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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Seasonal variations in photosynthesis, intrinsic water-use efficiency and stable isotope composition of poplar leaves in a short-rotation plantation</title><author><name sortKey="Broeckx, L S" sort="Broeckx, L S" uniqKey="Broeckx L" first="L. S." last="Broeckx">L. S. Broeckx</name></author><author><name sortKey="Fichot, R" sort="Fichot, R" uniqKey="Fichot R" first="R." last="Fichot">R. Fichot</name></author><author><name sortKey="Verlinden, M S" sort="Verlinden, M S" uniqKey="Verlinden M" first="M. S." last="Verlinden">M. S. Verlinden</name></author><author><name sortKey="Ceulemans, R" sort="Ceulemans, R" uniqKey="Ceulemans R" first="R." last="Ceulemans">R. Ceulemans</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25074859</idno><idno type="pmc">4131770</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4131770</idno><idno type="RBID">PMC:4131770</idno><idno type="doi">10.1093/treephys/tpu057</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">000034</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000034</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Seasonal variations in photosynthesis, intrinsic water-use efficiency and stable isotope composition of poplar leaves in a short-rotation plantation</title><author><name sortKey="Broeckx, L S" sort="Broeckx, L S" uniqKey="Broeckx L" first="L. S." last="Broeckx">L. S. Broeckx</name></author><author><name sortKey="Fichot, R" sort="Fichot, R" uniqKey="Fichot R" first="R." last="Fichot">R. Fichot</name></author><author><name sortKey="Verlinden, M S" sort="Verlinden, M S" uniqKey="Verlinden M" first="M. S." last="Verlinden">M. S. Verlinden</name></author><author><name sortKey="Ceulemans, R" sort="Ceulemans, R" uniqKey="Ceulemans R" first="R." last="Ceulemans">R. Ceulemans</name></author></analytic><series><title level="j">Tree Physiology</title><idno type="ISSN">0829-318X</idno><idno type="eISSN">1758-4469</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Photosynthetic carbon assimilation and transpirational water loss play an important role in the yield and the carbon sequestration potential of bioenergy-devoted cultures of fast-growing trees. For six poplar (<italic>Populus</italic>) genotypes in a short-rotation plantation, we observed significant seasonal and genotypic variation in photosynthetic parameters, intrinsic water-use efficiency (WUE<sub>i</sub>) and leaf stable isotope composition (δ<sup>13</sup>C and δ<sup>18</sup>O). The poplars maintained high photosynthetic rates (between 17.8 and 26.9 μmol m<sup>−2</sup> s<sup>−1</sup> depending on genotypes) until late in the season, in line with their fast-growth habit. Seasonal fluctuations were mainly explained by variations in soil water availability and by stomatal limitation upon photosynthesis. Stomatal rather than biochemical limitation was confirmed by the constant intrinsic photosynthetic capacity (<italic>V</italic><sub>cmax</sub>) during the growing season, closely related to leaf nitrogen (N) content. Intrinsic water-use efficiency scaled negatively with carbon isotope discrimination (Δ<sup>13</sup>C<sub>bl</sub>) and positively with the ratio between mesophyll diffusion conductance (<italic>g</italic><sub>m</sub>) and stomatal conductance. The WUE<sub>i</sub> – Δ<sup>13</sup>C<sub>bl</sub> relationship was partly influenced by <italic>g</italic><sub>m</sub>. There was a trade-off between WUE<sub>i</sub> and photosynthetic N-use efficiency, but only when soil water availability was limiting. Our results suggest that seasonal fluctuations in relation to soil water availability should be accounted for in future modelling studies assessing the carbon sequestration potential and the water-use efficiency of woody energy crops.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Al Afas, N" uniqKey="Al Afas N">N Al Afas</name></author><author><name sortKey="Pellis, A" uniqKey="Pellis A">A Pellis</name></author><author><name sortKey="Niinemets, U" uniqKey="Niinemets U">U Niinemets</name></author><author><name sortKey="Ceulemans, R" uniqKey="Ceulemans R">R Ceulemans</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Allen, Sj" uniqKey="Allen S">SJ Allen</name></author><author><name sortKey="Hall, Rl" uniqKey="Hall R">RL Hall</name></author><author><name sortKey="Rosier, Pt" uniqKey="Rosier P">PT 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Tree Physiol</journal-id><journal-id journal-id-type="iso-abbrev">Tree Physiol</journal-id><journal-id journal-id-type="publisher-id">treephys</journal-id><journal-id journal-id-type="hwp">treephys</journal-id><journal-title-group><journal-title>Tree Physiology</journal-title></journal-title-group><issn pub-type="ppub">0829-318X</issn><issn pub-type="epub">1758-4469</issn><publisher><publisher-name>Oxford University Press</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">25074859</article-id><article-id pub-id-type="pmc">4131770</article-id><article-id pub-id-type="doi">10.1093/treephys/tpu057</article-id><article-id pub-id-type="publisher-id">tpu057</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Papers</subject></subj-group></article-categories><title-group><article-title>Seasonal variations in photosynthesis, intrinsic water-use efficiency and stable isotope composition of poplar leaves in a short-rotation plantation</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Broeckx</surname><given-names>L.S.</given-names></name><xref ref-type="aff" rid="af1">1</xref><xref ref-type="author-notes" rid="AN1">†</xref></contrib><contrib contrib-type="author"><name><surname>Fichot</surname><given-names>R.</given-names></name><xref ref-type="aff" rid="af2">2</xref><xref ref-type="corresp" rid="cor1">3</xref><xref ref-type="author-notes" rid="AN1">†</xref></contrib><contrib contrib-type="author"><name><surname>Verlinden</surname><given-names>M.S.</given-names></name><xref ref-type="aff" rid="af1">1</xref></contrib><contrib contrib-type="author"><name><surname>Ceulemans</surname><given-names>R.</given-names></name><xref ref-type="aff" rid="af1">1</xref></contrib></contrib-group><contrib-group><contrib contrib-type="editor"><name><surname>Niinemets</surname><given-names>Ülo</given-names></name><role>handling Editor</role></contrib><aff id="af1"><label>1</label><addr-line>Department of Biology, Research Group of Plant and Vegetation Ecology, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Belgium</addr-line></aff><aff id="af2"><label>2</label><addr-line>University of Orléans, INRA, LBLGC, F-45067 Orléans, France</addr-line></aff></contrib-group><author-notes><corresp id="cor1"><label>3</label>Corresponding author (<email>regis.fichot@univ-orleans.fr</email>)</corresp><fn fn-type="con" id="AN1"><label>†</label><p>Both authors contributed equally to this manuscript.</p></fn></author-notes><pub-date pub-type="ppub"><month>7</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>28</day><month>7</month><year>2014</year></pub-date><pub-date pub-type="pmc-release"><day>28</day><month>7</month><year>2014</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
<volume>34</volume><issue>7</issue><fpage>701</fpage><lpage>715</lpage><history><date date-type="received"><day>2</day><month>4</month><year>2014</year></date><date date-type="accepted"><day>3</day><month>6</month><year>2014</year></date></history><permissions><copyright-statement>© The Author 2014. Published by Oxford University Press.</copyright-statement><copyright-year>2014</copyright-year><license license-type="creative-commons" xlink:href="http://creativecommons.org/licenses/by-nc/4.0/"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc/4.0/">http://creativecommons.org/licenses/by-nc/4.0/</ext-link>), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com</license-p></license></permissions><self-uri content-type="pdf" xlink:type="simple" xlink:href="tpu057.pdf"></self-uri><abstract><p>Photosynthetic carbon assimilation and transpirational water loss play an important role in the yield and the carbon sequestration potential of bioenergy-devoted cultures of fast-growing trees. For six poplar (<italic>Populus</italic>) genotypes in a short-rotation plantation, we observed significant seasonal and genotypic variation in photosynthetic parameters, intrinsic water-use efficiency (WUE<sub>i</sub>) and leaf stable isotope composition (δ<sup>13</sup>C and δ<sup>18</sup>O). The poplars maintained high photosynthetic rates (between 17.8 and 26.9 μmol m<sup>−2</sup> s<sup>−1</sup> depending on genotypes) until late in the season, in line with their fast-growth habit. Seasonal fluctuations were mainly explained by variations in soil water availability and by stomatal limitation upon photosynthesis. Stomatal rather than biochemical limitation was confirmed by the constant intrinsic photosynthetic capacity (<italic>V</italic><sub>cmax</sub>) during the growing season, closely related to leaf nitrogen (N) content. Intrinsic water-use efficiency scaled negatively with carbon isotope discrimination (Δ<sup>13</sup>C<sub>bl</sub>) and positively with the ratio between mesophyll diffusion conductance (<italic>g</italic><sub>m</sub>) and stomatal conductance. The WUE<sub>i</sub> – Δ<sup>13</sup>C<sub>bl</sub> relationship was partly influenced by <italic>g</italic><sub>m</sub>. There was a trade-off between WUE<sub>i</sub> and photosynthetic N-use efficiency, but only when soil water availability was limiting. Our results suggest that seasonal fluctuations in relation to soil water availability should be accounted for in future modelling studies assessing the carbon sequestration potential and the water-use efficiency of woody energy crops.