Literature DB >> 35582952

Higher leaf nitrogen content is linked to tighter stomatal regulation of transpiration and more efficient water use across dryland trees.

José Ignacio Querejeta1, Iván Prieto1,2,3, Cristina Armas2, Fernando Casanoves4, Joseph S Diémé2,5,6, Mayecor Diouf5,7, Harouna Yossi8, Bocary Kaya8,9, Francisco I Pugnaire2, Graciela M Rusch10.   

Abstract

The least-cost economic theory of photosynthesis shows that water and nitrogen are mutually substitutable resources to achieve a given carbon gain. However, vegetation in the Sahel has to cope with the dual challenge imposed by drought and nutrient-poor soils. We addressed how variation in leaf nitrogen per area (Narea ) modulates leaf oxygen and carbon isotopic composition (δ18 O, δ13 C), as proxies of stomatal conductance and water-use efficiency, across 34 Sahelian woody species. Dryland species exhibited diverging leaf δ18 O and δ13 C values, indicating large interspecific variation in time-integrated stomatal conductance and water-use efficiency. Structural equation modeling revealed that leaf Narea is a pivotal trait linked to multiple water-use traits. Leaf Narea was positively linked to both δ18 O and δ13 C, suggesting higher carboxylation capacity and tighter stomatal regulation of transpiration in N-rich species, which allows them to achieve higher water-use efficiency and more conservative water use. These adaptations represent a key physiological advantage of N-rich species, such as legumes, that could contribute to their dominance across many dryland regions. This is the first report of a robust mechanistic link between leaf Narea and δ18 O in dryland vegetation that is consistent with core principles of plant physiology.
© 2022 The Authors. New Phytologist © 2022 New Phytologist Foundation.

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Keywords:  Sahel; arid ecosystems; ci/ca ratio; leaf δ13C; leaf δ18O; plant isotopic composition; plant water-use strategies; stomatal conductance

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Year:  2022        PMID: 35582952      PMCID: PMC9542767          DOI: 10.1111/nph.18254

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.323


Introduction

Drylands occupy c. 45% of the Earth’s surface (Prăvălie, 2016; Maestre et al., 2021) and are defined as regions where evapotranspiration is greater than precipitation, leading to water deficit (Huang et al., 2016). Low soil fertility is yet another limitation for plant productivity in many drylands, especially regarding soil nitrogen and phosphorus content (Noy‐Meir, 1973; Breman & De Wit, 1983). However, dryland plants often show higher leaf nitrogen contents than do species from wetter ecosystems (Wright et al., 2001, 2003). Several hypotheses have been proposed to explain the high leaf N contents typically found in dryland vegetation (Prentice et al., 2014; Adams et al., 2016). More than 70% of the total N contained in plant leaves is allocated to RuBisCO and other enzymes and proteins involved in photosynthesis (Evans, 1989; Evans & Seemann, 1989; Onoda et al., 2017; Evans & Clarke, 2018). Hence, a higher investment in N uptake and allocation to leaves enhances CO2 fixation and reduces CO2 concentration in leaf intercellular spaces (c i) relative to the atmosphere (c a), leading to low internal c i/c a ratios at the sites of carboxylation. Wright et al. (2001, 2003) suggested that plants in low‐rainfall environments increase their N content per unit leaf area (Narea) so that they can save water while maintaining photosynthetic rates similar to plants from wetter environments. This is achieved by optimizing carboxylation and carbon assimilation capacity thanks to high leaf Narea, while at the same time reducing stomatal conductance (g s) and transpiration (E) rates to minimize water loss, given that a steeper CO2 diffusion gradient helps to maintain supply of CO2 into the leaves. This general theory has been named the least‐cost economic theory of photosynthesis (Wright et al., 2003; Prentice et al., 2014; Wang et al., 2017). Remote sensing studies have recently raised awareness about the high woody plant cover and large number of tree individuals present across the Sahelian drylands in northwest Africa (Brandt et al., 2020), despite the dual challenge imposed by low soil fertility and drought stress on plant photosynthesis. Legumes (Fabaceae) are often the dominant plant family in terms of cover and species diversity in Sahelian drylands (Felker, 1981; Sprent & Gehlot, 2010) and are also widely used for livestock feeding. In fact, Adams et al. (2016) showed that high leaf Nmass and Narea, acquired through symbiosis with N2‐fixing bacteria present in their roots (Powers & Tiffin, 2010; Vitousek et al., 2013; Song et al., 2015), allows legumes to use water more efficiently than nonlegumes at global scale. Furthermore, production and accumulation of N‐rich osmolytes can also help dryland legumes cope with drought through enhanced internal osmotic adjustment that lowers plant water potentials, thereby increasing plant water uptake from drying soil (Wink, 2013). However, the extent to which optimization of water‐use efficiency in dryland woody legumes is achieved primarily through tighter stomatal regulation or via enhanced carbon assimilation capacity (or both) remains unclear (but see Adams et al., 2018a,b for herbaceous and crop legumes). Carbon, oxygen and nitrogen stable isotopic composition of leaf material (leaf δ13C, δ18O and δ15N, respectively), along with xylem water isotopic composition (δ2H and δ18O), have become key traits that integrate information about plant‐resource acquisition and how plants interact with and respond to their abiotic and biotic environments (Dawson et al., 2002; Barbour, 2007; Prieto et al., 2018; Querejeta et al., 2018). Leaf δ13C and δ18O in dryland plants can provide reliable proxies of time‐integrated intrinsic water‐use efficiency (WUEi) and g s, respectively (Ehleringer, 1993; Williams & Ehleringer, 1996; Barbour, 2007). Leaf δ13C in C3 species is negatively and linearly correlated with the time‐integrated c i/c a ratios during photosynthesis (Farquhar et al., 1989) and reflects the relationship between net photosynthetic rate (A) and g s, thereby providing a robust indicator of time‐integrated intrinsic water‐use efficiency (WUEi = A/g s) during the growing season (Dawson et al., 2002). Leaf δ18O is influenced by the isotopic composition of the water source used by the plant (Sarris et al., 2013; Ding et al., 2021). The isotopic signal of the water source is thereafter modified by leaf‐level evaporative effects, including stomatal responses to changes in atmospheric relative humidity and soil moisture, making leaf δ18O a good proxy of time‐integrated stomatal conductance (g s) and cumulative transpiration in dryland species (Querejeta et al., 2006; Barbour, 2007; Ramírez et al., 2009; Prieto et al., 2018). The enrichment in 18O of leaf dry matter above the δ18O value of the source water used by the plant (leaf Δ18O) helps to remove the signal of interplant variation in water sources and is thus useful to estimate differences in stomatal regulation among coexisting species exposed to similar environmental conditions (Barbour, 2007). Overall, the combined measurement of leaf δ18O/Δ18O and δ13C (hereafter leaf δ13C‐WUEi) can help in assessing variations in photosynthetic capacity, stomatal conductance, WUEi and overall water‐use strategy (from conservative to profligate) among coexisting dryland species exposed to similar environmental conditions (Moreno‐Gutiérrez et al., 2012; Prieto et al., 2018). In this study, we addressed how interspecific variation in leaf Narea modulates leaf carbon and oxygen isotopic composition across 34 woody species encompassing diverse phylogenies and leaf habits in the Sahel. In particular, we hypothesized that leaf δ13C and δ18O values will be positively correlated across dryland species as a result of the shared dependence of both traits on stomatal conductance, and will converge towards a relatively narrow range of values constrained by the harsh climatic and soil conditions (Paillassa et al., 2020); and that higher leaf Narea will be associated with higher leaf δ18O and δ13C values across dryland species, indicating greater carboxylation capacity, tighter stomatal regulation with lower conductance and higher WUEi (Wright et al., 2001, 2003). We further aimed to elucidate whether higher leaf δ13C‐WUEi with increasing leaf Narea in dryland species might be achieved through higher carboxylation capacity, allowing lower stomatal conductance for any given photosynthetic rate (resulting in a strong influence of leaf Narea on both δ18O and δ13C), or primarily through enhanced carboxylation capacity but with little or no impact on stomatal conductance (resulting in weak or no influence of leaf Narea on leaf δ18O). These hypotheses were analyzed and tested with structural equation modeling (SEM; Fig. 1) using a dataset of leaf and stem traits collected on 34 Sahelian woody species. We thereafter compared legumes (Fabaceae) vs nonlegumes (Table 1) and hypothesized that legumes would exhibit higher leaf δ18O and δ13C‐WUEi values and greater drought tolerance than nonlegumes thanks to higher leaf Narea achieved through symbiotic atmospheric N2 fixation. We also hypothesized that dryland legumes would fix large amounts of atmospheric N2, resulting in distinct leaf δ15N values near 0‰, whereas co‐occurring nonlegumes would show high leaf δ15N values typical of plants using 15N‐enriched soil N sources in hot and dry environments (Amundson et al., 2003; Aranibar et al., 2004; Craine et al., 2009, 2015).
Fig. 1

