Diurnal and seasonal variation in light and dark respiration in field ...

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Tree Physiology 35, 840–849doi:10.1093/treephys/tpv065

Diurnal and seasonal variation in light and dark respiration in field-grown Eucalyptus pauciflora

Danielle A. Way1,2,6, Chris Holly3, Dan Bruhn4, Marilyn C. Ball3 and Owen K. Atkin3,5

1Department of Biology, University of Western Ontario, London, ON, Canada N6A 5B7; 2Nicholas School of the Environment, Duke University, Durham, NC 27708, USA; 3Division of Plant Sciences, Research School of Biology, Building 46, The Australian National University, Canberra, ACT 2601, Australia; 4Department of Environment, Earth and Ecosystems, The Open University, Milton Keynes MK7 6AA, UK; 5ARC Centre of Excellence in Plant Energy Biology, Research School of Biology, Building 134, The Australian National University, Canberra, ACT 2601, Australia; 6Corresponding author ([email protected])

Received March 20, 2015; accepted June 10, 2015; published online August 6, 2015; handling Editor David Tissue

Respiration from vegetation is a substantial part of the global carbon cycle and the responses of plant respiration to daily and seasonal fluctuations in temperature and light must be incorporated in models of terrestrial respiration to accurately predict these CO2 fluxes. We investigated how leaf respiration (R) responded to changes in leaf temperature (Tleaf) and irradiance in field-grown saplings of an evergreen tree (Eucalyptus pauciflora Sieb. ex Spreng). Seasonal shifts in the thermal sensitivity of leaf R in the dark (Rdark) and in the light (Rlight) were assessed by allowing Tleaf to vary over the day in field-grown leaves over a year. The Q10 of R (i.e., the relative increase in R for a 10 °C increase in Tleaf) was similar for Rlight and Rdark and had a value of ∼2.5; there was little seasonal change in the Q10 of either Rlight or Rdark, indicating that we may be able to use similar functions to model short-term temperature responses of R in the dark and in the light. Overall, rates of Rlight were lower than those of Rdark, and the ratio of Rlight/Rdark tended to increase with rising Tleaf, such that light suppression of R was reduced at high Tleaf values, in contrast to earlier work with this species. Our results suggest we cannot assume that Rlight/Rdark decreases with increasing Tleaf on daily timescales, and highlights the need for a better mechanistic understanding of what regulates light suppression of R in leaves.

Keywords: acclimation, day respiration, irradiance, leaves, snow gum, temperature.

Introduction

Anthropogenic disturbances, including fossil fuel emissions and land use change, have altered the global climate cycle, and are currently responsible for adding 9 GT carbon (C) year−1 to the atmosphere ( Canadell et al. 2007, Ciais et al. 2013). While this has clear implications for the Earth’s climate system, these C fluxes are still much smaller than those from terrestrial vegeta-tion. The CO2 uptake by land plants fixes 120 GT C year−1, and 60 GT C are emitted annually through plant respiration (R) ( Prentice et al. 2001), of which approximately half comes from leaves ( Atkin et al. 2007). Thus, relatively small changes in plant photosynthesis and R can have impacts on the global C cycle that are on the scale of anthropogenic disturbances ( Cox et al. 2000, Booth et al. 2012, Huntingford et al. 2013). Our ability

to model future climate change therefore depends on our accu-racy in predicting C fluxes from terrestrial vegetation, and how these fluxes vary with changes in the environment ( Heskel et al. 2013, Smith and Dukes 2013).

Rates of leaf R are strongly affected by light: over the course of a day, leaf respiration in the dark (Rdark) is usually higher than corresponding rates of non-photorespiratory mitochondrial CO2 release in the light (i.e., Rlight; Villar et al. 1994, Atkin et al. 1998, Way and Sage 2008, Ayub et al. 2011, Crous et al. 2012). However, the degree to which light suppresses leaf R varies substantially: Rlight can actually be greater than Rdark ( Hurry et al. 2005), but in other studies, light was found to suppress leaf R by up to 77% ( Atkin et al. 2006, Zaragoza-Castells et al. 2007). Failure to account for variations in the effect of light on leaf R

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can lead to large over-estimates of daily R in individual leaves, branches and whole ecosystems, with concomitant effects on calculated gross primary productivity ( Wohlfahrt et al. 2005, Wingate et al. 2007, Bruhn et al. 2011). Despite the importance of R, we know little of how diel and seasonal variations in air and leaf temperature (Tair and Tleaf) impact the degree of light sup-pression of leaf R and/or rates of Rlight per se.

Diel variations in Tleaf can have profound effects on rates of respiratory CO2 release, as both Rdark and Rlight are sensitive to short-term (scale of minutes) changes in Tleaf ( Wager 1941, Holmgren and Jarvis 1967, Atkin and Tjoelker 2003, Shapiro et al. 2004, Bruhn et al. 2008, Kruse et al. 2011, Griffin and Turnbull 2013). Averaged across a broad range of measurement Tleafs, the Q10 of Rdark (the relative change in respiration rate for a 10 °C increase in Tleaf) is often ∼2.0 ( Atkin et al. 2005a), although it can range from 1.1 to 4.2 ( Azcón-Bieto and Osmond 1983, Tjoelker et al. 2001). For Rlight, Q10 values are similarly variable for plants grown under controlled environment condi-tions, ranging from 1.0 to 4.9 ( Atkin et al. 2005b). While there is growing evidence that Rlight in leaves is influenced by factors such as growth irradiance, growth temperature, drought and atmospheric CO2 concentration ( Shapiro et al. 2004, Atkin et al. 2006, Zaragoza et al. 2007, Way and Sage 2008, Ayub et al. 2011, Crous et al. 2012), the extent to which the Q10 of Rlight varies seasonally under field conditions is not known.

