Abstract

Stemflow is known as a highly localized point input of rainwater and solutes around tree/shrub bases where roots are concentrated, thus having considerable effects on hydrology and biogeochemistry of vegetated ecosystems. Stemflow shows a pronounced inter-specific variation due to morphological differences among species, while the intra-specific variation of stemflow has been poorly explored. We systematically examined the effects of shrub morphological metrics on intra-specific funnelling efficiencies by quantifying the stemflow of nine shrubs of Caragana korshinskii within a water-limited arid desert ecosystem of northern China. Stemflow volume was used to compare the absolute amount of stemflow generated by shrubs of varying size, and funnelling ratio was used to assess their funnelling efficiencies. Both rainfall depth and shrub morphological metrics significantly affected stemflow volume, while funnelling ratio was more associated with shrub morphology. Under the same rainfall condition, smaller shrubs produced lower volumes of stemflow, while gaining access to rainfall via higher funnelling ratio than larger shrubs. Our findings highlight a large variation in funnelling efficiency among individual shrubs within the same species, and in particular, smaller shrubs might profit more from sporadic small rainfall events than larger shrubs.

INTRODUCTION

Drylands cover about 41% of Earth's terrestrial surface (Reynolds et al. 2007; Huang et al. 2015), characterized by a two-phase mosaic composed of vegetated patches interspersed with bare patches (Aguiar & Sala 1999; Tongway et al. 2001; Rietkerk & Van de Koppel 2008), where precipitation is scarce and typically unpredictable and hence a key limiting factor of ecosystem functioning (e.g., Noy-Meir 1973). Shrubs are the dominant vegetation over the vast drylands, and play a crucial role in the hydrological and biogeochemical cycles in terms of redistributing incident precipitation (Schlesinger & Pilmanis 1998; Llorens & Domingo 2007; Zhang et al. 2016a). Precipitation falling on the shrub canopy either is intercepted and subsequently evaporated (interception loss) or reaches the ground diffusely by throughfall or concentrated by funnelling down the stems in the form of stemflow.

Stemflow is volumetrically small (normally 5–10% of incident precipitation) in comparison to the other components of the canopy water balance; it is, however, of high eco-hydrological and chemical importance due to its very local input to nature (Johnson & Lehmann 2006; Levia & Germer 2015). Nutrient-enriched stemflow funnels down the shrub stems and infiltrates into deep soil layers through preferential pathways such as roots, creating islands of soil moisture and nutrients (e.g., Mauchamp & Janeau 1993; Navar 2011; Schwärzel et al. 2012; Zhang et al. 2013, 2016b). Stemflow is thus considered to be an important biological transfer mechanism in contributing to the development of ‘fertile islands’ under shrub canopies in the arid and semi-arid environments where water and nutrients are typically limited (Garner & Steinberger 1989; Whitford et al. 1997).

Stemflow has been reported to be influenced by a suite of biotic and abiotic factors, including canopy structure and architecture (e.g., Crockford & Richardson 2000; Park & Cameron 2008; Wang et al. 2013), rainfall depth, intensity and duration (e.g., Dunkerley 2014; Zhang et al. 2015), antecedent dry period (Tobon et al. 2004), wind direction and speed (e.g., Xiao et al. 2000; Van Stan et al. 2011) and vapour pressure deficit (e.g., Staelens et al. 2008; Pugh & Small 2013). The complex interactions among these factors also make it difficult to determine how a single factor affects stemflow production (Levia & Germer 2015).

Stemflow shows a highly inter-specific variation (the variation among species) due to morphological differences among tree/shrub species in a wide range of ecosystems (Van Dijk & Bruijnzeel 2001; Levia & Frost 2003; Llorens & Domingo 2007; Swaffer et al. 2014; Janeau et al. 2015; Zhang et al. 2015). For example, Llorens & Domingo (2007) reported that in the European Mediterranean area, stemflow percentage averaged 3%, with a variation coefficient of 111%, ranging from about 1% for Picea abies, Pinus sylvestris and Quercus pyrenaica and 12% for Pinus nigra. Yet the intra-specific variation (the variation within the same species) of stemflow has been poorly explored. A handful of recent studies from forested ecosystems showing high stemflow generating efficiencies for small trees (Germer et al. 2010; Siegert & Levia 2014; Su et al. 2016) are stimulating further research in various ecosystems. In the present study, event-based measurements on stemflow of nine shrubs of C. korshinskii varying from small to large were made during three rainy seasons of 2011–2013 within a water-limited arid desert ecosystem. The objectives of our study were: (1) to quantify the amount of rainwater flowing down the shrub stem and (2) to evaluate the differential funnelling efficiencies among individual shrubs within the same species. Achievement of these research objectives is important to gain a better understanding of vertical and horizontal water distribution under shrub canopies, and of different water acquisition strategies of individual shrubs within the same species in water-limited arid desert ecosystems.

MATERIALS AND METHODS

Site information

Field measurements were carried out during three growing seasons of 2011–2013 at the Water Balance Experimental Field (WBEF) (Figure 1(a)) of Shapotou Desert Research and Experiment Station of Chinese Academy of Sciences (37°32′ N, 105°02′ E, with an elevation of 1,300 m a.s.l.), on the southeastern fringe of the Tengger Desert in northwestern China. Mean annual precipitation is 191 mm with 80% of rain falling between July and September. Most storms are of a low amount and intensity, with around 80% of the rainfall intensities ≤5 mm h−1 (Zhang et al. 2015). The groundwater is at a depth of 50–80 m, and therefore inaccessible to plant roots. Potential evapotranspiration is approximately 2,500 mm during the growing season (April–October), resulting in a large annual moisture deficit. Mean maximum and minimum air temperature is 24.7 °C in July and −6.1 °C in January, respectively. Annual mean wind velocity is approximately 2.8 m s−1.

Figure 1

Map showing the location of the Water Balance Experimental Field (WBEF) (a); topography of the WBEF and the spatial distribution of C. korshinskii (the nine shrubs selected for the experiments are depicted by a solid triangle and the others by a solid circle) in the WBEF (b); and the method of collecting stemflow for C. korshinskii (c).

Figure 1

Map showing the location of the Water Balance Experimental Field (WBEF) (a); topography of the WBEF and the spatial distribution of C. korshinskii (the nine shrubs selected for the experiments are depicted by a solid triangle and the others by a solid circle) in the WBEF (b); and the method of collecting stemflow for C. korshinskii (c).

