was measured in natural conditions outside of the mesocosm</italic>.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="T3">
<label>Table 3</label>
<caption><p><bold>Total nitrogen (TN), total phosphorus (TP), phosphates (P-PO<sub>4</sub>), and nitrites &#x0002B; nitrates (N-NO<sub>x</sub>) content (mean of the experimental period &#x000B1; standard deviation, SD) of the water in mesocosm 2013 (<italic><bold>n</bold></italic> &#x0003D; 30), 2014 (<italic><bold>n</bold></italic> &#x0003D; 33) and water of outside mesocosm 2014 (<italic><bold>n</bold></italic> &#x0003D; 11)</bold>.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>TN</bold></th>
<th valign="top" align="center"><bold>TP</bold></th>
<th valign="top" align="center"><bold>P-PO<sub>4</sub></bold></th>
<th valign="top" align="center"><bold>N-NO<sub>x</sub></bold></th>
</tr>
<tr>
<th valign="top" align="left"><bold>Experimental period</bold></th>
<th valign="top" align="center"><bold>(&#x003BC;mol l<sup>&#x02212;1</sup>)</bold></th>
<th valign="top" align="center"><bold>(&#x003BC;mol l<sup>&#x02212;1</sup>)</bold></th>
<th valign="top" align="center"><bold>(&#x003BC;mol l<sup>&#x02212;1</sup>)</bold></th>
<th valign="top" align="center"><bold>(&#x003BC;mol l<sup>&#x02212;1</sup>)</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">2013 (water in mesocosms)</td>
<td valign="top" align="center">27.1&#x000B1;5.50</td>
<td valign="top" align="center">0.68&#x000B1;0.11</td>
<td valign="top" align="center">0.29&#x000B1;0.09</td>
<td valign="top" align="center">0.37&#x000B1;0.55</td>
</tr>
<tr>
<td valign="top" align="left">2014 (water in mesocosms)</td>
<td valign="top" align="center">34.1&#x000B1;3.36</td>
<td valign="top" align="center">0.95&#x000B1;0.28</td>
<td valign="top" align="center">0.26&#x000B1;0.15</td>
<td valign="top" align="center">0.11&#x000B1;0.11</td>
</tr>
<tr>
<td valign="top" align="left">2014 (water of outside mesocosm)</td>
<td valign="top" align="center">29.6&#x000B1;3.60</td>
<td valign="top" align="center">0.98&#x000B1;0.16</td>
<td valign="top" align="center">0.25&#x000B1;0.07</td>
<td valign="top" align="center">0.12&#x000B1;0.09</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec>
<title>Net photosynthetic rate of <italic>Zostera marina</italic> at different pCO<sub>2</sub> levels</title>
<p>The PERMANOVA analyses (conducted separately with the data obtained in 2013 and 2014) showed that the photosynthetic rate of the <italic>Z. marina</italic> varied significantly between different pCO<sub>2</sub> levels (Figure <xref ref-type="fig" rid="F1">1</xref>; Tables <xref ref-type="table" rid="T4">4</xref>, <xref ref-type="table" rid="T5">5</xref>; PERMANOVA: <italic>p</italic> &#x0003C; 0.05). In 2013 the variations of NPP rates were also affected by one of the tested environmental variables, namely water temperature, while the effect of the PAR was dependent on the level of pCO<sub>2</sub> and water temperature (Table <xref ref-type="table" rid="T4">4</xref>; PERMANOVA: <italic>p</italic> &#x0003C; 0.05). The net photosynthetic rates of <italic>Z. marina</italic> increased with increasing water temperature. In 2014 the NPP rates of <italic>Z. marina</italic> were affected by interactions of the PAR with water temperature and with the level of pCO<sub>2</sub> (Table <xref ref-type="table" rid="T5">5</xref>; PERMANOVA: <italic>p</italic> &#x0003C; 0.05). The results of the NPP measurements in mesocosm experiments are visualized in Figures <xref ref-type="fig" rid="F2">2</xref>, <xref ref-type="fig" rid="F3">3</xref>.</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p><bold>Mean net photosynthetic rates measured during two experimental periods (18 July 2013&#x02013;27 July 2013 and 16 July 2014&#x02013;26 July 2014) for seagrass <italic><bold>Zostera marina</bold></italic> at different water pCO<sub>2</sub> levels</bold>. Within experimental periods, same uppercase letters in 2013 and lowercase letters in 2014 indicate that net photosynthetic rates are not significantly different from one another (PERMANOVA pair-wise test for factor CO<sub>2</sub>). Bars represent mean &#x000B1; deviation (in mesocosm 2013 (<italic>n</italic> &#x0003D; 30), 2014 (<italic>n</italic> &#x0003D; 33) and in natural conditions 2014 (<italic>n</italic> &#x0003D; 11).</p></caption>
