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Journal of Arid Land >

2024 , Vol. 16 >Issue 6: 834 - 851

DOI: https://doi.org/10.1007/s40333-024-0100-5

Research article

Characterization of alpine meadow surface crack and its correlation with root-soil properties

  • WU Yuechen 1 ,
  • ZHU Haili , 1, 2, * ,
  • ZHANG Yu 3 ,
  • ZHANG Hailong 1 ,
  • LIU Guosong 1 ,
  • LIU Yabin 1, 2 ,
  • LI Guorong 1, 2 ,
  • HU Xiasong 1, 2
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  • 1School of Geological Engineering, Qinghai University, Xining 810016, China
  • 2Key Laboratory of the Cenozoic Resources and Environment on the North Rim of the Qinghai-Tibet Plateau, Xining 810016, China
  • 3Qinghai Provincial Transportation Planning and Design Research Institute Co. Ltd., Xining 810002, China
*ZHU Haili (E-mail: )

Received date: 2024-02-03

  Revised date: 2024-05-23

  Accepted date: 2024-06-04

  Online published: 2025-08-13

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Abstract

Quantifying surface cracks in alpine meadows is a prerequisite and a key aspect in the study of grassland crack development. Crack characterization indices are crucial for the quantitative characterization of complex cracks, serving as vital factors in assessing the degree of cracking and the development morphology. So far, research on evaluating the degree of grassland degradation through crack characterization indices is rare, especially the quantitative analysis of the development of surface cracks in alpine meadows is relatively scarce. Therefore, based on the phenomenon of surface cracking during the degradation of alpine meadows in some regions of the Qinghai-Tibet Plateau, we selected the alpine meadow in the Huangcheng Mongolian Township, Menyuan Hui Autonomous County, Qinghai Province, China as the study area, used unmanned aerial vehicle (UAV) sensing technology to acquire low-altitude images of alpine meadow surface cracks at different degrees of degradation (light, medium, and heavy degradation), and analyzed the representative metrics characterizing the degree of crack development by interpreting the crack length, length density, branch angle, and burrow (rat hole) distribution density and combining them with in situ crack width and depth measurements. Finally, the correlations between the crack characterization indices and the soil and root parameters of sample plots at different degrees of degradation in the study area were analyzed using the grey relation analysis. The results revealed that with the increase of degradation, the physical and chemical properties of soil and the mechanical properties of root-soil composite changed significantly, the vegetation coverage reduced, and the root system aggregated in the surface layer of alpine meadow. As the degree of degradation increased, the fracture morphology developed from "linear" to "dendritic", and eventually to a complex and irregular "polygonal" pattern. The crack length, width, depth, and length density were identified as the crack characterization indices via analysis of variance. The results of grey relation analysis also revealed that the crack length, width, depth, and length density were all highly correlated with root length density, and as the degradation of alpine meadows intensified, the underground biomass increased dramatically, forming a dense layer of grass felt, which has a significant impact on the formation and expansion of cracks.

Key words： alpine meadow; grassland degradation; grassland cracks; crack characterization index; crack morphology; root length density; grey relation analysis

Cite this article

WU Yuechen , ZHU Haili , ZHANG Yu , ZHANG Hailong , LIU Guosong , LIU Yabin , LI Guorong , HU Xiasong . Characterization of alpine meadow surface crack and its correlation with root-soil properties[J]. Journal of Arid Land, 2024 , 16(6) : 834 -851 . DOI: 10.1007/s40333-024-0100-5

