Leaf physiological plasticity in Schima superba and Schima argentea is related to ecological niche width under varied altitude gradients

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.

Methods
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: F-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 *< .05, **p < .01, ***p < .001.

 Table 3 F-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 *< .05, **p < .01, ***p < .001.

Table 4: RDPIs of leaf morphology and physiology traits of S. superba 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 (*p < .05; **p < .01; ****p *< .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 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 (p < .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 (p < .05).