C. korshinskii is a multiple-stemmed deciduous perennial leguminous shrub with an inverted cone shape, and is one of the successful shrubs used in revegetation for protecting the Baotou-Lanzhou railway against encroaching sand dunes in the Shapotou area (Li et al. 2006; Li 2012). The stems are smooth, the leaves are pinnately compound and opposite or subopposite in arrangement and 6–10 cm long, and each pinna has five to eight pairs of ovate leaflets (7–8 mm in length and 2–5 mm in width). The average height and the average canopy diameter of C. korshinskii at WBEF was 145 and 130 cm, respectively.

Shrub selection and measurements

Nine robust and healthy shrubs of C. korshinskii were selected for field observation (Figure 1(b)) according to the gradient of stem numbers of C. korshinskii in WBEF, and their morphological characteristics are quantified in Table 1. A shrub with more stems is also more likely to have a greater canopy area, thus we assume the nine shrubs represent the range of sizes of C. korshinskii at larger community scales. Stem diameter was measured with a vernier caliper at each stem base, and stem angle was determined by a protractor. The plant area index (PAI, m2 m−2), one-sided plant area (stems, twigs, leaves) per ground area, was estimated using a LAI-2000 plant canopy analyser (Li-Cor, Inc., USA). Shrub height was measured at the centre of the canopy using a tape. The projected canopy area (approximated as an ellipse) was calculated by taking the east–west and north–south diameters through the centre of the fullest part of the canopy (Martinez-Meza & Whitford 1996). Shrub volume was estimated by considering canopy shape as an inverted elliptic cone. Basal area was defined as the sum of the cross-sectional area of individual stems of a given shrub.

Table 1

Descriptive statistics (mean ± SE) of morphological metrics of C. korshinskii selected in the experiments

No. Stem
 
Shrub
 
PAI 
Number Diameter (cm) Length (cm) Angle (°) Height (cm) Canopy area (m2Volume (m3
CK_1 1.8 ± NA 98 ± NA 50 ± NA 114 0.39 0.15 0.69 
CK_2 2.2 ± 0.0 94 ± 5.5 77 ± 5 115 0.59 0.23 0.77 
CK_3 1.5 ± 0.2 77 ± 1.7 60 ± 19 126 0.60 0.25 0.54 
CK_4 1.4 ± 0.2 50 ± 5.9 59 ± 3 92 0.66 0.20 0.95 
CK_5 2.5 ± 0.2 159 ± 18.3 73 ± 3 245 3.69 3.02 0.71 
CK_6 1.9 ± 0.5 119 ± 14.3 72 ± 5 216 2.23 1.61 0.78 
CK_7 2.5 ± 0.4 151 ± 12.3 60 ± 8 203 5.19 3.51 1.02 
CK_8 11 1.7 ± 0.2 83 ± 2.6 56 ± 3 158 2.69 1.42 0.68 
CK_9 12 1.8 ± 0.1 103 ± 9.1 60 ± 4 182 2.07 1.26 1.01 
Mean 1.9 107 62 152 1.82 1.26 0.76 
SE 0.1 5.7 2.1 18 0.53 0.40 0.06 
No. Stem
 
Shrub
 
PAI 
Number Diameter (cm) Length (cm) Angle (°) Height (cm) Canopy area (m2Volume (m3
CK_1 1.8 ± NA 98 ± NA 50 ± NA 114 0.39 0.15 0.69 
CK_2 2.2 ± 0.0 94 ± 5.5 77 ± 5 115 0.59 0.23 0.77 
CK_3 1.5 ± 0.2 77 ± 1.7 60 ± 19 126 0.60 0.25 0.54 
CK_4 1.4 ± 0.2 50 ± 5.9 59 ± 3 92 0.66 0.20 0.95 
CK_5 2.5 ± 0.2 159 ± 18.3 73 ± 3 245 3.69 3.02 0.71 
CK_6 1.9 ± 0.5 119 ± 14.3 72 ± 5 216 2.23 1.61 0.78 
CK_7 2.5 ± 0.4 151 ± 12.3 60 ± 8 203 5.19 3.51 1.02 
CK_8 11 1.7 ± 0.2 83 ± 2.6 56 ± 3 158 2.69 1.42 0.68 
CK_9 12 1.8 ± 0.1 103 ± 9.1 60 ± 4 182 2.07 1.26 1.01 
Mean 1.9 107 62 152 1.82 1.26 0.76 
SE 0.1 5.7 2.1 18 0.53 0.40 0.06 

PAI: plant area index.

NA: not available.

Stemflow and rainfall measurements

Stemflow was collected using an aluminium foil collar that was fitted around the entire circumference of individual shrub stems (Figure 1(c)). Stemflow volume was measured by a graduated cylinder for each individual stem after the cessation of each rainfall event.

Funnelling ratio was used to compare differential stemflow funnelling efficiencies among individual shrubs of C. korshinskii. According to Herwitz (1986), it is defined as:  
formula
(1)
where VSF is the stemflow volume (mL), B is the stem basal area (cm2) of stemflow generating shrub, and R is depth equivalent of the incident gross rainfall (mm). Funnelling ratio represents the ratio of stemflow volume collected at the shrub base to the volume that would have been expected in a rain gauge occupying the same area as the stem basal area in the absence of the shrub. Funnelling ratio exceeding 1 indicates that the canopy component other than the stems are contributing to the stemflow input.

A standard tipping bucket rain gauge (Adolf Thies GMVH & Co. KG, Germany) with a resolution of 0.1 mm was installed in an open area approximately 50 m from the study plot. Individual events were separated by at least 4 h without rainfall.

Statistical analyses

Descriptive statistics were compiled for shrub morphological metrics, rainfall depth, stemflow volume and funnelling ratio. The correlations among shrub morphological metrics were analysed using Pearson correlation. The linear function was used to determine the relationships of stemflow volume with rainfall and shrub morphological metrics. The linear and the exponential decay functions were used to determine the relationships between funnelling ratio and shrub morphological metrics. All the descriptive statistics, correlations and fitted functions were performed using SPSS 16.0 statistical software (SPSS Inc., Chicago, IL, USA).

