Co-variation of fine-root distribution with vegetation and soil properties along a revegetation chronosequence in a desert area in northwestern China

Catena 151 (2017) 16–25

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Co-variation of fine-root distribution with vegetation and soil properties along a revegetation chronosequence in a desert area in northwestern China Yong-Le Chen a,b, Zhi-Shan Zhang a,b,⁎, Lei Huang a, Yang Zhao a, Yi-Gang Hu a, Peng Zhang a, Ding-Hai Zhang a,b,c, Hao Zhang a a Shapotou Desert Research and Experimental Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou 730000, People's Republic of China b University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, People's Republic of China c College of Natural Sciences, Gansu Agricultural University, 1 Yingmen Village, Lanzhou 730070, People's Republic of China

a r t i c l e

i n f o

Article history: Received 18 June 2016 Received in revised form 9 November 2016 Accepted 8 December 2016 Available online xxxx Keywords: Moving sand dunes Revegetation Desert steppe Sand-binding dunes Vegetation change Soil properties

a b s t r a c t This study investigated the changes in the distributions of fine roots and explored their responses to changes in vegetation and soil properties along a 46-year revegetation chronosequence in a desert area in northwestern China. Fine roots and soil samples at depths of 0–3.0 m soil profile were obtained from revegetated sand-binding areas and compared with those from moving sand dunes, natural undisturbed vegetated dunes, and a desert steppe. The soil physicochemical properties in the top 0.8 m layer were analyzed, and the soil water contents at depths of 0–3.0 m soil profile were measured. Redundancy and regression analyses were conducted to explore the relationships between fine roots, vegetation and soil properties. Both the cumulative fine-root length and mass in the 0–0.4 m layer and throughout the 0–3.0 m profile increased along the revegetation chronosequence, and those of the 1.0–3.0 m layer increased up to 29 years and then decreased. Additionally, the proportion of fine roots in the 0–0.4 m layer increased and the proportion of fine roots from 1.0–3.0 m decreased along the revegetation chronosequence. The fine-root length in 0–0.4 m layer was mainly influenced by herbaceous cover, while the fine-root mass at depth of 0–3.0 m was affected by shrub cover and biomass. The amounts of fine soil particles, soil organic carbon, and total nitrogen were the main edaphic factors that influenced the distribution of fine roots. The fine-root length and mass in the 0–0.4 m layer were weakly and positively correlated with soil water contents, while those in the 1.0–3.0 m layer had strong negative relations with the soil water contents in corresponding layers. Our results demonstrated that the fine-root distribution in revegetated sand dunes was regulated by the succession of the vegetation-soil system after revegetation. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Fine roots play a crucial role in the exchange of materials and energy flow between plants and soil (Casper and Jackson, 1997; Waisel et al., 2002), and the distribution of fine roots with depth is among the most

Abbreviations: BSCs, Biological soil crusts; MSD, Moving sand dunes; R20, Sandbinding dunes revegetated in 1990 (20 years old); R29, Sand-binding dunes revegetated in 1981 (29 years old); R46, Sand-binding dunes revegetated in 1964 (46 years old); Ref, Undisturbed naturally vegetated sand dunes; Ste, Desert steppe; SWC, Soil water content; FRLD, Fine-root length density per cubic meter (m m−3); FRMD, Fine-root mass density per cubic meter (kg m−3); FRL, Fine-root length per square meter (m m−2); FRM, Fine-root mass per square meter (m m−2). ⁎ Corresponding author at: Shapotou Desert Research and Experimental Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou 730000, People's Republic of China. E-mail address: [email protected] (Z.-S. Zhang).

http://dx.doi.org/10.1016/j.catena.2016.12.004 0341-8162/© 2016 Elsevier B.V. All rights reserved.

relevant aspects that influence water, carbon, and nutrient fluxes (Jackson et al., 1997; Norby and Jackson, 2000; Schenk and Jackson, 2002). Generally, the distribution of fine roots in a certain area results from the combined influences of climate, vegetation and soil (Schenk and Jackson, 2005). For instance, plants in water-limited ecosystems often present deep rooting and have relatively large root systems (Canadell et al., 1996; Chapin et al., 1993; Schenk and Jackson, 2002), particularly in coarse-textured soils in which soil water and nutrients are regularly scarce (Collins and Bras, 2007; Wilcox et al., 2004). Currently, changes in vegetation are mainly characterized by shifts between woody and herbaceous species, and associated soil changes are ongoing in water-limited ecosystems (Sala and Maestre, 2014). Studies of the potential consequences of such changes under certain climate conditions on root distributions are urgently needed. Changes in plant life forms typically alter the rooting depth and biomass of fine roots (Canadell et al., 1996; Jackson et al., 1996,

