Rainfall partitioning by vegetation affects water balance and utilization by plants. Caragana microphylla, Hedysarum fruticosum, and Salix gordejevii are three typical, morphologically different sand-fixing shrubs in Horqin Sand Land. However, few studies have compared rainfall partitioning by these shrubs. We examined rainfall partitioning differences among these shrubs in Horqin Sand Land, north-eastern China. On average, throughfall, stemflow (SF), and interception for C. microphylla accounted for 64.2, 11.0, and 24.8% of the individual incident rainfall, respectively; for H. fruticosum, they accounted for 71.2, 6.3, and 22.5%; and for S. gordejevii, they accounted for 75.3, 5.3, and 19.4%. The average funneling ratio for H. fruticosum (162.7 ± 33.2) was larger than that for C. microphylla (100.1 ± 16.9) and S. gordejevii (106.2 ± 23.1). Rainfall partitioning was significantly correlated with canopy area, branch number, and stem basal area for C. microphylla and S. gordejevii. SF volumes of 3,167, 676, and 2,210 L were estimated to have channeled into the plots for C. microphylla, H. fruticosum and S. gordejevii, respectively, indicating that C. microphylla is more effective in channeling SF to the root zone. These results suggest that C. microphylla may be more advantageous for sand-fixing and vegetation restoration in sand lands.

INTRODUCTION

The response of terrestrial ecosystems to global change is of current scientific interest (Vitousek 1994; Weltzin et al. 2003). Global climate changes are likely to alter patterns of global air circulation and hydrologic cycling, resulting in changes in precipitation regimes (Volder et al. 2013).

Vegetation modifies precipitation intensity and distribution via three pathways: throughfall (TF) (precipitation passing directly through or dripping from the canopy to the soil surface), stemflow (SF) (rainfall that reaches the base area of a plant by flowing down the branches and stems), and interception (precipitation that is captured by the canopy and subsequently returned to the atmosphere through evaporation) (Marin et al. 2000; Swaffer et al. 2014; Schumacher & Christiansen 2015). An understanding of rainfall partitioning by the vegetation is helpful for explaining the pattern of soil moisture (Liang et al. 2011; Wang et al. 2011), soil solution chemistry (Zhang et al. 2013; Shiklomanov & Levia 2014), groundwater recharge (Buttle et al. 2014), runoff generation and soil erosion (Cattan et al. 2009; Perez-Suarez et al. 2014), and spatial distribution of understory vegetation (Barbier et al. 2009).

Rainfall partitioning is influenced by plant characteristics such as canopy area and volume, plant height, branch number and angle, and stem basal area (Llorens & Domingo 2007; Frost & Levia 2014; Zimmermann & Zimmermann 2014) as well as by rainfall characteristics such as the amount, intensity, and duration of rainfall (Huber & Iroume 2001; Carlyle-Moses 2004; Muzylo et al. 2012). The regulation of TF and SF by vegetation is closely associated with the strategies of drought resistance employed by plants (Martinez-Meza & Whitford 1996; Levia & Frost 2003; Siegert & Levia 2014). Studies of rainfall partitioning have been conducted for plants growing in arid zones (Crockford & Richardson 2000; Perez-Suarez et al. 2014; Sadeghi et al. 2015) to elucidate adaptations to water-limited environments and to guide restoration.

Regarding rainfall partitioning by sand-binding shrubs, the following questions remain to be answered: (1) how much water is available after a rainfall event, and how does this differ between species and regions; (2) how do different shrub species use available rain water, i.e. how much rainfall water is utilized as SF and TF by different species; and (3) what are the rainfall use efficiency and water use strategies of different shrub species with reference to rainfall availability, SF, and TF. Since rainfall partitioning is mainly influenced by a plant's morphological characteristics (Mauchamp & Janeau 1993; Germer et al. 2010), it is essential to select shrub species with distinct canopy architecture to investigate it. Presumably, canopy size and shape, branch angle, branch number, stem roughness, and stem thickness are some of the canopy characteristics that control rainfall partitioning.

Horqin Sand Land is a typical semiarid sand region located in southeastern Inner Mongolia in north-eastern China. Due to environmental changes and human activities, this region has suffered severe land degradation. In recent decades, some sand-binding shrubs have been introduced to stabilize the shifting sand (Zhao et al. 2007). Among these species, Caragana microphylla, Hedysarum fruticosum and Salix gordejevii are the most important ones. In recent years, the vegetation used for stabilizing the dunes has deteriorated, which may have been caused by water deficit (Wang et al. 2005). Until now, few studies on rainfall redistribution characteristics of the shrubs in this region, each with distinct morphology, have been conducted.

