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Water-use efficiency and productivity in native Canadian populations of Populus trichocarpa and Populus.. Pointeau, Virginie M. 2008

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    WATER-USE EFFICIENCY AND PRODUCTIVITY IN NATIVE CANADIAN POPULATIONS OF POPULUS TRICHOCARPA AND POPULUS BALSAMIFERA  by  VIRGINIE M. POINTEAU  B.A., The University of Texas at Austin, 1996      A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE   in   THE FACULTY OF GRADUATE STUDIES  (Forestry)    THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)   March 2008  ?  Virginie M. Pointeau, 2008        ii   ABSTRACT    Afforestation and reforestation programs utilizing available fields for biofuel production, carbon sequestration, and other uses linked to climate change are looking to tree physiologists to identify species and genotypes best-suited to their purposes.  The ideal poplar genotype for use in Canadian programs would be drought-resistant, cold-climate adapted, and fast-growing, thus requiring an understanding of links between a variety of physiological traits linked to growth and productivity.  This study examined the basis for variations in water-use efficiency within four selected populations of Populus trichocarpa and  Populus balsamifera (2 provenances each).  Each species included both a northern and a southern provenance.  Correlations between water-use efficiency, nitrogen-use efficiency, 13C/12C isotope ratio, stomatal conductance, and overall productivity were evaluated.  Gas exchange variables measured included net photosynthesis, transpiration rate, stomatal conductance, and intercellular CO2 content.  Water-use efficiency and 13C content across all genotypes were highly correlated.  Results suggested that variation in water-use efficiency was primarily related to variation in stomatal conductance across all genotypes.  Whereas differences in net photosynthesis in this study were not significant between species, P. balsamifera did reveal a higher average stem volume overall.  Although variation in stomatal conductance was the major determinant of differences in water-use efficiency, positive correlations were found between  13C isotope abundance and net photosynthesis  in both P. balsamifera provenances.  In this regard, results for the northern P. balsamifera provenance are the most consistent across all gas-exchange and growth trait correlations, in terms of meeting expectations for sink-driven water-use efficiency.  The findings in this study suggest the possibility of identifying poplar genotypes with an absence of trade-off between water-use efficiency and nitrogen-use efficiency, notably among genotypes from the northern P. balsamifera provenance, near Gillam.    iii  TABLE OF CONTENTS   Abstract?????.????????.. ??????????......??????ii Table of Contents?????????..??????????????.???..iii List of Tables?????.??????. ?????????????????..v List of Figures??????..??.  ???????????????????.vi List of Illustrations????????..  ?.???????????????vii List of Abbreviations?????????????????????????..viii Acknowledgements???????. ????????????.??????...ix Dedication??????...?.. ????????????????.???.??..x  CHAPTER I  Introduction and Literature Review???????????..? ..1   Introduction??????????????????????...???????1 Populus for Afforestation????..????????????????????3  Water-Use  Efficiency?????..??????????????..??????4 Nitrogen-Use Efficiency??..??????????????????????..8 Gibberellins and Productivity??..????????????????????..9 Considerations & Current Work?.??????????????????.?....10  CHAPTER II  Objectives???????????....?..????????....12  CHAPTER III  Materials & Method???????????..??????.?13  Materials..??????????????????????????????13 Methods..??????????????????????????????.16   Gas Exchange???????...??????????????????16  Water-Use Efficiency???????...??????????????....17   Carbon Isotope and Total Nitrogen Composition???...????????.17  Dry Matter Production???..????????????????...??18  Stomatal Density????????...???????????????...19  Statistical Analyses.??????? ??????????..?????..19  CHAPTER IV  Results????????????..?????????....... ..20  Trends Throughout Populations??..??????????....??????.?. ..20 Resource-Use Efficiencies??????????????????????.... ..25 Provenance-Level????????????????????????..?? .26 Genotype Level???????????????????????????. ..31       ivCHAPTER V  Discussion?????????????..???????? ...35  Water-Use Efficiency????????????????????????? ..35 Nitrogen-Use Efficiency???????????????????????.... .38 NUE and WUE Trade-off???????????????????????.. .40 Considerations for Future Work...?..?????????????????? ?41  CHAPTER VI  Conclusions??..??????????????????. ?44  BIBLIOGRAPHY.?????? ???????????????????.?46  APPENDIX Analysis of Variance Model????????????......??57                                      v  LIST OF TABLES    Table 1:            Provenance locations, local provenance groupings, and climate data.. .14    Table 2:   One-way ANOVA for significant species- and genotype-level effects    for gas-exchange and growth traits??????????????..21  Table 3:  Pearson correlation among genotypes?????????...?..??23  Table 4:  Analysis of variance components???????????????57  Table 5:  Sources and components of variance for the analysis of variance   model??????...............................................................................58                                 vi   LIST OF FIGURES    Figure 1:  Net photosynthesis for all genotypes within provenances???. ?....22  Figure 2:  ? 13C foliar correlations with ? 13C stem, WUE, stomatal conductance,  and intercellular CO2????????????.????? ??..25  Figure 3:  Net photosynthesis correlations with intercellular CO2 concentrations  for each provenance???????????????..?.. ???27    Figure 4:  ? 13C correlations with net photosynthesis for each provenance  .??...28  Figure 5:  ? 13C correlations with photosynthetic NUE for each provenance. ?.?29  Figure 6:  ? 13C correlations with stem volume for each provenance??..???.30  Figure 7:  ? 13C plotted against photosynthetic NUE for all genotypes in each of  the four provenances????????????????.. ?..?...32    Figure 8:  Fresh total biomass for all genotypes within provenances?..????33                          vii   LIST OF ILLUSTRATIONS    Illustration 1:     Gas-exchange measurements using the LICOR 6400????..34                                         viii   LIST OF ABBREVIATIONS   Carbon????????????????????????????????C  Carnduff provenance?????????????????????????CAR  Gillam provenance?????????????????????.?????GIL  Intercellular CO2 content (? mol CO2 mol air-1)????.?????..??.????ci   Leaf amphistomaticity (adaxial Ds/abaxial Ds)??..?????????.????SR  MacMillan Island provenance??????????????????????MC  Net photosynthesis (? mol CO2 m-2s-1)???..????????????????A  Nitrogen????????????????????????..????..??N  Nitrogen-use efficiency????????????????????????NUE  Quesnel Lake provenance??????????????????? ?..???QL  Root-to-shoot ratio??????????????????..???????.. R:S  Specific leaf area (cm2g-1)???????????????????????SLA  Stable carbon isotope composition (?).?????????????????..? 13C  Stomatal conductance (mol H20 m-2s-1)??????....????????????gs  Total stomatal density (per mm2)??..??????????????????.. Ds  Transpiration (mmol H20 m-2s-1)??.????????????????.??? E  Water-use efficiency??????????????.??????????..WUE          ix     ACKNOWLEDGEMENTS     I would like to express my gratitude and appreciation to all who have helped me in this endeavour.  First and foremost, my supervisor, Dr. Rob Guy, for his patient and insightful mentorship; Dr. Shawn Mansfield and Dr. Richard Pharis, for serving on my committee and offering their knowledge and perspective; Dr. Andrew Riseman, for serving as my external examiner; my lab assistant, Nadja Johannsen; my labmates, Raju Soolanayakanahally, Dheeraj Chillakuru, Limin Liao, and Shofiul Azam; David Kaplan, manager of the UBC Greenhouse; Dr. Tony Kozak, for sharing his statistics expertise; Norman Hodges, for bringing his computer expertise to the rescue multiple times.  And to my community of friends in 3621, 3623 and beyond: thank you.  Plant material was obtained from a provenance trial established by Dr. Cheng Ying in Surrey, BC for P. trichocarpa, and from the Shelterbelt Centre, PFRA-AAFC in Indian Head, SK for P. balsamifera.  Funding was provided by NSERC and BioCap.                           x            To Tanya & To my parents, Jack & Fran?oise Pointeau                1  INTRODUCTION & LITERATURE REVIEW   Introduction Upon signing the Kyoto Protocol, Canada adopted the goal of reducing greenhouse gas emissions by 6% below its 1990 levels of 5.96 ?  108 tons of CO2, by the year 2012 (McKenney et al. 2004; Peterson et al. 1999).  Such reductions could be achieved by either decreasing fossil fuel emissions, or increasing net carbon sequestration through reforestation and afforestation programs, among other means (Cannell 1999).  Spatial simulation studies taking both biology and economics into account have estimated that between 12.7% and 32% of agricultural lands in western Canada are available for afforestation (McKenney et al. 2004; Van Kooten et al. 1999).  The use of such lands for biofuel production would address both above-mentioned options simultaneously, since CO2 would essentially be recycled in the processes of planting and subsequently converting trees to fuel (Lemus and Lal 2005; Povellato et al. 2007).  