1 Introduction

In recent years, the alpine meadows on the Qinghai-Tibetan Plateau, China have degraded to different degrees under the combined influence of natural and anthropogenic factors, such as global warming, dry weather, and overloading and overgrazing of grasslands (Zhou et al., 2023). When alpine meadows are degraded from a Gramineae-Kobresia humilis plant community to a Kobresia pygmaea plant community, the grass-felt layer gradually thickens and topsoil cracking occurs (Cao et al., 2010). Li et al. (2015) suggested that the emergence of grassland cracks signals that the degradation of alpine meadows has transitioned from a quantitative change to a qualitative change, and the degradation process is accelerated by the strengthening of external erosion effect (Miehe et al., 2008; Li et al., 2015). The surface cracking of alpine meadow soil not only accelerates the evaporation and loss of water but also aggravates the drought stress of plants, and it can even rip a plant's roots out, causing it to die (Xiong et al., 2008). Fissures also affect the root distribution and water absorption, causing damage to plant roots (Tian et al., 2003). In addition, cracks cause soil to split into discontinuous media, opening preferential channels of water and fertilizer in soil (Niu et al., 2019), exacerbating soil erosion, deepening destruction of alpine meadows, and even forming bald spots and black soil beaches (Li, 2002; Shang and Long, 2005). Due to simple structure of plant communities and fragile ecosystems of alpine meadows (Zhang et al., 2018), cracks are highly vulnerable to anthropogenic activities and climate change. Degradation of alpine meadows has increased difficulty of restoration and management of fragile ecological environment in the Qinghai-Tibetan Plateau. Therefore, research on development process of surface cracks in alpine meadows can provide a theoretical basis for clarifying the mechanism of surface cracking in alpine meadows and an effective strategy for restoration and management of degraded alpine meadows.
Many scholars in China and around the world have carried out abundant research on development of crack morphology and its formation mechanism in clayey soils (Tang et al., 2007; Li et al., 2023) and expansive soils during dry-wet cycles (Leng et al., 2016; Zhang et al., 2016; Tian et al., 2022). The research on crack morphology development initially evolved from measurement of crack length, width, and depth to application of image processing techniques such as the Crack Image Analysis System (CIAS) (Tang et al., 2008) and ArcGIS (Xiong et al., 2008) for in-depth research of parametric indices like crack connectivity index (Xiong et al., 2008), crack area ratio (Zhang et al., 2016; Yang et al., 2021), and fractal dimension (Tang et al., 2007; Li et al., 2020). Vogel et al. (2005) established a system of indices used to describe the connectivity of crack network, including crack surface density, length density, and Euler number. Baer et al. (2009) used fractal geometry to describe crack morphology of dry shrinkage soil, fractal cracking of soil surface, fractal dimension of mass, and fractal cracking dimension of soil edge. Due to different development forms of cracks in different soils under different conditions, crack formation mechanism is not completely clear.
Thus far, a complete set of index systems for characterizing soil cracks have not been developed (Tang et al., 2008). Relatively few studies have been conducted on characterization indices of root-bearing soil cracks. Niu et al. (2022) studied the role of shrub Lespedeza bicolor in preventing slope soil cracking and found that shrub roots can inhibit the formation of cracks and play an important role in soil conservation and stability. Zhou et al. (2009) used roots of Amorpha fruticosa and Robinia pseudoacacia as reinforcement material of a root-soil composite and found that plant roots have an inhibitory effect on development of soil cracks. Zhu et al. (2022) measured and analysed the crack width index of remoulded root-containing soil of Yunnan laterite and Hedera nepalensis roots under dry-wet cycle conditions, and they proposed that crack resistance effect was the best when root content was 20.00%.
The cracking of soil is closely related to its own basic characteristics (Yan et al., 2021). Therefore, generation of surface cracks in alpine meadows is closely related to the characteristics of root soil in alpine meadows, and quantitative analyses of relationship between root soil characteristics and crack generation are relatively rare. The most significant factors of alpine meadow degradation are changes in soil physical and chemical properties, decreases in surface vegetation cover and aboveground biomass (Zhou et al., 2005; Li et al., 2015), and sharp increases in underground biomass (Zhou et al., 2005). When grassland gradually degrades, the surface particles coarsen (Wang et al., 2006; Cheng, 2007), the soil organic matter content decreases (Yang et al., 2020), and the soil compactness and water content change (Niu et al., 2019). The changes in soil physical and chemical properties lead to reorganization of soil structure, decrease in tensile strength, and generation of an ability to resist external erosion, which makes grassland prone to cracking. The changes in soil compactness result in variations in soil density and porosity. The decrease in aboveground biomass is mainly manifested by changes in plant species, that is, the decrease in number of palatable herbaceous plants, the increase in number of weeds, and the dwarfing of aboveground vegetation. The upward growth of plants is blocked and turned into downward development, and the plant root system accumulates in surface layer, which is manifested by gradual increases in root volume ratio and root length density in shallow soils (Du et al., 2007; Xiong et al., 2008). The vegetation root system density has an inhibitory effect on growth and development of cracks when it reaches a certain level (Bordoloi et al., 2018a, b). In summary, root-soil interactions cause cracks in alpine meadows during degradation.
Niu et al. (2019) investigated and studied cracks in alpine meadows in Tianzhu Tibetan Autonomous County, Wuwei City, Gansu Province, China and compared the length, width, and depth of cracks in different seasons. They then proposed that the development of cracks in alpine meadows includes a cracking period and a closing period. However, there is still a lack of research on the density and connectivity of cracks in alpine meadows and their relationships with aboveground vegetation, underground root characteristics, and number of rat holes. Cao et al. (2010) observed the occurrence of surface cracking in degraded alpine meadows in multiple locations, including Yushu Tibetan Autonomous Prefecture, Golog Tibetan Autonomous Prefecture, and Darlag County, Qinghai Province, China.
Based on this, in this study, we selected alpine meadows at different degrees of degradation in Huangcheng Mongolian Township, Menyuan Hui Autonomous County, Haibei Tibetan Autonomous Prefecture, Qinghai Province, China as the study area and took soil cracks with different degrees of development in this area as the research object. Outdoor investigation and indoor tests were carried out to establish a surface crack characterization index of alpine meadows and to determine the main factors affecting the development of cracks. This study is significant for further research on crack development mechanism and the restoration and treatment of alpine meadows in Menyuan Hui Autonomous County, Qinghai Province, China.