Of particular interest is how sustained changes in growth tem-perature affect leaf R. While leaf R is sensitive to daily changes in Tleaf, it is also affected by changes in the leaf’s thermal envi-ronment over weeks, months and years ( Atkin et al. 2000a, Bruhn et al. 2007, 2008), such that the Q10 of R is reduced and/or the basal rate of R is suppressed in leaves that experi-ence warmer conditions ( Atkin and Tjoelker 2003, Way and Sage 2008, Slot and Kitajima 2015). While this thermal accli-mation of R to prevailing growth temperatures is common, it is not universal ( Atkin et al. 2006, Slot and Kitajima 2015). Reli-able temperature response functions of R on both short (i.e., diurnal) and long (i.e., seasonal) timescales are therefore key to modeling current and future R dynamics ( Vanderwel et al. 2015, Way et al. 2015).

Although there has been growing interest in understanding how Rdark and Rlight respond to temperature, the degree to which R varies over daily, weekly and seasonal temperature variations is unclear, especially in field-grown plants. Moreover, Rlight is often derived from measurements of Rdark, by assuming that Rlight is some constant fraction of Rdark ( Lloyd et al. 2009, Malhi et al. 2015), but the accuracy and generality of this approach across daily leaf temperature changes and seasonal variation in ambi-ent temperature has been questioned ( Way and Yamori 2014). The Q10 of Rlight can be lower than that of Rdark ( Atkin et al. 2000b, 2006, Bruhn et al. 2002), which implies that the ratio of Rlight/Rdark is not constant, but rather will decrease as Tleaf rises ( Atkin et al. 2006). If the Q10s of Rlight and Rdark also vary over

daily or seasonal timescales, this must be included in models that predict leaf R responses to climate.

We analyzed diurnal and seasonal temperature responses in Rlight and Rdark of Eucalyptus pauciflora Sieb. ex Spreng (snow gum) trees grown in the field. We hypothesized that: (i) Rlight would be lower than Rdark, on both daily and seasonal time scales; (ii) the Q10 of Rlight would be lower than that of Rdark, but the Q10 of each parameter would vary little across the seasons; and (iii) the degree of light inhibition of respiration would there-fore increase at higher Tleaf, generating a decline in the ratio of Rlight to Rdark with short-term increases in Tleaf.

Materials and methods

The site and experimental set-up are described in Atkin et al. (2000a), where the authors analyzed seasonal responses of Rdark and leaf non-structural carbohydrate concentrations to diel temperature changes in April, October, November and Decem-ber in these same trees. Here, we build on this dataset by adding new data on Rdark from the same leaves in February and March, as well as measurements of Rlight taken during the campaigns, to investigate differences in how Rlight and Rdark respond to daily and seasonal temperature variation. Seeds of E. pauciflora were col-lected from trees in Orroral Valley, Namadgi National Park, ACT in southeastern Australia (35°38′S, 148°57′E), vernalized at 4 °C for 6 weeks and germinated on seed trays in greenhouses at the Australian National University in Canberra, Australia in November 1995. Seedlings were transferred to 20 cm potting tubes, fertilized with 10% Hoagland’s solution and moved out-side during the summer until March 1996. When the seedlings were 0.1 m tall, they were planted into a grassland plot in the Gudgenby Valley (35°45′S, 148°59′E), with each plot sur-rounded by a 1 m tall open-weave chicken wire fence (that cast minimal shade) to prevent mammalian herbivory. Randomly assigned seedlings were planted 50 cm apart in six blocks, with six seedlings per block; each block was moved regularly to pre-vent excessive grass growth.

The Tair at the site was measured 1 m above the ground at 10-s intervals with shaded copper–constantan thermocouples referenced against Pt-100 platinum resistance thermometers; data were averaged into 30-min blocks and stored in a data log-ger (Datataker 100F; Data Electronics, Melbourne, VIC, Australia). Photosynthetically active radiation (PAR, 400–700 nm) was assessed with a horizontally mounted quantum sensor (LI-COR Inc., Lincoln, NE, USA) in full sun; PAR values were measured every 10 s and a 30-min average recorded on the same data logger as Tair.

Gas exchange measurements began in the summer of February 1997, with replicate campaigns made in March, April, October, November and December of the same year. Reliable measurements of CO2 exchange in the light were not possible in the winter months between May and September due to very

Respiration responses to temperature and irradiance 841


Tree Physiology Volume 35, 2015

low stomatal conductance rates. One tree in each of four blocks was measured repeatedly over the experiment (i.e., only four of the six planted blocks were measured). All measured leaves were fully expanded and had developed the previous spring (e.g., October 1996), though leaves from March and April exhibited higher specific leaf area than leaves from later sam-pling periods, indicating a continued development of leaf den-sity (data not shown). Diurnal and seasonal changes in Rlight were estimated on leaves using a modified Laisk (1977) method, as per Kirschbaum and Farquhar (1984). Responses of net CO2 assimilation rates (Anet) to changes in inter-cellular CO2 concentrations (Anet−Ci curves) were measured at saturat-ing light (1000 µmol photons m−2 s−1) with a portable photo-synthesis system (Licor-6400, LI-COR Inc.). The measurements concentrated on the initial slope of the Anet−Ci curve, with cuvette CO2 concentrations starting at 100 µmol mol−1 and dropping in 10–20 µmol mol−1 steps to 0 µmol mol−1. The cuvette block temperature was set to the prevailing Tair at the time of measurement and Tleaf was assessed by the thermo-couple in the gas exchange cuvette, with the same leaf being measured four to six times over a single day; leaves were other-wise allowed to experience ambient conditions over the day. Mean cuvette relative humidity ranged from 43 to 65% between measurement months.

