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Dryad

Data from: Growing at the arid edge: Leaf anatomy variations are more extensive than stems in five Mediterranean species across contrasting moisture regimes-all the raw data of the anatomic measurements

Cite this dataset

Alon, Asaf (2024). Data from: Growing at the arid edge: Leaf anatomy variations are more extensive than stems in five Mediterranean species across contrasting moisture regimes-all the raw data of the anatomic measurements [Dataset]. Dryad. https://doi.org/10.5061/dryad.7pvmcvf2k

Abstract

Premise:

The Mediterranean region is experiencing increasing aridity, affecting ecosystems and plant life. Plants exhibit various anatomical changes to cope with dry conditions, including anatomical changes. This study focused on five co-occurring Mediterranean plant species namely Quercus calliprinos, Pistacia palaestina, Pistacia lentiscus, Rhamnus lycioides, and Phillyrea latifolia in wet and dry sites, investigating anatomical differences in leaves and xylem.

Methods:

Leaf analysis involved stomatal density, stomatal length, Leaf Mass Area (LMA), lamina composition, quantification of leaf intercellular air spaces (IAS), and mesophyll cell area exposed to these spaces. Xylem anatomy was assessed through vessel length and area in branches.

Results:

In the dry site, three species showed increased stomatal density and decreased stomatal length. Four species exhibited increased palisade mesophyll (PM) and reduced air space volume. In contrast, the phenotypic change in the xylem was less pronounced, with vessel length remaining unaffected by the site conditions. Furthermore, vessel diameter decreased in two species. Intercellular air spaces (IAS) proved to be the most dynamic anatomical feature. Quercus calliprinos demonstrated the highest anatomical phenotypic changes, while Rhamnus lycioides exhibited minor changes.

Conclusions:

This study sheds light on the variation in anatomical responses among co-occurring Mediterranean plant species and identifies the most dynamic traits. Understanding these adaptations provides valuable insights into the ability of plants to thrive under changing climate conditions.

Methods

Histological preparations

The samples were collected in June 2021, at the beginning of the dry season. For stem anatomy, one cm long segments of 0.5 to 1 cm in diameter were taken from the terminal branches of new growth. The same branches were used for leaf anatomy, where a rectangle of 1 x 2 cm was cut along the lamina while avoiding the midrib. All samples were fixed immediately after cutting in a formaldehyde-acetic acid–alcohol solution (FAA, 10:5:50 in double-distilled water) for 48 h. Following gradual dehydration in an ethanol series (70, 80, 90, 95, and 100%, for 30 min each), the samples were subjected to a gradual Histoclear solution (25, 50, 75, and 100%). The samples were incubated overnight at room temperature with Paraplast chips (Leica, Wetzlar, Germany, Paraplast Plus) followed by several hours of incubation at 42 °C. The dissolved pure paraffin was changed twice a day for four days at 62 °C before the samples were embedded in blocks. Following embedding, stem samples were immersed in water for a few days and then sectioned using a microtome (Leica RM2245, Leica Microsystems Ltd. , Nussloch, Germany) into 12 μm sections which were mounted on slides, incubated overnight at 40 °C, and stained with Fast Green and Safranin (Ruzin and others, 1999). Images were captured using a light microscope (Leica DMLB, Leica Microsystems Ltd. , Nussloch, Germany) with a Nikon DS-fi1 camera (Nikon Corporation, Japan). Image analysis was done using ImageJ software (Rasband, W.S., ImageJ, US National Institutes of Health, Bethesda, MD, USA, http:// imagej.nih.gov/ij/, 1997–2015).

Leaf anatomy analyses

The leaf parameters (Table 3) were measured in eight samples from each of the five studied species at each site.

Leaf mass area (LMA) was computed by dividing the leaf dry mass (g) by the leaf area (cm²). Leaf area was determined through the analysis of RGB-scaled photos using ImageJ software. Subsequently, the leaves were dried at 70°C for 5 days, followed by measurement of the dry weight.

Stomatal density was measured from adaxial and abaxial epidermal imprints, which were made using a dental impression gel (CounterFit II, Clinician's Choice), followed by an impression of clear nail polish, which was removed using adhesive tape and mounted on a microscope slide. Stomata were counted on an area of 0.0837 mm2 which represented the whole image size at the corresponding magnification (x40).

