Structural characteristics of the moss (bryophyte) layer and its underlying soil structure and water retention characteristics

The influence of the moss layer on soil structure and soil water retention is not well understood. Therefore, this study aims to investigate the changes in soil structure and soil water retention under moss layer and to reveal the influencing factors of these changes. 3D networks of moss layer and soil macropores were quantified using CT scanning and image analysis techniques, and soil water retention characteristics were explored through soil water retention curves (SWRCs) and VG model. The length densities of the soil macropores under the thin moss and thick moss layers were approximately 2.7 and 1.6 times higher than that under no moss cover. The soil water retention under the thin and thick moss layers were greater than those under no moss cover, with the highest plant-available water capacity under the thin moss layer. The maximum water-holding capacity of the moss layer was significantly positively correlated with the field water-holding capacity of the soil and negatively correlated with the equivalent diameter of the macropores, while the storage capacity of the moss layer was significantly and negatively correlated with the maximum effective water content of the soil. The field capacity (FC) and permanent wilting point (PWP) were significantly and positively correlated with the soil organic matter. The effect of the moss layer on water retention may be mainly realized by influencing the pore distribution and organic matter accumulation. The moss layer had a positive ecohydrological effect on soil water retention and even water conservation in forest soils.


Introduction
Bryophytes, a group of land plants that include mosses, liverworts and hornworts, are broadly distributed among terrestrial ecosystems (Hedenäs 2007;Medina et al. 2011), where they play important functional roles (Cornelissen et al. 2007;Lindo and Gonzalez 2010).The moss layer plays important roles in influencing soil physical properties (Soudzilovskaia et al. 2013), forest regeneration (Soudzilovskaia et al. 2011), ecosystem water budgets (Bond-Lamberty et al. 2011), evaporation (Kidron and Tal 2012), seedling germination (Briggs and Morgan 2011) and mineral cycles (Gundale et al. 2011).Hrbáčeka et al. (2020) highlighted that the correct assessment of moss type and its water retention can be of great importance in the accurate modelling of active layer thickness variation and its feedback on climate change.Silva et al. (2019) indicated that development of moss cover would increase delay runoff response time, and a moss cover above 67% significantly reduced sediment and organic matter losses by 65% and 34% respectively.Gao et al. (2020) found that moss-dominated biocrusts could control water erosion through two tightly correlated mechanisms, decreasing erodibility and enhancing cover of the soil surface, and the increasing moss cover appears to induce a cascade of changes in soil organic matter, texture and organic carbon.Kidron et al. (2022) reported that biocrusts increased surface and subsurface temperatures, increased evaporation, subsequently negatively affected the growth and survival of vascular plants.Currently, relatively little is known about the relationships among structural characteristics of the moss layer and its underlying soil structure and water retention characteristics.
Soil structure is the three-dimensional arrangement of solid soil constituents and voids across different scales (Rabot et al. 2018), resulting from interactions of biotic and abiotic factors, including climate, mineral composition, organic matter, roots, fungal hyphae, soil fauna, and tillage.It regulates water retention and infiltration, gaseous exchanges, soil organic matter and nutrient dynamics, root penetration, and susceptibility to erosion (Elliott and Coleman 1988).X-ray computed tomography (CT) has been introduced in recent years to quantify soil pores at a much higher resolution than previous methods, such as dye tracing, spectral image analysis and soil thin sectioning (Katuwal et al. 2015;Larsbo et al. 2014;Vogel et al. 2010).Hu et al. (2020) linked 3-D soil macropores and root architecture to near saturated hydraulic conductivity of typical meadow soil types in the Qinghai Lake Watershed, northeastern Qinghai-Tibet Plateau.Hu et al. (2022) identified water flow through non-root soil macropores and along roots using CT scanning in shrub-encroached grassland.The above-mentioned studies indicate that X-ray CT is an appropriate method to quantify the root architecture and soil structure in undisturbed soil cores.
Soil water retention (SWR) is a vital hydrological property of soils, which is important in exploring soil water availability, storage capacity and groundwater recharge (Ebel 2012).Soil water retention curves (SWRCs) describe the relationship between soil water contents (SWC) and matric potential, which are useful for exploring SWR.SWR is influenced by many factors, including soil physical properties (Otalvaro et al. 2016), soil chemical properties (Yang et al. 2014;Zhou et al. 2020), roots (Gao et al. 2017), slope aspect (Geroy et al. 2011), and wet-dry cycles (Fu et al. 2019).However, the influence of the moss layer on SWR remain poorly understood due to difficult quantification of moss and soil structure.Kalhoro et al. (2018) explored the effect of land use on soil water retention through SWRCs on the Loess Plateau in northern China.Gao et al. (2021) explored SWR changes in a shrub-encroached grassland using SWRCs.Accordingly, it is urgent to understand changes in SWR under the moss layer using SWRCs.
In the arid northwestern region of China, the Qilian Mountains are a key nourishing and cherished water source area, feeding the Shiyanghe, Shulehe, and Heihe rivers.Qinghai spruce (Picea crassifolia Kom.) is the dominant tree species of natural forests in this region, growing on shaded or semi-shaded slopes with elevations of 2500 to 3300 m (Zhao et al. 2018;Wang et al. 2019;Wan et al. 2020).In recent decades, the area of P. crassifolia plantation has been growing to restore mountain vegetation (He et al. 2012).Mosses are the main ground cover species in the Qilian Mountains, with Abietinella abietina being the dominant species, with a cover of over 85% and up to 100% when it is not disturbed by human activity (Wang et al. 2017).The biomass of the entire ground cover layer of the Qinghai spruce forest on the northern slope of Qilian Mountain was 24.34 t/hm 2 , of Vol.: (0123456789) which 24.18 t/hm was moss, accounting for 99.30% of the ground cover layer and 9.95% of the total biomass of the Qinghai spruce forest in the Qilian Mountains (Wang et al. 2017).Liu et al. (2010) analysed the moss layer of Qinghai spruce forests in the Qilian Mountains and demonstrated that soil water evaporation was both less and more stable in mossy woodlands than in non-mossy woodlands.We expect that high water retention in the soil is closely related to 3D structure of moss and underlying soil, so it is crucial to explore the structural characteristics of the moss layer and its underlying soil structure and water retention characteristics using SWRCs and X-ray CT.
Based on the fact that moss can store much water and contain high soil organic matter, we hypothesized that (1) the soil macropores under moss layers were better than those under no moss cover, (2) soils under a moss layer have high soil water retention than soils under no moss cover, and (3) the effect of the moss layer on SWR may be mainly realized through influencing the pore distribution and organic matter accumulation.Our specific objectives were to (1) explore the effects of the moss layer on soil structure and SWR and (2) identify the dominant factors influencing soil structure and SWR characteristics under the moss layer.