Structural equation model based on the hypothesized effects of leaf N per area on time‐integrated stomatal conductance (g s) and intrinsic water‐use efficiency (WUEi) at leaf level in dryland woody species (Wright et al., 2001; Adams et al., 2016) in the Sahel. A priori set of hypotheses and relationships among variables (a) are described in the ‘Materials and Methods’ section. In this model, leaf Narea is considered as a surrogate of carboxylation capacity (V cmax), leaf δ18O is a surrogate of stomatal conductance (g s) and δ13C is a surrogate of WUEi. Continuous and dashed black arrows (b) indicate positive and negative relationships between variables, respectively. Numbers adjacent to arrows indicate the effect size (standardized path coefficients, analogous to partial regression weights) and significance (*, P < 0.05; **, P < 0.01; ***, P < 0.001; ¥, marginally significant, P = 0.074) of the path; arrow thickness is proportional to the effect size (n = 168). Numbers within circles indicate squared multiple correlations for the variables. Overall goodness‐of‐fit tests (χ2, comparative fit index (CFI), incremental fit index (IFI) and root mean square error of approximation (RMSEA)) are shown at the bottom of the model. SLA, specific leaf area.

Table 1

General characteristics of the tree and shrub species sampled in two semiarid agroforestry systems in the Sahel (Mali and Senegal).

SpeciesFamilyGrowth typeLeaf habitDBH (m)Height (m)Mali (no. of trees)Senegal (no. of trees)
Acacia nilotica (L.) Willd. ex DelileFabaceaeTD0.71 ± 0.115.80 ± 0.2816
Acacia senegal (L.) Willd.FabaceaeTD0.19 ± 0.017.25 ± 1.752
Acacia seyal DelileFabaceaeTD0.52 ± 0.084.94 ± 0.3062
Acacia tortilis spp. Raddiana (Forssk.) Hayne (Savi) BrenanFabaceaeTD0.27 ± 0.035.92 ± 1.056
Adansonia digitata L.MalvaceaeTD2.46 ± 0.6410.43 ± 0.8876
Annona senegalensis Pers.AnnonaceaeSD0.97 ± 0.056
Anogeissus leiocarpus (DC.) Guill. & Perr.CombretaceaeTE1.54 ± 0.0710.18 ± 1.196
Aphania senegalensis (Juss. ex Poir.) RadlkSapindaceaeTE0.29 ± 0.044.13 ± 0.882
Balanites aegyptiaca (L.) DelileZygophyllaceaeTE0.69 ± 0.125.98 ± 0.7066
Bauhinia rufescens Lam.FabaceaeTD0.14 ± 0.004.25 ± 0.523
Boscia senegalensis (Pers.) Lam. ex Poir.CapparaceaeS‐TE1.71 ± 0.236
Celtis integrifolia Lam.UlmaceaeTE0.55 ± 0.0811.42 ± 1.046
Combretum glutinosum Perr. ex DC.CombretaceaeT (S‐T)E0.75 ± 0.177.11 ± 0.7566
Combretum micranthum G. Don.CombretaceaeSD0.17 ± 0.062.68 ± 0.286
Cordia sinensis Lam.BoraginaceaeTE0.116.001
Crateva religiosa Forst. f.CapparaceaeTE0.33 ± 0.028.08 ± 0.963
Diospyros mespiliformis Hochst. ex A. DC.EbenaceaeTD1.34 ± 0.136.91 ± 0.817
Faidherbia albida (Delile) A. Chev.FabaceaeTD0.83 ± 0.179.04 ± 0.7066
Ficus gnaphalocarpa (Miq.) Steud.MoraceaeTD2.11 ± 0.438.53 ± 1.116
Guiera senegalensis J. F. Gmel.CombretaceaeS‐TD0.12 ± 0.023.02 ± 0.106
Maytenus senegalensis (Lam.) ExellCelastraceaeS‐TD0.12 ± 0.002.39 ± 0.445
Neocarya macrophylla (Sabine) PranceChrysobalanaceaeTE0.38 ± 0.046.08 ± 0.986
Piliostigma reticulatum (DC.) Hochst.FabaceaeTE0.79 ± 0.134.99 ± 0.2662
Prosopis africana (Guill. & Perr.) Taub.FabaceaeTD2.00 ± 0.249.53 ± 1.366
Prosopis juliflora (Sw.) DC.FabaceaeTE0.26 ± 0.038.17 ± 0.766
Pterocarpus erinaceus Poir.FabaceaeTD1.38 ± 0.117.78 ± 0.366
Saba senegalensis (A. DC.) PichonApocynaceaeTE4.20 ± 0.726
Sclerocarya birrea (A. Rich.) Hochst.AnacardiaceaeTD0.77 ± 0.137.98 ± 0.4066
Tamarindus indica L.FabaceaeTE1.20 ± 0.238.78 ± 0.9167
Tamarix senegalensis DC.TamaricaceaeT(S‐T)E2.20 ± 0.216
Terminalia laxiflora Engl.CombretaceaeTD1.70 ± 0.239.23 ± 1.146
Vitellaria paradoxa C.F.Gaertn.SapotaceaeTD1.70 ± 0.149.83 ± 1.406
Vitex doniana SweetLabiataeTD2.02 ± 0.128.62 ± 0.625
Ziziphus mauritiana Lam.RhamnaceaeSE0.43 ± 0.185.42 ± 0.4436
Total124106

Species (N = 34), families, growth type (T, tree; S, shrub; S‐T, spp. that can grow as a shrub or tree depending on the environmental conditions), leaf habit (E, evergreen (N = 15 spp.); D, deciduous (N = 19 spp.)), mean (± SE) diameter at breast height (DBH) and plant vegetative height (height) and number of sampled individuals.