Rlight could be assessed using the gas exchange data and val-ues for the temperature response of the CO2 compensation point in the absence of mitochondrial respiration (Γ*) from the same species (see Figure 1 for details), as in Kirschbaum and Farquhar (1984). The Γ* values at Tleaf (Γ*T) were calculated as:

Γ Γ* * [ . ( )] [ . ( ) ]T leaf leaf= + × − + × −2520 188 25 0 0036 25T T (1)

where Tleaf is in °C, assuming a Γ* value at 25 °C (Γ*25) of 43.1 ppm previously reported for E. pauciflora ( Atkin et al. 2000b), and temperature-correcting as per Brooks and Farquhar (1985). Because the choice of Γ*25 and its temperature correc-tion equation will influence estimates of Rlight using this approach, we compared our values for Rlight with those generated using the Γ*25 and thermal response of Γ* from tobacco in Bernacchi et al. (2001). To account for potential CO2 diffusion through the Licor-6400 gaskets, we used atmospheric CO2 concentrations of 350 µmol mol−1 (ambient values in 1997) and the equations in Bruhn et al. (2002) to diffusion correct the measurements of Anet.

Estimates of Rlight were made the day prior to measurements of diurnal variation in Rdark on the same leaves (see Atkin et al. 2000a for details and Rdark results for April–December). As with Rlight, Rdark was measured at various Tleaf values as Tair fluctuated during the day, by covering the leaves with a black cloth for 30 min before the Rdark measurement to prevent a post-illumina-tion burst of CO2 ( Azcón-Bieto and Osmond 1983). At the end of each day, measured leaves were harvested, placed in sealed

containers on ice and taken to Canberra where the leaf area (using a LI-3100, LI-COR Inc.) was assessed within ∼24 h.

All analyses of rates of R were performed on log-transformed data. The Rdark and Rlight data were both analyzed with analysis of covariances (ANCOVAs) using Tleaf as the co-variate and accounting for measurement month. In contrast, we restricted the comparison of Rdark with Rlight to data where both Rdark and Rlight were measured within a common temperature range in a given month (from 15 to 35 °C over the year) to account for lower measurement temperatures of Rdark than of Rlight. Differ-ences between Rdark and Rlight were analyzed with an ANCOVA using Tleaf as the co-variate, and accounting for measurement month and the type of R (Rdark or Rlight).

The Q10 for Rdark and Rlight of each individual leaf in each month was derived as

Q k10

1010= (2)

where k is the slope of the log-transformed respiration rate plot-ted against Tleaf ( Atkin et al. 2005a). While O’Sullivan et al. (2013) recently demonstrated that a polynomial function better captures the thermal response of R for an extensive set of data than does a simple Q10 approach, our dataset is not of sufficient temperature-interval resolution or over a wide enough range to generate accurate parameter estimates for a polynomial fit to our data. The Q10 values of Rdark and Rlight were both analyzed with one-way ANOVAs for month effects. The difference between the

842 Way et al.

Figure 1. Estimation of the leaf respiration rate in the light (Rlight; i.e., non-photorespiratory mitochondrial CO2 release) based on a modified version of the Laisk method from Kirschbaum and Farquhar (1984) on E. pauciflora. Net CO2 assimilation rates (Anet) were measured against changes in leaf inter-cellular CO2 concentrations at multiple leaf tem-peratures over a day [shown here for 21 °C (filled symbols) and 32 °C (empty symbols) for the same leaf measured in February]. The CO2 compensation point in the absence of mitochondrial respiration (Γ*) measured on the same species at various temperatures from Atkin et al. (2000b) was used (vertical solid for 21 °C and vertical dashed lines for 32 °C) to determine the intersection point, which represents Rlight (hori-zontal solid line and filled symbol on y-axis for 21 °C, and horizontal dashed lines and empty symbol on y-axis for 32 °C).



Q10 of Rlight and Rdark was analyzed with a two-way ANOVA using respiration type (Rlight versus Rdark) and month as classes. Signifi-cant effects were evaluated post hoc with Tukey’s honest signifi-cant difference tests (JMP Pro 11, SAS Institute, Cary, NC, USA).

Relationships between recent climate and respiration param-eters were assessed by evaluating the relationship between R and the mean Tair in windows of time ranging from 1 to 10 days before R was measured. The mean Tair of the 48 h preceding the measurements consistently had the greatest explanatory power (i.e., the highest r2 values), and was therefore used throughout the analyses.

Results

Weather patterns were stable across the two measurement days of each month’s campaign, such that there were no significant changes in atmospheric pressure or cloud cover (that would result in precipitation). All measurements were made on clear days, with maximum, midday PAR of >1900 µmol pho-tons m−2 s−1 (except for April, when maximum PAR was >1400 µmol photons m−2 s−1). The minimum Tair on the mea-surement days (from 0:01 to 24:00 h) varied from 0.3 to 8.8 °C and the daily maximum Tair ranged from 14.6 to 24.6 °C (Table 1). The mean Tair over the measurement day and the 2-day period prior to the measurements ranged from 8.9 to 16.3 °C and from 7.8 to 17.8 °C, respectively (Table 1). Over the course of each measurement day, Tleaf was low in the morning, peaking in the afternoon and decreasing in the evening, but the values reached on a given day varied throughout the year (Figure 2a). Over the year, the minimum Tleaf was 3.2 °C and the maximum Tleaf was 40.2 °C; the range of measurement Tleaf in any 1 month varied from 12 °C in October to over 27 °C in February, generat-ing an enormous range of natural variation in temperature over the dataset.

Rates of Rdark followed an exponential response with increas-ing short-term changes in Tleaf (Figure 3). The only exception was for a subset of the measurements in November, where there was a distinct minimum in Rdark near Tleaf = 12 °C, such that Rdark was negatively correlated with Tleaf below 12 °C and

positively correlated with Tleaf above 12 °C (see Figure S1 avail-able as Supplementary Data at Tree Physiology Online). This same phenomenon was reported in Atkin et al. (2000a), and was only seen in the first measurements of the day, taken before sunrise when air temperatures were low. These anomalous points from the first two morning measurements on each tree in November (when Tleaf < 12 °C) were therefore excluded from the analyses.

