Species-specific temporal variation in photosynthesis as a moderator of peatland carbon sequestration

Abstract

In boreal bogs plant species are low in number, but they differ greatly in their growth forms and photosynthetic properties. We assessed how ecosystem carbon (C) sink dynamics were affected by seasonal variations in the photosynthetic rate and leaf area of different species. Photosynthetic properties (light response parameters), leaf area development and areal cover (abundance) of the species were used to quantify species-specific net and gross photosynthesis rates (P_N and P_G, respectively), which were summed to express ecosystem-level P_N and P_G. The ecosystem-level P_G was compared with a gross primary production (GPP) estimate derived from eddy covariance (EC) measurements.Species areal cover, rather than differences in photosynthetic properties, determined the species with the highest P_G of both vascular plants and Sphagna. Species-specific contributions to the ecosystem P_G varied over the growing season, which, in turn, determined the seasonal variation in ecosystem P_G. The upscaled growing season P_G estimate, 230gCm^-2, agreed well with the GPP estimated by the EC (243gCm^-2).Sphagna were superior to vascular plants in ecosystem-level P_G throughout the growing season but had a lower P_N. P_N results indicated that areal cover of the species, together with their differences in photosynthetic parameters, shape the ecosystem-level C balance. Species with low areal cover but high photosynthetic efficiency appear to be potentially important for the ecosystem C sink. Results imply that functional diversity, i.e., the presence of plant groups with different seasonal timing and efficiency of photosynthesis, may increase the stability of C sinks of boreal bogs.

Biogeosciences, 14, 257269, 2017 www.biogeosciences.net/14/257/2017/ doi:10.5194/bg-14-257-2017 Author(s) 2017. CC Attribution 3.0 License.

Aino Korrensalo1, Pavel Alekseychik2, Tom Hjek3, Janne Rinne4, Timo Vesala2,5, Lauri Mehttalo6, Ivan Mammarella2, and Eeva-Stiina Tuittila1

1School of Forest Sciences, University of Eastern Finland, Joensuu, Finland

2Dept. of Physics, University of Helsinki, Helsinki, Finland

3Faculty of Science, University of South Bohemia,esk Budjovice, Czech Republic

4Dept. of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden

5Dept. of Forest Sciences, University of Helsinki, Helsinki, Finland

6School of Computing, University of Eastern Finland, Joensuu, Finland

Correspondence to: Aino Korrensalo (aino.korrensalo@uef.)

Received: 20 June 2016 Published in Biogeosciences Discuss.: 13 July 2016Revised: 9 December 2016 Accepted: 19 December 2016 Published: 18 January 2017

Abstract. In boreal bogs plant species are low in number, but they differ greatly in their growth forms and photosynthetic properties. We assessed how ecosystem carbon (C) sink dynamics were affected by seasonal variations in the photosynthetic rate and leaf area of different species. Photosynthetic properties (light response parameters), leaf area development and areal cover (abundance) of the species were used to quantify species-specic net and gross photosynthesis rates (PN and PG, respectively), which were summed to express ecosystem-level PN and PG. The ecosystem-level PG was compared with a gross primary production (GPP) estimate derived from eddy covariance (EC) measurements.

Species areal cover, rather than differences in photosynthetic properties, determined the species with the highest PG of both vascular plants and Sphagna. Species-specic contributions to the ecosystem PG varied over the growing season, which, in turn, determined the seasonal variation in ecosystem PG. The upscaled growing season PG estimate, 230 g C m2, agreed well with the GPP estimated by the EC (243 g C m2).

Sphagna were superior to vascular plants in ecosystem-level PG throughout the growing season but had a lower PN.

PN results indicated that areal cover of the species, together with their differences in photosynthetic parameters, shape the ecosystem-level C balance. Species with low areal cover but high photosynthetic efciency appear to be potentially important for the ecosystem C sink. Results imply that func-

Species-specic temporal variation in photosynthesis as a moderator of peatland carbon sequestration

tional diversity, i.e., the presence of plant groups with different seasonal timing and efciency of photosynthesis, may increase the stability of C sinks of boreal bogs.

1 Introduction

Northern peatlands are a globally important carbon (C) sink and storage of approximately 500 Gt C (Gorham, 1991; Yu, 2012) as a result of an imbalance between photosynthesis and decomposition. Boreal bogs are peatland ecosystems where photosynthetic productivity is limited by midsummer dry periods, light induced stress and, in particular, low nutrient availability (Frolking et al., 1998; Moore et al., 2002). Due to the low rate of photosynthesis, the annual C sink of boreal bogs is weak and sensitive to changes; even a small change in the environmental conditions that regulate the C cycle can turn the ecosystem into a C source (Waddington and Roulet, 2000; Lund et al., 2012). The rate by which CO2 enters the ecosystem through photosynthesis of all of the individual plants together is the denition of gross primary production (GPP). When ecosystem respiration (Reco) is subtracted from

GPP, the result is net ecosystem exchange (NEE) of CO2 between the ecosystem and the atmosphere. On the scale of individual plants, the same processes are called gross photo-synthesis (PG), plant respiration (R) and net photosynthesis (PN) (Chapin et al., 2011).

Published by Copernicus Publications on behalf of the European Geosciences Union.