Y.-L. Chen et al. / Catena 151 (2017) 16–25

2000). A study by Jackson et al. (2002) indicated that the rooting depths increased by at least 2 m from the initial depth following the invasion of woody plants into a grassland. Other studies have also shown that fine-root biomass in shallow soil layers after woody encroachments exceeded (Hibbard et al., 2001) or was no different than (Bai et al., 2009) the fine-root biomass in the shallow soil layers of semiarid grasslands. Consequently, limited available data has led to unclear and sometimes controversial depictions of the responses of fine-root distributions to changes in vegetation (Barger et al., 2011). Modifications in the distribution of fine roots are closely linked to the vertical changes of soil conditions in soil profiles (Schenk, 2005). The soil texture (Cable et al., 2008) and soil water content (SWC) (Cheng et al., 2009) have frequently been identified as important factors that regulate fine-root distribution patterns. Fine-textured soils favor fine-root distributions due to their greater water holding capacity (Peng et al., 2015; Sperry and Hacke, 2002). Additionally, fine-textured soils tend to increase soil nutrient availability and create nutrient-rich patches of soil (Ettema and Wardle, 2002), which further stimulates the accumulation of fine roots (Hodge, 2006). The positive responses of fine roots to soil nitrogen have been reported in numerous studies and are intensified when soil nutrients are limiting (Burton et al., 2000; February and Higgins, 2010; Imada et al., 2013; West et al., 2004). Wilcox et al. (2004) showed both positive and negative relationships between fine roots and soil moisture at the same site. In addition, Zhou and Shangguan (2007) reported a poor relationship between soil nitrogen and fine roots. Overall, the optimal fine-root distribution profile was shaped by the soil texture and soil nutrient availability. In the arid and semi-arid regions of China, revegetation is an effective method for controlling desert encroachment and desertification. For example, revegetation has been consistently implemented since the 1950s to stabilize moving sand dunes (MSD) and avoid sand burial of the Baotou-Lanzhou Railway, which lies along the southeastern fringe of the Tengger Desert. According to long-term monitoring data, significant changes in vegetation and soil properties occurred in our study area after revegetation of MSD (Li et al., 2007b). Ten initially planted shrub species grew rapidly and reached a peak cover of 33% after 15 years, but only three of the ten shrub species maintained a cover of 9% after 40 years. The number of naturally inhabited herbaceous species increased to 14 after 40 years, and their cover fluctuated and depended closely on precipitation. In addition, pedogenic processes occurred on the dune surface with the changes in revegetation. These processes were characterized by the accumulation of fine-textured aeolian deposits with high nutrient concentrations as well as the formation and development of biological soil crusts (BSCs) (Duan et al., 2004; Li et al., 2007a). Because of its high water-holding capacity, the topsoil intercepted most of the rainfall, which results in a lack of rainwater infiltration into the deep soil layers below a depth of 0.4 m (Wang et al., 2008). Similarly, the nutrient concentrations in the upper soil layers mainly resulted from nutrient-rich dustfall and nitrogen fixation by BSCs (Duan et al., 2004). Notably, the SWC in the deep layer gradually decreased because of the high rate of evapotranspiration by deep rooting shrubs and the low rainwater infiltration rate (Li et al., 2004a, 2014). Thus, the succession of the soil system increases soil water and nutrient availability in the shallow soil layer and decreases the soil water availability in the deep layers (Li et al., 2014). The revegetation chronosequence offers an opportunity to explore the responses of fine-root distributions to changes in vegetation and soil during revegetation. The objectives of this study are to characterize the vertical distribution of fine roots along the revegetation chronosequence and to investigate the relationships between fine-root distributions and vegetation and soil properties. Three revegetation sites (established in 1964, 1981, and 1990) were selected to conduct a rigorous investigation of fine roots relative to vegetation and soil properties, and one undisturbed

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naturally vegetated sand dune was considered as a reference site. One site on MSD was selected to represent the initial stage before revegetation, and one site on an adjacent desert steppe was considered to represent a future stage of revegetation. Previous studies indicated that the population of common shallow-rooted herbaceous species increased, the population of deeply rooted shrub species decreased, the topsoil conditions improved, and the availability of soil water in the shallow and deep soil layers was reversed following revegetation (Duan et al., 2004; Li et al., 2004b, 2007b, 2014; Wang et al., 2006). Based on these knowledge of the revegetation changes in our study area, we hypothesized that 1) the vertical fine-root distribution would generally shift toward shallow rooting along the 46-year revegetation chronosequence and that 2) the fine-root distribution would be closely linked to variations in the vegetation and soil properties.

2. Materials and methods 2.1. Site description This study was conducted along the southeastern fringe of the Tengger Desert in northwestern China, which is characterized as a zone of transition from a sandy desert to a steppe. Within this transition zone, six study sites were set up from the east to the west (Fig. 1). Because of the great depth of groundwater (N 80 m) and its unavailability to vegetation, precipitation is the sole source of soil water in the study area (Li et al., 2004a). Four sites are located near the Shapotou Desert Research and Experimental Station (here after abbreviated as SDRES) (Fig. 1). Three of these sites are located on sand-binding dunes that were revegetated in 1964, 1981 and 1990 (corresponding to revegetation ages of 46, 29 and 20 years and abbreviated as R46, R29, and R20, respectively, when the study was conducted in 2010.) Another site is located on a moving sand dune (hereafter abbreviated as MSD). SDRES (lat 37°32′ N, long 105°02′ E, at an elevation of 1300 m AMSL) is located in a typical temperate desert region. According to a 50-year (1956–2005) meteorological record, the annual mean temperature at SDRES is 10 °C, and the mean January and July temperatures are −6.9 and 24.3 °C, respectively. The annual mean wind velocity is 2.9 m s−1, and the annual mean precipitation is 186 mm, with 80% of the precipitation falling between May and September. Large and dense reticulated barchans sand dune chains are typical of the landscape, and the soils are mainly aeolian sandy soils (FAO/UNESCO, 1974). MSD are dominated by the shrub species Hedysarum scoparium Fisch. & C. A. Mey. and the herbaceous species, Agriophyllum squarrosum (L.) Moq., which provide a cover less than 1%. In the 1950s, a 16-km-long, 500-m-wide rain-fed revegetation protective system was established along both sides of the Baotou-Lanzhou Railway to stabilize MSD and prevent desert encroachment. Xerophytic shrubs were planted following the establishment of the sand barrier. Subsequently, revegetation was further developed in 1964, 1981, and 1990. After long-term revegetation efforts, a diversified ecosystem composed of planted xerophytic shrubs (mainly Artemisia ordosica Krasch., Caragana korshinskii Kom., and H. scoparium), naturally inhabited herbaceous species (Eragrosti spoaeoides P. Beauv., Bassia dasyphylla (Fisch. & et Mey.) O. Kuntze, Corispermum patelliforme Iljin, Salsola ruthenica Iljin, and Aristida adscensionis L.), and BSCs evolved on the sand-binding dunes. A control site (used as the reference and hereafter abbreviated as Ref) lies in the vegetated protective system of the railway (lat 37°27′ N, long 104°46′ E, at an elevation of 1570 m AMSL) and is characterized by undisturbed natural vegetation (Fig. 1). This site has the same landscape and soil type as the sites near SDRES, and the predominant plant species include the shrubs Ceratoides lateens (J. F. Gmel.) Reveal et Holmgren, A. ordosica, C. korshinskii, and Oxytropis aciphylla Ledeb. and the herbaceous plants Artemisia capillaries Thunb., Allium mongolicum Regel, S. ruthenica, Stipa breviflora Griseb., Cleistogenes