RESULTS

Rainfall, stemflow volume and funnelling ratio

In total, 37 rainfall events (totalling 410.3 mm) that can produce stemflow were recorded during the study period, ranging in depth from 2.4 to 28.8 mm with a mean of 11.1 mm and a variation of coefficient (CV) of 61% (Table 2).

Table 2

Total shrub stemflow volume on a rainfall event basis

Event Rainfall (mm) Total event stemflow volumes (mL)
 
CK_1 CK_2 CK_3 CK_4 CK_5 CK_6 CK_7 CK_8 CK_9 
2011-06-26 5.6 45 102 67 345 70 241 230 146 
2011-07-02 11.9 180 1,340 1,870 1,545 2,975 2,680 3,730 4,330 4,415 
2011-07-28 13.9 135 735 910 810 3,625 1,605 4,125 2,280 2,490 
2011-08-15 21.3 192 1,031 1,384 1,344 5,802 2,519 6,662 3,064 3,954 
2011-08-18 20.2 180 2,090 1,600 1550 8,090 4,020 12,730 2,875 3,760 
2011-08-23 10.6 120 900 460 760 4,095 2,030 7,180 2,560 2,600 
2011-09-02 50 410 365 300 1,165 878 1,805 930 704 
2011-09-04 8.4 20 320 230 242 910 650 2,015 895 549 
2011-09-05 3.1 10 92 132 100 502 439 743 372 284 
2011-09-09 11 125 1,348 798 858 4,174 3,275 9,247 3,824 2,802 
2011-09-15 6.1 55 575 375 395 2,225 1,415 4,675 1,395 1,170 
2011-09-16 12 125 1,300 990 845 4,280 2,785 9,260 2,425 2,520 
2011-09-18 4.3 14 285 255 262 1,280 950 2,450 713 698 
2011-10-09 6.4 50 515 315 360 1,715 1,031 4,295 1,077 698 
2011-10-12 7.3 65 590 450 465 2,660 1,430 5,335 1,695 1,560 
2011-11-07 8.6 60 610 455 496 2,160 1,332 4,540 1,262 1,052 
2012-04-11 4.4 15 130 215 235 965 625 1,360 594 510 
2012-04-30 6.1 30 370 410 285 2,055 1,185 2,270 1,110 1,560 
2012-05-23 18.1 220 1,920 1,730 1,365 5,470 3,665 10,700 5,070 5,415 
2012-05-28 3.7 25 250 235 175 850 314 1,315 735 690 
2012-06-27 23.2 340 2,250 2,030 2,220 5,620 4,765 11,460 5,240 7,500 
2012-06-28 14.8 155 1,970 1,380 1,265 3,780 3,815 15,520 3,880 5,494 
2012-07-08 2.4 25 205 170 150 420 310 1,540 500 865 
2012-07-17 20.4 270 1,610 1,750 1,465 4,020 3,240 13,535 3,800 5,870 
2012-07-21 17.5 200 1,650 1,500 1,340 3,410 3,320 10,530 4,000 5,560 
2012-07-30 3.5 10 45 30 250 59 475 160 138 
2012-09-01 28.8 350 2,330 2,310 2,330 4,620 1,810 6,425 4,350 6,070 
2012-09-11 3.5 20 195 133 94 362 322 1,656 286 676 
2012-09-25 9.1 100 860 815 640 1,460 1,040 6,020 1,075 3,380 
2013-05-15 8.4 80 850 685 545 1,360 2,770 1,335 1,225 1,760 
2013-06-09 6.2 30 145 185 170 635 625 625 600 660 
2013-06-21 19.4 245 415 1,570 1,660 5,815 2,660 5,000 4,760 4,690 
2013-07-03 18.1 300 1,220 1,180 1,050 3,580 2,390 7,460 4,160 4,850 
2013-07-09 14.6 180 1,250 990 1,105 1,290 1,795 5,460 3,070 3,520 
2013-07-26 17.7 200 1,720 1,530 1,175 3,500 2,920 6,535 3,995 4,140 
2013-08-06 8.6 105 380 790 485 985 1,005 1,425 1,825 2,137 
2013-10-31 7.1 105 210 360 207 661 683 370 618 734 
Mean 11.1 119 868 830 767 2,624 1,795 5,137 2,189 2,584 
Sum 410.3 4,387 32,126 30,704 28,390 97,111 66,427 190,049 80,980 95,621 
Min. 2.4 10 45 30 250 59 241 160 138 
Max. 28.8 105 610 685 545 2,160 1,430 4,540 1,695 2,137 
C.V. (%) 61 83 80 78 81 75 70 81 74 80 
Event Rainfall (mm) Total event stemflow volumes (mL)
 