258 A. Korrensalo et al.: Species-specic temporal variation in photosynthesis

Boreal bogs are ecosystems with low species diversity but a high diversity of growth forms due to the large microtopo-graphical variation and associated diversity of habitats along the water table gradient (Turetsky et al., 2012; Rydin and Jeglum, 2013). Several studies (e.g., Weltzin et al., 2000;Moore et al., 2002; Leppl et al., 2008) have reported that patterned bogs produce more biomass and have less variation in gross photosynthesis over the growing season than fens, which receive additional nutrients from the surrounding mineral soil and generally have more homogenous, sedge-dominated vegetation (Weltzin et al., 2000). Experimental studies have shown that bog plant growth forms have differential responses to warming and water table level manipulation, which can help to maintain the level of total ecosystem productivity under changing environmental conditions (Weltzin et al., 2000; Breeuwer et al., 2009). Short-term plant removal experiments have shown the differential roles of plant functional types for the peatland NEE and GPP (Ward et al., 2009; Kuiper et al., 2014). Photosynthetic properties of bog plants are known to differ widely between species of the same functional type (Small, 1972) and between phases of growing season (Korrensalo et al., 2016a). So far, the role of species-level differences in temporal variation of bog ecosystem photosynthesis has not been studied.

Here, we aim to solve the linkage between the temporal pattern of bog carbon balance and the development of species-specic potential photosynthesis and leaf area. For this purpose, we quantied the contribution of different plant species to ecosystem-level photosynthesis over a growing season. As species differ in their photosynthetic properties, and the properties vary over the growing season, we expect their importance for the ecosystem carbon sequestration to also vary over the season. To reach our aim we estimate PN and PG for the whole study site based on the monthly species-level light response of photosynthesis and species-specic leaf area development over a growing season. To validate the upscaling approach, the sum of species-level PG is compared to the GPP derived from eddy covariance (EC) measurements at the study site.

2 Methods

2.1 Study site

The study site (61 50.179[prime] N, 24 10.145[prime] E) is situated in an ombrotrophic bog, which is a part of the Siikaneva peatland complex in southern Finland, located in the southern bo-real vegetation zone. The annual temperature sum in the area (base temperature 5 C) is 1318 degree days, annual rainfall is 707 mm and the average annual, January and July temperatures are 4.2, 7.2 and 17.1 C, respectively (30-year

averages (years 19822011) from the Juupajoki-Hyytil weather station). The study site has a surface topography typical of raised bogs that varies from open water pools and mud

surfaces to hollows, lawns and hummocks. An EC ux tower is mounted on a raft in the center of the site.

The vegetation is mainly composed of 11 vascular plant and 8 Sphagnum species (Table 1), the abundance of which varies markedly along the microtopographical gradient. A continuous Sphagnum carpet covers the surfaces from hum-mocks to hollows, although no Sphagna are present on the mud and water surfaces. Sphagnum cuspidatum and S. majus are dominant in hollows, S. papillosum, S. rubellum, S. balticum and S. magellanicum in lawns, and S. fuscum, S. rubellum and S. angustifolium cover the hummocks. Vascular plant species composition includes Rhynchospora alba, Scheuchzeria palustris and Carex limosa vegetation on mud and hollow surfaces, dwarf shrubs (Andromeda polifolia, Vaccinium oxycoccos) and Eriophorum vaginatum on lawn surfaces, and a shrub layer of Calluna vulgaris, Betula nana, Empetrum nigrum, and sedges Eriophorum vaginatum and Trichophorum cespitosum on hummocks.

2.2 Plant level photosynthesis measurements

To quantify the role of plant species in ecosystem-level photosynthesis over the growing season, we conducted net photosynthesis (PN) measurements of the 19 most common species at the study site. Over the growing season 2013, we measured CO2 exchange of three to ve samples of each species per month at three light levels with two open, ow-through gas exchange measurement devices (GFS-3000, Walz, Germany, and LI-6400, LI-COR, USA). Samples were collected from several locations inside the study area a maximum of 30 h prior to measurement; Sphagna were collected in small plastic bags and vascular plants in plastic boxes with an ample amount of roots and peat. These were kept moist until measured. Vascular plants were kept in shaded conditions and Sphagna were stored in the dark at 5 C. The moss cuvettes were lled with Sphagnum capitula imitating the natural shoot density of each species in the eld, resulting in a total number of 616 capitula inside a cuvette depending on the species. Before placing the capitula into the cuvettes, they were rst wetted and then lightly dried of excess water with pulp paper. The cuvette was then placed under a photosynthetic photon ux density (PPFD) of approximately 1000 mol m2 s1 to acclimate to light for 20 min.

The measured light levels were 2000, 25 and 0 mol m2 s1 for vascular plants and 2000, 35 and 0 mol m2 s1 for

Sphagna. Light levels were designed to catch both the linear, light-limited beginning and the light-saturated maximum of the light response curve without causing photoinhibitory reduction of photosynthetic rate (Laine et al., 2015). Vascular plants were measured with a standard cuvette, but for Sphagna we used a moss cuvette of our own construction with internal dimensions of 3 [notdef] 2 [notdef] 1 cm (Hjek et al., 2009)

with a net bottom to allow airow above and below the sample reducing the aerodynamic resistance. After changing the light level, we waited for the PN to reach steady state be-

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A. Korrensalo et al.: Species-specic temporal variation in photosynthesis 259

Table 1. Average projection cover of the most common plant species at the study site, maximum leaf area index (LAI) values, and cumulative seasonal gross and net photosynthesis (PG, PN) of the species measured in this study. The cover values are based on a vegetation inventory conducted in 2013 at the study site within the 30 m radius footprint of the eddy covariance tower (N = 121). LAI values of vascular plants

are seasonal maxima of each species calculated by converting the cover values into LAI using species-wise linear relationships (Supplement Table S2). Sphagnum LAI is assumed to stay similar over the growing season and is simply the coverage expressed as LAI. Sphagnum and vascular species nomenclature according to Laine et al. (2009) and Hmet-Ahti (1998), respectively.

