Needle age and season influence photosynthetic temperature

Needle age and season influence photosynthetic temperature response and total

annual carbon uptake in mature Picea mariana trees

Anna M. Jensen*, Jeffrey M. Warren, Paul J. Hanson, Joanne Childs and Stan D. Wullschleger

Climate Change Science Institute, Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN37831-6301, USA

*For correspondence. Present address: Department of Forestry and Wood Technology, Linnaeus University, 351 95Vaxjo, Sweden. E-mail [email protected]

Received: 6 December 2014 Returned for revision: 6 February 2015 Accepted: 22 June 2015 Published electronically: 28 July 2015

� Background and Aims The carbon (C) balance of boreal terrestrial ecosystems is sensitive to increasing tempera-ture, but the direction and thresholds of responses are uncertain. Annual C uptake in Picea and other evergreen bo-real conifers is dependent on seasonal- and cohort-specific photosynthetic and respiratory temperature responsefunctions, so this study examined the physiological significance of maintaining multiple foliar cohorts for Piceamariana trees within an ombrotrophic bog ecosystem in Minnesota, USA.� Methods Measurements were taken on multiple cohorts of needles for photosynthetic capacity, foliar respiration(Rd) and leaf biochemistry and morphology of mature trees from April to October over 4 years. The results were ap-plied to a simple model of canopy photosynthesis in order to simulate annual C uptake by cohort age under ambientand elevated temperature scenarios.� Key Results Temperature responses of key photosynthetic parameters [i.e. light-saturated rate of CO2 assimila-tion (Asat), rate of Rubisco carboxylation (Vcmax) and electron transport rate (Jmax)] were dependent on season andgenerally less responsive in the developing current-year (Y0) needles compared with 1-year-old (Y1) or 2-year-old(Y2) foliage. Temperature optimums ranged from 18�7 to 23�7, 31�3 to 38�3 and 28�7 to 36�7 �C for Asat, Vcmax andJmax, respectively. Foliar cohorts differed in their morphology and photosynthetic capacity, which resulted in 64 %of modelled annual stand C uptake from Y1&2 cohorts (LAI 0�67 m2 m�2) and just 36 % from Y0 cohorts (LAI0�52 m2 m�2). Under warmer climate change scenarios, the contribution of Y0 cohorts was even less; e.g. 31 % ofannual C uptake for a modelled 9 �C rise in mean summer temperatures. Results suggest that net annual C uptakeby P. mariana could increase under elevated temperature, and become more dependent on older foliar cohorts.� Conclusions Collectively, this study illustrates the physiological and ecological significance of different foliar co-horts, and indicates the need for seasonal- and cohort-specific model parameterization when estimating C uptake ca-pacity of boreal forest ecosystems under ambient or future temperature scenarios.

Key words: Black spruce, Picea mariana, climate change, photosynthesis, temperature adjustment, carbonassimilation, A/Ci curve, leaf age, Q10, evergreen, SPRUCE project, STELLA model, respiration.

INTRODUCTION

Moderate climate warming is expected to prolong the growthseason in the boreal zone. For woody plants, the combinationof elevated air and soil temperatures will entail shifts in foliarontogeny – earlier onset of bud break, resumption of photosyn-thesis and acceleration of foliar maturation (Troeng and Linder,1982; Goulden et al., 1997; Makela et al., 2004; Goodine et al.,2008; Fløistad and Granhus, 2010; Sutinen et al., 2012) – allchanges that would increase the net annual carbon (C) uptake.In addition, greater C assimilation rates across a warmer growthseason may also initially result from photosynthesis operatingcloser to a localized species-specific photosynthetic tempera-ture optimum (Topt) (Berry and Bjorkman, 1980; Way andSage, 2008a, b; Lin et al., 2013; Way and Yamori, 2014;Yamori et al., 2014). Whether these positives will compensatefor C losses due to increased rates of respiration with risingtemperature is still unclear.

Identifying and quantifying seasonal, canopy and ontogeneticvariation in photosynthetic parameters is essential for modellingspecies and ecosystem-specific sensitivities to climate changes,including important aspects related to warming. Whereas theseasonal and canopy variations in photosynthetic capacity, suchas the maximum assimilation rate (Asat), the maximum Rubiscocarboxylation rate (Vcmax) and the maximum rate of electrontransport (Jmax), have been studied intensively across multiplespecies and functional groups (e.g. Wullschleger, 1993;Niinemets et al., 2004), the underlying photosynthetic tempera-ture responses have often been assumed to be constant. This as-sumption persists due to lack of data, even though factorsknown to affect the thermal adjustment of photosynthesis, suchas air temperature and nutrient or water availability, are knownto vary between seasons, canopy position and foliar age(Niinemets, 2002; Grassi et al., 2005; Gunderson et al., 2010;Salmon et al., 2011).

Published by Oxford University Press on behalf of the Annals of Botany Company 2015.This work is written by US Government employees and is in the public domain in the US.

Annals of Botany 116: 821–832, 2015

doi:10.1093/aob/mcv115, available online at www.aob.oxfordjournals.org

Downloaded from https://academic.oup.com/aob/article-abstract/116/5/821/165273by gueston 05 February 2018

Temperature not only affects the immediate biochemical andenzymatic activities involved in photosynthesis but also drivesshort- and long-term temperature acclimation (Stinziano andWay, 2014). Higher growth temperatures often result in greaterTopt for key photosynthetic parameters, such as Vcmax and Jmax

(Berry and Bjorkman, 1980; Way and Sage, 2008a). Severalstudies have looked at thermal regulation/adjustment betweenseasons and across a latitudinal temperature gradient (e.g.Hikosaka et al., 2007; Dillaway and Kruger, 2010), whereasfew studies have investigated effects of ontogeny or seasonalityon Topt of these key photosynthetic parameters (Medlyn et al.,2002a; Gunderson et al., 2010).

Here we identify seasonal and ontogenetic variation of thephotosynthetic temperature responses in Picea mariana (blackspruce) to explore the physiological/ecological significance ofmaintaining multiple foliar cohorts. In P. mariana, as in manyevergreen trees, the maintenance of multiple foliar cohorts isconsidered an adaptive trait to conserve nutrients but also to en-able early-season C assimilation prior to and during shoot flush-ing (Troeng and Linder, 1982; Greenway et al., 1992; Oquistand Huner, 2003). The latter may be especially important forboreal conifers, in which bud break occurs in May–June andnew foliage is only fully mature late in the growing season(Teskey et al., 1984). For such conifers, a combination of ele-vated air temperatures and altered precipitation regimes associ-ated with global warming may enhance total seasonal CO2

assimilation, thus potentially reducing the physiological signifi-cance of maintaining older foliar cohorts (Dang and Lieffers,1989; Way and Sage, 2008b).

The purpose of the study was to identify and quantify sea-sonal, canopy and cohort C assimilation patterns of aP. mariana stand, using seasonal- and cohort-specific tempera-ture responses. To meet these objectives we: (1) characterizedseasonal temperature responses of key photosynthetic parame-ters (i.e. Asat, Vcmax and Jmax) and daytime foliar dark respira-tion (Rd) of two successive P. mariana needle cohorts; (2)characterized spatial differences in the key photosynthetic pa-rameters Rd, foliar morphology and nitrogen (N) status; and (3)used these data, in combination with site-specific climatic andallometric data, as model input to project annual tree canopy Cuptake for the stand using dynamic cohort-specific photosyn-thetic temperature response functions in a simple modellingframework. The model was used to project annual net C ex-change for three temperature scenarios [þ0 (ambient), þ4�5and þ9 �C] to evaluate the importance and relative influence offoliar cohort differences on total annual C gain for warmer cli-mate scenarios.

