Intraspecific Variability of Xylem Hydraulic Traits of Calligonum mongolicum Growing in the Desert of Northern Xinjiang, China

Abstract

Plant hydraulic traits are essential for understanding and predicting plant drought resistance. Investigations into the mechanisms of the xylem anatomical traits of desert shrubs in response to climate can help us to understand plant survival strategies in extreme environments. This study examined the xylem anatomical traits and related functional traits of the branches of seven Calligonum mongolicum populations along a precipitation gradient, to explore their adaptive responses to climatic factors. We found that (1) the vessel diameter (D), vessel diameter contributing to 95% of hydraulic conductivity (D₉₅), hydraulic weighted vessel diameter (Dh), vessel density (VD), percentage of conductive area (CA), thickness-to-span ratio of vessels ((t/b)²), and theoretical hydraulic conductivity (K_th) varied significantly across sites, while the vessel group index (V_g), wood density (WD), and vulnerability index (VI) showed no significant differences. (2) Principal component analysis revealed that efficiency-related traits (K_th, D_h, D₉₅) and safety-related traits (VI, VD, inter-wall thickness of the vessel (t)) were the primary factors driving trait variation. (3) Precipitation during the wettest month (PWM) had the strongest influence, positively correlating with (t/b)² and negatively with D, D₉₅, D_h, CA, and K_th. (4) Structural equation modeling confirmed PWM as the main driver of K_th, with indirect effects through CA. These findings indicate that C. mongolicum displays high plasticity in xylem traits, enabling adaptation to changing environments, and providing insight into the hydraulic strategies of desert shrubs under climate change.

Keywords: desert shrub; ecological adaptation strategy; environmental gradient; intraspecific variability; xylem anatomical traits.

Figure 1

Sampling maps and measurements of the C. mongolicum. Notes: (A) Different sample sites (triangular sites) with different colors are sorted from low to high by MAP and marked A–G. The inset map displays the location, shape, and size of the sampling plots. (B) Shows the habitat and general morphology of the sampled individuals. Yellow rectangles indicate the specific sections where sampling occurred on the plant stems. (C) A close-up view of the collected branch samples. (D) Xylem cross-section images of C. mongolicum. The yellow sector is the measurement area. Yellow rectangle, a group of vessels.

Figure 2

Quartile coefficient of dispersion of the stem xylem hydraulic traits of C. mongolicum.

Figure 3

Analysis of differences in stem xylem hydraulic traits of C. mongolicum among sample sites. Notes: (A) Mean vessel diameter; (B) hydraulic weighted vessel diameter; (C) vessel diameter contributing 95% hydraulic conductivity; (D) vessel density; (E) percentage of conductive area; (F) vessel grouping index; (G) inter-wall thickness of the vessel; (H) thickness-to-span ratio of vessels; (I) wood density; (J) theoretical hydraulic conductivity; (K) Carlquist’s vulnerability index. Error bars are standard errors. Different letters indicate significant differences at p < 0.05. Different sample sites with different colors are sorted from small to large by MAP and marked A–G. * p < 0.05, ** p <  0.01, *** p < 0.001.

Figure 4

Correlations between the stem xylem hydraulic traits. Notes: Pearson’s correlation analysis (A) and general linear regression analysis (B–G) of hydraulic functional traits and anatomical traits of C. mongolicum. (A) The triangular section in the upper left corner depicts the relationship between the traits, where the color gradient indicates Pearson’s correlation coefficient. The solid line and dashed lines represent positive and negative correlations, respectively. The line color indicates statistical significance; red is an extremely significant correlation, dark red is a significant correlation, and gray is a non-significant correlation. (B–G) The points with different colors in the linear regression analysis represent different sample sites. The blue lines represent the fitted curves or relationship lines obtained through general linear regression analysis, which are statistically significant (p < 0.05), while shaded areas represent the 95% confidence interval. The asterisk indicates significant correlations. * p <  0.05; ** p <  0.01.

Figure 5

PCA of stem xylem hydraulic traits of C. mongolicum. Notes: (A) Principal component analysis of stem xylem hydraulic traits of C. mongolicum; (B) the contribution of each trait to PC1; (C) the contribution of each trait to PC2. The points of different colors represent the different sample sites.

Figure 6

Relationships between stem xylem hydraulic traits and climatic factors. Notes: The heatmap displays a significant correlation (calculated by Pearson’s correlation analysis). The color of the circle indicates a positive correlation (red) or negative correlation (blue), while color intensity signifies the strength of the correlation. * p < 0.05; ** p < 0.01.

Figure 7

Driving factors of stem xylem hydraulic traits of C. mongolicum. Notes: (A,C) Structural equation modeling illustrating the impact of climatic factors on K_th and VI. (B,D) The histogram depicts the standardized impacts of driving factors. The red and blue arrows represent statistically significant positive and negative effects (p  <  0.05), while the gray arrows indicate a non-significant relationship. The numerical value next to the arrow represents the standardized path coefficient. The width of the arrow is directly proportional to the strength of the path coefficient. R² donates the proportion of variance that is accounted for by the model. Significant levels of each predictor are * p  <  0.05; ** p < 0.01; *** p < 0.001.