Study area and plot description
This study was carried out on Ladong Mountain (38°10′N, 100°19′E, 2760 m asl), located in Qilian County, Qinghai Province, northeastern China.The climate of the area results from the influence of both alpine and continental climates.The mean annual temperature is − 1.5 ℃, with a maximum monthly temperature of 11.0 ℃ in July and a minimum monthly temperature of − 14.5 ℃ in January.The average annual precipitation is 600.7 mm, while the mean annual evaporation is approximately 1050 mm (Wang et al. 2017).The soils are grey-cinnamon soils that are equivalent to Andisols according to the USDA Soil Taxonomy (Soil Survey Staff 2014).P. crassifolia is the dominant tree species in the area, and there is a moss layer on the soil surface.A. abietina is the dominant species in the moss layer, while Hypnum plumaeforme and Cirriphyllum piliferum are rarely distributed. 1 m × 1 m quadrats were used to analyze species richness and biomass.Species richness was defined as the total number of species occurring per unit area in the quadrats (Peng et al. 2013).
Three 2 m × 2 m plots were established in open terrain to represent areas with no moss cover, a thin moss layer, and a thick moss layer (Fig. 1).The mean thicknesses of the thin moss layer and thick moss layer are 2.67 cm and 7.10 cm, respectively, which were measured several times with a ruler to take the average.The plots with thin and thick moss layers were approximately 4 m apart due to the distribution of light, and the non-mossy plots were approximately 10 m from the plots with thin and thick moss layers.Mosses are shade-loving plants, so no moss plots appeared in places with strong light.The canopy densities of the plots with no moss, thin moss, and thick moss were 30%, 50%, and 65%, respectively.The canopy densities were recorded on paper in the field in each 25 m × 25 m plot and were then digitized using ArcGIS 9.3 to estimate the area percentage and the spatial distribution of the canopy densities (Peng et al. 2013).