</p></abstract><kwd-group><kwd>leaf nitrogen</kwd><kwd>maximum rate of carboxylation</kwd><kwd>mesophyll conductance</kwd><kwd>photosynthetic nitrogen-use efficiency</kwd><kwd>short-rotation-coppice</kwd><kwd>soil water deficit</kwd><kwd>stomatal conductance</kwd></kwd-group><counts><page-count count="15"></page-count></counts></article-meta></front><body><sec sec-type="intro" id="s1"><title>Introduction</title><p>Fast-growing tree species, such as poplar and willow, implemented in short-rotation bioenergy cultures (SRC), represent a promising renewable energy source (<xref rid="TPU057C1" ref-type="bibr">AEBIOM 2012</xref>). The success of this renewable bioenergy largely depends on the yields that can be achieved. The large genetic variability found within the <italic>Populus</italic> genus (<xref rid="TPU057C26" ref-type="bibr">Dunlap and Stettler 1998</xref>, <xref rid="TPU057C2" ref-type="bibr">Al Afas et al. 2005</xref>, <xref rid="TPU057C66" ref-type="bibr">Paris et al. 2011</xref>, <xref rid="TPU057C11" ref-type="bibr">Broeckx et al. 2012<italic>a</italic></xref>, <xref rid="TPU057C12" ref-type="bibr">2012<italic>b</italic></xref>) offers the possibility to select highly productive genotypes. The high productivity of poplar has been associated with its high water use (water consumption) (<xref rid="TPU057C98" ref-type="bibr">Zsuffa et al. 1996</xref>, <xref rid="TPU057C3" ref-type="bibr">Allen et al. 1999</xref>, <xref rid="TPU057C60" ref-type="bibr">Meiresonne et al. 1999</xref>) and with its sensitivity to drought (<xref rid="TPU057C58" ref-type="bibr">Lindroth et al. 1994</xref>, <xref rid="TPU057C55" ref-type="bibr">Liang et al. 2006</xref>, <xref rid="TPU057C63" ref-type="bibr">Monclus et al. 2009</xref>). The increasing probability of seasonal droughts (<xref rid="TPU057C28" ref-type="bibr">Easterling et al. 2000</xref>, <xref rid="TPU057C81" ref-type="bibr">Seneviratne et al. 2010</xref>) and the prospects of freshwater scarcity (<xref rid="TPU057C8" ref-type="bibr">Berndes 2002</xref>) emphasize the importance of traits such as water-use efficiency (WUE) and drought tolerance as the selection criteria for biomass production under future climate conditions (<xref rid="TPU057C52" ref-type="bibr">King et al. 2013</xref>).</p><p>At the whole-plant level, WUE is defined as plant dry matter production per unit of water loss via transpiration. Substantial species and genotypic variation in whole-plant WUE have been reported (<xref rid="TPU057C17" ref-type="bibr">Cernusak et al. 2007</xref>, <xref rid="TPU057C57" ref-type="bibr">Linderson et al. 2007</xref>, <xref rid="TPU057C72" ref-type="bibr">Rasheed et al. 2013</xref>). At the leaf level, intrinsic water-use efficiency (WUE<sub>i</sub>) is defined as the instantaneous ratio between net CO<sub>2</sub> assimilation rate (<italic>A</italic>) and stomatal conductance to water vapour (<italic>g</italic><sub>s</sub>). The carbon isotope discrimination (Δ<sup>13</sup>C) is expected to scale negatively with WUE<sub>i</sub> (<xref rid="TPU057C30" ref-type="bibr">Farquhar and Richards 1984</xref>), and has been commonly used as an indicator of WUE<sub>i</sub> in poplar (<xref rid="TPU057C75" ref-type="bibr">Ripullone et al. 2004</xref>, <xref rid="TPU057C62" ref-type="bibr">Monclus et al. 2006</xref>, <xref rid="TPU057C9" ref-type="bibr">Bonhomme et al. 2008</xref>, <xref rid="TPU057C23" ref-type="bibr">Dillen et al. 2008</xref>, <xref rid="TPU057C35" ref-type="bibr">Fichot et al. 2011</xref>, <xref rid="TPU057C72" ref-type="bibr">Rasheed et al. 2013</xref>). However, the relationship between Δ<sup>13</sup>C and WUE<sub>i</sub> can be disturbed because of differences in the respective time of integration (<xref rid="TPU057C70" ref-type="bibr">Ponton et al. 2002</xref>, <xref rid="TPU057C75" ref-type="bibr">Ripullone et al. 2004</xref>) or of variable mesophyll diffusion conductances (<italic>g</italic><sub>m</sub>) (<xref rid="TPU057C88" ref-type="bibr">Warren and Adams 2006</xref>, <xref rid="TPU057C83" ref-type="bibr">Soolanayakanahally et al. 2009</xref>). Selecting genotypes for low Δ<sup>13</sup>C—and assumingly for high WUE<sub>i</sub>—may not necessarily result in a selection towards higher productivity, as this depends on the main source of variation driving WUE<sub>i</sub> (<xref rid="TPU057C44" ref-type="bibr">Gilbert et al. 2011</xref>). As such, Δ<sup>13</sup>C does not allow distinguishing between the effects of <italic>A</italic> and <italic>g</italic><sub>s</sub>. On the contrary, the oxygen composition of organic matter (δ<sup>18</sup>O) may be used to independently estimate variations in WUE<sub>i</sub> originating from variations in <italic>g</italic><sub>s</sub> (<xref rid="TPU057C79" ref-type="bibr">Scheidegger et al. 2000</xref>, <xref rid="TPU057C4" ref-type="bibr">Barbour 2007</xref>). As water in the leaf is the most important source of oxygen, bulk leaf oxygen isotope composition (δ<sup>18</sup>O<sub>bl</sub>) integrates <italic>g</italic><sub>s</sub> over the leaf life span. It thus combines source water oxygen isotope composition and leaf water enrichment, partly affected by evaporative processes. When combined with Δ<sup>13</sup>C data, δ<sup>18</sup>O is a means to distinguish between the different sources of variation in WUE<sub>i</sub>.</p><p>Seasonal variations in photosynthetic parameters and resource-use efficiency largely affect the modelling of ecosystem carbon uptake (<xref rid="TPU057C92" ref-type="bibr">Wilson et al. 2001</xref>, <xref rid="TPU057C87" ref-type="bibr">Wang et al. 2004</xref>, <xref rid="TPU057C53" ref-type="bibr">Kosugi and Matsuo 2006</xref>, <xref rid="TPU057C95" ref-type="bibr">Zhu et al. 2011</xref>), determining the efficiency of bioenergy cultures. Strong seasonal variations in photosynthetic parameters have been reported for deciduous species, but mostly under Mediterranean climate conditions in relation to water availability (<xref rid="TPU057C91" ref-type="bibr">Wilson et al. 2000<italic>b</italic></xref>, <xref rid="TPU057C92" ref-type="bibr">2001</xref>, <xref rid="TPU057C93" ref-type="bibr">Xu and Baldocchi 2003</xref>, <xref rid="TPU057C56" ref-type="bibr">Limousin et al. 2010</xref>, <xref rid="TPU057C61" ref-type="bibr">Misson et al. 2010</xref>). Stomatal closure is generally the primary diffusive limitation to carbon assimilation rate and one of the earliest responses to drought during the growing season (<xref rid="TPU057C91" ref-type="bibr">Wilson et al. 2000<italic>b</italic></xref>, <xref rid="TPU057C18" ref-type="bibr">Chaves et al. 2002</xref>, <xref rid="TPU057C37" ref-type="bibr">Flexas and Medrano 2002</xref>). Mesophyll conductance to CO<sub>2</sub> (<italic>g</italic><sub>m</sub>) also decreases in response to decreasing soil water availability, adding an additional resistance to CO<sub>2</sub> diffusion to the chloroplasts (<xref rid="TPU057C78" ref-type="bibr">Roupsard et al. 1996</xref>, <xref rid="TPU057C46" ref-type="bibr">Grassi and Magnani 2005</xref>, <xref rid="TPU057C56" ref-type="bibr">Limousin et al. 2010</xref>, <xref rid="TPU057C61" ref-type="bibr">Misson et al. 2010</xref>). Photosynthetic limitations because of biochemical impairments are generally observed under severe water stress (<xref rid="TPU057C10" ref-type="bibr">Bota et al. 2004</xref>, <xref rid="TPU057C38" ref-type="bibr">Flexas et al. 2004</xref>). Besides increasing WUE, stomatal closure decreases photosynthetic nitrogen-use efficiency (PNUE), defined as the ratio between <italic>A</italic> and leaf nitrogen (N) concentration (<xref rid="TPU057C88" ref-type="bibr">Warren and Adams 2006</xref>). The trade-off between WUE and PNUE arises from the generally observed relationship between light-saturated photosynthesis (<italic>A</italic><sub>sat</sub>) and leaf N (<xref rid="TPU057C93" ref-type="bibr">Xu and Baldocchi 2003</xref>). Stomatal closure has a smaller effect on photosynthesis when compared with the direct impact on transpiration, and has no effect on leaf N. However, <italic>g</italic><sub>m</sub> influences the variation in PNUE, and hence its relationship with WUE (<xref rid="TPU057C88" ref-type="bibr">Warren and Adams 2006</xref>). The role of <italic>g</italic><sub>m</sub> and its relationship to <italic>g</italic><sub>s</sub> is important for a better understanding of the economics of photosynthetic and N use in a changing climate (<xref rid="TPU057C14" ref-type="bibr">Buckley and Warren 2014</xref>).</p><p>For SRC plantations under temperate climate conditions, the seasonal evolution of photosynthesis, transpirational water loss and WUE are of utmost importance for their productivity and biomass yield. This is especially true when one considers that (i) seasonal variability in photosynthesis is a strong determinant of carbon balance and therefore of the environmental benefit of bioenergy-devoted plantations (<xref rid="TPU057C96" ref-type="bibr">Zona et al. 2012</xref>); (ii) SRC plantations devoted to biomass production rely on high-yielding species which are generally very sensitive to fluctuations in water availability, such as poplars (<xref rid="TPU057C58" ref-type="bibr">Lindroth et al. 1994</xref>, <xref rid="TPU057C55" ref-type="bibr">Liang et al. 2006</xref>, <xref rid="TPU057C63" ref-type="bibr">Monclus et al. 2009</xref>); (iii) high planting densities (6000–20,000) are likely to exacerbate competition for water acquisition and lead to faster water depletion (<xref rid="TPU057C85" ref-type="bibr">Toillon et al. 2013</xref>); and (iv) climate change might result in increased frequency and duration of abnormal drought episodes (<xref rid="TPU057C51" ref-type="bibr">IPCC 2007</xref>, <xref rid="TPU057C81" ref-type="bibr">Seneviratne et al. 2010</xref>). In view of the above, the seasonal evolution in Δ<sup>13</sup>C and δ<sup>18</sup>O as a potential indicator of WUE<sub>i</sub> in combination with seasonal changes in photosynthesis provides a more detailed study, in particular under field conditions of changing soil water availability. The rationale of the present study is also to quantify genotypic variation in the aforementioned seasonal evolution and in the WUE<sub>i</sub> relationships for poplar.</p><p>The objectives of this study were (i) to investigate and characterize seasonal and genotypic variation in photosynthesis, WUE<sub>i</sub> and leaf stable isotope composition (<sup>13</sup>C and <sup>18</sup>O); and (ii) to examine how genotypes and timing throughout the growing season affect the relationships between the aforementioned leaf traits. Measurements were performed in a young SRC plantation on six genotypes throughout the growing season (from early May to the end of September 2011). An atypical dry spring to summer period allowed studying the effect of soil water availability. We hypothesized that decreased soil water availability would lead to an increased WUE<sub>i</sub> and to a decreased PNUE, mainly due to diffusional (stomatal and mesophyll) limitation of assimilation. We investigated the relationship between WUE<sub>i</sub>, Δ<sup>13</sup>C and δ<sup>18</sup>O, as well as between PNUE and WUE<sub>i</sub>, including the potential effect of <italic>g</italic><sub>m</sub>. Based on the theory, we expected an inverse relationship between WUE<sub>i</sub> and Δ<sup>13</sup>C, between Δ<sup>13</sup>C and δ<sup>18</sup>O and between WUE<sub>i</sub> and PNUE. We hypothesized significant genotypic variation in the studied parameters and in their response to varying environmental parameters.