In this study, we selected three shrub species with distinct morphological characteristics, i.e. C. microphylla (umbrella-shaped canopy, multiple smooth stems, and numerous ovate leaves), H. fruticosum (rough stems and thin leaves) and S. gordejevii (loosely branched, slender stems, and leptophyllous leaves) to investigate rainfall partitioning and SF funneling. Our objectives were (1) to determine how much rainwater is available to the different species, (2) to determine how much available rainwater is utilized as SF and TF by the different species, and (3) to elucidate the rainfall use efficiency and water use strategies of the different shrub species.

MATERIALS AND METHODS

Study site

The study site was located in the Songshushan Nature Reserve (43°3′36″ N, 119°14′6″ W) of Horqin Sand Land, Inner Mongolia Autonomous Region, north-eastern China. It has a temperate semi-arid climate, i.e. dry and windy in winter and spring, warm and rainy in summer, and cool in autumn. Mean annual temperature is 6.2 °C with the coldest and the hottest mean monthly temperatures of −14.0 °C in January and 40.5 °C in July, respectively. Mean annual precipitation is 351 mm, of which 69% is concentrated in June and July. The annual potential evaporation is 2,352 mm. The dominant winds blow in a north-westerly direction from March to May and in a south-westerly direction from June to September. Average wind speed is 2.9 m/s; mean annual vapor pressure is 6.6 kpa; and mean annual relative humidity is 47%.

The study area is a semiarid region surrounded by fixed, semi-fixed, and active sand dunes, with the vegetation consisting of shrubs such as C. microphylla, S. gordejevii, and H. fruticosum and herbs such as Pennisetum centrasiaticum, Corispermum macrocarpum, and Setaria viridis (Zhao et al. 2007).

Experimental design

Target species

Three typical sand-fixing shrubs with distinct morphological characteristics were used in this study: C. microphylla, a multiple-stemmed, smooth-stemmed shrub (1–2 m tall) with numerous ovate leaves that forms an umbrella-shaped canopy; S. gordejevii, a loosely branched shrub (1.5–2 m tall) with slender stems and leptophyllous leaves; and H. fruticosum, a leguminous shrub (0.5–1.5 m tall) with rough stems and thin leaves. Considering these different characteristics, each shrub species represents different canopy types: C. microphylla represents a dense-branch-type shrub; S. gordejevii represents a loose-stem-type shrub; and H. fruticosum represents a thin-leaf-type shrub.

Caragana microphylla is highly effective in stabilizing the shifting sand in north-eastern China (Zhang et al. 2006). S. gordejevii, widely distributed in the semiarid area of northern China, can survive in the shifting sand dunes as a pioneer species (Yuan et al. 2005). H. fruticosum is widely distributed as a sand-fixing species in arid and semi-arid sandy regions of Inner Mongolia. There have been many studies concentrated on rainfall use efficiency and water use strategies of these shrub species by investigating plant transpiration, photosynthesis, and water transportation (Liu et al. 2003; Ma et al. 2004), however, comparisons of rainfall partitioning by these shrub species with regard to the morphological characteristics are not well understood.

Nine 10 × 10 m plots were selected to monitor TF and SF. Three shrubs of each species were selected in each plot for a total of 27 shrubs selected for monitoring. All gross rainfall, TF, and SF measurements were taken during the growing season from May to September of 2014.

Rainfall

Gross rainfall data were collected from 25 rainfall events. Gross rainfall data were obtained at the Songshushan Experiment Station, approximately 0.5 km east of the study plots. Gross rainfall was measured in an open area without obstructions using a standard rain gauge (diameter = 20 cm) and was observed immediately after a rainfall event or before sunrise if the rainfall occurred overnight (Carlyle-Moses 2004).

Throughfall

TF was collected during 16 rainfall events with cylindrical polyethylene gauges similar to the standard rain gauges (diameter = 20 cm). The gauges were arranged under the canopy of each shrub in four directions (0, 90, 180 and 270 °). Corresponding to the differences in canopy area among species (Table 1), a varying number of gauges were installed from shrub base to crown periphery at each direction for each species. Four gauges were used in each of the four directions for C. microphylla and S. gordejevii, and three gauges for each direction were used for H. fruticosum. Thus, 16 TF collectors were used for each C. microphylla and S. gordejevii shrub and 12 for each H. fruticosum shrub. TF was measured immediately after the rainfall ended or in the morning the next day in case the rainfall event occurred overnight. TF was calculated as the following: , where TF is throughfall amount (mm), TV is throughfall volume (L) for each gauge, n is the number of throughfall gauges under each shrub canopy, and GA is the gauge projection area (m2).