Values and temperature responses of Rlight were similar when estimated with the Γ*25 values and temperature responses from either E. pauciflora in Atkin et al. (2000b) or from Nicotiana tabacum in Bernacchi et al. (2001) (see Figure S2 available as Supplementary Data at Tree Physiology Online), and we there-fore used Rlight derived from the species-specific Γ* values. Rates of Rlight followed a similar daily pattern to Tleaf, but maximum Rlight was higher for a given time of day in February, March and November than in other months (Figure 2b). Rlight was signifi-cantly correlated with Tleaf and varied between months, showing the lowest rates in December and the highest in February ( Figures 2b and 3, Table 2). The response of Rlight to changes in Tleaf was similar across the measurement months (Figure 3, Table 2), in agreement with the lack of a change in the Q10 of Rlight across the months (P = 0.21). The Q10 of Rlight was not linked to variation in recent Tair (P > 0.1; Figure 4).


Table 1. Environmental conditions on the day of the measurement cam-paigns (from 0:01 to 24:00 h) or the 48 h before the measurements began in each month. PAR, photosynthetically active radiation; Tair, air temperature.

Month Maximum PAR (µmol m−2 s−1)

Mean Tair (°C)

Minimum Tair (°C)

Maximum Tair (°C)

Mean Tair (°C) of previous 48 h

February 2075 16.3 8.6 23.7 17.8March 2008 16.1 8.8 24.6 15.1April 1420 9.3 0.3 20.1 7.8October 1930 8.9 3.8 14.6 8.5November 2093 13.9 1.5 22.2 14.5December 2160 13.5 6.8 19.3 16.4

Figure 2. Daily courses of (a) leaf temperature and (b) respiration rates in the light (Rlight) measured over 6 months in a year. Means ± SE, n = 3–4 trees.


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As was the case for Rlight, rates of Rdark shifted over the sea-sons, with the temperature response of Rdark varying over the year (Figure 3, Table 2). While the Q10 for Rdark was thus not constant across the year (P < 0.05), this result was only due to significantly higher Q10 values in December than in November

(P < 0.05). Moreover, the Q10 of Rdark did not vary significantly with ambient Tair in the field (P = 0.5, Figure 4).

Because both Rdark and Rlight were measured on the same leaves over a relatively short time period (<36 h), we used our data to investigate the relationship between Rlight and Rdark over daily and seasonal time scales when ambient Tair fluctuates. Rates of Rlight were usually measured at a higher range of Tleaf than those where Rdark was assessed in any given month ( Figure 3), so when comparing the temperature responses of Rlight and Rdark, we restricted our analysis of their relative values to a common Tleaf range in each month (see Figure S3 available as Supplementary Data at Tree Physiology Online). When assessed on the same leaves over these common ranges of Tleaf, Rlight was significantly lower than Rdark (Table 3). Mean values of Rdark and Rlight were 2.76 and 2.49 µmol m−2 s−1 at mean Tleaf values of 21.7 and 24.3 °C, respectively; thus, despite leaves being warmer when measuring Rlight, average rates of Rlight were lower than Rdark. When the monthly Q10 values for Rlight and Rdark were compared across the season, there was no difference in

844 Way et al.

Figure 3. Responses of leaf respiration rates in the light (Rlight, empty circles, dashed line) and in the dark (Rdark, filled circles, solid line) versus short-term changes in leaf temperature, measured over 6 months in a year. Points represent individual measurements from three to four trees. The April, October, November and December Rdark data are taken from Atkin et al. (2000a).

Table 2. ANCOVA results for monthly changes in respiration in the dark (Rdark) and in the light (Rlight) in response to variation in leaf temperature (Tleaf) across a year. The overall model for Rdark explained 85% of the data (<0.0001) and for Rlight, the overall model explained 78% of the data (P < 0.0001). Bold values indicate P < 0.05.

df Sum of squares F ratio P-value

Rdark

Tleaf 1 5.24 337.8 <0.0001 Month 5 0.78 10.0 <0.0001 Tleaf × month 5 0.35 4.5 <0.001

Rlight

Tleaf 1 2.47 102.4 <0.0001 Month 5 0.58 4.8 0.0006 Tleaf × month 5 0.12 0.98 0.44




the Q10 values (mean Q10 of 2.45 and 2.55 for Rlight and Rdark, respectively; P = 0.07, Figure 4).

We fitted exponential functions to the monthly temperature responses of Rdark and Rlight for the range of Tleaf where both Rdark and Rlight had been assessed within a given month (see Figure S3 available as Supplementary Data at Tree Physiology Online). We then estimated the ratio of Rlight to Rdark (Rlight/Rdark) across the range of Tleaf values used to derive the data points. The Rlight/Rdark was <1 (i.e., Rlight < Rdark), but the degree of light inhibition var-ied month to month and with Tleaf (Figure 5). Averaged across the six measurement months, respiration was suppressed by 25–29% by light at a Tleaf of 25 °C [Rlight/Rdark = 0.71 ± 0.08 (mean ± SE)], consistent with the ∼30% suppression of respira-tion often reported in the literature (e.g., Crous et al. 2012, Weerasinghe et al. 2014). However, the response of Rlight/Rdark to increasing Tleaf was not consistent over the year, although this ratio was usually positively correlated with Tleaf (Figure 5).

Discussion

We set out to evaluate the effects of changes in light and tem-perature on leaf respiration. Regarding our first hypothesis, we found that Rlight was generally lower than Rdark for a given Tleaf, across both diurnal and seasonal fluctuations in Tair. However, the Q10 of Rlight and Rdark did not differ, and the Q10 values of both parameters were relatively constant over the year. Despite the overall similarity in the Q10 values of Rlight and Rdark, the ratio of Rlight/Rdark was not constant, but varied over the year and, within each month, with Tleaf.