</p></sec><sec sec-type="materials|methods" id="s2"><title>Materials and methods</title><sec id="s2a"><title>Experimental site and plant material</title><p>The experimental site was located in Lochristi, East-Flanders, Belgium (51°06′44″N, 3°51′02″E; 6.25 m above sea level). The poplar bioenergy plantation (<uri xlink:type="simple" xlink:href="http://uahost.uantwerpen.be/popfull">http://uahost.uantwerpen.be/popfull</uri>) was established in April 2010 on 18.4 ha of former agricultural land. The long-term average annual temperature at the site is 9.5 °C and the average annual precipitation is 726 mm, equally distributed over the year. A detailed soil analysis prior to planting characterized the soil type as sandy in texture, with clay-enriched deeper soil layers. After site preparation, 25-cm-long dormant and unrooted hardwood cuttings were planted at a density of 8000 ha<sup>−1</sup> in a double-row design, with alternating distances of 0.75 and 1.50 m between the rows and 1.1 m between the individuals within each row. A total area of 14.5 ha was planted with 12 selected poplar genotypes representing different species and hybrids of <italic>Populus deltoides</italic> Bartr. (ex Marsh.), <italic>Populus maximowiczii</italic> Henry, <italic>Populus nigra</italic> L. and <italic>Populus trichocarpa</italic> Torr & Gray (ex Hook), arranged in large monoclonal blocks. Neither irrigation nor fertilization was applied. Additional information on the site, the soil characteristics and the plantation layout can be found in <xref rid="TPU057C11" ref-type="bibr">Broeckx et al. (2012<italic>a</italic>)</xref>. For the present study, six out of the 12 poplar genotypes were retained, covering the different parentages present in the plantation: Koster and Oudenberg (<italic>P. deltoides</italic> × <italic>P. nigra</italic>), Bakan and Skado (<italic>P. trichocarpa</italic> × <italic>P. maximowiczii</italic>), Grimminge (<italic>P. deltoides</italic> × (<italic>P. trichocarpa</italic> × <italic>P. deltoides</italic>)) and Wolterson (<italic>P. nigra</italic>) (see <ext-link ext-link-type="uri" xlink:href="http://treephys.oxfordjournals.org/lookup/suppl/doi:10.1093/treephys/tpu057/-/DC1">Table S1A available as Supplementary Data at <italic>Tree Physiology</italic> Online</ext-link>; <xref rid="TPU057C11" ref-type="bibr">Broeckx et al. 2012<italic>a</italic></xref>)<italic>.</italic> All measurements reported in this contribution were performed between May and September 2011, i.e., during the second growing season of the SRC plantation.</p></sec><sec id="s2b"><title>Meteorological parameters</title><p>Meteorological parameters were recorded half-hourly using a meteorological mast installed within the SRC plantation at the experimental site. Air temperature and relative humidity data, recorded using Vaisala probes (Model HMP45C, Vaisala, Helsinki, Finland), were used to calculate vapour pressure deficit (VPD). The incoming short-wave radiation (SWR, 0.3–3 μm) was measured using a pyranometer (Model CNR1, Kipp & Zonen, Delft, The Netherlands). The amount of precipitation was measured with a tipping bucket rain gauge (Model 3665R, Spectrum Technologies, Inc., Plainfield, IL, USA). Moisture probes (TDR Model CS616, Campbell Scientific, Logan, UT, USA) placed at depths of 20 and 40 cm close to the mast were used to measure soil water content (SWC, m<sup>3</sup> m<sup>−3</sup>). As a complement, soil water potential (<italic>Ψ</italic><sub>S</sub>) was measured from June to November 2011 using calibrated equitensiometer probes (Type EQ-2, Delta-T Devices Ltd, Cambridge, UK) installed at depths of 20 and 40 cm at four locations around the mast. We chose to characterize soil water availability along the growing season through the time course of <italic>Ψ</italic><sub>S</sub> values, averaged among the four locations. Therefore, <italic>Ψ</italic><sub>S</sub> values were extrapolated for the missing period (May–early June) based on the relationship observed between SWC and <italic>Ψ</italic><sub>S</sub> measurements at each measuring depth. A feed-forward Neural Network (Matlab R2012a, Mathworks, Natick, MA, USA) was used to interpolate missing values. The correlation between predicted and measured values ranged between 0.83 and 0.98 for different soil depths (see <xref rid="TPU057C13" ref-type="bibr">Broeckx et al. 2013</xref>).</p></sec><sec id="s2c"><title>Leaf gas exchange, chlorophyll content and PNUE</title><p>Leaf gas exchange measurements were performed repeatedly on the same trees during the 2011 growing season in seven measurement campaigns (MCs): 4–6 May (MC1), 18–20 May (MC2), 4–8 July (MC3), 27–29 July (MC4), 16–19 August (MC5), 5–9 September (MC6) and 26–30 September 2011 (MC7). For the six genotypes, measurements were done on four replicate trees located close to the mast with a LI-6400 open path photosynthesis system (Li-Cor, Lincoln, NE, USA) equipped with a leaf chamber fluorometer (LI-6400-40, Li-Cor). Measurements were taken in the upper canopy, on the first fully mature sunlit leaf of the current-year main axis. To minimize differences in leaf age across MCs, we sampled leaves of the same leaf rank. Leaves were first acclimated for 10 min in the chamber at a CO<sub>2</sub> concentration of 400 ppm and under a photosynthetic photon flux density (PPFD) of 1500 μmol m<sup>−2</sup> s<sup>−1</sup>. Preliminary test experiments had shown that this PPFD was enough to ensure saturating light conditions for all genotypes. Afterwards, light-saturated assimilation rate at atmospheric CO<sub>2</sub> concentration (<italic>A</italic><sub>sat</sub>, μmol m<sup>−2</sup> s<sup>−1</sup>) and stomatal conductance (<italic>g</italic><sub>s-sat</sub>, mol m<sup>−2</sup> s<sup>−1</sup>) were recorded before establishing the response of the net assimilation rate (<italic>A</italic>) to varying intercellular CO<sub>2</sub> concentrations (<italic>C</italic><sub>i</sub>), i.e., the <italic>A</italic>–<italic>C</italic><sub>i</sub> curve. Each curve consisted of 10 steps of external CO<sub>2</sub> concentrations set in succession to 400, 300, 250, 150, 100, 50, 500, 750, 1000 and 1250 ppm (<xref rid="TPU057C62" ref-type="bibr">Monclus et al. 2006</xref>). Leaves were allowed to equilibrate at least 3 min at each step before data were logged. Net assimilation rates were corrected for the effect of CO<sub>2</sub> diffusion, according to the instrument manual (LI-6400XT Version 6), using a diffusion correction term of 0.46 μmol s<sup>−1</sup>. Before logging at each step of the <italic>A</italic>–<italic>C</italic><sub>i</sub> curves, steady state (<italic>F</italic><sub><italic>s</italic></sub>) and maximum fluorescence (<italic>F</italic><sub><italic>m</italic></sub>′) were measured during a light-saturating pulse (7 mmol m<sup>−2</sup> s<sup>−1</sup>) and the efficiency of Photosystem II (<italic>Φ</italic><sub>PSII</sub>) was determined as:
<disp-formula id="TPU057UM1"><mml:math id="M1"><mml:msub><mml:mi mathvariant="normal">Φ</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">PSII</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mstyle><mml:mrow><mml:mfrac><mml:mrow><mml:msubsup><mml:mi>F</mml:mi><mml:mrow><mml:mi mathvariant="normal">m</mml:mi></mml:mrow><mml:mi mathvariant="normal">′</mml:mi></mml:msubsup><mml:mo>−</mml:mo><mml:msub><mml:mi>F</mml:mi><mml:mrow><mml:mi mathvariant="normal">s</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msubsup><mml:mi>F</mml:mi><mml:mrow><mml:mi mathvariant="normal">m</mml:mi></mml:mrow><mml:mi mathvariant="normal">′</mml:mi></mml:msubsup></mml:mrow></mml:mfrac></mml:mrow><mml:mo>.</mml:mo></mml:mstyle></mml:math></disp-formula></p><p>Then, the CO<sub>2</sub> concentration in the chamber was set back to 400 ppm. Once the net assimilation rate had stabilized, the response to varying light intensities was recorded (<italic>A</italic>-light curve). Leaf photosynthesis was measured at eight PPFD intensities in the following order: 1500, 1000, 800, 600, 400, 200, 100, 0 μmol m<sup>−2</sup> s<sup>−1</sup>. A minimum of 2 min of leaf equilibration was set at each step before data were logged. Dark respiration was defined as the absolute CO<sub>2</sub> exchange rate measured during the last step of the <italic>A</italic>-light curve. All measurements were done at a constant block temperature (25 °C) and at a controlled VPD close to 1 kPa (1.2 ± 0.04, mean ± SE). Intrinsic water-use efficiency under saturating conditions (<inline-formula><mml:math id="M2"><mml:msub><mml:mtext>WUE</mml:mtext><mml:mrow><mml:mi mathvariant="normal">i</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mtext> mmol</mml:mtext><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">CO</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:msub><mml:msubsup><mml:mtext> mol</mml:mtext><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">H</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msub><mml:mtext> O</mml:mtext></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msubsup></mml:math></inline-formula>) was calculated as the ratio between the values of <italic>A</italic><sub>sat</sub> and <italic>g</italic><sub>s-sat</sub> obtained from the <italic>A</italic>–<italic>C</italic><sub>i</sub> and <italic>A</italic>-light curves under reference conditions (PPFD of 1500 μmol m<sup>−2</sup> s<sup>−1</sup> and CO<sub>2</sub> concentration of 400 ppm).</p><p>Once gas exchange measurements were completed, a minimum of six chlorophyll readings was taken on the same leaf with a portable chlorophyll content meter (CCM-200, Opti-Sciences, Inc., Hudson, NH, USA). Total chlorophyll content (Chl) was estimated from the CCM values according to the equations reported in <xref rid="TPU057C74" ref-type="bibr">Richardson et al. (2002)</xref>. The leaf sampled was then harvested and the individual leaf area (LA) was measured using a LI-3000 leaf area meter (Li-Cor). A subsample was punched out of the leaf lamina to determine leaf mass per area (LMA, g m<sup>−2</sup>) after drying at 70 °C; LMA was only available from MC3 onwards. The dried leaf material was then ground and used for the assessment of the leaf N content per unit mass (<italic>N</italic><sub>M</sub>, mg g<sup>−1</sup>) with an elemental analyser (Carlo Erba, NA 1500-NC, Milan, Italy). The values of <italic>N</italic><sub>M</sub> were converted to N content per unit area (<italic>N</italic><sub>A</sub>, mg cm<sup>−2</sup>) using LMA values. Photosynthetic nitrogen-use efficiency (μmol mg<sup>−1</sup> s<sup>−1</sup>) was calculated as the ratio of <italic>A</italic><sub>sat</sub> (μmol m<sup>−2</sup> s<sup>−1</sup>) to <italic>N</italic><sub>A</sub>.</p></sec><sec id="s2d"><title>Estimation of mesophyll conductance and photosynthetic parameters</title><p>The mesophyll diffusion conductance to CO<sub>2</sub> from the sub-stomatal cavities to the chloroplast (<italic>g</italic><sub>m</sub>) was estimated by combining gas exchange and chlorophyll fluorescence measurements (<xref rid="TPU057C69" ref-type="bibr">Pons et al. 2009</xref>). The rate of photosynthetic electron transport (<italic>J</italic><sub>ETR</sub>) was calculated as:
<disp-formula id="TPU057UM2"><mml:math id="M3"><mml:msub><mml:mi>J</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">ETR</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mi>α</mml:mi><mml:mo>×</mml:mo><mml:mn>0.5</mml:mn><mml:mo>×</mml:mo><mml:mtext>PPFD</mml:mtext><mml:mo>×</mml:mo><mml:msub><mml:mi mathvariant="normal">Φ</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">PSII</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mo>,</mml:mo></mml:math></disp-formula>where <italic>α</italic> is the leaf absorptance and 0.5 is the fraction of photons absorbed by Photosystem II. Absorptance was derived from the CCM readings according to <xref rid="TPU057C5" ref-type="bibr">Bauerle et al. (2004)</xref> after conversion of the CCM readings to soil plant analysis development (SPAD) values (<xref rid="TPU057C74" ref-type="bibr">Richardson et al. 2002</xref>). Mesophyll conductance was then estimated following the equation of <xref rid="TPU057C50" ref-type="bibr">Harley et al. (1992)</xref>:
<disp-formula id="TPU057UM3"><mml:math id="M4"><mml:msub><mml:mi>g</mml:mi><mml:mrow><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mstyle><mml:mrow><mml:mfrac><mml:mi>A</mml:mi><mml:mrow><mml:msub><mml:mi>C</mml:mi><mml:mrow><mml:mi mathvariant="normal">i</mml:mi></mml:mrow></mml:msub><mml:mo>−</mml:mo><mml:mfenced open="(" close=")"><mml:mrow><mml:mrow><mml:mrow><mml:mn>42.7</mml:mn><mml:mfenced open="[" close="]"><mml:mrow><mml:msub><mml:mi>J</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">ETR</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:mn>8</mml:mn><mml:mo stretchy="false">(</mml:mo><mml:mi>A</mml:mi><mml:mo>+</mml:mo><mml:msub><mml:mi>R</mml:mi><mml:mrow><mml:mi mathvariant="normal">d</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mfenced></mml:mrow><mml:mrow><mml:mo>/</mml:mo></mml:mrow><mml:mrow><mml:mfenced open="[" close="]"><mml:mrow><mml:msub><mml:mi>J</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">ETR</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mo>−</mml:mo><mml:mn>4</mml:mn><mml:mo stretchy="false">(</mml:mo><mml:mi>A</mml:mi><mml:mo>+</mml:mo><mml:msub><mml:mi>R</mml:mi><mml:mrow><mml:mi mathvariant="normal">d</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mfenced></mml:mrow></mml:mrow></mml:mrow></mml:mfenced></mml:mrow></mml:mfrac></mml:mrow><mml:mo>,</mml:mo></mml:mstyle></mml:math></disp-formula>where 42.7 is the CO<sub>2</sub> compensation point in the absence of dark respiration, as taken from <xref rid="TPU057C6" ref-type="bibr">Bernacchi et al. (2001)</xref>, and <italic>R</italic><sub>d</sub> is the mitochondrial respiration in the light, taken as half of the dark respiration obtained from the <italic>A</italic>-light curves (<xref rid="TPU057C67" ref-type="bibr">Piel et al. 2002</xref>, <xref rid="TPU057C65" ref-type="bibr">Niinemets et al. 2005</xref>). The values of <italic>g</italic><sub>m</sub> were then used to convert <italic>A</italic>–<italic>C</italic><sub>i</sub> curves to <italic>A</italic>–<italic>C</italic><sub>c</sub> curves, with <italic>C</italic><sub>c</sub> being the CO<sub>2</sub> concentration in the chloroplast stroma calculated as (<xref rid="TPU057C56" ref-type="bibr">Limousin et al. 2010</xref>, <xref rid="TPU057C61" ref-type="bibr">Misson et al. 2010</xref>):
<disp-formula id="TPU057UM4"><mml:math id="M5"><mml:msub><mml:mi>C</mml:mi><mml:mrow><mml:mi mathvariant="normal">c</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mrow><mml:mi mathvariant="normal">i</mml:mi></mml:mrow></mml:msub><mml:mo>−</mml:mo><mml:mstyle><mml:mrow><mml:mfrac><mml:mi>A</mml:mi><mml:mrow><mml:msub><mml:mi>g</mml:mi><mml:mrow><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfrac></mml:mrow><mml:mo>.</mml:mo></mml:mstyle></mml:math></disp-formula></p><p>The maximum carboxylation rate (<italic>V</italic><sub>cmax</sub>) and the maximum rate of electron transport (<italic>J</italic><sub>max</sub>) were estimated by fitting the <italic>A</italic>–<italic>C</italic><sub>c</sub> curves to the biochemical photosynthesis model of <xref rid="TPU057C31" ref-type="bibr">Farquhar et al. (1980)</xref> using the routine developed by <xref rid="TPU057C82" ref-type="bibr">Sharkey et al. (2007)</xref>. The Michaelis constant of Rubisco for carbon dioxide (<italic>K</italic><sub>c</sub>), the inhibition constant of Rubisco for oxygen (<italic>K</italic><sub>o</sub>) and the photocompensation point (<italic>Γ</italic>*) used for fitting were taken from <xref rid="TPU057C82" ref-type="bibr">Sharkey et al. (2007)</xref>.</p></sec><sec id="s2e"><title>Carbon and oxygen stable isotope analyses</title><p>Isotopic analyses were performed at the Stable Isotope Laboratory of the James Hutton Institute (Invergowrie, Dundee, UK). Bulk leaf carbon isotope composition (δ<sup>13</sup>C<sub>bl</sub>) was determined on the leaves used for gas exchange measurements. Subsamples of ground leaf material were enclosed and weighed in tin capsules and combusted in a continuous flow isotope ratio mass spectrometer (IRMS) (Delta V, Thermo Fisher Scientific, Bremen, Germany). The CO<sub>2</sub> produced by combustion was purified and its <sup>13</sup>CO<sub>2</sub>/<sup>12</sup>CO<sub>2</sub> ratio was analysed by the IRMS. The δ<sup>13</sup>C<sub>bl</sub> (‰) was expressed relative to the Pee Dee Belemnite standard (<xref rid="TPU057C19" ref-type="bibr">Craig 1957</xref>). The accuracy of measurements was assessed by repeated measures of laboratory standards and was ±0.08‰ (standard deviation). Carbon isotope discrimination between the atmosphere and the bulk leaf organic matter (Δ<sup>13</sup>C<sub>bl</sub>, ‰) was then calculated as in <xref rid="TPU057C33" ref-type="bibr">Farquhar et al. (1989)</xref>:
<disp-formula id="TPU057UM5"><mml:math id="M6"><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow></mml:msup><mml:msub><mml:mi>C</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">bl</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mstyle><mml:mrow><mml:mfrac><mml:mrow><mml:msup><mml:mrow><mml:mi>δ</mml:mi></mml:mrow><mml:mrow><mml:mn>13</mml:mn></mml:mrow></mml:msup><mml:msub><mml:mi>C</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">air</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mi>δ</mml:mi></mml:mrow><mml:mrow><mml:mn>13</mml:mn></mml:mrow></mml:msup><mml:msub><mml:mi>C</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">bl</mml:mi></mml:mrow></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:mo stretchy="false">[</mml:mo><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mrow><mml:msup><mml:mrow><mml:mi>δ</mml:mi></mml:mrow><mml:mrow><mml:mn>13</mml:mn></mml:mrow></mml:msup><mml:msub><mml:mi>C</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">bl</mml:mi></mml:mrow></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:mo>/</mml:mo></mml:mrow><mml:mrow><mml:mn>1000</mml:mn></mml:mrow></mml:mrow><mml:mo stretchy="false">)</mml:mo><mml:mo stretchy="false">]</mml:mo></mml:mrow></mml:mfrac></mml:mrow><mml:mo>,</mml:mo></mml:mstyle></mml:math></disp-formula>with δ<sup>13</sup>C<sub>air</sub> assumed to equal −8‰.</p><p>The same leaf powder used for δ<sup>13</sup>C analyses was used to measure the <sup>18</sup>O composition of bulk leaf matter (δ<sup>18</sup>O<sub>bl</sub>). Leaf material was enclosed and weighed in silver capsules. Analyses were conducted with a continuous flow IRMS (Delta Plus XP, Thermo Fisher Scientific) interfaced with a high temperature elemental analyser. Bulk leaf oxygen isotope composition was expressed relative to the sea mean ocean water standard and the analytical precision for repeated measurements was ±0.09‰ (standard deviation).</p></sec><sec id="s2f"><title>Statistical analysis</title><p>Some data were missing at random (MAR) and could be ignored for parameters and genotypes that were measured from the third MC onwards (<xref rid="TPU057C86" ref-type="bibr">Verbeke and Molenberghs 2000</xref>). The mixed procedure for repeated measurements was used to analyse the effects of genotype and seasonality on the above-mentioned parameters. Measurements were performed seven times during the growing season (repeated variable ‘MC’) on the same four replicate trees of each genotype (subject variable ‘Tree’). A linear mixed model with fixed effects genotype, MC and their interaction—indicating the genotype-specific behaviour in time—was used. The unstructured repeated covariance structure was chosen and the variance component was estimated using restricted maximum likelihood (REML). When significant genotype or MC effects were found, pairwise comparisons of the means were performed using the Bonferroni adjustment (see <ext-link ext-link-type="uri" xlink:href="http://treephys.oxfordjournals.org/lookup/suppl/doi:10.1093/treephys/tpu057/-/DC1">Table S2A available as Supplementary Data at <italic>Tree Physiology</italic> Online</ext-link>). Relationships between photosynthetic, WUE and isotopic parameters were examined using linear and non-linear regression analyses and coefficients of determination (<italic>R</italic><sup>2</sup>) as well as genotype-specific Spearman's rank correlation coefficients. All statistical tests were considered significant when <italic>P</italic> < 0.05. All statistical analyses were performed in SPSS 20.0 (IBM Corp., SPSS Statistics for Windows, Armonk, NY, USA).</p></sec></sec><sec sec-type="results" id="s3"><title>Results</title><p>The seasonal course of precipitation, air temperature, daytime (SWR >20 W m<sup>−2</sup>) maximum VPD (VPD<sub>max</sub>) and soil water availability at the site during the 2011 growing season (May–September) is presented in Figure <xref ref-type="fig" rid="TPU057F1">1</xref>. Although the 2011 growing season showed a normal pattern of temperature and rainfall throughout the season, there were a few periods with dry conditions. The first drop in soil water potential (<italic>Ψ</italic><sub>s</sub>) was observed at the end of May in the upper soil layer (20 cm depth). Close to MC2 <italic>Ψ</italic><sub>s</sub> peaked at approximately −1.8 MPa, while there was no apparent response in the 40-cm depth layer. The precipitation and lower VPD that occurred afterwards led to a progressive recovery. The second drop in <italic>Ψ</italic><sub>s</sub> to −1.5 MPa was observed in mid-July (close to MC3) for both soil layers, concomitantly with high air temperatures and high VPD. The high amount of precipitation after mid-July combined with a progressive decrease in VPD resulted in the recovery of <italic>Ψ</italic><sub>s</sub> close to zero for the rest of the growing season (MC4–MC7).