The CO2 released by burning fuel would originally have been removed from the atmosphere by the bioenergy crop, making the use of plant biomass as a source of fuel carbon-neutral (Hall and House 1995).  Between 1993 and 2002, approximately 2650 hectares of privately owned land in the Canadian prairie provinces were converted to tree plantations, with white spruce and hybrid poplar making up 93% of the planted area (Hall et al. 2005).  Although afforestation alone, even on the global scale, would not be   2sufficient to stabilize atmospheric CO2 levels, let alone lower them, forestry does have both short- (Cannel 1999) and long-term roles to play in contributing to Kyoto Protocol commitments.  Ongoing reforestation and afforestation efforts, implying in part the conversion of depleted or marginal agricultural soils to tree plantations, is believed to have multiple ecological benefits beyond Kyoto goals, including protecting the soil from water and wind erosion, capturing nutrients, increasing soil stability through the development of roots at depths, and increasing biodiversity (Laureysens et al. 2005; Mann and Tolbert 2000; Pellis et al. 2004; Sage 1998).  Others have found increases in nonnative species, coupled with a reduction in species diversity (Clavijo et al. 2005).  Potential benefits to biodiversity, including the return of native plant and animal species, could require the use of native tree species for afforestation purposes (Cowie et al. 2007). The establishment of tree plantations on lands depleted from years of tillage could increase soil quality by adding substantial levels of carbon to the soils (Grigal and Berguson 1998; Guo and Gifford 2002), although such benefits may take years to materialize; soil C may actually be depleted during the first 6-10 years following afforestation, as the plantation is being established (Paul et al. 2002; 2003).  It has been suggested that plantations of hybrid poplar species could potentially increase organic carbon stored in soils to levels twice as high as those of soils covered with either row crops or grasses (Mann and Tolbert 2002), though others argue that, especially in the first 10 years following afforestation, soil C levels may be less beneath tree plantations than under agriculture (Paul et al. 2003).  Studies involving a variety of tree species have been highly variable, showing both net increases and decreases in soil carbon levels (Del Galdo et al. 2003; Garten 2002; Tolbert et al. 2002).  Establishing forest rotations of 20-  350 years, and including litter in soil C calculations will increase recorded levels of soil C accumulation (Paul et al. 2002).  Approximately 150 tonnes of carbon in total could be sequestered per hectare of established tree plantation (Natural Resources Canada 2007); where soil C is concerned, however, current literature is lacking in long-term data spanning more than a few years (Paul et al. 2003).   Populus for Afforestation Populus tree species, including poplars, cottonwoods and aspens (Taylor 2002) (henceforth referred to as poplars), are among the favored tree species for use in afforestation efforts for numerous reasons:  they have a wide natural distribution in the Northern Hemisphere, with 30 recognized species, providing a large pool of genetic variation; they have the ability to reproduce asexually, by sprouting from roots or growing from abscised or broken branches; they are fast-growing trees, capable of reaching 40 m in less than 20 years (Bradshaw et al. 2000; Ceulemans and Deraedt 1999).  Poplars can reach reproductive maturity in only four years in a plantation setting (Vanden Broek 2005), and have wide interspecific crossability and high plasticity (Gielen and Ceulemans 2001), thus making them relatively easy to manipulate in ongoing efforts to improve yield on tree plantations.  Besides their usefulness in rapid C sequestration and as a source of bioenergy (Hall and House 1995), poplars may also prove to be ideal as model trees for use in studying processes and physiology unique to trees, which Arabidopsis cannot provide (Jansson and Douglas 2007; Taylor 2002).  The relatively small genome size of Populus, together with the multiple poplar genomic maps currently developed (Taylor 2002), render any research done on poplar physiology   4potentially useful and applicable to research needs on other tree species.  Populus represents the first tree species to have its genome entirely sequenced (and the third plant, after Arabidopsis and rice) (Tuskan et al. 2004, 2006).    The high productivity of poplars depends on the availability of water, and typically limits their cultivation mostly to floodplains and bottomlands, where water is not a limiting factor (Monclus et al. 2006).  In Canada, hybrid poplars are most successful in the relatively milder climates of southern Ontario and southwest British Columbia (Guy et al. 2001).  The majority of the 7 million hectares of marginal agricultural lands currently available in Canada for poplar cultivation, however, is located in the prairie provinces, where few hybrid poplar species have proven successful (Guy et al. 2001).  In order to take full advantage of available lands, hybrids must be developed that combine cold hardiness with both high productivity and high drought tolerance.  The ideal poplar genotype for use in Canadian carbon sequestration programs would be drought-resistant, cold-climate adapted, and fast-growing (Guy et al. 2001), thus requiring a thorough understanding of links between water-use efficiency (WUE), photosynthesis, endogenous gibberellin levels, nitrogen-use efficiency (NUE), and other physiological traits linked to growth and productivity.          5Water-Use Efficiency Water-use efficiency has commonly been defined as the ratio of biomass production to unit water used (Monclus et al. 2006).  Given the difficult and labor-intensive nature of measuring total water-use throughout a growing season, WUE is often estimated at the leaf level by measuring the ratio of photosynthesis (A) to transpiration (E).  Long-term water-use efficiency can also be estimated through measurements of stable carbon isotope abundance (? 13C) (Farquhar et al. 1982, 1989).  The heavier of the two stable carbon isotopes, 13C, makes up approximately 1.11% of the carbon present in the biosphere, compared to 98.89% for 12C (Griffiths 1993).   ? 13C represents the ratio of 13C to 12C in a plant sample, expressed in per mil (?) relative to the commonly-used Vienna Pee Dee belemnite standard (Coplen 1994; Condon et al. 2002).  ? 13C in C3 plants reflects a plant?s level of discrimination against the heavier and less abundant 13C during various processes from diffusion of CO2 from the atmosphere to carboxylation (Farquhar et al. 1982).  Plant discrimination against 13C is linked to levels of intercellular CO2 (ci), which in turn reflect changes in either stomatal conductance or photosynthetic capacity (Silim et al. 2001).  ? 13C values are negatively correlated with the ratio of internal versus atmospheric CO2 levels (ci/ca).  Low ci caused by high photosynthetic rates will lead to less negative ? 13C values (Gornall and Guy 2007).  More positive ? 13C values are linked to higher WUE, while more negative ? 13C values are linked to lower WUE.  Thus both ? 13C values and ci/ca serve as indicators of plant WUE.   Since WUE is defined as the ratio of net photosynthesis (A) to transpiration (E), or A/E, then changes in WUE, and thus changes in ? 13C, must be due to changes in either stomatal conductance or photosynthetic capacity (Silim et al. 2001), assuming an   6otherwise constant environment.  Trees displaying both high WUE and high productivity, therefore, likely indicate WUE primarily associated with variations in photosynthetic capacity, as opposed to variations in stomatal conductance, which would theoretically lead to a decrease in productivity (Guy and Holowachuk 2001; Sun et al. 1996).   Previous work done on Populus trichocarpa Torr. & A. Gray ? Populus deltoides Marsh. (Bunn et al. 2004; Rae et al. 2004), Populus deltoides Marsh. ? Populus nigra L. (Monclus et al. 2005), and Populus trichocarpa Torr. & A. Gray (Gornall & Guy 2007) suggested that population-level variation in WUE in these species was not clearly associated with variation in either stomatal conductance or photosynthetic capacity, as evidenced in each study by the lack of any correlation between WUE, or ? 13C values, and indices of productivity such as photosynthesis, biomass or stem volume. Studies conducted on Populus deltoides ? P. nigra clones by Marron et al. (2005) and Monclus et al. (2005), and on Populus trichocarpa ?  Populus deltoides by Rae et al. (2004), exploring relationships between various leaf-level traits and overall productivity, found no correlation between stable C isotope discrimination (? ) and total biomass.  Others have found positive correlation between growth and WUE in Populus ? euramericana Dode (Guinier) clones (Voltas et al. 2006), indicating the possibility for WUE in poplar hybrids driven at least in part by photosynthetic capacity.  Likewise, Zhang et al. (2004) found there to be positive correlations between WUE, productivity and ? 