Short-term exposure to light usually suppresses leaf R, such that Rlight is lower than Rdark ( Brooks and Farquhar 1985, Villar et al. 1994, Atkin et al. 2006, Weerasinghe et al. 2014), but studies have also found no effect of light on R (e.g., Loreto et al. 1999) and cases where Rlight is greater than Rdark ( Hurry et al. 1996, Atkin et al. 2006, Griffin and Turnbull 2013). Although the exact mechanism responsible for the light suppression of R remains unclear, it may involve the inhibition of glycolytic or Krebs cycle enzymes in illuminated leaves via high NAD(P)H/NAD(P)+ ratios ( Atkin et al. 2000c, Igamberdiev and Gardeström 2003, Tcherkez et al. 2005, 2008). Across ecologically realistic varia-tion in Tleaf on both daily and seasonal timescales, we found that Rlight was indeed lower than Rdark in E. pauciflora. Moreover, when assessed at a Tleaf of 25 °C, seasonally averaged rates of Rlight were ∼70% of Rdark, in line with the conclusion that light sup-presses R by ∼30% in many studies that measured Rlight/Rdark at a Tleaf near 25 °C ( Crous et al. 2012, Weerasinghe et al. 2014). As well, our daily and monthly patterns for Rlight were unaffected by whether we used the temperature response of Γ* from E. pauciflora or the more commonly used tobacco function, implying that our results and the technique used to derive Rlight are robust.


Table 3. ANCOVA results for monthly changes in respiration (Rdark and Rlight) to variation in leaf temperature (Tleaf) from leaves measured at a common Tleaf range within each month. The overall model explained 82% of the data (P < 0.0001). Rtype indicates whether respiration was Rdark or Rlight. Bold values indicate P < 0.05.

df Sum of squares F ratio P-value

Tleaf 1 3.08 200.2 <0.0001Rtype 1 0.32 21.1 <0.0001Month 5 0.92 12.1 <0.0001Tleaf × Rtype 1 0.046 3.0 0.09Tleaf × month 5 0.16 2.0 0.15Rtype × month 1 0.56 7.2 <0.0001Tleaf × Rtype × month 5 0.070 0.9 0.048

Figure 5. Modeled temperature sensitivity of the ratio of leaf respiration rates in the light to leaf respiration rates in the dark (Rlight/Rdark) mea-sured over 6 months across a year. Ratios derived for 5 °C increments from fits to the Rdark and Rlight responses to short-term changes in leaf temperature (Tleaf). Values are based on data restricted to a range of Tleaf where both parameters were measured within a given month (see Figure S3 available as Supplementary Data at Tree Physiology Online).

Figure 4. The temperature sensitivity (Q10) of leaf respiration rates in the dark (Rdark, filled symbols) and in the light (Rlight, empty symbols) plotted against the mean air temperature (Tair) of the 2 days preceding the measurements. Values are based on measurements from the range of Tleaf where both parameters were measured within a given month (see Figure S3 available as Supplementary Data at Tree Physiology Online). Means ± SE, n = 4 for Rdark, n = 3–4 for Rlight.






Although Rlight was lower than Rdark, the degree of light sup-pression of R was highly variable. We initially hypothesized that light suppression of R would be greatest during the hottest parts of the day, as a warmer Tleaf promotes higher photorespiration rates, which have been correlated with a reduction in Rlight/Rdark in E. pauciflora grown under controlled conditions ( Atkin et al. 2000b). Instead, when both Rlight and Rdark were assessed on these field-grown trees on the same leaf at a common set of Tleaf values, light suppression of R tended to decrease as Tleaf increased over a day, such that Rlight/Rdark ranged from 0.35 to just less than unity. Previous work has shown that Rlight/Rdark can increase (e.g., Way and Sage 2008, Griffin and Turnbull 2013) or decrease (e.g., Atkin et al. 2000b, 2006) as Tleaf rises ( Way and Yamori 2014), but our current study is the first (to our knowledge) to find that the ratio of Rlight/Rdark to Tleaf increases in some instances and decreases in others (e.g., November) in the same experimental plants. While photorespiratory conditions have been postulated to enhance light suppression of R, Tcherkez et al. (2008) suggested that high photorespiration rates could increase demand for tricarboxylic acid (TCA) cycle intermediates, thus stimulating Rlight, consistent with our results. Consistent with this idea and the results we present here, recent studies using evergreen and herbaceous plants have found that light inhibition of R is lowest in plants with high rates of photo-respiration ( Way and Sage 2008, Ayub et al. 2011, Crous et al. 2012, Griffin and Turnbull 2013). While we cannot determine the mechanism underpinning the temperature sensitivity of light suppression of R, our data strongly suggest we cannot assume that Rlight/Rdark decreases with increasing Tleaf on daily timescales, nor should Rlight be necessarily modeled as a constant fraction of Rdark. More work is clearly needed to determine the pattern of how light suppression of R responds to short-term changes in temperature ( Way and Yamori 2014), especially in field-grown vegetation.

With the exception of data from November, our results show that Rlight/Rdark increased with Tleaf when rates of R were mea-sured on the same leaves at comparable Tleaf values (Figure 5). In contrast, we also found that there was no difference in the Q10 of Rlight and Rdark (Figure 4). On first inspection, these results appear incompatible, as constancy of Q10 values would imply that Rlight/Rdark should remain constant with increasing Tleaf. One explanation for the apparent discrepancy between these obser-vations is the fact that the Q10 values were derived separately for each tree from measurements of R made over all available Tleaf values, with mean Q10 monthly values of Rlight and Rdark then being calculated using these individual tree values. In contrast, to assess patterns in Rlight/Rdark, it was necessary to use the monthly Rlight–Tleaf and Rdark–Tleaf relationships (generated by combining data from all trees measured in a given month) to calculate Rlight/Rdark values at each Tleaf. The latter approach pro-vides a robust indicator of how mean values of Rlight/Rdark vary with Tleaf, but do not provide insights into whether the same

pattern is held within individual trees. The absence of significant differences in Q10 values (Figure 4) suggests, therefore, that Rlight/Rdark of individual trees might actually remain constant with increasing measuring T, rather than increase as shown in Figure 5. Thus, while caution is needed when deciding on the diel pattern in Rlight/Rdark, our results do not support the hypoth-esis that Rlight/Rdark consistently decreases with rising Tleaf.