<fig id="TPU057F1" position="float"><label>Figure 1.</label><caption><p>Seasonal time course of the main meteorological parameters during the period of this study (May–September 2011): (a) precipitation; (b) daily minimum (<italic>T</italic><sub>air</sub> min) and maximum (<italic>T</italic><sub>air</sub> max) air temperature; (c) daytime maximum vapour pressure deficit (VPD<sub>max</sub>); and (d) soil water potential at 20 cm (solid line) and 40 cm (dotted line) soil depths. Grey bars indicate the timing of gas exchange MCs: 4–6 May (MC1), 18–20 May (MC2), 4–8 July (MC3), 27–29 July (MC4), 16–19 August (MC5), 5–9 September (MC6), 26–30 September 2011 (MC7).</p></caption><graphic xlink:href="tpu05701"></graphic></fig></p><p>Overall, nearly all of the photosynthetic leaf traits differed significantly among genotypes and fluctuated during the growing season, i.e., along the MCs (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>, Table <xref ref-type="table" rid="TPU057TB1">1</xref>; see <ext-link ext-link-type="uri" xlink:href="http://treephys.oxfordjournals.org/lookup/suppl/doi:10.1093/treephys/tpu057/-/DC1">Table S2A available as Supplementary Data at <italic>Tree Physiology</italic> Online</ext-link>). Considering the average pattern across the six genotypes, <italic>A</italic><sub>sat</sub>, <italic>g</italic><sub>s-sat</sub> and Δ<sup>13</sup>C<sub>bl</sub> exhibited a similar time course with a pronounced decrease in mid-July (MC3), when the soil water potential was low at both 20 and 40 cm depths, and a progressive increase towards the end of the growing season (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>a, b and d). The values of WUE<sub>i</sub> followed an opposite trend (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>c). The time course observed for <italic>V</italic><sub>cmax</sub>, <italic>J</italic><sub>max</sub> and <italic>g</italic><sub>m</sub> was slightly different. <italic>V</italic><sub>cmax</sub> and <italic>J</italic><sub>max</sub> increased progressively during the growing season and <italic>g</italic><sub>m</sub> decreased, especially in July (MC3; Figure <xref ref-type="fig" rid="TPU057F2">2</xref>f and g; <italic>J</italic><sub>max</sub> data not shown). Mesophyll conductance showed overall a similar seasonal evolution to that of <italic>g</italic><sub><italic>s-</italic></sub><sub>sat</sub> for the dry period May–July but remained higher than <italic>g</italic><sub>s-sat</sub> (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>b and g). From August onwards, however, <italic>g</italic><sub>s-sat</sub> and <italic>g</italic><sub>m</sub> followed an opposite pattern; <italic>g</italic><sub>m</sub> decreased progressively (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>b and g). The overall means of <italic>V</italic><sub>cmax</sub> and <italic>J</italic><sub>max</sub> were 125.2 and 172.1 μmol m<sup>−2</sup> s<sup>−1</sup>, respectively (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>f), both parameters being strongly and linearly correlated across genotypes and MCs (<italic>R</italic><sup>2</sup> = 0.79; <italic>P</italic> < 0.0001). A decrease throughout the growing season was also observed in δ<sup>18</sup>O<sub>bl</sub> (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>e). The seasonal trends in <italic>N</italic><sub>A</sub> and in LMA were less obvious (despite a significant time effect; Table <xref ref-type="table" rid="TPU057TB1">1</xref>), potentially due to some missing data points in the beginning of the growing season (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>h and i). Photosynthetic nitrogen-use efficiency was lower in July at low soil water availability (MC3; Figure <xref ref-type="fig" rid="TPU057F2">2</xref>j), but—as for <italic>N</italic><sub>A</sub> and LMA—the response to water availability was less clear. Genotypes were not significantly different in their seasonal evolution of <italic>N</italic><sub>A</sub> and PNUE (Table <xref ref-type="table" rid="TPU057TB1">1</xref>).
<table-wrap id="TPU057TB1" position="float"><label>Table 1.</label><caption><p>Output of the mixed model analysis (REML) showing the effects of genotype and time in the season (MC) on photosynthetic and related parameters. The different parameters have been identified and described in the text. *, 0.01 < <italic>P</italic> ≤ 0.05; **, 0.001 < <italic>P</italic> ≤ 0.01; ***, <italic>P</italic> ≤ 0.001; MC, measurement campaign.</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col><col align="left" span="1"></col><col align="left" span="1"></col><col align="left" span="1"></col><col align="left" span="1"></col><col align="left" span="1"></col><col align="left" span="1"></col></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Parameters</th><th align="center" rowspan="1" colspan="1">df</th><th align="center" rowspan="1" colspan="1">Genotype</th><th align="center" rowspan="1" colspan="1">Df</th><th align="center" rowspan="1" colspan="1">MC</th><th align="center" rowspan="1" colspan="1">df</th><th align="center" rowspan="1" colspan="1">Genotype × MC</th></tr></thead><tbody><tr><td rowspan="1" colspan="1"><italic>A</italic><sub>sat</sub></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">25</td><td rowspan="1" colspan="1">***</td></tr><tr><td rowspan="1" colspan="1"><italic>g</italic><sub>s-sat</sub></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">25</td><td rowspan="1" colspan="1">***</td></tr><tr><td rowspan="1" colspan="1">WUE<sub>i</sub></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">**</td><td rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">25</td><td rowspan="1" colspan="1">*</td></tr><tr><td rowspan="1" colspan="1">Δ<sup>13</sup>C<sub>bl</sub></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">26</td><td rowspan="1" colspan="1">*</td></tr><tr><td rowspan="1" colspan="1">δ<sup>18</sup>O<sub>bl</sub></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">**</td><td rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">26</td><td rowspan="1" colspan="1">***</td></tr><tr><td rowspan="1" colspan="1"><italic>V</italic><sub>cmax</sub></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">**</td><td rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">25</td><td rowspan="1" colspan="1">***</td></tr><tr><td rowspan="1" colspan="1"><italic>J</italic><sub>max</sub></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">**</td><td rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">25</td><td rowspan="1" colspan="1">***</td></tr><tr><td rowspan="1" colspan="1"><italic>g</italic><sub>m</sub><sup><xref rid="TPU057C1" ref-type="bibr">1</xref></sup></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">24</td><td rowspan="1" colspan="1">**</td></tr><tr><td rowspan="1" colspan="1"><italic>N</italic><sub>A</sub></td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">4</td><td rowspan="1" colspan="1">**</td><td rowspan="1" colspan="1">20</td><td rowspan="1" colspan="1"></td></tr><tr><td rowspan="1" colspan="1">LMA</td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1">4</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">20</td><td rowspan="1" colspan="1">***</td></tr><tr><td rowspan="1" colspan="1">PNUE</td><td rowspan="1" colspan="1">5</td><td rowspan="1" colspan="1">**</td><td rowspan="1" colspan="1">4</td><td rowspan="1" colspan="1">***</td><td rowspan="1" colspan="1">19</td><td rowspan="1" colspan="1"></td></tr></tbody></table><table-wrap-foot><fn id="tbfn1"><p><sup><xref rid="TPU057C1" ref-type="bibr">1</xref></sup>Heterogeneous Toeplitz covariance structure was used.</p></fn></table-wrap-foot></table-wrap><fig id="TPU057F2" position="float"><label>Figure 2.</label><caption><p>Seasonal evolution of (a) net assimilation rate (<italic>A</italic><sub>sat</sub>); (b) stomatal conductance (<italic>g</italic><sub>s-sat</sub>); (c) intrinsic water-use efficiency (WUE<sub>i</sub>); (d) bulk leaf carbon isotope discrimination (Δ<sup>13</sup>C<sub>bl</sub>); (e) bulk leaf oxygen isotope composition (δ<sup>18</sup>O<sub>bl</sub>); (f) maximum carboxylation rate (<italic>V</italic><sub>cmax</sub>); (g) mesophyll conductance (<italic>g</italic><sub>m</sub>); (h) area-based leaf N content (<italic>N</italic><sub>A</sub>); (i) leaf mass per area (LMA); and (j) photosynthetic nitrogen-use efficiency (PNUE). Data points represent genotypic means (±SE) for six poplar genotypes of different parentages: T × M (Bakan, Skado), D × N (Koster, Oudenberg), D × (T × D) (Grimminge) and N (Wolterson).