The moss layer sampling
The moss layer was gently lifted from the soil surface and then put into polyvinyl chloride (PVC) cylinders with an inner diameter of 7.5 cm.The upper and lower ends of the cylinder were fixed with plugs, and 6 replicates were taken from each plot.Soil profiles (1 m in depth and 1 m in width) in the plots with no moss cover, thin moss layer, and thick moss layer were then excavated.

Soil core and column sampling
378 undisturbed soil core samples (6 replicates for each section) were collected using PVC rings (7.5 cm in diameter and 1 cm in height) according to 0-10 cm, 10-20 cm and 20-30 cm, and 6 replicates were collected in each layer for the measurement of SWRCs.Soil samples were wrapped with plastic films to prevent water evaporation and weighed before storage.Three undisturbed soil cores collected with cutting rings (5 cm in diameter and height) were used for the measurement of soil bulk density and gravimetric water content, which followed the oven-dried method (Klute 1986).
A total of 12 intact soil columns (7.5 cm in diameter and 30 cm in length) were excavated from the three plots.Four replicates were randomly sampled from each plot (Fig. 1).The soil columns were collected with PVC cylinders, and the detailed extraction procedure is described in a previous publication (Hu et al. 2022).The undisturbed moss layer and soil cores were used for CT scanning.

Soil physicochemical analysis sampling
Disturbed soil samples were collected at depths of 0-30 cm and intervals of 10 cm along the same profile to measure the soil particle composition and organic carbon content.The sand content (50-2000 μm) was measured through sieving, and the silt (2-50 μm) and clay (< 2 μm) contents were measured through the pipette method (Klute 1986).The soil organic carbon (SOC) contents were determined by high temperature combustion using a carbon nitrogen analyser (CN802, VELP, Italy; Pella and Colombo 1973).The soil physiochemical characteristics are listed in Table 1.

The moss layer properties
The moss samples in the natural state were weighed to obtain the wet weight of the moss layer (m).After that, the moss layer samples were put into nylon mesh bags, and the mesh bags were completely immersed in water for 24 h.Then, the samples were taken out and hung in the air for about 5 min, and weighed immediately when no water drops fell down to obtain the saturation weight of the moss layer (m s ), and finally the moss layer samples were put into the oven to dry at 65 ℃ until constant Where A is the natural water holding rate of the moss layer (%), A max is the maximum water holding rate of the moss layer (%), m is the wet weight of the moss layer in its natural state (g), and m 0 is the dry weight of the moss layer (g).
The moss layer in its original form in the PVC pipe was placed on the soil sieve, and the rainfall was simulated according to the gradient of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 25, 30 mm, and the interception of rainfall (p) of the moss layer under different rainfall amounts was measured.
Where P is the retention rate of moss layer at a certain rainfall (%), V p is the retention volume of moss layer at a certain rainfall (ml), and V is the rainfall volume (ml).

CT scanning and image processing
A nanoVoxel-3000 X-ray CT (Sanying Precision Instruments Company) at an energy level of 120 kV and 200 μA was used to scan the moss layer samples.The exposure time and resolution were 0.15 s and 40 μm, respectively.A Geoscan-200 X-ray CT (Sanying Precision Instruments Company) at energy levels of 150 kV and 250 μA was used to scan the soil core samples.The exposure time and resolution were 0.1 s and 68 μm, respectively.The images of the moss layer and soil cores were analysed using Avizo Fire 9.0 (FEI 2016).Firstly, a cylindrical cropping tool was applied to obtain a region of interest (ROI) and remove disturbances along the margin of the samples.Secondly, according to the intensity histogram, the thresholds of the moss layer and soil macropores were obtained to segment the moss layer from the soil matrix (Katuwal et al. 2015).The moss layer and soil macropore networks were then visualized by volume rendering.Soil macropore characteristics were further calculated, including the macroporosity of the ROI (volume of macropores/volume of the ROI), macroporosity of each slice (volume of macropores in the slice/volume of the slice), macropore number, macropore volumetric size, and macropore surface area.After skeletonization, the macropore number density ( d (m −3 )), node density ( n (m −3 )), length density ( l (km m −3 )), mean tortuosity (τ), mean angle (θ) and mean equivalent radius were calculated.
After skeletonization, macropore number density ( d , m −3 ) was defined as the number of macropore networks ( N m ) in a unit volume (V): A node refers to an intersection at which two macropore branches are connected.The number of nodes in each macropore network was recorded, and we calculated the node density ( n , m −3 ) as the number of nodes ( N n ) in a unit volume (V): The length density ( l , km m −3 ) was also analysed as the total actual macropore length ( L t ) in a unit vol- ume (V) (Luo et al. 2010).
The mean tortuosity (τ) was calculated as ratio of the total actual macropore length (L t ) to total straightline distance (L l ) of all the macropores in a certain volume (Luo et al. 2010).The mean tortuosity means the ratio of total pore length to that of the shortest possible path.
where i is the index of a macropore branch and n is the total number of macropore branches.
The inclination of a macropore branch was characterized by an angle (θ) away from vertical direction.The mean angle was calculated as: Assuming that all macropores are cylindrical, its mean equivalent hydraulic radius (mm) was calculated by the total volume V t and total length L t of the macropore:

SWRCs and parameters
The SWRCs were obtained using an exactor (1500F2, Soilmoisture Ltd., USA) at room temperature (20 ℃).Soil samples were first placed on a pressure plate, and then water was added to the plate so that the soil samples reached saturation in 24 h.A total of 8 suction values (0, 0.3, 0.5, 1, 3, 5, 10, and 15 bar) were then applied to the saturated samples (Kalhoro et al. 2018;Reatto et al. 2008).After the equilibrium time (i.e., the point at which no water escaped from the exactor), the soil samples were weighed and then ovendried at 105 °C for 24 h to measure the gravimetric water content at each suction level.SWRCs were fitted by the VG model, and can illustrate the relationship between matric suction and the volumetric water content.The plant-available water (PAW), which directly reflects how much soil water can be used by plants, was calculated as the difference between the field capacity (FC) and the permanent wilting point (PWP) (Gao et al. 2021).Concomitantly, soil water storage (SWS) and plantavailable water storage (PAWS) were calculated for each 10 cm soil layer using the following equations (Wang et al. 2013) where SWS is the soil water storage (mm), PAWS is the plant-available water storage (mm), SWC is the measured soil water content (cm 3 cm −3 ), PAW is the plant-available water (cm 3 cm −3 ), ρ b is the soil bulk density (g cm −3 ), Δd is the thickness of the each soil layer (10 cm), ρ w is the water density (g cm −3 ), and UCF is a unit conversion factor (10 mm cm −1 ).
The pores were classified into three classes: micropores (< 30 μm), mesopores (30-100 μm) and macropores (> 100 μm).Microporosity was caculated as the soil water content when the pressure head was 100 cm.Mesoporosity was caculated as the soil water content between the pressure heads of 30 cm and 100 cm.Macroporosity was caculated as the difference between the saturated water content (θ s ) and the sum of mesoporosity and microporosity.

Statistical analyses
SWRCs were fitted by the VG model using the nonlinear least-square method with MATLAB R2019a (MathWorks Inc., MA, USA).All the statistical analyses were conducted using SPSS 20 (SPSS Inc., USA).Homogeneity of variances and normal distribution of the data were tested before applying the parametric methods by formula (12).Differences ( 10) between the macropore characteristics of the three plots were analysed by one-way analysis of variance (ANOVA), and differences were considered significant at the level of p < 0.05.Pearson correlations were conducted to evaluate the linkages among moss coverage, soil macropores, and soil water retention.
Where: t = critical value from the t-distribution table, MSw = mean square within, obtained from the results of the ANOVA test, n = number of scores used to calculate the means.