We found that the degree of light inhibition of R varied from month to month being greatest in December and lowest in November (Figure 5). This, in turn, suggests fundamental shifts in metabolic processes that control light inhibition. Unfortunately, we lack a clear understanding of the factors responsible for light inhibition of leaf R, particularly for field-grown trees experienc-ing variable abiotic conditions (temperature, light, water avail-ability), which in turn are likely to impact processes that modulate respiratory fluxes in the light. Thus, further research is needed to determine the mechanistic basis for seasonal vari-ability in light inhibition of R. Here, a priority will be to establish the role of factors such as temporal variations in cellular energy status, photorespiration-dependent inactivation of the pyruvate dehydrogenase complex ( Budde and Randall 1990, Gemel and Randall 1992) and the transition to a truncated TCA cycle (Igamberdiev et al. 2001, Tcherkez et al. 2008) in controlling light inhibition of respiration in the field. However, the lack of a strong effect of seasonal shifts in Tair on the Q10 of R is in agree-ment with earlier work on E. pauciflora, which also found the Q10 of Rdark was constant when daily Tair ranged between 5 and 17 °C, although the Q10 was higher on days when Tair fell below 5 °C ( Atkin et al. 2000a). Assessments of how the Q10 of Rlight varies over the year in field-grown plants are uncommon, and our results imply that there is no need to assume that the tempera-ture sensitivity of Rlight and Rdark differ in a systematic way to annual changes in Tair and other environmental drivers.

Leaf R can acclimate to changes in prevailing Tleaf within days ( Zaragoza-Castells et al. 2007, other reference), such that rates of R in cool-grown leaves tend to be higher than those of warm-grown leaves, when assessed at a common Tleaf ( Atkin and Tjoelker 2003, Atkin et al. 2005b, Slot and Kitajima 2015). While acclimation of R to a new temperature or irradiance regime is often greatest in leaves that develop in the new envi-ronment ( Campbell et al. 2007), species with long-lived leaves also show substantial acclimation of R in existing leaves that are transferred to new light or temperature conditions ( Noguchi et al. 2001, Zaragoza-Castells et al. 2007). We would thus expect that rates of R measured at a common Tleaf (e.g., 25 °C) to be lowest in the hot, summer months. However, we generally do not find this. For example, daily changes in Tleaf were similar in April and November, but Rlight was substantially greater in November than in April (Figure 2); as the mean Tair of the previ-ous 2 days was ∼6.5 °C higher in November than April (Table 1), if thermal acclimation had occurred, the opposite pattern should have occurred. Importantly, our ability to investigate thermal

846 Way et al.



acclimation of R to seasonal shifts in Tair was constrained to rela-tively warm months, as low stomatal conductance rates pre-cluded measurements of Rlight and Rdark in colder months, which may contribute to the absence of apparent temperature acclima-tion of R. The differences between months shown here are also unlikely to be associated with changes in leaf carbohydrate sta-tus, as in previous work on these trees, Atkin et al. (2000a) showed that there was no correlation between leaf non- structural carbohydrate concentrations and seasonal acclimation of Rdark from April to December. Our ability to evaluate thermal acclimation of R may also have been constrained because the leaves from February to March, while fully expanded in size, exhibited higher specific leaf area values than leaves sampled in other months (indicating temporal changes in leaf development and potential phenological shifts in R over the season). Notwith-standing these issues, our study does provide new insights into how the rates and short-term thermal sensitivities of Rlight and Rdark vary throughout the warmer, growing season months expe-rienced by E. pauciflora, as leaves develop in a field setting.

Given the importance of R in the global C cycle, understand-ing how R responses to changes in environmental conditions is critical for modeling both current and future C fluxes from veg-etation. We show that models of R in terrestrial vegetation may be able to use a simplified approach, whereby the same value can be used for the Q10 of Rlight and Rdark across the year. Our results also indicate that the ratio of Rlight/Rdark is affected by both daily and seasonal variations in Tleaf, but we need a better understanding of the mechanisms underlying these shifts in the light suppression of R to accurately model these responses.

Supplementary data

Supplementary data for this article are available at Tree Physiology Online.

Acknowledgments

We acknowledge the expert technical assistance of Jack Egerton. We thank the ACT Parks and Conservation Service for allowing this study to be undertaken in Namadgi National Park.

Conflict of interest

None declared.

Funding

D.A.W. gratefully acknowledges support from the Hawkesbury Institute for the Environment visiting fellow program at the Uni-versity of Western Sydney, as well as support from the Natural Sciences and Engineering Research Council of Canada, the Canadian Foundation for Innovation and the Ontario Research

Fund. We also acknowledge funding from the Australian Research Council (DP130101252, CE140100008, FT0991448) to O.K.A. and (DP110105380) to M.C.B.

References

Atkin OK, Tjoelker MG (2003) Thermal acclimation and the dynamic response of plant respiration to temperature. Trends Plant Sci 8:343–351.

Atkin OK, Evans JR, Siebke K (1998) Relationship between the inhibi-tion of leaf respiration by light and enhancement of leaf dark respiration following light treatment. Aust J Plant Physiol 25: 437–443.

Atkin OK, Holly C, Ball MC (2000a) Acclimation of snow gum (Eucalyp-tus pauciflora) leaf respiration to seasonal and diurnal variations in temperature: the importance of changes in the capacity and tempera-ture sensitivity of respiration. Plant Cell Environ 23:15–26.

Atkin OK, Evans JR, Ball MC, Lambers H, Pons TL (2000b) Leaf respira-tion of snow gum in the light and dark. Interactions between tempera-ture and irradiance. Plant Physiol 122:915–923.

