Oecologia DOI 10.1007/s00442-017-3829-0

PHYSIOLOGICAL ECOLOGY - ORIGINAL RESEARCH

Stomatal CO2 responsiveness and photosynthetic capacity of tropical woody species in relation to taxonomy and functional traits

Thomas B. Hasper1 · Mirindi E. Dusenge1,2 · Friederike Breuer1 · Félicien K. Uwizeye2 · Göran Wallin1 · Johan Uddling1

Received: 27 November 2015 / Accepted: 22 January 2017 © The Author(s) 2017. This article is published with open access at Springerlink.com

Abstract Stomatal CO2 responsiveness and photosynthetic rather than to area-based total leaf N content. Within-leaf capacity vary greatly among plant species, but the factors N allocation and water use were strongly co-ordinated controlling these physiological leaf traits are often poorly (r2 0.67), such that species with high fractional N invest- = understood. To explore if these traits are linked to taxo- ments into compounds maximizing photosynthetic capac- nomic group identity and/or to other plant functional traits, ity also had high stomatal conductance. We conclude that we investigated the short-term stomatal CO2 responses and while stomatal CO2 responsiveness of tropical woody spe- the maximum rates of photosynthetic carboxylation (Vcmax) cies seems poorly related to other plant functional traits, and electron transport (Jmax) in an evolutionary broad photosynthetic capacity is linked to fractional within-leaf N range of tropical woody plant species. The study included allocation rather than total leaf N content and is closely co- 21 species representing four major seed plant taxa: gym- ordinated with leaf water use. nosperms, monocots, rosids and asterids. We found that stomatal closure responses to increased CO2 were stronger Keywords Carbon dioxide · Transpiration · Leaf traits · in angiosperms than in gymnosperms, and in monocots Stomatal patterning · Tropical trees compared to dicots. Stomatal CO2 responsiveness was not significantly related to any of the other functional traits investigated, while a parameter describing the relation- Introduction ship between photosynthesis and stomatal conductance in combined leaf gas exchange models (g1) was related to Anthropogenic fossil fuel burning and land use change leaf area-specific plant hydraulic conductance. For photo- have increased the atmospheric carbon dioxide concentra- synthesis, we found that the interspecific variation in Vcmax tion [CO2] by over 40% (Ciais et al. 2013), with today’s 1 and Jmax was related to within leaf nitrogen (N) allocation concentration of over 400 μmol mol− being the highest in approximately 40 millions years (Frank et al. 2015). This

large and rapid ongoing increase in [CO2] has profound Communicated by Bettina Engelbrecht. impacts on land plants, which typically respond to altered [CO2] by increasing leaf photosynthesis (A) and decreas- Electronic supplementary material The online version of this ing stomatal conductance (gs; Ainsworth and Rogers 2007). article (doi:10.1007/s00442-017-3829-0) contains supplementary However, the direct stomatal responses to a short-term material, which is available to authorized users. increase in [CO2] vary greatly among species and experi- * Johan Uddling ments, from no change to 75% reduction in gs at doubled [email protected] compared to ambient [CO2] (Morison 1998). Understand- ing this variation is important, since the short-term stoma- 1 Department of Biological and Environmental Sciences, University of Gothenburg, PO Box 461, 405 30 Gothenburg, tal CO2 response appears to be an important determinant Sweden for the long-term effect of growth in elevated [CO2] on gs 2 Department of Biology, University of Rwanda, University under field conditions. In so called free-air CO2 enrichment Avenue, PO Box 56, Huye, Rwanda (FACE) experiments with trees, the interspecific variation

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in long-term (years) effects of growth under elevated [CO2] Short-term gs responses to [CO2] (%) on gs was significantly and positively related to the varia- -12-10 -8 -6 -4 -2 tion in short-term stomatal CO2 responsiveness, measured Betula as the effect of short (hours) interruptions in CO enrich- papyrifera 2 0 ment on sap flow (Cech et al. 2003; Keel et al. 2007; Tor- Fagus ngern et al. 2015) or leaf gs (Maier et al. 2008; Domec et al. -5 Quercus sylvatica 2009; Onandia et al. 2011) in some of these experiments petraea ] (% ) responses 2 2 s Pinus (Fig. 1; r 0.81; P 0.014). Tree species that exhibit g -10 Tilia platyphyllos = = taeda a pronounced direct stomatal closure response to a short- Acer campestre

to [C O -15 Prunus avium term increase in [CO2] are thus also likely to develop a long-term gs reduction in the field. Therefore, a better y = 2.02x + 2.52 Long-term 2 understanding of the factors that control the large natural -20 Carpinus r = 0.81 betulus P = 0.014 variation in short-term stomatal CO2 responses would pro- vide indication of which plant species and groups that are likely to experience large increases in water-use efficiency Fig. 1 Relationship between the short-term response of gs to elevated in future higher [CO ] scenarios. [CO2] [measured during short (hours) interruptions in CO2 enrich- 2 ment] and the long-term effect of growth under elevated [CO ] on Both the short-term stomatal CO response and the long- 2 2 gs in temperate forest free-air CO2 enrichment (FACE) experiments. term effect of growth under elevated [CO2] on gs have been Regression statistics are shown in the figure. Based on data from found to be weaker in gymnosperms compared to angio- Cech et al. (2003), Keel et al. (2007), Maier et al. (2008), Domec sperms (Medlyn et al. 2001; Brodribb et al. 2009). Brodribb et al. (2009), Onandia et al. (2011) and Tor-ngern et al. (2015) et al. (2009) even suggested that gymnosperms lack a pri- mary stomatal CO2 response, while others have found that types and in different biomes (Lin et al. 2015). In angio- this is not the case (Haworth et al. 2013). To our knowl- sperm trees, it was found that g1 was positively related to edge, there has been no study designed to explore possi- wood density, reflecting a higher cost of wood construction ble taxonomic patterns in the large interspecific variation in per unit water transported in species with higher wood den- stomatal CO2 responsiveness among different angiosperm sity (Lin et al. 2015). However, the relationship with wood taxa. Furthermore, possible functional determinants of the density was quite weak (r2 0.21; Lin et al. 2015) and = interspecific variation in stomatal CO2 responsiveness have when gymnosperms were included it was not significant also been poorly explored. If stomatal CO2 responses are at all. There is thus a need to further explore the relation- linked to physiological, chemical or structural plant traits ship of g1 with wood density and other plant traits, such as for which more knowledge is available, this could facili- hydraulic conductance. Hydraulic conductance and gs are tate future trait-based modelling of plant water-use under often co-ordinated in trees (Brodribb and Jordan 2008) and rising [CO2] (Van Bodegom et al. 2012). For example, it since high hydraulic conductance essentially reduces the is possible that (but unknown if) stomatal CO2 responsive- carbon cost of water use (Prentice et al. 2014) it is plausible ness is linked to stomatal density since, in general, plants that (but unexplored if) g1 is positively related to hydraulic with high stomatal density have more efficient stomatal conductance. With respect to taxonomic patterns, there are regulation (Franks et al. 2009). It is also plausible that sto- typically distinct differences in water-use strategy between matal CO2 responsiveness is linked to hydraulic traits since angiosperm and gymnosperm trees, with angiosperms typi- plants with high hydraulic conductance often exhibit tight cally exhibiting higher gs, hydraulic conductance and g1 at stomatal control over transpiration to avoid severe cavita- the expense of considerably smaller hydraulic safety mar- tion (Bond and Kavanagh 1999). Since stomatal regulation gin compared to gymnosperms (Choat et al. 2012; Lin et al. is an energy consuming process, CO2 sensitivity may also 2015). be linked to indicators of leaf metabolic activity, such as There is also considerable uncertainty with respect to the photosynthetic capacity. variation in the maximum rates of photosynthetic carboxy-