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Y.-L. Chen et al. / Catena 151 (2017) 16–25

songorica (Roshev.) Ohwi, Scorzonera divaricata Turcz., and Iris tenuifolia Pall. The last site (lat 37°30′ N, long 104°26′ E), is located at an elevation of 1655 m (AMSL) in a desert steppe (hereafter abbreviated as Ste). This site is 60 km from SDRES and contains a local climax community within the transitional zone (Fig. 1). The landscape at this site is characterized as a piedmont alluvial fan, and the soil is classified as orthic sierozem (FAO/UNESCO, 1974). The zonal vegetation is primarily composed of semi-shrubs, including Salsola passerina Bunge, Reaumuria soongarica (Pall.) Maxim. and the associated Nitraria tangutorum Bobrov and Sympegma regelii Bunge. The dominant herbs are Artemisia frigida Willd., A. capillaris, Allium polyrhizum Turcz. ex Regel, Lepidium apetalum Willd., and Plantago minuta Pall. 2.2. Experimental design In August 2010, two parallel 150-m line transects were established at each site. The two transects were separated by a distance of 2 m and were used to collect root and soil samples, respectively. Each line transect included 10 sample points separated by approximately 15 m. The line transects at the MSD, R20, R29, R46, and Ref sites on the sand dunes were arranged perpendicularly across topographic types (all including dune crests, hollows between dunes, and the windward and leeward slopes), whereas the line transects at the Ste site were positioned along the piedmont alluvial fan with a gentle slope. Along each line transect, topographic types were used as blocks. Specifically, four blocks were located within each site, and at least two sample points were located within each block. To facilitate statistical analysis, the sampling points at the Ste site, which had smooth topography, were divided into four blocks, with two to three sampling points in each block. 2.3. Vegetation survey A 10 m × 10 m plot was delineated around the center of each root sampling point to survey the shrubs. Three 1 m × 1 m quadrats were randomly laid out within each plot to survey the herbs. Overall, 10 plots were surveyed for the shrubs and 30 quadrats were surveyed for the herbs at each site. At each plot, the density of shrubs was surveyed, and plant height and crown diameters were measured from the east to the west and from the north to the south for each individual shrub. The projected crown area of each individual shrub was calculated as an ellipse by using the crown diameter, and the crown volume was calculated as a spheroid by using the plant height and crown diameters. The amount of shrub cover at each plot was calculated using the cumulative projected crown area of all the shrubs, and the shrub biomass was estimated using a pre-built regression between the individual shrub biomass and crown volume. In each quadrat, the density of herbs was surveyed and the cover was estimated by a frame with small grids (0.1 m × 0.1 m). Then, all of the herbaceous species in the quadrats were mowed and weighed after drying for 48 h in an oven at 65 °C to obtain biomass values. The results of the vegetation survey are summarized in Table 1. 2.4. Fine root sampling and measurement A homemade soil auger (0.1 m inner diameter and 0.2 m height) with a flat edge was used to collect soil samples for fine roots in 0.1 m increments to a depth of 3.0 m. At the Ste site, because of the presence of compacted red clay and gravel in the 2.0 m layer, it was difficult to obtain

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all of the samples from the 0–3.0 m profiles. The shallowest depth for an individual sampling point was 2.0 m, and 251 samples were obtained at the Ste site. In addition, 300 samples were obtained from each of the other five sand dune sites. Because of the presence of dry and loose sandy soils, water was applied to retrieve soil samples, as described by Zhang et al. (2009). Soil samples were taken to the laboratory and then immediately frozen at −20 °C for 48 h in a freezer to facilitate separation of the roots and soil particles (Samson and Sinclair, 1994). Next, the samples were wet sieved through a mesh screen with a 0.3 mm aperture to separate the roots from the soils. To remove any remaining soil particles, the roots were soaked in a 0.015 M NaOH solution for 2 h. The fine roots were not identified as specific plant species because the focus of this study was to investigate all of the fine roots from the vegetation within a specified site. The roots were individually separated into fine (b1 mm) and coarse roots (≥1 mm) following the methods of previous studies (Zhang et al., 2008, 2009) and into live and dead roots based on the empirical approach of inspecting the color and resilience of each root (Joslin et al., 2006; Trumbore, 2006; Vogt and Persson, 1991; Zhang et al., 2008). Generally, the live roots were light in color, elastic, and smooth, whereas the dead roots were brown or black, easily broken, and sometimes hollow. The roots were then digitized as TIFF images (10 M, 300 dpi) using a scanner equipped with additional lighting (transparency unit). The lengths of the fine roots were determined by performing image analysis using WinRHIZO (Reg 2009c; Regent Instruments Inc., Canada) software, and the root mass was determined using an electronic balance (precision 10−4 g) after oven-drying for 48 h at 65 °C. 2.5. Soil sampling and analysis A regular soil auger (AMS, Inc., USA) was used to collect soil samples for the SWC measurements (0.1 m to 0.4 m, and then 0.2 m to 3.0 m) and physicochemical properties analyses (at 0–0.1, 0.1–0.2, 0.2–0.3, 0.3–0.4, 0.4–0.6, and 0.6–0.8 m layers). The soil samples used in the SWC measurements were immediately transported to the laboratory to measure the gravimetric SWC using the oven-drying method (oven-dried at 105 °C for 48 h), and the volumetric SWC was obtained from the soil bulk density. To determine the soil physicochemical properties, soil samples were obtained from the same layer of two adjacent sample points and were mixed to form a composite sample; thus, five replicates of each type of soil sample were collected from six layers, and a total of 30 samples were collected at each site. The soil samples were then air dried and passed through a 1-mm-mesh sieve. A mixed soil-water ratio of 1:5 was used to determine the pH and electrical conductivity by using a calibrated pH meter (PHS-4, China) and a portable conductivity meter (Cole-Parmer Instrument Company, USA), respectively. The soil organic carbon content was determined using the dichromate oxidation method (Bao and Shi, 2005), and the total nitrogen content was analyzed determined using a Kjeltec System 1026 distilling unit (Tecator A B, Höganäs, Sweden). The hydrofluoric acid digestion method was used to measure the total phosphorus content (Bao and Shi, 2005), and the pipette method (Bao and Shi, 2005) was used to determine the soil particle size distribution. The field capacity and wilting point were measured using a laboratory pressure plate extractor (CAT 1600, Soil moisture Equipment Company, Santa Barbara, CA, USA) and then transformed into a volumetric unit (m3 m−3). The soil water availability was calculated by subtracting the wilting point from the field capacity. The soil bulk density was determined using a specialized soil auger and a cutting ring (0.05 m in depth and diameter) with a known weight to obtain intact soil samples. These samples were dried at 105 °C for 48 h and then weighed.