2 Study area

The study area is located in the western part of Huangcheng Mongolian Township, Menyuan Hui Autonomous County, Haibei Tibetan Autonomous Prefecture, Qinghai Province, China (37°39′56.99′′-37°42′05.26′′N, 101°10′09.55′′-101°16′00.02′′E), with an average elevation of 3400 mFig. 1. This area has a highland continental climate characterized by significant diurnal temperature difference, cold weather, long winter, short summer, distinct cold and warm seasons, and no absolute frost-free period throughout the year. Moreover, the study area has a high evaporation rate, with maximum annual evaporation of up to 1160.30 mm (Wang et al., 2008), and low precipitation, with an average annual precipitation of 524.10 mm, which is mainly concentrated in May-September, accounting for 83.41% of the total annual precipitation (Yu et al., 2019). The predominant soil type is alpine meadow soil, and the vegetation community has a simple structure, dominated by Cyperaceae (e.g., Kobresia humilis and Kobresia pygmaca), Gramineae (e.g., Stipa capillata, Elymus nutans, and Poa crymophila), legumes, and other miscellaneous grass plants (Niu et al., 2019). The growing season is from June to September. According to statistics, the actual stocking rate in the local area of Huangcheng Mongolian Township ranges from 3.75 to 11.75 sheeps/hm2, corresponding to overgrazing (Lin et al., 2022). This has led to various degrees of cracking of the grassland inside and outside fences under different grazing pressure gradients. Soil cracking occurs from late October to mid-May, with healing occurring from late May to mid-October (Niu et al., 2019).
Fig. 1 Location of the study area in Huangcheng Mongolian Township, Menyuan Hui Autonomous County. DEM, digital elevation model.

3 Experimental design and analysis method

3.1 Experimental design

We adopted a method of spatial sampling at various locations rather than collecting measurements over time to compare the crack development characteristics of alpine meadows at different degrees of degradation in the study area, determine crack characterization indices, and analyse the main influencing factors. Based on the vegetation communities in alpine meadows, and in accordance with the local standard of Qinghai Province (Qinghai Provincial Bureau of Quality and Technical Supervision, 2015), we selected three different degradation levels of sample plots, namely, light degradation (LD), medium degradation (MD) and heavy degradation (HD) in the study area. The investigation of cracks and the sampling of the basic characteristics of the meadow plants and soils were carried out in these three sample plots. Large-scale crack surveys and small-scale in situ measurements and sampling were employed in this study. Specifically, within each sample plot, a large-scale (100.0 m×100.0 m) sample plot was established, and within this large-scale sample plot, three small-scale (0.5 m×0.5 m) sample plots were set at 70.5 m intervals along a diagonal line (Fig. 2a). To obtain low-altitude images of the cracks in the alpine meadows at different degrees of degradation, we used unmanned aerial vehicle (UAV) sensing technology to collect large-scale images in large-scale sample plots. Combined with image processing technology, the changes in the representative indices that could characterize the different development degrees of cracks were analysed. In addition, in situ investigation and sampling were carried out at crack locations (the fissures and the surrounding 1-2 cm subsidence area were referred to as crack location) and crack elevation locations (the patch that rises 2-6 cm above the surface was referred to as crack elevation location) in small-scale sample plot (Fig. 2b). Based on the thickness of the sedimentary soil layers, sampling was conducted at depths of 0-10, 10-20, and 20-30 cm below the surface. The objective was to determine the basic physical properties of the in situ alpine meadow soil (moisture content, density, and fine grain content), vegetation characteristics (vegetation coverage, species, and root parameters), soil mechanical characteristic (compactness), and soil chemical property (organic matter content).
Fig. 2 Schematic diagram of large-scale and small-scale sample plots (a) and sampling position (b)