Most land-surface and ecosystem models apply com- lation (Vcmax) and electron transport (Jmax) among plant spe- bined stomatal–photosynthesis models (Ball et al. 1987; cies in general (Ali et al. 2015) and tropical tree species in Leuning 1995; Medlyn et al. 2011), in which plant car- particular (Dusenge et al. 2015). Current vegetation models bon and water vapor fluxes are linked as they both pass typically base their values of Vcmax and Jmax on area-based through plant stomata. The empirical slope parameter of total leaf N content (e.g., Zaehle et al. 2005; Rogers 2014). the combined stomatal–photosynthesis model (g1), which However, a recent global meta-analysis found that Vcmax is inversely proportional to leaf water use efficiency (at and Jmax were more closely related to within-leaf nitrogen constant environmental conditions; Medlyn et al. 2011), (N) allocation than to total leaf N content (Ali et al. 2015), has been determined for a large number of plant functional as also observed in two studies with tropical tree species

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(Coste et al. 2005; Dusenge et al. 2015). Part of the reason woody plants of 21 species growing at four locations in for why interspecific variation in photosynthetic capacity the surroundings of Butare, Huye district, Rwanda, central is often poorly related to total leaf nutrient content may be Africa: Rwanda Agriculture Board (RAB) Ruhande Arbo- linked to differences in within-leaf N allocation among spe- retum (“Arboretum” hereafter; 2°36′55.2′′S, 29°44′53.8′′E; cies with different successional strategies. It is well estab- 1700 m asl; 17 species), Ruhande Fisheries Research Sta- lished that early-successional species invest more leaf N tion (2°36′22.1′′S, 29°45′29.7′′E; 1650 m asl; one species), into N-rich molecules involved in photosynthesis and res- Marist Missionary Sisters of the Society of Mary’s garden piration compared to late-successional tree species, which (2°36′32.1′′S, 29°44′37.6′′E; 1700 m a.s.l.; two species) typically have larger fractional N investments in rather and RAB Rubona station (2°38′57.1′′S, 29°45′54.2′′E; N-poor structural compounds (Raaimakers et al. 1995; Val- 1690 m a.s.l.; one species). The Arboretum was estab- ladares and Niinemets 2008). Dusenge et al. (2015) further lished in 1934 and since then has gathered 227 tree species suggested that there is a trade-off in how the photosynthetic (50 native to Rwanda) planted, in most part, as replicated leaf N is invested, with pioneer species making higher (n 3) monospecific 50 50 m plots within its 200 ha = × relative investments into compounds maximizing photo- plantation area. Out of the 21 species investigated five were synthetic carboxylation and bioenergetics (i.e., Vcmax and native to Africa and 16 were exotic (Table 1). Jmax) and climax species investing more into compounds The nearest meteorological station is located ca. 2 km involved in light-harvesting. However, that study included from the Arboretum, showing for the period 2006–2013 a rather small number of species and this hypothesis, there- mean day and night air temperatures of 20.8 and 17.1 °C, fore, needs to be further evaluated by field data. respectively, average humidity of 74%, and mean annual Tropical forests have a fundamental role in the global rainfall of 1231 mm. The climate of the region is character- carbon and water cycles and in controlling the rate of cli- ized as tropical humid, with 1.5 °C difference between the mate change (Lewis 2006). They account for about a third warmest and coolest months. Precipitation exhibits some of the global terrestrial primary production (Beer et al. seasonal variation, with the highest and lowest amounts 2010) and their evapotranspiration regulates regional tem- occurring in March–May and June–August, respectively. perature and precipitation and runoff patterns (Bonan 2008). Additional meteorological information can be found in Given all the challenges associated with research in tropical Nsabimana et al. (2009) and Vårhammar et al. (2015). forests (e.g. large stature, biological complexity and logis- The 21 species were selected to represent a broad evo- tics), much less is known about stomatal regulation and lutionary cross-section of seed plant species, representing photosynthesis of trees in these ecosystems compared to four major lineages of seed plants: gymnosperms, mono- temperate forests (Kattge et al. 2009). To improve the poor cots [commelinids], rosids and asterids (Table 1). Of the understanding of the phylogenetic and functional controls selected species, 16 were silviculturally or agriculturally of the large interspecific variation in stomatal CO2 respon- important exotics, while five were native tropical species. siveness and photosynthetic capacity among tropical woody All species exhibited a woody stem and plants investigated species, we examined physiological, chemical and structural were older than two years. In this study, we define wood plant traits in an evolutionary broad cross-section of tropi- as tissue produced of secondary xylem, including highly cal woody seed plant species in a common garden experi- lignified xylem tissue in secondary vascular bundles in ment in Rwanda. The specific objectives were to answer monocots. The focus on tropical woody species minimized the following three research questions: (1) Does the stoma- sources of variation related to growth form and climate of tal response to a short-term increase in [CO2] vary among origin, thereby increasing the chance of finding possible major taxonomic groups? (2) What functional characteris- taxonomic patterns. For each species, measurements were tics can explain the interspecific variation in stomatal behav- done on five individual plants, measuring leaf gas exchange ior (i.e. in the short-term CO2 response and g1)? (3) Is the on one fully developed leaf of each individual (except for interspecific variation in photosynthetic capacity controlled Phoenix reclinata, where two and three leaves were meas- by differences in within-leaf nutrient allocation rather than ured in each of two different plants). by differences in total area-based leaf nutrient content? Gas exchange measurements

Materials and methods Leaf gas exchange measurements were conducted in situ between 09:00 and 15:00 h using two portable photosyn- Study sites and plant material thesis systems (LI-6400 and LI-6400XT with the 2 3 cm × standard leaf chamber and LI-6400-02B LED light source; From February 27 until March 25 in 2014, data were col- Li-Cor Inc., Lincon, NE, USA). For each species, five fully lected on mature (having reached reproductive stage) developed, visually healthy, sun-exposed leaves (one per