Characteristics of structural networks of moss layer
The moss layer was composed of a number of mosses of varying thicknesses twisted and interwoven in matlike clusters, and the structure of the moss layer was generally loose and porous, with the underlying structure being more compacted than the surface layer.
Single mosses also exhibit certain morphological and structural features: the stems are more branched and plumose, the apexes of the stems and branches become progressively more pointed and curved to varying degrees, and most of the moss plants are stout and play a skeleton-like support role in maintaining the structure of the moss layer (Fig. 2).
Figure 3 shows the characteristics of the variation in the volume densities of the thin and thick moss layers.The volume densities of the thin moss and thick moss layers were 0.086 cm 3 cm −3 and 0.141 cm 3 cm −3 respectively.There were significant differences between the volume densities of the thin and thick mosses at the p < 0.05 level.In terms of the variation in the volume density curves of mosses, both the thin and thick mosses showed a gradual increase in volume density with soil depth (Fig. 3).The volume density curves of thin moss layer showed a more moderate increase, and thick mosses showing a steeper and sudden increase in volume density in the bottom parts of the layer.
Table 2 shows the thickness, accumulation, natural water-holding rate and maximum water-holding rate of the thin mosses and thick mosses.The average thicknesses of the thin and thick mosses were 3.07 and 7.10 cm, respectively, and there were significant differences between them.The storage volume of the thick mosses was also higher than that of the thin mosses.The natural water-holding rate of the thick mosses was 208.00%, 2.08 times its own dry Fig. 2 Three-dimensional visualization of the moss layer (green denotes moss) Vol:. (1234567890) weight, which was higher than that of the thin mosses (169.92%).
Figure 4 shows changes in the interception (a) and interception percentage (b) of the moss layer with the increase in simulated precipitation.The interception of the moss layer increased with increasing rainfall for both the thin and thick moss layers, especially at depths of 0-10 mm, and remained stable at approximately 1.5 mm after 10 mm of rainfall, indicating that there is a limit to the retention capacity of the moss layer.The interception percentage of the moss layer showed the opposite trend, decreasing with increasing rainfall, with a steeper decrease in the range of 0-10 mm, from 45 to 10% for the thick moss layer and 37% to 13% for the thin moss layer, and remained stable after 10 mm of rainfall.In addition, the interception percentage of the thick mosses were higher than those of the thin mosses in the rainfall range of 0-3 mm, and higher than those of the thick mosses after 3 mm of rainfall.

Visualization and characteristics of soil macropore networks
Figure 5 shows the 3D visualization of soil macropores under no moss cover, thin moss layer and thick moss layer.The soil macropores covered with the thin moss layer were relatively more abundant, distributed throughout the entire soil profile (0-25 cm), and more  evenly distributed spatially, and more macropores were distributed laterally in the soils under the thin moss layer.However, the soil macropores under no moss cover and thick moss layer were less abundant in the deeper layers, and the macropores in the soil covered with thin and thick moss layers were more connected.
Figure 6 shows the variation in soil macroporosity with soil depth covered with no moss cover, thin moss layer and thick moss layer.The soil macroporosity decreased sharply at depths of 0-10 cm, and there was greater macroporosity in the soil covered with the thick moss layer than in the soil covered with no moss cover or the thin moss layer.The macroporosity of the soil covered with a thin moss layer fluctuated less frequently but to a greater extent.Therefore, the macroporosity of the soil covered with a thick moss layer was concentrated in the surface layer, while the macroporosity of the soil covered with no moss cover or a thin moss layer was mostly distributed in the deeper layers.
Table 3 shows the 3D parameters of soil macroporosity under no moss cover, thin moss layer and thick moss layer.The soil macroporosity, number density and surface area density of soil macroporosity under the thin moss layer were higher than those under no moss cover and thick moss layer, but there was not a significant difference in the mean equivalent diameter or mean volume among soils under no moss cover, thin moss layer and thick moss layer.The average angles of the macropores in the soil under no moss cover and a thin moss layer were 64° and 69°, respectively, which were higher than that under the thick moss layer (58°), indicating that the soil macropores under the thick moss layer more vertically distributed, while the soil macropores under the thin moss layer and no moss cover were more horizontally distributed.In addition, the length density of the macropores in the soil covered with a thin moss layer and a thick moss layer was 412.3 km m −3 , which was approximately 2.7 and 1.6 times higher than that under no moss cover.The branch density and node density of the macropores in the soil covered with a thin moss layer were higher than those in the soils under no moss cover, which was consistent with the findings for length density.
Figure 7 shows the volume percentages of soil macropores under no moss cover, thin moss layer and thick moss layer, classified by equivalent diameter, surface area and volume.In terms of equivalent diameter, soil macroporosity was distributed in all the equivalent diameter ranges, and the overall distribution was relatively homogeneous, with the no moss cover and thick moss layer having the largest volume percentages in the range of equivalent diameter > 15 mm, 27% and 53%, respectively, while soils covered with a thin moss layer had the largest volume percentages in the range of equivalent diameter 10-15 mm, 36%.In terms of surface area, the distribution of soil macroporosity varied considerably between surface area zones, with the largest volume share of soil macroporosity in the no moss cover, thin moss layer and thick moss layer all occurring in the range of surface area > 1000 mm 2 , at 69%, 76% and 70%, respectively.In terms of volume, soil macroporosity under the three moss cover conditions showed more similarities: soil macroporosity was less distributed in small volumes, with a mean value of 28% of the total volume share in the 0-0.1, 0.1-1, 1-10 and 10-100 mm 3 volume ranges, and the concentration of soil macroporosity in the 100-1000 and > 1000 mm 3 intervals, with no volume share in the volume range 100-1000 mm 3 .