Table 1

Characteristics of the canopy morphology for C. microphylla, H. fruticosum and S. gordejevii in the study area

 Average value
 
Variables C. microphylla H. fruticosum S. gordejevii 
Canopy area (m24.01 ( ± 1.67) 2.66 ( ± 1.27) 4.15 ( ± 1.97) 
Number of branches 31 ( ± 7)ab 19 ( ± 8)b 36 ( ± 20)a 
Stem basal diameter (cm) 1.39 ( ± 0.28)a 0.89 ( ± 0.13)b 0.93 ( ± 0.09)b 
Branch angle (°) 52.8 ( ± 9.8) 58.2 ( ± 11.5) 56.3 ( ± 13.6) 
Stem basal area (cm241.94 ( ± 15.61)a 10.35 ( ± 6.11)b 21.34 ( ± 12.35)b 
Shrub height (m) 1.56 ( ± 0.37)ab 1.39 ( ± 0.15)b 1.62 ( ± 0.24)a 
Canopy volume (m32.39 ( ± 1.47) 1.42 ( ± 0.84) 2.04 ( ± 1.06) 
 Average value
 
Variables C. microphylla H. fruticosum S. gordejevii 
Canopy area (m24.01 ( ± 1.67) 2.66 ( ± 1.27) 4.15 ( ± 1.97) 
Number of branches 31 ( ± 7)ab 19 ( ± 8)b 36 ( ± 20)a 
Stem basal diameter (cm) 1.39 ( ± 0.28)a 0.89 ( ± 0.13)b 0.93 ( ± 0.09)b 
Branch angle (°) 52.8 ( ± 9.8) 58.2 ( ± 11.5) 56.3 ( ± 13.6) 
Stem basal area (cm241.94 ( ± 15.61)a 10.35 ( ± 6.11)b 21.34 ( ± 12.35)b 
Shrub height (m) 1.56 ( ± 0.37)ab 1.39 ( ± 0.15)b 1.62 ( ± 0.24)a 
Canopy volume (m32.39 ( ± 1.47) 1.42 ( ± 0.84) 2.04 ( ± 1.06) 

Mean ± standard deviation are reported.

Different letters in rows indicate significant differences among three shrub species at P ≤ 0.05.

Stemflow

SF was measured during 16 rainfall events by self-made collectors (Figure 1). Different stem diameter classes were chosen to collect the SF. Aluminum foil tape (approximately 6 cm wide) was wrapped around a branch to form a funnel-form groove at the upper portion, using adhesive to glue the branch and the aluminum foil tape at the antapical half. A flexible plastic tube was used to connect the groove and a plastic bottle. Silicon was used to seal the gap of the conjoining line and the bottom of the aluminum foil tape to prevent water leakage. Rainfall running down the stem and flowing into the groove was ultimately collected in the plastic bottle through the flexible plastic tube. The SF volume was measured with a measuring cylinder immediately after each rainfall event or at sunrise if the rainfall event occurred overnight. SF was calculated by using the following formula: , where n is the total number of stems on the shrub, SVi is the stemflow volume (L) of stem diameter class i, Mi is the number of stems in diameter class i, and SA is the projected area of shrub canopy (m2). The stemflow funneling ratio (F) was calculated with the following formula:, where SFv is the stemflow volume (L), BA is the stem basal area (m2), and P is the amount of rainfall (mm). Plot SF was estimated using the volume of SF collected by each of the measured stems and then relating the basal area of these stems to the total plot basal area, following the upscaling method described by Swaffer et al. (2014).

Figure 1

Photograph of the method to collect the SF.

Figure 1

Photograph of the method to collect the SF.

Interception

Although canopy interception cannot be measured directly, the value of this partitioning part was calculated by subtracting the sum of TF and SF from gross rainfall.

Canopy characteristics

Canopy variables measured on each shrub included: shrub height, canopy area and volume, branch number and angle, stem basal area, and stem basal diameter (Table 1). Canopy area was calculated by taking the east-west and north-south diameters through the center of the fullest part of the canopy. Canopy volume was calculated by using the volume formula of an inverted cone. All branches on each shrub base were counted to determine the branch number. Canopy angle was measured using an angle protractor. Stem basal diameter was measured using a Vernier caliper and used to calculate stem basal area.