1 3 Oecologia ~2008 2012 1943 1984 1943 1934 1945 1948 1934 1943 ~2009 2008 ~2009 1934 2005 1955 ~2004 1948 1959 1948 Stand planted (year) 1938 BL BL BL BL BL BL BL BL BL BL BL BL BL BL BL NL BL NL NL NL Leaf shape NL EG EG EG EG DE DE EG EG EG EG EG EG EG EG EG EG EG EG EG EG Leaf longevity EG 1.8 2.7 5.1 9.1 14.9 42.4 22.2 19.9 15.7 15.0 5.6 8.0 2.2 5.0 6.4 39.2 22.0 19.7 66.9 36.6 Mean DBH (cm) 19.2 37 c 67 30 75 8 111–112 11 6 65 b 224 b 26 293 2 a 43 48 144 Plot 47 Exotic Exotic Exotic Exotic Exotic Exotic Exotic Native Exotic Exotic Exotic Native Exotic Exotic Exotic Native Native Native Exotic Exotic Origin Exotic - A.Gray Oken (A.Cunn. Ex G.Don) Macar thur & C. Morre K.D. Hill & L.A.S. Johnson (Pax.) Pavon Munro R.Br. ex Mirb ex R.Br. R.Br. ex Mirb. ex R.Br. Kuntze (Hemsl.) diversifolia Tithonia Cyphornandra betaceae Cay. Cyphornandra W. T.Aiton Ligustrum lucidum W. (Ruiz & Pay.) (Ruiz & Pay.) alliodora Cordia Brachychiton acerifolius Brachychiton Jacaranda rnirnosifolia D.Don Jacaranda Royle serrata Cedrela Sprage grandiflora Carapa Eucalyptus maculata (Hook.) Prunus caretta Musa sapientum L. kilirnandscharica Macaranga Ruiz & Heliconia rostrata Bambusa vulgaris Schrad. Bambusa Dendrocalamus giganteus Dendrocalamus (Thunb.) falcatus (Thunb.) Podocarpus Jacq. Phoenix reclinata (Thunb.) latifolius (Thunb.) Podocarpus Pinus patula Schlecht. & Cham. Cupressus lusitanica Mill. Cupressus Species Araucaria angustifolia (Bertol.) Araucaria Asteraceae Solanaceae Oleaceae Boraginaceae Malvaceae Bignoniaceae Meliaceae Meliaceae Myrtaceae Rosaceae Musacea Chrysobalanaceae Heliconiaceae Poaceae Poaceae Podocarpaceae Arecaceae Podocarpaceae Pinaceae Cupressacaea Family Araucariaceae Asterales Solanales Lamiales Lamiales Malvales Lamiales Sapindales Sapindales Myrtales Rosales Zingiberales Malphigiales Zingiberales Poales Poales Pinales Arecales Pinales Pinales Pinales Order Pinales Tree species description and their plot location at the Ruhande Arboretum species description and their plot location at the Ruhande Tree Asterids Rosids Dicots Monocots (Commelinids) Angiosperms 1 Table Group DE deciduous, NL needle leaf, BL broadleaf) DBH diameter at breast high, EG evergreen, Arboretum Adjacent to the a Fisheries Research Station Garden b Marist Missionary Sisters of the Society Mary’s c RAB Rubona station Gymnosperms

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plant) were selected and measured for the response of net leaf conductance for CO2 was not estimated and, therefore, photosynthetic rate (An) to eight different [CO2] [so called ‘apparent’ Vcmax and Jmax values are reported, based on Ci A-C curves; C leaf intercellular (CO )]. In large trees, rather than on the [CO ] at the chloroplast. The uncertainty i i = 2 2 the measured leaves were attached to lower sun-exposed of the values of the curvature of the light-response (0.9) branches by the edge of the stand. All measurements were and quantum yield of electron transport (0.3 mol electrons 1 conducted at a photosynthetic photon flux density (PPFD) mol− photons) used when calculating Jmax from J has only 2 1 of 1800 µmol m− s− and a leaf temperature of 25 °C. Fol- a minor effect on the estimated value of Jmax (Medlyn et al. lowing the A-Ci curve measurements, direct responses of 2002). Values of Vcmax, Jmax and Rd were determined simul- gs to a short-term change in leaf chamber [CO2] (600 vs. taneously with the only a priori restriction made to the 1 1 400 μmol mol− ) were measured on the same leaves, at A C fitting that data points with C below 100 µmol mol− − i i the same leaf temperature and PPFD. Measurements were were forced to be Vcmax-limited. The discontinuity of the taken every minute and the steady-state g at each [CO ] transition from V - to J -limitation in the A C curve s 2 cmax max − i was recorded after gs values had stabilized for at least was not smoothed out. Jmax values were reported only if 15 min and changed 2% within a 5 min period. The order the A limited part of the A C curve had at least two data ≤ j − i of the [CO2] applied was randomized for the first leaf of points, or from one single data point if Aj was at least 10% a species, and then alternated for the remaining leaves of lower than Ac at the Ci value of that data point. The latter that species. For each leaf, the leaf-to-air vapour pressure was the case in nine leaves only and the Jmax value of these deficit (D) was kept constant ( 0.03 kPa) around a leaf- leaves were similar to those of the other leaves. Light-satu- ± 1 specific value in the range 1.15–1.80 kPa during the entire rated net photosynthesis at a Ci of 280 µmol mol− (An280; measurement. i.e. assuming a Ci that is 70% of an ambient CO2 concen- 1 Shoots of needle-leaf species were also measured using tration of 400 µmol mol− ) was calculated based on the fit- the standard leaf chamber. Needles were removed at the ted photosynthesis model for each leaf. points where the shoot axis passed the chamber gasket. Leaf-specific values of g1 were calculated from Needles were scanned (Epson V200 Perfection, Epson the steady-state leaf gas exchange measurement at 1 America Inc., USA) and their projected surface area were 400 μmol mol− CO2 concentration of the air, according estimated using WinRHIZO analysis software (Win- the model for optimal stomatal conductance given in Med- RHIZO, Regent Instruments Inc., Canada), and leaf and lyn et al. (2011): needle temperatures were calculated using energy balance g1 An equations. gs g0 1.6 1 (3) ≈ + + √D Ca

Photosynthesis model parameterization where g0 is the gs at zero An, 1.6 is the ratio of the diffusivi- ties of water vapour and CO2, and Ca is the [CO2] of the air 1 The photosynthesis model by Farquhar et al. (1980), with surrounding the leaf (µmol mol− ). Values of g0 are often modifications of photosynthetic temperature dependencies small (Medlyn et al. 2011) and were assumed to be zero by Bernacchi et al. (2001), was used to parameterize Vcmax in the present study. The model parameter g1, which is the and Jmax from A-Ci curve data by the least squares method. key parameter of the optimal stomatal conductance model The rates of Vcmax-limited net photosynthesis (Ac) and Jmax- and inversely related to water use efficiency, could thus be limited net photosynthesis (Aj) were calculated using: analytically calculated for each individual leaf.