Soil water retention curves and fitting parameters
Table 4 shows the fitting parameters of the SWRCs and the predictive performance of the VG model.The soils under the thin moss layer and thick moss layer at a depth of 20-30 cm exhibited 43.1% and 44.8% higher soil saturated water content than the soils under no moss cover.Among the soil layers, the n value of the soils was lowest under no moss cover, while there was no significant difference between the n value of the soils under the thin moss and thick moss layers.Table 5 shows the FC, PWP, and PAWC of the soils under no moss cover and under the thin moss layer and thick moss layer.The FC, PWP and PAWC values (0.301 cm 3 .cm−3 , 0.106 cm 3 .cm−3 , and 0.195 cm 3 .cm−3 , respectively) were higher in the soils under the thin moss layer than in those under the thick moss layer (0.243 cm 3 .cm−3 , 0.102 cm 3 .cm−3 , 0.141 cm 3 .cm−3 , respectively).The PAWC of the soil under the moss layers showed an increasing trend from the soil surface to the deeper layers.The 0-10 cm and 10-20 cm soil layers under no moss cover had the highest FC values, while the FC, PWP, and PAWC were all the lowest in the 20-30 cm soil layer under no moss cover.There was a significant difference in these parameters between the soil layers under the thin moss layer and the moss layer.Therefore, the moss layer increased the PAWC of the soils under the thin moss layer and thick moss layer.
Figure 8 displays the SWRCs of different soil depths under no moss cover, the thin moss layer and thick moss layer.For the soils under the thick moss layer, there were small differences in the SWRCs among different soil layers, and the soil water retention was the highest in the 20-30 cm soil depth.For the soils under the thin moss layer, the patterns of soil water retention in different soil layers were similar to those under the thick moss layer.However, for the soils under no moss cover, the 10-20 cm soil depth had almost 50% higher soil water retention than the 0-10 cm soil layer.Therefore, there were higher soil water retentions in the 10-20 cm and 20-30 cm soil layers than that of 0-10 cm soil layer under the thin and thick moss layers, while there was high soil water retention in the 0-10 cm soil layers under no moss.
Figure 9 shows the profile distributions of SWC under no moss cover, the thin moss layer and thick moss layer.The increase in moss thickness reduced the differences in the SWCs among the soil layers.More specifically, the difference between the SWCs of the soil under the moss layers and no moss cover was mainly present in the 0-20 cm soil layers.Additionally, the plant-available water (PAWCs) of the soils with moss cover were higher than that of the soil with no moss cover, indicating that the moss layer had a certain positive effect on improving the PAWC of the soil.The PAWCs (0.17 cm 3 cm −3 ) of soil under the thin moss layer were higher than that of soils under the thick moss layer (0.14 cm 3 cm −3 ).So, the moss layer reduced spatial  The soil water storage (SWS)and plant-available water storage (PAWS) under no moss cover, thin moss layer and thick moss layer are provided in Table 6.For the 30 cm soil profile, the soils under the thin moss layer had the highest water storage and exhibited 46% and 57% higher SWS than the soils under no moss cover or the thick moss layer, respectively.The 10-20 cm soil layer had the higher SWS than those of 0-10 and 20-30 soil layers under both no moss cover and a thin moss layer, while the 0-10 cm soil layer had the higher SWS than those of 10-20 and 20-30 cm soil layers under the thick moss layer.The soils under the thin moss layer had 51% and 110% higher PAWS than the soils under the thick moss layer and no moss cover, respectively.The soil layers with the highest PAWS were 20-30 cm, 10-20 cm, and 0-10 cm for the soils under no moss cover, the thin moss layer and the thick moss layers, respectively.The relationship between the moss layer and soil structure and soil water retention Table 7 shows the correlation between moss layer properties and soil macroporosity.The maximum waterholding rate of the moss layer was significantly and negatively correlated with the equivalent diameter of soil macropores, with a Pearson correlation coefficient of -0.847.The moss layer had a retention effect on precipitation, so higher maximum water-holding rates of the moss layer indicate less soil water infiltration, which results in a narrower water transport channel, i.e., soil macropores with smaller equivalent diameters.
Table 8 shows the correlation between moss layer properties and soil water retention characteristics.The maximum water-holding capacity of the moss layer was significantly and positively correlated with the field water-holding capacity, with a Pearson correlation coefficient of 0.865, while the storage capacity of the moss layer was significantly and negatively correlated with the maximum effective water content of the soil, with a Pearson correlation coefficient of -0.848.The effect of the moss layer on water retention may be mainly through influencing the pore distribution and organic matter accumulation, which are discussed in detail in the next section.
Table 9 shows the correlation between soil water constants and soil physicochemical properties.Soil organic matter was significantly and positively correlated with the field capacityand the permanent wilting point.