Fig. 1. Geographical locations and landscapes of the study sites. The yellow points in A and C indicate the six sites; the green points in A, B, and C indicate the Shapotou Desert Research and Experimental Station (SDRES); the red dashed line indicates the Baotou-Lanzhou railway. A: location of the Ste site, Ref site, and SDRES along the Baotou-Lanzhou railway at the edge of the Tengger Desert. B: location of SDRES on the map of China. C: map of the four sand dunes sites (MSD, R20, R29 and R46) near SDRES. D: landscape of the MSD site. E: landscape of the revegetation areas (R20, R29 and R46). F: landscape of the Ref site. G: landscape of the Ste site. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Y.-L. Chen et al. / Catena 151 (2017) 16–25

Table 1 Vegetation characteristics of the six study sites. Values represent the means (four replicates) and standard error. Biomass indicates aboveground biomass. “\” denotes that no shrubs were found at the MSD site. Shrubs

Herbs

Total

Site

Density (100 m−2)

Cover (%)

Biomass (kg m−2)

Density (100 m−2)

Cover (%)

Biomass (kg m−2)

Cover (%)

Biomass (kg m−2)

MSD R20 R29 R46 Ref Ste

\ 21.3 ± 5.16 25.1 ± 5.89 22.7 ± 7.92 37.0 ± 0.670 232 ± 28.8

\ 20.0 16.1 16.3 21.4 28.2

\ 0.0647 ± 0.00869 0.0899 ± 0.0171 0.0731 ± 0.0141 0.117 ± 0.0137 0.237 ± 0.0203

5.44 25.7 19.0 12.1 23.2 20.6

0.551 ± 219 7.08 ± 0.539 4.82 ± 0.557 4.12 ± 0.731 6.56 ± 0.753 4.95 ± 0.550

2.18E-04 ± 1.03E-04 0.343 ± 0.101 0.561 ± 0.117 0.348 ± 0.0525 0.100 ± 0.0145 0.106 ± 0.00969

0.551 ± 0.219 27.1 ± 2.71 21.0 ± 2.37 20.4 ± 3.55 28.0 ± 0.483 33.2 ± 2.63

2.18E-04 ± 1.03E-04 0.407 ± 0.0931 0.651 ± 0.126 0.421 ± 0.0444 0.217 ± 0.0262 0.340 ± 0.0294

± ± ± ± ±

2.78 2.43 3.95 0.989 2.32

± ± ± ± ± ±

2.58 5.15 8.19 3.82 3.76 3.60

2.6. Data processing For each root core, the fine-root length density (FRLD) and fine-root mass density (FRMD) per unit volume of soil were calculated. Then, the soil profile was divided into three layers (0–0.4, 0.4–1.0, and 1.0–3.0 m) and the cumulative fine-root length (FRL) and mass (FRM) per unit ground area in each layer and in the entire 0–3.0 m profile were calculated. The cumulative FRL and FRM in each layer and in the entire 0– 3.0 m soil profile and the proportions of the FRL and FRM in each soil layer relative to the entire 0–3.0 m soil profile were also calculated. Because the topographic types of the sand dune sites (the MSD, R20, R29, R46, and Ref site) did not affect the fine-root densities within each site (Table S1), one-way ANOVA was used to test for differences in the cumulative and proportional FRL and FRM in the 0–0.4, 0.4–1.0, and 1.0–3.0 m layers and the entire 0–3.0 m profile among the six sites. Tukey's post hoc test was used for multiple comparisons. The variables were checked using the Shapiro-Wilk test for normality and Levene's test for homogeneity. The data were transformed to follow normal distributions when needed. A significance level of P b 0.05 was used. The FRLD and FRMD per cubic meter of each sample point were fitted with the following equation developed by Gale and Grigal (1987): Y ¼ 1−β d where Y is the cumulative root fraction (ranging from 0 to 1) to a certain depth d (m), and β is the numerical index of the root distribution and is defined as the extinction coefficient (high values of β indicate a greater

proportion of fine roots with increasing depth). Additionally, one-way ANOVA was used to compare the means of β among the six sites. A redundancy analysis was used to explore how the fine-root distributions varied with the soil properties. Moreover, linear, exponential, and logarithmic equations were used to quantify the relationships between fine roots and the vegetation and soil properties. The best fit was selected based on the R2, P-value, and Akaike information criterion (AIC) (Akaike, 1974; Burnham and Anderson, 2002). Statistical analyses were conducted using SPSS16.0 (SPSS Inc., Chicago, IL, USA) and Canoco 4.5 (Microcomputer Power, Ithaca, NY, USA), and the figures were generated using Origin 8.0 (Origin Lab, Northampton, MA, USA).