Structural equation model based on the hypothesized effects of leaf N per area on time‐integrated stomatal conductance (g s) and intrinsic water‐use efficiency (WUEi) at leaf level in dryland woody species (Wright et al., 2001; Adams et al., 2016) in the Sahel. A priori set of hypotheses and relationships among variables (a) are described in the ‘Materials and Methods’ section. In this model, leaf Narea is considered as a surrogate of carboxylation capacity (V cmax), leaf δ18O is a surrogate of stomatal conductance (g s) and δ13C is a surrogate of WUEi. Continuous and dashed black arrows (b) indicate positive and negative relationships between variables, respectively. Numbers adjacent to arrows indicate the effect size (standardized path coefficients, analogous to partial regression weights) and significance (*, P < 0.05; **, P < 0.01; ***, P < 0.001; ¥, marginally significant, P = 0.074) of the path; arrow thickness is proportional to the effect size (n = 168). Numbers within circles indicate squared multiple correlations for the variables. Overall goodness‐of‐fit tests (χ2, comparative fit index (CFI), incremental fit index (IFI) and root mean square error of approximation (RMSEA)) are shown at the bottom of the model. SLA, specific leaf area. General characteristics of the tree and shrub species sampled in two semiarid agroforestry systems in the Sahel (Mali and Senegal). Species (N = 34), families, growth type (T, tree; S, shrub; S‐T, spp. that can grow as a shrub or tree depending on the environmental conditions), leaf habit (E, evergreen (N = 15 spp.); D, deciduous (N = 19 spp.)), mean (± SE) diameter at breast height (DBH) and plant vegetative height (height) and number of sampled individuals.

Materials and Methods

Study sites

The study was conducted in silvopastoral and agroforestry ecosystems of the western Sahel region. Sampling sites were selected near Louga (15°37′N, 16°13′W) in northwest Senegal (seven sites), and near Ségou (13°27′N, 6°16′W) in south‐central Mali (eight sites). In this region, rain falls mainly during the monsoon season (June–October), followed by a dry season between November and June (Supporting Information Fig. S1). Louga has a semiarid sub‐Canarian climate (Wade, 1997) with a mean temperature of 24.9°C and average annual rainfall of 330 mm (1950–2000). Both rain and the warmest temperatures occur mostly during the monsoon season (Edmunds & Gaye, 1994; NOAA, 2015). Ségou has a continental semiarid climate with lower relative humidity than Louga, but has higher mean annual temperature (27.8°C) and precipitation (566 mm; NOAA, 2015; Fig. S1). Daily maximum temperatures in both areas frequently reach above 50°C. Soils in Louga and Ségou are highly weathered acidic sands on ancient dunes, inter‐dune depressions or plains that typically show low water‐holding capacity and organic matter content, and are particularly poor in phosphorus and other nutrients (Bitchibaly et al., 2012). Relatively shallow groundwater can be found in both the Louga and Ségou sites studied. Vegetation of these agroforestry ecosystems is an open savannah with sparse trees and shrubs scattered across a grassland matrix and interspersed with croplands where typical management practices include harvesting of trees and shrubs, grazing and farming (IER, 2010; Konaté, 2010).

Sampling and trait data collection

We sampled leaves and stems from 230 individual trees and shrubs of 34 species, including 11 species from the Fabaceae family (legumes, Table 1). Both legumes and nonlegumes include evergreen species that retain a full canopy throughout the year and drought‐deciduous species that remain leafless or partially leafless for several months during the dry season. The only exception is Faidherbia albida, a deciduous legume that sheds leaves during the rainy season (Diémé et al., 2018). Species were assigned to leaf habit categories based on local expert knowledge (Diémé et al., 2018, 2019) and descriptions in Arbonnier (2004). Plant samples were collected in the early dry season of 2011 before leaf senescence of deciduous species. Sampled trees and shrubs were healthy‐looking and were at least 15 m far apart from each other (ranging between 0.015 and 60 km apart within each country; http://wms.nina.no/FunciTree/) and with their crowns fully exposed to sunlight. From each plant, we sampled two sun‐exposed branches from the eastern side of the canopy before dawn. One branch was placed in a sealed plastic bag within a dark hermetic bucket and was used for measuring stem predawn water potential (Ψpd) with a Scholander‐type pressure bomb. Leaf thickness (mm), specific leaf area (SLA; m2 kg−1), and leaf relative water content (RWC; g g−1) were measured in fully expanded, mature, damage‐free fresh leaves. Thickness was measured in three points in each leaf with a digital caliper and the mean value was recorded. The leaf collected to measure RWC was first weighed (FW), then fully rehydrated overnight in the dark, weighed again (hydrated weight, HW) and then scanned, and leaf area was then measured with ImageJ. Leaves were then oven‐dried at 60°C for 72 h and weighed again (DW). SLA is the one‐sided area (leaf area, LA) of the fully rehydrated leaf divided by its dry mass (SLA = LA/DM), while leaf RWC is the difference between leaf FW and DW divided by the difference between fully hydrated weight and leaf DW (i.e. RWC = (FW − DW)/(HW − DW)). Dry leaves were then ground using a ball‐mill to determine C and N concentrations (mass based) and δ13C, δ15N and δ18O composition. Leaf Narea (mg cm−2) was calculated as the ratio between leaf Nmass and SLA. From the second branch, we cut a terminal 8 cm leafless woody stem which was immediately placed in a screw‐cap polypropylene vial and sealed with Parafilm. Vials were transported in a cooler to the laboratory within 4 h and stored frozen. Xylem water was extracted using cryogenic vacuum distillation (Ehleringer & Osmond, 1989). The oxygen isotopic composition of xylem water (xylem water δ18O) helps in assessing the approximate depth of soil water uptake by roots in dryland ecosystems where steep vertical gradients in soil water δ18O develop during rainless periods (Moreno‐Gutiérrez et al., 2012). Evaporation from upper soil during hot, dry periods leads to heavy isotopic enrichment of the remaining soil water near the surface, which decreases steeply with depth (Allison & Hughes, 1983). Higher xylem water δ18O values indicate uptake of isotopically enriched water from shallower soil layers exposed to intense evaporation, whereas lower xylem water δ18O values indicate utilization of non‐enriched water from deeper, less evaporated water sources (Querejeta et al., 2007; Ding et al., 2021). Foliar δ13C can be used to estimate long‐term ratios of the intercellular to ambient CO2 values (c i/c a) if the carbon isotope ratio of atmospheric CO2 (δ13Cair) is known (Farquhar et al., 1989). To calculate long‐term c i/c a ratios, we first calculated Δ13C as: where δ13Cair is the C isotopic composition of atmospheric CO2 (−8.45‰, Mauna Loa records; http://www.esrl.noaa.gov/gmd/dv/ftpdata.html) and δ13Cleaf is the C isotopic composition of leaf material. Then, from Δ13C values, we calculated c i/c a as: where a s is the fractionation factor of gaseous diffusion (4.4‰) and represents effective fractionation as a result of carboxylation (27‰), estimated empirically (Farquhar et al., 1982). Cryogenic vacuum distillation and stable isotope analyses of leaf and water samples were conducted at the Stable Isotope Ratio Facility for Environmental Research, University of Utah (USA). Leaf N and C concentrations and δ13C, δ15N were measured with an isotope ratio mass spectrometer (Finnigan Mat Delta+ IRMS, Waltham, MA, USA) coupled to an elemental analyzer (EA; Carlo Erba CHN EA1110, Waltham, MA, USA). Leaf δ18O was measured with a Finnigan TC/EA IRMS. The δ18O isotopic composition of xylem water was measured using a laser water isotope analyzer (Picarro L2130i, Santa Clara, CA, USA).