3.2 Test methods

3.2.1 Large-scale UAV aerial survey

In May 2021, during a period of favourable weather conditions, a DJI Phantom 4 RTK UAV (Shenzhen DJI Innovation Technology Co. Ltd., Shenzhen City, Guangdong Province, China) was employed to capture digital orthophoto map (DOM) images at a low altitude of 25.00 m above the ground surface within the three large-scale sample plots, namely, LD, MD, and HD sample plots, in the study area (Fig. 3). The aerial survey was conducted using a flight plan designed to achieve a technical requirement of 80.00% forward overlap and 70.00% lateral overlap, and automatic route planning was conducted through a ground station. Subsequently, the acquired DOM images were processed by applying image analysis techniques in ArcGIS 10.5 software (Environmental Systems Research Institute Inc., Redlands, California, USA).
Fig. 3 Digital orthophoto maps (DOM) of large-scale alpine meadow sample plot. (a), light degradation (LD) sample plot; (b), moderate degradation (MD) sample plot; (c), heavy degradation (HD) sample plot.

3.2.2 Small-scale in situ measurements and sampling

In the small-scale sample plots, in situ sampling was conducted at the locations of fissures (i.e., crack locations) and soil protrusions (i.e., crack elevation locations) at depths of 0-10, 10-20, and 20-30 cm below the surface. Following the guidelines outlined in the Standard for Geotechnical Testing Method (Ministry of Housing and Urban-Rural Development of the People's Republic of China, 2019), the soil moisture content was determined using the drying method, the natural density of the undisturbed soil was determined using the ring knife method, and the particle size distribution of soil was determined through the sieve analysis method. Percentage by mass of soil particles less than 0.075 mm in size was counted to obtain the fine grain content. The organic matter content of the soil was determined using the potassium dichromate capacity method (Shi et al., 2023). Each layer was subjected to three replicate tests. In addition, the soil compactness was measured at the locations of the fissures and soil protrusions using a SC 900 Soil Compaction Meter (Spectral Technology Corporation, Madison, Wisconsin, USA) with three layers inserting vertically for measurement.
The vegetation cover within a 50 cm×50 cm quadrat (i.e., the small-scale sample plot) was determined using visual estimation, and the species of vegetation were recorded. Simultaneously, soil sampling was performed at the locations of fissures and soil protrusions within each quadrat using a JC-802 soil sampler (100 mm×200 mm) (Nanjing Soil Instrument Factory Co. Ltd., Nanjing City, China), three soil layers were sampled, and three root parameters, namely, the underground plant root-soil ratio (Zi et al., 2016), root volume ratio (Lacurain et al., 2021), and root length density (Ning et al., 2019), were quantified. The formulas for calculating these parameters are as follows:
R S = m R m S
R V = ∑ i = 1 n d i 2 2 × π × L i V Z
R Z = ∑ i = 1 n L i V Z
where RS is the root-soil ratio of underground plant; mR is the mass of dry roots (g); mS is the mass of dry soil (g); RV is the root volume ratio; di is the diameter of the ith root (mm); Li is the length of the ith root in the washed out root system (cm); VZ is the volume of the soil sampler (cm3), and in this study VZ=785.00 cm3; RZ is the root length density (cm/cm3); and n is the total number of roots counted.

3.2.3 Statistical methods for fracture characterization parameters

Combining the data from the DOM image maps of the large-scale sample plots, which were directly analyzed by ArcGIS 10.5 software with the in situ measured data of the cracks in the small-scale sample plots, the fracture-related parameters were quantitatively calculated, including the crack length, width, depth, length density, branch angle, and number of rat holes. Subsequently, the crack length density (Bordoloi et al., 2020) and burrow (rat hole) distribution density (Hou et al., 2019) were calculated using the following formulas:
D L = ∑ j =1 e D j S
D R = R w S
where DL is the crack length density (m/m2); Dj is the length of jth crack (m); S is the area of the grassland where the aerial image was collected (m2), and in this study S=1.00×104 m2; e is the number of fractures; DR is the burrow distribution density (number/m2); and Rw is the total number of burrows.
The crack length, width, and depth were directly measured using a digital calliper with a numerical display (Ningbo Deli Tools Co. Ltd., Ningbo City, China). Measurements in each sample plot were replicated 45-65 times, and the average values were calculated. The obtained parameters were subjected to one-way analysis of variance (ANOVA) using the SPSS 24.0 software (International Business Machines Corporation, Amonk, New York, USA) to ultimately determine the indices characterizing the cracks.