MATERIALS AND METHODS

Study site

The study was conducted in a mixed peatland Picea mariana(black spruce) and Larix laricina (tamarack) stand at theMarcell Experimental Forest in northern Minnesota, USA(47�3001900 N, 93�2701800 W). Elevation is 410 m above sealevel. The stand was established by natural regeneration follow-ing two strip-cuttings in 1969 and 1974 (Sebestyen et al.,2011). The evaluated bog (S1 Bog) had an open canopy struc-ture, with an average tree height of 4�5 m and a basal area of

5�6 cm2 m�2 in February 2013. At the site, P. mariana trees re-tain on average five foliar cohorts. Bud break occurs duringJune and the newly developed foliage (Y0) becomes fully ex-panded towards the end of July and the beginning of August.The understorey consists of woody shrub species [e.g.Rhododendron groenlandicum (Labrador tea) andChamaedaphne calyculata (leatherleaf)] and a ground layer ofmoss species (e.g. Sphagnum spp. and Polytrichum spp.) andherbaceous species [e.g. Eriophorum angustifolium (cottongrass) and Maianthemum trifolium (three-leaf false Solomon’sseal)]. The climate is continental, with a 40-year average Tair of�15 and 19 �C during January and July, respectively, and an-nual precipitation averages 780 mm (Sebestyen et al., 2011).Site-specific climatic conditions (Tair, relative humidity, photo-synthetically active radiation (PAR) and wind speed) at 2 mwere measured at the south end of S1 Bog, 20–200 m frommeasurement trees (Table 1). Our study site is part of a long-term climate change experiment to study ecosystem response toelevated CO2 and temperature: Spruce and Peatland ResponsesUnder Climatic and Environmental Change (SPRUCE; http://mnspruce.ornl.gov/). Beginning in 2015, the experimental plotswill be exposed to elevated CO2 (400 and 900 ppm) and tem-peratures (þ0, þ4�5 and þ9 �C). We expect the treatments tochange soil water availability, photosynthesis, respiration andlikely relative species composition. Here we studied spatial andseasonal pretreatment patterns of photosynthetic capacity inmature P. mariana trees.

Gas exchange

Seasonal patterns of the photosynthetic capacity of current-year (Y0) and 1-year-old (Y1) foliage were measured in April,May, July, September, August and October between 2010 and2013. We combined data across years, as both year of collec-tion and the interaction between season and year of collectionhad no significant effect (P> 0�05) on photosynthetic patterns.Influences of canopy position and needle age on photosynthesiswere measured for three successive needle cohorts [Y0, Y1 and2-year-old (Y2)] from top, middle and bottom branches in July2011. Photosynthetic response (A/Ci) curves were produced us-ing portable infrared gas analyser systems (LI6400XT, Li-COR, USA). We generated A/Ci curves at saturating light levels(PAR¼ 1000 lmol m�2 s�1) by sequential adjustment of thereference CO2 concentration between 50 and 1600 ppm (400,

Table 1. Observed environmental data for 2011, 2012 and 2013at S1 Bog in northern Minnesota, USA. All data are based onhalf-hour data collected 20–200 m from measured trees. Climaticdata collection began in late June 2010; annual values are there-

fore not available for 2010

Variable 2011 2012 2013

Mean annual Tair (�C) 3�6 5�0 2�2Maximum annual Tair (�C) 34�2 33�8 33�1Minimum annual Tair (�C) –39�7 –31�1 –37�7Mean annual relative humidity (%) 77�8 77�5 77�5Cumulative incident PAR (mol quanta m–2 year–1) 7929 8162 7750Annual precipitation (mm) 645 660 586Mean wind velocity (m s–1) 0�6 0�5 0�6

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300, 200, 100, 50, 400, 550, 650, 800, 950, 1200 and1600 ppm) to assess A across a broad range of intercellular CO2

(Ci) concentrations. Temperature response surfaces were gener-ated by replication of the A/Ci curves at multiple temperatures.Cuvette air temperature was regulated from 2 to 50 �C byPeltier adjustment of the block temperature and by use of an ex-ternal temperature-controlled circulating water bath attached tothe cuvette with block water jackets (LI-COR model 6400-88).Temperature increments were done in steps of 3–5 �C. We mea-sured and included both full (2–50 �C) and partial (2–25 �C and20–50 �C) temperature series. It took our set-up �5 min toreach target temperature, except at low (2–5 �C) and high(40–50 �C) temperatures, where additional time was needed.We used air temperature here, as the spruce needles were notalways in direct contact with the leaf thermocouple, as is thecase when making measurements on broadleaved species. Leafand air temperatures differed on average by 0�5 �C (rangingfrom 0�2 to 4�3 �C) in the chamber. Rates were recorded 5–10 min after target temperatures were reached. Values of va-pour pressure deficit (VPD) were calculated based on air tem-perature and relative humidity in the cuvette, and varied from0�3 to 8�6 kPa (average 1�9 kPa). We minimized variation inVPD by regulating humidity manually (adjusting the scrub). Athigh temperature we used a compact travel humidifier to in-crease humidity of the inlet air. Humidity was adjusted prior tobut not during the automated A/Ci curve measurements. In total,308 A/Ci curves were used. Temperature responses of foliardaytime Rd were measured in a similar fashion but using adarkened conifer chamber (April and September 2013), withseveral needle cohorts within the same chamber. Rates of respi-ration were recorded at PAR¼ 0 lmol m�2 s�1 after the signalhad stabilized (typically after 5–10 min). Following gas ex-change measurements, foliage and branch material was shippedon ice to Tennessee, USA for analysis of leaf area, leaf massand N content. Shoots were defoliated and projected leaf areawas estimated using WinRHIZO 2012b (Regent InstrumentsCanada Inc., Canada) and ImageJ 1�47 (Rasband, 2012) soft-ware. Tissue was dried at 70 �C then analysed for leaf N contentby mass (Nm) and carbon content using an elemental analyser(Costech Analytical Technologies, Inc., USA). We calculatednitrogen per leaf area (Na) as Na¼Nm� leaf mass per area(LMA).

Tree allometry

To estimate canopy foliar mass distribution, eight trees 4–6 m tall were harvested during June/July 2010 and 2011. Eachtree was divided into 1-m stem sections and dried, suchthat foliar mass represented all cohorts of needles within each1-m-stem increment. Additionally, to determine the proportionof total foliar mass represented by each cohort, 15 trees weresampled in October 2012. A total of 45 branches were collectedat the south side of the tree at three different positions withinthe canopy. Foliage on each branch was separated by cohort foranalysis of foliar and woody mass, LMA and N content.

Data analysis

We obtained values for Vcmax and Jmax for each individualA/Ci curve using the platform LeafWeb (http://leafweb.ornl.gov).

LeafWeb utilizes the Farquhar–von Caemmerer–Berry methodwith a novel exhaustive dual optimization approach integratingmesophyll conductance (gm) (Gu et al., 2010). Values of Asat

(PAR 1000lmol m�2 s�1, CO2 400 ppm) were obtained from in-dividual A/Ci curves. By using our protocol, we generated twovalues of Asat per A/Ci curve (see above). The two values wereoften similar (2–6 %) but when they differed (>25 %) we se-lected the observation that aligned best with the full A/Ci curve.Only a single value of Asat was retrieved per A/Ci curve.

We parameterized the temperature response of Asat, Vcmax

and Jmax according to Medlyn et al. (2002b) by fitting eqns (1)and (2) to gas exchange data collected from Y0 and Y1 needlesin August and October:

f Tkð Þ ¼ P 25�Cð Þ exp

Ea Tk�298ð Þ298 R Tk

h i !1þ exp

298 DS�Hd298 R

� �1þ exp

Tk DS�HdTk R

� �0B@

1CA (1)

f Tkð Þ ¼ P optð ÞHd exp

HaðTk�ToptÞTk R Topt

� �

Hd � Ha 1� expHd Tk�Toptð Þ

Tk R Topt

� �� 0BB@

1CCA (2)

P(25 �C) is the specific parameter (Asat, Vcmax and Jmax) at 25 �C(298 K), Ea describes the exponential part of the function orthe activation energy, R is the gas constant (8�3143 J K–1 mol–1),T is air temperature in K, DS (J K–1 mol–1) is an entropy term andHd (J mol–1) is the deactivation energy. We kept Hd constant at200 kJmol–1 to ensure model stability (Medlyn et al., 2002b).The second part of eqn (1) adjusts for loss of enzyme activity athigher temperatures (Leuning, 2002). Equation 2 includes the pa-rameter Topt, which is related to DS; see Dreyer et al. (2001) andMedlyn et al. (2002b) for a full description of the method. Allvalues of foliar Rd were measured directly. Foliar Rd Q10 valueswere calculated according to Linder and Troeng (1981) usinga linear regression model from the natural logarithm ofRd [ln(Rd)¼aþ b Tair].

Q10 ¼ expð10bÞ (3)

As Q10 values may be dependent on the underlying temperaturerange used (Atkin et al., 2005; Kruse et al., 2008), we normal-ized Rd values to 25 �C (Rd25 �C) using eqn (4), with a Q10 valuecalculated between 15 and 30 �C using our September 2013temperature response data.