Species Cover mean LAI Seasonal PG Seasonal PN

SE (%) (m2 m2) (g C m2) (g C m2)

Vascular total 24.2 [notdef] 1.9 0.29 92.2 57.3

Rhynchospora alba 6.9 [notdef] 0.8 0.10 23.3 15.1

Andromeda polifolia 3.7 [notdef] 0.4 0.03 14.4 8.4

Calluna vulgaris 2.8 [notdef] 0.9 0.04 13.8 9.1

Rubus chamaemorus 2.5 [notdef] 0.6 0.03 6.9 4.5

Eriophorum vaginatum 1.5 [notdef] 0.3 0.02 6.0 3.8

Vaccinium oxycoccos 1.2 [notdef] 0.2 0.01 5.3 3.2

Drosera rotundifolia 1.1 [notdef] 0.1

Empetrum nigrum 1.0 [notdef] 0.5 0.01 2.3 1.2

Trichophorum cespitosum 1.0 [notdef] 0.5 0.02 11.5 6.7

Drosera longifolia 0.8 [notdef] 0.4

Scheuchzeria palustris 0.8 [notdef] 0.1 0.02 5.1 3.0

Betula nana 0.4 [notdef] 0.2 0.004 1.1 0.5

Carex limosa 0.4 [notdef] 0.1 0.005 2.4 1.8 Sphagnum total 63.8 [notdef] 3.7 0.65 137.8 19.9

Sphagnum rubellum 18.3 [notdef] 2.6 0.18 30.7 0.8

S. papillosum 12.9 [notdef] 2.3 0.13 33.9 6.8

S. fuscum 11.0 [notdef] 2.3 0.11 27.1 7.4

S. balticum 8.3 [notdef] 1.5 0.08 15.7 0.5

S. cuspidatum 4.8 [notdef] 1.3 0.05 13.4 1.7

S. majus 4.7 [notdef] 1.2 0.05 12.7 2.8

S. angustifolium 1.3 [notdef] 0.5 0.01 3.6 0.6

S. lindbergii 0.8 [notdef] 0.8

S. magellanicum 0.3 [notdef] 0.1 0.003 0.7 0.1 Other mosses and lichens

Pleurozium schreberi 0.8 [notdef] 0.5

Mylia anomala 0.2 [notdef] 0.1

Cladina rangiferina 0.4 [notdef] 0.2

fore recording the CO2 exchange. Only PPFD was varied during the measurements, while we kept air temperature at constant 20 C, the ow rate at 600 mol s1 and the CO2 concentration in the incoming air at 400 ppm to be able to compare the seasonal changes in photosynthetic potential among species. The relative humidity inside the cuvette was kept at 50 % for the vascular plants and below 90 % for the Sphagna. The measured PN value of each sample at the three light levels was expressed per photosynthesizing leaf area (mg CO2 m2 (LA) h1), which was the leaf area inside the cuvette measured with a scanner for vascular plants and assumed to be the cuvette area for Sphagna. Two of the species, namely Rhynchospora alba and Rubus chamaemorus, were not yet of measurable size in May; R. alba had already mostly senesced in September, and therefore the two species were

not measured in those months. Altogether, the data consisted

of 720 measurements.

2.3 Net photosynthesis model

To obtain a species-wise ux reconstruction of PN and PG, we tted a nonlinear mixed-effects model separately for each combination of species and month. The mixed-effects modeling approach allowed us to take into account the variation between samples, of which each was measured at three light levels. We used the hyperbolic light saturation curve of PN (Larcher, 2003):

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260 A. Korrensalo et al.: Species-specic temporal variation in photosynthesis

esi, (1)

where PNsi is the observed net CO2 exchange (mg CO2 m2 (LA) h1) and PPFDsi is the photosynthetic photon ux density for measurement i of sample s. The three parameters to be estimated are the maximum rate of light-saturated net photosynthesis (Pmaxs), the PPFD level where half of Pmax was reached (ks) and respiration (Rs), and they were assumed to be constant for each combination of species and month. esi is the normally distributed residual variance of the model with a mean of zero. The normally distributed random effect of the sample was included in one to three of the parameters depending on the model. The random effect structure was selected based on the Akaike information criterion (AIC) values of the alternative models with random effects included in a different combination of parameters. The random effects for the sub-models of each nonlinear model form a vector of random effect with nonzero correlation. Parameter values for the 87 PN models are presented in the Supplement (Table S1). The separate tting for each combination of species and months leads to models with similar asymptotic unbiasedness as a single model for complete data would do. However, separate models do not quantify the temporal and between-species correlation of random effects and residuals and therefore do not provide a sufciently detailed model for evaluating the prediction errors of upscaled estimates of net photosynthesis. A proper model for such a purpose would model both temporal and between-species covariance of both random effects and residuals, but model tting procedures for such models are not available in the standard statistical software. All models were tted using the function nlme of the R program package nlme (Pinheiro and Bates, 2000).

