DOI: 10.5061/dryad.rr4xgxdjr
title: Leaf physiological plasticity in Schima superba and Schima argentea is related to ecological niche width under varied altitude gradients

description: Plasticity magnitude may affect the distribution and adaptability of
 species in altitude gradients. The term is broadly defined as the
 adaptability of organisms to alter their morphological and physiological
 traits in response to varying environments. Morphological and
 physiological plasticity may have different mechanisms and resource costs.
 However, our understanding of the mechanisms by which plasticity affects
 species’ adaptation to altitude changes is limited. This study focused on
 the differences in the leaf traits of Schima
 superba (narrow ecological niche) and S. argentea (wider
 ecological niche) in response to altitude gradients. It also
 explored the adaptive strategies and mechanisms behind the
 plasticity of morphological and physiological
 traits under similar environmental pressures. The interaction
 between altitude and species significantly impacted morphological traits,
 such as leaf thickness, width, and mass, and physiological traits, such as
 chlorophyll, carotenoids (Car), relative water, soluble
 sugar (SS), leaf nitrogen (LNC), and leaf
 phosphorus (LPC) contents, as well as the N/P ratio. The
 leaf traits of the two
 species responded similarly to altitude gradient
 changes, but the adaptive potential of S.
 argentea was higher. Compared with S. superba,
 the chlorophyll content of S. argentea at high
 altitude (1912 m) was remarkably greater than that at
 two lower altitudes (1375 and 1552 m). Moreover, it was affected
 by nitrogen and phosphorus limitation only when the
 altitude exceeded 1912 m. Quantitative analysis based on
 the simplified relative distance plasticity index (RDPIs) showed
 that the RDPIs of physiological traits in S. argentea
 were significantly greater than thanthoset of morphological traits, and
 the RDPIs of most physiological traits were greater than that of S.
 superba, mainly due to the RDPIs of its physiological
 traits—especially LNC (0.357), Car (0.328), and SS (0.319). Thus,
 physiological plasticity plays a critical role in adapting to
 environmental changes, especially in the case of vertical gradients.
description: All data were analyzed using SPSS 18.0 software (IBM, NY, USA).
 Before statistical analysis, the Shapiro–Wilk test was applied to assess
 data normality, and the Bartlett test was applied for homogeneity of
 variances. Tukey’s HSD test following one-way ANOVA was used to compare
 the differences in leaf morphology and physiological traits of each
 species at different altitude gradients. The final data presented are the
 means ± standard error. For morphology and physiological traits, two-way
 ANOVA was conducted for the effects of species, altitude gradients, and
 their interactions. A paired t-test was applied to examine the difference
 in RDPIs and average RDPIs of morphological and physiological traits among
 species. The Origin 2020 software (https://www.originlab.com/) was used for data visualization. Relative distances plasticity index (RDPI) was used to quantify the plasticity of individual traits for each species, with the following formula: RDPI = ∑ (dij→iʹjʹ / (xiʹjʹ + xij)) / n RDPI was computed as the Euclidean distances (d) between the trait values at different altitudes (ij and iʹjʹ, respectively). To normalize the distances, the d value was divided by the sum of the absolute trait values (xiʹjʹ+ + x+ ij), where “n” is the total number of distances. When the number of replicates, species, and environments had excessively complicated calculations, the index was simplified (RDPIs) by calculating the distances among mean phenotypic values for each species–environment combination. Table 2: <em>F</em>-values from two-way ANOVA for leaf length (LL), leaf width (LW), leaf thickness (LT), leaf area (LA), leaf mass (LM), and specific leaf area (SLA) for the effects of altitude gradient (AG), species (SP), and their interactions. Significance levels: **p *&lt; .05, **<em>p</em> &lt; .01, ***<em>p</em> &lt; .001.  