<graphic xlink:href="fmars-03-00239-g0001.tif"/>
</fig>
<table-wrap position="float" id="T4">
<label>Table 4</label>
<caption><p><bold>Results of PERMANOVA analysis on the separate and interactive effects of pCO<sub>2</sub>, PAR, and water temperature on the net primary production rate of <italic><bold>Zostera marina</bold></italic> in 2013</bold>.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>Source</bold></th>
<th valign="top" align="center"><bold>DF</bold></th>
<th valign="top" align="center"><bold>MS</bold></th>
<th valign="top" align="center"><bold>Pseudo-F</bold></th>
<th valign="top" align="center"><bold>P(perm)</bold></th>
<th valign="top" align="center"><bold>Perms</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">PAR</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.4935</td>
<td valign="top" align="center">0.3410</td>
<td valign="top" align="center">0.559</td>
<td valign="top" align="center">9825</td>
</tr>
<tr>
<td valign="top" align="left">Water temperature</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">59.935</td>
<td valign="top" align="center">41.42</td>
<td valign="top" align="center">&#x0003C;<bold>0.001</bold></td>
<td valign="top" align="center">9828</td>
</tr>
<tr>
<td valign="top" align="left">pCO<sub>2</sub></td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">6.4308</td>
<td valign="top" align="center">4.4442</td>
<td valign="top" align="center">&#x0003C;<bold>0.05</bold></td>
<td valign="top" align="center">9942</td>
</tr>
<tr>
<td valign="top" align="left">PAR&#x0002A;Water temperature</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.0017</td>
<td valign="top" align="center">0.0020</td>
<td valign="top" align="center">0.9737</td>
<td valign="top" align="center">9854</td>
</tr>
<tr>
<td valign="top" align="left">PAR&#x0002A;pCO<sub>2</sub></td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">8.909</td>
<td valign="top" align="center">6.1568</td>
<td valign="top" align="center">&#x0003C;<bold>0.05</bold></td>
<td valign="top" align="center">9956</td>
</tr>
<tr>
<td valign="top" align="left">Water temperature&#x0002A;pCO<sub>2</sub></td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">0.8313</td>
<td valign="top" align="center">0.5745</td>
<td valign="top" align="center">0.5574</td>
<td valign="top" align="center">9937</td>
</tr>
<tr>
<td valign="top" align="left">PAR&#x0002A;Water temperature&#x0002A;pCO<sub>2</sub></td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">5.7391</td>
<td valign="top" align="center">3.9661</td>
<td valign="top" align="center">&#x0003C;<bold>0.05</bold></td>
<td valign="top" align="center">9957</td>
</tr>
<tr>
<td valign="top" align="left">Res</td>
<td valign="top" align="center">168</td>
<td valign="top" align="center">1.447</td>
<td/>
<td/>
<td/>
</tr>
<tr style="border-top: solid thin #000000;">
<td valign="top" align="left">Total</td>
<td valign="top" align="center">179</td>
<td/>
<td/>
<td/>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>Significant effects (p &#x0003C; 0.05 and p &#x0003C; 0.001) are indicated in bold</italic>.</p>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="T5">
<label>Table 5</label>
<caption><p><bold>Results of PERMANOVA analysis on the separate and interactive effects of pCO<sub>2</sub>, PAR, and water temperature on the net primary production rate of <italic><bold>Zostera marina</bold></italic> in 2014</bold>.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>Source</bold></th>
<th valign="top" align="center"><bold>DF</bold></th>
<th valign="top" align="center"><bold>MS</bold></th>
<th valign="top" align="center"><bold>Pseudo-F</bold></th>
<th valign="top" align="center"><bold>P(perm)</bold></th>
<th valign="top" align="center"><bold>Perms</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">PAR</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">5.1443</td>