CK_1 CK_2 CK_3 CK_4 CK_5 CK_6 CK_7 CK_8 CK_9 
2011-06-26 5.6 45 102 67 345 70 241 230 146 
2011-07-02 11.9 180 1,340 1,870 1,545 2,975 2,680 3,730 4,330 4,415 
2011-07-28 13.9 135 735 910 810 3,625 1,605 4,125 2,280 2,490 
2011-08-15 21.3 192 1,031 1,384 1,344 5,802 2,519 6,662 3,064 3,954 
2011-08-18 20.2 180 2,090 1,600 1550 8,090 4,020 12,730 2,875 3,760 
2011-08-23 10.6 120 900 460 760 4,095 2,030 7,180 2,560 2,600 
2011-09-02 50 410 365 300 1,165 878 1,805 930 704 
2011-09-04 8.4 20 320 230 242 910 650 2,015 895 549 
2011-09-05 3.1 10 92 132 100 502 439 743 372 284 
2011-09-09 11 125 1,348 798 858 4,174 3,275 9,247 3,824 2,802 
2011-09-15 6.1 55 575 375 395 2,225 1,415 4,675 1,395 1,170 
2011-09-16 12 125 1,300 990 845 4,280 2,785 9,260 2,425 2,520 
2011-09-18 4.3 14 285 255 262 1,280 950 2,450 713 698 
2011-10-09 6.4 50 515 315 360 1,715 1,031 4,295 1,077 698 
2011-10-12 7.3 65 590 450 465 2,660 1,430 5,335 1,695 1,560 
2011-11-07 8.6 60 610 455 496 2,160 1,332 4,540 1,262 1,052 
2012-04-11 4.4 15 130 215 235 965 625 1,360 594 510 
2012-04-30 6.1 30 370 410 285 2,055 1,185 2,270 1,110 1,560 
2012-05-23 18.1 220 1,920 1,730 1,365 5,470 3,665 10,700 5,070 5,415 
2012-05-28 3.7 25 250 235 175 850 314 1,315 735 690 
2012-06-27 23.2 340 2,250 2,030 2,220 5,620 4,765 11,460 5,240 7,500 
2012-06-28 14.8 155 1,970 1,380 1,265 3,780 3,815 15,520 3,880 5,494 
2012-07-08 2.4 25 205 170 150 420 310 1,540 500 865 
2012-07-17 20.4 270 1,610 1,750 1,465 4,020 3,240 13,535 3,800 5,870 
2012-07-21 17.5 200 1,650 1,500 1,340 3,410 3,320 10,530 4,000 5,560 
2012-07-30 3.5 10 45 30 250 59 475 160 138 
2012-09-01 28.8 350 2,330 2,310 2,330 4,620 1,810 6,425 4,350 6,070 
2012-09-11 3.5 20 195 133 94 362 322 1,656 286 676 
2012-09-25 9.1 100 860 815 640 1,460 1,040 6,020 1,075 3,380 
2013-05-15 8.4 80 850 685 545 1,360 2,770 1,335 1,225 1,760 
2013-06-09 6.2 30 145 185 170 635 625 625 600 660 
2013-06-21 19.4 245 415 1,570 1,660 5,815 2,660 5,000 4,760 4,690 
2013-07-03 18.1 300 1,220 1,180 1,050 3,580 2,390 7,460 4,160 4,850 
2013-07-09 14.6 180 1,250 990 1,105 1,290 1,795 5,460 3,070 3,520 
2013-07-26 17.7 200 1,720 1,530 1,175 3,500 2,920 6,535 3,995 4,140 
2013-08-06 8.6 105 380 790 485 985 1,005 1,425 1,825 2,137 
2013-10-31 7.1 105 210 360 207 661 683 370 618 734 
Mean 11.1 119 868 830 767 2,624 1,795 5,137 2,189 2,584 
Sum 410.3 4,387 32,126 30,704 28,390 97,111 66,427 190,049 80,980 95,621 
Min. 2.4 10 45 30 250 59 241 160 138 
Max. 28.8 105 610 685 545 2,160 1,430 4,540 1,695 2,137 
C.V. (%) 61 83 80 78 81 75 70 81 74 80 

A great variability in stemflow volume can be found among rainfall events for individual shrubs. Stemflow volume increased significantly (P < 0.01) with rainfall depth for all studied shrubs (Figure 2). Total event stemflow volumes differed considerably among individual shrubs of C. korshinskii (Table 2). For example, the sum of stemflow volume produced by CK_7 (190,049 mL) was 43.3 times greater than CK_1 (4,387 mL). These findings highlight the important interactions between rain event magnitude and intra-specific stemflow yield.

Figure 2

Stemflow volume in relation to rainfall depth for individual shrubs.

Figure 2

Stemflow volume in relation to rainfall depth for individual shrubs.

Mean event funnelling ratio also differed considerably among individual sample shrubs of C. korshinskii, suggesting the differential funnelling efficiencies among shrubs (Table 3). For example, the funnelling ratio was 37 for CK_1 and 123 for CK_3. Generally, the event funnelling ratio for individual shrubs had an increased tendency with rainfall depth (Figure 3(b)) until a threshold value around 12 mm and then began to decline (Figure 3(a)).

Table 3

Stemflow funnelling ratio on a rainfall event basis

Event Rainfall (mm) Event funnelling ratio
 
CK_1 CK_2 CK_3 CK_4 CK_5 CK_6 CK_7 CK_8 CK_9 
2011-06-26 5.6 4.3 11.1 32.5 15.1 19.8 4.5 8.2 14.3 7.6 
2011-07-02 11.9 60.8 155.1 280.5 163.5 80.5 80.9 59.5 126.5 108.8 
2011-07-28 13.9 39.0 72.8 116.9 73.4 84.0 41.5 56.3 57.0 52.5 
2011-08-15 21.3 36.2 66.7 116.0 79.5 87.7 42.5 59.4 50.0 54.5 
2011-08-18 20.2 35.8 142.5 141.4 96.7 129.0 89.2 119.6 49.5 54.6 
2011-08-23 10.6 45.5 116.9 77.5 90.3 124.4 68.8 128.6 84.0 72.0 
2011-09-02 50.2 141.2 162.9 94.5 93.8 78.8 85.6 80.8 51.6 
2011-09-04 8.4 9.6 52.5 48.9 36.3 34.9 27.8 45.5 37.0 19.2 
2011-09-05 3.1 13.0 40.9 76.0 40.6 52.2 50.8 45.5 41.7 26.9 
2011-09-09 11 45.7 168.8 129.5 98.2 122.2 106.9 159.5 120.9 74.7 
2011-09-15 6.1 36.2 129.8 109.7 81.6 117.5 83.3 145.4 79.5 56.3 
2011-09-16 12 41.9 149.2 147.3 88.7 114.9 83.3 146.5 70.3 61.6 
2011-09-18 4.3 13.1 91.3 105.9 76.7 95.9 79.3 108.1 57.7 47.6 
2011-10-09 6.4 31.4 110.8 87.9 70.9 86.3 57.8 127.4 58.5 32.0 
2011-10-12 7.3 35.8 111.3 110.0 80.2 117.4 70.3 138.7 80.7 62.7 
2011-11-07 8.6 28.0 97.7 94.4 72.6 80.9 55.6 100.2 51.0 35.9 
2012-04-11 4.4 13.7 40.7 87.2 67.3 70.6 51.0 58.7 46.9 34.0 
2012-04-30 6.1 19.8 83.5 120.0 58.9 108.5 69.8 70.6 63.3 75.0 
2012-05-23 18.1 48.8 146.1 170.6 95.0 97.3 72.7 112.2 97.4 87.8 
2012-05-28 3.7 27.2 93.1 113.4 59.6 74.0 30.5 67.5 69.1 54.7 
2012-06-27 23.2 58.9 133.6 156.2 120.5 78.0 73.8 93.8 78.5 94.8 
2012-06-28 14.8 42.1 183.3 166.5 107.7 82.3 92.6 199.0 91.2 108.9 
2012-07-08 2.4 41.9 117.6 126.5 78.7 56.4 46.4 121.8 72.4 105.7 
2012-07-17 20.4 53.2 108.7 153.1 90.5 63.5 57.0 125.9 64.8 84.4 
2012-07-21 17.5 45.9 129.8 153.0 96.5 62.8 68.1 114.2 79.5 93.2 
2012-07-30 3.5 5.7 3.9 23.0 10.8 23.0 6.1 25.8 15.9 11.6 
2012-09-01 28.8 48.8 111.4 143.2 101.9 51.7 22.6 42.3 52.5 61.8 
2012-09-11 3.5 23.0 76.7 67.8 33.8 33.3 33.0 89.8 28.4 56.7 
2012-09-25 9.1 44.2 130.1 159.9 88.6 51.7 41.0 125.6 41.1 109.0 
2013-05-15 8.4 38.3 139.3 145.6 81.7 52.1 118.4 30.2 50.7 61.5 
2013-06-09 6.2 19.4 32.2 53.3 34.5 33.0 36.2 19.1 33.6 31.2 
2013-06-21 19.4 50.6 29.4 144.2 107.6 96.3 49.1 48.8 85.1 70.8 
2013-07-03 18.1 66.6 92.8 116.4 73.1 63.7 47.4 78.2 79.9 78.6 
2013-07-09 14.6 49.5 117.9 121.0 95.3 28.5 44.1 71.0 73.1 70.7 
2013-07-26 17.7 45.4 133.8 154.3 83.6 63.7 59.2 70.1 78.5 68.6 
2013-08-06 8.6 49.1 60.8 164.0 71.0 36.9 42.0 31.4 73.8 72.9 
2013-10-31 7.1 50.1 61.8 165.0 72.0 37.9 43.0 32.4 74.8 73.9 
Mean 11.1 37 100 123 78 73 57 85 65 63 
Min. 2.4 23 11 20 14 
Max. 28.8 67 183 281 164 129 118 199 127 109 
C.V. (%) 61 43 45 39 37 43 44 53 38 42 
Event Rainfall (mm) Event funnelling ratio
 
