Intra-annual stem radial growth of four plantation species with different water use strategies and life types on the Loess Plateau, China

doi:10.1007/s40333-025-0109-4

Journal of Arid Land

2025, Vol. 17

Issue (9): 1252-1269 DOI: 10.1007/s40333-025-0109-4 CSTR: 32276.14.JAL.02501094

Research article

Intra-annual stem radial growth of four plantation species with different water use strategies and life types on the Loess Plateau, China

YANG Xindong¹^,², XIANG Yuxiao¹^,², Muhammad Saddique AFZAL¹^,², ZHAO Zhiguang²^,³, ZHAO Changming¹^,²^,^*(

)

¹State Key Laboratory of Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou 730000, China
²Yuzhong Mountain Ecosystems Observation and Research Station, Lanzhou University, Lanzhou 730000, China
³Gansu Key Laboratory of Biomonitoring and Bioremediation for Environmental Pollution, Lanzhou University, Lanzhou 730000, China

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Abstract

Tree growth is extremely vulnerable to climate change, especially in semi-arid areas. Although the response of stem radial growth (SRG) to climate change has been extensively studied, the intra-annual regulatory mechanisms of SRG in trees with different water use strategies and life types remain poorly understood. This study calculated the SRG of four native species in the semi-arid area of the Loess Plateau, China, including two isohydric species (Pinus tabuliformis Carrière and Populus × hopeiensis Hu & Chow) and two anisohydric species (Prunus sibirica L. and Platycladus orientalis (L.) Franco). The results revealed that the intra-annual SRG of all the four tree species exhibited a single peak, and greater SRG was found in anisohydric species. Principal component analysis and structural equation model revealed that atmospheric water, particularly relative humidity, was the main factor affecting the SRG of coniferous species (P. tabuliformis and P. orientalis), whereas the SRG was mainly affected by soil water content in broadleaf species (P. sibirica and P. × hopeiensis). These findings suggested that water use strategies and life types play important roles in SRG and environmental response of trees in semi-arid area. Considering the high climate sensitivity of wood formation in trees, our results highlight the importance of water use strategies and life types of trees in SRG prediction in the context of future climate change in arid and semi-arid areas.

Key words： semi-arid area plantations water use strategy stem radial growth tree water deficit environmental factor

Received: 15 May 2025 Published: 30 September 2025

Corresponding Authors: ^*ZHAO Changming (E-mail: zhaochm@lzu.edu.cn)

About author: The first and second authors contributed equally to this work.

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	YANG Xindong
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Cite this article:

YANG Xindong, XIANG Yuxiao, Muhammad Saddique AFZAL, ZHAO Zhiguang, ZHAO Changming. Intra-annual stem radial growth of four plantation species with different water use strategies and life types on the Loess Plateau, China. Journal of Arid Land, 2025, 17(9): 1252-1269.

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http://jal.xjegi.com/10.1007/s40333-025-0109-4 OR http://jal.xjegi.com/Y2025/V17/I9/1252

Table 1 Basic information of the sample plots and trees used for stem radial growth (SRG) monitoring

Fig. 1 Landscape of P. tabuliformis (a), P. sibirica (b), P. orientalis (c), and P. × hopeiensis (d). P. tabuliformis, Pinus tabuliformis Carrière; P. sibirica, Prunus sibirica L.; P. orientalis, Platycladus orientalis (L.) Franco; P. × hopeiensis, Populus × hopeiensis Hu & Chow.

Fig. 2 Variation in environmental factors in the sample plots on the Loess Plateau from 2022 to 2023. (a), mean (T_a), maximum (T_max), and minimum (T_min) air temperature; (b), photosynthetically active radiation (PAR) and net radiation (RA); (c), relative humidity (RH); (d), vapor pressure deficit (VPD); (e), soil water content (SWC) and precipitation (P); (f), soil temperature (ST).

Fig. 3 Gompertz growth function fitting for the daily cumulative stem radial growth (SRG) and daily SRG rate of the four plantation species during the growing season in 2022 (a and b) and 2023 (c and d). DOY, day of year.

Table 2 SRG data of the four plantation species on the Loess Plateau in 2022 and 2023

Fig. 4 Daily relative SRG and tree water deficit (TWD) of the four plantation species during the growth season in 2022 (a and b) and 2023 (c and d)

Fig. 5 Principal component analysis (PCA) of the daily SRG of the four plantation species in response to environmental factors. (a), P. tabuliformis; (b), P. sibirica; (c), P. orientalis; (d), P. × hopeiensis. PC, principal component.

Fig. 6 Scatter plot of PCA results for the daily SRG of the four plantation species in response to environmental factors. (a), P. tabuliformis; (b), P. orientalis; (c), P. sibirica; (d), P. × hopeiensis.

Fig. 7 Ranking of importance between daily SRG and environmental factors for the four plantation species. (a), P. tabuliformis; (b), P. sibirica; (c), P. orientalis; (d), P. × hopeiensis. Feature values refer collectively to the input data of meteorological and soil factors in the model. A positive SHAP value indicates that the feature value contributes positively to the model's prediction, while a negative value suggests a negative contribution.

Fig. 8 Correlation between daily TWD and environmental factors for the four plantation species. The positive correlation coefficient represents a positive association between daily TWD and environmental factor, while the negative coefficient represents a negative association. ^*, significance at P<0.050 level; ^**, significance at P<0.010 level; ^***, significance at P<0.001 level.

Fig. 9 Environmental factors driving the SRG of the four plantation species based on structural equation model (SEM) analysis. (a), P. tabuliformis; (b), P. sibirica; (c), P. orientalis; (d), P. × hopeiensis. The values above the lines indicate path coefficients (λ), of which positive values represent positive effect; negative values represent negative effect. The yellow lines indicate positive paths, and the blue lines indicate negative paths. The solid lines represent significant paths, whereas the dashed lines represent insignificant paths. A solid arrow between two variables indicates a significant direct effect, whereas a significant indirect effect is inferred when variables are connected through one or more mediating variables via two or more solid arrows without a direct solid arrow between them. The P-value indicates the overall model fit and the model is accepted as having good fit to the data when P>0.050. RMSEA, root mean square error of approximation; CFI, comparative fit index; AIC, Akaike information criterion; ns, non-significance; ^*, significance at P<0.050 level; ^**, significance at P<0.010 level; ^***, significance at P<0.001 level.


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