Statistical analysis

Statistical analyses and model development were completed using Systat SigmaPlot v12.0 Systat Software Inc. and SPSS Statistics v17.0 SPSS Inc. All model parameters were chosen based on goodness of fit and residual analyses. Levels of significance, including the standard errors associated with model parameters, were given at the 95% confidence interval (p < 0.05) unless otherwise stated.

RESULTS

Rainfall characteristics

During the measurement period, 25 rainfall events, divided into six classes (Table 2), were observed, and 246.2 mm of rainfall were recorded (Figure 2). The precipitation of individual events averaged 9.8 mm, and ranged from 0.1 to 34.8 mm. The precipitations events below 2 mm accounted for 32% of all events, and those below 10 mm accounted for 72% of events. Small precipitation events were frequent but produced a small percentage of the total precipitation amount, whereas large precipitation events were rare but were the main water supply source.

Table 2

Characteristics of rainfall partitioning of three shrub species during the experimental period in the study area

    C. microphylla
 
H. fruticosum
 
S. gordejevii
 
Rainfall amount (mm) Frequency percentage (%) Rainfall percentage (%) Rainfall intensity (mm h–1TF (%) SF (%) I (%) TF (%) SF (%) I (%) TF (%) SF (%) I (%) 
<2 32 1.9 0.5 30.0 13.5 56.5 45.6 9.7 44.7 47.1 8.1 44.8 
2–5 12 4.5 1.3 48.9 13.1 38.0 59.6 8.9 31.5 69.9 7.0 23.1 
5–10 28 20.2 2.3 62.0 11.3 26.7 67.5 6.4 26.1 72.8 5.4 22.3 
10–15 4.5 1.2 67.3 10.4 22.3 80.6 4.3 15.1 74.1 4.7 21.2 
15–20 6.9 11.3 55.8 10.6 33.6 60.2 5.6 34.2 64.1 3.9 32.0 
>20 20 62.1 3.9 71.9 10.3 17.8 80.0 6.0 14.0 83.0 5.9 11.2 
    C. microphylla
 
H. fruticosum
 
S. gordejevii
 
Rainfall amount (mm) Frequency percentage (%) Rainfall percentage (%) Rainfall intensity (mm h–1TF (%) SF (%) I (%) TF (%) SF (%) I (%) TF (%) SF (%) I (%) 
<2 32 1.9 0.5 30.0 13.5 56.5 45.6 9.7 44.7 47.1 8.1 44.8 
2–5 12 4.5 1.3 48.9 13.1 38.0 59.6 8.9 31.5 69.9 7.0 23.1 
5–10 28 20.2 2.3 62.0 11.3 26.7 67.5 6.4 26.1 72.8 5.4 22.3 
10–15 4.5 1.2 67.3 10.4 22.3 80.6 4.3 15.1 74.1 4.7 21.2 
15–20 6.9 11.3 55.8 10.6 33.6 60.2 5.6 34.2 64.1 3.9 32.0 
>20 20 62.1 3.9 71.9 10.3 17.8 80.0 6.0 14.0 83.0 5.9 11.2 

TF: Throughfall; SF: Stemflow; I: Interception.

Figure 2

Rainfall amount (mm), rainfall intensity (mm/h) and rainfall duration (h) during the experimental period in the study area.

Figure 2

Rainfall amount (mm), rainfall intensity (mm/h) and rainfall duration (h) during the experimental period in the study area.

TF, SF, and interception

Of the 25 rainfall events, it was possible to collect TF and SF during 16 of them. Individual TF (mm), SF (mm) and interception (mm) for each shrub were strongly positively correlated with individual rainfall (mm). The rainfall threshold values for initiation of TF for C. microphylla, H. fruticosum and S. gordejevii were 1.6, 1.0, and 1.1 mm, respectively. Similarly, the rainfall threshold values for SF initiation were 0.73, 0.27, and 1.54 mm (Figure 3(a), 3(c) and 3(e)).

Figure 3

The relationship between individual rainfall (mm) and (a) individual TF (mm) and (c) individual SF (mm) and (e) individual interception (mm) for three shrub species over the study period. Box plots depict comparisons among C. microphylla, H. fruticosum and S. gordejevii for (b) TF, (d) SF and (f) interception data at the median and 25th and 75th percentile. Whiskers show the 5th and 95th percentile.