Rd25 �C ¼ RdT � Q10½25–TÞ=25� (4)

Seasonal-, canopy- and cohort-specific values of Asat, Vcmax andJmax were normalized to 25 �C (Asat25 �C, Vcmax25 �C andJmax25 �C) by parameterization of eqn (1), according to seasonand needle cohort (Table 3). Photosynthetic parameters for Y2needles were normalized using the response of Y1 needles. Wemake this assumption based on similar photosynthetic capaci-ties of Y1 and Y2 needles in July (see Results section, Fig. 4).Effects of needle age (Y), canopy position (C), seasonality (M)and their interactions were evaluated using an ANCOVAmodel, using a Tukey–Kramer honest significant difference(HSD) test to separate means. Pseudoreplication was accounted

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for when repeated measurements occurred (e.g. needle cohortsfrom the same branch or tree). We used an ordinary leastsquares model to test relationships between temperatures, foliarN, needle age and Rd, Vcmax25 �C, Jmax25 �C, foliar mass, LMAand C:N ratios. Model assumptions were tested using aShapiro–Wilk normality test and a Bartlett test of homogeneityof variances. Test outputs are given as R2 and Fd.f.,n, with an in-dication of significance. Data analyses were carried out in Rversion 3�0 (www.r-project.org). All data (environmental, allo-metric and physiological) are available at http://mnspruce.ornl.gov (Jensen et al., 2015).

Estimating annual carbon uptake by foliar cohorts

We estimated the net annual total foliar C uptake contribu-tion of each individual foliar cohort of P. mariana trees by us-ing the derived seasonal- and cohort-specific temperatureresponse functions applied to a simple model of canopy photo-synthesis. Annual net C uptake was interpolated and integratedover a calendar year using an hourly time step model for P.mariana cohorts coded for each cohort class using STELLA10�0�3 modelling software (ISEE Systems Inc., NH, USA).This photosynthetic module has been successfully used as acomponent within an ecosystem level C and water cycle model(INTRASTAND; for more information see Hanson et al., 2004,2005) and was used here only to estimate net foliar C uptakebased on site-specific photosynthetic and Rd measurements andenvironmental drivers (Tables 1 and 2). The photosyntheticmodule estimated annual C uptake from the coupled Farquhar/Ball–Berry photosynthetic and stomatal conductance model asdescribed by Harley et al. (1992), incorporating the temperatureresponse functions (eqn 1).

Farquhar model and Rd variables were obtained from thegas exchange measurements described above (Table 2).Using values of daytime Rd likely underestimates extrapo-lated night-time respiratory C losses, as mitochondrial respi-ration can be suppressed by light (Atkin et al., 2005).Measured half-hourly site meteorological conditions at 2 m(Tair, relative humidity and PAR) were applied as the effec-tive conditions at the leaf surface (Table 1). Daytime wind ve-locities at the site averaged �0�6 m s�1, which reduced theboundary layer conductance sufficiently to support this as-sumption. We also assumed that T responses were constantfor different light levels. This protocol ensured integration ofboth diurnal and seasonal conditions, including short-termchanges due to clouds or rain events. Given the open natureof the S1 Bog forest, all foliage was assumed to be fully sun-exposed for the purposes of annual C gain calculations. Therecertainly was some shading of the older cohorts, especiallythose >3 years old, which were assumed not to be a signifi-cant component of C uptake due to their low residual bio-mass. Canopy foliar biomass per unit ground area wasderived from mass allometric relationships developed specifi-cally for the SPRUCE site for trees with diameter >1�3 m atbreast height. Site-specific tree diameter data for 21 definedplot areas (113 m2 plot–1) combined with the allometric rela-tionship data provided a ground-area-based estimate of totalstanding above-ground biomass for February 2013. Live fo-liar mass data multiplied by corresponding leaf mass per unitarea yielded the leaf area index (LAI) for the defined annual

cohort(s) (Table 2). At the SPRUCE site, foliage older thanthree cohorts makes up only a small fraction of P. marianafoliar mass (7 %). Because such older foliage has reducedphotosynthetic capacity (see also Niinemets, 2002), these co-horts were not considered an important contribution to P.mariana annual C uptake. Net C uptake was modelled forthree different temperature assumptions [þ0 (ambient), þ4�5and þ9 �C] using site-specific environmental data from 2011,2012 and 2013. These temperature scenarios were chosenbased on the temperature treatments within the SPRUCE ex-periment, enabling future physiological and model compari-sons. While 4�5 �C is within the expected range of futuretemperature for the boreal north, 9 �C is high, but used here todetermine potential threshold responses. Total annual C up-take was calculated for the sum of individual cohort groups(multiple foliar cohort simulation), but was also estimated fora simplified single cohort (Y1) to judge the significance ofmulti-cohort data (single foliar cohort simulation).

RESULTS

Climate and shoot phenology

Climatic conditions between 2011 and 2013 were similar to the40-year monthly means reported by Sebestyen et al. (2011).Measured mean annual Tair ranged from 2�2 to 5�2 �C, withmaximum and minimum temperatures around 34 and �36 �C(Table 1). Annual cumulative PAR averages were 7929, 8162and 7750 mol quanta m�2 year–1 in 2011, 2012 and 2013, re-spectively, whereas annual precipitation averaged 645, 660 and586 mm in 2011, 2012 and 2013, respectively (Table 1).

Table 2. Needle cohort and physiological and mass characteris-tics used in the annual C estimation. Values of Asat, Vcmax andJmax are normalized to 25 �C according to season and needle age

Variable Y1&2 Y0

Vcmax25 �C (mmol m–2 s–1)DOY 115–150 33 –DOY 150–180 53 –DOY >180 71 –DOY 150–240 – 33DOY >240 – 36

Jmax25 �C (mmol m–2 s–1)DOY 115–150 70 –DOY 150–180 90 –DOY >180 112�8 –DOY 150–240 – 71DOY >240 – 93�8

go (mmol m–2 s–1) 0�0018 0�0018gl (mmol m–2 s–1) 0�0032 0�0052Rd25 �C (mmol m–2 s–1)

DOY590 1�4 0DOY 90–150 1�4 0�2DOY >150 1�4 1�4

Q10

DOY590 2�3 1�9DOY 90–150 2�3 1�9DOY >150 2�3 2�3

LAI (m2 m–2) 0�67 0�52Needle mass (g m–2 ground) 223 162LMA (g m–2 needle) 333 313

DOY, day of year.



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Growing season length [frost-free period (Monson et al., 2005;Viereck and Johnston, 1990)] averaged 175 d between 2010and 2013 at S1 Bog.

Seasonal temperature response of photosynthesis

Season and needle cohort affected photosynthetic (Asat,Vcmax and Jmax) responsiveness to temperature and CO2, typi-cally displaying flat response surfaces early in the season andin younger foliage (Fig. 1A–I). Table 3 gives the estimated pa-rameters of the temperature response of Asat, Vcmax and Jmax

according to season and needle age. In April, when air tempera-tures were low, photosynthetic capacity (Asat, Vcmax and Jmax)of overwintering needles (Y1) showed a low responsiveness toCO2 and temperature, compared with later in the season(Fig. 1, Table 3); as a result, temperature responses were notconsidered in April. Projected leaf area values of Asat and its re-sponse to temperature were similar for Y0 and Y1 needles butdiffered across seasons, averaging 9�2 6 0�3, 8�9 6 0�4 and6�4 6 0�4 lmol m�2 s�1 at 25 �C for Y1 August, Y0 August andY0 October, respectively (Fig. 1B and C and Table 3). In con-trast, both rates and responses of the biochemical parameters(Vcmax and Jmax) depended on foliar age and season. In August,values of rates for Vcmax and Jmax were much more responsiveto temperature in Y1 needles compared with the new (Y0) fo-liage (Fig. 1E, H and Table 3). For Y0 foliage, values ofP(25 �C) of Vcmax and Jmax increased with time (Fig. 1E, F, H, Iand Table 3). Activation energy (Ea) ranged between 18�3and 49�8 kJmol–1 for Vcmax and between 14�4 and 32�5 kJmol–1

for Jmax, generally increasing as needles aged. For example, Ea

values for Vcmax and Jmax were 2- to 3-fold greater in Octobercompared with August in Y0 foliar cohorts. Temperatureoptima (Topt) differed between cohorts and across seasons(Table 3). In August, Topt values for Vcmax and Jmax were 3�4and 1�2 �C lower in Y0 foliage compared with Y1 foliage. Incontrast, Topt values for Vcmax and Jmax decreased in Y0 needlesby 3�7 and 6�8 �C, respectively between August and October.