CK_1 CK_2 CK_3 CK_4 CK_5 CK_6 CK_7 CK_8 CK_9 
2011-06-26 5.6 4.3 11.1 32.5 15.1 19.8 4.5 8.2 14.3 7.6 
2011-07-02 11.9 60.8 155.1 280.5 163.5 80.5 80.9 59.5 126.5 108.8 
2011-07-28 13.9 39.0 72.8 116.9 73.4 84.0 41.5 56.3 57.0 52.5 
2011-08-15 21.3 36.2 66.7 116.0 79.5 87.7 42.5 59.4 50.0 54.5 
2011-08-18 20.2 35.8 142.5 141.4 96.7 129.0 89.2 119.6 49.5 54.6 
2011-08-23 10.6 45.5 116.9 77.5 90.3 124.4 68.8 128.6 84.0 72.0 
2011-09-02 50.2 141.2 162.9 94.5 93.8 78.8 85.6 80.8 51.6 
2011-09-04 8.4 9.6 52.5 48.9 36.3 34.9 27.8 45.5 37.0 19.2 
2011-09-05 3.1 13.0 40.9 76.0 40.6 52.2 50.8 45.5 41.7 26.9 
2011-09-09 11 45.7 168.8 129.5 98.2 122.2 106.9 159.5 120.9 74.7 
2011-09-15 6.1 36.2 129.8 109.7 81.6 117.5 83.3 145.4 79.5 56.3 
2011-09-16 12 41.9 149.2 147.3 88.7 114.9 83.3 146.5 70.3 61.6 
2011-09-18 4.3 13.1 91.3 105.9 76.7 95.9 79.3 108.1 57.7 47.6 
2011-10-09 6.4 31.4 110.8 87.9 70.9 86.3 57.8 127.4 58.5 32.0 
2011-10-12 7.3 35.8 111.3 110.0 80.2 117.4 70.3 138.7 80.7 62.7 
2011-11-07 8.6 28.0 97.7 94.4 72.6 80.9 55.6 100.2 51.0 35.9 
2012-04-11 4.4 13.7 40.7 87.2 67.3 70.6 51.0 58.7 46.9 34.0 
2012-04-30 6.1 19.8 83.5 120.0 58.9 108.5 69.8 70.6 63.3 75.0 
2012-05-23 18.1 48.8 146.1 170.6 95.0 97.3 72.7 112.2 97.4 87.8 
2012-05-28 3.7 27.2 93.1 113.4 59.6 74.0 30.5 67.5 69.1 54.7 
2012-06-27 23.2 58.9 133.6 156.2 120.5 78.0 73.8 93.8 78.5 94.8 
2012-06-28 14.8 42.1 183.3 166.5 107.7 82.3 92.6 199.0 91.2 108.9 
2012-07-08 2.4 41.9 117.6 126.5 78.7 56.4 46.4 121.8 72.4 105.7 
2012-07-17 20.4 53.2 108.7 153.1 90.5 63.5 57.0 125.9 64.8 84.4 
2012-07-21 17.5 45.9 129.8 153.0 96.5 62.8 68.1 114.2 79.5 93.2 
2012-07-30 3.5 5.7 3.9 23.0 10.8 23.0 6.1 25.8 15.9 11.6 
2012-09-01 28.8 48.8 111.4 143.2 101.9 51.7 22.6 42.3 52.5 61.8 
2012-09-11 3.5 23.0 76.7 67.8 33.8 33.3 33.0 89.8 28.4 56.7 
2012-09-25 9.1 44.2 130.1 159.9 88.6 51.7 41.0 125.6 41.1 109.0 
2013-05-15 8.4 38.3 139.3 145.6 81.7 52.1 118.4 30.2 50.7 61.5 
2013-06-09 6.2 19.4 32.2 53.3 34.5 33.0 36.2 19.1 33.6 31.2 
2013-06-21 19.4 50.6 29.4 144.2 107.6 96.3 49.1 48.8 85.1 70.8 
2013-07-03 18.1 66.6 92.8 116.4 73.1 63.7 47.4 78.2 79.9 78.6 
2013-07-09 14.6 49.5 117.9 121.0 95.3 28.5 44.1 71.0 73.1 70.7 
2013-07-26 17.7 45.4 133.8 154.3 83.6 63.7 59.2 70.1 78.5 68.6 
2013-08-06 8.6 49.1 60.8 164.0 71.0 36.9 42.0 31.4 73.8 72.9 
2013-10-31 7.1 50.1 61.8 165.0 72.0 37.9 43.0 32.4 74.8 73.9 
Mean 11.1 37 100 123 78 73 57 85 65 63 
Min. 2.4 23 11 20 14 
Max. 28.8 67 183 281 164 129 118 199 127 109 
C.V. (%) 61 43 45 39 37 43 44 53 38 42 
Figure 3

Funnelling ratio in relation to rainfall depth for individual shrubs (a) and an example from three shrubs (CK_1, CK_2 and CK_3) showing the relationship between funnelling ratio and rainfall depth for rainfall ≤12 mm (b).