<td valign="top" align="center">1.363</td>
<td valign="top" align="center">0.2382</td>
<td valign="top" align="center">9830</td>
</tr>
<tr>
<td valign="top" align="left">Water temperature</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">2.398</td>
<td valign="top" align="center">0.6354</td>
<td valign="top" align="center">0.4247</td>
<td valign="top" align="center">9845</td>
</tr>
<tr>
<td valign="top" align="left">pCO<sub>2</sub></td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">97.402</td>
<td valign="top" align="center">25.807</td>
<td valign="top" align="center">&#x0003C;<bold>0.001</bold></td>
<td valign="top" align="center">9946</td>
</tr>
<tr>
<td valign="top" align="left">PAR&#x0002A;Water temperature</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">26.279</td>
<td valign="top" align="center">6.9627</td>
<td valign="top" align="center">&#x0003C;<bold>0.05</bold></td>
<td valign="top" align="center">9835</td>
</tr>
<tr>
<td valign="top" align="left">PAR&#x0002A;pCO<sub>2</sub></td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">39.866</td>
<td valign="top" align="center">10.563</td>
<td valign="top" align="center">&#x0003C;<bold>0.001</bold></td>
<td valign="top" align="center">9949</td>
</tr>
<tr>
<td valign="top" align="left">Water temperature&#x0002A;pCO<sub>2</sub></td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">4.7296</td>
<td valign="top" align="center">1.2531</td>
<td valign="top" align="center">0.292</td>
<td valign="top" align="center">9964</td>
</tr>
<tr>
<td valign="top" align="left">PAR&#x0002A;Water temperature&#x0002A;pCO<sub>2</sub></td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">7.2072</td>
<td valign="top" align="center">1.9095</td>
<td valign="top" align="center">0.1291</td>
<td valign="top" align="center">9934</td>
</tr>
<tr>
<td valign="top" align="left">Res</td>
<td valign="top" align="center">246</td>
<td valign="top" align="center">3.7743</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Total</td>
<td valign="top" align="center">261</td>
<td/>
<td/>
<td/>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>Significant effects (p &#x0003C; 0.05 and p &#x0003C; 0.001) are indicated in bold</italic>.</p>
</table-wrap-foot>
</table-wrap>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p><bold>Net photosynthesis rates (NPP) plotted against water temperature (T&#x000B0;) and photosynthetically active radiation (PAR) at different pCO<sub>2</sub> levels in 2013</bold>.</p></caption>
<graphic xlink:href="fmars-03-00239-g0002.tif"/>
</fig>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption><p><bold>Net photosynthesis rates (NPP) plotted against water temperature (T&#x000B0;) and photosynthetically active radiation (PAR) at different pCO<sub>2</sub> levels in 2014</bold>.</p></caption>
<graphic xlink:href="fmars-03-00239-g0003.tif"/>
</fig>
<p>There were remarkable differences in the NPP rates of <italic>Z. marina</italic> between the two experimental periods: the average NPP rate was 4.08 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2013 and 5.19 O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2014 (Figure <xref ref-type="fig" rid="F1">1</xref>). However, in both experimental periods, the NPP rates showed similar response patterns to CO<sub>2</sub> enrichment in mesocosm experiment. The highest NPP rates for <italic>Z. marina</italic> were measured in the untreated water (control conditions), while at the intermediate pCO<sub>2</sub> level the seagrass had lower rates than at the high pCO<sub>2</sub> levels (Figure <xref ref-type="fig" rid="F1">1</xref>). Based on a PERMANOVA pairwise <italic>post-hoc</italic> test, the differences in the average NPP rates of <italic>Z. marina</italic> at the pCO<sub>2</sub> levels between 1000 and 2000 &#x003BC;atm were significant (<italic>p</italic> &#x0003C; 0.01) in 2013. At the same time, NPP rates of <italic>Z. marina</italic> at the pCO<sub>2</sub> levels between 200 and 2000 &#x003BC;atm were not significant, while at the