Sphagna were not measured in June nor were vascular plants measured in July due to technical failures of the devices. Therefore, light response curves for these 2 months were tted by combining data from the previous and following month for each species. In 5 of the 95 speciesmonth combinations only one sample of the species had an acceptable measurement. The parameters for these months were estimated separately without the mixed model structure (Table S1).

2.4 Upscaling

To upscale species-level photosynthesis to the ecosystem level, the cover of each species was estimated within the study site with a systematic vegetation inventory conducted in July 2013. We estimated the relative cover of each plant species in 121 plots of 0.071 m2 (Table 1), which were arranged in a regular grid in a 30 m radius circle around the EC tower. To link net photosynthesis measured per leaf area to species cover, we converted species cover in the study area

to leaf area index (LAI) using linear relationships between the two (Table S2). Relationships were based on an inventory made in July 2012 over a 200 m radius circle where species cover was estimated, and then all living aboveground vegetation was harvested from 65 inventory plots of 0.071 m2 for LAI measurements. The vascular plant LAI of these samples was measured in the laboratory.

We monitored LAI development of each vascular plant species over the growing season in 18 permanent sampling plots (0.36 m2) that represented all the vegetation communities (n = 3 in each vegetation community) along the microto

pographical gradient at the study site. LAI was estimated every third week according to the method described by Wilson et al. (2007). Continuous LAI development of each species was then estimated by tting a log-linear response to the observations. The shape of the log-linear LAI development was taken from this tting, and the growing season LAI maximum for each species was taken from the converted average cover (Table 1). Sphagnum leaf area was assumed to stay constant over the whole growing season and was obtained using the average cover from the 2013 inventory.

Using the light response curves, estimated daily LAI, and half-hourly, above-canopy PPFD data from SMEAR II measurement station (61 50.845[prime] N, 24 17.686[prime] E), we calculated PN and PG for each half hour period (mg CO2 m2 30 min1) over the growing season (Julian days 121273) with the species-wise and monthly light response curves. PG was calculated with the same model without the R parameter, i.e., assuming that respiration is zero. Model predictions were not meaningfully changed by using marginal prediction, i.e., averaging the predictions over the distribution random effects (e.g., de Miguel et al., 2012) and were therefore computed using the xed part of the model only. Growing season PN and PG of the whole study site were calculated as a sum of their daily values.

2.5 Ecosystem-level CO2 exchange measurements and estimation of gross primary production

To validate the measured levels of photosynthesis, the calculated values were compared with the GPP estimates obtained by EC measurements, which offer an independent estimate of the ecosystem-level CO2 exchange measured directly as turbulent vertical uxes (e.g., Baldocchi, 2003; Aubinet et al., 2012). The EC system comprised a 3-D ultrasonic anemometer (USA-1, METEK Meteorologische Messtechnik GmbH, Germany) and an enclosed H2O/CO2 gas analyzer (LI-7200,

LI-COR Biosciences, USA). The EC sensors were mounted on the mast 2.5 m above the peat surface. EddyUH software was used to process the raw data and produce the 30 min average uxes of latent heat, sensible heat and CO2 (Mammarella et al., 2015). Standard EC data checks based on the widely accepted quality criteria (e.g., Aubinet et al., 2012) were applied partly automatically by the software and partly manually; the EC data at friction velocity (u ) less than

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PNsi = Rs +

Pmaxs PPFDsi

ks + PPFDsi +

A. Korrensalo et al.: Species-specic temporal variation in photosynthesis 261

0.1 m s1 were rejected. The resulting EC uxes represent the exchange over a quasi-elliptical source area (footprint) located within about 30 m upwind of the EC mast, as suggested by footprint calculations using the model by Kormann and Meixner (2001).

NEE measured by the EC method was then partitioned into ecosystem GPP and Reco. The daytime Reco estimates were obtained from the Q10-type temperature response curve tted to the nighttime EC data, when respiration is the only component of NEE. Nighttime was dened as all the periods when the sun elevation angle was lower than 5 . Peat temperature at 5 cm depth was used as the driver of Reco, in the following relationship:

Reco = RrefQ[parenleftBig]

TpTref

10

[parenrightBig]

10 , (2) where Tp is the peat temperature at a 5 cm depth ( C) and

Tref is the peat reference temperature of 12 C. Parameters to be estimated from the t of the model (Eq. 2) to all available nighttime NEE data were Rref, the reference respiration at the temperature of 12 C, and Q10, the temperature sensitivity coefcient.

The GPP estimates were calculated by subtracting the modeled Reco from the EC-derived NEE values. Finally, in order to gap-ll the GPP time series, a model using PPFD (from the SMEAR II measurement station) and the footprint-scale LAI was tted to the data following

GPP =

Pmax PPFD

k + PPFD

(LAI + b), (3)

where GPP is expressed in milligrams (CO2) per square meter per hour. LAI is the modeled daily vascular leaf area index described above, while b represents the temporally constant contribution of the Sphagnum to total LAI.

One of the major sources of random uncertainty in cumulative GPP originates from the uncertainty in the Reco and

GPP model parameters. Random uncertainty was calculated as the 95 % condence interval of a set of 1000 cumulative GPP estimates obtained using Rref, Q10, Pmax and k varied within their respective 95 % condence intervals. Since laboratory measurements of PG were conducted at a constant temperature of 20 C and EC measurements at the air temperatures present at the eld site, the temperature limitation of GPP was studied by tting to the GPP data a model similar to Eq. (3), but complemented with a Gaussian-type temperature response (Maanavilja et al., 2011):

GPP =

Pmax PPFD k + PPFD

(deviation from the optimum at which GPP is 60 % of the maximum). Using Eq. (4), GPP at 20 C and at ambient PAR and LAI was simulated for the study site over the growing season.