3. Results 3.1. Fine-root distribution along the revegetation chronosequence Both the live FRLD and FRMD (per cubic meter) decreased with increasing soil depth, except for at the MSD site (Fig. 2). The fine-root distribution at the MSD site showed no notable tendency, and the root density peaked in the 0.6–0.7 and 2.4–2.5 m soil layers. The vertical distribution of the dead FRLD and FRMD were similar to the live FRLD and FRMD (Fig. S1). The fitted results of the live FRLD showed that the rooting depths from the MSD to Ste site generally decreased, although the β values were not different. The Ref site had the shallowest rooting profiles (average β was 0.958), and the average β values at the MSD, R20, R29, R46, and Ste sites were 0.983, 0.977, 0.985, 0.976 and 0.972,

Fig. 2. Vertical distribution of the live fine-root length density (FRLD, m m−3) and mass density (FRMD, kg m−3). The original data were transformed by ln(x + 1) to ensure that the fineroot densities of each site exhibit the same graduation along the horizontal axis. Values represent the means (four replicates) and standard errors.

Y.-L. Chen et al. / Catena 151 (2017) 16–25

respectively. Significant differences were also not observed among the β values of the fitted live FRMD at the six sites (P N 0.05) (Table S2). The cumulative live FRL and FRM (per square meter) in the 0–3.0 m soil profile at the MSD site were significantly lower than the cumulative live FRL and FRM at the other five sites. Moreover, the cumulative live FRL and FRM at the sand dune sites increased significantly along the revegetation chronosequence (from MSD to Ref) (P b 0.01). The cumulative dead FRL and FRM increased to their maximum values at the R29 site but decreased thereafter (Fig. 3, Table 2, and Table S3). By dividing the soil profiles into three continuous soil layers (0–0.4, 0.4–1.0, and 1.0–3.0 m), we found that the cumulative live FRL and FRM in the shallow soil layer (0–0.4 m) accounted for most of the root system within the entire soil profile, and gradually increased along the revegetation chronosequence as well as their proportion (Fig. 3). The peak values of the proportions of live FRL and FRM in the shallow layer (0– 0.4 m) occurred at the Ref (73.3%) and Ste. (78.3%) sites. The cumulative live FRL and FRM in the 0–0.4 m layer at the Ref site was significantly higher than the cumulative live FRL and FRM at the MSD and R20 sites. The cumulative live FRL and FRM in the middle layer (0.4–1.0 m) remained essentially constant, and only the cumulative live FRL and FRM at the MSD site were lower than of the cumulative live FRL and FRM at the other five sites. The proportions of the live FRL and FRM in the deep layer (1.0–3.0 m) generally decreased from the MSD to the Ste. sites, whereas the cumulative live FRL and FRM generally increased to the R29 site and then decreased (Table 2, Table S3). 3.2. Relationships between the fine roots and vegetation properties Fitting the vegetation properties with fine-root densities was successful for the sand dune sites but not for the Ste site. The cumulative live FRL in the 0–0.4 m layer increased significantly with increasing vegetation cover, especially with increasing herbaceous cover (R2 = 0.518), while the cumulative live FRL in the 0–3.0 m profile was positively related to shrub cover (R2 = 0.754). A weaker correlation was also observed between the proportion of the cumulative FRL in the 0–0.4 m soil layer and the total vegetation cover (R2 = 0.272). The cumulative FRM in the 0–0.4 m layer and throughout the 0–3.0 m soil profile was significantly related to the shrub biomass (R2 = 0.484 and R2 = 0.639). The total biomass was closely related to the proportion of cumulative FRM in the 0– 0.4 m soil layer (Fig. 4, Tables S4 and S5).

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Table 2 Results of the one-way ANOVA for the cumulative live/dead FRL and FRM in three layers (0–0.4, 0.4–1.0, and 1.0–3.0 m) and 0–3.0 m profile, and proportions of the three layers accounted in the 0–3.0 m profile. Original data were transformed to meet the assumptions of the ANOVA. 0–0.4 m

Live FRL Live FRM Dead FRL Dead FRM Proportion of live FRL Proportion of live FRM Proportion of dead FRL Proportion of dead FRM

0.4–1.0 m

1.0–3.0 m

0–3.0 m

F

P

F

P

F

P

F

P

11.6 4.22 6.50 5.74 3.04

b0.001 b0.05 b0.01 b0.01 b0.05

1.63 5.44 22.8 18.1 1.01

0.226 b0.01 b0.001 b0.001 0.458

4.58 4.78 9.50 11.6 3.57

b0.05 b0.05 b0.01 b0.001 b0.05

4.93 7.00 24.0 11.3

b0.01 b0.01 b0.001 b0.001

2.42

b0.05

3.84

b0.05

0.893

0.518

3.81

b0.05

10.4

b0.001

6.87

b0.01

5.92

b0.01

16.0

b0.001

7.28

b0.01

0–0.4 m: proportion of live FRL, Johnson transformation. 0.4–1.0 m: live FRM, square root; dead FRM, square root. 1.0–3.0 m: live FRL, square root; dead FRL, square root; dead FRM, square root; proportion of live FRL, square root; proportion of live FRM, square root; proportion of dead FRM, square root.