pCO<sub>2</sub> level of 200 &#x003BC;atm a significantly higher average NPP rate was measured compared to the elevated pCO<sub>2</sub> level of 1000 &#x003BC;atm (<italic>p</italic> &#x0003C; 0.01) in 2013 (Figure <xref ref-type="fig" rid="F1">1</xref>). In 2014 the differences in the NPP rates of <italic>Z. marina</italic> at the pCO<sub>2</sub> levels of 1000 and 2000 &#x003BC;atm were not significant but at the pCO<sub>2</sub> level of 200 &#x003BC;atm a significantly higher average photosynthetic rate compared to elevated pCO<sub>2</sub> levels was measured (PERMANOVA pairwise <italic>post-hoc</italic> test: <italic>p</italic> &#x0003C; 0.05; Figure <xref ref-type="fig" rid="F1">1</xref>). In the natural conditions outside of mesocosm the average photosynthetic rates of <italic>Z. marina</italic> were significantly lower (PERMANOVA pairwise <italic>post-hoc</italic> test: <italic>p</italic> &#x0003D; 0.0001) compared to the NPP values measured in mesocosms in 2014. At the pCO<sub>2</sub> levels of 200 &#x003BC;atm (mesocosm control conditions), the average NPP values of <italic>Z. marina</italic> were 4.38 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2013 and 5.80 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2014. At the high pCO<sub>2</sub> levels of 2000 &#x003BC;atm the average NPP value was 4.08 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2013 and 5.05 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2014, while at the intermediate pCO<sub>2</sub> level the average NPP value was 3.77 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2013 and 4.73 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2014. The lowest average NPP rate for <italic>Z. marina</italic> was measured under natural conditions outside of the mesocosm: 2.94 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup> in 2014 (Figure <xref ref-type="fig" rid="F1">1</xref>).</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>The vast majority of studies have shown that photosynthesis of seagrasses increases with the elevated pCO<sub>2</sub> (e.g., Thom, <xref ref-type="bibr" rid="B52">1996</xref>; Zimmerman et al., <xref ref-type="bibr" rid="B55">1997</xref>; Invers et al., <xref ref-type="bibr" rid="B25">2001</xref>; Ow et al., <xref ref-type="bibr" rid="B38">2015</xref>). However, this effect is highly species specific (e.g., Invers et al., <xref ref-type="bibr" rid="B24">1997</xref>, <xref ref-type="bibr" rid="B25">2001</xref>; Ow et al., <xref ref-type="bibr" rid="B38">2015</xref>). For example, Invers et al. (<xref ref-type="bibr" rid="B24">1997</xref>) investigated the effect of pH on photosynthesis in the three species of seagrasses: <italic>Posidonia oceanica, Cymodocea nodosa</italic>, and <italic>Zostera noltii</italic> in the laboratory conditions. Seagrasses <italic>P. oceanica</italic> and <italic>C. nodosa</italic> demonstrated a decrease in photosynthetic rates with an increase of pH and showed a significant reduction in NPP rates at pH 8.8. At the same time, <italic>Z. noltii</italic> showed high photosynthetic rates up to pH 8.8 and significant reduction in NPP rates only at pH 9.0. On the other hand, several studies have found unaltered response in the growth rate of seagrasses under long-term CO<sub>2</sub> enrichment (e.g., Palacios and Zimmerman, <xref ref-type="bibr" rid="B43">2007</xref>; Campbell and Fourqurean, <xref ref-type="bibr" rid="B8">2013</xref>). We hypothesized that in our mesocosm experiments the net photosynthetic rates of <italic>Zostera marina</italic> would increase with the elevated pCO<sub>2</sub> levels. In our mesocosm experiments the highest NPP rate of <italic>Z. marina</italic> was measured in the untreated water (control conditions) compared to the average values of elevated pCO<sub>2</sub> levels in both experimental periods. Cox et al. (<xref ref-type="bibr" rid="B10">2016</xref>) investigated the effect of ocean acidification on the seagrass <italic>P. oceanica</italic> meadows under controlled CO<sub>2</sub>/pH conditions using a Free Ocean Carbon Dioxide Enrichment (FOCE) system. They found no effect of elevated pCO<sub>2</sub> on the photosynthesis of Mediterranean seagrass <italic>P. oceanica</italic> from the two enclosures, neither pH manipulated nor control.</p>