13C in Populus davidiana  Dode.  Bungart and H?ttl (2004), in a study using several different poplar species and hybrids, also found positive correlations between WUE (measured as biomass gain per total transpiration) and growth rates. In conifer species, positive correlations between growth traits and ? 13C values have consistently been found,   7suggesting variation in WUE driven primarily by photosynthetic capacity for Picea glauca (Moench) Voss (Sun et al. 1996; Silim et al. 2001), P. sitchensis (Bong.) Carr. (Silim et al. 2001), Pinus contorta Dougl. ex Loud. (Guy & Holowachuk 2001) and in Picea rubens Sarg. and Picea mariana (Mill.) BSP (Major et al. 2007).  Benowicz et al. (2001) found that differences in intrinsic WUE in paper birch (Betula papyrifera Marsh.) were due to differences in net photosynthesis, and not stomatal conductance, whereas Wang et al. (1998) attributed higher WUE in paper birch to decreased stomatal conductance (gs).  Ripullone et al. (2004), in a study looking at the effects of nitrogen supply on WUE in Populus  ?   euroamericana  Dode, also found a positive correlation between WUE and ? 13C.  These results, together with the high heritability of both productivity and C isotope discrimination (? ) in poplar species (Rae et al. 2004; Monclus et al. 2005), suggest the possibility of selecting poplar genotypes with high WUE driven by high photosynthetic rates, and thus at no cost to growth.  Alternatively, a lack of correlation between WUE and growth indices could have its advantages in a breeding program, as it would allow for the independent selection of both high WUE and high productivity; normal fluctuations in WUE and gs, in this case, should not affect growth (Monclus et al. 2006).  While correlations between WUE and ? 13C values are presently well-accepted in the field of plant physiology, positive correlation between ? 13C and productivity in poplars has not been consistently established.    Guy and Holowachuck (2001) suggest that high sink demand resulting from increased growth leads to an increase in photosynthetic rate, and, subsequently, more positive  ? 13C values and higher WUE.  Blum (2005), on the other hand, in a review addressing links between yield potential, drought resistance and WUE, maintains that   8WUE in crops results from water-use primarily, rather than from productivity or carbon assimilation.  Similarly, in a study addressing wheat and barley cultivars, Condon et al. (2002) suggest that low carbon discrimination resulting from higher photosynthetic capacity could lead to a negative correlation between photosynthesis and biomass in crops.  In order to best utilize the potential for rapid growth and high productivity seemingly inherent to poplar species, more studies addressing the links between WUE, ? 13C, net photosynthesis and productivity in a variety of poplars and poplar hybrids are needed.  Nitrogen-Use Efficiency Positive correlations between nitrogen content and net photosynthesis in C3 plants are widely recognized (Evans 1989), and have been identified in a variety of gymnosperm (Field et al. 1983; Robinson et al. 2001; Major et al. 2007) and angiosperm species (Sobrado 1991), including Populus trichocarpa (Gornall & Guy 2007).  Ripullone et al. (2004) found that an increase in both WUE and productivity in Populus ?  euroamericana were caused by effects of N on photosynthetic rates, rather than changes in stomatal conductance or transpiration.  Stomatal conductance, and subsequently both ci/ca and WUE, is also affected by nitrogen availability.   Photosynthetic nitrogen-use efficiency is defined as the ratio of net photosynthesis to N content per unit leaf area (Larcher 2003).  The expected positive linear relationship between photosynthetic capacity and nitrogen content (Larcher 2003) implies a possible inherent trade-off between WUE and NUE, given that any increase in ci (leading to increased NUE) will lead to more negative ? 13C values and lower WUE   9(Patterson et al. 1997).  This is consistent with studies done on various evergreen shrub and tree species (Field et al. 1983), white spruce (Livingston et al. 1999), and paper birch (Wang et al. 1998), although others found an absence of intrinsic trade-off between WUE and NUE for both white and black spruce (Patterson et al. 1997), suggesting the possibility of selecting for both high WUE and NUE separately.  It is possible that relatively higher WUE resulting from high photosynthetic capacity could result in higher levels of yield even in nitrogen-deficient environments (Livingston et al. 1999; Pritchard and Guy 2005).  In times of drought, however, a tendency in plants to increase stomatal closure will simultaneously increase WUE and decrease NUE, as shown in hybrid willow (Weih et al. 2006).  Current literature is lacking in studies addressing correlations, or lack thereof, between WUE and NUE, and the implications of such links on growth and productivity, specifically in poplar species and their hybrids.     Gibberellins and Productivity Productivity in trees is also thought to have possible links with concentrations of endogenous gibberellins (GAs) (Pharis et al. 1991).  In a recent review, Kende and Zeevaart (1997) discuss literature linking gibberellin to stem and cell elongation (Raskin and Kende 1984), and suggesting a GA role in cell division in multiple plant species (Sauter and Kende 1992).  A study conducted on maize parental inbreds and their hybrids, by Rood et al. (1988), found that inbreeding depression in maize was partly due to low levels of endogenous GAs, whereas hybrids displaying vigorous shoot growth contained higher GA concentrations.  In a study conducted on soy beans and broad beans (Yuan and Xu 2001), the application of exogenous gibberellin was shown to increase   10photosynthetic rate, leading to a subsequent increase in photosynthetic carbon fixation, and further demonstrating correlations between gibberellin content and growth.  Later studies showed both evidence for (Pharis et al. 1991) and against (Pearce et al. 2004) positive correlations between endogenous GA concentration and superior growth in poplar species.  The over-expression of a GA 20-oxidase gene in a study using hybrid aspen (Populus tremula L. ? P. tremuloides Michx.) resulted in increased growth rate, larger leaves and greater biomass (Eriksson et al. 2000), though direct links to secondary growth and wood formation have yet to be entirely established (Israelsson et al. 2003).  Although the use of genetic engineering for the improvement of plantation trees may or may not be implemented, further studies exploring links between naturally-occurring GA concentrations and WUE, NUE and overall productivity in poplar species native to Canada would certainly be beneficial for breeding programs seeking to breed native poplar species.  Considerations and Current Work   Abundant studies addressing WUE, ? 13C, net photosynthesis and various growth indices in numerous tree species have substantially increased our understanding of the links and correlations present among these traits; however, while positive correlation between intrinsic WUE and ? 13C has clearly and consistently been shown in C3 plants, correlations between WUE indices (including ? 13C) and growth in poplar species have yet to be established.  Likewise, current literature is lacking in studies addressing links, or lack thereof, between WUE and NUE in tree species, and especially in poplars.  Further work on naturally occurring, inherent gibberellin concentrations in poplar   11species, and possible correlations with WUE, growth and productivity, would lend additional insight and guidance to tree breeding programs and hybridization efforts intent on creating the ideal poplar trees for biofuel production, carbon sequestration, or other uses linked to climate change.   This study endeavoured to determine the basis for variations in WUE within selected provenances of Populus trichocarpa and  Populus balsamifera, along with correlations between WUE, NUE, C isotope content (? 13C), net photosynthesis, stomatal conductance, and overall productivity. It was expected that genotypes displaying positive correlations between ? 13C values (proxy for long-term WUE) and productivity would also display a high photosynthetic capacity, and that genotypes displaying relatively high WUE as a result of high sink-driven photosynthetic capacity would show a less severe or absent trade-off with NUE.                12    OBJECTIVES   1.  Determine whether variation in WUE within selected provenances of Populus trichocarpa growing along the coast of British Columbia, and P. balsamifera growing along a north-south transect from Manitoba to Saskatchewan are related more to photosynthetic capacity or to stomatal conductance. 2.  Further define possible links between water-use efficiency, ? 13C, nitrogen-use efficiency, stomatal conductance, net photosynthesis and overall productivity. 3.  Identify genotypes with relatively high water-use efficiency combined with high productivity.           13  MATERIALS & METHODS  Materials Populus trichocarpa Torr. & A. Gray (black cottonwood) and Populus balsamifera L. (balsam poplar) clones from selected populations located along two north-south transects in western Canada were used in this study.  