Lamina anatomy was analyzed from leaf cross sectional images using the ImageJ software to obtain thickness values in microns for the different leaf organs: adaxial (Ad) and abaxial (Ab) epidermis layers, palisade mesophyll (Pal) and spongy mesophyll (SM) as well as total leaf thickness (T). Cuticle thickness assessment was available only on the adaxial side (Ac) as the abaxial cuticle was indistinct. All parameters were measured at three different locations on a cross section. The Midrib vessel area was assessed by measuring the ten largest vessels using the ImageJ software.

Intercellular airspaces were evaluated from the mesophyll surface area exposed to intercellular airspace per unit leaf area , which was calculated according to (Evans et al., 1994)::

Where is the total length of mesophyll cells facing the intercellular air space,  is the section width and F is the curvature correction factor, which depends on the shape of the cells and was calculated as the weight average of the palisade and spongy mesophyll according to (Thain, 1983).

The fraction of the intercellular air space (%IAS) was calculated as

 Where ΣSs is the sum of the cross-sectional areas of the mesophyll cells and is the thickness of the mesophyll between the two epidermal layers.

Stem anatomy analyses

The stem parameters (Table 3) were measured in eight samples from each of the five studied species at each site.

Vessel length distribution was measured by the "air injection method" (Cohen et al., 2003), with some modifications according to Wang et al. (2014). Briefly, fresh long shoots were cut using a sharp razor blade. The basal end of the stem segment was attached to a flexible silicone tube (clamped to it) and connected to an air compressor which injected air into an old dial manometer and a digital pressure sensor (MPX5100 IC, NXP Semiconductors, Netherlands) wired to a datalogger (Campbell Sci.  CR1000 datalogger, Campbell Scientific, Inc., Utah, United States), along with a "bleed" valve. Pressure was adjusted to 0.08-0.15 MPa and logged during the measurements. The distal end of each shoot was immersed in water. Stem segments (2 cm long) were cut  back until bubbling was observed, and the length of the remaining stem was taken as the maximum vessel length (in some cases, bubbles appeared immediately before cutting, in which case the maximum vessel length was longer). Then, the stem was cut back consistently to measure air flow rate at several lengths. For each stem length, the bubbles flowing out from the distal end were collected in a volumetric cylinder by the water displacement method according to (Wang et al., 2014). The airflow rate [Q (mL/min)] was computed as follows:

Q =(Wi − Wf)/(ΔTρ)

Where Wi and Wf  are the initial and final weights of the volumetric cylinder respectively, ΔT is the time interval for the water displacement by the bubbles and ρ is the density of water displaced by the air.

Air conductivity (C) was calculated according to equation [4] at (Cohen et al., 2003) as follows:

Where L is the length of the wood segment (m), P is the distal pressure (kPa) at which the flow rate Q was measured at the distal end  is the average pressure in the segment and ΔP  is the pressure difference across the segment.

According to Cohen et al. (2003) C should decrease exponentially as:                                                 

Where  is the limiting conductivity as x approaches zero, k is the extinction coefficient and x is the stem length. The plot of the natural log of C versus x resulted in a linear plot, from which k was evaluated from the slope. The most common of mode vessel length (Lmode) was −1/k. The mean vessel length was calculated from Lmean = 2Lmode.

The probability density function (PDF) of vessel length was calculated as described in  (Cohen et al., 2003) and (Sperry et al., 2005) was:

Where  is the probability of vessels of length x and k (negative value) is the slope of the linear plot.

The vessel area/diameter was evaluated from the most two outer rings of the stem cross sections (described above), which were marked and measured manually by "tracking tool" by Image J software. The vessel diameter (D) was calculated from the vessel area as follows:

Statistical analyses 

The individual data for each anatomical trait are presented as boxplots. To test the effect of site, species, and their interaction on the anatomical traits, a two-way ANOVA was conducted using Python software (Python Software Foundation, Wilmington, Delaware, United States; package: statsmodel).Traits for which variances were non-homogeneous underwent logarithmic transformation before analysis.

To compare the two sites for each species, contrast t-tests were performed. To quantify the degree of the difference between the two sites for each species, the effect size was measured using Cohen's d method for each anatomy trait. The formula used for calculating Cohen's d is:

Cohen's d = (M1 - M2) / pooled standard deviation

where M1 - M2 is the difference between means, i.e., the absolute value of the difference between the mean values of the wet and arid sites, and the pooled standard deviation was calculated as follows:

pooled standard deviation = sqrt[(SD1^2 + SD2^2)/2]

where SD1 and SD2 are the standard deviations for the wet and dry sites, respectively.