Vcmax(Ci Γ ∗) A R Additional leaf traits c − d (1) = C K 1 O − i c Ko + +  After the gas exchange measurements, epidermal impres- and sions of around 2 cm2 of the center of the left part of the abaxial leaf surface were made from all measured leaves Ci Γ ∗ Aj J − Rd (2) except Tithonia diversifolia (due to its hairy leaf surface) = 4Ci 8Γ − + ∗ to determine stomatal density and length. A thin layer of where Kc and Ko are Michaelis–Menten constants for CO2 nail varnish was carefully peeled off after 10 min drying, and O2, respectively; Γ* is the [CO2] at which the carboxy- and was gently placed over a microscope slide and covered lation reaction of Rubisco equals the oxygenation reaction; and sealed by a cover slip. Six photos of evenly distributed

Rd is the non-photorespiratory CO2 release in the light; areas of each peel where taken using a microscope (Zeiss, and J is the rate of electron transport. For Kc, Ko and Γ*, Axio Scope.A1, Germany) equipped with a digital camera the values at 25 °C as well as the temperature sensitivi- (Zeiss, AxioCam MRm, Germany) using 100 magni- × ties were taken from Bernacchi et al. (2001). The internal fication. The photos were treated for higher contrast and

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definition using ImageJ 1.48v software before measure- pre-dawn Ψleaf measurements were done in the last day ments of stomatal density and guard cell length. Stomatal of the measurement campaign (except for Phoenix rec- density was estimated by calculating the average number linata, Musa sapientum, Heliconia rostrata and Cypho- of stomata per mm2 from the six photos taken from each mandra betaceae). The measured values of pre-dawn peeling, except in Macaranga kilimandcharica where pho- Ψleaf were high, and this variable likely did not vary tos could be used from only one of the five peels. Stomatal much over the 1 month measurement campaign since length was estimated by calculating the average of 30 ran- precipitation was quite high and temperature similar domly chosen guard cell pairs from three of the six photos in both March (109 mm/19.5 °C; measurement month) taken (10 from each photo). The estimates of stomatal den- and February 2014 (89 mm/19.2 °C; preceding month). sity and length were used to calculate the maximal gs that The evening before the pre-dawn Ψleaf measurements, was anatomically possible (gsmax) according to Franks and one leaf per tree was kept in darkness inside a water Beerling (2009): vapour saturated Ziploc plastic bag covered in alumin- ium foil. At pre-dawn on the following day (ca. 05:00 h) dw/v ρ amax gsmax ∗ ∗ (4) the plastic bags were collected and pre-dawn Ψleaf was = l π/2√amax/π + measured and used as an estimate of soil water potential 2 1 where dw is the diffusivity of water vapour (0.26 m s− ), (Ψsoil). From data of Ψsoil (i.e., pre-dawn Ψleaf), leaf tran- 3 1 v is the molar volume of air (24.47 dm mol− ), ρ is the spiration (E), leaf temperature and Ψleaf, leaf area-spe- 2 number of stomata per m , amax is the area of a fully open cific plant hydraulic conductance (Kp) was determined stomatal pore (m2) and l is the depth of stomatal pore according to: (m). Assumptions used in the calculation of stomatal pore vE length, width and depth in relation to guard cell length Kp ˜ ( 5) = ψsoil ψleaf were the same as in Franks and Beerling (2009). − Leaf length, width and thickness were recorded. Leaf where ṽ is the relative temperature dependent kinematic discs of known area were punched from each leaf, avoiding viscosity of water (set to 1 at 20 °C; dimensionless). Val- major veins, to determine leaf mass per unit area (LMA) ues of ṽ were calculated using leaf-specific values of leaf and leaf N and phosphorus (P) content. Leaves of species temperature, which may be a fair simplification since the with needles (Cupressus lusitanica, Pinus patula, Arau- leaf accounts for about half of the whole-plant hydraulic caria angustifolia, Podocarpus latifolius, Podocarpus resistance (Sack and Holbrook 2006). Soil water poten- falcatus) or small leaves (Jacaranda mimosifolia) were tial values for the three species lacking pre-dawn data scanned (Epson Expression 1600, Epson America Inc., CA, were taken as the mean value across all other species. USA) and projected leaf surface area was determined using A 3 cm piece of wood on a branch close to the meas- WinRhizo software (2007, Regents Instruments, Canada). ured leaf was cut and its volume (without the bark) was The collected leaf material was dried to constant weight measured by immersion in a volumetric cylinder on an at 70 °C before dry mass was recorded. The leaf discs and analytical balance (except for H. rostrata and M. sapien- needles were milled using a ball mill (Retsch MM301, tum which have pseudostem). All pieces of wood were Haan, Germany) and leaf N concentration was determined later dried to constant weight at 70 °C and wood mass using an elemental analyser (Europe EA-GSL, Sercon Ltd., and density were determined. Crewe, UK) coupled to a stable isotope ratio mass spec- The fractional leaf N investments were determined for trometer (20-22, Sercon Ltd. Crewe, UK). Leaf P content the following components of the photosynthetic appara- was determined for three leaves per species by first treat- tus: Rubisco (NR); bioenergetics, including coupling fac- ing samples with the Kjeldahl method and later analyzing tors, electron carriers except for photosystems, and Cal- them with a continuous flow automated analyzer (SEAL vin-Benson cycle enzymes except for Rubisco (NB); and Analytical, AutoAnalyzer 3HR, Norderstedt, Germany). light-harvesting complexes and photosystems (NLH). The Leaf chlorophyll content was determined by extraction of NR was estimated using the equation and parameters pro- leaf samples in 80% acetone and subsequent filtering and vided by Niinemets and Tenhunen (1997): spectrophotometric absorbance measurement, as described 0.16Vcmax by Uddling et al. (2007). NR (6) N V Immediately after the gas exchange measurements, = a cr leaves were collected and leaf water potentials (Ψleaf, where Vcmax is the maximum rate of carboxylation, 0.16 1 MPa) were measured using a Scholander type pressure converts Rubisco to N [g N in Rubisco (g Rubisco)− ] and chamber (SAPS II Model 3115, Soilmoisture Equip- Vcr the specific activity of Rubisco at 25 °C [20.78 μmol 1 1 ment Corp., Santa Barbara, CA, USA). In addition, CO2 (g Rubisco)− s− ]. The NB was estimated as:

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a b ab ab ]

2 (a) (e) 0.5 -10 ) ] (% ) -1 0.4 2 s

-2 -20 0.3 -30 change at

0.2 s (mol m g

at ambient [C O -40

s 0.1 elevated [C O g ) -1 (b) (f) s 6 -2 25 5 20 4 1 mol m

15 g

( 3 10 2 n280

A 5 1 ) -1 ) (c) (g) -1 O

120 2

s 8 -2 100 80 6 mol H 2 mol m 60 WUE 4 ( 40

cmax 2 20 V (mmol CO

) a ab ab b

) (d) (h) -1

-1 6

s 200 -2 5 MPa

150 -1 p

s 4 -2 K mol m

100 m 3 ( 2

ma x 50 J 1 (mmol

GYMMON ROS AST GYM MONROS AST

Fig. 2 Physiological traits in different taxonomic groups: a stoma- f g1 (see Eq. 3); g water use efficiency (WUE); and h leaf area-spe- tal conductance (gs) at ambient [CO2]; b net photosynthetic rate at cific plant hydraulic conductance (Kp). Each data point represents the 1 280 µmol mol− intercellular [CO2] (An280); c maximum rate of car- mean value of a species and thick black lines represent mean values boxylation (Vcmax); d maximum rate of electron transport (Jmax); e of the taxonomic groups. GYM gymnosperms; MON monocots; ROS 1 short-term gs response to increased [CO2] (600 vs. 400 μmol mol− ); rosids; and AST asterids