Figure 3

The relationship between individual rainfall (mm) and (a) individual TF (mm) and (c) individual SF (mm) and (e) individual interception (mm) for three shrub species over the study period. Box plots depict comparisons among C. microphylla, H. fruticosum and S. gordejevii for (b) TF, (d) SF and (f) interception data at the median and 25th and 75th percentile. Whiskers show the 5th and 95th percentile.

TF of C. microphylla ranged from 1.4 to 24.6 mm and accounted for 43.5–79.5% (mean = 64.2%) of individual rainfall events, that of H. fruticosum ranged from 1.7 to 28.0 mm and accounted for 49.2–85.0% (mean = 71.2%), and that of S. gordejevii ranged from 2.0 to 30.2 mm and accounted for 55.7–93.7% (mean = 75.3%). Similarly, SF of C. microphylla ranged from 0.3 to 4.0 mm and accounted for 9.0–16.0% (mean = 11.0%) of individual rainfall events, that of H. fruticosum ranged from 0.2 to 2.2 mm and accounted for 4.2–8.9% (mean = 6.3%), and that of S. gordejevii ranged from 0.2 to 2.4 mm and accounted for 3.1–7.0% (mean = 5.3%). Interception by C. microphylla ranged from 1.2 to 8.5 mm and accounted for 9.5–46.8% (mean = 24.8%) of individual rainfall events, that of H. fruticosum ranged from 0.8 to 10.2 mm and accounted for 8.6–46.6% (mean = 22.5%), and that of S. gordejevii ranged from 0.5 to 7.1 mm and accounted for 1.7–41.2% (mean = 19.4%) (Figure 4(a)4(c)).

Figure 4

Rainfall partitioning into TF, SF and interception and its associated rainfall intensity during observation periods for (a) C. microphylla, (b) H. fruticosum and (c) S. gordejevii.

Figure 4

Rainfall partitioning into TF, SF and interception and its associated rainfall intensity during observation periods for (a) C. microphylla, (b) H. fruticosum and (c) S. gordejevii.

TF percentage increased, but interception percentage decreased with individual event rainfall amount for the three shrub species. However, an inflection point occurred at 16.9 mm (the corresponding rainfall intensity was 11.3 mm h–1), where TF percentage decreased but interception percentage increased for C. microphylla, H. fruticosum, and S. gordejevii (Table 2).

Correlations between rainfall partitioning and canopy characteristics

For C. microphylla, SF and interception were positively correlated with canopy area. For S. gordejevii, SF increased with branch number and decreased with stem basal area; however, its interception was significantly positively correlated with stem basal area. There was no significant correlation between rainfall partitioning and any canopy characteristics for H. fruticosum (Table 3).

Table 3

Correlation coefficients between rainfall partitioning and canopy characteristics of three shrub species

 Correlation coefficient
 
 C. microphylla
 
H. fruticosum
 
S. gordejevii
 
Variables TF SF Interception TF SF Interception TF SF Interception 
Canopy area (m2−0.331 0.707* 0.696* −0.271 0.451 0.079 −0.168 0.591 0.523 
Number of branches −0.639 0.283 0.065 −0.196 0.035 0.187 −0.067 0.857** 0.635 
Stem basal diameter (cm) −0.203 −0.457 0.446 0.31 −0.073 −0.25 0.574 −0.121 −0.481 
Branch angle (°) 0.071 −0.472 −0.398 −0.199 0.399 0.034 −0.097 −0.019 0.055 
Stem basal area (cm2−0.417 −0.46 0.543 0.201 −0.026 −0.169 0.179 −0.844** 0.704* 
Shrub height (m) −0.256 −0.381 0.41 −0.141 −0.045 0.141 0.209 −0.177 −0.023 
Canopy volume (m3−0.235 0.546 0.529 0.166 −0.392 −0.007 0.201 0.479 −0.468 
 Correlation coefficient
 
 C. microphylla
 
H. fruticosum
 
S. gordejevii
 
Variables TF SF Interception TF SF Interception TF SF Interception 
Canopy area (m2−0.331 0.707* 0.696* −0.271 0.451 0.079 −0.168 0.591 0.523 
Number of branches −0.639 0.283 0.065 −0.196 0.035 0.187 −0.067 0.857** 0.635 
Stem basal diameter (cm) −0.203 −0.457 0.446 0.31 −0.073 −0.25 0.574 −0.121 −0.481 
Branch angle (°) 0.071 −0.472 −0.398 −0.199 0.399 0.034 −0.097 −0.019 0.055 
Stem basal area (cm2−0.417 −0.46 0.543 0.201 −0.026 −0.169 0.179 −0.844** 0.704* 
Shrub height (m) −0.256 −0.381 0.41 −0.141 −0.045 0.141 0.209 −0.177 −0.023 
Canopy volume (m3−0.235 0.546 0.529 0.166 −0.392 −0.007 0.201 0.479 −0.468 

Note: *P < 0.05; **P < 0.01.