Discussion
Our results showed that, the soil macroporosity, number density and surface area density of soil macropores under the thin moss layer were higher than those under no moss cover and thick moss layer.The equivalent diameter of soil macropores was higher under the thick moss layer than under the thin moss layer.The results showed that, the maximum water-holding rate of the moss layer was significantly and negatively correlated with the equivalent diameter of soil macropores, with a Pearson correlation coefficient of -0.847.This is consistent with the fact that the maximum water-holding rate of the thin moss layer was higher than that of the thick moss layer.The studies of Borges et al. (2019) and Hu et al. (2020) showed that there was a significant and positive correlation between the soil pore length density and near-saturated water conductivity.Jarvis (2007) found that connected soil macropores accelerated water transport through soil macropore.It is expected that, water would move more readily through soil macropores under the thin moss layer than those under thick moss layer and no cover.
The results showed that FC of soils was significantly and positively correlated with maximum waterholding percentage of moss layers, and PAWC of soils was significantly and negatively correlated with accumulated amount of moss layers (Table 8).The maximum water-holding percentage of thin moss layers were higher (899.99%)than that under the thick moss layer (815.49%), and accumulated amount of thick moss layers were higher (32.94 t hm −2 ) than that under the thin moss layer (25.84 t hm −2 ).This is also consistent with soil water content along soil depths, which showed that, the moss layer improved soil water retention, and the moss cover reduced spatial differences in soil water in both the horizontal and   2023) also reported that moss-dominated biocrusts reduced runoff and sediment loss, and increased cumulative infiltration and hydraulic conductivity.The sparse and porous structural characteristics of the moss layer determine its strong ability to retain and hold water, which plays an important role in maintaining soil moisture and reducing the spatial variation of soil moisture.Kidron et al. (2022) has indicated that, when there was no rainfall, the moss layer mainly plays the role of water retention and reduces the evaporation of soil moisture, while the moss layer mainly plays the role of water holding and reduces the amount of water infiltration by secondary distribution of precipitation during rainfall.Therefore, the moss layer could reduce the spatial variation of soil moisture in both horizontal and vertical dimensions, and improve soil water retention.The moss layer was an external factor for the improvement of soil water retention.Soil pores of different sizes have distinct functions (Rabot et al. 2018).Soil micropores are classified as storage pores, which are helpful for water retention but are unable to provide enough water to meet the plant growth requirements.The microporosity under no moss cover, thin moss layer and thick moss layer were 0.34, 0.41 and 0.32 mm 3 mm −3 (Fig. 10), respectively.The soil water storage measured in the field were ranked as thin moss layer > no moss cover > thick moss layer, which indicated that micropore is important for soil water storage.So, thin moss layers enhance soil microporosity, leading to appropriate air permeability and water flow for plants by increasing the field water-holding capacity.Although macropores make up only a small part of  the soil (Jarvis 2007), air and water can flow preferentially through them.So, thick moss layers further enhance soil macroporosity, leading to an increase in subsoil flow and infiltration, causing the transport of water to the deeper soil layers, and leading to the decrease in soil water retention.The effect of the moss layer on soil water retention may be mainly through influencing the pore distribution.
The study also showed that the FC and PWP were significantly and positively correlated with the soil organic matter (Table 9).This is consistent with the results, the 0-10 cm and 10-20 cm soil layers under no moss cover had the highest FC values, while the FC and PWP were lowest in the 20-30 cm soil layers under no moss cover.The 0-10 cm and 10-20 cm soil layers under no moss cover had the highest SOM values (13.82% and 8.75%, respectively).The FC and PWP values were higher in the soils under a thin moss layer than those under a thick moss layer, while the SOM value was higher in the soils under a thin moss layer than in those under a thick moss layer.This is also consistent with other results, which showed that SOM was the important factor influencing soil water retention (Gao et al. 2021).Some studies have shown that SOM can improve water infiltration and the soil water-holding capacity by reducing the bulk density and increasing the porosity of soils (Franzluebbers 2002;Zacharias and Wessolek 2007;Naveed et al. 2014;Yang et al. 2014;Zhou et al. 2020).Ebel (2012) indicated that SOM was the main parameter influencing soil water retention.Yang et al. (2014) also pointed out SOM could control soil water retention.Therefore, SOM was the most crucial factor positively affecting the FC and PWP under moss layer.