Temperature response of foliar Rd, on a leaf area basis, dif-fered seasonally (M� Tair: F1,8¼ 24�6; P50�001), with Q10

values of 1�89 and 2�25 (between 15 and 30 �C) during Apriland September 2013, respectively (Fig. 2). While LMA wasgreater in September (371 6 19 g m�2) compared with April(274 6 18 g m�2), temperature response on a mass basis stilldiffered (M�Tair, F1,8¼ 13�1; P50�01). No sharp Rd reduc-tions were observed at higher temperatures, and Q10 values(calculated in steps of 10 �C) were similar over the range oftemperatures used (data not shown).

Seasonal patterns in needle photosynthetic capacity andmorphology

Photosynthetic capacity at 25 �C (Asat25 �C, Vcmax25 �C,Jmax25 �C), Na and LMA were affected by both foliar ageand season (Fig. 3). Mean (6 s.e.) values of Asat25 �C rangedfrom 0�1 6 0�2 to 11�2 6 2�3 and from 5�8 6 0�2 to9�1 6 0�2 lmol m�2 s�1 for Y1 and Y0 needles, respectively.Whereas rates of Asat25 �C differed with foliar age (part of theseason, Y, F1,210¼ 13�2, P50�001; M, F5,210¼ 20�1,

Table 3. Parameters of the temperature response of Asat, Vcmax, Jmax and TPU by cohort and season1. Rates were generated usingeqns (1) and (2) and given on projected leaf area. All estimated parameters, with the exception of Asat Ea of Y1 needles, were signifi-

cant (P50�01)

P(25 �C)

(lmol m–2 s–1)P(opt)

(lmol m–2 s–1)Hd

(kJ mol–1)Ea (kJ mol–1) DS

(J mol–1)Topt (�C) Residual s.e.

(P(25 �C)/P(opt))D.f.

(P(25 �C)/P(opt))

Asat (lmol m–2 s–1)August

Y1 9�2 (0�3) 9�3 (0�3) 200 0�3 (2�5)2 633�4 (3�1) 18�7 1�8/1�8 62/64Y0 8�9 (0�4) 8�7 (0�2) 200 6�7 (3�1) 639�9 (2�3) 26�3 1�5/1�5 70/72

OctoberY0 6�4 (0�4) 5�9 (0�2) 200 12�9 (4�9) 643�9 (2�4) 23�7 1�1/1�1 60/62

Vcmax (lmol m–2 s–1)August

Y1 70�7 (2�3) 102�1 (2�8) 200 30�7 (3�2) 628�0 (2�3) 38�3 14�6/14�4 60/62Y0 33�4 (1�3) 38�6 (1�2) 200 18�3 (3�4) 630�1 (2�7) 35�0 8�0/7�9 70/72

OctoberY0 35�5 (2�0) 40�8 (1�4) 200 49�8 (7�8) 647�8 (2�5) 31�3 7�8/7�7 60/62

Jmax (lmol m–2 s–1)August

Y1 112�8 (2�2) 135�1 (2�7) 200 17�6 (2�1) 625�9 (2�3) 36�7 16�7/16�4 55/57Y0 71�0 (2�0) 80�5 (1�8) 200 14�4 (2�3) 625�6 (2�8) 35�4 12�2/12�0 62/64

OctoberY0 93�8 (4�8) 92�9 (2�57) 200 32�5 (5�7) 649�0 (2�5) 28�7 12�1/11�8 31/33

TPU (lmol m–2 s–1)August

Y1 8�5 (0�2) 9�9 (0�2) 200 15�9 (1�9) 623�8 (2�5) 37�3 1�2/1�2 55/57Y0 5�2 (0�2) 6�2 (0�2) 200 16�1 (2�6) 624�0 (2�8) 37�3 1�1/1�1 70/72

OctoberY0 7�0 (0�2) 6�2 (0�2) 200 33�2 (3�8) 647�2 (1�5) 29�6 0�9/0�9 60/62

TPU, triose phosphate utilization.1Parameters for April were not estimated due to low responsiveness.2P-values> 0�05.



P50�001; Y�M, F1,210¼ 12�0, P50�001), similar rates wereobserved for July and August (Fig. 3A). For overwintering nee-dles (Y1), mean values of Vcmax25 �C increased from 5�1 6 0�5to 66�0 6 4�0 lmol m�2 s�1 between April and May, and werestable around 66–76 lmol m�2 s�1 until August. Current year(Y0) needles had 67 % and 58 % lower Vcmax25 �C values com-pared with Y1 foliage in July and August, respectively. WhileVcmax25 �C of Y0 needles increased from 21�0 6 5�9 to45�8 6 7�7 lmol m�2 s�1 between July and September, they re-mained well below Vcmax25 �C of Y1 needles during the growingseason (Fig. 3B). For Y1 foliage, Jmax25 �C increased signifi-cantly between April and May from 14�5 6 0�9 to90 6 5�1 lmol m�2 s�1 (Fig. 3C). Seasonal maximum valuesof Jmax25 �C were 129�2 6 0�6 and 93�8 6 4�8 lmol m�2 s�1 inY1 and Y0 foliage, occurring in August and October, respec-tively (Fig. 3C). Values of Na differed between cohort and sea-son (Y, F1,62¼ 44�5, P50�001; M, F5,62¼ 5�4, P50�001) andincreased over time from 158�6 6 4�3 to 200�3 6 4�8 and130�4 6 7�3 to 177�3 6 17�2 mmol m�2 in Y1 and developing

April

A

10

Asa

t(m

mol

m–2

s–1

)

Vcm

ax(m

mol

m–2

s–1

)

J max

(mm

ol m

–2 s

–1)

0

0

00 20 40 0 20

Tair (°C)Tair (°C) Tair (°C)

40 0 20 40

100

100

50

B C

D E F

G H I

August October

Y1

Y0

FIG. 1. Seasonal temperature response of (A–C) Asat, (D–F) Vcmax and (G–I) Jmax in 1-year-old (Y1) and current-year (Y0) P. mariana needles at S1 Bog in northernMinnesota, USA. The scatter shows individual values of Asat, Vcmax and Jmax and lines (solid, Y1; broken, Y0) denote the curve fittings (eqn 1) including all observa-

tions; see Table 3.

2 y = –2·0 + 0·02x

R2 = 0·924∗∗∗

y = –2·7 + 0·05x

R2 = 0·658 P < 0·001

April, Y0–Y2

September, Y0–Y2

0

–2

–40 10 20 30

Tair (°C)

ln R

d(m

mol

m–2

s–1

)

40

FIG. 2. Temperature response of foliar daytime respiration rates (Rd) in Y0–Y2needle cohorts during April and September 2013.



Y0 needles, respectively (Fig. 3D). Similarly, LMA was af-fected by cohort and season (Y, F1,63¼ 12�3, P50�001; M,F5,63¼ 41�2, P50�001), with average values ranging from274�1 6 5�4 to 364�4 6 10�9 and 229�9 6 10�8 to 355�2 613�6 g m�2 in Y1 and Y0 needles, respectively (Fig. 3E).

Photosynthetic capacity and Rd by needle age and canopyposition

In July of 2011, Vcmax25 �C and Jmax25 �C were affected byneedle age (Y, F2,22¼ 5�9, P50�05 and F2,20¼ 4�1, P50�05,respectively) and canopy position (C, F2,22¼ 6�1, P50�05 andF2,20¼ 4�4, P50�05), but not their interaction, whereas Rd25 �C

was only affected by needle age (Y, F2,28¼ 12�9, P50�001)(Fig. 4A–C). Low rates of Vcmax25 �C and Jmax25 �C were gener-ally observed in Y0 needles and in lower parts of the canopy(Fig. 4A, B), although there was substantial variation in valuesdue to environmental conditions, such as periodic shading fromadjacent trees. The Y0 foliage exhibited variation in Vcmax25 �C

and Jmax25 �C that was at least partially the result of differencesin Na content, although linear regressions only explained 25 %of the variation (Vcmax25 �C, R2¼ 0�24, P50�001; Jmax25 �C,R2¼ 0�25, P50�001).