3 Results

3.1 Cumulative growing season gross photosynthesis

Fitting the temperature response curve of Reco, Eq. (2), into the nighttime eddy covariance data yielded a reference respiration (Rref) of 123 mg (CO2) m2 h1 and Q10 of 3.5. In the

GPP model (Eq. 3) t, Pmax was 1721.8 mg CO2 m2 h1, k was 128.3 mol m2 s1 and b was 0.08. After gap-lling the GPP data (Eq. 3), the resulting cumulative growing season GPP estimate was 243 g C m2 (95 % condence interval; 220265 g C m2). In the GPP model t complemented with the temperature response (Eq. 4), Pmax was 1852 mg (CO2) m2 h1, k was 170.3 mol m2 s1, b was 0.1, Topt was 22.6 C and Ttol was 20.9 C.

Cumulative growing season PG upscaled to the ecosystem level using the separate light response curves for species and months (Eq. 1) was 230 g C m2 (Julian days 121273).

Daily PG estimates were higher than GPP values from the EC tower in spring and lower in the middle of the summer (Fig. 1a). The GPP simulated at 20 C, the same temperature as during the laboratory measurements, was similar to the upscaled PG in spring but closer to the measured GPP in the middle of the summer (Fig. 1a). In the autumn, all of the three estimates showed fairly similar levels (Fig. 1a).

Sphagna at the study site had a higher cumulative growing season PG value (138 g C m2) than vascular plants (92 g C m2). Sphagna had higher daily PG than vascular plants in spring and autumn but were almost at the same level in the middle of the summer (Fig. 2). A small increase in Sphagnum photosynthesis was observed during May (Figs. 2 and 3b) due to increments of daily PPFD towards midsummer. Otherwise, Sphagnum PG decreased steadily over the growing season (Fig. 2). Seasonal changes in vascular PG showed similar patterns to vascular LAI development, although the maximum PG was reached slightly earlier in the season than maximum LAI (Figs. 1a, c and 2).

The three vascular plant species with the highest PG in the ecosystem were C. vulgaris, R. alba and A. polifolia.A. polifolia was the most productive species in May and September, R. alba in June and July, and C. vulgaris in August (Figs. 3a and 4a). With 13 % cover altogether (Table 1), they formed 22 % of the seasonal ecosystem PG and 56 % of the vascular plant PG (Fig. 4). The three Sphagnum species with the highest PG at the ecosystem level were S. papillosum, S. fuscum and S. rubellum (Figs. 3b and 4b). As with all of the Sphagnum species, their PG per ground area decreased steadily over the growing season (Figs. 2 and 3b).With 42 % cover altogether (Table 1), they formed 40 % of

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( LAI + b)exp

0.5(Ta Topt)

2 !, (4)

where Ta is the air temperature, Topt is the temperature optimum of GPP and Ttol is the temperature tolerance of GPP

T 2

tol

262 A. Korrensalo et al.: Species-specic temporal variation in photosynthesis

0.51.01.52.02.53.03.5

(a)

PG

GPP in ambient T

GPP in 20 C

1 )

2 d

P G /GPP (g C m

JD Month

120 150 180 210 240 270

May June July August September

(b)

(c)

(d)

2 )

Air T (C)

051015202530

LAI ( m

0.000.100.200.30

WT (cm)

2015105

2 m

JD Month

120 150 180 210 240 270

120 150 180 210 240 270

May Jun Jul Aug Sep

May Jun Jul Aug Sep

120 150 180 210 240 270

May Jun Jul Aug Sep

The same vascular plant species had the highest growing season PN and PG; R. alba, C. vulgaris and A. polifolia had the highest PN estimates of 15.1, 9.1 and 8.4 g C m2, respectively (Table 1). These three species made up 57 % of the total vascular PN and 42 % of the whole ecosystem-level

PN.S. fuscum, S. papillosum and S. majus had the highest seasonal PN of Sphagnum species: 7.4, 6.8 and 2.8 g C m2, respectively (Table 1). The PN of these three species was 85 % of the total Sphagnum PN and 22 % of the seasonal ecosystem PN. Although having one of the highest coverage and PG values, S. rubellum was not among the three most productive species in terms of PN.

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Figure 1. (a) Comparison of total daily ecosystem-level gross photosynthesis estimate of all plants (PG) derived from laboratory measurements, with GPP estimates derived directly from the eddy covariance measurements and with GPP simulated at constant temperature of 20 C. The temperature in laboratory photosynthesis measurements was kept constant at 20 C during the whole growing season. (b) Daily mean air temperature (in black) and daily temperature variation (in grey ll; Hyytil Forest Research Station 10 km from the study site,

Finnish Meteorological Institute, 2016); (c) sum of modeled vascular leaf area during the growing season 2013 and (d) average daily lawn(i.e., intermediate) surface water table (WT) at the study site. Lines represent locally weighted scatterplot smoothing (Loess, smoothing parameter = 0.25) curves.

the seasonal ecosystem PG and 67 % of the PG of Sphagnum mosses (Fig. 4).