Data analysis

To investigate the influence of leaf Narea on δ18O and δ13C‐WUEi in dryland vegetation, we built an a priori structural equation model (SEM) of hypothesized relationships within a path diagram (see the ‘Introduction’ section and Fig. 1a), allowing a causal interpretation of the model outputs (Grace, 2006). This a priori set of hypothesized relationships were as follows: high leaf N concentration (Nmass) and low SLA (i.e. higher LMA) both increase leaf Narea, which in turn enhances carboxylation capacity, allowing tighter stomatal regulation of transpiration and lower time‐integrated stomatal conductance (Wright et al., 2001, 2003). A key underlying assumption in this SEM model is that a higher leaf Narea enhances the leaf carboxylation capacity (V cmax) and thus enables the leaf to achieve a given carbon assimilation rate with lower stomatal aperture and conductance under dry environmental conditions. In our a priori SEM model, leaf Narea is considered a proxy of V cmax (Wright et al., 2001, 2003), leaf δ18O is considered a proxy of time‐integrated stomatal conductance (inversely related, 1/g s; Barbour, 2007), and leaf δ13C is a proxy of WUEi (Farquhar et al., 1989). The SEM was first tested with the experimental data collected in 34 dryland tree and shrub species from the Sahel (n = 168 individuals for which both SLA and Narea data were available; Fig. 1). Then, to rule out any potential confounding effects as a result of pooling together species of different leaf habits (deciduous vs evergreens) and with different proportions of legumes (eight legume species were deciduous and two were evergreen), we reanalyzed the dataset excluding evergreen species (Powers & Tiffin, 2010). Goodness of fit of the SEM model was assessed using the traditional χ2 goodness‐of‐fit test, but because of its sensitivity to sample size, the Bentler comparative fit index (CFI) and the incremental fit index (IFI) and root mean square error of approximation (RMSEA) were also considered (Grace, 2006). For the SEM analysis, contrary to other statistical analyses, model P‐values > 0.05 in the χ2 and RMSEA indices (Schermelleh‐Engel et al., 2003), and values close to 1 (> 0.90) for CFI and IFI indices are required to guarantee an acceptable fit (Hu & Bentler, 1999). We did not account for spatial variability among sampling sites in the SEM, but performed pairwise regression analyses between traits using linear mixed regression models with sampling site included as a random factor. Differences in plant traits between legumes and nonlegumes were analyzed with linear mixed models were the main fixed factor was Fabaceae/nonFabaceae. Geographic area (i.e. sampling site) was included as a random factor. Normality of residuals and homogeneity of variances assumptions were assessed by graphical inspection of residuals, and when these assumptions were not met (i.e. for Ψpd), we used a model correction for heterogeneity of variance (varExp), which represents an exponential structure of the variance–covariance matrix (Gałecki & Burzykowski, 2013). Post hoc differences were tested with Fisher least significant difference tests. All statistical analyses were performed with R software (R Core Team, 2019) interfaced by InfoStat statistical software v.2020 (Di Rienzo et al., 2020) using the packages lme4 (Bates et al., 2015) and nlme (Pinheiro et al., 2014). Structural equation modeling analyses were carried out with the AMOS extension in Spss (Arbuckle, 2014).

Results

Trait coordination across dryland woody species

Our pool of 34 woody species (mean height = 7.3 m; Table 1) encompassed a remarkably wide range of leaf Narea, Nmass, δ18O and δ13C values, thereby revealing large interspecific differences in carboxylation capacity, stomatal regulation of transpiration, c i/c a ratios and WUEi (Table 2). Sahelian trees and shrubs also showed large interspecific variability in SLA, leaf thickness, leaf RWC, δ15N and Δ18O, xylem water δ18O, and predawn water potentials (Fig. 2; Table S1). Whereas interspecific differences accounted for most of the variability in trait values (Fig. 2), intraspecific variability across sites was also rather high for some traits (Table S1 and indirectly shown in Fig. 2), suggesting large phenotypic trait variability in response to environmental heterogeneity. We did not detect any significant phylogenetic signal (λ) in any of the measured traits (Table S2).
Table 2

Description, number of trees and range of values (min to max) for the 10 functional traits measured in 34 woody species in the Sahel (Mali and Senegal) and their key role in plant functioning.

TraitAbbreviationUnits N RangeKey role in plant functioning/interpretation
Leaf carbon isotopic compositionLeaf δ13C217−31.5 to −24.6Time‐integrated water‐use efficiency
Ratio of intercellular and ambient CO2 concentrations c i/c a Unitless2170.57 to 0.91CO2 carboxylation capacity, stomatal conductance
Leaf nitrogen concentrationLeaf Nmass %2161.32 to 4.80Photosynthetic and carboxylation capacity, osmoregulation, nutritional quality
Leaf nitrogen areaLeaf Narea mg cm−2 1690.08 to 0.98Carboxylation capacity
Leaf oxygen isotopic compositionLeaf δ18O21119.02 to 34.53Time‐integrated stomatal conductance, cumulative transpiration
Leaf oxygen isotopic enrichment above source waterLeaf Δ18O19923.58 to 42.08Time‐integrated stomatal conductance, cumulative transpiration
Predawn stem water potentialΨpd MPa224−5.59 to −0.28Soil water availability, rooting depth, osmolyte accumulation in plant tissues
Relative water contentRWC%22161.1 to 96.4Leaf water status and hydration
Leaf thicknessLeaf Thicknessmm2070.12 to 0.62Leaf gas exchange, water retention
Specific leaf areaSLAm2 kg−1 1754.25 to 18.63Photosynthetic rate, light capture, relative growth rate
Leaf nitrogen isotopic compositionLeaf δ15N2173.42 to 12.9Atmospheric N2 fixation, soil N sources
Oxygen isotopic composition of xylem waterXylem water δ18O211−8.13 to 1.20Water sources, depth of soil water uptake

Description of traits and key role in plant function are based on Wright et al. (2001, 2005); Barbour (2007); Bernard‐Verdier et al. (2012); Perez‐Harguindeguy et al. (2013), and Craine et al. (2015).

Fig. 2

Estimated variance decomposition for 12 functional traits measured in woody species in the Sahel: (a) in the 34 woody species measured; and (b) in nine species common to the two sites sampled (Ségou, Mali, and Louga, Senegal; see Table 1 and Supporting Information Table S1). Variance partitioning between sites (15 sample sites, brown) and species (interspecific, green) is shown; residual variance is also shown (light gray). Leaf trait abbreviations and units are as follows: leaf Nmass, leaf nitrogen concentration on a mass basis (%); leaf Narea (mg cm−2), leaf N content per leaf area; SLA (m2 kg−1), specific leaf area; leaf thick, leaf thickness (mm); leaf δ13C, leaf carbon isotopic composition (‰); c i/c a, ratio of intercellular and ambient CO2 concentrations (unitless); leaf δ18O, leaf oxygen isotopic composition (‰); leaf Δ18O, leaf 18O enrichment above source (xylem) water (‰); xylem δ18O, xylem water oxygen isotopic composition (‰); RWC, leaf relative water content (g g−1); Ψpd, predawn stem water potential (MPa); leaf δ15N, leaf nitrogen isotopic composition (‰).

