DOI: 10.5061/dryad.pzgmsbcv4
title: Pushing the limits of C3 intrinsic water use efficiency in Mediterranean semiarid steppes: responses of a drought-avoider perennial grass to climate aridification

description: Intrinsic water use efficiency (WUEi) reflects the trade-off between
 photosynthetic carbon gain and water loss through stomatal conductance and
 is key for understanding dryland plant responses to climate change. Stipa
 tenacissima is a perennial tussock C3 grass with an opportunistic,
 drought-avoiding water use strategy that dominates arid and semiarid
 steppes across the western Mediterranean region. However, its
 ecophysiological responses to aridification and woody shrub encroachment,
 a major land-use change in drylands worldwide, are not well understood. We
 investigated the variations in leaf stable isotopes (δ18O, δ13C, δ15N),
 nutrient concentrations (N, P, K), and culm water content and isotopic
 composition (δ18O, δ2H) of paired pure-grass and shrub-encroached S.
 tenacissima steppes along a 350 km aridity gradient in Spain (10 sites,
 160 individuals).  Culm water isotopes revealed that S.
 tenacissima is a shallow-rooted grass that depends heavily on recent
 rainwater for water uptake, which may render it vulnerable to increasingly
 irregular rainfall combined with faster topsoil drying under climate
 warming and aridification. With increasing aridity, S. tenacissima
 enhanced leaf-level WUEi through more stringent stomatal regulation of
 plant water flux and carbon assimilation (higher δ13C and δ18O), reaching
 exceptionally high δ13C values (-23 to -21‰) at the most arid steppes.
 Foliar N concentration was remarkably low across sites regardless of woody
 shrub encroachment, evidencing severe water and N co-limitation of
 photosynthesis and productivity. Shrub encroachment decreased leaf P and K
 but did not affect S. tenacissima water status. Perennial grass cover
 decreased markedly with both declining winter rainfall and shrub
 encroachment suggesting population- rather than individual-level responses
 of S. tenacissima to these changes. The fundamental physiological
 constraints of photosynthetic C3 metabolism combined with low foliar N
 content may hamper the ability of S. tenacissima and other drought-avoider
 species with shallow roots to achieve further adaptive improvements in
 WUEi under increasing climatic stress. A drought-avoiding water use
 strategy based on early stomatal closure and photosynthesis suppression
 during prolonged rainless periods may thus compromise the capacity of S.
 tenacissima steppes to maintain perennial grass cover, sustain
 productivity and cope with ongoing climate aridification at the drier
 parts of their current distribution. 
description: We selected 10 locations along a ~350 km transect from Central to
 Southeastern Spain (Fig. S1) representing an increasing climatic aridity
 gradient encompassing much of the geographical distribution of
 <em>S. tenacissima</em> in the Iberian Peninsula, including
 areas with MAP ranging from 346 to 464 mm and mean annual temperature
 (MAT) from 12.6 to 16.3℃ (Supporting Information Table S1, S2). The
 climate is semiarid Mediterranean, with asynchronous wet and warm seasons,
 as maximum and minimum precipitation fall in winter and summer,
 respectively. The soils are classified as Calcisols and are weakly
 developed and thin, with sandy loam texture and high pH values
 (&gt;7–8) (Maestre<em> et al.</em> 2009). Transpiration
 fluxes and primary productivity in semiarid <em>S. tenacissima
 </em>steppes are rather low, with peak plant ecophysiological
 activity occurring shortly after the irregular rainfall pulses
 (Domingo<em> et al.</em> 2011). Using the
 geographical coordinates of each location, we obtained the elevation and
 available climatic information from Worldclim (http://www.worldclim.org;
 Hijmans<em> et al.</em> 2005), and measured the minimum
 distance to the Mediterranean Sea (DTMS) using Google Earth. Climate
 variables included temperature and precipitation (mean annual, average of
 the wettest and coldest quarter and month, average of the driest and
 warmest quarter and month). We calculated the Aridity for each location as
 A= 1- (annual precipitation/annual potential evapotranspiration). Mean
 annual vapor pressure deficit (VPD) for each location was obtained from
 TerraClimate data (Abatzoglou<em> et al.</em> 2018). Several
 geographic and climatic variables showed substantial multi-collinearity
 along the aridity gradient (Table S3). Field
 surveys Field sampling was conducted during May 2008,
 and no permissions were needed for fieldwork. At each sampling location,
 we selected two paired sites with contrasting woody shrub cover (i.e. pure
 <em>S. tenacissima</em> grass steppes vs. nearby
 shrub-encroached steppes with 26.4% shrub cover; see Maestre <em>et
 al</em>. 2009), totaling 20 sites. The encroaching shrub species
 were <em>Quercus coccifera</em>, <em>Pistacia
 lentiscus</em>, <em>Rhamnus lycioides,</em>
 <em>Juniperus phoenicea</em> and <em>Juniperus
 oxycedrus</em>. Plant cover at each site was measured using the
 point-intercept methodology in four 30-m transects separated 8 m from each
 other. At each of the 20 sites, we sampled 8 adult
 <em>S. tenacissima</em> individuals (replicates) resulting in
 160 individuals. The canopy size of each tussock individual was measured
 using two diameters (parallel and perpendicular to the steepest slope) and
 calculated using the formula for the area of an ellipse. At sites
 undergoing woody shrub encroachment, we sampled tussock individuals
 located at a fixed distance (5-m) from the canopy edge of woody shrubs to
 exclude direct, immediate competition effects between shrubs and
 <em>S. tenacissima </em>at close range. Our assessment of how
 woody shrub encroachment impacts on the water and nutrient status of
 <em>S. tenacissima</em> focuses on diffuse competitive effects
 of encroaching shrubs, and therefore excludes the effects of direct,
 interspecific shrub-grass interactions at close range.