As the emphasis of this study was on within-population variations in physiological traits, only four provenances in total were selected: two Populus trichocarpa provenances from the British Columbia Ministry of Forests collection, and two Populus balsamifera provenances, one each from Manitoba and Saskatchewan, from the Natural Resources Canada AgCanBaP collection.  One northern provenance and one southern provenance were utilized for each species.  From BC, the two selected provenances were Quesnel River (QL), located at 52? 65?N 122? 26?W, and McMillan Island (MC), located at 49? 14?N 121? 81?W.  From Manitoba, the Gillam provenance was used (GIL), located at 56? 27?N 94? 41?W, and from Saskatchewan, the Carnduff provenance (CAR), located at 49? 14?N 101? 56?W.  For QL and MC, numbers were increased by grouping three local populations together for each provenance (Table 1).  The area encompassing the local groups for each P. trichocarpa provenance is comparable to the area defining the Gillam provenance, roughly 40?14 km.  Climate data collected for all P. trichocarpa genotypes showed very similar elevations, temperature ranges, and precipitation for all groupings within provenances   14(Table 1).  The specific locations stated above represent the average latitude and longitude for each provenance (Table 1).      Lat ? N Long ? W  Elev (m) MAT MWMT MCMT MAP  NFFD QAUS QLKE QFRS Average 52.43 52.48 53.04 52.65 122.28 122.19 122.31 122.26 442 488 472 467.33 6.2 6.1 5.9 6.07 17 16.7 16.4 16.7 -4.1 -4.2 -5.6 -4.63 458 467 667 530.67 197 197 194 196.00 MCMN HRSO HRSP Average 49.11 49.17 49.14 49.14 122.35 121.57 121.51 121.81 15 40 30 28.33 9.6 9.1 9.9 9.53 17.2 17.3 18.1 17.53 2.1 1 1.4 1.50 1648 1771 1785 1735 294 288 298 293.33 GIL 3 GIL4 GIL5 GIL6 GIL7 GIL10 GIL12 GIL13 GIL14 GIL15 Average Gillam, MB 56.21 56.20 56.19 56.19 56.22 56.56 56.28 56.28 56.29 56.30 56.27 56.21 94.36 94.34 94.32 94.30 94.24 94.28 94.38 94.42 94.48 95.01 94.41 94.42 115 123 126 129 104 131 133 137 124 90 121.20 145            -4.2            15.3            -25.8            499.4            128.6 CAR1 CAR2 CAR3 CAR4 CAR5 CAR7 CAR8 CAR11 CAR14 CAR15 Average Estevan, SK 49.11 49.13 49.13 49.13 49.14 49.15 49.14 49.16 49.13 49.16 49.14 49.13 101.50 101.56 101.56 101.56 101.56 101.57 101.58 101.58 101.57 101.57 101.56 102.58 533 545 545 545 543 548 550 553 546 549 545.70 580            3.7            19.5            -14.8            4.33            172.8  Table 1.  Provenance locations, local provenance groupings, and climate data.   P. trichocarpa provenances are QL (QAUS, QLKE and QFRS) and MC (MCMN, HRSO, HRSP); P. balsamifera provenances are GIL and CAR.  Climate data include mean average temperature (MAT), mean warmest month temperature (MWMT), mean coldest month temperature (MCMT), mean average precipitation (MAP), and number of frost-free days (NFFD).  Temperatures are in degrees Celsius; precipitation is in centimeters.  Climate data for British Columbia were obtained through ClimateBC (Centre for Forest Conservation Genetics, University of British Columbia); climate data for Saskatchewan and Manitoba were obtained from Environment Canada (Canadian Climate Normals or Averages 1971-2000).  For the CAR and GIL provenances, the closest weather stations with all necessary data were located in Estevan, SK (approximately 90 km west of Carnduff) and Gillam, MB, respectively.        15The study included three replicates for 10 genotypes from each of the four provenances, for a total of 120 trees.  The trees were organized into three blocks, with each block containing one of each clone from each of the four provenances. Trees were grown from cuttings rooted in Rootrainers?  (Spencer-Lemaire Industries Limited, Edmonton, AB, Canada), on February 7, 2007.  Cuttings were just long enough to contain two buds (approximately 5 cm); the lower bud was buried in the soil for rooting. Between 13 and 15 genotypes were started for each provenance.  Roots were allowed to develop over a period of 4 weeks. On March 8, dead or weakly-rooted cuttings were culled from each provenance, reducing the collection to 10 genotypes per provenance.  These stecklings were transferred to 4-litre pots and arranged randomly along a single flood bench in the University of British Columbia greenhouse.  A random-number generator was used to assign trees to pre-numbered slots along the bench.  The trees were allowed to grow for an additional 4? weeks before gas-exchange measurements began on April 8.   Cuttings were planted in a mixture of 75% peat moss and 25% perlite.  During the initial four weeks of growth, the cuttings received only enough water to keep the soil damp, so as not to risk damage to emerging roots.  On the flood bench, the trees were initially watered three times a week with a 120 ppm fertigation solution (15-5-15 Cal-Mag, The Scotts Company, Marysville, OH).  After two weeks on the flood bench, the trees received 400 ml 20-20-20 Soluble Plant Food (Sunshine? ) solution (approx. 31g/100 L water) once a week for the remainder of the experiment.  During the entire experiment, the stecklings received 18 hours of light per day, with HPS 400 Watt lights installed over the flood bench to supplement natural light.  The trees were 60 days old   16when the first gas-exchange measurements were taken.  Methods                         Gas Exchange Gas exchange variables were measured using a LI-6400 portable gas-exchange system (LI-COR Biosciences, Lincoln, NB, USA).  The leaf chamber was attached to a tripod to ensure stability, and allow for necessary adjustments to varying tree heights.  All measurements were conducted April 8-24, 2007, between 8:00 am and 1:00 pm.   Measurements were conducted on one block at a time, with each block taking 3-5 days.  A random number generator was used to determine sampling order within each block.  In order to ensure constant light at saturation levels, an artificial light source (LI-COR 6400-02B LED Light Source) was used for all measurements.  Light level was set at 1000 ? mol? m-2? s-1 to ensure light saturation, estimated at approximately 800 ? mol? m-2? s-1.  Conditions inside the leaf chamber were set as follows:  CO2 concentration at 360 ? l? L-1; relative humidity at 45%; and block temperature at 20? C.  Two recently fully-expanded sun leaves from the upper stem of each tree were measured twice, and combined to provide an average for each tree.  Leaves were allowed 10-12 minutes to adjust to chamber conditions prior to recording measurements.   Recorded data for gas-exchange parameters included net photosynthesis (A, ? mol CO2 m-2 s-1), transpiration rate (E, mmol H2O? m-2? s-1), stomatal conductance (gs, mol H2O m-2 s-1), and intercellular CO2 content (ci, ? mol CO2 mol air-1) (equations derived by von Caemmerer and Farquhar 1981).     17Water-Use Efficiency Instantaneous WUE (?mol CO2? mol-1H2O) was calculated as the ratio of net photosynthesis to transpiration, or A/E (Farquhar et al. 1982).  The ratio of net photosynthesis to stomatal conductance, or A/gs, was also calculated, to compare with A/E.  Leaf values for ? 13C were used as a surrogate for long-term WUE (Farquhar et al. 1982, 1989).  Stem values for ? 13C were collected from the base of all third harvest stems (not old wood), both for comparison purposes, and to ensure the value of foliar analyses as accurate representations of whole-canopy trends.  Carbon Isotope and Total Nitrogen Composition Leaf samples were collected from each tree immediately after gas-exchange measurements were completed.  Samples were kept in storage at -20? C until they could be oven-dried; samples were dried at 70? C to constant mass.  A stainless-steel ball mill was used to grind dried leaf samples into a fine powder; 1-2 mg sub-samples were analyzed for ? 13C and total C and N content at the Stable Isotope Facility at the University of California at Davis. Following leaf sample combustion to CO2 and N2 at 1000? C in an on-line elemental analyzer (PDZEuropa ANCA-GSL), stable isotope ratios of C and N were measured by continuous flow isotope ratio mass spectrometry (20-20 Mass Spectrometer, Sercon, Crewe, UK). ? 13C values were calculated based on a working standard mixture of ammonium sulfate and sucrose with ? 13C V-PDB -23.83.   ? 13C reflects the ratio of the two stable carbon isotopes 13C and 12C within a plant, relative to an arbitrary standard.  The C isotope composition of the samples was calculated using the following equation:   18 ? 13C (?) = [(Rsample ? Rstandard) / Rstandard] ?  1000  Where Rstandard and Rsample refer to the ratios of 13C/12C of the standard and the sample, respectively.  The current standard, Vienna-PDB, was originally based on a fossil belemnite from the Peedee Formation (PDB) (Coplen TB 1994).  Net photosynthesis (A: ? mol CO2 m2 s-1) and leaf N density (? mol N cm-2) were used to calculate photosynthetic nitrogen-use efficiency (NUE: ? mol CO2 ? mol N-1 s-1).    Dry Matter Production Destructive sampling of trees for measurement of dry matter production occurred throughout the course of the experiment, as gas-exchange measurements were completed on each tree.  Stem basal diameter, height and fresh mass, and root fresh mass were measured for each clone.  Stem volume was estimated from height and basal diameter, using the formula for a cone (?? r2h), and used as a measure of total above-ground growth.  