SF funneling ratio

Funneling ratios of C. microphylla first increased and then decreased, with a threshold at approximately 7.2 mm. H. fruticosum and S. gordejevii showed a similar trend with the threshold at approximately 6.5 mm (Figure 5(a)). H. fruticosum exhibited a high variability in its funneling ratio value. In contrast, C. microphylla and S. gordejevii exhibited low variability. The average funneling ratio was 100.1 ± 16.9, 162.7 ± 33.2 and 106.2 ± 23.1 for C. microphylla, H. fruticosum and S. gordejevii, respectively (Figure 5(b)).

Figure 5

The relationship between individual rainfall and SF funneling ratio for C. microphylla, H. fruticosum and S. gordejevii. Box plots portray comparisons among C. microphylla, H. fruticosum and S. gordejevii for stem funneling ratio data at the median and 25th and 75th percentile. Whiskers show the 5th and 95th percentile.

Figure 5

The relationship between individual rainfall and SF funneling ratio for C. microphylla, H. fruticosum and S. gordejevii. Box plots portray comparisons among C. microphylla, H. fruticosum and S. gordejevii for stem funneling ratio data at the median and 25th and 75th percentile. Whiskers show the 5th and 95th percentile.

The stem basal area of the shrubs significantly influenced the SF funneling ratio. The funneling ratio value decreased with stem basal area (y = 248.064 x−0.246; R2 = 0.445; p < 0.0001) (Figure 6). The volumes of SF channeled into the plots were estimated to be 3,167, 676, and 2,210 L for C. microphylla, H. fruticosum, and S. gordejevii, respectively (Table 4).

Table 4

Estimated SF funneling ratio and volume of SF generated in the study area, using the regression from Figure 5 and the volume of rainfall observed

   Stem basal area (cm2)
 
Funneling ratio
 
 
Species Pg (mm) Number of branches min max min max SF (L) 
C. microphylla 246.2 31 0.80 67.17 88 262 3,167 
H. fruticosum 246.2 19 0.31 24.48 113 331 676 
S. gordejevii 246.2 36 0.51 37.77 102 293 2,210 
   Stem basal area (cm2)
 
Funneling ratio
 
 
Species Pg (mm) Number of branches min max min max SF (L) 
C. microphylla 246.2 31 0.80 67.17 88 262 3,167 
H. fruticosum 246.2 19 0.31 24.48 113 331 676 
S. gordejevii 246.2 36 0.51 37.77 102 293 2,210 
Figure 6

The relationship between stem basal area and average SF funneling ratio for C. microphylla, H. fruticosum and S. gordejevii using total rainfall, SF volume and stem basal area measurements over the study period.

Figure 6

The relationship between stem basal area and average SF funneling ratio for C. microphylla, H. fruticosum and S. gordejevii using total rainfall, SF volume and stem basal area measurements over the study period.

DISCUSSION

Rainfall partitioning

Over the study period, TF, SF, and interception were found to be positively correlated with rainfall amount for all three species, which is in accordance with the conclusions drawn from other regions (Návar 2011; Zhang et al. 2013; Swaffer et al. 2014; Fan et al. 2015). This means that rainfall processes rather than plant species and study regions are the determinant factors in rainfall partitioning. However, the correlation between interception and rainfall amount was less prominent, indicating that interception was less influenced by rainfall characteristics than SF and TF.