3.3. Relationships between the fine roots and soil properties According to the redundancy analysis, 11 soil properties accounted for 88.8 and 10.8% of the correlations with fine roots on the first and second axis, respectively. All of the fine-root parameters were located on the right of the first axis. The soil organic carbon, total nitrogen and wilting point have the greatest arrow lengths along the first axis and were found to be main factors that affect the fine-root distribution. In addition, the field capacity, total phosphorus content, soil water availability and fine particle content positively affected the fine-root distribution, whereas the soil coarse particles and the SWC affected the fine-root distribution in completely opposite directions. Electrical conductivity and pH were more influential on the second axis, especially for the FRL (Fig. 5 and Table S6). The regression analyses further confirmed the relationships between the fine-root densities and soil physicochemical properties. The

Fig. 3. Stack columns showing the cumulative live and dead fine-root length (FRL, m m−2) and mass (FRM, kg m−2) and the corresponding proportions of the three soil layers (0–0.4, 0.4– 1.0, and 1.0–3.0 m) in the 0–3.0 m profile. F and P values were obtained from the ANOVA results from the mean comparisons of the FRL and FRM (0–3.0 m) of each site. Values represent the means (four replicates) and standard errors.

Y.-L. Chen et al. / Catena 151 (2017) 16–25

Proportion of FRL (%)

0-0.4 m 2500 R2=0.518 2000 P<0.001 1500 1000 500 0 0

2

4

6

8

0-0.4 m 2 80 R =0.272 P<0.05 60 40 20 0

Proportion of FRM (%)

FRM (kg m -2)

0-0.4 m 0.5 R2=0.484 0.4 P<0.001 0.3 0.2 0.1 0.0 0.06

0.09

0.12

Shrub biomass (kg m-2)

1500 1000 500

6

12

18

24

30

36

0

Total cover (%)

0.6

0.03

0-3.0 m 2500 R2=0.754 2000 P<0.001

0 0

10

Herbaceous cover (%)

0.00

3000

100

0.15

5

10

15

20

25

30

Shrub cover (%)

100

0.6

80

FRM (kg m -2)

FRL (m m -2)

3000

FRL (m m -2)

22

60 40 0-0.4 m R2=0.469 P<0.001

20 0 0.0

0.2

0.4

0.6

0.8

0-3.0 m 0.5 R2=0.639 0.4 P<0.001 0.3 0.2 0.1 0.0

1.0

Total biomass (kg m-2)

0.00

0.03

0.06

0.09

0.12

0.15

Shrub biomass (kg m-2)

Fig. 4. Best fitting relationships between the vegetation properties (cover, and biomass) and cumulative live FRL and FRM in the 0–0.4 m and 0–3.0 m soil profiles at the sand dune sites (MSD, R20, R29, R46, and Ref). Black lines denote the best fits. The values of the vegetation properties and fine roots are representative of four replicates. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

FRL and its proportions at the sand dune sites were significantly affected by the soil particle size, and their higher values corresponded to greater levels of fine particles (R2 = 0.621 and R2 = 0.521). The FRL and its proportions also increased linearly with increasing soil organic carbon (R2 = 0.682 and R2 = 0.441). The proportion of FRM was significantly affected by soil fine particle content (R2 = 0.461) and the increasing soil organic carbon (R2 = 0.488), while only a weaker relation was found between the FRM and soil fine particle content (R2 = 0.138). For the fine roots at the Ste. site, the FRL was significantly related to the wilting point (R2 = 0.865) and total nitrogen content (R2 = 0.958), and the proportion of roots was as significantly related to the soil field capacity (R2 = 0.863) and organic carbon content (R2 = 0.725). In addition, the FRM and its proportions were significantly related to the wilting point (R2 = 0.944), total nitrogen content (R2 = 0.855), field capacity (R2 = 0.920) and soil organic carbon content (R2 = 0.752), respectively (Fig. 6, Tables S7 and S8).

Weak positive relationships were observed between the cumulative FRL and FRM with SWC in the 0–0.4 m layer (R2 = 0.069 and R2 = 0.026), and weak negative relationships were detected between the cumulative FRL and FRM and the SWC in the 0.4–1.0 m layer (R2 = 0.082 and R2 = 0.081). Furthermore, strong negative relationships were found between the cumulative FRL and FRM and the SWC in both the 1.0–3.0 m layer and the entire 0–3.0 m profile (Table S9). 4. Discussion The study area experienced significant changes in vegetation and soil properties during conversion from barren MSD to stable sand-binding revegetation. The revegetation chronosequence provided us with an opportunity to investigate the distributions of fine roots following revegetation and to determine how the distribution of fine roots varies with vegetation and soil properties (Li et al., 2011; Wilcox et al., 2004). 4.1. Effects of revegetation on the fine-root distribution

Fig. 5. Biplot of the redundancy analysis of the relationships between the soil properties and the live FRL and FRM in each layer of the 0–0.8 m profile (0–0.1, 0.1–0.2, 0.2–0.3, 0.3–0.4, 0.4–0.6, and 0.6–0.8 m). PFRL: proportion of the fine-root length in each layer in the 0–0.8 m profile; PFRM: proportion of the fine-root mass in each layer in the 0–0.8 m profile; SWA: soil water availability; CPs: coarse particles; FPs: fine particles; FC: field capacity; WP: wilting point; EC: electronic conductivity; SOC: soil organic carbon; TN: total nitrogen in soil; TP: total phosphorus; SWC: soil water content.

In our study, the cumulative live FRL and FRM in the shallow layers (0–0.4 m) continuously increased along the revegetation chronosequence and were highest (including their proportions) at the Ref site (Fig. 3). However, the cumulative live FRL and FRM in the deep layers (1.0– 3.0 m) increased, peaked at the R29 site, and then decreased to minimum values at the Ref site. These variations in the fine-root distribution corresponded well with the changes in vegetation composition after revegetation. Specifically, deep-rooted shrubs thrived and then retreated while herbaceous species gradually and naturally inhabited the dunes (Li et al., 2007b). The results verified our first hypothesis and were consistent with the model of Schenk (2008), in which roots are mainly distributed in the shallowest soil layer and only extend to deeper layers to fulfill evapotranspiration demands. Collins and Bras (2007) also found that the rooting depth was driven by the depth of water infiltration in the absence of groundwater. In fact, the deep SWC was reduced to approximately 1% in the current revegetation areas, with ages of 40 years (Li et al., 2004a, 2014), and such conditions could be further intensified by reducing rainwater infiltration to the deep soil layer because of the development of surface soils and the formation of BSCs (Wang et al., 2007). In our study area, the soil water in the deep soil layers was most likely overconsumed by the sand-binding revegetation, and groundwater was unavailable because it