Total biomass (g) was estimated by combining fresh mass measurements for stem and roots.  Given the need to conserve fresh frozen material for further work, dry biomass could not be recorded.  Leaf area, fresh and dry mass were recorded for all leaves used for gas-exchange measurements.  Specific Leaf Area (SLA: cm2 g-1) was calculated based on leaf area and dry mass.      19Stomatal Density   Leaf stomatal impressions were taken for each leaf used in gas-exchange.  These impressions were made using clear fingernail polish, which, once dry on the leaf, was pealed off and applied to a slide (as per Gornall and Guy 2007).  Stomatal counts for each leaf were done on three separate areas along the impression, then averaged, for both abaxial (lower) and adaxial (upper) sides of the leaf, for all genotypes.  Leaf amphistomaticity (SR) was calculated as the ratio of adaxial to abaxial stomatal densities.  Adaxial and abaxial counts were added together to yield total stomatal density for each genotype (Ds).    Statistical Analyses Statistical analyses were conducted in SigmaPlot 9.0 and SAS 9.1.  Variables were analyzed by analysis of variance (ANOVA) using a two-factor factorial in a randomized complete block design (see Appendix for complete ANOVA model); the general linear models (GLM) procedure was used to address unequal numbers of observations within factors.  Genotypes were nested within species and latitude.  The Kolmogorov-Smirnov test for normality and Bartlett?s test for homogeneity of variances were conducted on the residuals.  Significance levels were tested at ?  = 0.05 for all data.  Genotype means (average of three values for each genotype) were used in regression analysis; Pearson correlation coefficients (r) were calculated using all data.  Linear regressions were conducted to describe relationships between physiological traits (WUE, ? 13C, NUE, gs, ci, A, and stem volume).      20  RESULTS  Trends throughout populations Results from one-way analyses of variance (ANOVA) for all trees revealed significant differences both between species and within provenances for most physiological traits (Table 2). There were no significant differences between latitudes for any tested variable, except SLA, which is greater for northern provenances, with means of 233.13 cm2g-1 and 215.52 cm2g-1 for north and south, respectively (p=0.0217).  ANOVA revealed no differences in net photosynthesis (A) between species or latitudes (Table 2 and Fig. 1).  Significant differences in A were found within provenances (p=0.0037), however, with values (? mol CO2 m-2s-1) ranging as follows for each provenance: Gillam, 10.11-16.26; Carnduff, 12.78-15.56; Quesnel Lake, 11.98-16.23; MacMillan Island, 11.29-15.21.  A showed no correlation across all genotypes with any of the gas-exchange traits, including stomatal conductance (gs), intercellular CO2 (ci), and transpiration (E); or with water-use efficiency indices including A/E, A/gs and ? 13C (Table 3, A/gs not shown).  A was positively correlated with both leaf N density (p=0.0080) and photosynthetic NUE (p=0.0353) (Table 3).  A was also positively correlated with stem volume (p=0.0156) and total biomass (p=0.0002), and negatively correlated with SLA (p=0.0055) (Table 3).  Correlations did not exist, however, between these growth parameters and any of the three WUE indices mentioned above (Table 3).  21                  Table 2.  One-way ANOVA for significant species- and genotype-level effects for the following gas-exchange and growth traits:  net photosynthesis (A), stomatal conductance (gs), stem volume, leaf area, specific leaf area, water-use efficiency (WUE), stable carbon isotope content (?13C), root-to-shoot ratio (R:S), and nitrogen-use efficiency (NUE).    A gs Stem Volume Leaf Area SLA WUE (A/E) ?13C R : S NUE Species df: 1 SS: 0.5481 MS: 0.5481 F: 0.10 p: 0.7593 df: 1 SS: 1.3676 MS:1.3676 F: 114.74 p: <0.0001 df: 1 SS: 1.4349 MS: 1.4349 F: 8.38 p: 0.0049 df: 1 SS: 15640.2625 MS: 15640.263 F: 88.98 p: <0.0001 df: 1 SS: 18900.3000 MS: 18900.300 F: 28.39 p: <0.0001 df: 1 SS: 12.4415 MS: 12.4415 F: 85.69 p: <0.0001 df: 1 SS: 25.5774 MS: 25.5774 F: 95.99 p: <0.0001 df: 1 SS: 0.7384 MS: 0.7384 F: 13.30 p: 0.0008 df: 1 SS: 1.4348E-9 MS: 1.434E-9 F: 6.92 p: 0.069 Gen (Sp*lat) df: 36 SS: 207.0155 MS: 5.7504 F: 2.08 p: 0.0037 df: 36 SS: 1.0323 MS:0.0287 F: 2.41 p: 0.0007 df: 36 SS: 25.8261 MS: 0.7174 F: 4.19 p: <0.0001 df: 36 SS: 48095.1018 MS: 1335.9751 F: 7.60 p:  <0.0001 df: 36 SS: 58182.1632 MS: 1616.1712 F: 2.43 p: 0.0006 df: 36 SS: 17.8693 MS: 0.4964 F: 3.42 p: <0.0001 df: 36 SS: 32.1817 MS: 0.8939 F: 3.36 p: <0.0001 df: 36 SS: 1.9994 MS: 0.0555 F: 1.68 p: 0.0287 df: 36 SS: 1.4674E-8 MS: 4.076E-10 F: 1.97 p:  0.0072   22Figure 1.  Net photosynthesis (A) for all genotypes within provenances.  Gillam (GIL) and Carnduff (CAR) represent the northern and southern Populus balsamifera provenances, respectively.  Quesnel Lake (QFRS, QLKE, QAUS) and MacMillan Island (MCMN, HRSP, HRSO) represent the northern and southern Populus trichocarpa provenances, respectively.      Stomatal conductance (gs) varied between species (p<0.0001) as well as within provenances (p=0.0007), but not between latitudes; P. balsamifera showed higher gs than P. trichocarpa, with means of 0.693 mol H2O m-2s-1  versus 0.477 mol H2O m-2s-1, respectively  (Table 2).  Stomatal conductance values within provenances ranged from 0.51-0.88 and 0.60-0.79 mol H2O m-2s-1 for Gillam and Carnduff (P. balsamifera), and from 0.32-0.68 and 0.34-0.68 mol H2O m-2s-1 for Quesnel Lake and MacMillan Island (P. trichocarpa), respectively.  Stomatal conductance was highly positively correlated with ci (p<0.0001) and E (p<0.0001), and negatively correlated with all WUE indices (A/E: p<0.0001;  ? 13C: p<.0001; A/gs: p<0.0001) (Table 3).  Stomatal conductance was also positively correlated with Ds (p<0.0001) and negatively correlated with SR (p=0.0013) (Table 3).  SR, in turn, was negatively correlated, and Ds positively correlated, with all gas-exchange parameters (ci, gs,  and  E) (Table 3).  Reverse trends were found for GIL 4GIL 12GIL 10GIL 14GIL 15GIL 7GIL 5GIL 6GIL 3GIL 13CAR 7CAR 14CAR 15CAR 4CAR 8CAR 3CAR 11CAR 1CAR 2CAR 5QFRS 1QFRS 4QLKE 3QAUS 4QFRS 2QFRS 3QAUS 5QLKE 2QAUS 7QAUS 1MCMN 3MCMN 2HRSP 2HRSO 5HRSO 3HRSO 4MCMN 1HRSO 2HRSP 4MCMN 4024681012141618A (?mol CO2 m-2s-1)   23 Table 3.  Pearson correlations: r-values on top, with p-values below.  Highlighted cells indicate p<0.0001; bold indicates p<0.01; net photosynthesis (A), stomatal conductance (gs), intercellular CO2 (ci), transpiration (E), water-use efficiency (WUE), stem volume, root-to-shoot ratio (R:S), leaf dry weight (g), leaf area (cm2), specific leaf area (SLA: cm2g-1), adaxial and abaxial stomatal densities, leaf amphistomaticity (SR), stomatal density (Ds), stable C isotope abundance (?13C), nitrogen content, nitrogen-use efficiency (NUE) and total biomass (g).   A gs ci E WUEi Stem Vol R:S Leaf Dry Leaf Area SLA Adaxial Abaxial SR Ds ?13C N NUE Biomass A  0.1253 0.4409  -0.263 0.1008 0.1965 0.2242 0.2571 0.1093 0.3800 0.0156 0.0502 0.7584 0.4007 0.0104 0.2295 0.1542 -0.431 0.0055 0.0861 0.5975 -0.003 0.9851 0.0884 0.5877 0.0235 0.8856 0.1880 0.2455 0.4135 0.0080 0.3338 0.0353 0.5631 0.0002 gs   0.8726 <.0001 0.9742 <.0001 -0.858 <.0001 0.2026 0.2099 -0.244 0.1294 -0.109 0.5030 -0.252 0.1166 -0.307 0.0538 -0.408 0.0090 0.6759 <.0001 -0.491 0.0013 0.6296 <.0001 -0.811 <.0001 0.1723 0.2878 -0.094 0.5623 0.2276 0.1579 ci    0.8543 <.0001 -0.972 <.0001 0.0199 0.9030 -0.278 0.0819 -0.259 0.1062 -0.336 0.0341 -0.140 0.3876 -0.486 0.0015 0.6041 <.0001 -0.520 0.0006 0.5247 0.0005 -0.864 <.0001 -0.030 0.8564 -0.158 0.3315 -0.053 0.7452 E     -0.872 <.0001 0.2290 0.1552 -0.238 0.1394 -0.099 0.5418 -0.245 0.1274 -0.312 0.0503 -0.392 0.0124 0.6372 <.0001 -0.456 0.0031 0.5912 <.0001 -0.767 <.0001 0.1444 0.3742 0.0070 0.9660 0.2442 0.1289 WUEi      -0.015 0.928 0.2568 0.1097 -0.272 0.089 0.3288 0.0383 0.0903 0.5795 0.4201 0.007 -0.576 0.0001 0.462 0.0027 -0.514 0.0007 0.8252 <.0001 0.0810 0.6193 0.099 0.5421 0.048 0.7693 Stem Vol       -0.196 0.2255 0.5724  0.0001 0.4199 0.0070 -0.335 0.0344 -0.061 0.7103 0.2537 0.1143 -0.097 0.5501 0.2651 0.0982 0.0719 0.6594 0.5144 0.0007 -0.170 0.2934 0.8679 <.0001 R:S        0.0799 0.6241 0.1011 0.5350 0.0634 0.6975 0.2952 0.0645 -0.321 0.0434 0.3032 0.0572 -0.267 0.0955 0.2070 0.1999 -0.012 0.9428 -0.001 0.9964 -0.034 0.8353 Leaf Dry         0.8852 <.0001 -0.305 0.0558 0.2213 0.1700 -0.190 0.2409 0.2256 0.1617 -0.143 0.3775 0.3687 0.0192 0.2782 0.0822 0.0426 0.7943 0.6958 <.0001 Leaf Area          0.1549 0.3400 0.3620 0.0217 -0.428 0.0058 0.4197 0.0070 -0.367 0.020 0.4534 0.0033 -0.097 0.5496 0.2803 0.0798 0.5324 0.0004  SLA           0.2894 0.0701 -0.462 0.0027 0.3853 0.0141 -0.427 0.0059 0.1598 0.3247 -0.751 <.0001 0.4425 0.0042 -0.390 0.0129 Adaxial            -0.503 0.0009 0.9395 <.0001 -0.251 0.1190 0.3203 0.0439 -0.129 0.4278 0.1969 0.2233 -0.010 0.9496 Abaxial             -0.687 <.0001 0.9629 <.0001 -0.529 0.0005 0.3823 0.0149 -0.470 0.0022 0.1316 0.4183 SR              -0.476 0.0019 0.3867 0.0137 -0.208 0.1986 0.3196 0.0444 -0.043 0.7932 Ds               -0.492 0.0013 0.3879 0.0134 -0.465 0.0025 0.1441 0.3749 ?13C                -0.020 0.9043 0.1640 0.3120 0.1271 0.4347 N                 -0.649 <.0001 0.4893 0.0014 NUE                  -0.084 0.6045   24correlations with WUE and ? 