3.2.4 Grey relation analysis

Based on the previous research, it was decided that the moisture content, density, and fine grain content were selected as physical properties of soil, the organic matter content was selected as chemical property, the compactness was selected as mechanical property, and root-soil ratio, root volume ratio, and root length density were selected as root parameters (Zhou et al., 2005; Bordoloi et al., 2020; Niu et al., 2021). These were used as the evaluation parameters affecting the development of the crack characterization indices. The grey relation analysis was used to research the degree of correlation between the crack characterization indices and the eight evaluation parameters. The specific steps are as follows.
(1) The dimensionless of the data column, the calculation formula is:
x p , = x p ( k ) 1 h ∑ k = 1 h x p ( k )
where
x p ,
 and xp are the eigenvalues of the kth factor of the pth pattern before and after normalization, respectively; and h is the number of characteristic factors affecting the object to be estimated.
(2) The formula for the differences between each evaluation parameter and reference sequence is as follows:
ξ 0 p ( k ) = min m p = 1 min h k = 1 x 0 , ( k ) − x p , ( k ) + ρ max m p = 1 max h k = 1 x 0 , ( k ) − x p , ( k ) x 0 , ( k ) − x p , ( k ) + ρ max m p = 1 max h k = 1 x 0 , ( k ) − x p , ( k )
where
ξ 0 p ( k )
 is the correlation coefficient between the reference sequence and the corresponding value;
x 0 , ( k ) − x p , ( k )
 is the absolute difference between the data value in the reference series and the corresponding value;
min m p = 1 min h k = 1 x 0 , ( k ) − x p , ( k )
 is the minimum value of the absolute difference;
max m p = 1 max h k = 1 x 0 , ( k ) − x p , ( k )
 is the maximum value of the absolute difference; m is the number of known pattern characteristic factors; and ρ is the resolution coefficient, which normally takes the value of 0.50.
(3) The calculation of the correlation degree, the formula is:
γ = 0 p 1 h ∑ k = 1 h ξ 0 p ( k )
where γ0p is the correlation degree.

4 Results

4.1 Basic characteristics of soil

The basic physical, chemical, and mechanical characteristics of the soil in the study area and the average values of each parameter are presented in Table 1. The average soil moisture content ranged from 25.13% to 62.65%, and the soil density was 0.85-1.38 g/cm3. The soil compactness varied from 234.42 to 1299.64 kPa. When comparing the variations in the parameters such as moisture content, density, compactness, and organic matter content at crack locations and crack elevation locations within the same depth range of soil layer, it was observed that crack elevation locations had lower moisture and organic matter contents than crack locations. Taking the LD sample plot as an example, the soil moisture content at crack locations was 1.11, 1.22, and 1.15 times higher than those at crack elevation locations in the 0-10, 10-20, and 20-30 cm depth intervals, respectively. The corresponding organic matter content at crack locations was 1.16, 1.11, and 1.06 times higher than those at crack elevation locations in the 0-10, 10-20, and 20-30 cm depth intervals, respectively. Within the 0-10 cm depth interval, the soil density at crack elevation locations was approximately 1.08 times higher than that at crack locations. The soil compactness was significantly higher at crack elevation locations than at crack locations, and in the 0-10, 10-20, and 20-30 cm depth intervals, the values were 2.28, 1.87, and 1.88 times higher at crack elevation locations than those at crack locations, respectively. Based on a vertical comparison of numerical variations in the relevant parameters at crack locations and crack elevation locations at different soil depths, it was observed that as the sampling depth increased, the moisture content, compactness, and organic matter content decreased, while the density generally increased.
Table 1 Soil characteristics of the three alpine meadow sample plots at different degrees of degradation
Sample plot Sampling position Layer depth (cm) Soil moisture content (%) Soil density (g/cm3) Soil compactness (kPa) Fine grain content (%) Organic matter content (g/kg)
LD Crack location 0-10 42.84 1.06 426.30 11.19 151.50
10-20 35.00 1.20 306.82 10.23 111.25
20-30 28.95 1.08 325.78 9.16 98.31
Crack elevation location 0-10 38.66 0.98 970.99 7.93 130.05
10-20 28.66 1.18 574.55 13.36 100.07
20-30 25.13 1.14 612.46 14.95 92.64
MD Crack location 0-10 46.73 0.85 589.50 7.67 209.65
10-20 37.70 1.31 413.69 12.63 106.41
20-30 35.66 1.20 465.40 13.04 72.08
Crack elevation location 0-10 43.14 0.98 1299.64 14.19 145.71
10-20 32.91 1.20 772.21 15.72 86.65
20-30 29.63 1.03 730.84 12.85 67.56
HD Crack location 0-10 62.65 0.90 405.60 10.11 170.34
10-20 48.78 1.23 275.79 18.98 104.74
20-30 44.75 1.18 234.42 17.58 99.79
Crack elevation location 0-10 61.09 1.00 973.33 8.69 126.90
10-20 47.06 1.38 417.73 22.84 105.72
20-30 37.39 1.16 391.83 12.55 70.60