Figure 3

Funnelling ratio in relation to rainfall depth for individual shrubs (a) and an example from three shrubs (CK_1, CK_2 and CK_3) showing the relationship between funnelling ratio and rainfall depth for rainfall ≤12 mm (b).

Stemflow volume and funnelling ratio in relation to shrub morphology

The relationship between the total stemflow yield from all the individual stemflow events and shrub morphological metrics was analysed separately (Figure 4). Stemflow volume had a significant positive linear relationship with projected canopy area (R2 = 0.92, P < 0.001), shrub volume (R2 = 0.83, P < 0.001), basal area (R2 = 0.94, P < 0.001), shrub height (R2 = 0.49, P= 0.036), number of stems (R2 = 0.45, P= 0.047), stem diameter (R2 = 0.53, P < 0.001) and stem length (R2 = 0.19, P < 0.001), respectively. It had an increased tendency with PAI (Figure 4(d)), although the relation was not statistically significant (P= 0.13). No clear relation was found between stemflow volume and stem angle (Figure 4(g)). Moreover, for morphological metrics (Table 1), significant positive relations (r > 0.7, P < 0.05) were found among canopy area, canopy volume, basal area and stem diameter.

Figure 4

Stemflow volume during study period in relation to shrub morphological metrics: (a)–(f) refer to the total amount of stemflow collected by individual shrubs; (g)–(i) refer to the total amount of stemflow collected by individual stems.

Figure 4

Stemflow volume during study period in relation to shrub morphological metrics: (a)–(f) refer to the total amount of stemflow collected by individual shrubs; (g)–(i) refer to the total amount of stemflow collected by individual stems.

Morphological metrics clearly affected stemflow funnelling efficiencies for shrubs within the same species (Figure 5). Funnelling ratio decreased at first and then became constant after a threshold value with increasing projected canopy area (Figure 5(a)), shrub volume (Figure 5(b)), basal area (Figure 5(c)) and stem diameter (Figure 5(h)), respectively, being fitted by an exponential decay function. Funnelling ratio was negatively correlated with PAI (Figure 5(d)), shrub height (Figure 5(e)) and number of stems (Figure 5(f)), respectively, although the relations were not statistically significant for the former two parameters; it increased with stem angle (Figure 5(g)), although the relation was rather weak (R2 = 0.08). No clear relationship was found between funnelling ratio and stem length (Figure 5(i)).

Figure 5

Mean event funnelling ratio in relation to shrub morphological metrics: (a)–(f) refer to the funnelling ratio of individual shrubs; (g)–(i) refer to the funnelling ratio of individual stems. Error bar indicates confidence interval (a = 0.05) of the associated mean value.

Figure 5

Mean event funnelling ratio in relation to shrub morphological metrics: (a)–(f) refer to the funnelling ratio of individual shrubs; (g)–(i) refer to the funnelling ratio of individual stems. Error bar indicates confidence interval (a = 0.05) of the associated mean value.

DISCUSSION

Stemflow volume represents the quantity of stemflow flux. In our study, stemflow volume increased with some shrub size metrics such as canopy area, canopy volume, basal area and stem diameter (Figure 4), and significant positive Pearson correlations (r > 0.7, P < 0.05) were found among these metrics. This indicates that smaller shrubs generate lower quantities of stemflow than larger shrubs, which is supported by studies from forested ecosystems that larger trees within the same species are inclined to generate higher volumes of stemflow due to large canopies, i.e., rainwater collecting area (e.g., Levia et al. 2010; Honda et al. 2015). However, this does not mean that larger trees/shrubs profit more from stemflow than smaller ones, because basal area, not canopy area, is the true area over which stemflow is delivered to the soil (Herwitz 1986; Germer et al. 2010; Levia et al. 2011). Although stemflow volume is an important metric for calculating watershed inputs and overall budgets, it is unreasonable to use this metric to assess the hydrologic implications of stemflow by leaving out the stemflow-affected area (Germer et al. 2010). Also, this unstandardized metric is unsuitable for use in hydrologic models (Levia & Germer 2015). This metric thereby inevitably fails to compare the funnelling efficiencies among individual plants. Alternatively, the stemflow funnelling ratio is an effective quantitative tool to assess how efficient a tree/shrub is at funnelling water to its base, because it identifies the true delivering area (shrub basal area) of stemflow and allows researchers to readily compare results with other studies and achieve meaningful cross-site comparisons (Llorens & Domingo 2007; Levia & Germer 2015).

In our study, funnelling ratio differed considerably among individual shrubs within the same species (Table 3), with a mean funnelling ratio range of 37–123 (CV = 33%), suggesting that the shrub basal area of C. korshinskii can receive 37–123 times the amount of rainwater by stemflow as compared to an open area. This fell in the range of studies from arid and semi-arid environments (Navar 1993; Llorens & Domingo 2007; Li et al. 2008; Yang et al. 2008; Wang et al. 2011). For example, Li et al. (2009) reported an average funnelling ratio of 77.8 and 48.7 for shrubs H. scoparium and S. psammophila, respectively; Garcia-Estringana et al. (2010) observed that the average funnelling ratio for nine Mediterranean shrubs was 104 with a range of 30–250. Stemflow is thus considered as an essential water resource available for growth and survival of shrubs, which may further contribute to the stability of shrub communities in water-limited arid desert environments. Moreover, we found an exponential decay relationship between funnelling ratio and some shrub size metrics (Figure 5). This suggests that smaller shrubs gain access to rainfall via higher funnelling ratio than larger shrubs. Our findings thus highlight the importance of morphological metrics on stemflow yield, and in particular, small shrubs might profit from sporadic rainfall events. Small shrubs generally lack deep developed roots to draw water from deep soil layers, whereas small shrubs are more efficient at funnelling rainwater than their large counterparts. This is of eco-hydrological importance for the survival and growth of juvenile shrubs in drought conditions of arid desert ecosystems. Moreover, according to Kidron (2015), each millimetre of rain infiltrates to ∼10–11 mm in sand; it is therefore expected that long-term mean precipitation (191 mm) in our study area should result in an infiltration of ∼191–210 cm. Funnelling ratio is an important parameter for a better understanding of shrub-related infiltration (Levia & Germer 2015). In our study, shrubs had a high funnelling ratio with small shrubs possessing higher funnelling efficiencies than larger ones, it is therefore reasonable to estimate that the infiltration under shrub canopies should be greater than in bare sand soil; it is, however, difficult to precisely estimate infiltration depth due to complex root structure and the great difference between stemflow infiltration process and vertical rainfall infiltration process (Liang et al. 2009).