13C, with negative correlations between Ds and WUE indices, and positive correlations between SR and WUE indices (Table 3).  No correlations were found between either SR or Ds and A, stem volume, root-to-shoot ratio (R:S) or biomass (Table 3).  Abaxial Ds is higher in P. balsamifera than in P. trichocarpa (p<0.0001), with means of 174 mm-2 and 102 mm-2, respectively; no differences were found within provenances.  Interestingly, adaxial and abaxial stomatal densities were negatively correlated (p=0.0009), indicating a constant total density of stomata despite differences in leaf amphistomaticity.  Pearson correlations revealed a positive significant correlation between SR and SLA (p=0.0141, Table 3), indicating thinner leaves (SLA is defined here as cm2g-1) with increasing leaf amphistomaticity.   Stem volume was higher in P. balsamifera with a mean of 5.38 cm3 compared with 4.31 cm3 for P. trichocarpa (p=0.0049), and differed within provenances (p<0.0001), with values ranging from 3.56-12.2 cm3 and 3.17-7.82 cm3 for Gillam and Carnduff, respectively; and from 1.36-9.06 cm3 and 2.20-7.39 cm3 for Quesnel Lake and MacMillan Island, respectively (Table 2).  Leaf area was substantially larger in P. trichocarpa provenances with a mean of 103 cm2 compared to 80.6 cm2 for P. balsamifera (p<0.0001), and differed within provenances (p<0.0001).  SLA was higher in P. trichocarpa, with a mean of 236.88 cm2g-1, compared with 211.78 cm2g-1 for P. balsamifera (p<0.0001).  SLA also differed within provenances (p=0.0006) (Table 2), with the following ranges in value for each provenance: Gillam, 160-274 cm2g-1; Carnduff, 193-214 cm2g-1; Quesnel Lake, 194-293 cm2g-1; and MacMillan Island, 163-248 cm2g-1.    25Resource-Use Efficiencies Stem values for ? 13C were highly positively correlated with foliar values (p<.0001).  Given that stem values better integrate ? 13C through time and space, and thus provide a much more accurate read for whole-plant WUE, the correlation between foliar and stem values lent added confidence to my reliance on foliar ? 13C to represent the entire tree as a surrogate for long-term water-use efficiency (Fig. 2A).  Additionally, the close comparison of these two traits indicated a consistent environment in the greenhouse throughout the duration of the study, where all gas-exchange measurements were taken.    Figure 2.  ? 13C foliar correlations with (A)  ? 13C stem (r=0.7333, p<0.0001);  (B) intrinsic water-use efficiency (A/E) (r=0.8252, p<0.0001); (C) stomatal conductance (gs) (r=-0.811, p<0.0001); and (D) intercellular CO2 (ci) (r=-0.864, p<0.0001).  Circles represent the P. balsamifera provenances (Gillam: closed, Carnduff: open) and triangles represent the P. trichocarpa provenances (Quesnel Lake: closed, MacMillan Island: open).   d13C Stem -33 -32 -31 -30 -29 -28d13C Foliar-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.0WUEi1.0 1.5 2.0 2.5 3.0 3.5 4.0-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.0Stomatal Conductance (gs)0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0d13C Foliar-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.0Intercellular CO2 (Ci)250 260 270 280 290 300 310 320-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.0A B C D ? 13C Stem (?)   A/E (? mol CO2 mmol H2O-1) gs (mol H2O m-2s-1)  Ci  (?      ?13C Foliar (?) ?13C Foliar (?)   26Both A/E and ? 13C (foliar unless otherwise noted) were tested with ANOVAs as indices of water-use efficiency.  ANOVA revealed differences between species (p<.0001 for both) as well as within provenances (p<0.0001 for both) (Table 2).  A/E was higher and  ? 13C less negative among the P. trichocarpa provenances; the mean A/E  for  P. trichocarpa was 2.86 ? mol CO2 mmol H2O-1, compared with 2.20 CO2 mmol H2O-1 for P. balsamifera, while the mean ? 13C for P. trichocarpa genotypes was -29.67?, compared with -30.60? for P. balsamifera.  ? 13C was positively correlated with A/E (p<0.0001), as expected (Fig. 2B).   ? 13C was negatively correlated with both stomatal conductance (gs) (p<0.0001) and intercellular CO2 (ci) (p<.0001) (Table 3 and Figure 2C & D, respectively), as well as with E (p<0.0001) (Table 3).      ANOVAs revealed differences for NUE within (p=0.0072) but not between provenances (Table 2).  Across all provenances, NUE showed no correlation with ? 13C or A/E, but was correlated with A (p=0.0353) and SLA (p=0.0042) (Table 3).     Provenance-level  Further correlation analyses carried out at the provenance level revealed some notable differences between provenances.  Whereas A and ci  showed no correlation across all provenances combined (Table 3), both P. balsamifera provenances, Gillam (p=.004) and Carnduff (p=0.004), revealed a negative correlation between A and ci (Fig. 3).  These same provenances also showed a positive correlation between A and ? 13C, with a p-value of 0.017 for Gillam, and 0.028 for Carnduff (Fig. 4), whereas no correlation existed across provenances combined (Table 3).  ? 13C and NUE were negatively correlated for the Quesnel Lake provenance (p=0.004) and positively correlated for   27Carnduff (p=0.042) (Fig. 5).  ? 13C and stem volume were positively correlated for the MacMillan Island provenance (p=0.011) (Fig. 6).      Figure 3.  Net photosynthesis (A) correlations with intercellular CO2 concentrations (ci) for each provenance.  The P. trichocarpa provenances are Quesnel Lake (A: r=0.156, p=0.668) and MacMillan Island (C: r=-0.395, p=0.258); the Populus balsamifera provenances are Gillam (B: r=-0.813, p=0.004) and Carnduff (D: r=-0.819, p=0.004).  250 260 270 280 290 300 310 32091011121314151617250 260 270 280 290 300 310 32091011121314151617250 260 270 280 290 300 310 32091011121314151617250 260 270 280 290 300 310 32091011121314151617A B C D A (?mol CO2 m-2s-1) A (?mol CO2 m-2s-1) Ci (?       Ci (?        28  Figure 4.  ? 13C correlations with net photosynthesis (A) for each provenance. The P. trichocarpa provenances are Quesnel Lake (A: r=-0.086, p=0.813) and MacMillan Island (C: r=-0.072, p=0.843); the Populus balsamifera provenances are Gillam (B: r=0.730, p=0.017) and Carnduff (D: r=0.687, p=0.028).  9 1011121314151617-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.09 1011121314151617-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.09 1011121314151617-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.09 1011121314151617-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.0A B C D ?13C (?) ?13C (?) A (?          A (?          29  Figure 5.  ? 13C correlations with photosynthetic NUE for each provenance. The P. trichocarpa provenances are Quesnel Lake (A: r=-0.818, p=0.004) and MacMillan Island (C: r=-0.079, p=0.829); the Populus balsamifera provenances are Gillam (B: r=0.220, p=0.541) and Carnduff (D: r=0.650, p=0.042).  0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.00.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.00.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.00.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.0A B C D ?13C (?) ?13C (?) NUE (? mol CO2 mmol N-1s-1) NUE (?          30  Figure 6.  ? 13C correlations with stem volume for each provenance. The P. trichocarpa provenances are Quesnel Lake (A: r=-0.117, p=0.748) and MacMillan Island (C: r=0.761, p=0.011); the Populus balsamifera provenances are Gillam (B: r=0.496, p=0.145) and Carnduff (D: r=-0.485, p=0.156).         02468101214-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.002468101214-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.002468101214-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.002468101214-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.0A  B C D ?13C (?) ?13C (?) Stem volume (cm3)  Stem volume (cm3)   31  Figure 2A revealed possible population differences in the leaf to stem gradient in ? 13C.  A subsequent two-way analysis of variance was carried out on the differences between leaf and stem values for each provenance.  The ANOVA revealed significant differences between the southern P. trichocarpa provenance (MCMN) and the southern P. balsamifera provenance (CAR), with a p-value <0.05 based on Bonferroni?s adjustment (original p-value was 0.002; Bonferroni?s adjustment assigned significance equal to 0.05 for ?   ?  0.0083).  Means for leaf to stem differences in ? 13C each provenance were as follows: Quesnel Lake, -0.816?; MacMillan Island, -1.58?; Gillam, -1.01?; and Carnduff, -0.636?.    Genotype-level Figure 7 shows the scatter plot of ? 13C and NUE divided into quadrants, with approximately 10 genotypes per quadrant.  The plot was divided in this manner to facilitate the identification of genotypes most- and least-likely to have sink-driven WUE, in the upper-right and lower-left quadrants, respectively.  Of the ten genotypes located in the upper right quadrant, five revealed high levels of net photosynthesis within their respective provenance: from MacMillan Island, MCMN4 and HRSO2; from Quesnel Lake, QAUS7 and QFRS3; and from Gillam, GIL3 (Fig. 7 and Fig. 1).  Of these five, four have high A coupled with high biomass, relative to their respective provenance: HRSO2, MCMN4, GIL3, and QAUS7 (Fig. 8).     32  Figure 7.  ? 13C plotted against photosynthetic NUE for all genotypes in each of the four provenances.  