</p></caption><graphic xlink:href="tpu05702"></graphic></fig></p><p>A closer look at the observed results showed that the six genotypes did not respond in the same way or with the same amplitude with time in the growing season, as indicated by the significant genotype × MC interactions observed for most traits (Table <xref ref-type="table" rid="TPU057TB1">1</xref>; see also Figure <xref ref-type="fig" rid="TPU057F2">2</xref>). Differences among genotypes were particularly reinforced during the dry period around MC3 (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>). Genotypes Wolterson and Oudenberg were clearly less responsive to the dry period than the other genotypes in terms of <italic>A</italic><sub>sat</sub>, <italic>g</italic><sub>s-sat</sub>, WUE<sub>i</sub> and PNUE (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>a–c and j). Overall, genotype Wolterson showed the highest values of <italic>A</italic><sub>sat</sub>, <italic>g</italic><sub>s-sat</sub>, <italic>V</italic><sub>cmax</sub> and <italic>N</italic><sub>A</sub> throughout most of the growing season (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>a, b, f and h), while WUE<sub>i</sub> was at the lower end of the genotypic range (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>c). The ranking of the other genotypes changed substantially during the growing season, although genotypes Bakan and Skado remained consistently at the lower end of the range for <italic>A</italic><sub>sat</sub> and <italic>g</italic><sub>s-sat</sub> (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>a and b). Genotype Skado had the lowest Δ<sup>13</sup>C<sub>bl</sub> and the highest WUE<sub>i</sub> throughout the entire growing season (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>d and e). On the other end, the highest Δ<sup>13</sup>C<sub>bl</sub> values were observed for genotype Grimminge, which also showed the lowest <italic>V</italic><sub>cmax</sub> and <italic>J</italic><sub>max</sub> values with an early decrease from August onwards (MC5–7; Figure <xref ref-type="fig" rid="TPU057F2">2</xref>d and f). In contrast to other leaf traits, the genotypic ranking for <italic>N</italic><sub>A</sub> did not significantly change throughout the growing season (no significant genotype × MC interaction, Table <xref ref-type="table" rid="TPU057TB1">1</xref>; Figure <xref ref-type="fig" rid="TPU057F2">2</xref>h). Genotypes Wolterson and Grimminge generally showed the highest and lowest <italic>N</italic><sub>A</sub> values, respectively (Figure <xref ref-type="fig" rid="TPU057F2">2</xref>h).</p><p>The values of <italic>A</italic><sub>sat</sub> and <italic>g</italic><sub>s-sat</sub> were significantly, but non-linearly, related (<italic>A</italic><sub>sat</sub> = 36.25 × <italic>g</italic><sub>s-sat</sub>/(0.22 + <italic>g</italic><sub>s-sat</sub>)), with <italic>A</italic><sub>sat</sub> reaching saturation at high <italic>g</italic><sub>s-sat</sub> (Figure <xref ref-type="fig" rid="TPU057F3">3</xref>). A similar but less significant pattern was found between <italic>A</italic><sub>sat</sub> and <italic>g</italic><sub>m</sub><inline-formula><mml:math id="M7"><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>A</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">sat</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mn>22.67</mml:mn><mml:mo>×</mml:mo><mml:mo stretchy="false">(</mml:mo><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>7.27</mml:mn><mml:mo>×</mml:mo><mml:msub><mml:mi>g</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">s</mml:mi><mml:mo>−</mml:mo><mml:mi mathvariant="normal">sat</mml:mi></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:msup><mml:mo stretchy="false">)</mml:mo><mml:mo stretchy="false">)</mml:mo></mml:math></inline-formula>, with <italic>A</italic><sub>sat</sub> saturating at high <italic>g</italic><sub>m</sub>. The relationship between <italic>g</italic><sub>s-sat</sub> and <italic>g</italic><sub>m</sub> was linear at low values, with a decoupling among both parameters at higher values <inline-formula><mml:math id="M8"><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>g</mml:mi><mml:mrow><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mn>0.33</mml:mn><mml:mo>×</mml:mo><mml:mo stretchy="false">(</mml:mo><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>15.52</mml:mn><mml:mo>×</mml:mo><mml:msub><mml:mi>g</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">s</mml:mi><mml:mo>−</mml:mo><mml:mi mathvariant="normal">sat</mml:mi></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:msup><mml:mo stretchy="false">)</mml:mo><mml:mo stretchy="false">)</mml:mo></mml:math></inline-formula>. The linear part of the relationship was mainly determined by values recorded during MC3, when soil water availability was reduced.
<fig id="TPU057F3" position="float"><label>Figure 3.</label><caption><p>Curvilinear relationships between (a) stomatal conductance (<italic>g</italic><sub>s-sat</sub>) and net assimilation rate (<italic>A</italic><sub>sat</sub>); (b) mesophyll conductance (<italic>g</italic><sub>m</sub>) and net assimilation rate (<italic>A</italic><sub>sat</sub>); and (c) <italic>g</italic><sub>s-sat</sub> and <italic>g</italic><sub>m</sub>. Data points indicate the first letter of each genotype (B, Bakan; S, Skado; K, Koster; O, Oudenberg; G, Grimminge; W, Wolterson) followed by the number of MCs (<xref rid="TPU057C1" ref-type="bibr">1</xref>–<xref rid="TPU057C7" ref-type="bibr">7</xref>) and represent the mean of four individuals. For (a) the genotype-specific Spearman's correlation coefficients are presented (**, 0.001 < <italic>P</italic> ≤ 0.01; ***, <italic>P</italic> ≤ 0.001).</p></caption><graphic xlink:href="tpu05703"></graphic></fig></p><p>Net assimilation rate was linearly and negatively related to WUE<sub>i</sub> (Figure <xref ref-type="fig" rid="TPU057F4">4</xref>a). A stronger negative, but non-linear (WUE<sub>i</sub> = (0.15 × 0.31)/(0.31 + <italic>g</italic><sub>s-sat</sub>) relationship was found between <italic>g</italic><sub>s-sat</sub> and WUE<sub>i</sub> (Figure <xref ref-type="fig" rid="TPU057F4">4</xref>b). The ratio of <italic>g</italic><sub>m</sub> to <italic>g</italic><sub>s-sat</sub> was significantly and positively related to WUE<sub>i</sub> (Figure <xref ref-type="fig" rid="TPU057F4">4</xref>c). The highest values along the curve were identified as MC3 observations, suggesting a shift in the relative contribution of mesophyll vs stomatal limitation when soil water was limiting. As expected from the theory, Δ<sup>13</sup>C<sub>bl</sub> and WUE<sub>i</sub> were linearly and negatively related although the relationship showed some scatter (Figure <xref ref-type="fig" rid="TPU057F5">5</xref>b). There was no significant correlation between δ<sup>18</sup>O<sub>bl</sub> and Δ<sup>13</sup>C<sub>bl</sub> (Figure <xref ref-type="fig" rid="TPU057F5">5</xref>c). However, a significant and positive relationship was found between δ<sup>18</sup>O<sub>bl</sub> and WUE<sub>i</sub> (Figure <xref ref-type="fig" rid="TPU057F5">5</xref>a), while a significant and negative (non-linear; δ<sup>18</sup>O<sub>bl</sub> = (28.24 × 2.51)/(2.51 + <italic>g</italic><sub>s-sat</sub>); <italic>R</italic><sup>2</sup> = 0.42, <italic>P</italic> < 0.0001) relationship was observed between δ<sup>18</sup>O<sub>bl</sub> and <italic>g</italic><sub>s-sat</sub>.
<fig id="TPU057F4" position="float"><label>Figure 4.</label><caption><p>Relationships between (a) net assimilation rate (<italic>A</italic><sub>sat</sub>) and intrinsic water-use efficiency (WUE<sub>i</sub>); (b) stomatal conductance (<italic>g</italic><sub>s-sat</sub>) and WUE<sub>i</sub>; (c) the ratio of mesophyll conductance (<italic>g</italic><sub>m</sub>) to stomatal conductance (<italic>g</italic><sub>s-sat</sub>) and WUE<sub>i</sub>. Data points indicate the first letter of each genotype (B, Bakan; S, Skado; K, Koster; O, Oudenberg; G, Grimminge; W, Wolterson) followed by the number of MCs (<xref rid="TPU057C1" ref-type="bibr">1</xref>–<xref rid="TPU057C7" ref-type="bibr">7</xref>) and represent the mean of four individuals. For (b) the genotype-specific Spearman's correlation coefficients are presented (*, 0.01 < <italic>P</italic> ≤ 0.05; **, 0.001 < <italic>P</italic> ≤ 0.01; ***, <italic>P</italic> ≤ 0.001).</p></caption><graphic xlink:href="tpu05704"></graphic></fig><fig id="TPU057F5" position="float"><label>Figure 5.</label><caption><p>Relationships between (a) intrinsic water-use efficiency (WUE<sub>i</sub>) and bulk leaf oxygen isotope composition (δ<sup>18</sup>O<sub>bl</sub>); (b) WUE<sub>i</sub> and bulk leaf carbon isotope discrimination (Δ<sup>13</sup>C<sub>bl</sub>); (c) bulk leaf oxygen isotope composition (δ<sup>18</sup>O<sub>bl</sub>) and bulk leaf carbon isotope discrimination (Δ<sup>13</sup>C<sub>bl</sub>). Data points indicate the first letter of each genotype (B, Bakan; S, Skado; K, Koster; O, Oudenberg; G, Grimminge; W, Wolterson) followed by the number of MCs (<xref rid="TPU057C1" ref-type="bibr">1</xref>–<xref rid="TPU057C7" ref-type="bibr">7</xref>) and represent the mean of four individuals. For (b) the genotype-specific Spearman's correlation coefficients are presented (*, 0.01 < <italic>P</italic> ≤ 0.05; ***, <italic>P</italic> ≤ 0.001).</p></caption><graphic xlink:href="tpu05705"></graphic></fig></p><p>The maximum rate of carboxylation scaled positively with leaf N content, especially when expressed on an area basis (Figure <xref ref-type="fig" rid="TPU057F6">6</xref>). In addition, <italic>V</italic><sub>cmax</sub> and <italic>N</italic><sub>A</sub> scaled positively with Chl (data not shown). Leaf N content on an area basis was significantly and negatively correlated to WUE<sub>i</sub> (<italic>R</italic><sup>2</sup> = 0.18, <italic>P</italic> = 0.0123) but no relationship could be observed with Δ<sup>13</sup>C<sub>bl</sub>. No correlation was observed between <italic>N</italic><sub>A</sub> and LMA while <italic>N</italic><sub>M</sub> was significantly and positively correlated to LMA (<italic>R</italic><sup>2</sup> = 0.42, <italic>P</italic> < 0.0001). Neither <italic>g</italic><sub>m</sub> nor <italic>V</italic><sub>cmax</sub> was correlated to LMA. A significant and negative relationship was found between WUE<sub>i</sub> and PNUE, mainly due to the observations during MC3 (Figure <xref ref-type="fig" rid="TPU057F7">7</xref>a). Similarly, the significant and positive relationship between <italic>g</italic><sub>m</sub> and PNUE was mainly driven by MC3 readings.