Table 3 <em>F</em>-values from two-way ANOVA for chlorophyll a content (Chl a), chlorophyll b content (Chl b), total chlorophyll content (T Chl), carotenoid content (Car), relative water content (RWC), soluble sugar content (Ss), nitrogen content (LNC), phosphate content (LPC), potassium content (LKC), leaf nitrogenphosphate content (LN/P) for the effects of altitude gradient (AG), species (SP), and their interactions. Significance levels: **p *&lt; .05, **<em>p</em> &lt; .01, ***<em>p</em> &lt; .001. Table 4: RDPIs of leaf morphology and physiology traits of <em>S. superba</em> and S. argentea and the average RDPIs of leaf morphology and physiology traits of the two species. Various symbols indicate significant differences among species based on a paired T-test (*<em>p</em> &lt; .05; **<em>p</em> &lt; .01; ****p *&lt; .001). Figure 1: Map showing the study area and sampling plots. Figure 2 Altitudinal variation in leaf length (LL; a), leaf width (LW; b), leaf thickness (LT; c), leaf area (LA; d), leaf mass (LM; e), and specific leaf area (SLA; f) for <em>S. superba</em> and <em>S. argentea</em>. Data are presented as means ± SE. Different letters indicate significant differences among elevations based on ANOVA followed by Tukey’s HSD test (<em>p</em> &lt; .05). Figure 3 Altitudinal variation in chlorophyll a content (Chl a; a), chlorophyll b content (Chl b; b), total chlorophyll content (T-Chl; c), carotenoid content (Car; d), relative water content (RWC; e), soluble sugar content (SS; f), leaf nitrogen content (LNC; g), leaf phosphorus content (LPC; h), leaf potassium content (LKC; i), and nitrogen-to-phosphorus ratio (LN/P; j) for S. superba and S. argentea. Data are presented as means ± SE. Different letters indicate significant differences among elevations based on ANOVA followed by Tukey’s HSD test (<em>p</em> &lt; .05).
description: # Leaf physiological plasticity in Schima superba and Schima argentea is
 related to ecological niche width under varied altitude gradients Dataset
 DOI: [10.5061/dryad.rr4xgxdjr](10.5061/dryad.rr4xgxdjr) ## Description of
 the data and file structure ### Files and variables #### File:
 Leaf_physiological_plasticity_in_Schima_superba_and_Schima_argentea_is_related_to_ecological_niche_width_under_varied_altitude_gradients.xls **Description:**  Hunan Nanshan National Park (26°01′–26°21′N, 109°59′–110°33′E) is located at the Nanling Mountain peaks, at an intersection of the east–west and north–south mountains in China, across the evergreen broad-leaved forests of the eco-geographical regions of the hilly basin on the south bank of the Yangtze River and Wuling Mountain. The region is located in the central subtropical zone, with a subtropical and monsoon humid climate dominated by mountains. The terrain varies greatly in altitude (425–1946 m). It is successively divided into subtropical evergreen broad-leaved, evergreen mixed deciduous broad-leaved, deciduous broad-leaved, and mountain-top dwarf forest belts. The average annual temperature is 16.1°C, the annual sunshine duration is 1138 h, the frost-free period is 271 d, the relative humidity is 75%–83%, the annual rainfall is 1100–1400 mm (mostly concentrated in May–June), and the soil types is yellow-brown soil, which is classified as Podzoluvisols (according to the FAO soil classification). Preliminary surveys were performed to identify sites dominated by *S. superba* and *S. argentea.* Four sample plots (50 × 50 m) were identified at elevation intervals of approximately 200 m, located on the southern slopes of the Nanshan National Park along an elevation gradient ranging from 1375–1912 m. The elevations of the four plots were 1375, 1552, 1716, and 1912 m, respectively. *S. superba* and *S. argentea *were two plant species distributed in these plots, their heights ranged between 8.3–4.3 m and 9.5–5.2 m (Table 1). Samples were collected in July 2022. To minimize the influence of individual growth environment heterogeneity at the same altitude on the experimental results, 5 individuals were selected from each of the two populations of *S. superba* and *S. argentea* at each sampling site, and 10–20 fully expanded sun leaves were collected from each individual. The