<p>However, in 2014 our results showed that the NPP rates of <italic>Z. marina</italic> were significantly lower in the natural conditions outside of the mesocosm as compared to the results from the mesocosm experiment (elevated water pCO<sub>2</sub> levels as well as the untreated water). There might be several explanations for that since in natural conditions several stress factors might be affecting the condition of the plants which are eliminated in the mesocosm, e.g., water movement or presence of suspended organic particles consuming part of the oxygen production in an incubation bottle during NPP measurement.</p>
<p>In the shallow coastal K&#x000F5;iguste Bay, pH, and pCO<sub>2</sub> show a substantial amplitude of natural variability under summer conditions. In the early morning pCO<sub>2</sub> values were extremely high, being well above the concentration of 1000 &#x003BC;atm in the natural conditions outside of the mesocosm. But during the daytime, when inorganic carbon was used for photosynthesis, pCO<sub>2</sub> declined to &#x0007E;150 &#x003BC;atm. In addition, fluctuation of pH between 8 and 9 are common in shallow water macroalgal habitats under summer conditions. There might be remarkable differences in pH and pCO<sub>2</sub> changes between different days. These natural fluctuations of the environmental factors in the shallow coastal waters are driven by direct effects of photosynthesis (increasing pH), respiration (lowering pH) and meteorological conditions. Additionally, in the mesocosm control treatment, during the photosynthesis measurements the average pCO<sub>2</sub> was ca. 200 &#x003BC;atm. At the same time (hour) the average pCO<sub>2</sub> was ca. 350 &#x003BC;atm in the natural conditions outside of the mesocosm. So, considering above-mentioned natural fluctuations of pCO<sub>2</sub>, we chose to operate in mesocosms with the pCO<sub>2</sub> levels of ca. 2000, ca. 1000, and control ca. 200 &#x003BC;atm. Similarly, Paul et al. (<xref ref-type="bibr" rid="B44">2015</xref>) have used the pCO<sub>2</sub> levels from ambient (240 &#x003BC;atm) up to 1650 &#x003BC;atm in mesocosm experiments carried out in the Gulf of Finland, northern Baltic Sea.</p>
<p>In the mesocosm experiments some variation between NPP rates within the two experimental periods was found which could be explained by the differences in the weather conditions and other limiting environmental factors. Several studies conducted outside of the Baltic Sea have shown that the capacity of seagrasses to respond to ocean acidification depends on the nutrients content in the water and light levels, and their interactions (e.g., Invers et al., <xref ref-type="bibr" rid="B24">1997</xref>; Palacios and Zimmerman, <xref ref-type="bibr" rid="B43">2007</xref>; Mart&#x000ED;nez-Crego et al., <xref ref-type="bibr" rid="B30">2014</xref>). Besides seagrasses, Celis-Pl&#x000E1; et al. (<xref ref-type="bibr" rid="B9">2015</xref>) found that macroalgal responses to elevated pCO<sub>2</sub> depend on nutrients content and light availability. Within the Baltic Sea, the environmental factors vary highly regionally and seasonally (Feistel et al., <xref ref-type="bibr" rid="B18">2008</xref>). In the Estonian coastal waters, the seagrass <italic>Z. marina</italic> grows at its lowest salinity limit (5&#x02013;7 PSU) and this may cause physiological stress for their communities. Therefore, in the north-eastern Baltic Sea the factors driving the dynamics of <italic>Z. marina</italic> populations and their physiological processes are expected to be different compared to other regions of the Baltic Sea (Bostr&#x000F6;m et al., <xref ref-type="bibr" rid="B6">2014</xref>; M&#x000F6;ller et al., <xref ref-type="bibr" rid="B32">2014</xref>). In this study, variation in NPP rates within the two experimental periods could be explained first of all by