3.2 Cumulative growing season net photosynthesis

The aboveground vegetation of the study site was a carbon sink of 77 g C m2 over the growing season as estimated by PN values upscaled to the ecosystem level using the species- and month-wise light response curves. PN results for Sphagna and vascular plants were reversed in comparison to PG estimates; PN of Sphagna was 20 g C m2 and vascular

PN was 57 g C m2.

A. Korrensalo et al.: Species-specic temporal variation in photosynthesis 263

errors related to the LAI development measurements, visual species cover estimation, the conversion from cover to LAI and the laboratory measurements of photosynthetic parameters. Although the shading of the moss layer by vascular plants may gure as a potential error source of PG upscaled with PPFD measured above the vegetation, it is not likely to be caused by the sparse cover of vascular plants at the site (Supplement Fig. S3) with low seasonal maximum LAI (Fig. 1c). By taking into account the variation between samples in the 87 PN models (Eq. 1), we aimed at a more accurate estimation of the light response parameters. Nevertheless, our ecosystem-level PG estimate may contain bias caused by not accounting for the random effects of the 87 models in the upscaling procedure. The cumulative growing season PG of 230 g C m2 is very similar to the 205 g C m2 obtained by Alm et al. (1999) at an ombrotrophic bog site under similar climatic conditions and comparable water levels but where the exceptionally dry conditions during the measured season reduced the photosynthetic capacity of many Sphagnum species. Our growing season PG was considerably lower than the 500 g C m2 obtained by Moore et al. (2002) and Roulet et al. (2007) at a temperate ombrotrophic bog with much lower water table levels. While our value only covers the period from May until September, it falls just below the large range of annual GPP values (250 to 900 g C m2) measured with the EC method from seven northern peatland sites (Lund et al., 2010).

The shapes of PG and GPP development differed over the growing season, especially at the beginning of the summer, which is largely due to the constant temperature of 20 C in our laboratory measurements (Fig. 1a). The constant temperature allowed us to investigate how the changes in species-specic photosynthetic parameters were affected by the seasonal changes in moisture conditions in the eld. Since the measuring of species-specic temperature responses of PG was unachievable due to the large number of species, we instead chose to model the temperature dependence of EC-derived GPP (Eq. 4, Fig. 1a). Our upscaled PG values were higher than GPP in May when vascular plants had a high capacity to use low light levels (low k value) and Sphagna had high Pmax (Fig. 1a; Table S1), but this was the case when temperatures in the eld remained mostly below 20 C and limited the measured GPP (Fig. 1b). The temperature limitation of measured GPP is demonstrated by the lower springtime measured GPP in comparison with GPP simulated at 20 C (Eq. 4, Fig. 1a). Both measured GPP and GPP simulated at 20 C show higher levels than PG in July and August (Fig. 1a), the reason for which remains partly unclear.Because the difference between GPP and PG lasted for 2 months, the lack of vascular plant PG measurements in July can only partly explain this midsummer deviation between the two methods. In September, when Sphagnum Pmax values and k values of both vascular plants and Sphagna were at their lowest, PG, measured GPP and GPP at 20 C were all similar despite the difference between air and laboratory

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Figure 2. Daily gross photosynthesis estimates (g C m2 d1) of vascular plants and Sphagna upscaled to the ecosystem level using the species-specic, monthly light response curves derived from laboratory measurements. Lines represent Loess averaging (smoothing parameter = 0.25).

4 Discussion

4.1 Comparison of upscaled gross photosynthesis values with eddy covariance gross primary production estimates

Accounting for the differences in photosynthetic parameters between species and between phases of the growing season appeared to accurately estimate ecosystem PG when up-scaling species-level measurements. Sphagnum mosses especially showed a large seasonal variation in their photosynthetic light response, which could be accounted for in this upscaling approach. The similarity of the PG estimates calculated with species-wise and monthly light response curves and GPP estimates derived from EC measurements (Fig. 1a) adds credibility to the methods used and indicates that the photosynthetic parameters measured under laboratory conditions are comparable with eld measurements. Both methods have their error sources. Annual CO2 ux balances from EC measurements are prone to signicant systematic bias, sometimes in excess of 30 % but usually between 10 and 30 % of the cumulative ux (e.g., Baldocchi, 2003; Rannik et al., 2006). The underestimation of the EC uxes implicit in the unclosed energy balance (70 % for Siikaneva-1, unpublished data) might be partly compensated for by the Kok effect, which might be more signicant than previously thought, as indicated by Wehr et al. (2016). Our PG estimates include

264 A. Korrensalo et al.: Species-specic temporal variation in photosynthesis

moisture conditions at that time (Fig. 2), but the low eld temperatures limited ecosystem-level GPP (Fig. 1a and b).Temperature limitation of springtime photosynthesis is well known for boreal forests (Tanja et al., 2003; Ensminger et al., 2004), as well as for bog Sphagna (Moore et al., 2006). Mean annual temperature together with PPFD during the growing season are the most important factors explaining Sphagnum productivity on the global scale (Gunnarsson, 2005; Loisel et al., 2012), and the temperature optimum of Sphagnum photosynthesis is known to change over the growing season (Gaberik and Martini, 1987). However, the temperature dependence and acclimatization of species-level photosyn-thesis in peatlands has been studied only with a few Sphagnum species (Gaberik and Martini, 1987; Robroek et al., 2007).