collected leaves of each individual were mixed thoroughly and evenly, then divided into marked plastic bags and placed in an incubator at 4°C for refrigeration. In total, leaves from eight populations were sampled, including four each of *S. superba* (1375–1912 m) and *S. argentea* (1375–1912 m; Fig. 1). The trees used for sampling were ensured to be healthy, disease–free, and devoid of physical injury. From each individual, 3 leaf samples were randomly selected for the measurement of morphological traits (3 samples × 5 individuals × 4 altitude gradients × 2 species = 120 samples in total). The Yaxin-1241 leaf area meter (Beijing Yaxinliyi Science and Technology Co. Ltd., Beijing, China) was used to measure leaf length (LL), leaf width (LW), and leaf area (LA). An electronic digital vernier caliper (accuracy: .01 mm) was used to measure the leaf thickness (LT) while avoiding the main vein. The leaves were weighed using an electronic balance (accuracy .001 g) to obtain fresh mass. Then, each leaf was placed in an envelope bag and incubated in a 105°C oven for 30 min. After drying at 70°C to a constant weight was achieved, the leaf mass (LM) was determined. Finally, the specific leaf area (SLA) was calculated as the leaf area/leaf mass. From each individual, 3 leaf samples were randomly selected for the measurement of physiological traits (3 samples × 5 individuals × 4 altitude gradients × 2 species = 120 samples in total). The relative water content (RWC) was determined using the conductance method. Sampled leaves were weighed as fresh weight (W1), subsequently soaked in distilled water for 24 h in the dark to measure the saturated weight (W2), oven-dried at 105℃ for 15 min, and then dried to a constant weight (W3) at 80℃. The RWC was calculated by applying the following formula: RWC = (W1 − W3)/(W2 − W3). To determine chlorophyll a (Chl a), chlorophyll b (Chl b), total chlorophyll (T Chl), and carotenoids (Car) contents, 10 mL of ice-cold 80% (v/v) acetone was used to extract these pigments from 0.05 g of fresh leaves. After mixing overnight and centrifuging for 10 min at 12,000 rpm, the supernatant was collected, and its absorbance was measured at 663, 646, and 470 nm. The Chl and Car concentrations were calculated using the equations described by Lichtenthaler. Soluble sugar content (Ss) was determined using anthrone colorimetry. About 0.5 g of fresh leaves were ground in liquid N2. The solution was taken in a test tube, added with 5 mL of distilled water, and the SS was extracted by placing it in boiling water for 30 min. After the solution cooled down to 25℃, it was centrifuged at 5000 rpm for 5 min. The supernatant was poured into a 25 mL volumetric flask, and the extraction was repeated twice with constant volume. About 0.5 mL of the extract was taken in a hard test tube, and added with ~1.5 mL of distilled water, 0.5 mL of anthrone–ethyl acetate reagent, and 5 mL of concentrated sulfuric acid in an ice bath. After mixing, the solution was quickly heated in boiling water for 1 min, and the OD630 was measured. The plant samples were dried for 72 h at 60℃ and ground using an MM 400 ball mill (Retsch, Haan, Germany). A Z-2300 NaOH melting-flame atomic absorption spectrophotometer (Hitachi Company, Japan) was used to determine the leaf potassium content (LKC). Leaf nitrogen content (LNC) was determined using the Kjeldahl method, and leaf phosphorus content (LPC) employing the Mo-Sb colorimetry (Gao & Zhang, 2023). Finally, we calculated the N:P ratios (LN/P) to assess the N and P limitations of the plant. ##### Variables * leaf length (LL),  * leaf width (LW), * leaf thickness (LT),  * leaf area (LA),  * leaf mass (LM),  * specific leaf area (SLA),  * chlorophyll a content (Chl a),  * chlorophyll b content (Chl b),  * total chlorophyll content (T Chl), * carotenoid content (Car), * relative water content (RWC), * soluble sugar content (Ss), * leaf nitrogen content (LNC), * leaf phosphate content (LPC), * leaf potassium content (LKC), * and leaf nitrogen/phosphate content (LN/P) ## Access information Other publicly accessible locations of the data: * NA Data was derived from the following sources: * NA