Not surprisingly, stemflow volume increased significantly (P < 0.01) with rainfall depth for all studied shrubs (Figure 2). For funnelling ratio, it first showed an increased tendency with rainfall depth until a threshold value around 12 mm and then began to decline (Figure 3). With increasing rainfall depth, a general increase in funnelling ratios (e.g., Figure 3(b)) can be found in the literature, whereas deviations exist as to this relationship after exceeding a certain point of rainfall depth. For co-occurring evergreen broadleaved trees (Cyclobalanopsis multinervis and Cyclobalanopsis oxyodon) and deciduous broadleaved trees (Fagus engleriana and Quercus serrata var. brevipetiolata) in a subtropical forest, Su et al. (2016) found that funnelling ratio displayed a tendency to increase with incident rainfall up to a rainfall depth of 50 mm, above which funnelling ratio remained relatively constant despite increasing rainfall. In a northern hardwood stand in southern Ontario under growing season conditions, Carlyle-Moses & Price (2006) found that stemflow funnelling ratios increased with increasing rainfall depth in a linear fashion until a peak (17.4 mm) was reached with funnelling ratios declining with greater rainfalls. Similar results as Carlyle-Moses & Price (2006) have been found for desert shrubs in China with a threshold value of 11 mm for C. korshinskii and 17 mm for Reaumuria soongorica and Tamarix ramosissima (Li et al. 2008), and for a juniper (Juniperus virginiana, redcedar) woodland and a tallgrass prairie with a threshold value of 35 mm in the south-central Great Plains of the US (Zou et al. 2015). According to Carlyle-Moses & Price (2006), a greater proportion of a tree becomes saturated with increasing rainfall input and thus the area contributing to stemflow increases until a threshold rainfall input that saturates all areas capable of producing stemflow is reached; once this threshold rainfall depth has been exceeded, funnelling ratios would be expected to decrease since the numerator in Equation (1) will be limited by the maximum contributing area of the tree, while the denominator will increase in proportion with the rainfall input.

CONCLUSIONS

Both stemflow volume and funnelling ratio differed considerably among individual shrubs within the same species. Greater incident rainfalls resulted in larger event stemflow volumes, while funnelling ratio seems to be less affected by rainfall depth. Smaller shrubs generate a lower quantity of stemflow, while gaining access to rainfall via higher funnelling ratio than larger shrubs, suggesting that small shrubs may have a favourable soil water condition around the shrub base for survival and growth when competing with larger ones in water-limited arid desert environments. Investigation into soil moisture variations related to the stemflow induced by shrubs of varying sizes is called for in the future to obtain direct and more convincing evidence of differential intra-specific stemflow funnelling efficiencies on the growth of shrubs.

ACKNOWLEDGEMENTS

This study was supported by the National Natural Science Foundation of China (grant nos. 41530750, 41501108, 41371101) and the CAS ‘Light of West China’ Program. The authors would like to express their gratitude to the associate editor and three anonymous reviewers for their constructive comments in improving the manuscript.