Note: LD, light degradation; MD, moderate degradation; HD, heavy degradation.

From LD to MD and then to HD, at crack locations, the moisture content and fine grain content of soil increased and the density and compactness decreased. However, as the fine grain content increased with increasing degradation of the alpine meadows, the contact area between particles increased, and the cohesive forces between particles caused the soil particles to bond to form tight aggregates, resulting in an increase in soil density and tightness at crack elevation locations.

4.2 Vegetation characteristics

4.2.1 Species and distribution of aboveground vegetation

The study area was dominated by alpine meadow vegetations. The type of grass in the LD sample plot was Gramineae-Kobresia pygmaea, and the type of grass in the MD and HD sample plots was Kobresia pygmaca-Kobresia humilis. Based on the survey results of the vegetation samples of the three plots, with the degradation of alpine meadow evolved from LD to MD eventually to HD, the total coverage of vegetation samples decreased by 29.34%-50.00%, and the coverage of Cyperaceae and Gramineae plants such as Kobresia humilis and Elymus nutants decreased from 63.00% to 41.00% and then to 26.00%, and the declinations were 34.92% and 58.73%, respectively (Table 2). The LD sample plot consisted of 18 species from 8 families, the MD sample plot consisted of 14 species from 8 families, and the HD sample plot consisted of 10 species from 6 families. This indicated that with increasing degradation, the coverage of weeds increased, resulting in an overall decrease in species diversity and abundance. The analysis revealed that under high-intensity grazing conditions, the foraging behaviour of grazing livestock prioritized nibbling on high-quality edible forage grasses, mainly graminaceous. This led to the gradual reduction or even disappearance of graminaceous plants, which are mainly reproduced by seeds, through excessive deprivation and a decrease in the proportion of good forage grasses, accompanied by an increase in the proportion of poor-quality forage grasses or poisonous weeds. At the same time, it had an inhibitory effect on the growth of good forage grasses in terms of their height, coverage, and biomass.
Table 2 Vegetation species and coverage in the three sample plots at different degrees of degradation
Sample plot Total vegetation coverage (%) Number of families Number of species Coverage of Cyperaceae and Gramineae plants (%) Dominant plant species
LD 92.00-100.00 8 18 63.00 Kobresia pygmaca, Elymus nutans, Stipa capillata, and Oxytropis kansuensis
MD 75.00-88.00 8 14 41.00 Kobresia pygmaca, Kobresia humilis, Anaphalis hancockii, and Gentiana macrophylla
HD 50.00-65.00 6 10 26.00 Kobresia humilis, Stipa capillata, Saussurea pulchra, and Leontopodium leontopodioides