2 Jmax where Chl is the area-based chlorophyll content (g m− ), NB (7) = Na 156 8.06 0.0155 is the mass fraction of one mole N to one mole × chlorophyll, and 41 is the N content per unit chlorophyll where it is assumed that N in bioenergetics is propor- in light-harvesting complexes and photosystems in sun- 1 tional to Jmax, that 156 is the ratio of electron transport exposed leaves in mol mol− . 1 1 to cytochrome f content in mol mol− s− and that 8.06 is the amount of cytochrome f per unit N in bioenergetics in Statistical analysis 1 μmol g− (Evans and Seemann 1989; Niinemets and Ten- hunen 1997). The sum of NR and NB (NR B) was used as One-way analysis of variance (ANOVA) with Scheffe’s a measure of leaf N in compounds determining+ the maxi- posthoc test was performed using SPSS 21 software (IBM, mum photosynthetic rate, i.e. photosynthetic capacity. New York, USA) to test whether structural, chemical and

The NLH was estimated according to Evans and Poorter physiological characters differed significantly among the (2001) as: studied taxonomic groups. No heterogeneity of variance was found according to Cochran’s C test, but in two cases 0.0155 41Chl NLH × (8) where data distributions were skewed (stomatal density and N = a LMA), log-transformation was performed prior to ANOVA

1 3 Oecologia tests. Linear regression and Pearson’s correlation statis- a ab b ab (a) ) tics to test the significance of relationships between the -2 800 measured structural, chemical and physiological variables 600 were also performed using SPSS 21. In three cases there were duplicate species represented within the same family 400

(stomata mm 200

(Podocarpaceae, Poacea and Meliaceae; Table 1). Replac- Stomatal density ing species-specific data of these six species with the fam- ily-specific mean values did not change the significances of (b) any of the group comparisons or regressions of the study h 40 (data not shown). 30 m)

( 20

Results Stomatal lengt 10

(c) Taxonomic group comparisons ) -1 5 s -2 1 4 Values of gs at 400 µmol mol− [CO2] did not significantly differ among taxonomic groups, with asterids having the 3 highest mean but also the highest variation (Fig. 2a). Simi- (mol m 2 smax

g 1 larly, neither An280 nor Vcmax or Jmax differed significantly among these groups (Fig. 2b–d). All taxonomic groups exhibited significant stomatal closure responses to a short- (d) term increase in [CO ], (Fig. 2e). Gymnosperms had a sig- 0.8 2 ) nificantly weaker response ( 12%) than monocots ( 29%; -3 0.6 − − P 0.011) while asterids and rosids were intermediate (g cm 0.4 = ood density

and did not significantly differ from any other group. At a W 0.2 higher taxonomic level, stomatal CO2 responsiveness was stronger in angiosperms compared to gymnosperms and in (e) monocots compared to dicots (Online Resource 1). The dif- 300

) 250 a babab ferent taxonomic groups had similar values of g1 and WUE, -2 again with asterids exhibiting the highest variation among 200 150 species (Fig. 2f–g). Values of Kp varied greatly both among 100 and within taxonomic groups, with gymnosperms having LM A (g m significantly lower K than asterids (P 0.019; Fig. 2h). 50 p = Stomatal density and stomatal length exhibited large var- GYMMON ROS AST iation both within and among taxonomic groups (Fig. 3a, b). Stomatal density was lower in gymnosperms than in rosids Fig. 3 Structural traits in different taxonomic groups: a stomatal (P 0.007), while stomatal length did not differ among tax- density; b stomatal length; c maximum stomatal conductance (gsmax) = calculated from stomatal density and length data (see Eq. 4); d wood onomic groups. Values of gsmax (determined from stomatal density and stomatal length data) and wood density varied density; and e leaf mass per unit area (LMA). Different letters rep- resent significant difference between groups (P 0.05). Each data greatly among species but did not significantly differ among point represents the mean value of a species and≤ thick black lines groups (Fig. 3c–d). Gymnosperms had significantly higher represent mean values of the taxonomic groups. GYM gymnosperms, LMA than monocots (P 0.017) and marginally signifi- MON monocots, ROS rosids, AST asterids = cantly higher LMA than asterids (P 0.051; Fig. 3e). = Leaf area-based N and P contents (Na and Pa) did not significantly differ among taxonomic groups, but there (P 0.003) and rosids (P 0.023). The N:P ratio did not = = were several differences in leaf mass-based concentra- significantly differ among plant groups. Leaf area based tions (Table 2). Leaf mass-based N concentration (Nm) chlorophyll content was significantly higher in gymno- was significantly lower in gymnosperms than in mono- sperms than in monocots, rosids and asterids (P 0.001, = cots (P 0.043) and asterids (P 0.004; Table 2), while P 0.014 and P 0.007, respectively; Table 2). = = = = leaf mass-based P (Pm) did not significantly differ among All these traits varied greatly among individual spe- taxonomic groups. Leaf mass-based C (Cm) concentration cies and species-specific data can be found in Table 2 and was significantly lower in monocots than in gymnosperms Online Resource 2.