Description, number of trees and range of values (min to max) for the 10 functional traits measured in 34 woody species in the Sahel (Mali and Senegal) and their key role in plant functioning. Description of traits and key role in plant function are based on Wright et al. (2001, 2005); Barbour (2007); Bernard‐Verdier et al. (2012); Perez‐Harguindeguy et al. (2013), and Craine et al. (2015). Estimated variance decomposition for 12 functional traits measured in woody species in the Sahel: (a) in the 34 woody species measured; and (b) in nine species common to the two sites sampled (Ségou, Mali, and Louga, Senegal; see Table 1 and Supporting Information Table S1). Variance partitioning between sites (15 sample sites, brown) and species (interspecific, green) is shown; residual variance is also shown (light gray). Leaf trait abbreviations and units are as follows: leaf Nmass, leaf nitrogen concentration on a mass basis (%); leaf Narea (mg cm−2), leaf N content per leaf area; SLA (m2 kg−1), specific leaf area; leaf thick, leaf thickness (mm); leaf δ13C, leaf carbon isotopic composition (‰); c i/c a, ratio of intercellular and ambient CO2 concentrations (unitless); leaf δ18O, leaf oxygen isotopic composition (‰); leaf Δ18O, leaf 18O enrichment above source (xylem) water (‰); xylem δ18O, xylem water oxygen isotopic composition (‰); RWC, leaf relative water content (g g−1); Ψpd, predawn stem water potential (MPa); leaf δ15N, leaf nitrogen isotopic composition (‰). Leaf δ18O was unrelated to xylem water δ18O across species and sites, indicating that variation in leaf δ18O was not primarily driven by inter‐plant differences in source water isotopic composition or root water uptake depth. Instead, both foliar δ18O and Δ18O were positively related to leaf δ13C (Fig. 3; Table 3), indicating that foliar oxygen isotopic composition primarily reflected leaf‐level evaporative effects related to stomatal regulation and time‐integrated stomatal conductance and cumulative transpiration (Fig. 3). Moreover, both foliar δ18O/Δ18O and δ13C correlated positively with leaf Narea, revealing tighter stomatal regulation and higher WUEi with increasing carboxylation capacity (i.e. leaf Narea; Fig. 3; marginally significant for leaf Narea‐δ13C relationship). Furthermore, leaf δ18O and Δ18O correlated closely with RWC (Fig. 3; Table 3), suggesting that tighter stomatal regulation and lower time‐integrated stomatal conductance are linked to improved leaf hydration during the early dry season in dryland species.
Fig. 3

Relationships between different pairs of traits measured in 34 woody species in the Sahel (n = 168–230 individuals): relationship between leaf Narea and leaf carbon isotopic composition (δ13C) (a), leaf oxygen isotopic composition (δ18O) (b) and predawn stem water potential (Ψpd) (c), between leaf δ13C and leaf δ18O isotopic composition (d), and between relative water content (RWC) and leaf δ18O (e) and leaf oxygen isotopic enrichment above source (xylem) water (Δ18O) (f). Solid lines represent the model‐predicted relationships, and dotted lines the 95% confidence intervals. Colored dots depict different species. Log‐transformed Narea values (negative scale) are shown in panels (a–c).

Table 3

Results from linear mixed regression models for pairwise relationships between key traits analyzed in this study (many of them included in the a priori structural equation modeling; see Fig. 1) for the whole dataset (N = 34 species).

Predictor variableResponse variableSlopeSE F‐value P‐value
Leaf Narea Leaf δ13C1.1620.6842.887 0.091
Leaf Narea Leaf δ18O5.2471.8697.885 0.005
Leaf Narea Leaf Δ18O5.6142.3625.648 0.019
Leaf Narea Ψpd −2.8690.51331.258 < 0.001
Leaf Narea RWC0.0200.0330.3680.545
Leaf Narea Leaf δ15N1.7620.52011.46 < 0.001
Leaf Nmass Leaf δ13C0.3120.1167.269 0.007
Leaf Nmass Leaf δ18O1.6740.5339.883 0.002
Leaf Nmass Leaf Δ18O1.3770.6544.437 0.036
Leaf Nmass Ψpd −0.5140.12517.048 0.000
Leaf Nmass RWC−0.0080.008−0.9230.357
Leaf Nmass Leaf δ15N0.4470.2054.756 0.030
Leaf δ18OΨpd −0.0070.0150.1770.674
Leaf δ18ORWC0.0040.00117.57 < 0.001
Xylem water δ18OLeaf δ18O−0.0570.1220.2180.641
Leaf δ13CΨpd −0.0530.0521.0480.307
Leaf δ13CRWC−0.0020.0030.3420.559
Leaf δ13CLeaf δ18O0.7580.21312.641 < 0.001

Shown are the slope and standard error of the slope (SE) and F‐ and P‐values (significant relationships, i.e. P < 0.05, are in bold, and marginal significant relationships are in italics). Trait abbreviations are as in Table 2.

Relationships between different pairs of traits measured in 34 woody species in the Sahel (n = 168–230 individuals): relationship between leaf Narea and leaf carbon isotopic composition (δ13C) (a), leaf oxygen isotopic composition (δ18O) (b) and predawn stem water potential (Ψpd) (c), between leaf δ13C and leaf δ18O isotopic composition (d), and between relative water content (RWC) and leaf δ18O (e) and leaf oxygen isotopic enrichment above source (xylem) water (Δ18O) (f). Solid lines represent the model‐predicted relationships, and dotted lines the 95% confidence intervals. Colored dots depict different species. Log‐transformed Narea values (negative scale) are shown in panels (a–c). Results from linear mixed regression models for pairwise relationships between key traits analyzed in this study (many of them included in the a priori structural equation modeling; see Fig. 1) for the whole dataset (N = 34 species). Shown are the slope and standard error of the slope (SE) and F‐ and P‐values (significant relationships, i.e. P < 0.05, are in bold, and marginal significant relationships are in italics). Trait abbreviations are as in Table 2.

Modulation of water‐use efficiency by leaf Narea is achieved through both enhanced carboxylation capacity and tighter stomatal regulation in dryland trees

The SEM analysis (Fig. 1) indicated that both higher leaf N concentration on a mass basis (Nmass) and lower SLA (i.e. higher LMA) contributed to enhance leaf Narea in dryland trees and shrubs. As predicted by theory and global datasets, leaf Nmass and SLA (1/LMA) were positively related to each other across species (e.g. Wright et al., 2004). Furthermore, the SEM analysis revealed two simultaneous pathways that explained the positive relationship between leaf Narea and δ13C‐WUEi in dryland species (Fig. 1b). A main SEM pathway linking leaf Narea, δ18O and δ13C highlighted a strong influence of leaf Narea on foliar δ18O (β = 0.20, P < 0.01), indicating tighter stomatal regulation and lower time‐integrated stomatal conductance with increasing leaf Narea, which in turn contribute to enhanced WUEi through leaf δ18O/stomatal effects on δ13C‐WUEi (β = 0.22, P < 0.01). Leaf Narea also had a smaller direct positive effect on leaf δ13C (β = 0.14, P = 0.07; marginally significant; Fig. 1b) that was unrelated to stomatal effects, which we interpret as an indication of enhanced carboxylation capacity with increasing Narea across species (as predicted by theory) that further contributes to increase WUEi. Pairwise regression analyses between leaf traits further supported the key role of a high leaf Narea in enhancing carboxylation capacity, thereby allowing a tighter stomatal regulation of transpiration (i.e. lower time‐integrated stomatal conductance) and higher WUEi. It is worth highlighting that, in addition to the positive pairwise relationship between leaf Narea and δ13C (Figs. 1, 3; marginally significant), there was also a stronger positive pairwise relationship between leaf Nmass and δ13C (Table 3). Leaf Narea was also positively correlated with leaf δ15N, and negatively correlated with predawn water potential (Table 3), the latter suggesting greater tree ability to sustain more negative water potentials probably through internal plant osmoregulation linked to accumulation of N‐based osmolytes (Fig. 3c). Pairwise regression analyses also revealed a strong positive relationship between leaf δ13C and δ18O across dryland species (Fig. 3d), further evidencing a shared stomatal control on both traits. Moreover, tighter stomatal regulation and lower time‐integrated stomatal conductance (inferred from higher leaf δ18O and Δ18O values) were linked to improved leaf hydration and higher leaf relative water content in dryland woody species (Fig. 3e,f). The majority of N‐fixing species in our dataset where drought deciduous (Table 1), so we thereafter tested the robustness of the described links among traits within the subset of drought deciduous species only, in order to ascertain that the potentially confounding effects of contrasting leaf phenology (evergreen/deciduous) were not biasing the results of the SEM analyses (while at the same encompassing the full range of Narea and Nmass values present in the dataset). Within the subset of deciduous species (i.e. excluding evergreens), SEM analyses revealed very similar links among traits; however, the overall fit of the SEM analysis was poorer as a result of low statistical power (n = 87; data not shown). Anyhow, pairwise relationships between variables for deciduous species were also similar to those found in the whole dataset (Table S3), which further confirms the robustness of the described patterns.

