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Journal of Arid Land
Journal of Arid Land  2025, Vol. 17 Issue (12): 1741-1760    DOI: 10.1007/s40333-025-0034-6     CSTR: 32276.14.JAL.02500346
Research article     
Spatiotemporal niche separation mechanisms of water utilization strategies in the desert steppe plant communities, northern China
SONG Kechen1, HU Haiying1,*(), ZHANG Hao1, GUAN Siyu1, DENG Wenhui1, YONG Jiayi1, ZHAO Xiaona1, WANG Xing2
1College of Forestry and Prataculture, Ningxia University, Yinchuan 750021, China
2Chengdu Institute of Biology, Chinese Academy of Science, Chengdu 610041, China
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Abstract  

Amid global precipitation changes, it remains unclear whether hydrological niche separation (HNS) mechanisms apply to herbaceous plant communities in desert steppes are severely affected by seasonal drought. How these plants access limited water and tolerate drought to coexist also remains unverified. In this study, we employed stable isotope techniques to examine water acquisition and drought adaptation in coexisting species of the desert steppe in northern China under five precipitation treatments, i.e., decreased 50%, decreased 30%, ambient, increased 30%, and increased 50% precipitation. The following results showed that: (1) water sources of coexisting species shifted with changes in precipitation amount and timing, i.e., all coexisting plants exhibited preferential utilization of surface soil moisture. When surface soil moisture was scarce, they shifted to deeper water sources, and when deep water sources remained scarce, they were forced to compete more intensely for surface water sources; (2) community's HNS was affected by precipitation amount but not by timing, i.e., with adequate soil moisture, plant water source ranges expanded, reducing overlap and enhancing HNS, whereas under extreme drought, the range contracted and increased the overlap, although HNS remained stable; and (3) water acquisition strategies of coexisting species differed along hydrological niche axis defined by water stress adaptability (i.e., stable carbon isotope composition and proline content). Convolvulus ammannii Desr. had the strongest drought adaptation, although its strategy showed a weak correlation with water uptake. Stipa breviflora Griseb., with moderate drought resistance, adopted a water-conserving strategy that was suitable for extreme drought. Leymus secalinus (Georgi) Tzvelev, Polygala tenuifolia Willd., and Larix potaninii Batalin showed resource-dependent and flexible water strategies, thriving in wetter soils but struggling under extreme drought. Our findings indicated that herbaceous species in desert steppes adapted their water uptake and drought tolerance strategies according to changes in precipitation amount and timing. As a core regulatory mechanism, HNS (under increasing precipitation variability due to climate change) not only supports species coexistence by reducing interspecific competition, but also promotes efficient soil moisture use. This mechanism enhances community drought resistance and contributes to ecosystem stability. Overall, this study provides key ecological evidence for understanding plant community adaptation in arid and semi-arid areas facing the influence of global climate change.

Key words： hydrological niche separation      coexisting herbaceous plant      water source      drought adaptation      desert steppe     
Received: 23 April 2025      Published: 31 December 2025
Corresponding Authors: *HU Haiying (E-mail: haiying@nxu.edu.cn)
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SONG Kechen
HU Haiying
ZHANG Hao
GUAN Siyu
DENG Wenhui
YONG Jiayi
ZHAO Xiaona
WANG Xing
Cite this article:

SONG Kechen, HU Haiying, ZHANG Hao, GUAN Siyu, DENG Wenhui, YONG Jiayi, ZHAO Xiaona, WANG Xing. Spatiotemporal niche separation mechanisms of water utilization strategies in the desert steppe plant communities, northern China. Journal of Arid Land, 2025, 17(12): 1741-1760.

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http://jal.xjegi.com/10.1007/s40333-025-0034-6     OR     http://jal.xjegi.com/Y2025/V17/I12/1741