1 3 Oecologia B B B A ) − 2 0.25 ± 0.07 0.18 ± 0.03 0.57 ± 0.11 0.43 ± 0.07 0.20 ± 0.05 0.59 ± 0.10 0.45 ± 0.17 0.60 ± 0.04 0.44 ± 0.11 0.37 ± 0.01 0.77 ± 0.19 0.38 ± 0.04 0.16 ± 0.02 0.35 ± 0.06 0.39 ± 0.07 0.85 ± 0.05 0.50 ± 0.06 0.26 ± 0.03 0.40 ± 0.05 0.32 ± 0.16 0.68 ± 0.06 0.29 ± 0.09 0.42 ± 0.04 0.34 ± 0.15 0.69 ± 0.10 Chlorophyll (g Chlorophyll m (%) m :P m 15.03 ± 0.21 10.60 ± 2.79 10.52 ± 0.98 11.65 ± 1.26 11.92 ± 3.72 10.18 ± 1.15 10.27 ± 2.55 16.30 ± 2.10 20.33 ± 2.75 18.52 ± 0.58 10.06 ± 0.33 16.18 ± 2.13 12.88 ± 3.10 7.86 ± 1.50 23.93 ± 2.67 8.83 ± 1.32 17.63 ± 2.78 13.07 ± 1.15 18.28 ± 2.91 12.03 ± 0.66 10.67 ± 1.10 15.40 ± 4.98 15.09 ± 3.93 13.79 ± 1.63 10.05 ± 0.64 N ) − 2 leaf area-based P content a (g m a 0.13 ± 0.01 0.17 ± 0.02 0.21 ± 0.01 0.23 ± 0.02 0.15 ± 0.04 0.23 ± 0.05 0.22 ± 0.05 0.18 ± 0.02 0.11 ± 0.02 0.08 ± 0.01 0.27 ± 0.00 0.13 ± 0.01 0.14 ± 0.03 0.28 ± 0.04 0.06 ± 0.03 0.45 ± 0.10 0.13 ± 0.04 0.23 ± 0.07 0.10 ± 0.01 0.23 ± 0.02 0.18 ± 0.04 0.14 ± 0.06 0.16 ± 0.06 0.18 ± 0.04 0.27 ± 0.09 P ) − 2 (g m a 1.91 ± 0.19 1.85 ± 0.24 2.16 ± 0.18 2.72 ± 0.28 1.81 ± 0.49 2.29 ± 0.57 2.28 ± 0.24 2.97 ± 0.34 2.19 ± 0.28 1.43 ± 0.24 2.74 ± 0.36 2.05 ± 0.33 1.75 ± 0.39 2.22 ± 0.30 1.39 ± 0.36 3.98 ± 0.49 2.34 ± 0.24 3.01 ± 0.78 1.77 ± 0.27 2.75 ± 0.73 1.97 ± 0.41 N 1.85 ± 0.48 2.14 ± 0.17 2.47 ± 0.53 2.63 ± 0.71 leaf area-based N content, P a A B AB A (%) m 41.79 ± 1.54 40.33 ± 0.98 43.42 ± 1.22 43.03 ± 0.77 42.44 ± 1.27 45.59 ± 1.55 43.95 ± 0.29 43.14 ± 1.87 45.21 ± 1.56 40.05 ± 1.42 46.45 ± 1.33 45.52 ± 0.89 41.39 ± 0.93 44.45 ± 1.31 39.67 ± 2.46 45.99 ± 1.04 42.52 ± 1.59 46.40 ± 1.54 43.17 ± 0.98 42.84 ± 0.48 41.07 ± 1.28 44.14 ± 0.93 43.15 ± 1.73 45.31 ± 1.02 45.13 ± 0.78 C (%) leaf mass-based C concentration, N m m 0.34 ± 0.06 0.29 ± 0.05 0.17 ± 0.02 0.37 ± 0.05 0.29 ± 0.05 0.16 ± 0.01 0.24 ± 0.08 0.17 ± 0.05 0.06 ± 0.01 0.16 ± 0.00 0.16 ± 0.00 0.18 ± 0.00 0.22 ± 0.04 0.29 ± 0.03 0.15 ± 0.02 0.14 ± 0.03 0.11 ± 0.03 0.19 ± 0.01 0.11 ± 0.02 0.16 ± 0.01 0.21 ± 0.06 0.17 ± 0.07 0.26 ± 0.08 0.16 ± 0.01 0.15 ± 0.03 P AB B B A (%) m 3.50 ± 0.98 2.98 ± 0.56 1.58 ± 0.17 5.06 ± 0.58 3.05 ± 0.20 1.79 ± 0.12 2.15 ± 0.42 4.30 ± 0.34 3.42 ± 0.41 1.62 ± 0.09 2.48 ± 0.18 2.79 ± 0.45 1.28 ± 0.10 2.99 ± 0.08 1.59 ± 0.20 2.84 ± 0.27 2.81 ± 0.31 2.25 ± 0.38 3.52 ± 0.12 1.26 ± 0.10 1.98 ± 0.29 2.53 ± 0.25 2.07 ± 0.08 1.90 + 0.47 N 1.65 ± 0.15 - leaf mass-based P concentration, C m folia falcatus betaceae flora latifolius acerifolius dum maculata giganteus tanica rnirnosifolia nandscharica tifolia - diversi Tithonia Musa sapientum Podocarpus Podocarpus Cyphornandra Cyphornandra - grandi Carapa Heliconia rostrata Heliconia Podocarpus Podocarpus Brachychiton Brachychiton Ligustrum luci - Eucalyptus Bambusa vulgaris Bambusa Pinus patula Cedrela serrata Cedrela Cordia alliodora Cordia Prunus caretta Dendrocalamus Dendrocalamus Cupressus lusi - Cupressus Macaranga kilir Macaranga Jacaranda Phoenix reclinata Species Araucaria angus - Araucaria Asteraceae Musacea Podocarpaceae Solanaceae Meliaceae Heliconiaceae Podocarpaceae Malvaceae Oleaceae Myrtaceae Poaceae Pinaceae Meliaceae Boraginaceae Rosaceae Poaceae Cupressacaea Chrysobalanaceae Bignoniaceae Arecaceae Family Araucariaceae Chemical leaf trait values leaf mass-based N concentration, P m Mean Mean Mean Mean Rosidss Asterids 2 Table Monocots ( P ≤ 0.05) letters for a trait were significantly different Group means with different mean ± 95% CI The values N Group Gymnosperms

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Functional relationships different species are studied at different locations and the variation in plant traits is the combined result of both adap- Across all data, the inter-specific variation in the tation and acclimation. This study specifically addressed short-term gs response to increased [CO2] (i.e. 600 vs. the following three questions: 1 400 µmol mol− ) was not significantly related to variation in stomatal density, stomatal length, Kp, wood density, An280 Does the short‑term stomatal response to [CO2] vary or g (r2 0.11; P 0.13; Fig. 4a–f). There were, how- among taxonomic groups? 1 ≤ ≥ ever, a couple of exceptions within individual taxonomic groups, with stomatal CO2 responsiveness being stronger in Species of all taxonomic groups significantly decreased gymnosperm species with high stomatal density (r2 0.91; g in response to a short-term increase in [CO ] (Fig. 2e), = s 2 P 0.011; Fig. 4a) and in monocot species with high A with this response being stronger in angiosperms than in = n280 (r2 0.96; P 0.002; Fig. 4e). gymnosperms and in monocots compared to dicots (Online = = Values of g1 showed a positive relationship with Kp Resource 1). These results are generally in line with ear- (r2 0.29; P 0.017), but were not significantly related lier observations of lower stomatal CO responsiveness = = 2 to stomatal density or length, or wood density (r2 < 0.08; in gymnosperm compared to angiosperm species (Med- P > 0.21; Fig. 5). lyn et al. 2001; Brodribb et al. 2009), but do not support