Differences in plant traits between dryland legumes and nonlegumes

Dryland legumes (Fabaceae) had, on average, higher leaf Nmass, SLA and δ18O/Δ18O values, and thinner, less sclerophyllous leaves compared with nonlegumes (Fig. 4). By contrast, legumes and nonlegumes did not differ significantly in leaf Narea, δ13C (Fig. 4) or leaf RWC (F 1,212 = 0.67; P = 0.414), predawn water potential of stems (F 1,215 = 1.35; P = 0.247), xylem water δ18O values (F 1,202 = 1.64; P = 0.202) or average tree height (F 1,219 = 1.19; P = 0.276).
Fig. 4

Differences in average trait values between legume and nonlegume species from the Sahel. From left to right panels and from the top to the bottom panels: leaf N content on a mass basis (leaf Nmass), leaf N content per leaf area (leaf Narea), specific leaf area (SLA), leaf thickness, leaf oxygen isotopic composition (leaf δ18O), leaf oxygen enrichment above source (xylem) water (leaf Δ18O), leaf carbon isotopic composition (leaf δ13C), and leaf N isotopic composition (leaf δ15N) measured in nonlegumes (nonFabaceae, nonFab) and legumes (Fabaceae species, Fab). Values included in each panel are F‐Fisher results (F , where n 1 and n 2 are degrees of freedom) of the linear mixed models testing differences between nonFab and Fab species and model significance (**, P < 0.01; ***, P < 0.001; ns, nonsignificant differences). Results are shown as boxplots that include different components: midline, median; upper and lower box edges, first and third quartiles; whiskers, 5% and 95% confidence intervals; points, outliers.

Differences in average trait values between legume and nonlegume species from the Sahel. From left to right panels and from the top to the bottom panels: leaf N content on a mass basis (leaf Nmass), leaf N content per leaf area (leaf Narea), specific leaf area (SLA), leaf thickness, leaf oxygen isotopic composition (leaf δ18O), leaf oxygen enrichment above source (xylem) water (leaf Δ18O), leaf carbon isotopic composition (leaf δ13C), and leaf N isotopic composition (leaf δ15N) measured in nonlegumes (nonFabaceae, nonFab) and legumes (Fabaceae species, Fab). Values included in each panel are F‐Fisher results (F , where n 1 and n 2 are degrees of freedom) of the linear mixed models testing differences between nonFab and Fab species and model significance (**, P < 0.01; ***, P < 0.001; ns, nonsignificant differences). Results are shown as boxplots that include different components: midline, median; upper and lower box edges, first and third quartiles; whiskers, 5% and 95% confidence intervals; points, outliers. When considering only deciduous species (n = 19 spp.), legumes had marginally higher leaf δ13C‐WUEi (Fig. S2) than nonlegumes, along with higher leaf Nmass and δ18O/Δ18O values and thinner leaves. Differences in leaf Nmass between legumes and nonlegumes were larger in deciduous species than in the whole dataset, which includes evergreens (0.75% vs 0.39% higher Nmass in Fabaceae, deciduous vs all spp., respectively). Compared with deciduous nonlegumes (nonFab), deciduous legumes (Fab) also had significantly lower predawn water potentials (−1.41 ± 0.36 vs −2.02 ± 0.36 MPa, nonFab vs Fab; F 1,114 = 22.82, P < 0.0001) and higher xylem water δ18O values (−4.75 ± 0.47 vs −3.78 ± 0.51‰, nonFab vs Fab; F 1,106 = 4.04, P = 0.047), suggesting colonization of drier microsites and use of shallower, more evaporatively enriched soil water sources by deciduous legumes.