Different shrub species partition rainfall into TF, SF, and interception differently, resulting in different amounts of available rainwater. The TF percentage of S. gordejevii (75.3%) was the highest, followed by H. fruticosum (71.2%) and C. microphylla (64.2%); while the SF percentage of C. microphylla (11.0%) was higher than that of H. fruticosum (6.3%) and S. gordejevii (5.3%); and the interception percentage of C. microphylla (24.8%) was higher than that of H. fruticosum (22.5%) and S. gordejevii (19.4%). These results indicate that C. microphylla exhibits a higher interception and a higher SF than H. fruticosum or S. gordejevii. Large variations in rainfall partitioning patterns can be found between species in different areas, with SF percentages ranging from 2.2 to 43.3% (Table 5). The difference in rainfall partitioning of shrub species may be attributed to the differences in morphological characteristics of the plant species. For example, the multiple-stems, umbrella-shaped canopy, smooth stems, and numerous ovate leaves of C. microphylla enable it to better intercept rainwater and thus generate greater SF production. H. fruticosum, on the other hand, is a shrub with rough stems and thin leaves, thus its canopy reduces interception and its branches are capable of absorbing SF. The slender and loose stems and leptophyllous leaves of S. gordejevii are unfavorable for rainfall interception but enhance net precipitation.

Table 5

Gross rainfall (Pg) partitioning into TF, SF and interception (I) in different shrub species

No. Location Shrub species Pg (mm) TF (%) SF (%) I (%) References 
USA Prosopis glandulosa 230 62.8 5.4 31.8 Martinez-Meza & Whitford (1996)  
Flourensia cernua 230 55.8 10.6 34.6 
USA Larrea tridentata 235 64.7 16.8 18.5 Whitford et al. (1997)  
Spain Rosmarinus officinalis 290 31.5 43.3 25.2 Serrato & Diaz (1998)  
Thymus vulgaris 290 37.2 29.8 33 
Juniperus oxycedrus 232 44.5 18.7 36.5 
Spain Anthyllis cytisoides 300 40 20 40 Domingo et al. (1998)  
Retama sphaerocarpa 300 72 21 
China Tamarix ramosissima 263 – 2.2 – Li et al. (2008)  
Caragana korshinskii 263 – 3.7 – 
Reaumuria soongorica 263 – 7.2 – 
China Salix psammophila 395 – 7.6 – Yang et al. (2008)  
Artemisia sphaerocephala 395 – 2.7 – 
China Caragana korshinskii 427 – 12.3 – Jian et al. (2014)  
Hippophae rhamnoides 427 – 8.4 – 
China Caragana korshinskii 413 74.3 16.7 Zhang et al. (2015)  
Artemisia ordosica 413 74.8 2.9 22.3 
China Caragana microphylla 238 64.2 11 24.8 In this study 
Hedysarum fruticosum 238 71.2 6.3 22.5 
Salix gordejevii 238 75.3 5.3 19.4 
No. Location Shrub species Pg (mm) TF (%) SF (%) I (%) References 
USA Prosopis glandulosa 230 62.8 5.4 31.8 Martinez-Meza & Whitford (1996)  
Flourensia cernua 230 55.8 10.6 34.6 
USA Larrea tridentata 235 64.7 16.8 18.5 Whitford et al. (1997)  
Spain Rosmarinus officinalis 290 31.5 43.3 25.2 Serrato & Diaz (1998)  
Thymus vulgaris 290 37.2 29.8 33 
Juniperus oxycedrus 232 44.5 18.7 36.5 
Spain Anthyllis cytisoides 300 40 20 40 Domingo et al. (1998)  
Retama sphaerocarpa 300 72 21 
China Tamarix ramosissima 263 – 2.2 – Li et al. (2008)  
Caragana korshinskii 263 – 3.7 – 
Reaumuria soongorica 263 – 7.2 – 
China Salix psammophila 395 – 7.6 – Yang et al. (2008)  
Artemisia sphaerocephala 395 – 2.7 – 
China Caragana korshinskii 427 – 12.3 – Jian et al. (2014)  
Hippophae rhamnoides 427 – 8.4 – 
China Caragana korshinskii 413 74.3 16.7 Zhang et al. (2015)  
Artemisia ordosica 413 74.8 2.9 22.3 
China Caragana microphylla 238 64.2 11 24.8 In this study 
Hedysarum fruticosum 238 71.2 6.3 22.5 
Salix gordejevii 238 75.3 5.3 19.4 

–: not available.

For all three species, TF percentage increased but interception percentage decreased with rainfall amount. However, high-intensity individual rainfall events resulted in lower TF production and higher interception. High intensity rainfall with larger raindrop volume, terminal velocity, and kinetic energy enhances the proportion of rain intercepted by the canopy, thereby reducing the water available for TF production (Carlyle-Moses 2004).