<fig id="TPU057F6" position="float"><label>Figure 6.</label><caption><p>Relationship between the leaf N content (<italic>N</italic><sub>M</sub>) and the maximum rate of carboxylation (<italic>V</italic><sub>cmax_M</sub>) on a mass basis. The genotype-specific Spearman's correlation coefficients are presented (*, 0.01 < <italic>P</italic> ≤ 0.05; **, 0.001 < <italic>P</italic> ≤ 0.01). The insert panel shows the same relationship on an area basis, <italic>N</italic><sub>A</sub> vs <italic>V</italic><sub>cmax_A</sub>. Data points indicate the first letter of each genotype (B, Bakan; S, Skado; K, Koster; O, Oudenberg; G, Grimminge; W, Wolterson) followed by the number of MCs (<xref rid="TPU057C1" ref-type="bibr">1</xref>–<xref rid="TPU057C7" ref-type="bibr">7</xref>) and represent the mean of four individuals.</p></caption><graphic xlink:href="tpu05706"></graphic></fig><fig id="TPU057F7" position="float"><label>Figure 7.</label><caption><p>Relationships between (a) intrinsic water-use efficiency (WUE<sub>i</sub>) and photosynthetic nitrogen-use efficiency (PNUE); and (b) between mesophyll conductance (<italic>g</italic><sub>m</sub>) and PNUE. Data points indicate the first letter of each genotype (B, Bakan; S, Skado; K, Koster; O, Oudenberg; G, Grimminge; W, Wolterson) followed by the number of MCs (<xref rid="TPU057C1" ref-type="bibr">1</xref>–<xref rid="TPU057C7" ref-type="bibr">7</xref>) and represent the mean of four individuals. For (a) the genotype-specific Spearman's correlation coefficients are presented (*, 0.01 < <italic>P</italic> ≤ 0.05).</p></caption><graphic xlink:href="tpu05707"></graphic></fig></p></sec><sec sec-type="discussion" id="s4"><title>Discussion</title><p>The results reported above illustrate that photosynthesis-related leaf traits, including WUE<sub>i</sub>, significantly varied during the growing season in an SRC bioenergy plantation, and that this variation was genotype dependent in poplar. Furthermore, our results indicate that the relation between Δ<sup>13</sup>C<sub>bl</sub> and WUE<sub>i</sub> did not always hold throughout the growing season, and that water availability played a significant role in this relationship. Since we have shown that seasonal variations and genotypic differences in photosynthetic parameters are substantial in SRC poplar plantations, they need to be accounted for in future modelling studies. Seasonality of leaf gas exchange can result from leaf ontogeny and dynamic changes in environmental conditions such as light, nutrients, temperature or water availability. In our study, potential effects of leaf ontogeny were minimized by always measuring recently matured leaves emerging on the current-year axis, taking advantage of the indeterminate growth of poplars. As all measurements were performed under saturating irradiance and constant VPD<italic>,</italic> seasonal variations could be mostly attributed to variations in soil water availability. Temporal variation in photosynthetic parameters is important in determining the seasonality and magnitude of ecosystem carbon fluxes and is therefore an important factor to consider for modelling studies (<xref rid="TPU057C92" ref-type="bibr">Wilson et al. 2001</xref>).</p><p>Leaf photosynthetic parameters recorded in this study were consistent with data previously reported for several poplar species and hybrids (<xref rid="TPU057C78" ref-type="bibr">Roupsard et al. 1996</xref>, <xref rid="TPU057C68" ref-type="bibr">Pons and Westbeek 2004</xref>, <xref rid="TPU057C75" ref-type="bibr">Ripullone et al. 2004</xref>, <xref rid="TPU057C62" ref-type="bibr">Monclus et al. 2006</xref>, <xref rid="TPU057C45" ref-type="bibr">Gornall and Guy 2007</xref>, <xref rid="TPU057C83" ref-type="bibr">Soolanayakanahally et al. 2009</xref>, <xref rid="TPU057C34" ref-type="bibr">Fichot et al. 2010</xref>, <xref rid="TPU057C35" ref-type="bibr">2011</xref>). Eddy covariance measurements of net ecosystem CO<sub>2</sub> fluxes performed during the same period confirmed a net ecosystem carbon uptake until the end of September (<xref rid="TPU057C13" ref-type="bibr">Broeckx et al. 2013</xref>, <xref rid="TPU057C97" ref-type="bibr">Zona et al. 2013</xref>). This indicated a good agreement between the timing of leaf-level and canopy-level photosynthetic processes in the plantation. High photosynthetic activity until the end of September has already been reported for three different genotypes of <italic>P. alba</italic> L., <italic>P. nigra</italic> L. and <italic>P. deltoides</italic> × <italic>P. nigra</italic> (<xref rid="TPU057C7" ref-type="bibr">Bernacchi et al. 2003</xref>). However, this pattern contrasts with data reported for other temperate deciduous species such as ash, maple and oak, for which photosynthetic uptake and photosynthetic capacity already showed a substantial decline by early or mid-September (<xref rid="TPU057C90" ref-type="bibr">Wilson et al. 2000<italic>a</italic></xref>, <xref rid="TPU057C47" ref-type="bibr">Grassi et al. 2005</xref>, <xref rid="TPU057C24" ref-type="bibr">Dillen et al. 2012</xref>). Delayed senescence with sustained carbon uptake is most likely associated with the pioneering and fast-growth habit of poplar species.</p><p>Drought-induced variations in leaf photosynthesis can be mediated by stomatal closure, by changes in mesophyll conductance to CO<sub>2</sub> and by alterations of photosynthetic capacities. Reduced <italic>g</italic><sub>m</sub> was observed concomitantly with reduced <italic>g</italic><sub>s-sat</sub> during the period of low water availability, as already documented for different species (<xref rid="TPU057C78" ref-type="bibr">Roupsard et al. 1996</xref>, <xref rid="TPU057C89" ref-type="bibr">Warren et al. 2004</xref>, <xref rid="TPU057C42" ref-type="bibr">Galmes et al. 2007</xref>, <xref rid="TPU057C39" ref-type="bibr">Flexas et al. 2008</xref>). However, in the present study not all poplar genotypes responded in the same way to drier soil conditions, indicating substantial genotypic variation in the degree of this response. Local measurements of soil water potential around the mast could not exclude the possibility of genotypic differences in soil water potential related to genotypic differences in total LA. Bigger trees encounter a more rapid and more severe water shortage due to their high transpiratory water loss. In contrast, the values of <italic>V</italic><sub>cmax</sub> and <italic>J</italic><sub>max</sub> did not show any clear pattern during the dry period, suggesting that the decrease in photosynthesis was mostly caused by diffusional limitations (stomatal and non-stomatal) rather than by biochemical limitations. This is consistent with the idea that biochemical limitations become quantitatively important only during severe droughts (<xref rid="TPU057C46" ref-type="bibr">Grassi and Magnani 2005</xref>, <xref rid="TPU057C42" ref-type="bibr">Galmes et al. 2007</xref>). The values of <italic>V</italic><sub>cmax</sub> were tightly correlated with leaf N contents expressed either on a unit mass or on an area basis, suggesting that leaf N contents were a reliable estimator of photosynthetic capacities across all poplar genotypes along the growing season (<xref rid="TPU057C95" ref-type="bibr">Zhu et al. 2011</xref>). The constant <italic>N</italic><sub>A</sub> observed during the period of low water availability is in line with the absence of a reduction in <italic>V</italic><sub>cmax</sub>, and suggests that there was no marked seasonal change in N allocation to the photosynthetic apparatus (i.e., Rubisco and chlorophyll) (<xref rid="TPU057C20" ref-type="bibr">Demarez et al. 1999</xref>, <xref rid="TPU057C64" ref-type="bibr">Montpied et al. 2009</xref>).</p><p>Stomatal conductance remained higher than <italic>g</italic><sub>m</sub> during the drier period, suggesting that stomatal conductance was actually the most limiting process to photosynthesis at this time. This is in line with other studies (<xref rid="TPU057C91" ref-type="bibr">Wilson et al. 2000<italic>b</italic></xref>, <xref rid="TPU057C46" ref-type="bibr">Grassi and Magnani 2005</xref>, <xref rid="TPU057C65" ref-type="bibr">Niinemets et al. 2005</xref>, <xref rid="TPU057C56" ref-type="bibr">Limousin et al. 2010</xref>, <xref rid="TPU057C40" ref-type="bibr">Flexas et al. 2012</xref>). The relative contribution of stomatal vs mesophyll conductance to total limitations may however vary with species, with drought intensity and also with canopy position (<xref rid="TPU057C22" ref-type="bibr">Diaz-Espejo et al. 2007</xref>, <xref rid="TPU057C42" ref-type="bibr">Galmes et al. 2007</xref>, <xref rid="TPU057C15" ref-type="bibr">Cano et al. 2013</xref>, <xref rid="TPU057C41" ref-type="bibr">Flexas et al. 2013</xref>). This was confirmed in our study by the fact that <italic>g</italic><sub>s</sub> reached higher values than <italic>g</italic><sub>m</sub> by the end of the growing season. The curvilinear relationship between <italic>g</italic><sub>m</sub> and <italic>g</italic><sub>s-sat</sub> substantiates the modelled relationship predicted by <xref rid="TPU057C84" ref-type="bibr">Tholen et al. (2012)</xref>. Significant relationships between <italic>g</italic><sub>s</sub> and <italic>g</italic><sub>m</sub> have also been reported in other studies (<xref rid="TPU057C25" ref-type="bibr">Douthe et al. 2011</xref>, <xref rid="TPU057C29" ref-type="bibr">Egea et al. 2011</xref>, <xref rid="TPU057C14" ref-type="bibr">Buckley and Warren 2014</xref>).