Conclusion
The findings of this study verified our hypotheses that the soil water retention under the thin and thick moss layers were greater than those under no moss cover, with the highest plant-available water capacity under the thin moss layer.Under the thin moss cover, soil macropores were distributed throughout the soil profile, with a relatively uniform spatial distribution and a more lateral appearance; while the soil macropores under no moss cover and the thick moss layer were less abundance in the deep soil layer, and the connectivity of soil macropores under the thick moss layer was also better than that under no moss cover.The length density of the soil macropores under the thin moss layer and thick moss layer was approximately 2.7 and 1.6 times higher than that under no moss cover.The effective water content of the soil under the moss layer was also higher than that under no moss cover, and moss cover may increase the effective water content of the soil.The maximum water-holding capacity of the moss layer was significantly positively correlated with the field water-holding capacity of the soil and negatively correlated with the equivalent diameter of the macropores, while the storage capacity of the moss layer was significantly negatively correlated with the maximum effective water content of the soil.The FC and PWP were significantly and positively correlated with the soil organic matter.The moss layer has a positive ecohydrological effect on water retention and even water conservation in Qinghai spruce forest soils.In the future, we will focus on the effect of moss layer on infiltration, runoff and soil microbial community.

Fig
Fig. 1 Landscapes of the field sites

Fig. 3
Fig. 3 Vertical distribution of moss volume density along the range of moss thickness

Fig. 4
Fig. 4 Changes in the interception (a) and interception percentage (b) of the moss layer with the increase in simulated precipitation

Fig. 6
Fig. 6 Vertical distribution of soil macroporosity along the soil depths

Fig
Fig. 7 Volume percentage of soil macropores categorized by equivalent diameter, surface area, and volume

Fig. 9
Fig. 9 Plant-available water in soils under different moss cover conditions

Fig. 10
Fig. 10 Porosity composition derived from soil water retention curves

Table 1
Soil properties under different moss cover conditions

Table 2
Thickness, accumulation amount, and water-holding properties of the moss layer Column marked by the same letter is not significantly different at p = 0.05 between the treatments, the absence of letters indicates no significant differences.Data in the parentheses are standard deviations

Table 3
Three-dimensional parameters of soil macropores Column marked by the same letter is not significantly different at p = 0.05 between the treatments, the absence of letters indicates no significant differences.Data in the parenthe-

Table 5 The
Fig. 8 Soil water retention curves of different soil layers under different moss cover conditions

Table 6
Soil water storage (SWS) and plant-available water storage (PAWS) of different soil layers under different moss cover conditions

Table 8
Correlations between moss layer parameters and soil water retention (Gauthier et al. 2022)icant at the 0.05 probability level (2-tailed) **Correlation is significant at the 0.01 probability level (2-tailed) vertical dimensions.Previous studies also showed that moss could improve water retention in a restored bog(Gauthier et al. 2022).Kakeh et al. (