Discussion

Variation in SLA, leaf Nmass, Narea and water‐related isotope traits (δ13C, δ18O, Δ18O) among Sahelian woody plants was strikingly large, revealing large interspecific differences in the relative costs of nitrogen and water acquisition. This finding can be interpreted in light of the least‐cost economic theory of photosynthesis, showing that nitrogen and water are mutually substitutable resources to achieve a given photosynthetic carbon gain, so that the cost associated with acquiring one of them can be alleviated by increased supply of the other (Wright et al., 2001, 2003; Prentice et al., 2014; Wang et al., 2017). Therefore, a high photosynthesis can be achieved by either high leaf Narea or high stomatal conductance, so that the total cost per unit photosynthetic carbon gain associated with carboxylation and transpiration is minimized under the environmental conditions prevailing in the plant's habitat (Paillassa et al., 2020). Within this optimality framework, the positive foliar Narea–δ18O and Narea–δ13C correlations found across Sahelian plants are in agreement with the theory's prediction that a high leaf Narea should allow higher carboxylation capacity, tighter stomatal regulation of transpiration for any given carbon assimilation rate and more efficient use of water in dryland vegetation (Wright et al., 2001, 2003). The structural equation model analysis revealed that the link between leaf Narea and δ13C‐WUEi was driven by an enhanced carboxylation capacity but even more strongly by a tighter stomatal regulation of transpiration (inferred from leaf δ18O) with increasing leaf Narea. To our knowledge, this is the first study demonstrating a robust mechanistic link between leaf N content per area and foliar oxygen isotope composition in dryland vegetation, which is fully consistent with first principles of plant physiology (Wright et al., 2001, 2003; Dong et al., 2017). Our pool of 34 phylogenetically diverse tree and shrub species spanned c. 70% of the range of δ13C values commonly encountered in C3 vegetation at global scale (−22 to −32‰; Kohn, 2010; Maire et al., 2015; Cornwell et al., 2018; Paillassa et al., 2020). The hot and dry climate with a short rainy season and the nutrient‐poor sandy soils and flat terrain of low elevation (< 300 m asl) that prevail across our sampling sites appear to offer limited potential for environmental heterogeneity and niche segregation that could favor such wide c i/c a divergence among coexisting Sahelian woody species. However, more subtle environmental heterogeneity regarding microtopography, groundwater accessibility to roots, soil fertility or microclimatic conditions across and within sampling sites may create opportunities for niche segregation and physiological divergence among species (Álvarez‐Yépiz et al., 2017). Environmental heterogeneity could also explain the large within‐species variability encountered for some key traits, including leaf Narea, δ18O and δ13C (Donovan et al., 2007). Nonetheless, the strikingly large interspecific differences in trait values encountered in this study primarily reflect idiosyncratic differences in leaf physiology and resource use strategies among coexisting species, and must therefore have an evolutionary basis (Fig. 2). The average c i/c a ratio of Sahelian woody species (0.74) was unexpectedly high considering their rather high leaf N concentrations (> 2% on average), Narea values and the high vapor pressure deficit (VPD) prevailing across sampling sites (for comparison, see the average c i/c a ratios typically found in drylands as reported by Prentice et al. (2014) and Paillassa et al. (2020)). High leaf Narea and carboxylation capacity combined with high VPD would be expected to favor tight stomatal regulation of leaf gas exchange, leading to very low c i/c a ratios (Cernusak et al., 2013; Cornwell et al., 2018; Grossiord et al., 2020; Paillassa et al., 2020). However, extremely hot temperatures combined with the high O2 partial pressure at low elevations may boost photorespiration in C3 plants, thereby constraining photosynthetic nitrogen‐use efficiency and preventing further decreases in c i (Paillassa et al., 2020; but see also Terashima et al., 1995). Moreover, low availability of soil P or other essential nutrients for photosynthesis as a result of poor soil fertility may further constrain carbon assimilation capacity despite high leaf Narea (Augusto et al., 2017; Du et al., 2020; Paillassa et al., 2020). Alternatively, the high c i/c a ratios observed in our study may simply reflect that most of the annual carbon assimilation in Sahelian species takes place during the short rainy season when high soil water availability may help to sustain high stomatal conductance, but with little additional carbon assimilation during the drier part of the year (Choat et al., 2006). Finally, taproot access to relatively shallow groundwater may have further contributed to higher‐than‐expected average c i/c a ratios, particularly for some phreatophytic species that can behave as profligate water users under hot and high VPD conditions (Gries et al., 2003). The leaf δ18O and Δ18O values of Sahelian woody species were generally lower than those of trees and shrubs from other drylands with less extreme temperature, VPD and more fertile soils (e.g. semiarid Mediterranean ecosystems; Cernusak et al., 2005; Moreno‐Gutiérrez et al., 2012, 2015). This suggests rather high stomatal conductance during the short growing season, possibly linked to the need for evaporative leaf cooling to prevent leaf overheating and damage of the photosynthetic machinery under extremely hot conditions in the Sahel (Helliker & Richter, 2008; Aparecido et al., 2020). Moreover, high stomatal conductance may be needed to enhance nutrient harvesting through transpiration‐driven mass flow of soil nutrients to roots in these low‐fertility sandy soils (Cramer et al., 2009; Matimati et al., 2014; Salazar‐Tortosa et al., 2018). Modeling studies at a global scale have shown that stomatal conductance should reach peak levels in dry tropical vegetation (savannah trees; Lin et al., 2015). The high leaf Narea combined with low leaf δ18O, Δ18O and δ13C values of Sahelian woody plants suggests that they are capable of achieving high rates of transpiration and carbon assimilation during the short rainy season (Cornwell et al., 2018; Sibret et al., 2021). Sahelian woody vegetation may thus contribute substantially to global primary productivity, despite the severe water and nutrient limitations typical of these drylands (Ahlström et al., 2015; Smith et al., 2019; Brandt et al., 2020). High foliar N content can reflect the production and accumulation of N‐based osmolytes, such as proline, that enable plants to endure and sustain more negative internal water potentials during drought (Wink, 2013; Adams et al., 2016), as suggested by the strong negative correlation found between foliar Nmass and predawn water potential across species (Table 3). Accumulation of N‐based osmolytes enhances internal plant osmotic adjustment and thus the ability of N‐rich species to extract water held at progressively lower soil moisture potentials during dry periods, potentially conferring a competitive advantage in drylands (Giordano et al., 2011). Lower predawn water potentials with increasing foliar N content may thus indicate greater drought tolerance and a superior ability to establish in drier microsites in N‐rich species such as legumes.

Limited N fixation in dryland legumes

The wide range of leaf δ15N values encountered among Sahelian woody species revealed the existence of a wide diversity of N‐acquiring mechanisms and N sources (Craine et al., 2008). Sahelian trees and shrubs exhibited remarkably high foliar δ15N values, suggesting high rates of gaseous N losses from the soil system (i.e. through ammonia volatilization, nitrification and denitrification) that could explain the heavy 15N enrichment of leaf nitrogen pools despite vegetation dominance by N2‐fixing legumes (Craine et al., 2008, 2015; Ruiz‐Navarro et al., 2016). High rates of gaseous N losses from the soil system may be greatly favored by hot temperatures and transiently moist soil conditions during the short Sahel rainy season, which are known to stimulate the abiotic (e.g. ammonia volatilization) and biotic (e.g. microbial denitrification) processes driving gaseous N losses from soil (Craine et al., 2015). The large inputs of 15N‐enriched livestock manure in Sahelian silvopastoral systems may further stimulate heavy gaseous N losses and 15N enrichment of the remaining soil and vegetation N pools. Interestingly, highly enriched plant δ15N values were also reported in the Kalahari drylands dominated by woody legumes growing on nutrient‐poor sandy soils (Aranibar et al., 2004). Contrary to expectations, the remarkably high leaf δ15N values found in legumes were indistinguishable from those of nonlegumes, which suggests that atmospheric N2 fixation may not be their primary source of nitrogen, possibly as a result of the strong water and P limitation imposed on biological N2 fixation by the weathered sandy soils of the Sahel (Breman & De Wit, 1983; Henao & Baanante, 1999; Vitousek et al., 2010). Sahelian legumes may instead deploy other effective N‐acquiring mechanisms that may contribute to their higher average leaf N concentration as a group (McKey, 1994; Dovrat et al., 2020). Moreover, the livestock habit of seeking shelter under the shade of large trees and shrubs in this hot climate may provide an abundant external N subsidy of animal origin from the surrounding grasslands in the silvopastoral systems of the Sahel. This ‘fertility’ island effect could be even greater under legume trees and shrubs producing nutritious pods or fodder that are attractive for livestock (Casals et al., 2014; Hoosbeek et al., 2018).