Plot is divided into four quadrants, with each containing as close to 10 genotypes as possible.  Genotypes are labeled in the upper right quadrant, indicating both high  ? 13C and high NUE.  Level of net photosynthesis for each labeled genotype can be compared to other genotypes within its provenance (see Fig. 1).  The same can be done for biomass (see Fig. 8). Circles represent the P. balsamifera provenances (Gillam: closed, Carnduff: open) and triangles represent the P. trichocarpa provenances (Quesnel Lake: closed, MacMillan Island: open).     0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14-32.0-31.5-31.0-30.5-30.0-29.5-29.0-28.5-28.0QAUS7 GIL3 HRSP2 MCMN4 HRSO4 QFRS2 HRSO2 QLKE3 QFRS3HRSO5 NUE (?        ?13C   33Figure 8.  Fresh total biomass (g) for all genotypes within provenances.  Gillam (GIL) and Carnduff (CAR) represent the northern and southern Populus balsamifera provenances, respectively.  Quesnel Lake (QFRS, QLKE, QAUS) and MacMillan Island (MCMN, HRSP, HRSO) represent the northern and southern P. trichocarpa provenances, respectively.  Genotypes within each provenance are sorted according to increasing net photosynthesis.  For comparison with net photosynthesis measurements for each genotype, see Figure 1.                                                              GIL 4GIL 12GIL 10GIL 14GIL 15GIL 7GIL 5GIL 6GIL 3GIL 13CAR 7CAR 14CAR 15CAR 4CAR 8CAR 3CAR 11CAR 1CAR 2CAR 5QFRS 1QFRS 4QLKE 3QAUS 4QFRS 2QFRS 3QAUS 5QLKE 2QAUS 7QAUS 1MCMN 3MCMN 2HRSP 2HRSO 5HRSO 3HRSO 4MCMN 1HRSO 2HRSP 4MCMN 4020406080100Total Biomass (g)   34   Illustration 1.  Gas-exchange measurements using the LICOR 6400.      35  DISCUSSION  Water-Use Efficiency The two stable carbon isotopes, 13C and 12C, respectively make up 1.11% and 98.89% of the atmospheric carbon pool (Griffiths 1993), giving the atmosphere a more negative isotopic composition relative to the standard Vienna-PDB (Coplen 1994, 1995).  Carbon isotopic composition of C3 plants is more negative than that of the atmosphere due to discrimination against the heavier of the two isotopes during diffusion through the stomata and at the sites of carboxylation, thus giving C3 plants isotopic compostitions ranging from -30 to -22? (Farquhar 1982).  These values fluctuate with the level of internal CO2 partial pressure (ci), becoming more negative, and thus less rich in 13C, as ci increases. Given the direct link between ? 13C values and ci, and between ci and WUE, where WUE is defined as the ratio of C assimilation to transpiration (A/E), C isotope composition is commonly used as a surrogate index for plant water-use efficiency (Farquhar et al. 1982, 1989; Griffiths 1993).  WUE and ? 13C across all genotypes were highly correlated in my results (Fig. 2B); as an additional precaution, ? 13C foliar values were compared with ? 13C stem values, to ensure accuracy.  High correlation (Fig. 2A) here as well lent further confidence to my use of ? 13C foliar values throughout this paper as a measure of WUE.   High WUE results either from decreased stomatal conductance accompanied by decreased growth, or from increased photosynthetic capacity followed by increased   36productivity (Gornall & Guy 2007; Condon et al. 2002).  Highly significant correlation between ? 13C and stomatal conductance across populations (p<0.0001, Table 3) suggests variations in WUE caused primarily by variations in stomatal conductance.  This is consistent with previous work done on Populus trichocarpa Torr. & A. Gray ? Populus deltoides (Rae et al. 2004), Populus deltoides ? Populus nigra (Monclus et al. 2005), and Populus trichocarpa (Gornall & Guy 2007).   However, for WUE to be primarily linked to variations in stomatal conductance, I would expect to find complementary negative correlations between ? 13C and net photosynthesis, stem volume and/or biomass; no such correlations were found (Table 3), suggesting a lack of definitive association between WUE and variations in either stomatal conductance or photosynthetic capacity across all populations in this study.  Others have found positive correlation between growth and WUE in poplar species (Voltas et al. 2006), suggesting a clear link between WUE and photosynthetic capacity.  In conifer species, positive correlations between growth traits and ? 13C values have consistently been found, suggesting WUE determined primarily by variations in photosynthetic capacity for these trees (Sun et al. 1996; Guy & Holowachuk 2001; Silim et al. 2001; Major et al. 2007).  Benowicz et al. (2001) found that differences in intrinsic WUE in paper birch were due to variations in net photosynthesis, and not stomatal conductance, whereas Wang et al. (1998) attributed higher WUE in paper birch (Betula papyrifera) to decreased gs.  Whereas Gornall & Guy (2007) found links between gas-exchange traits and growth in P. trichocarpa, the absence of correlation between net photosynthesis and gs or ci in this present study further implies complete independence of growth from WUE across species and provenances (Table 3).  The same results were found for studies done on Populus deltoides ? Populus nigra clones (Marron et al. 2005;   37Monclus et al. 2005).  As suggested by Monclus et al. (2006), this could have its advantages in a breeding program, as it would allow for the independent selection of both high WUE and high productivity; normal fluctuations in WUE and gs, in this case, should not affect growth.   Significant correlations between A and both biomass and stem volume across all genotypes in this study suggest that more productive genotypes could potentially be identified based on leaf photosynthesis, and independent of WUE.  Measures of leaf photosynthesis using gas-exchange instruments have recently been shown to be reliable in predicting relative growth rate in a wide variety of tree species (Kruger & Volin 2006), although others have found no link between leaf photosynthesis or net assimilation rate and biomass accumulation (Warren & Adams 2005).  Whereas differences in A in this study are not significant between species, P. balsamifera revealed a higher average stem volume overall (5.38 cm3 vs. 4.31 cm3 in P. trichocarpa).  This may simply be due to differences in resource allocation, given the lack of difference in total fresh biomass (not shown), and the greater R:S in P. trichocarpa (Table 2).  Greater growth in P. balsamifera could also be linked to a shorter growing season (fewer frost-free days: average of 151 for P. balsamifera vs. 245 for P. trichocarpa; see Table 1), as suggested by previous work done on Populus species (Gornall & Guy 2007).     Several other trends were revealed at the species and genotype levels.  Positive correlations were found between ? 13C and A in both P. balsamifera provenances (Fig. 4), together with negative correlations between A and ci (Fig. 3).  No correlations were found between these traits in either of the P. trichocarpa provenances.  These results present potentially more complex relationships between WUE and growth for P.   38balsamifera, suggesting that high WUE may result from a combination of lower gs and increased photosynthetic capacity for the Gillam and Carnduff provenances.  The non-significant yet negative trend between ? 13C values and stem volume for the Carnduff provenance (Fig. 6) leaves this possibility unresolved for that provenance specifically.  For Gillam, although correlation between ? 13C values and stem volume is not significant, it is positive (Fig. 6), thus making this provenance the most consistent across all gas-exchange and growth trait correlations, in terms of meeting expectations for sink-driven WUE.  The southern P. trichocarpa provenance, MacMillan Island, may also have partially sink-driven WUE, given the positive correlation between C isotope composition and stem volume (p=0.011, Fig. 6) found for this provenance, however trends across gas-exchange and growth traits are not consistent and remain somewhat inconclusive.      Nitrogen-Use Efficiency Positive correlations between nitrogen content and net photosynthesis in C3 plants are widely recognized (Evans 1989), and have been identified in a variety of gymnosperm (Field et al 1983; Robinson et al. 2001; Major et al. 2007) and angiosperm species (Sobrado 1991), including Populus trichocarpa (Gornall & Guy 2007).  A and leaf N density were positively correlated in this study across all genotypes (p=0.008, Table 3), although at the species level, only P. trichocarpa revealed a positive A ? N correlation (p=0.013, not shown), while P. balsamifera showed a positive yet non-significant correlation (p=0.152, not shown). Photosynthetic nitrogen-use efficiency is defined as the ratio of net photosynthesis to N content per unit leaf area (Larcher 2003).  The expected positive linear relationship between photosynthetic capacity and nitrogen   39content (Larcher 2003) implies a possible inherent trade-off between WUE and NUE, given that any increase in ci (leading to increased NUE) will lead to more negative ? 13C values and lower WUE (Patterson et al. 1997).  This is consistent with studies done on various evergreen species (Field et al. 1983), white spruce (Livingston et al. 1999), and paper birch (Wang et al. 1998), although others found an absence of intrinsic trade-off between WUE and NUE for both white and black spruce (Patterson et al. 1997). In times of drought especially, a tendency in plants to increase stomatal closure will simultaneously increase WUE and decrease NUE, as shown in hybrid willow (Weih et al. 2006).  