4.2 The contribution of plant species to ecosystem-level gross photosynthesis

Among both Sphagna and vascular plants, the species with the highest seasonal upscaled PG (g C per m2 of ground area) and hence the most productive species on the ecosystem scale were also the ones with the highest areal cover.No interspecies differences in photosynthetic properties, either within vascular plants or Sphagna, could change this order. On the ecosystem scale, Sphagna covering on average 63 % of the ground area had higher upscaled daily PG values for the whole summer than vascular plants covering only 24 % despite the lower Pmax values of Sphagna (Table S1). In ombrotrophic bogs, Sphagna are known to be the rst group to start photosynthesizing in early spring (Moore et al., 2006), which was also evident at our site (Fig. 2). The combination of low Pmax values in July and September and high respiration rates in August and September (Table S2) resulted in an almost linear decrease in ecosystem-scale Sphagnum PG over the growing season (Fig. 2). The seasonally decreasing Sphagnum PG is likely to reect the change in the moisture conditions. Water table depth, which, together with precipitation, is known to be the most important moderator of Sphagnum photosynthesis (Hayward and Clymo, 1983;Backus, 1988; Lindholm, 1990; Nijp et al., 2014), decreased at the study site over the growing season (Fig. 1d).

Despite low Pmax values, R. alba was among the three vascular plant species with highest PG on the ecosystem scale due to its high cover at the site (Table 1). It also had a very sharp but short-lived LAI and PG peak at the end of June (Fig. 3a), which was largely the reason for the peak in vascular plant PG (Fig. 2), occurring slightly earlier in the season than maximum vascular LAI (Fig. 1c). Evergreen shrubs have been observed to be the second group to start photo-synthesizing after Sphagna in spring (Moore et al., 2006).Similarly, the vascular plants with the highest upscaled PG in May were the evergreen shrubs A. polifolia and C. vulgaris (Fig. 3a). The contributions of different species to total Sphagnum PG did not differ over the growing season

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Figure 3. Daily gross photosynthesis estimates (g C m2 d1) of the three most productive (a) vascular and (b) Sphagnum species upscaled to the ecosystem level using the species-specic, monthly light response curves derived from laboratory measurements. Lines represent Loess averaging (smoothing parameter = 0.25). The

species cover within the study site (EC footprint) is given in Table 1. Abbreviations of the species names are AndrPol: Andromeda polifolia; CallVul: Calluna vulgaris; RhynAlb: Rhynchospora alba; SphaFusc: Sphagnum fuscum; SphaPapi: Sphagnum papillosum; SphaRube: Sphagnum rubellum.

temperatures (Fig. 1a). According to our results peatland photosynthesis is temperature limited, especially in spring; Sphagna had a high photosynthetic potential due to favorable

A. Korrensalo et al.: Species-specic temporal variation in photosynthesis 265

P (g C m month )

(a)

4.3 Ecosystem-level net photosynthesis

The variation in photosynthetic properties changed the roles of the plant species into a seasonal ecosystem-level carbon sink. Although Sphagna had more than twice the cover of vascular plants, seasonal PN was much lower than vascular plants (Table 1). The seasonal PN of Sphagnum species was not proportional to their areal cover; for example, the species with the highest cover, S. rubellum, had a small seasonal PN (Table 1). S. rubellum has earlier found to have lower light-saturated photosynthesis and higher respiration than most of the other Sphagnum species (Table S1, Korrensalo et al., 2016a). The differences in photosynthetic parameters of Sphagnum species seem to become much more visible in ecosystem-level PN than in that of vascular plant species, since the leaf area of Sphagna stays similar over the growing season. The vascular plants most important for the ecosystem-level PN were the same as the species with the greatest cover. However, T. cespitosum, with only 1 % of areal cover, made up 12 % of the seasonal vascular PN.

Our results indicate that in addition to the areal cover of the species, differences in photosynthetic parameters between species shape the ecosystem-level carbon sink of a bog. Species with low areal cover may be important for the ecosystem carbon sink because of their high photosynthetic efciency. However, the PN results have to be interpreted with care, since they contain the R parameter estimated based on respiration measurements done at 20 C, which is higher than the eld temperature for most of the growing season.This general overestimation of respiration may be the reason behind a slightly negative seasonal PN of S. balticum (Table 1).

4.4 The role of functional diversity for peatland carbon sink

According to the insurance hypothesis, species diversity both enhances productivity and decreases the temporal variance of productivity of a plant community (Yachi and Loreau, 1999). This hypothesis has gained support from testing in several ecosystem types, especially in grasslands (Hector et al., 2010; Cardinale et al., 2011; Morin et al., 2014). In addition to species and genotype diversity (Hughes et al., 2008), the functional diversity, i.e., the presence of species and plant functional types with different physiology, morphology, resource requirements, seasonal growth patterns and life history may increase the productivity of an ecosystem (Tilman et al., 1997; Cadotte et al., 2008). Although this study did not directly test the insurance hypothesis, our results also indicate that functional diversity, especially in regard of differences in phenology and seasonal changes in photosynthetic parameters, decreased the temporal variation of ecosystem-level PG and could therefore decrease the variation of the ecosystem C sink. Vascular plant species of different phenology had the highest ecosystem-level photosynthesis at dis-

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0102030405060

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Figure 4. Species proportions of monthly ecosystem-scale gross photosynthesis (PG) of (a) vascular plants, (b) Sphagnum mosses and (c) the contribution of those two groups to total monthly ecosystem-scale PG. Ecosystem-level PG was calculated using the species-specic, monthly light response curves derived from laboratory measurements. For abbreviations of the species names, see Fig. 3.