4.2.2 Underground root parameters

According to the statistics of the root parameters of the three alpine meadow sample plots at different degrees of degradation in the study area (Fig. 4), the underground biomass decreased significantly with increasing soil depth. The underground biomass was mainly concentrated in the 0-10 cm soil layer, and the root-soil ratio of the 0-10 cm soil layer was 4.59-45.31 times higher than those of the 10-20 and 20-30 cm soil layers. Moreover, the root volume ratio increased with increasing degradation, and the values of root-soil ratio, root volume ratio, and root length density at crack elevation locations were higher than those at crack locations. By comparing the values of root-soil ratio, root volume ratio, and root length density at different soil depths at crack locations and crack elevation locations in the LD, MD, and HD sample plots, it was found that the values of root-soil ratio, root volume ratio, and root length density all decreased with increasing soil depth. In the same horizontal depth range, the values of root-soil ratio and root length density at crack locations gradually increased with the aggravation of meadow degradation, while the root-soil ratio at crack elevation locations gradually decreased. This occurred because with the aggravation of degradation, the fracture morphology became more developed, and the water and fertilizer collection at the fracture made plants grow better, then the underground biomass at the fracture increased. By contrast, due to soil shrinkage and compaction, the elevation areas of fracture were unfavourable for water storage, resulting in a decrease in the belowground vegetation biomass. As the alpine meadow degraded from LD to MD and then to HD, root volume ratio initially decreased and then increased overall, while the root length density generally increased. This occurred due to the alpine meadow degradation, and the plant root system in the shallow soil body produced an aggregation phenomenon.
Fig. 4 Root-soil ratio (a), root volume ratio (b), and root length density (c) at different soil depth layers in the three alpine meadow sample plots at different degrees of degradation. C, crack location; E, crack elevation location.

4.3 Fracture characterization of alpine meadows

4.3.1 Crack patterns

The degrees of crack development of the three alpine meadow sample plots at different degrees of degradation in the study area were different. When alpine meadow degraded from LD to MD and then to HD, the main body of fracture morphology transformed from a linear type (Fig. 5a) to a dendritic type (Fig. 5b) and then to a polygonal type (Fig. 5c). Therefore, the crack development process was divided into three stages: a fracture occurrence stage (linear type), a fracture development stage (dendritic type), and a fracture stability stage (polygon type). During the formation of surface cracks in the alpine meadow sample plots of the study area and their gradual extension in the depth and horizontal directions, the shape evolved from a simple linear shape to a polygonal planar combination. When two or more linear fractures intersected and developed into dendritic and polygonal combined fractures, intersections appeared, and rat holes were mostly distributed at the intersections of fractures. With increasing crack development, the number of rat holes and the area of bare land increased (Fig. 5d), which aggravated the degradation of alpine meadows under the action of external erosion, such as erosion caused by water flow, wind, and freezing and thawing.
Fig. 5 Fracture morphology in alpine meadows. (a), linear fracture; (b), dendritic fracture; (c) polygonal fracture; (d), rat hole and surrounding bare ground.

4.3.2 Fracture characterization parameter statistics

As can be seen from Table 3, with the aggravation of alpine meadow degradation, the length and width of cracks gradually decreased, while the depth, length density, and burrow distribution density of cracks increased. With the degradation of alpine meadow from LD to MD and then to HD, the crack width gradually decreased, with reduction rate of 20.67% and 38.22%, respectively. The crack depth increased with increasing degradation, and the crack depth in the HD sample plot was 1.35 and 1.11 times longer than those in the LD and MD sample plots, respectively.
Table 3 Statistic result of fracture characterization parameter in the three alpine meadow sample plots at different degrees of degradation
Fracture characterization parameter Alpine meadow sample plot at different degrees of degradation
LD MD HD
Crack length (m) 2.22±1.63a 2.26±1.89a 1.66±1.24b
Crack width (cm) 13.11±6.12a 10.40±6.49b 8.10±3.55c
Crack depth (cm) 3.99±1.20b 4.88±1.73a 5.40±1.84a
Crack length density (m/m2) 0.20 0.22 0.27
Burrow distribution density (number/m2) 0.002 0.061 0.231
Crack branch angle (°) 30-110 50-100 30-70
Fracture morphology Linear type Dendritic type Polygonal type

Note: ±, mean±SD. Different lowercase letters within the same row represent significant difference at P<0.05 level.

The crack branch angles of the three alpine meadow sample plots at different degrees of degradation in the study area were stabilized in the range of 30°-110°. When the alpine meadows degraded from LD to MD and then to HD, the crack branch angle gradually decreased, while the crack length density and burrow distribution density increased. From LD to HD, the crack length density and burrow distribution density increased by 1.35 and 115.50 times, respectively. The increasing degradation of alpine meadows, the increasing number of surface cracks, the fragmentation of grassland integrity, and the frequent activities of rodents were the main reasons for the accelerated degradation of alpine meadows.
According to the results of ANOVA, the crack length, width, and depth of the alpine meadows at different degrees of degradation were significantly different (P<0.05). Therefore, the crack length, width, and depth were selected as the characterization parameters for evaluating the fractures in the sample plots at different degrees of degradation. The statistical analysis results revealed that there were significant differences in crack lengths among the alpine meadows at different degrees of degradation. The crack length index per unit area, i.e., the crack length density, was also used as a parameter for fracture characterisation in alpine meadows based on the results of Vogel et al. (2005).