Y.-L. Chen et al. / Catena 151 (2017) 16–25

Sand dunes

FRL (m m-2)

1500 1200

R2=0.682 P<0.001

900 600 300 0 0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Steppe 630 2 0-0.1 m R =0.682 540 0.2-0.3 m P<0.001 450 0.4-0.6 m 360 270 180 90 0.18 0.21 0.24 0.27 0.30 0.33

FRM (kg m-2)

Soil organic carbon (g kg-1) 0.30 0.24 0.18

R2=0.138 P<0.05

Proportion of FRL (%) Proportion of FRM (%)

36 24

93 94 95 96 97 Coarse particles (%)

0.21

98 99 100

R2=0.944 P<0.001

0.020

0.024

0.028

0.032

0.036

0.225

0.250

Wilting point (m3 m-3) 35

R2=0.521 P<0.001

28

R2=0.863 P<0.001

21 14 7 90

36

0.28

0.00 91 92

0

48

0.35

0.07

12

60

0.36 0.39 0.42

0.14

90

48

0.1-0.2 m 0.3-0.4 m 0.6-0.8 m

Total nitrogen (g kg-1)

0.12 0.06 0.00

60

23

91 92

93 94 95 96 97 Coarse particles (%)

98 99 100

0.150

0.175

0.200 3

-3

Field capacity (m m )

R2=0.488 P<0.01

48 36

24

24

12

12

0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 -1

Soil organic carbon (g kg )

0

R2=0.920 P<0.001

0.150

0.175

0.200

0.225

0.250

Field capacity (m3 m-3)

Fig. 6. Best fitting relationships between the soil physicochemical properties and the live FRL and FRM in the 0–0.8 m soil profiles (0–0.1, 0.1–0.2, 0.2–0.3, 0.3–0.4, 0.4–0.6, and 0.6–0.8 m) at the sand dune sites and the Ste. site. The values of FRL and FRM represent the means (four replicates) and standard errors. The values of the soil properties were calculated from five replicates. Black lines denote the best fits. Detailed fitting results are available in Tables S7 and S8. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

was too deep (N80 m) (Li et al., 2004a). However, the availability of soil water and nutrients in the surface soils increased following revegetation, which provided advantageous conditions for fine-root growth (Hodge, 2004; Li et al., 2007a). These factors led to the distribution of fine roots in shallow soil layers, which may represent an optimal strategy for the establishment of vegetation on sand dunes.

4.2. Co-variations between fine roots and vegetation properties In this study, only three of the ten initially planted shrub species (A. ordosica, C. korshinskii, and H. scoparium) remained, with a total cover of 9% after 40 years since the sand-binding shrubs were planted on the MSD (Li et al., 2007b). Meanwhile, fine roots moved toward the shallow soil layer (0–0.4 m) following the degradation of the shrubs synusium and the development of naturally inhabited herbaceous species. The vegetation properties were positively correlated with the cumulative FRL in the shallow layer along the 46-year revegetation chronosequence (Fig. 4). These results demonstrated synchronal variations in the vegetation and fine-root distribution.

The fine-root distributions in water-limited ecosystems are subjected to shifts between woody and herbaceous species (Gill and Burke, 1999; Gwenzi et al., 2011; Jackson et al., 2000) and respond to shifts at the community and individual scales. Therefore, it is necessary to examine the individual fine-root distribution characteristics of key species. The roots of the shrub A. ordosica are usually distributed within shallow soil layers, whereas the roots of C. korshinskii and H. scoparium are usually distributed in deeper soil layers (Zhang et al., 2008, 2009). Furthermore, self-renewal of the population of C. korshinskii is difficult because it has a low seed-setting rate and a large seed size, which hinders burying and germination and is often impacted by disease and insect risks (Liu et al., 1991). H. scoparium primarily flourishes on moving and semi-fixed dunes because of its exceptional clonal growth characteristics, which allow the roots to distribute widely within shallow and deep soil layers. However, such advantages can be restrained by gradual topsoil compaction and the development of BSCs (Liu et al., 1991). Consequently, the deep-rooted shrubs C. korshinskii and H. scoparium will retreat and maintain low but stable cover and densities. However, A. ordosica has a high seed production capacity, and its seedlings can tolerate denudation by strong winds as well as burial in sand.

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Y.-L. Chen et al. / Catena 151 (2017) 16–25