 Isotopic and nutrient analyses Fully
 expanded and healthy-looking leaves with their corresponding basal culms
 were collected for isotopic and nutrient analyses. Green leaf samples were
 oven-dried (60℃, 24h) and finely ground using a ball mill. Leaf
 δ<sup>13</sup>C and δ<sup>15</sup>N were measured
 by continuous flow dual isotopic analysis using an IsoPrime 100 IRMS
 (IsoPrime, UK) interfaced to a CHNOS C/N Elemental Analyzer. Leaf
 δ<sup>18</sup>O was measured in continuous flow using an
 Elementar PYRO Cube interfaced to a Thermo Finnigan Delta V IRMS (Thermo
 Finnigan, Germany). The analytical precision was ±0.1‰ for leaf
 δ<sup>13</sup>C and ±0.2‰ for leaf δ<sup>18</sup>O
 and δ<sup>15</sup>N. Ground leaves were digested with
 HNO<sub>3</sub>:HClO<sub>4 </sub>(2:1, v:v) and P
 and K concentrations were measured in the digested solution by a Perkin
 Elmer Inductively Coupled Plasma 5500 atomic absorption
 spectrometer. Time-integrated WUEi at leaf level was
 estimated based on foliar δ<sup>13</sup>C values (Cernusak
 <em>et al.,</em> 2013) as determined by the atmospheric
 CO<sub>2</sub> concentration (385.97 ppm in 2008) and the
 ratio of atmospheric [CO<sub>2</sub>] to intracellular
 [CO<sub>2</sub>]
 (<em>c<sub>i</sub>/c<sub>a</sub></em>)
 as follows:   WUEi = <em>A/g<sub>s
 </sub></em>= <em>c<sub>a</sub>
 </em>[1-(<em>c<sub>i</sub>/c<sub>a</sub></em>)]×0.625                           Eqn (1) d<sup>13</sup>C<sub>leaf </sub>= d<sup>13</sup>C<sub>atm </sub>– a - (b-a)×(<em>c<sub>i</sub>/c<sub>a</sub></em>)                           Eqn (2) <em> </em> where δ<sup>13</sup>C<sub>leaf</sub> is the foliar isotope ratio, δ<sup>13</sup>C<sub>atm</sub> is isotopic ratio of atmospheric CO<sub>2</sub> (-8.321‰ in 2008) and a and b are isotopic fractionation factors associated with CO<sub>2</sub> diffusion (4.4‰) and Rubisco discrimination (27‰), respectively. Non-transpiring basal culms (5-6) from the base of the perennial tussock grasses near ground level were collected from each target individual as a proxy of the isotopic signature of source water used by <em>S. tenacissima </em>at the peak of the growing season. The basal culms were quickly placed in capped glass vials, sealed with parafilm, transported in coolers, and stored in the freezer (-20℃) until water extraction. Water extractions were performed using cryogenic vacuum distillation and lasted 2-4 h at 105 ºC until culm water was extracted completely. Culm water content (CWC) was calculated as:   CWC=(W<sub>wet</sub>-W<sub>dry</sub>)/W<sub>wet</sub>·100%                                Eqn (3)   where W<sub>wet </sub>is the weight of fresh culm sample and W<sub>dry</sub> is the weight of culm sample after water extraction. The culm water δ<sup>18</sup>O and δ<sup>2</sup>H values of half of the samples (n=80) were determined by continuous flow using a Thermo Gas Bench II interfaced to a Thermo Finnigan Delta plus XL IRMS (Thermo Finnigan, Germany). The analytical precision was ±0.12‰ for δ<sup>18</sup>O and ±0.6‰ for δ<sup>2</sup>H. Water extracted from non-transpiring tissues in grasses inevitably includes some phloem water mixed with xylem water, which may cause some isotopic fractionation issues (Barnard et al., 2006; Jiang et al., 2022).
description: # Pushing the limits of C3 intrinsic water use efficiency in Mediterranean
 semiarid steppes: responses of a drought-avoider perennial grass to
 climate aridification ##
 Description of the data and file structure We investigated the variations
 in multiple plant traits in the perennial tussock grass *Stipa
 tenacissima* along an aridity gradient in Spain. Traits measured include
 leaf stable isotopes (δ18O, δ13C, δ15N), nutrient concentrations (N, P,
 K), and culm water content and isotopic composition (δ18O, δ2H) of paired
 pure-grass and shrub-encroached *S. tenacissima* steppes along a 350 km
 aridity gradient in Spain (10 sites, 160 individuals). Here, we provide a
 summary of mean (± SE), minimum and maximum values of *S. tenacissima*
 traits for pure grass and shrub-encroached steppes at ten sampling
 locations. The blank cells for the variable "Plant cover"
 indicate that there are no maximum or minimum values per study plot, just
 a single overall value for each study plot.