Values of Vcmax and Jmax had no significant relationship the claim that stomata of gymnosperms entirely lack pri- with N (r2 < 0.01; P 0.65; Fig. 6a) or P (r2 < 0.004; mary responses to increased [CO ] (Brodribb et al. 2009). a ≥ a 2 P > 0.78; Fig. 6b), but was significantly related to leaf mN Other recent studies also found significant stomatal clo- (r2 0.53; P < 0.001 and r2 0.28; P 0.027, respec- sure responses to increased [CO ] in gymnosperm species = = = 2 tively; Online Resource 3a) and P (r2 0.40; P 0.002 (e.g. Haworth et al. 2013) and molecular studies indicate m = = and r2 0.29; P 0.015, respectively; Online Resource that the genetic tool kits necessary to respond to environ- = = 3b). The photosynthetic N and P use-efficiencies (i.e. mental cues such as [CO2] were present already in early the ratios of An280 to Na and Pa, respectively) did not sig- land plants and are not exclusive to angiosperms (Chater nificantly differ among plant groups, largely due to large et al. 2013). Furthermore, observational studies based on interspecific variation (P 0.19; Online Resource 4). ecosystem flux measurements or stable carbon isotopes in ≥ The variation in Vcmax and Jmax among species was, how- tree rings in temperate and boreal ecosystems have found ever, significantly related to the fraction of leaf N allo- similar (Keenan et al. 2013) or even stronger (Frank et al. cated to Rubisco and bioenergetics (N N ) (r2 0.77; 2015) increases in water-use efficiency under rising atmos- R + B = P < 0.001 and r2 0.47; P 0.001, respectively; Fig. 6c). pheric [CO ] in gymnosperms compared to angiosperms, = = 2 In addition, there was a marginally significant negative further indicating that species of both taxonomic groups relationship between N N and the fraction of leaf N may have stomatal closure responses to increased [CO ]. If R + B 2 allocated to light harvesting (N ; r2 0.15; P 0.085; we assume that short-term stomatal CO responsiveness is LH = = 2 Fig. 6d). Values of Vcmax and Jmax were closely related, an important determinant of the long-term effect of growth both within taxonomic groups and across the entire data set under elevated [CO2] on gs, as indicated by observations in 2 (r 0.82; P < 0.001; Online Resource 5). Finally, both free-air CO2 enrichment experiments (Fig. 1), our results = 2 2 An280 (r 0.75) and NR NB (r 0.67) were strongly suggest that stomatal closure-induced leaf water savings = + = 1 and positively related to gs measured at 400 µmol mol− air under rising [CO2] may be expected in both angiosperms [CO2] (Fig. 7). and gymnosperms also in tropical forests.

What functional characteristics can explain the Discussion interspecific variation in stomatal behavior?

Data on physiological, structural and chemical plant traits Across all species, the interspecific variation in short-term were collected and analyzed to explore the controls of stomatal CO2 responsiveness was not significantly related interspecific variation in stomatal CO2 responsiveness and to any of the measured structural or functional plant traits photosynthetic capacity (Vcmax and Jmax) among tropical (Fig. 4). However, in gymnosperms, the taxonomic group woody plant species in central Africa. The broad selection with the lowest stomatal density, the gs response got of tree species together with the common garden approach stronger with increasing stomatal density (Fig. 4a). We also allowed us to isolate the effects of long-term evolutionary found a significant relationship between An280 and stoma- adaptation from plastic adjustments to local environmen- tal CO2 responsiveness in monocots (Fig. 4e), indicating tal conditions (i.e., acclimation), a separation that is not that CO2 responsiveness may be linked to the metabolic possible in observational studies or meta-analyses where activity of the leaf in this taxonomic group where stomatal

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Fig. 4 The short-term gs Gymnosperms Monocots Rosids Asterids response to elevated [CO2] (600 1 vs. 400 µmol mol− ) in relation y = -0.113x - 3.82 (a) (b) 2 to a stomatal density; b stomatal r = 0.91 -10 P = 0.012 -10 length; c leaf area-specific plant hydraulic conductance (Kp); d -20 -20 wood density; e net photosyn- 1 thetic rate at 280 µmol mol− -30 -30 intercellular [CO ] (A ); and f 2 n280 y = -0.0159x - 17.90 y = 0.267x - 27.63 g1 (see Eq. 3). Regression lines -40 2 -40 2 2 r = 0.09 r = 0.06 with r and P values are shown. P = 0.19 P = 0.28 Solid lines for relationships 200 400 600 800 10 20 30 40 across all species and dashed -2 Stomatal length ( m) lines for significant (P 0.05) Stomatal density (stomata mm ) relationships within individual≤

] (% ) (c) (d) taxonomic groups (gymno- 2 O -10 sperms in 4a and monocots -10 in 4e). A color version of this figure is available in the online -20 version of the journal -20 -30 y = -1.144x - 18.02 -30 -40 y = -6.386x - 16.03 r2 = 0.04 r2 = 0.018 P = 0.32 P = 0.69 change at elevated [C s 246 0.20.4 0.60.8 g -2 -1 -1 -3 Kp (mmol m s MPa ) Wood density (g cm ) (e) (f) -10 -10

-20 -20

-30 -30

y = -1.945x - 9.93 y = -0.178x - 19.12 y = 2.287x - 28.83 -40 -40 2 r2 = 0.96 r2 = 0.01 r = 0.11 P = 0.002 P = 0.63 P = 0.13 510152025 246

-2 -1 An280 ( mol m s ) g1

CO2 responses were strong (Fig. 2e). Further studies are suggestion by Lin et al. (2015) that wood density is a required to confirm these relationships and why they are good proxy for quantifying g1 in angiosperm trees is thus not found in all taxonomic groups. not corroborated by the present study, which points at tree

The slope parameter of the combined stomatal-pho- hydraulics being more important. The mean g1 value for tosynthesis model (Eq. 3), g1, was significantly related to gymnosperms observed in this study (3.45) was not lower leaf area-specific plant hydraulic conductance, Kp (Fig. 5c). than that for angiosperms (3.33; Fig. 2f), and markedly Admittedly, the positive relationship found between g1 higher than the mean g1 value for gymnosperms reported and Kp (Fig. 5c) may be confounded by the use of leaf gas by Lin et al. (2015) (2.35). This discrepancy between our exchange data in the calculation of both traits (see Eqs. 3 study and the Lin et al. meta-analysis may be a conse- and 5). However, we find it highly likely that it reflects quence of the shortage of tropical gymnosperm data in the a true dependence of the marginal carbon cost of water latter study, and that gymnosperm and angiosperm trees use, which is inversely related to the square of g1 accord- may have similar g1 if measured in similar climates (at least ing to the model of optimal stomatal behaviour proposed in the tropics). by Medlyn et al. (2011). Such dependence agrees well with the common observation that plants that use a lot of What controls the interspecific variation water (which is made possible though high Kp) also have in photosynthetic capacity? low water-use efficiency (i.e. high g1; Larcher 2003). We did not, however, find thatg 1 was negatively related to Total leaf area-based nutrient content (Na and Pa) did not wood density (Fig. 5d), as reported for angiosperm trees explain the large interspecific variation in photosynthetic in a recent global meta-analysis (Lin et al. 2015). The capacity (Fig. 6a, b), in agreement with previous tropical

1 3 Oecologia

Gymnosperms Monocots Rosids Asterids Gymnosperms, Vcmax Gymnosperms, Jmax (a) Monocots, Vcmax Monocots, Jmax Rosids, Vcmax Rosids, Jmax 6 Asterids, Vcmax Asterids, Jmax Vcmax Jmax y = -0.0592x + 56.14 y = 6.919x + 100.92 2 4 r2 = 0.000 r = 0.01 200 P = 0.65 P = 0.99