Foliar respiration (Rd25 �C) was 73–84, 61–69 and 75–75 %greater in Y0 than Y1 and Y2 needles for branches at the top, mid-dle and bottom of the canopy, respectively (Fig. 4C). There was anegative association between Na and Rd25 �C (R2¼ 0�41, P50�01)but only in the developing Y0 foliage. As LMA was 14–18 %greater in Y1 and Y2 needles, there was a positive correlationbetween Rd25 �C and N on a leaf mass basis (data not shown).

Canopy allometric and foliar morphology

Needle mass distribution varied according to canopy posi-tion and cohort, as represented by a 6-m tall P. mariana treewhose foliage was sequentially harvested in 2012 (Fig. 5).For the eight P. mariana trees harvested in June and July of2010 and 2011, 2–30 %, 19–67 % and 25–32 % of the totalneedle mass (3�39 6 1�02 kg) was distributed in the bottom,middle and top canopy layers, respectively. Towards the endof the 2012 growing season �80 % of the total foliar massbelonged to the three youngest foliar cohorts (Y0, Y1 andY2) (Fig. 6A), displayed towards the more exposed tips ofthe branches. Branches in the top of the canopy had a signifi-cantly greater proportion of foliar mass in the Y0 cohort,while the proportion of foliar mass in other cohorts was notaffected by height, and declined with needle age (Fig. 6A).Older needle cohorts were observed to have higher LMA (Y,F5,238¼ 2�4, P50�05) and C:N ratios (Y, F5,194¼ 2�9,P50�05) compared with Y0 needles, whereas canopy posi-tion had no significant effect (Fig. 6B, C).

10

Asa

t25°

C

(mm

ol m

–2 s

–1)

Vcm

ax25

°C

(mm

ol m

–2 s

–1)

J max

25°C

(mm

ol m

–2 s

–1)

Na

(mm

ol m

–2)

LMA

(g m

–2)

A Y: F(1) = 13·2∗∗∗

M: F(5) = 20·1∗∗∗

Y × M: F(1) = 12·0∗∗∗

n = 210

Y: F(1) = 201·3∗∗∗

M: F(5) = 79·1∗∗∗

Y × M: F(1) = 0·5ns

n = 287

Y: F(1) = 173·2∗∗∗

M: F(5) = 75·6∗∗∗

Y × M: F(1) = 0·8ns

n = 209

Y: F(1) = 44·5∗∗∗

M: F(5) = 5·4∗∗∗

Y × M: F(1) = 2·9ns

n = 62

Y: F(1) = 12·3∗∗∗

M: F(5) = 41·2∗∗∗

Y × M: F(1) = 1·9ns

n = 63

Y1Y0

B

C

D

E

0

50

0

100

0

200

0500

0April June August

Months

October

FIG. 3. Seasonal patterns in (A–C) photosynthetic capacity, (D) Na and (E) LMAin 1-year-old (Y1) and current-year (Y0) P. mariana needles. Values ofAsat, Vcmax and Jmax were normalized to 25 �C based on season and needle age(Table 3). Data were collected and combined over a 4-year period. Year ofcollection was not a significant factor for any of the variables. Values are means(6 1 s.e., variation often smaller than the symbols) and ANCOVA output[Fd.f. values and n (total number of A/Ci curves across cohorts and months)],with significance levels for cohort (Y), month (M) and their interaction (Y�M)

estimates.

200A

B

C

100

0

200

100

0

2

1

00 1

Needle age (years)

2V

cmax

25°C

(mm

ol m

–2 s

–1)

J max

25°C

(mm

ol m

–2 s

–1)

Rd2

5°C

(mm

ol m

–2 s

–1)

Y: F(2) = 5·9∗

C: F(2) = 6·1∗

Y × C: F(3) = 0·8ns

n = 22

Y: F(2) = 4·1∗

C: F(2) = 4·4∗

Y × C: F(3) = 0·6ns

n = 20

Y: F(2) = 12·9∗∗∗

Top

Middle

Bottom

C: F(2) = 0·9ns

Y × C: F(3) = 0·8ns

n = 28

FIG. 4. Photosynthetic capacity [(A) Vcmax25 �C and (B) Jmax25 �C] and (C) foliarday-respiration rates (Rd25 �C) by needle age and canopy position measured overa 4-day period in July 2011. Values are means (6 1 s.e.) and ANCOVA output(Fd.f. values and n), with significance levels for cohort (Y), canopy position (C)

and their interaction (Y�C) estimates.



Annual carbon uptake components by foliar cohort

Temperature-sensitive Farquhar/Ball–Berry model projec-tions of annual net C uptake across cohorts (see Methods) indi-cated that foliar cohort contributions to total annual C uptakewere different, and thus should be estimated independently bycohort groups having similar characteristics. Table 4 illustratesthe model-estimated annual net C uptake for the S1 BogP. mariana stand, integrating cohort-specific photosynthetictemperature responses (multiple foliar cohort simulation) or

assuming similar photosynthetic temperature responsivenessacross all cohorts (single foliar cohort simulation) for three dif-ferent temperature conditions.

When integrating cohort-specific characteristics, we esti-mated the total (Y0þY1&2) annual C uptake for theP. mariana stand at ambient Tair to be 551, 507 and534 gC m�2 year–1 for 2011, 2012 and 2013, respectively(Table 4). Although Y0 LAI, at 0�52 m2 m�2, was relativelylarge compared with 0�67 m2 m�2 for Y1 and Y2, current yearfoliage contributed only �36 % of the total annual C uptake(Tables 2 and 4). To evaluate the importance and relative influ-ence of foliar cohort differences on annual C gain, we estimatedannual foliar C uptake assuming all needles belonged to asingle cohort (Y1 in this example). By comparison, the singlefoliar cohort simulation estimated annual C uptake for the P.mariana stand at ambient Tair to be �11 % greater (614, 563and 589 gC m�2 year–1 for 2011, 2012 and 2013, respectively)than the multiple foliar cohort simulation. In addition, and as aresult of the relatively low photosynthetic responsiveness toCO2 and temperature in Y0 needles (Fig. 1 and Table 3), therelative influence of foliar cohort differences on total annual Cgain became more pronounced when warmer temperature as-sumptions were applied (þ4�5 and þ9 �C) (Table 4).

DISCUSSION

In P. mariana, where seasonal shoot development is slow,maintaining multiple foliar cohorts is of key importance for to-tal annual C uptake. Results presented here demonstrate that (1)photosynthetic capacity and temperature responsiveness are sig-nificantly lower during midsummer in the developing Y0 co-hort compared with older cohorts; and (2) estimates of canopyC uptake without integrating seasonal- and cohort-specific pho-tosynthetic temperature response functions could result in over-estimation of annual C uptake, relative to each cohort’s LAIcontribution. Furthermore, and as result of the relatively lowphotosynthetic responsiveness to temperatures observed in Y0needles, the relative C contribution by Y0 needles decreasedwhen warmer climate assumptions were applied (Table 4). Theresults illustrate the importance of accounting for underlyingseasonal- and cohort-specific differences when estimatingcurrent and future ecosystem C uptake capacities in boreal ever-green forest ecosystems.

Seasonal dynamics of photosynthetic capacity

The cohort-specific seasonal patterns of Asat25 �C values weresimilar to rates reported earlier in P. mariana and other borealconifers, such as Picea abies and Pinus sylvestris (Fig. 3A)(Troeng and Linder, 1982; Bergh and Linder, 1999). While ourAsat25 �C estimates, on average, were greater than earlier pub-lished values for P. mariana (Goulden et al., 1997; Bronsonand Gower, 2010; Hebert et al., 2010), it may reflect site-specific differences in growth temperature and resourceavailabilities. For example, values of Asat25 �C presented hereare 2- to 2�5-fold greater than values reported by Bronson andGower (2010) for P. mariana saplings grown in Manitoba,Canada (1300 km north of S1 Bog). It is generally assumedthat Asat declines with needle age, at least on a leaf area basis

6

5

4

3

2

1

0 200 400 600Needle mass (g)

Tre

e he

ight

(m

)

800 1000

>Y3

Y2

Y1

Y0

1200

FIG. 5. Needle mass distribution within the canopy (m) of a 6 -m tall representa-tive P. mariana tree, according to needle age. Whole trees were harvested in

June/July 2010 and 2011; cohort proportions were estimated in October 2012.