Atkin OK, Millar AH, Gärdestrom P, Day DA (2000c) Photosynthesis, carbohydrate metabolism and respiration in leaves of higher plants. In: Leegood RC, Sharkey TD, von Caemmerer S (eds), Photosynthesis, physiology and metabolism. Kluwer Academic Publishers, London.

Atkin OK, Bruhn D, Tjoelker MG (2005a) Response of plant respiration to changes in temperature: mechanisms and consequences of variations in Q10 values and acclimation. In: Lambers H, Ribas-Carbo M (eds) Plant respiration. Springer, Dordrecht, The Netherlands, pp 95–135.

Atkin OK, Bruhn D, Hurry VM, Tjoelker MG (2005b) The hot and the cold: unravelling the variable response of plant respiration to tempera-ture. Funct Plant Biol 32:87–105.

Atkin OK, Scheurwater I, Pons TL (2006) High thermal acclimation potential of both photosynthesis and respiration in two lowland Plan-tago species in contrast to an alpine congeneric. Glob Change Biol 12:500–515.

Atkin OK, Scheurwater I, Pons TL (2007) Respiration as a percentage of daily photosynthesis in whole plants is homeostatic at moderate, but not high, growth temperatures. New Phytol 174:367–380.

Ayub G, Smith RA, Tissue DT, Atkin OK (2011) Impacts of drought on leaf respiration in darkness and light in Eucalyptus saligna exposed to industrial-age atmospheric CO2 and growth temperature. New Phytol 190:1003–1018.

Azcón-Bieto J, Osmond CB (1983) Relationship between photosynthesis and respiration: the effect of carbohydrate status on the rate of CO2 production by respiration in darkened and illuminated wheat leaves. Plant Physiol 71:574–581.

Bernacchi CJ, Singsaas EL, Pimentel C, Portis Jr AR, Long SP (2001) Improved temperature response functions for models of Rubisco-lim-ited photosynthesis. Plant Cell Environ 24:253–259.

Booth BBB, Jones CD, Collins M et al. (2012) High sensitivity of future global warming to land carbon cycle processes. Environ Res Lett 7:024002. doi:10.1088/1748-9326/7/2/024002

Brooks A, Farquhar GD (1985) Effect of temperature on the CO2/O2 specificity of ribulose-1,5-bisphosphate carboxylase/oxygenase and the rate of respiration in the light: estimates from gas-exchange mea-surements on spinach. Planta 165:397–406.

Bruhn D, Mikkelsen TN, Atkin OK (2002) Does the direct effect of atmo-spheric CO2 concentration on leaf respiration vary with temperature? Responses in two species of Plantago that differ in relative growth rate. Plant Physiol 114:57–64.

Bruhn D, Loveys BR, Egerton JJG, Ball MC (2007) Evergreen leaf respira-tion acclimates to long-term nocturnal warming under field conditions. Glob Change Biol 13:1216–1223.




http://dx.doi.org/10.1088/1748-9326/7/2/024002


Bruhn D, Schortemeyer M, Edwards EJ, Egerton JJG, Hocart CH, Evans JR, Ball MC (2008) The apparent temperature response of leaf respira-tion depends on the timescale of measurements: a study of two cold climate species. Plant Biol 10:185–193.

Bruhn D, Mikkelsen TN, Herbst M, Kutsch WL, Ball MC, Pilegaard K (2011) Estimating daytime ecosystem respiration from eddy-flux data. BioSystems 103:309–313.

Budde RJA, Randall DD (1990) Pea leaf mitochondrial pyruvate dehy-drogenase complex is inactivated in vivo in a light-dependent manner. Proc Natl Acad Sci USA 87:673–676.

Campbell C, Atkinson L, Zaragoza-Castells J, Lundmark M, Atkin O, Hurry V (2007) Acclimation of photosynthesis and respiration is asynchro-nous in response to changes in temperature regardless of plant func-tional group. New Phytol 176:375–389.

Canadell JG, Le Quere C, Raupach MR et al. (2007) Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc Natl Acad Sci USA 104:18866–18870.

Ciais P, Sabine C, Bala G et al. (2013) Carbon and other biogeochemical cycles. In: Stocker TF, Qin D, Plattner G-K et al. (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USA.

Cox PM, Betts RA, Jones CD, Spall SA, Totterdell IJ (2000) Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408:184–187.

Crous KY, Zaragoza-Castells J, Ellsworth DS, Duursma RA, Low M, Tissue DT, Atkin OK (2012) Light inhibition of leaf respiration in field-grown Eucalyptus saligna in whole-tree chambers under elevated atmo-spheric CO2 and summer drought. Plant Cell Environ 35:966–981.

Gemel J, Randall DD (1992) Light regulation of leaf mitochondrial pyru-vate dehydrogenase complex. Role of photorespiratory carbon metab-olism. Plant Physiol 100:908–914.

Griffin KL, Turnbull MH (2013) Light saturated RuBP oxygenation by Rubisco is a robust predictor of light inhibition of respiration in Triticum aestivum L. Plant Biol 15:769–775.

Heskel MA, Atkin OK, Turnbull MH, Griffin KL (2013) Bringing the Kok effect to light: a review on the integration of daytime respiration and net ecosystem exchange. Ecosphere 4:art98. doi:10.1890/ES13-00120.1

Holmgren P, Jarvis PG (1967) Carbon dioxide efflux from leaves in light and darkness. Physiol Plant 20:1045–1051.

Huntingford C, Zelazowski P, Galbraith D et al. (2013) Simulated resil-ience of tropical rainforests to CO2-induced climate change. Nat Geosci 6:268–273.

Hurry V, Keerberg O, Pärnik T, Öquist G, Gardeström P (1996) Effect of cold hardening on the components of respiratory decarboxylation in the light and in the dark in leaves of winter rye. Plant Physiol 111:713–719.

Hurry V, Igamberdiev AU, Keerberg O, Pärnik T, Atkin OK, Zaragoza-Cas-tells J, Gardeström P (2005) Respiration in photosynthetic cells: gas exchange components, interactions with photorespiration and the oper-ation of mitochondria in the light. In: Lambers H, Ribas-Carbo M (eds) Plant respiration. Springer, Dordrecht, The Netherlands, pp 43–61.