</p><p>Variations in WUE<sub>i</sub> originate from variations in either <italic>A</italic>, <italic>g</italic><sub>s</sub> or both (<xref rid="TPU057C30" ref-type="bibr">Farquhar and Richards 1984</xref>). Previous studies on poplars have suggested that variations among genotypes are generally driven by variations in <italic>g</italic><sub>s</sub> (<xref rid="TPU057C62" ref-type="bibr">Monclus et al. 2006</xref>, <xref rid="TPU057C35" ref-type="bibr">Fichot et al. 2011</xref>, <xref rid="TPU057C71" ref-type="bibr">Rasheed et al. 2011</xref>, <xref rid="TPU057C16" ref-type="bibr">Cao et al. 2012</xref>) although one opposite result has been reported (<xref rid="TPU057C72" ref-type="bibr">Rasheed et al. 2013</xref>). Our results suggest that variations in WUE<sub>i</sub> across dates and genotypes were primarily driven by variations in <italic>g</italic><sub>s-sat</sub>. This was supported by the fact that while WUE<sub>i</sub> and <italic>g</italic><sub>s-sat</sub> were negatively related—as expected—WUE<sub>i</sub> and <italic>A</italic><sub>sat</sub> were also negatively related which was at first counter-intuitive. This negative relationship can be explained by the fact that variations in <italic>A</italic><sub>sat</sub> were actually overridden by larger parallel variations in <italic>g</italic><sub>s-sat</sub>. In addition, WUE<sub>i</sub> and <italic>g</italic><sub>s-sat</sub> were negatively and positively related to δ<sup>18</sup>O<sub>bl</sub>, respectively. Our results suggest that variations in δ<sup>18</sup>O<sub>bl</sub> reflected a significant part of variations in <italic>g</italic><sub>s-sat</sub>. The oxygen in organic matter is derived from water and the δ<sup>18</sup>O of organic matter is primarily affected by source δ<sup>18</sup>O and by evaporative processes (<xref rid="TPU057C79" ref-type="bibr">Scheidegger et al. 2000</xref>, <xref rid="TPU057C76" ref-type="bibr">Roden and Farquhar 2012</xref>). As we did not measure the source δ<sup>18</sup>O in the present study, we have no evidence for differences in the source δ<sup>18</sup>O. We know, however, that the different genotypes experienced different water table depths, which significantly and spatially varied throughout the plantation (L.S. Broeckx, unpublished data). So we hypothesize that the different genotypes acquired water from different soil horizons, considering the observed genotypic differences in plant size (<xref rid="TPU057C27" ref-type="bibr">Duursma et al. 2011</xref>) and assuming genotypic differences in rooting depth in response to the varying water table depths. The response of rooting depth to water table depth is a trait adaptive to the native riparian habitat of poplars (<xref rid="TPU057C77" ref-type="bibr">Rood et al. 2003</xref>).</p><p>As expected from the theory (<xref rid="TPU057C32" ref-type="bibr">Farquhar et al. 1982</xref>), the values of WUE<sub>i</sub> and Δ<sup>13</sup>C<sub>bl</sub> were significantly and negatively related, which confirms previously reported observations for various crop species (<xref rid="TPU057C30" ref-type="bibr">Farquhar and Richards 1984</xref>, <xref rid="TPU057C59" ref-type="bibr">Meinzer et al. 1990</xref>) and for woody species (<xref rid="TPU057C48" ref-type="bibr">Guehl et al. 1995</xref>, <xref rid="TPU057C70" ref-type="bibr">Ponton et al. 2002</xref>, <xref rid="TPU057C75" ref-type="bibr">Ripullone et al. 2004</xref>). The significant scatter in and disturbance of the observed relationship may be explained by several things. Firstly, WUE<sub>i</sub> values correspond to virtually instantaneous measurements, while Δ<sup>13</sup>C<sub>bl</sub> reflects a temporal integration of WUE<sub>i</sub> over the course of leaf formation and recent photosynthetic activity. Secondly, <italic>A</italic><sub>sat</sub> and <italic>g</italic><sub>s-sat</sub> were measured under saturating conditions after the sampled leaf had acclimated to the chamber conditions, such that the values of WUE<sub>i</sub> reflected ‘maximal’ functioning. This optimal functioning is obviously not maintained during the entire leaf lifespan. Thirdly, finite but variable <italic>g</italic><sub>m</sub> can affect WUE<sub>i</sub> and influence the relationship between WUE<sub>i</sub> and Δ<sup>13</sup>C<sub>bl</sub> (<xref rid="TPU057C88" ref-type="bibr">Warren and Adams 2006</xref>, <xref rid="TPU057C39" ref-type="bibr">Flexas et al. 2008</xref>, <xref rid="TPU057C80" ref-type="bibr">Seibt et al. 2008</xref>, <xref rid="TPU057C83" ref-type="bibr">Soolanayakanahally et al. 2009</xref>). The hyperbolic relationship observed between WUE<sub>i</sub> and <italic>g</italic><sub>m</sub>/<italic>g</italic><sub>s-sat</sub> supports this line of reasoning and is consistent with both theory (<xref rid="TPU057C41" ref-type="bibr">Flexas et al. 2013</xref>) and data reported for different species (<xref rid="TPU057C43" ref-type="bibr">Galmes et al. 2010</xref>, <xref rid="TPU057C41" ref-type="bibr">Flexas et al. 2013</xref>). In addition, the observed negative Δ<sup>13</sup>C<sub>bl</sub>–WUE<sub>i-sat</sub> relationship varied significantly among genotypes and with timing throughout the growing season. This observation confirms the effects of both species and water availability on the relationship between Δ<sup>13</sup>C<sub>bl</sub> and WUE<sub>i</sub> that were previously reported for poplar (<xref rid="TPU057C21" ref-type="bibr">DesRochers et al. 2007</xref>, <xref rid="TPU057C94" ref-type="bibr">Xu et al. 2008</xref>, <xref rid="TPU057C54" ref-type="bibr">Larchevêque et al. 2011</xref>). The absence of a correlation in genotype Wolterson is most likely explained by lower water availability experienced as a consequence of low(er) total LA (<xref rid="TPU057C11" ref-type="bibr">Broeckx et al. 2012<italic>a</italic></xref>, <xref rid="TPU057C12" ref-type="bibr">2012<italic>b</italic></xref>), hence the lower transpiration and reduced soil water depletion. The lack of a significant correlation observed between Δ<sup>13</sup>C<sub>bl</sub> and δ<sup>18</sup>O<sub>bl</sub>, although δ<sup>18</sup>O<sub>bl</sub> was significantly related to <italic>g</italic><sub>s-sat</sub> and WUE<sub>i</sub> (see the discussion above), also reinforces the idea that the WUE<sub>i</sub>–Δ<sup>13</sup>C<sub>bl</sub> relationship was partly influenced by <italic>g</italic><sub>m</sub>.</p><p>The economics of N and water use during photosynthesis is primarily interlinked through their mutual dependence on stomatal conductance. Especially during drought stomatal closure contributes to increasing WUE<sub>i</sub> on the one hand, while decreasing PNUE on the other hand resulting in a trade-off between both traits (<xref rid="TPU057C36" ref-type="bibr">Field et al. 1983</xref>, <xref rid="TPU057C88" ref-type="bibr">Warren and Adams 2006</xref>). Our results were consistent with this concept. The reduced assimilation rate caused by a decrease in stomatal conductance with constant N allocation increased the N cost per unit of carbon gain, suggesting maximization of resource-use efficiency depending on the most limiting resource (<xref rid="TPU057C73" ref-type="bibr">Reich et al. 1989</xref>, <xref rid="TPU057C93" ref-type="bibr">Xu and Baldocchi 2003</xref>, <xref rid="TPU057C49" ref-type="bibr">Han 2011</xref>). However, when the early July data (i.e., when low soil water availability had the largest effect on leaf gas exchange) were discarded from the analysis, WUE<sub>i</sub> and PNUE were not significantly related. This suggests that WUE<sub>i</sub> and PNUE are uncoupled under optimal conditions, as already observed for other poplar species (<xref rid="TPU057C83" ref-type="bibr">Soolanayakanahally et al. 2009</xref>). As suggested by <xref rid="TPU057C83" ref-type="bibr">Soolanayakanahally et al. (2009)</xref>, this might be expected if <italic>g</italic><sub>s-sat</sub>, <italic>g</italic><sub>m</sub> and other factors influencing net assimilation rate vary independently, as was apparently the case in our study under non-limiting conditions (Figure <xref ref-type="fig" rid="TPU057F3">3</xref>).</p><p>In conclusion, our results showed significant seasonal evolution in photosynthesis, in WUE<sub>i</sub>—as quantified by δ<sup>13</sup>C and δ<sup>18</sup>O—and in PNUE of poplars grown under a high-density SRC regime. The seasonal evolution was mostly explained by variations in soil water availability and by stomatal control, but was strongly genotype dependent. This study suggests taking genotypic differences in seasonal evolution into account in future modelling studies.</p></sec><sec id="s5"><title>Supplementary data</title><p><ext-link ext-link-type="uri" xlink:href="http://treephys.oxfordjournals.org/lookup/suppl/doi:10.1093/treephys/tpu057/-/DC1">Supplementary data are available at <italic>Tree Physiology</italic> online</ext-link>.</p></sec><sec id="s6"><title>Conflict of interest</title><p>None declared.</p></sec><sec id="s7"><title>Funding</title><p>This research has received funding from the European Research Council under the European Commission's Seventh Framework Programme (FP7/2007–2013) as ERC grant agreement no. 233366 (POPFULL), as well as from the Flemish Hercules Foundation as Infrastructure contract ZW09-06. Further funding was provided by the Flemish Methusalem Programme and by the Research Council of the University of Antwerp. Funding to pay the Open Access publication charges for this article was provided by the European Commission's Seventh Framework Programme (FP7/2007–2013) as ERC grant agreement n° 233366 (POPFULL).</p></sec><sec sec-type="supplementary-material"><title>Supplementary Material</title><supplementary-material id="PMC_1" content-type="local-data"><caption><title>Supplementary Data</title></caption><media mimetype="text" mime-subtype="html" xlink:href="supp_34_7_701__index.html"></media><media xlink:role="associated-file" mimetype="application" mime-subtype="msword" xlink:href="supp_tpu057_tpu057supp_table1A.docx"></media><media xlink:role="associated-file" mimetype="application" mime-subtype="msword" xlink:href="supp_tpu057_tpu057supp_table2A.docx"></media></supplementary-material></sec></body><back><ack><title>Acknowledgments</title><p>The authors gratefully acknowledge Joris Cools for excellent technical support, Kristof Mouton for logistic support at the field site, thesis student Elyne Beernaert for assistance with fieldwork, M.Sc. 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