A

0·5

0400

300

80

60

40

0 1 2 3

Needle age (years)

Pro

port

ion

of to

tal f

olia

r m

ass

LMA

(g m

–2)

C:N

rat

io

4 5

B

C

Y: F(5) = 342·3∗∗∗

C: F(2) = 2·3ns

Y × C: F(10) = 6·3∗∗∗

y = 0·5182e–0·646x

R 2 = 0·963∗∗∗

n = 239

Y: F(5) = 2·4∗

C: F(2) = 2·0ns

Y × C: F(10) = 0·7ns

y = 318·7 + 7·5x

R 2 = 0·473∗

n = 238

Y: F(5) = 2·9∗

C: F(2) = 0·4ns

Y × C: F(10) = 1·5ns

n = 194

TopMiddleBottom

FIG. 6. (A) Proportion of total needle mass distribution, (B) leaf mass per area(LMA) and (C) C:N ratios by cohort and canopy position, October 2013. Valuesare means (6 1 s.e.), regression lines and the ANCOVA output (Fd.f. values andn), with significance levels for cohort (Y), canopy position (C) and their interac-

tion (Y�C) estimates.



(e.g. Hebert et al., 2010); however, our results contrast withthis, in general having lower values of Asat in younger needles.This reduced photosynthetic capacity is mainly a result of thecohort-specific temperature response of the photosynthetic bio-chemical component (Vcmax and Jmax), whereas foliar morpho-logical development may partly counter this effect in P.mariana (Figs 1 and 3). This is illustrated by the relatively simi-lar overall values and temperature response of Asat between Y0and Y1 needles, in spite of significantly lower rates of Vcmax

and Jmax in Y0 needles (Figs 1B, E, H and 3A, B, C), a discrep-ancy that can be explained by a shift in mesophyll conductance(gm) with leaf maturation (Gu et al., 2010). Developing needlesmay therefore, at least to some extent, be able to compensatefor this reduced capacity by adjusting mesophyll conductance(Busch et al., 2013).

Springtime resumption of photosynthesis in overwinteringneedle cohorts and bud break is a function of plant-availablewater and soil and air temperature in many conifer species(Bergh and Linder, 1999; Tanja et al., 2003). The release ofphotosynthetic dormancy in overwintering needles entailschanges in chloroplast ultrastructure and elevated levels ofchlorophyll, photosystem II, Rubisco and downstream co-/enzymes of the Calvin cycle (Oquist and Huner, 2003;Monson et al., 2005). Similarly, we observed a substantial in-crease in Vcmax25 �C and Jmax25 �C in P. mariana Y1 needlesduring spring. However, rates of recovery of Vcmax25 �C andJmax25 �C (e.g. times to seasonal optima) differed, suggestingthat growth temperatures and/or plant-available water (indi-rectly soil/peat temperature) stimulate production and activa-tion of Rubisco and the electron transport chain differently(Fig. 3B, C) (Monson et al., 2005; Sevanto et al., 2006).Whereas an increase in these biochemical parameters is oftenpositively correlated with an increase in foliar nitrogen (e.g.Greenway et al., 1992), N concentrations in P. mariana Y1needles were stable during the period of photosyntheticresumption (April to June; Fig. 3B–D). Using N concentra-tion as a proxy of the Rubisco content, our findings suggestactivation of Rubisco rather than an increase in foliarcontent.

The photosynthetic capacity (Vcmax25 �C and Jmax25 �C) ofthe developing Y0 cohort of needles increased during thegrowing season, but did not reach the capacity of the Y1

needles measured in August despite equal or greater LMAand Na (Fig. 3A–C). Although we did not quantify the photo-synthetic temperature response functions of Y1 needlesin October, our results indicate that the photosynthetic appa-ratus of Y0 needles may require more than one growth sea-son to mature, and therefore may help explain th edifferencein the springtime rates of recovery of Vcmax25 �C andJmax25 �C.

Seasonality and needle age affected both Topt and tempera-ture response curve shapes (Fig. 1 and Table 3). Temperatureresponse curves for Vcmax and Jmax were noticeably more bell-shaped and had greater thermal optimums and greater activationenergies (Ea) in 1-year-old (Y1) needles than in new (Y0) nee-dles. However, with time and towards the end of the growthseason, Y0 needles’ response curves became more similar to re-sponse curves observed for Y1 needles (Fig. 1 and Table 3).Observed values of Topt in P. mariana are of the same magni-tude as reported for Quercus robur and Betula pendula (Dreyeret al., 2001) but �10 �C greater than observed for Pinuspinaster (Medlyn et al., 2002a).

Multiple factors are correlated with the shifts in Topt ofVcmax and Jmax, including growth temperature, ontogeny andleaf nutrient status (Berry and Bjorkman, 1980; Martindaleand Leegood, 1997; Medlyn et al., 2002a; Khaembah et al.,2013). While changes in growth temperatures and light avail-ability may partially explain seasonal differences in Topt ofVcmax and Jmax, foliar nutrient status and ontogeny may alsoaccount for the observed cohort-age-dependent differences.We note that, as field conditions made it difficult to maintaina consistent VPD across temperatures, A/Ci curves generatedat higher temperatures are less reliable (Medlyn et al.,2002a). Thermal adjustment of the photosynthetic apparatusoccurred in both old and developing needles, sometimes inparallel with shifts in N allocations (Fig. 3A–D; Oquist andHuner, 2003). Although changes in air temperature likely in-duce similar physiological responses for all cohorts, their ca-pacity to respond and thus adjust would be dependent on thebiochemical status of the tissue. To our knowledge, onto-genic thermal adjustment capacity has never been describedfor the temperature response of Vcmax or Jmax. However, it isoutside the scope of the study to quantify thermal adjustmentcapacity at different developmental stages.

Table 4. Extrapolated annual net C exchange (gC m–2 ground area year–1) for Picea mariana needles for cohorts for three temperatureassumptions [þ0 (ambient), þ4�5 and þ9 �C] and three years of environmental driver data (2011, 2012 and 2013). Annual positivevalues of C exchange are net uptake into the foliage from the atmosphere, with and without considering cohort-specific differences in

the model. See Materials and methods section for model description

Treatment (�C) Year (A) Simulation of multiple foliar cohorts (B) Simulation of single foliar cohort (B) – (A) difference (%)

Y1&2 Y0 All foliar cohorts All Y1 foliar

þ0 2011 356 195 551 614 þ63 (11�4)þ0 2012 326 181 507 563 þ56 (11�0)þ0 2013 341 193 534 589 þ55 (10�3)þ4�5 2011 409 210 619 707 þ88 (14�2)þ4�5 2012 379 194 573 655 þ82 (14�3)þ4�5 2013 392 206 598 678 þ80 (13�4)þ9 2011 464 209 673 801 þ128 (19�0)þ9 2012 429 189 618 742 þ124 (20�1)þ9 2013 436 200 636 753 þ117 (18�4)



Seasonal temperature adjustment of foliar Rd

The adjustment of foliar respiration to temperature in maturetissues is common and is thought to lead to plant C balance ho-meostasis (Reich et al., 1998). In contrast to Way and Sage(2008a), we found seasonal adjustment of Q10 Rd in P. mariananeedles between April and September, when assessed on both aleaf area and a mass basis. This adjustment reflects differencesin metabolic activity (mitochondrial activity and substrate/co-enzyme availability) (e.g. Atkin et al., 2005; Kruse et al.,2008). Here we measured the instantaneous foliar Rd tempera-ture response of multiple needle cohorts, but as metabolic activ-ity is often greater during rapid growth and expansion(Machado and Reich, 2006), Q10 values are likely greater forthe Y0 cohort. This is partly supported by the 61–75 % greaterRd values observed during July (2011) for Y0 needles com-pared with Y1 and Y2 needles (Fig. 4C) (Teskey et al., 1984).In agreement with earlier findings (Way and Sage, 2008a;Tjoelker et al., 1998), lower levels of foliar N were associatedwith lower rates of respiration per leaf mass in P. mariana.