The most striking trait of A. ordosica is the intermittent germination of its small seeds during the rainy season (Li et al., 2010). A recent study noted that the rooting depth and root distribution characteristics of A. ordosica tend to readily respond to precipitation in the shallow soil layers (Li et al., 2014). Thus, these characteristics help improve the population of A. ordosica. Overall, shifts in shrub species facilitate shallow rooting patterns for sand-binding vegetation. The cover of the herbaceous species fluctuated with precipitation and gradually increased during the succession of the sand-binding vegetation, and a relatively stable species richness was achieved after 40 years of revegetation (Li et al., 2007b). These changes profoundly altered the fine-root distribution patterns of the sand-binding vegetation. A. squarrosum is a pioneer and dominant annual herbaceous species that thrives on MSD. By rooting deeply to obtain available soil water (Nemoto and Lu, 1992; Wang et al., 1998), A. squarrosum can survive in extremely unstable and sandy habitats, where it benefits from the deep infiltration of rainwater on MSD. Because of the sparse community structure of H. scoparium and A. squarrosum, the MSD site had the lowest root biomass and the highest proportion of roots in the deep soil layers (Fig. 3). After revegetation on the MSD, most of the properties of the soils in the shallow layer improved, providing conditions that supported shallow-rooted herbaceous species (Schenk and Jackson, 2002). For instance, herbaceous species naturally inhabited, including annual E. poaeoides, B. dasyphylla, C. patelliforme, S. ruthenica, and E. gmelinii and perennial S. divaricata and S. glareosa. These herbaceous species used shallow soil water and nutrients and increased the number and distribution of fine roots in the shallow layers. 4.3. Co-variations between fine roots and soil properties In the present study, redundancy analysis and regression analyses indicated that the fine-root densities were strongly and positively correlated with the total nitrogen content, soil organic carbon content and wilting point (Fig. 5 and Fig. 6). In addition, positive relationships were observed between the FRL and FRM and the total phosphorus content, field capacity and soil water availability. Together with the development of surface soils along the revegetation chronosequence (Duan et al., 2004), our results demonstrated the well-known co-variation between fine roots and soil properties (Schenk, 2005) following revegetation. Previous studies have shown that greater levels of total nitrogen and phosphorus are directly beneficial for the growth of fine roots and that high soil organic carbon contents indirectly facilitate the growth of tine roots by increasing the soil water holding capacity (Boldt-Burisch et al., 2013; Craine et al., 2003; Hodge, 2004). Moreover, fine roots exhibit particular plasticity when faced vertically heterogeneous soil properties (Hodge, 2004; Robinson, 1994). Evidence from a study conducted by Ferrante et al. (2014) also suggested that nutrient availability in soil surface layers promotes the lateral expansion of plant roots rather than the growth of roots to deeper soil layers. In fact, soil properties, including soil organic carbon content, total nitrogen content, wilting point, field capacity and soil water availability, are significantly influenced by the soil texture (Hook and Burke, 2000; Kaye et al., 2002). Both empirical and modeling studies demonstrated that fine-textured soils can preserve soil organic carbon and have greater nitrogen mineralization than coarse-textured soils (Degens, 1998; Fernandez-Illescas et al., 2001; Müller and Höper, 2004). In addition, the soil texture was often considered as a driving factor that underlies the relationships between the soil hydrological features and roots (Laio et al., 2001; Porporato et al., 2002). Generally, uniformly coarse soil particles create larger pore sizes than fine particles or a mixture of particle sizes in identical bioclimatic divisions and led to a lower water holding capacity in most cases (Dexter, 2004; Fernandez-Illescas et al., 2001; Noy-Meir, 1973; Schenk and Jackson, 2002). In our study, the coarse soil texture at the MSD and R20 sites (representing the early stages of revegetation succession) likely favored rainfall infiltration into deeper soil layers (Wang et al., 2007), which encouraged deep

rooting. In contrast, the well-developed fine-textured soils had much greater available SWCs in the shallow layer at the R46 and Ref sites (Hook and Burke, 2000) and favored shallow rooting. Fine-root distributions are largely constrained by the heterogeneity of the SWC in soil profiles (Hodge, 2004; Hutchings et al., 2003; Schenk, 2006; Wilcox et al., 2004). In our study, the SWC in the 0– 3.0 m profile was negatively related with the FRL and FRM. Compared with the fine roots in the shallow layers, the fine roots in the deep layers were more sensitive to changes in the SWC (Table S9), and successful fits between the SWC and deep fine root contents were primarily observed in the sand dunes. These results were inconsistent with the classical root-water relationship principle, which states that higher SWC often leads to greater fine-root densities (Hodge, 2004; Pregitzer et al., 1993). This inconsistency was probably caused by the consumption of limited soil water by the dense fine-root system. The sandy soils had a higher proportion of fine-roots in the deep layers (1.0–3.0 m), which was consistent with observations from previous studies (Jackson et al., 2000; Schenk and Jackson, 2002). In this study, the deep fine roots at the MSD and R20 sites during the early stages of revegetation tended to rely on the soil water in the deep layers rather than on the ephemeral input of water to the shallow soil layers. Although the steppe site (Ste) had higher SWC in the shallow and deep layers, the fine roots at this site responded negatively to increasing SWC. Similar results were also found among different shrubs within the same study site in the Mojave Desert (Wilcox et al., 2004). Therefore, higher SWC does not always correspond with higher soil water availability and greater fine roots systems. 5. Conclusions This study investigated the distributions of fine roots along a 46-year revegetation chronosequence in a desert area. Our results demonstrated that fine roots accumulated faster in shallow layers than in deeper layers and the proportion of fine roots in the shallow layer increased while the proportion of fine roots in the deep layer decreased along the revegetation chronosequence. Fine-root length in the 0–0.4 m layer were dependent on the herbaceous cover, while the fine-root mass in the entire 0–3.0 m profile was affected by the shrub biomass. The soil fine particle content, soil organic carbon content, and total nitrogen content were the main edaphic factors that influenced the fineroot distribution. Fine-root length and mass in the 0–0.4 m layer were weakly and positively related to SWC, while those in the 1.0–3.0 m layer had strong positive relations with SWC in the corresponding layers. The fine-root distribution data obtained from this long-term revegetation succession can be used as base line data for the establishment and protection of revegetated areas in arid and semiarid regions. Acknowledgements This study was funded by the National Natural Sciences Foundation of China (41471434 and 41530746). We sincerely appreciate three anonymous reviewers, whose constructive comments and suggestions were used to revise the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.catena.2016.12.004. References Akaike, H., 1974. A new look at the statistical model identification. IEEE Trans. Autom. Control 19, 716–723. Bai, Y., Colberg, T., Romo, J.T., McConkey, B., Pennock, D., Farrell, R., 2009. Does expansion of western snowberry enhance ecosystem carbon sequestration and storage in Canadian prairies? Agric. Ecosyst. Environ. 134, 269–276. Bao, S., Shi, R., 2005. The Analysis of Soil Agriculturalization. China Agriculture Press, Beijing.

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