Fig. 1 Schematic layout of experimental design (a) and field photographs (b and c) of the study area. Five precipitation treatments were applied, i.e., decreased 50% (P-50%), decreased 30% (P-30%), ambient (control; PCK), increased 30% (P+30%), and increased 50% (P+50%) precipitation. The numbers of 1-, 2-, and 3- of each treatment are three replicates.
Fig. 2 Daily cumulative precipitation during growing season in 2023 and rainwater isotope value. Major precipitation events (>30 mm) are marked with blue circles, occurring on 29 May, 25 August, 16 September, and 19 September. The red dashed line means the three precipitation periods.
Species Root type Importance value
P+50% P+30% PCK P-30% P-50%
Stipa breviflora Griseb. Fibrous root type 0.91 0.90 0.93 1.15 1.03
Larix potaninii Batalin Axial root type 0.38 0.39 0.29 0.17 0.10
Convolvulus ammannii Desr. Axial root type 0.20 0.22 0.27 0.31 0.30
Leymus secalinus (Georgi) Tzvelev Creeping root type 0.60 0.25 0.20 0.25 0.01
Polygala tenuifolia Willd Taproot type 0.13 0.12 0.11 0.15 0.12
Table S1 Root types and importance values of five coexisting plant species
Fig. 3 Fitted regression lines of hydrogen (δD) and oxygen isotopes (δ18O) in soil water under different precipitation amount treatments. SWL+50%, SWL+30%, SWLCK, SWL-30%, and SWL-50% represent the regression lines for δD and δ18O under P+50%, P+30%, PCK, P-30%, and P-50% treatments, respectively. GMWL, global meteoric water line (Craig, 1961); LMWL, local meteoric water line; NMWL, Northwest China arid zone meteoric water line (Chen, 2021).
Factor and interaction Soil moisture content δD δ18O
P F P F P F
Precipitation (P) *** 15.552 *** 8.504 ns 0.861
Depth (D) *** 74.125 *** 130.411 *** 371.269
Period (Pe) *** 28.425 ns 0.530 *** 21.412
P×Pe ns 1.702 ns 1.154 ns 0.358
P×D ns 0.664 ns 0.440 ns 0.793
Pe×D ns 2.077 ns 0.881 ns 1.323
P×D×Pe ns 1.181 ns 0.121 ns 0.134
Table 1 Regression analysis for the relationships of precipitation amount, precipitation period, and soil depth with soil water content, δD, and δ18O
Fig. 4 Effects of precipitation changes on soil water properties at different soil depths. (a), soil water content; (b), δD in soil water; (c), δ18O in soil water. EP, MP, and LP represent late spring, mid-summer, and late summer precipitation periods, respectively. Bars are standard deviations.
Fig. 5 Variations in δD (a) and δ18O (b) of root and stem water under different precipitation amount, precipitation period, and plant species treatments. S. breviflora, Stipa breviflora Griseb.; C. ammannii, Convolvulus ammannii Desr.; L. secalinus, Leymus secalinus (Georgi) Tzvelev; L. potaninii, Larix potaninii Batalin; P. tenuifolia, Polygala tenuifolia Willd. Bars are standard deviations.
Factor and interaction δD δ18O
P F P F
Precipitation (P) *** 14.177 ** 4.766
Species (S) *** 6.965 *** 20.531
Period (Pe) *** 83.588 *** 22.574
P×Pe *** 8.497 *** 49.575
P×S ns 0.923 *** 5.866
Pe×S ** 4.807 *** 13.995
P×S×Pe ns 0.915 ** 2.384
Table 2 Regression analysis for the relationships of precipitation amount, precipitation period, and plant species with δD and δ18O in root and stem water
Factor and interaction 0-5 cm 5-10 cm 10-20 cm 20-40 cm 40-60 cm
P F P F P F P F P F
Precipitation (P) *** 1.523 ns 1.192 ns 0.798 ns 6.807 *** 1.956
Species (S) *** 0.249 ns 0.478 ns 0.118 ns 0.871 ns 1.426
Period (Pe) ns 0.199 ns 0.964 ns 0.126 ns 2.253 ns 9.414
P×Pe ns 2.089 ns 4.467 ** 0.528 ns 9.339 *** 7.515
P×S *** 0.047 ns 0.172 ns 0.042 ns 0.451 ns 0.107
Pe×S * 0.151 ns 0.081 ns 0.074 ns 0.934 ns 0.835
P×S×Pe ** 0.077 ns 0.304 ns 0.063 ns 0.651 ns 0.322
Table 3 Regression analysis for the relationships of precipitation amount, precipitation period, and plant species with relative contributions of δD and δ18O in different soil depths
Fig. 6 Relative contributions of δD and δ18O in root and stem water under different precipitation amount, precipitation period, plant species, and soil depth treatments. (a), S. breviflora; (b), C. ammannii; (c), L. potaninii; (d), L. secalinus; (e), P. tenuifolia. Bars are standard deviations.
Fig. 7 Effects of precipitation changes on leaf δ13C (a1-a5) and free proline content (b1-b5) of different plant species. Different lowercase letters within the same period indicate significant differences among different precipitation treatments at P<0.050 level. Different uppercase letters within the same precipitation treatment indicate significant differences among different periods at P<0.050 level. Bars are standard deviations.
Factor and interaction δ13C Proline
P F P F
Precipitation (P) ns 179.043 *** 139.844
Species (S) ns 72.867 *** 196.794
period (Pe) ** 4.944 * 0.001
P×Pe *** 3.132 * 0.418
P×S ns 10.393 *** 7.189
Pe×S ns 17.548 *** 2.572
P×De×Pe ns 4.241 *** 2.441
Table 4 Regression analysis for the relationships of precipitation amount, precipitation period, and species with leaf δ13C and proline content
Fig. 8 Community-level overlap in water extraction depth under different precipitation amount (a) and period (b) treatments
Fig. 9 Species-level overlap in water uptake depth under different precipitation period (a1-a5, b1-b5, and c1-c5) and amount (d1-d5, e1-e5, f1-f5, g1-g5, and h1-h5) treatments
Fig. 10 Canonical discriminant analysis (CDA) of water uptake depth and drought adaptation traits in coexisting species. D5 cm, D10 cm, D20 cm, D40 cm, and D60 cm are water source contributions from soil depths of the 0-5, 5-10, 10-20, 20-40, and 40-60 cm, respectively.
Species Can1 Can2
C. ammannii 3.04 0.40
L. potaninii -1.70 1.06
L. secalinus -0.21 -0.95
P. tenuifolia -0.48 0.40
S. breviflora -0.65 -0.91
Table S2 Class means of canonical discriminant analysis
Index Can1 Can2
Proline -1.01 -0.04
13C 0.09 -0.96
D5 cm -0.84 -4.27
D10 cm -0.52 -2.77
D20 cm -0.28 -1.75
D40 cm 0.03 -1.20
D60 cm -0.33 -1.57
Table S3 Standard coefficients of canonical discriminant analysis
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