Igamberdiev AU, Gardeström P (2003) Regulation of NAD- and NADP-dependent isocitrate dehydrogenases by reduction levels of pyridine nucleotides in mitochondria and cytosol of pea leaves. Biochim Bio-phys Acta 1606:117–125.

Igamberdiev AU, Bykova NV, Lea PJ, Gardeström P (2001) The role of photorespiration in redox and energy balance of photosynthetic plant cells: A study with a barley mutant deficient in glycine decarboxylase. Physiol Plant 111:427–438.

Kirschbaum MUF, Farquhar GD (1984) Temperature dependence of whole-leaf photosynthesis in Eucalyptus pauciflora Sieb. Ex Spreng. Aust J Plant Physiol 11:519–538.

Kruse J, Rennenberg H, Adams MA (2011) Steps towards a mechanistic understanding of respiratory temperature responses. New Phytol 189:659–677.

Laisk AK (1977) Kinetics of photosynthesis and photorespiration in C3 plants. Nauka, Moscow, Russia.

Lloyd J, Patiño S, Paiva RQ et al. (2009) Variations in leaf physiological properties within Amazon forest canopies. Biogeosci Discuss 6:4639–4692.

Loreto F, Delfine S, Di Marco G (1999) Estimation of photorespiratory carbon dioxide recycling during photosynthesis. Aust J Plant Physiol 26:733–736.

Malhi Y, Doughty CE, Goldsmith GR et al. (2015) The linkages between photosynthesis, productivity, growth and biomass in lowland Amazo-nian forests. Glob Change Biol 21:2283–2295.

Noguchi K, Nakajima N, Terashima I (2001) Acclimation of leaf respira-tory properties in Alocasia odora following reciprocal transfers of plants between high- and low-light environments. Plant Cell Environ 24:831–839.

O’Sullivan OS, Weerasinghe KWLK, Evans JR, Egerton JJG, Tjoelker MG, Atkin OK (2013) High-resolution temperature responses of leaf res-piration in snow gum (Eucalyptus pauciflora) reveal high-temperature limits to respiratory function. Plant Cell Environ 36:1268–1284.

Prentice IC, Farquhar GD, Fasham MJR et al. (2001) The carbon cycle and atmospheric carbon dioxide. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (eds) Contribution of working group I to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 183–237.

Shapiro JB, Griffin KL, Lewis JD, Tissue DT (2004) Response of Xanthium strumarium leaf respiration in the light to elevated CO2 concentration, nitrogen availability and temperature. New Phytol 162:377–386.

Slot M, Kitajima K (2015) General patterns of acclimation of leaf respi-ration to elevated temperatures across biomes and plant types. Oeco-logia 177:885–900.

Smith NG, Dukes JS (2013) Plant respiration and photosynthesis in global-scale models: incorporating acclimation to temperature and CO2. Glob Change Biol 19:45–63.

Tcherkez G, Cornic G, Bligny R, Gout E, Ghashghaie J (2005) In vivo respi-ratory metabolism of illuminated leaves. Plant Physiol 138:1596–1606.

Tcherkez G, Bligny R, Gout E, Mahé A, Hodges M, Cornic G (2008) Respiratory metabolism of illuminated leaves depends on CO2 and O2 conditions. Proc Natl Acad Sci USA 105:797–802.

Tjoelker MG, Oleksyn J, Reich PB (2001) Modelling respiration of vege-tation: evidence for a general temperature-dependent Q10. Glob Change Biol 7:223–230.

Vanderwel MC, Slot M, Lichstein JW, Reich PB, Kattge J, Atkin OK, Bloom-field KJ, Tjoelker MG, Kitajima K (2015) Global convergence in leaf respiration from estimates of thermal acclimation across time and space. New Phytol; doi:10.1111/nph.13417.

Villar R, Held AA, Merino J (1994) Comparison of methods to estimate dark respiration in the light in leaves of two woody species. Plant Physiol 105:167–172.

Wager HG (1941) On the respiration and carbon assimilation rates of some arctic plants as related to temperature. New Phytol 40:1–19.

Way DA, Sage RF (2008) Thermal acclimation of photosynthesis in black spruce [Picea mariana (Mill.) B.S.P.]. Plant Cell Environ 31:1250–1262.

Way DA, Yamori W (2014) Thermal acclimation of photosynthesis: on the importance of adjusting our definitions and accounting for thermal acclimation of respiration. Photosynth Res 119:89–100.

Way DA, Oren R, Kroner Y (2015) The space-time continuum: the effects of elevated CO2 and temperature on trees and the importance of scal-ing. Plant Cell Environ 38:991–1007.

Weerasinghe LK, Creek D, Crous KY, Xiang S, Liddell MJ, Turnbull MH, Atkin OK (2014) Canopy position affects the relationships between

848 Way et al.


http://dx.doi.org/10.1890/ES13-00120.1

doi:10.1111/nph.13417


leaf respiration and associated traits in a tropical rainforest in Far North Queensland. Tree Physiol 34:564–584.

Wingate L, Seibt U, Moncrieff JB, Jarvis PG, Lloyd J (2007) Variations in 13C discrimination during CO2 exchange by Picea sitchensis branches in the field. Plant Cell Environ 30:600–616.

Wohlfahrt G, Bahn M, Haslwanter A, Newesely C, Cernusca A (2005) Estimation of daytime ecosystem respiration to determine gross

primary production of a mountain meadow. Agric For Meteorol 130:13–25.

Zaragoza-Castells J, Sanchez-Gomez D, Valladares F, Hurry V, Atkin OK (2007) Does growth irradiance affect temperature depen-dence and thermal acclimation of leaf respiration? Insights from a Mediterranean tree with long-lived leaves. Plant Cell Environ 30:820–833.



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