the differences in the water temperature. In our experiment the higher NPP values of <italic>Z. marina</italic> were measured under the higher water temperatures in 2014 (average water temperature 21.9&#x000B0;C and average rate of NPP 5.19 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup>) compared to the values of 2013 (average water temperature 13.5&#x000B0;C and average rate of NPP 4.08 mg O<sub>2</sub> gdw<sup>&#x02212;1</sup> h<sup>&#x02212;1</sup>). Likewise, the favorable effect of the elevated pCO<sub>2</sub> on the photosynthesis of <italic>Z. marina</italic> was more pronounced at higher water temperature in 2014 than in 2013. Therefore, it could be suggested that a future increase in water temperature under climate change may benefit the net photosynthesis of <italic>Z. marina</italic> and also alter the response of <italic>Z. marina</italic> to CO<sub>2</sub> enrichment. This highlights the fact that in the Baltic Sea, where the temperature is characterized by high seasonal and annual variations, the effects of increasing CO<sub>2</sub> and water temperature should be observed together. In the Mediterranean, Baggini et al. (<xref ref-type="bibr" rid="B3">2014</xref>) found that macroalgal community responses to increased pCO<sub>2</sub> are strongly affected by season and this can alter community composition under future ocean acidification.</p>
<p>Light availability controls sea plants carbon fixation and is therefore often the primary limiting factor for seagrass productivity (Hemminga and Duarte, <xref ref-type="bibr" rid="B21">2000</xref>; Zimmerman, <xref ref-type="bibr" rid="B54">2006</xref>). Several studies have shown that the decline of <italic>Z. marina</italic> distribution is caused by deteriorating underwater light climate due to eutrophication in the Baltic Sea (Bostr&#x000F6;m et al., <xref ref-type="bibr" rid="B6">2014</xref> and references therein). In the both experimental years, our results showed that NPP rates of <italic>Z. marina</italic> were affected by the combined effects of light and pCO<sub>2</sub> levels. In the Estonian coastal waters, the main distribution depth of <italic>Z. marina</italic> is between 2 and 4 m (M&#x000F6;ller et al., <xref ref-type="bibr" rid="B32">2014</xref>). This low distribution depth of <italic>Z. marina</italic> is probably due to poor underwater light climate. Therefore, seagrass responses to the increasing water CO<sub>2</sub> concentrations also depend on the light availability in the north-eastern Baltic Sea.</p>
<p>The response of seagrasses to the elevated pCO<sub>2</sub> will depend also on the carbon source they use for photosynthesis as well as on the mechanisms of carbon acquisition. Several studies have found that <italic>Z. marina</italic> is using <inline-formula><mml:math id="M1"><mml:mrow><mml:msubsup><mml:mrow><mml:mtext>HCO</mml:mtext></mml:mrow><mml:mn>3</mml:mn><mml:mo>&#x02212;</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> as external Ci-source for photosynthesis (Sand-Jensen and Gordon, <xref ref-type="bibr" rid="B49">1984</xref>; Beer and Rehnberg, <xref ref-type="bibr" rid="B5">1997</xref>; Koch et al., <xref ref-type="bibr" rid="B27">2013</xref>). Beer and Rehnberg (<xref ref-type="bibr" rid="B5">1997</xref>) investigated two different acquisition systems of inorganic carbon for <italic>Z. marina</italic> and showed that <inline-formula><mml:math id="M2"><mml:mrow><mml:msubsup><mml:mrow><mml:mtext>HCO</mml:mtext></mml:mrow><mml:mn>3</mml:mn><mml:mo>&#x02212;</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> was used as a main source of inorganic carbon at the normal seawater pH of 8.2. Rather recently Hellblom et al. (<xref ref-type="bibr" rid="B20">2001</xref>) detected other <inline-formula><mml:math id="M3"><mml:mrow><mml:msubsup><mml:mrow><mml:mtext>HCO</mml:mtext></mml:mrow><mml:mn>3</mml:mn><mml:mo>&#x02212;</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> utilization mechanism for <italic>Z. marina</italic> when using the buffer tris (hydroxymethyl) aminomethane (TRIS) for keeping a