(Fig. 4). Based on these observations, phenology and areal cover rather than differences in photosynthetic parameters among species seem to be the key factor in determining the species with the highest PG of a bog ecosystem.

266 A. Korrensalo et al.: Species-specic temporal variation in photosynthesis

tinct phases of the growing season (Fig. 3a). In addition, Sphagna and evergreen shrubs formed two stable baselines of ecosystem PG, which was further increased by the midsummer PG peak of the sedge R. alba (Fig. 3a and b). Especially ecosystem-level Sphagnum PG was modied by the seasonal decrease in photosynthetic potential (Table S1). This suggests that the growing season PG of our study site is not only more stable, but it is also larger than it would be with a more functionally homogenous assemblage of species. Several studies have suggested that the C sink function of bogs is more stable over the growing season than that of fens, which have more homogenous and sedge-dominated vegetation (Bubier et al., 1998; Leppl et al., 2008). Hence, our results should be compared with the patterns of photosynthetic productivity of a peatland site with a more homogenous plant assemblage.

Based on small-scale experimental studies, bog species and growth forms are known to vary in terms of their contribution to ecosystem productivity and to differ in their responses to manipulations of environmental conditions (Weltzin et al., 2000; Ward et al., 2009; Kuiper et al., 2014).In this study, the laboratory measurements of species photo-synthetic parameters were for the rst time upscaled to the ecosystem level over a whole growing season and veried by the comparison with EC measurements. Boreal bog species were found to differ in the timing of their maximum PG over a growing season (Fig. 3a and b). Diversity in species responses to environmental factors is hypothesized to make a plant community more resilient towards changing conditions (Yachi and Loreau, 1999; Gunderson, 2000). In addition to species diversity, plant community diversity within an ecosystem has been shown to increase ecosystem stability during a severe drought in grasslands (Frank and Mc-Naughton, 1991). In boreal bogs, Sphagnum mosses create microtopographic variations that according to model simulations increase resilience towards environmental perturbations both through the diversity of growth forms they support and by variation in physical properties between micro-forms (Turetsky et al., 2012). To nd out about the effect of bog spatial heterogeneity on ecosystem resilience, studies extending over several growing seasons are needed. As demonstrated in an arctic sedge fen, the impact of extreme weather conditions on an ecosystem C sink may occur with a lag of one growing season (Zona et al., 2014). Our study provides tools to empirically study the role of species and community diversity on the ecosystem scale. The combination of laboratory measurements of photosynthetic parameters, phenological monitoring and EC measurements opens up the possibility of long-term and experimental ecosystem-level studies on the effect of functional diversity on the peatland ecosystem carbon sink. The long-term measurements would permit the inclusion of a wider range of environmental conditions.In particular, the EC method would allow for a comparison of the effect of diversity at sites with different plant assemblages.

5 Conclusions

The areal cover of the species determined the species with the highest gross photosynthesis, while phenology in leaf area and photosynthetic activity drove the variation in ecosystem-level gross photosynthesis. In spring, potential ecosystem-level gross photosynthesis was much higher than measured gross primary production, which appeared to be due to temperature limitation of photosynthesis. Ecosystem-level net photosynthesis was more of a combination of the differences in (i) photosynthetic parameters, which were important in Sphagna, (ii) phenology, which largely dened vascular productivity, and (iii) areal coverage, which acted in both vascular plants and Sphagna.

The different growth strategies of the plant species present at our study site appeared to increase the ecosystem-level photosynthesis and decrease its variation within a growing season. We are looking forward to the future studies nding out if the diversity of growth forms has the same stabilizing effect on the interannual variation of ecosystem-level photo-synthesis.

6 Data availability

The data associated with the paper are published in the PANGAEA repository under doi:http://dx.doi.org/10.1594/PANGAEA.862986

Web End =10.1594/PANGAEA.862986 (Korrensalo et al., 2016b).

The Supplement related to this article is available online at http://dx.doi.org/10.5194/bg-14-257-2017-supplement

Web End =doi:10.5194/bg-14-257-2017-supplement .

Competing interests. The authors declare that they have no conict of interest.

Author contributions. Eeva-Stiina Tuittila formulated the idea for this paper. Aino Korrensalo, Tom Hjek and Eeva-Stiina Tuittila designed the measurements, which were done by Aino Korrensalo and Tom Hjek. Aino Korrensalo, Tom Hjek and Eeva-Stiina Tuittila were responsible for the primary photosynthesis data processing. Eddy covariance data collection and analysis was done by Pavel Alekseychik, Janne Rinne, Timo Vesala and Ivan Mammarella. The mixed-effects models were developed by Lauri Mehttalo and Aino Korrensalo. Aino Korrensalo, Pavel Alekseychik and Eeva-Stiina Tuittila wrote the paper, on which all the other authors commented.

Acknowledgement. The work presented here is supported by the Faculty of Science and Forestry at the University of Eastern Finland, the Finnish Cultural Foundation, the Academy of

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A. Korrensalo et al.: Species-specic temporal variation in photosynthesis 267

Finland (287039, 118780, 1284701, 1282842), ICOS (271878), ICOS-Finland (281255) and the Nordic Centre of Excellence DEFROST. We would also like to thank the staff at Hyytil Forest Research Station and Salli Uljas, Janne Sormunen, Mara Gutierrez, Laura Kettunen and Eva-Stina Kerner for their help with the measurements and Nicola Kokkonen for revising the English language of the paper.

Edited by: P. StoyReviewed by: three anonymous referees

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