Annual carbon uptake contribution by foliar cohorts and modelimplications

Our simulations differ from earlier studies (Girardin et al.,2008; Hall et al., 2009) in that we modelled total annual Cuptake separately for each foliar cohort based on seasonal- andcohort-specific photosynthetic temperature responses (Smithand Dukes, 2013). For S1 Bog, this reduced the total estimatedannual C uptake, as the Y0 needle cohort contributed only31–36 % of the total annual C uptake (Table 4). Multi-cohortmodelling illustrates the physiological/ecological significanceof retaining several needle cohorts, not only by allowing for en-hanced CO2 assimilation earlier in the season (resumption ofphotosynthesis) (Oquist and Huner, 2003; Tanja et al., 2003;Hall et al., 2009), but also by maintaining significantly greaterphotosynthetic capacity throughout the growth season. At treeand stand level, the physiological significance of retaining sev-eral cohorts should be put in the context of a cohort’s total life-span C uptake: from sink (net Asat is negative) to source (netAsat is positive) and finally sink again (Asat declines). AlthoughY0 needles contribute significantly to the total C uptake towardsthe end of the growth season, our results clearly demonstratethat maximum photosynthetic capacity is only reached in thesecond year. This finding underlines the need to better under-stand interactions between ontogeny and environmental drivers.

However, in a future warmer climate the relative importancesof different cohorts may shift. Over the last century mean annualair temperature in the North American boreal zone has increasedby 1�75–2�5 �C, and global atmospheric model simulations sug-gest this trajectory will continue (Christensen et al., 2007). ForP. mariana, a combination of elevated air temperatures with in-creased soil water availability during spring will likely prolongthe growth season length by (1) earlier initiation of bud break indeveloping shoots (Y0); (2) accelerated shoot maturation; (3)earlier full photosynthetic recovery in overwintering needles;and (4) a shift in Topt of key photosynthetic parameters.Together, these changes have the potential to significantly in-crease net annual C uptake (Goodine et al., 2008; Fløistad andGranhus, 2010; Sutinen et al., 2012). Indeed, our simulations in-dicate an overall increase in net foliar C uptake under warmer

climate scenarios, a positive effect that remained after integrat-ing enhanced C losses as a result of increased respiration rateswith rising temperature. It is worth noting that we most likelyunderestimated respiratory C losses, as values of Rd were mea-sured during daytime, as Q10 values are often lower in light thanin darkness (see Table 2 in Atkin et al., 2005).

For model simplification, we assumed homogeneous lightavailability (full sun) between needle cohorts and throughoutthe canopy, likely resulting in an overestimation of the totalcanopy C uptake. Even so, we observed little evidence of self-shading between Y0 and Y1 (Fig. 3A, B) or between Y1 andY2 at branch level. Vertical light stratification influencedwithin-canopy photosynthetic capacity (Fig. 4A, B), suggestingthat, for this relatively open S1 Bog P. mariana secondary for-est, within-canopy self-shading induces greater C estimation er-rors compared with branch-level self-shading. However, theassumption of homogeneous light availability across multipleneedle cohorts may induce greater C estimation errors in othersystems, such as productive upland forests with denser canopies(Dewar et al., 2012).

Conclusions

The findings presented here have two major implications formodelling C assimilation at the canopy and stand levels, espe-cially for boreal conifers with prolonged foliar ontogeny (weeksto months). Firstly, it is evident that individual foliar cohortcontributions to annual C uptake must be estimated for cohortgroups having similar characteristics, requiring high-resolutionspecies- and site-specific-allometric and physiological informa-tion at the leaf, canopy and stand levels. Secondly, the underly-ing photosynthetic temperature response depends on foliar age(ontogeny) and seasonality. We suggest that, in spite of beingvery labour-intensive, species-, seasonal- and age-specific tem-perature response dynamics should be integrated and linked togrowth temperatures. Taken together, our findings show thephysiological significance of maintaining multiple foliar co-horts, not only during bud break but also throughout the growthseason. Our results thus illustrate the need for seasonal- and co-hort-specific model parameterization when estimating the C up-take capacity of boreal forest ecosystems under ambient orfuture temperature scenarios.

ACKNOWLEDGEMENTS

The authors appreciate fieldwork, development of allometricrelationships and data analysis from Carla Gunderson, KelseyCarter, Lianhong Gu, Donald E. Todd, Deanne Brice, JanaPhillips, W. Robert Nettles and Les Hook. This material isbased upon work supported by the US Department of Energy,Office of Science, Office of Biological and EnvironmentalResearch, under contract DE-AC05-00OR22725.

LITERATURE CITED

Atkin OK, Bruhn D, Hurry VM, Tjoelker MG. 2005. The hot and the cold:unraveling the variable response of plant respiration to temperature.Functional Plant Biology 32: 87–105.



Bergh J, Linder S. 1999. Effects of soil warming during spring on photosyn-thetic recovery in boreal Norway spruce strands. Global Change Biology 5:245–253.

Berry J, Bjorkman O. 1980. Photosynthetic response and adaptation to temper-ature in higher plants. Annual Review of Plant Physiology 31: 491–543.

Bronson DR, Gower ST. 2010. Ecosystem warming does not affect photosyn-thesis or aboveground autotrophic respiration for boreal black spruce. TreePhysiology 30: 441–449.

Busch FA, Sage TL, Cousins AB, Sage RF. 2013. C-3 plants enhance rates ofphotosynthesis by reassimilating photorespired and respired CO2. Plant,Cell and Environment 36: 200–212.

Christensen JH, Hewitson B, Busuioc A, et al. 2007. Regional climate projec-tions. In: SD Solomon, M Qin, et al. eds. Climate Change 2007: ThePhysical Science Basis. Contribution of Working Group I to the FourthAssessment Report of the Intergovernmental Panel on Climate Change.Cambridge, UK: Cambridge University Press.

Dang QL, Lieffers VJ. 1989. Climate and annual ring growth of black spruce insome Alberta peatlands. Canadian Journal of Botany 67: 1885–1889.

Dewar RC, Tarvainen L, Parker K, Wallin G, McMurtrie RE. 2012. Whydoes leaf nitrogen decline within tree canopies less rapidly than light? Anexplanation from optimization subject to a lower bound on leaf mass perarea. Tree Physiology 32: 520–534.

Dillaway DN, Kruger EL. 2010. Thermal acclimation of photosynthesis: a com-parison of boreal and temperate tree species along a latitudinal transect.Plant, Cell and Environment 33: 888–899.

Dreyer E, Le Roux X, Montpied P, Daudet F, Masson F. 2001. Temperatureresponse of leaf photosynthetic capacity in seedlings from seven temperatetree species. Tree Physiology 21: 223–232.

Fløistad IS, Granhus A. 2010. Bud break and spring frost hardiness in Piceaabies seedling in response to photoperiod and temperature treatments.Canadian Journal of Forest Research 40: 968–976.

Girardin MP, Raulier F, Bernier PY, Tardif JC. 2008. Response of treegrowth to a changing climate in boreal central Canada: a comparison of em-pirical, process-based, and hybrid modelling approaches. EcologicalModelling 213: 209–228.

Goodine GK, Lavigne MB, Krasowski MJ. 2008. Springtime resumptionof photosynthesis in balsam fir (Abies balsamea). Tree Physiology 28:1069–1076.

Goulden ML, Daube BC, Fan S-M, et al. 1997. Physiological response of ablack spruce forest to weather. Journal of Geophysical Research 102:28987–28996.

Grassi G, Vicinelli E, Ponti F, Cantoni L, Magnani F. 2005. Seasonaland interannual variability of photosynthetic capacity in relation to leaf ni-trogen in a deciduous forest plantation in northern Italy. Tree Physiology 25:349–360.

Greenway KJ, MacDonald SE, Lieffers VJ. 1992. Is long-lived foliage 553in Picea marina an adaption to nutrient-poor conditions. Oecologia 91:184–191.

Gu LH, Pallardy SG, Tu K, Law BE, Wullschleger SD. 2010. Reliableestimation of biochemical parameters from C3 leaf photosynthesis-intercel-lular carbon dioxide response curves. Plant, Cell and Environment 33:1852–1874.

Gunderson CA, O’Hara KH, Campion CM, Walker AV, Edwards NT.

2010. Thermal plasticity of photosynthesis: the role of acclimation in forestresponses to a warming climate. Global Change Biology 16: 2272–2286.

Hall M, Rantfors M, Slaney M, Linder S, Wallin G. 2009. Carbon dioxide ex-change of buds and developing shoots of boreal Norway spruce exposed toelevated or ambient CO2 concentration and temperature in whole-tree cham-bers. Tree Physiology 29: 467–481.

Hanson PJ, Amthor JS, Wullschleger SD, et al. 2004. Oak forest carbon andwater simulations: model intercomparisons and evaluations against indepen-dent data. Ecological Monographs 74: 443–489.