My results revealed no correlation, and thus no obvious trade-off, between ? 13C and photosynthetic NUE across all genotypes.  At the species level, however, P. trichocarpa revealed a negative correlation between these two traits (p=0.016, not shown), thus indicating a probable trade-off in resource use.  This trend is consistent with the positive correlation between A and N here as well.  The P. balsamifera provenances, Gillam and Carnduff, were not significantly correlated, though revealed a slightly positive r-value of 0.16, coupled with no apparent correlation between A and N, as mentioned previously.  ANOVA revealed no significant differences in NUE at the species level between P. balsamifera and P. trichocarpa (Table 2), but higher WUE for P. trichocarpa, suggesting that these opposing trends separating the two species are likely due to differences in WUE.  Having tested only two provenances for each species, however, makes it impossible to draw definitive conclusions here.  Further examination of  ? 13C ? NUE correlations among the four tested provenances revealed a significant negative correlation for the Quesnel provenance (p=0.004, P. trichocarpa), and a positive correlation for Carnduff (p=0.042, P. balsamifera: Fig. 5).     40NUE and WUE Trade-off The presence of this trade-off, or lack thereof, opens up another avenue by which to better manage the goals of a potential hybridization program.  High productivity in poplars is commonly associated with high water availability (Monclus et al. 2006).  It is possible that apparent trade-offs in resource-use efficiencies among certain species are linked to water availability, and that trees grown under ideal watering schedules would be more likely to show little or no trade-off between WUE and NUE, as suggested by Weih et al. (2006) in an experiment using different watering regimes conducted on hybrid willow.  This may be the case for P. balsamifera and P. trichocarpa, where WUE appears more closely associated with variations in stomatal conductance than with variations in photosynthetic capacity.  However, unless WUE were primarily sink-driven (see Voltas et al. 2006, discussed earlier), growth would likely be compromised as a result of drought and, subsequently, prolonged reduced stomatal conductance (Monclus et al. 2006; Zhang et al. 2004).  Current literature is lacking in studies addressing correlations, or lack thereof, between WUE and NUE, and the implications of such links on growth and productivity, specifically in poplar species and their hybrids.  Further work would need to be done with P. balsamifera and P. trichocarpa to determine the effects of drought on both WUE and NUE.               41Considerations for future work This study admittedly encompasses only a small percentage of available plant material for the species and provenances presented herein.  More extensive work including a greater number of provenances would be very useful in more accurately determining trends within species.  On a provenance level, a more thorough study of Gillam genotypes would be especially interesting, given the trends revealed within that particular provenance.  Studies addressing the link, or lack thereof, between WUE and NUE in tree species, and especially in poplars, are currently lacking in the literature.  The findings in this study suggest the possibility of identifying poplar genotypes with an absence of trade-off between WUE and NUE, notably among genotypes from the northern P. balsamifera provenance, near Gillam.  It would be interesting to survey a wider selection of P. balsamifera provenances, in an attempt to determine whether the trends seemingly present in the GIL provenance are consistently present across P. balsamifera populations.       The experimental design for this work was meant to explore differences within provenances primarily, and was in fact successful to that end, revealing large differences for a variety of traits.  However, definitive statements at both provenance and species levels can hardly be made here.  Comparisons of northern versus southern provenances, for example, would likely reveal more accurate results given a clearer separation between northern and southern provenances, and also given more similar latitudes for each end.  For this study, QL was defined as the northern provenance for P. trichocarpa, despite being located quite a bit further south than Gillam, Manitoba, the location of the northern provenance for P. balsamifera (Table 1).  It would be worthwhile to acquire plant   42material from a P. trichocarpa provenance located at latitudes as similar to those of the GIL trees as possible; such material was not available for this study.  This would allow further inquiry into previous findings that populations of poplar species with shorter growing seasons assimilate biomass at a faster rate (Gornall & Guy 2007), and would allow comparisons to be made between the two species in question here.   Follow-up work with these poplar species should include a more in-depth analysis of the underlying causes of leaf to stem differences in ? 13C.  Such work might reveal differences in C allocation at leaf and stem levels, as well as possibly identify provenances with photosynthetic bark, among other explanations.  Further studies focused on leaf amphistomaticity for both species would also likely prove interesting, and hopefully shed some light on links between leaf morphology, stomatal density and gas-exchange parameters.  Further analysis may show some links between transfer conductance processes (see Warren 2006) and positive correlations between WUE and SR. The inclusion of gibberellin (GA) content analyses in further studies would likely be quite telling as well.  All harvested stems from this study were freeze-dried and set aside for such analysis, to be carried out as soon as possible.  Unfortunately, results could not be included in this paper due to time constraints.  Growth and productivity have been linked with concentrations of endogenous GAs in various plant species (Kende and Zeevaart 1997; Rood et al. 1988) including poplars (Pharis et al. 1991; Eriksson et al. 2000).  A better understanding of the role of GAs in poplar growth and productivity, and their potential link to other physiological traits, would lend additional insight and guidance to tree breeding programs and hybridization efforts intent on creating the ideal   43poplar trees for biofuel production, carbon sequestration, or other uses linked to climate change.                          44  CONCLUSION  The original driving motivation behind this study was to explore and ultimately identify ideal candidates for future hybridization of P. balsamifera and P. trichocarpa genotypes, in the hopes of developing a hybrid poplar that would thrive in continental Canada.  In order to begin identifying which genotypes would fit the goals of such a breeding program, including frost and drought tolerance, rapid growth and high productivity, I took into account WUE, NUE and productivity first and foremost.  Individual genotypes displaying both high WUE and high NUE, together with high productivity, would likely have at least partially sink-driven WUE, and thus would be less likely to compromise growth in times of moderate water stress.  A scatter plot showing the relationship between WUE and NUE across all genotypes combined has the upper right quadrant occupied mostly by genotypes from the Quesnel Lake and MacMillan Island provenances (Fig. 7), with Quesnel Lake displaying a likely trade-off between WUE and NUE (Fig. 5A).  However, genotypes located in the upper right quadrant are the most likely individuals among the four studied provenances to have both high WUE and high NUE, especially if they also display high productivity.  Of the ten individual genotypes most likely to combine high WUE with high NUE (Fig. 7), five also displayed high photosynthesis relative to their provenance: HRSO2, MCMN4, QFRS3, GIL3, and QAUS7 (Fig. 1).  Of these five, four have high A coupled with high biomass, relative to their respective provenance: HRSO2, MCMN4, GIL3, and QAUS7   45(Fig. 8), making these trees excellent candidates for further study.  However, while the P. trichocarpa provenances have more genotypes in this category, if the goal is to create crosses between P. trichocarpa and  P. balsamifera genotypes, then genotypes in the upper right quadrant of each provenance?s ? 13C ? NUE scatter plot should be considered (see Fig. 5), based on their productivity and net photosynthesis levels relative to other genotypes within the same provenance.  Gillam genotypes appear more promising than Carnduff as P. balsamifera candidates for hybridization, given provenance-level correlations most consistent with what would be expected for sink-driven WUE. Canada, the United States and the Russian Federation currently claim the largest naturally occurring stands of poplars and willows (Ball et al. 2005).  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Ljk  ?    ?    ?  ? L2G/(S? L)l(jk)  ?    ?     ?   

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