constant pH. The addition of buffering solution (pH 8.1) to natural seawater reduced net photosynthetic rates of <italic>Z. marina</italic> by some 70% as compared to the values in the non-buffered seawater of the same pH. So, considering above-mentioned results, <italic>Z. marina</italic> can use different mechanisms of carbon acquisition for photosynthesis under different environmental conditions. It could be speculated that in our experiments under high-pH treatment in the enclosed conditions <inline-formula><mml:math id="M4"><mml:mrow><mml:msubsup><mml:mrow><mml:mtext>HCO</mml:mtext></mml:mrow><mml:mn>3</mml:mn><mml:mo>&#x02212;</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> transport is more efficient for <italic>Z. marina</italic>. However, this statement needs further verification. Similarly, Axelsson et al. (<xref ref-type="bibr" rid="B2">2000</xref>) found that brown macroalgae <italic>Laminaria saccharina</italic> appears to be able to utilize the <inline-formula><mml:math id="M5"><mml:mrow><mml:msubsup><mml:mrow><mml:mtext>HCO</mml:mtext></mml:mrow><mml:mn>3</mml:mn><mml:mo>&#x02212;</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> of seawater even more efficiently at high pH.</p>
<p>Seagrass meadows are amongst the most productive autotrophic ecosystems on the planet (Duarte and Chiscano, <xref ref-type="bibr" rid="B13">1999</xref>). Several studies have found seagrass meadows to be globally significant as carbonate reservoir (e.g., Duarte et al., <xref ref-type="bibr" rid="B14">2010</xref>; Hendriks et al., <xref ref-type="bibr" rid="B22">2014</xref>; Mazarrasa et al., <xref ref-type="bibr" rid="B31">2015</xref>). Seagrass metabolic activity is likely to buffer ocean acidification in the seagrass meadows, but the magnitude of this effect will depend on their metabolic parameters and vary regionally as well seasonally (Hendriks et al., <xref ref-type="bibr" rid="B22">2014</xref>). We can suggest that also in the Baltic Sea conditions seagrass beds could have a buffering role in the case of elevated pCO<sub>2</sub> conditions.</p>
<p>In conclusion, our study shows that elevated pCO<sub>2</sub> alone did not enhance the photosynthesis of the seagrass <italic>Z. marina</italic>. The photosynthetic response of <italic>Z. marina</italic> to elevated pCO<sub>2</sub> levels appears to be the result of interactions with water temperature and light availability in the north-eastern Baltic Sea.</p>
</sec>
<sec id="s5">
<title>Author contributions</title>
<p>Original idea: LP and GM. Study design: AP, GM and LP. Performing the experiments: LP and AP. Data analyses: LP, AP and TP. Writing a draft of the article LP and TP.</p>
<sec>
<title>Conflict of interest statement</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
</sec>
</body>
<back>
<ack><p>We would like to thank hydrochemistry laboratory of Estonian Marine Institute, University of Tartu for analysing water samples. We are also grateful to Teemar P&#x000FC;ss for help with the design of the experiments and Birgit Jullinen for her assistance in the field work. The work was funded by Estonian Ministry of Education and Research (grant SF0180005s10). We would also like to thank Katarina Oganjan for revising the text of the manuscript.</p>
</ack>
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<fn-group>
<fn id="fn0001"><p><sup>1</sup>EN ISO 11905-1 Water quality - Determination of nitrogen. Part 1: Method using oxidative digestion with petoxodisulfate.</p></fn>
<fn id="fn0002"><p><sup>2</sup>EN ISO 15681-2 Water quality - Determination of orthophosphate and total phosphorus contents by flow analysis (FIA and CFA) - Part 2: Method by continuous flow analysis (CFA).</p></fn>
<fn id="fn0003"><p><sup>3</sup>EN ISO 13395 Water quality - Determination of nitrite nitrogen and nitrate nitrogen and the sum of both by flow analysis (CFA and FIA) and spectrometric detection.</p></fn>
<fn id="fn0004"><p><sup>4</sup>EN ISO 5814 Water quality - Determination of dissolved oxygen - Electrochemical probe method.</p></fn>
</fn-group>
</back>
</article>