The thresholds for TF initiation of C. microphylla, H. fruticosum, and S. gordejevii were 1.6, 1.0, and 1.1 mm, respectively, indicating that they are species-specific. The threshold for SF initiation for S. gordejevii (1.54 mm) was larger than that for C. microphylla (0.73 mm) and H. fruticosum (0.27 mm). The higher value of S. gordejevii is likely to be due to the long, thick, and coarse branches with high bark storage capacities that are unfavorable for channeling SF (Levia & Herwitz 2005). The multiple smooth stems and ovate, small, waxy leaves of C. microphylla led to its rapid generation and large production of SF.

Rainfall partitioning in relation to canopy characteristics

There was a weak correlation between rainfall partitioning and canopy characteristics such as stem basal diameter, branch angle, shrub height, and canopy volume, but some studies have found that SF is correlated with canopy area, shrub height, branch number, and canopy volume for Caragana korshinskii and Hippophae rhamnoides (Jian et al. 2014). The differences between our results and those of previous studies may be explained by two possible reasons. First, canopy structure and characteristics are species-specific, and bark surface structure, stem number, and density affect rainfall partitioning pattern (Zhang et al. 2015). Second, seasons and precipitation conditions may play a role in how plants partition rainfall. For example, in the dry season, the interception percentage by a canopy may be greater during low intensity, low volume precipitation events than a similar event in the wet season (Deguchi et al. 2006). To arrive at more general conclusions, future research should include more parameters relevant to rainfall partitioning.

SF funneling ratio

The average funneling ratios for the three species were considerably outweighed by 1, indicating that the rainwater caught by the funnels was greater than that caught by the rain gauges placed in the open areas (Li et al. 2008; Wang et al. 2013; Jian et al. 2014). That H. fruticosum contributed to more SF than C. microphylla and S. gordejevii could be due to its branches being smoother and slimmer than C. microphylla and S. gordejevii.

Because SF funneling ratios decrease exponentially with stem basal area (Figure 6), it is reasonable to scale SF at the individual level up to the stand level by using stem basal area (Macinnis-Ng et al. 2014). Although the average funneling ratio of H. fruticosum was larger than that of C. microphylla or S. gordejevii at the individual scale, SF of C. microphylla was the largest at the plot scale, indicating that there are discrepancies in calculating SF fractions across scales.

Implications

Available water, which is dependent on rainfall partitioning in arid regions (Levia & Frost 2003; Frost & Levia 2014), is the most important factor for shrubs used for sand stabilization, especially when potential evapotranspiration is much larger than precipitation. Since C. microphylla, H. fruticosum and S. gordejevii are good sand-fixing shrubs in northern China (Zhang et al. 2006; Zhao et al. 2007), it is necessary to know their rainwater use strategies under different rainfall partitioning patterns. Our study indicates that C. microphylla, a dense-branch-type shrub, which can intercept more rainwater and generate larger SF fractions than the other two shrubs, represents a ‘capturing type’ strategy of rainwater use. H. fruticosum, a thin-leaf-type shrub, which can result in more SF production, represents a ‘funneling type’ strategy of rainwater use. S. gordejevii, a loose-stem-type shrub, which has larger TF production but generates less SF production, represents a ‘through type’ strategy of rainwater use. Therefore, C. microphylla has an advantage in enhancing net precipitation through greater interception over H. fruticosum and S. gordejevii, facilitating the formation of ‘moist islands’ around its root zone (Zhao et al. 2007). Thereby, it is the best sand binder of the three tested here with regard to rainwater use efficiency in semiarid sand lands.

CONCLUSIONS

The different morphological characteristics of shrub species affect how rainfall is partitioned into TF, SF, and interception, resulting in different rainwater use strategies. Dense-type shrubs (umbrella-shaped canopy, multiple smooth stems and numerous ovate leaves) such as C. microphylla represent a ‘capturing type’ strategy of rainwater use. Thin-leaf-type shrubs (rough stems and thin leaves) such as H. fruticosum represent a ‘funneling type’ strategy of rainwater use. Loose-stem-type shrubs (loosely branched slender stems, and leptophyllous leaves) such as S. gordejevii represent a ‘through type’ strategy of rainwater use. From the perspective of rainfall partitioning, C. microphylla may be the best shrub for re-vegetation in arid sandy regions.

ACKNOWLEDGEMENTS

The study was funded by the National Basic Research Program of China (No. 2013CB429902). The authors would like to thank the anonymous reviewers for their helpful comments. Additionally, we would like to thank Editage (http://online.editage.cn/) for English language editing.

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