2 y = -0.0009x + 3.56 150 r 2 = 0.01 P = 0.62 200400 600800 100 Stomatal density (stomata mm-2) 50 (b) (a) 6 1 243 )

-1 -2 Na (g m ) s 4 -2 Vcmax Jmax y = 12.659x + 58.36 y = 29.358x + 111.24 2 2

mol m r = 0.002 r = 0.005 2 200 P = 0.85 P = 0.78 y = -0.0452x + 4.49 ( r 2 = 0.08 P = 0.21 150

1 10 20 30 40 g Stomatal length ( m) 100 (c) 50 6 (b) 0.1 0.2 0.30.4 4 Photosynthetic capacity -2 Pa (g m )

Vcmax 2 y = 0.456x + 2.23 (c) 2 y = 1.852x + 12.85 r = 0.29 r2 = 0.77 P = 0.017 200 P < 0.001 12 3 4 5 6 -2 -1 -1 150 Kp (mmol m s MPa )

(d) 100

6 Jmax 50 y = 2.310x + 60.88 r2 = 0.47 4 P = 0.001 10 20 30 40 50 2 N + N (%) y = 1.522x + 2.73 R B 2 r = 0.03 y = -0.962x + 35.56 P = 0.67 Gymnosperms r2 = 0.15 0.20.4 0.60.8 50 Monocots P = 0.085 Wood density (g cm-3) Rosids 40 Asterids (% ) B 30 Fig. 5 The combined stomatal–photosynthesis model parameter g1 + N (see Eq. 3) in relation to a stomatal density; b stomatal length; c leaf R N 20 area-specific plant hydraulic conductance (Kp); and d wood density. 2 Regression lines with r and P values are shown. A color version of 10 (d) this figure is available in the online version of the journal

5 10 15 20 studies (Coste et al. 2005; van de Weg et al. 2012; Houter NLH (%) and Pons 2014; Dusenge et al. 2015). Instead, the differ- ences in photosynthetic capacities among species were Fig. 6 Photosynthetic capacity (i.e. Vcmax and Jmax) in relation to strongly linked to the fractional investment of leaf N into a area-based leaf N content (Na); b area-based leaf P content (Pa); and c the fraction of leaf N allocated to Rubisco and bioenergetics compounds maximizing these capacities, i.e. NR NB (N N ). Also shown d is the fraction of leaf N allocated to Rubisco + R + B (Fig. 6c). Similar results were reported from two studies and bioenergetics (NR NB) vs. the fraction of N allocated to light har- + 2 with tropical montane tree species (Coste et al. 2005; Duse- vesting (NLH). Regression lines with r and P values are shown. A color nge et al. 2015) and in a global meta-analysis (Ali et al. version of this figure is available in the online version of the journal

1 3 Oecologia

These results demonstrate that the interspecific variation in photosynthetic capacity is strongly linked to within-leaf N allocation and water use strategies in tropical woody species. The finding that within-leaf N allocation is more important than total leaf N content in controlling photo- synthetic capacity implies that current vegetation models,

which often assume that Vcmax and Jmax are plant functional type-specific functions of area-based leaf N content (e.g. Rogers 2014; Zaehle et al. 2005), would be much improved if they could also account for differences in within-leaf N allocation.

Acknowledgements The first and last authors were supported by the strategic research areas Biodiversity and Ecosystem services in a Changing Climate (BECC; http://www.becc.lu.se/) and Modelling the Regional and Global Earth system (MERGE; http://www.merge. lu.se/). We are grateful to the Rwanda Agricultural Board (RAB) and Rwanda Development Board (RDB), which authorized the data col- lection in the Ruhande Arboretum. We are also grateful to Dr. Elias Bizuru for helping with the species selection and Mr. Bonaventure

1 Ntirugulirwa for field logistics in the arboretum. Fig. 7 a Net photosynthetic rate at 280 µmol mol− intercellu- lar [CO ] (A ) and b the fraction of leaf N allocated to Rubisco 2 n280 Author contribution statement TBH and JU conceived and and bioenergetics (NR NB) in relation to stomatal conductance at 1 + designed the study. TBH, MED, FB and FUK performed the field and 400 µmol mol− air [CO ] 2 laboratory measurements. TBH, JU and GW analysed the data and wrote the manuscript. All authors provided editorial advice.

2015). Dusenge et al. (2015) suggested that there is a trade- Compliance with ethical standards off, such that species with large fractional leaf N investment into light harvesting have low investments into compounds Conflict of interest The authors declare that they have no conflict of interest. maximizing photosynthetic capacity, and vice versa. In that study, which included a limited number of tree species (n 10), the former strategy was present in climax species Open Access This article is distributed under the terms of the Crea- = tive Commons Attribution 4.0 International License (http://crea- while the latter strategy was used by pioneers. This study tivecommons.org/licenses/by/4.0/), which permits unrestricted use, corroborates the hypothesis of Dusenge et al. (2015), with distribution, and reproduction in any medium, provided you give a marginally significant (P 0.08) negative relationship appropriate credit to the original author(s) and the source, provide a = link to the Creative Commons license, and indicate if changes were between the relative (%) leaf N investments into Rubisco made. and bioenergetics (N N ) versus light harvesting com- R + B pounds (NLH; Fig. 6d). It should be noted that while the relationship between N N and photosynthetic capac- R + B References ity (Fig. 6c) was expected since the absolute N investments into these components were calculated from the values of Ainsworth EA, Rogers A (2007) The response of photosynthesis Vcmax and Jmax (Eqs. 6 , 7), the relationship between NLH and stomatal conductance to rising [CO2]: mechanisms and and N N (Fig. 6d) was based on independent estimates environmental interactions. Plant, Cell Environ 30:258–270. R + B doi:10.1111/J.1365-3040.2007.01641.X of leaf chlorophyll content and photosynthetic capacity, Ali AA, Xu C, Rogers A et al (2015) Global scale environmen- respectively. tal control of plant photosynthetic capacity. Ecol Appl. Leaf N allocation and water use were strongly co-ordi- doi:10.1890/14-2111.1 nated (r2 0.67; Fig. 7b), showing that species with high Ball JT, Woodrow IE, Berry JA (1987) A model predicting stomatal = conductance and its contribution to the control of photosynthe- relative N investments into compounds maximizing pho- sis under different environmental conditions. In: Biggins J (ed) tosynthetic capacity take advantage of this investment by Progress in Photosynthesis Research. Springer, Providence, pp having high gs. This finding is in line with earlier obser- 221–224 vations of tight co-ordination between photosynthesis and Beer C, Reichstein M, Tomelleri E et al (2010) Terrestrial gross car- bon dioxide uptake: global distribution and covariation with cli- gs (e.g. Wong et al. 1979; Franks and Farquhar 1999), but mate. Science 329:834–838. doi:10.1126/science.1184984 extends beyond these by showing that also within-leaf N Bernacchi CJ, Singsaas EL, Pimentel C et al (2001) allocation strategy plays an important part in this coupling. Improved temperature response functions for models of

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