Differences in water‐use traits between legumes and other species

The higher average leaf δ18O and Δ18O values of legumes compared with nonlegumes revealed a tighter stomatal regulation of transpiration with lower time‐integrated stomatal conductance, which may represent a key physiological advantage of Fabaceae that could contribute decisively to their dominance across the Sahel and other tropical dryland ecosystems (Felker, 1981; Sprent & Gehlot, 2010; Pellegrini et al., 2016; Gei et al., 2018). However, dryland legumes as a group exhibited higher leaf N concentrations (Nmass) but did not exhibit significantly higher average leaf Narea or δ13C‐WUEi values than nonlegumes, even though higher leaf Nmass was strongly linked to higher δ13C‐WUEi across the whole dataset (Table 3). This was an unexpected result, as tighter stomatal control of transpiration in N‐rich legumes (inferred from their high leaf δ18O and Δ18O values) would be expected to also lead to higher δ13C‐WUEi. Moreover, higher leaf Nmass in legumes would be expected to enhance carboxylation capacity and thus lead to greater drawdown of CO2 concentration at the sites of carbon fixation, thereby widening the c a – c c gap (i.e. lower c c/c a ratios) and further enhancing δ13C‐WUEi (Wright et al., 2001, 2003; Prentice et al., 2011, 2014; Onoda et al., 2017). However, it is important to note that average Narea values did not differ significantly between legumes and nonlegumes, because much higher average LMA in nonlegumes (i.e. thicker leaves with lower SLA) compensated for their lower leaf Nmass, thereby leading to converging and similar Narea and δ13C‐WUEi values between these two plant functional groups. In other words, Sahelian legumes and nonlegumes achieved similar average Narea and δ13C‐WUEi values through contrasting trait combinations: high SLA and leaf N concentrations in legumes vs lower N concentrations with lower SLA values (i.e. higher LMA) in nonlegumes. Several other nonmutually exclusive hypotheses could further contribute to explain the unexpected lack of differences in average δ13C‐WUEi values between legumes and nonlegumes: a substantial proportion of leaf N in Sahelian legumes may be invested in nonphotosynthetic proteins, such as N‐based osmolytes and/or defensive compounds against herbivores (Adams et al., 2016); the thin, high‐SLA, nitrogen‐rich leaves of legumes may exhibit high mesophyll conductance to CO2 (g m) favoring high CO2 concentration at the sites of carboxylation (c c) (Seibt et al., 2008; Niinemets et al., 2009; Onoda et al., 2017; Ma et al.,  2021); legumes could be more prone to photorespiration burdens under hot conditions if their tighter stomatal regulation of transpiration and lower time‐integrated stomatal conductance hamper evaporative leaf cooling aimed at alleviating overheating. A higher vulnerability to leaf overheating and photorespiration in legumes would constrain carbon assimilation capacity and impede any further decreases in c i despite their high leaf N concentrations (Paillassa et al., 2020). All this would help to reconcile the lower stomatal conductance of legumes as a group (inferred from their higher leaf δ18O and Δ18O) with the unexpected lack of differences in c i/c a ratios between legumes and nonlegumes, along with the similar Narea between both functional groups (Warren & Adams, 2006). Nonetheless, it should be noted that the subset of deciduous legumes still had marginally higher mean leaf δ13C‐WUEi value and higher Narea as a group compared with deciduous nonlegumes (Fig. S2), as previously reported at a global scale (Adams et al., 2016). Achieving any given leaf Narea value through high SLA and Nmass (as in dryland legumes) could be more effective for enhancing carboxylation and photosynthetic nitrogen‐use efficiency than achieving it through lower SLA (i.e. higher LMA) with lower Nmass (as in nonlegumes), given that a larger proportion of leaf N is usually invested in nonphotosynthetic structural tissues and compounds in low SLA leaves (e.g. cell walls; Poorter & Evans, 1998; Onoda et al., 2017). In conclusion, the Western Sahelian drylands harbor woody species with strikingly diverse leaf δ18O and δ13C values and water‐use strategies that appear to be similarly adaptive to cope with the dual challenge imposed by drought and nutrient‐poor soils (Wright et al., 2001). Our findings provide strong experimental support for the least‐cost economic theory of photosynthesis in which water and nitrogen are mutually substitutable resources to achieve a given carbon assimilation gain in dryland ecosystems (Wright et al., 2003). Structural equation modeling revealed that foliar Narea is a pivotal trait linked to multiple other traits related to water use in Sahelian woody vegetation. In particular, higher leaf Narea is linked to both higher carboxylation capacity and tighter stomatal regulation of transpiration, which in turn is associated with higher WUEi and a more conservative water‐use strategy in dryland trees. Legumes possess several key functional traits that may help them thrive under the harsh environmental conditions of the Sahel. Their efficient N‐acquiring ability enables them to achieve both high carboxylation capacity and tight stomatal control of transpiration and may also enhance their drought tolerance through improved osmotic adjustment and ability to extract water from drying soil. Finally, our study highlights the promise offered by leaf δ18O and δ13C measurements as useful functional traits for screening the water‐use strategies of multiple species in remote dryland locations where extensive gas exchange measurements are often not feasible.

Author contributions

GMR and FIP conceived the FUNCiTREE project and designed the general field campaign. JIQ designed the hypotheses to be tested with the help of IP and CA, and proposed new variables to be measured. IP led the statistical analyses with the help of FC and CA. Field data collection was led by GMR, CA, MD, JSD, HY and BK, and CA organized the laboratory analyses, and assembled and curated the database. JIQ, IP and CA wrote the first draft of the manuscript, and all authors contributed substantially to revisions. JIQ, IP and CA contributed equally to this work. Fig. S1 Climograms for the studied regions in the Sahel. Fig. S2 Differences in trait values between deciduous legume and deciduous nonlegume woody species. Table S1 Summary statistics of 12 functional traits measured in 34 woody species in the Sahel (Mali and Senegal). Table S2 Phylogenetic tree for the 34 target species and phylogenetic signals in measured traits. Table S3 Pairwise relationships between all traits analyzed in legumes and deciduous tree species. Please note: Wiley Blackwell are not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office. Click here for additional data file.
  52 in total

1.  Internal conductance does not scale with photosynthetic capacity: implications for carbon isotope discrimination and the economics of water and nitrogen use in photosynthesis.

Authors:  Charles R Warren; Mark A Adams
Journal:  Plant Cell Environ       Date:  2006-02       Impact factor: 7.228

2.  Physiological and structural tradeoffs underlying the leaf economics spectrum.

Authors:  Yusuke Onoda; Ian J Wright; John R Evans; Kouki Hikosaka; Kaoru Kitajima; Ülo Niinemets; Hendrik Poorter; Tiina Tosens; Mark Westoby
Journal:  New Phytol       Date:  2017-03-10       Impact factor: 10.151

3.  Resource partitioning by evergreen and deciduous species in a tropical dry forest.

Authors:  Juan C Álvarez-Yépiz; Alberto Búrquez; Angelina Martínez-Yrízar; Mark Teece; Enrico A Yépez; Martin Dovciak
Journal:  Oecologia       Date:  2016-12-03       Impact factor: 3.225

4.  Contrasting responses of crop legumes and cereals to nitrogen availability.

Authors:  Mark A Adams; Thomas N Buckley; William T Salter; Nina Buchmann; Carola H Blessing; Tarryn L Turnbull
Journal:  New Phytol       Date:  2017-11-27       Impact factor: 10.151

5.  Legumes are different: Leaf nitrogen, photosynthesis, and water use efficiency.

Authors:  Mark Andrew Adams; Tarryn L Turnbull; Janet I Sprent; Nina Buchmann
Journal:  Proc Natl Acad Sci U S A       Date:  2016-03-30       Impact factor: 11.205

6.  Plant δ15 N reflects the high landscape-scale heterogeneity of soil fertility and vegetation productivity in a Mediterranean semiarid ecosystem.

Authors:  Antonio Ruiz-Navarro; Gonzalo G Barberá; Juan Albaladejo; José I Querejeta
Journal:  New Phytol       Date:  2016-07-13       Impact factor: 10.151

7.  An unexpectedly large count of trees in the West African Sahara and Sahel.

Authors:  Martin Brandt; Compton J Tucker; Ankit Kariryaa; Kjeld Rasmussen; Christin Abel; Jennifer Small; Jerome Chave; Laura Vang Rasmussen; Pierre Hiernaux; Abdoul Aziz Diouf; Laurent Kergoat; Ole Mertz; Christian Igel; Fabian Gieseke; Johannes Schöning; Sizhuo Li; Katherine Melocik; Jesse Meyer; Scott Sinno; Eric Romero; Erin Glennie; Amandine Montagu; Morgane Dendoncker; Rasmus Fensholt
Journal:  Nature       Date:  2020-10-14       Impact factor: 49.962

Review 8.  Environmental and physiological determinants of carbon isotope discrimination in terrestrial plants.

Authors:  Lucas A Cernusak; Nerea Ubierna; Klaus Winter; Joseph A M Holtum; John D Marshall; Graham D Farquhar
Journal:  New Phytol       Date:  2013-07-31       Impact factor: 10.151

9.  Carbon isotope discrimination in three semi-arid woodland species along a monsoon gradient.

Authors:  David G Williams; James R Ehleringer
Journal:  Oecologia       Date:  1996-06       Impact factor: 3.225

10.  Nutrient concentration ratios and co-limitation in South African grasslands.

Authors:  Joseph M Craine; Carl Morrow; William D Stock
Journal:  New Phytol       Date:  2008-06-05       Impact factor: 10.151

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