REFERENCES

REFERENCES
Aguiar
,
M. R.
&
Sala
,
O. E.
1999
Patch structure, dynamics and implications for the functioning of arid ecosystems
.
Trends in Ecology and Evolution
14
,
273
277
.
Carlyle-Moses
,
D. E.
&
Price
,
A. G.
2006
Growing-season stemflow production within a deciduous forest of southern Ontario
.
Hydrological Processes
20
,
3651
3663
.
Garcia-Estringana
,
P.
,
Alonso-Blázquez
,
N.
&
Alegre
,
J.
2010
Water storage capacity, stemflow and water funneling in Mediterranean shrubs
.
Journal of Hydrology
389
,
363
372
.
Garner
,
W.
&
Steinberger
,
Y.
1989
A proposed mechanism for the formation of fertile islands in the desert ecosystem
.
Journal of Arid Environments
16
,
257
262
.
Germer
,
S.
,
Werther
,
L.
&
Elsenbeer
,
H.
2010
Have we underestimated stemflow? Lessons from an open tropical rainforest
.
Journal of Hydrology
395
,
169
179
.
Herwitz
,
S. R.
1986
Infiltration-excess caused by stemflow in a cyclone-prone tropical rain-forest
.
Earth Surface Processes and Landforms
11
,
401
412
.
Honda
,
E. A.
,
Mendonca
,
A. H.
&
Durigan
,
G.
2015
Factors affecting the stemflow of trees in the Brazilian Cerrado
.
Ecohydrology
8
,
1351
1362
.
Huang
,
J.
,
Yu
,
H.
,
Guan
,
X.
,
Wang
,
G.
&
Guo
,
R.
2015
Accelerated dryland expansion under climate change
.
Nature Climate Change
6
,
166
171
.
Levia
,
D. F.
,
Van Stan
,
J. T.
,
Mage
,
S. M.
&
Kelley-Hauske
,
P. W.
2010
Temporal variability of stemflow volume in a beech-yellow poplar forest in relation to tree species and size
.
Journal of Hydrology
380
,
112
120
.
Levia
,
D. F.
,
Van Stan
,
J. T.
,
Siegert
,
C. M.
,
Inamdar
,
S. P.
,
Mitchell
,
M. J.
,
Mage
,
S. M.
&
McHal
,
P. J.
2011
Atmospheric deposition and corresponding variability of stemflow chemistry across temporal scales in a mid-Atlantic broadleaved deciduous forest
.
Atmospheric Environment
45
,
3046
3054
.
Li
,
X. R.
2012
Eco-hydrology of Biological Soil Crusts in Desert Regions of China
.
Higher Education Press
,
Beijing
,
China
(in Chinese)
.
Li
,
X. R.
,
Xiao
,
H. L.
,
He
,
M. Z.
&
Zhang
,
J. G.
2006
Sand barriers of straw checkerboards for habitat restoration in extremely arid desert regions
.
Ecological Engineering
28
,
149
157
.
Li
,
X. Y.
,
Liu
,
L. Y.
,
Gao
,
S. Y.
,
Ma
,
Y. J.
&
Yang
,
Z. P.
2008
Stemflow in three shrubs and its effect on soil water enhancement in semiarid loess region of China
.
Agricultural and Forest Meteorology
148
,
1501
1507
.
Li
,
X. Y.
,
Yang
,
Z. P.
,
Li
,
Y. T.
&
Lin
,
H.
2009
Connecting ecohydrology and hydropedology in desert shrubs: stemflow as a source of preferential flow in soils
.
Hydrology and Earth System Sciences
13
(
7
),
1133
1144
.
Martinez-Meza
,
E.
&
Whitford
,
W. G.
1996
Stemflow, throughfall and channelization of stemflow by roots in three Chihuahuan desert shrubs
.
Journal of Arid Environments
32
,
271
287
.
Mauchamp
,
A.
&
Janeau
,
J. L.
1993
Water funnelling by the crown of Flourensia cernua, a Chihuahuan Desert shrub
.
Journal of Arid Environments
25
,
299
306
.
Noy-Meir
,
I.
1973
Desert ecosystems: environment and producers
.
Annual Review of Ecology and Systematics
4
,
25
51
.
Reynolds
,
J. F.
,
Stafford Smith
,
D. M.
,
Lambin
,
E. F.
,
Turner
,
B. L.
,
Mortimore
,
M.
,
Batterbury
,
S. P. J.
,
Downing
,
T. E.
,
Dowlatabadi
,
H.
,
Fernandez
,
R. J.
,
Herrick
,
J. E.
,
Huber-Sannwald
,
E.
,
Jiang
,
H.
,
Leemans
,
R.
,
Lynam
,
T.
,
Maestre
,
F. T.
,
Ayarza
,
M.
&
Walker
,
B.
2007
Global desertification: building a science for dryland development
.
Science
316
,
847
851
.
Rietkerk
,
M.
&
Van de Koppel
,
J.
2008
Regular pattern formation in real ecosystems
.
Trends in Ecology and Evolution
23
,
169
175
.
Schlesinger
,
W. H.
&
Pilmanis
,
A. M.
1998
Plant-soil interactions in deserts
.
Biogeochemistry
42
,
169
187
.
Schwärzel
,
K.
,
Ebermann
,
S.
&
Schalling
,
N.
2012
Evidence of double-funneling effect of beech trees by visualization of flow pathways using dye tracer
.
Journal of Hydrology
470
,
184
192
.
Swaffer
,
B. A.
,
Holland
,
K. L.
,
Doody
,
T. M.
&
Hutson
,
J.
2014
Rainfall partitioning, tree form and measurement scale: a comparison of two co-occurring, morphologically distinct tree species in a semi-arid environment
.
Ecohydrology
7
,
1331
1344
.
Tongway
,
D. J.
,
Valentin
,
C.
&
Seghieri
,
J.
2001
Banded Vegetation Patterning in Arid and Semiarid Environments: Ecological Processes and Consequences for Management
.
Springer Science & Business Media
,
New York
,
USA
.
Van Stan
,
J. T.
,
Siegert
,
C. M.
II
,
Levia
,
D. F.
&
Scheick
,
C. E.
2011
Effects of wind-driven rainfall on stemflow generation between codominant tree species with differing crown characteristics
.
Agricultural and Forest Meteorology
151
,
1277
1286
.
Wang
,
X. P.
,
Wang
,
Z. N.
,
Berndtsson
,
R.
,
Zhang
,
Y. F.
&
Pan
,
Y. X.
2011
Desert shrub stemflow and its significance in soil moisture replenishment
.
Hydrology and Earth System Sciences
15
,
561
567
.
Wang
,
X. P.
,
Zhang
,
Y. F.
,
Wang
,
Z. N.
,
Pan
,
Y. X.
,
Hu
,
R.
,
Li
,
X. J.
&
Zhang
,
H.
2013
Influence of shrub canopy morphology and rainfall characteristics on stemflow within a revegetated sand dune in the Tengger Desert, NW China
.
Hydrological Processes
27
,
1501
1509
.
Whitford
,
W. G.
,
Anderson
,
J.
&
Rice
,
P. M.
1997
Stemflow contribution to the ‘fertile island’ effect in creosotebush, Larrea tridentata
.
Journal of Arid Environments
35
,
451
457
.
Xiao
,
Q.
,
McPherson
,
E. G.
,
Ustin
,
S. L.
,
Grismer
,
M. E.
&
Simpson
,
J. R.
2000
Winter rainfall interception by two mature open-grown trees in Davis, California
.
Hydrological Processes
14
,
763
784
.
Yang
,
Z. P.
,
Li
,
X. Y.
,
Liu
,
L. Y.
,
Wu
,
J. J.
,
Hasi
,
E. D.
&
Sun
,
Y. L.
2008
Characteristics of stemflow for sand-fixed shrubs in Mu Us sandy land, Northwest China
.
Chinese Science Bulletin
53
,
2207
2214
.
Zhang
,
Y. F.
,
Wang
,
X. P.
,
Hu
,
R.
,
Pan
,
Y. X.
&
Zhang
,
H.
2013
Stemflow in two xerophytic shrubs and its significance to soil water and nutrient enrichment
.
Ecological Research
28
,
567
579
.
Zhang
,
Y. F.
,
Wang
,
X. P.
,
Pan
,
Y. X.
&
Hu
,
R.
2016b
Variations of nutrients in gross rainfall, stemflow, and throughfall within revegetated desert ecosystems
.
Water, Air, & Soil Pollution
227
,
1
17
.
Zou
,
C. B.
,
Caterina
,
G. L.
,
Will
,
R. E.
,
Stebler
,
E.
&
Turton
,
D.
2015
Canopy interception for a tallgrass prairie under juniper encroachment
.
PLoS ONE
.
10
,
http://dx.doi.org/10.1371/journal.pone.0141422
.