Hanson PJ, Wullschleger SD, Norby RJ, Tschaplinski TJ, Gunderson CA.

2005. Importance of changing CO2, temperature, precipitation, and ozoneon carbon and water cycles of an upland-oak forest: incorporatingexperimental results into model simulations. Global Change Biology 11:1402–1423.

Harley PC, Thomas RB, Reynolds JF, Strain BR. 1992. Modelling photosyn-thesis of cotton growth in elevated CO2. Plant, Cell and Environment 15:271–282.

Hebert F, Thiffault N, Munson AD. 2010. Field photosynthesis measurementson black spruce (Picea mariana): does needle age matter? Communicationin Soil Science and Plant Analysis 42: 2738–2750.

Hikosaka K, Nabeshima E, Hiura T. 2007. Seasonal changes in the tempera-ture response of photosynthesis in canopy leaves of Quercus crispula in acool-temperate forest. Tree Physiology 27: 1035–1041.

Jensen AM, Warren JM, Hanson PJ, Childs J, Wullschleger SD. 2015.

SPRUCE S1 Bog Pretreatment Photosynthesis and Respiration for BlackSpruce: 2010–2013. Oak Ridge, TN, USA: Carbon Dioxide InformationAnalysis Center, Oak Ridge National Laboratory, US Department ofEnergy. doi:10.3334/CDIAC/spruce.007.

Khaembah EN, Irving LJ, Thom ER, Faville MJ, Easton HS, Matthew C.

2013. Leaf Rubisco turnover in a perennial ryegrass (Lolium perenne L.)mapping population: Genetic variation, identification of associated QTL,and correlation with plant morphology and yield. Journal of ExperimentalBotany 64: 1305–1316.

Kruse J, Hopmans P, Adams MA. 2008. Temperature responses are a windowto the physiology of dark respiration: differences between CO2 release andO2 reduction shed light on energy conservation. Plant, Cell andEnvironment 31: 901–914.

Leuning R. 2002. Temperature dependence of two parameters in a photosynthe-sis model. Plant, Cell and Environment 25: 1205–1210.

Lin Y-S, Medlyn BE, Kauwe MGD, Ellsworth DS. 2013.

Biochemical photosynthetic responses to temperature: How do inter-specific differences compare with seasonal shifts? Tree Physiology33: 793–806.

Linder S, Troeng E. 1981. The seasonal course of respiration and photosynthe-sis in strobili of Scots pine. Forest Science 27: 267–276.

Machado J-L, Reich PB. 2006. Dark respiration rate increases with plant size insaplings of three temperate tree species despite decreasing tissue nitrogenand nonstructural carbohydrates. Tree Physiology 26: 915–923.

Makela A, Hari P, Berninger F, Hanninen H, Nikinmaa E. 2004.

Acclimation of photosynthetic capacity in Scots pine to the annual cycle oftemperature. Tree Physiology 24: 369–376.

Martindale W, Leegood RC. 1997. Acclimation of photosynthesis to low tem-perature in Spinacia oleracea L. II. Effects of nitrogen supply. Journal ofExperimental Botany 48: 1873–1880.

Medlyn BE, Loustau D, Delzon S. 2002a. Temperature response of parametersof a biochemically based model of photosynthesis. I. Seasonal changes inmature maritime pine (Pinus pinaster Ait.). Plant, Cell and Environment25: 1155–1165.

Medlyn BE, Dreyer E, Ellsworth D, et al. 2002b. Temperature response of pa-rameters of a biochemically based model of photosynthesis. II. A review ofexperimental data. Plant, Cell and Environment 25: 1167–1179.

Monson RK, Sparks JP, Rosenstiel TN, et al. 2005. Climatic influences on netecosystem CO2 exchange during the transition from wintertime carbonsource to springtime carbon sink in a high-elevation, subalpine forest.Oecologia 146: 130–147.

Oquist G, Huner NPA. 2003. Photosynthesis of overwintering evergreen plants.Annual Reviews of Plant Biology 54: 329–355.

Niinemets U. 2002. Stomatal conductance along does not explain the decline infoliar photosynthetic rates with increasing tree age and size in Picea abiesand Pinus sylvestris. Tree Physiology 22: 515–535.

Niinemets U, Kull O, Tenhunen JD. 2004. Within-canopy variation in the rateof development of photosynthetic capacity is proportional to integratedquantum flux density in temperate deciduous trees. Plant, Cell andEnvironment 27: 293–313.

Rasband WS. 1997–2012. ImageJ. Bethesda, MD: National Institutes of Health.Reich PB, Walters MB, Tjoelker MG, Vanderklein D. 1998. Photosynthesis

and respiration rates depend on leaf and root morphology and nitrogen con-centration in nine boreal trees species differing in relative growth rate.Functional Ecology 12: 395–405.

Salmon Y, Barnard RL, Buchmann N. 2011. Ontogeny and leaf gas exchangemediate the carbon isotopic signature of herbaceous plants. Plant, Cell andEnvironment 34: 465–479.

Sevanto S, Suni T, Pumpanen J, et al. 2006. Wintertime photosyn-thesis and water uptake in a boreal forest. Tree Physiology 26:749–757.

Sebestyen SD, Dorrance C, Olson DM, et al. 2011. Long-term monitoring sitesand trends at the Marcell Experiment Forest. In: RK Kolka, SD Sebestyen,ES Verry, KN Brooks. eds. Peatland biogeochemistry and watershed hy-drology at the Marcell Experimental Forest. Boca Raton, FL: CRC Press,15–72.

Smith NG, Dukes JF. 2013. Plant respiration and photosynthesis in global-scalemodels: incorporating acclimation to temperature and CO2. Global ChangeBiology 19: 45–63.



Stinziano JR, Way DA. 2014. Combined effects of rising [CO2] andtemperature on boreal forest: growth, physiology and limitations. Botany92: 425–436.

Sutinen S, Partanen J, Vihera-Aarnio A, Hakkinen R. 2012. Developmentand growth of primordial shoots in Norway spruce buds before visible budburst in relation to time and temperature in the field. Tree Physiology 32:987–997.

Tanja S, Berninger F, Vesala T, et al. 2003. Air temperature triggers the recov-ery of evergreen boreal forest photosynthesis in spring. Global ChangeBiology 9: 1410–1426.

Teskey RO, Grier CC, Hinckley TM. 1984. Change in photosynthesis and wa-ter relations with age and season in Abies amabilis. Canadian Journal ofForest Research 14: 77–84.

Tjoelker MG, Oleksyn J, Reich PB. 1998. Temperature and ontogeny mediategrowth response to elevated CO2 in seedlings of five boreal tree species.New Phytologist 140: 197–210.

Troeng E, Linder S. 1982. Gas-exchange in a 20-year-old stand of Scots pine. 1.Net photosynthesis of current- and one-year-old shoots within and betweenseasons. Physiologia Plantarum 54: 7–14.

Viereck LA, Johnston WF. 1990. Black spruce. In: RM Burns, BH Honkala,eds. Silvics of North America: 1. Conifers. Washington, DC: USDepartment of Agriculture, Forest Service, http://www.na.fs.fed.us/spfo/pubs/silvics_manual/Volume_1/picea/mariana.htm.

Way DA, Sage RF. 2008a. Thermal acclimation of photosynthesis inblack spruce Picea mariana (Mill.) BSP. Plant, Cell and Environment 31:1250–1262.

Way DA, Sage RF. 2008b. Elevated growth temperatures reduce the carbongain of black spruce [Picea mariana (Mill.) B.S.P.] Global Change Biology14: 624–636.

Way DA, Yamori W. 2014. Thermal acclimation of photosynthesis: on the im-portance of adjusting our definitions and accounting for thermal acclimationof respiration. Photosynthesis Research 119: 89–100.

Wullschleger SD. 1993. Biochemical limitations to carbon assimilation in C3plants—a retrospective analysis of the A/Ci curves from 109 species.Journal of Experimental Botany 44: 907–920.

Yamori W, Hikosaka K, Way DA. 2014. Temperature response of photosyn-thesis in C3, C4 and CAM plants: temperature acclimation and temperatureadaption. Photosynthesis Research 119: 101–117.



http://www.na.fs.fed.us/spfo/pubs/silvics_manual/Volume_1/picea/mariana.htm

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Needle age and season influence photosynthetic temperature