4.4 Correlation between crack and root-soil properties

Due to the aggravation of alpine meadow degradation, the surface vegetation species, coverage, underground root parameters, and soil characteristics all exhibited certain differences. To quantitatively analyse the main factors affecting the characterization indices of cracks in the sample plots at different degrees of degradation, the grey relation analysis method was used. The length, width, depth, and length density of cracks were used as four reference factors, and the root parameters and the soil physical, mechanical, and chemical properties were used as eight comparative factors to conduct the relation analysis (Table 4). The results of grey relation analysis revealed that there were significant correlations among the eight comparative factors and the four reference factors, indicating that the development of the crack length, width, depth, and length density was affected by the root parameters and the physical, mechanical, and chemical properties of soil. The root parameters (root-soil ratio, root volume ratio, and root length density) had the highest correlations (all greater than 0.60) with the length, width, depth, and length density of cracks in the alpine meadows at different degrees of degradation, and the overall order was root length density>root volume ratio>root-soil ratio. The influence of comparative factors on each reference factor at crack elevation locations was higher than that on the related factor at crack locations. Among the physical properties, the soil moisture content had significant influences on the length, width, and length density of grassland cracks, and the correlation values were 0.56-0.78. In addition, the fine grain content also had strong correlations with the width, depth, and length density of crack.
Table 4 Correlation between basic characteristics of vegetation and soil and crack characterization indices
Reference factor Sampling position Comparative factor
Soil physical property Soil mechanical property Soil chemical property Root parameter
Soil moisture content Soil density Fine grain content Soil compactness Organic matter content Root-soil ratio Root volume ratio Root length density
Crack length Crack location 0.56 0.74 0.68 0.61 0.61 0.72 0.80 0.82
Crack elevation location 0.62 0.76 0.62 0.70 0.50 0.83 0.83 0.89
Crack width Crack location 0.74 0.65 0.62 0.69 0.67 0.61 0.66 0.72
Crack elevation location 0.78 0.78 0.72 0.63 0.64 0.80 0.80 0.87
Crack depth Crack location 0.76 0.72 0.67 0.69 0.66 0.66 0.72 0.78
Crack elevation location 0.72 0.79 0.69 0.65 0.63 0.81 0.82 0.88
Crack length density Crack location 0.74 0.69 0.62 0.67 0.66 0.62 0.68 0.72
Crack elevation location 0.74 0.82 0.68 0.65 0.61 0.81 0.81 0.88
According to Table 4, the crack length exhibited the highest correlation with root length density at both crack locations and crack elevation locations, with correlation coefficients of 0.82 and 0.89, respectively, closely followed by root-soil ratio and root volume ratio. This suggested that the underground root parameters played a significant role in the development of crack length in alpine meadows. The correlations between the various comparative factors and crack width at crack locations were in the following order: soil moisture content (0.74)>root length density (0.72)>soil compactness (0.69)>organic matter content (0.67)>root volume ratio (0.66)>soil density (0.65)>fine grain content (0.62)>root-soil ratio (0.61). This indicated that the soil moisture content had the greatest impact on crack width at crack locations. This can be attributed to the fact that the cracks served as preferential pathways for water flow, exacerbating water erosion of soil and causing expansion of crack width. For the crack elevation locations and crack width, the order of correlations was as follows: root length density (0.87)>root-soil ratio (0.80)=root volume ratio (0.80)>soil moisture content (0.78)=soil density (0.78)>fine grain content (0.72)>organic matter content (0.64)>soil compactness (0.63). It should be noted that the soil compactness had the smallest impact on crack width at crack elevation locations. By comparing the correlations between soil compactness and crack width at crack locations and crack elevation locations, it was found that the correlation was higher at crack locations (0.69) than at crack elevation locations (0.63). These differences stemmed from the differences in the pore size at crack location and protruding parts, which are manifested as different degrees of compaction. The correlation coefficients between crack depth and the eight comparative factors revealed that the influence of organic matter content on crack depth was the lowest at both crack locations and crack elevation locations, with correlation coefficient of 0.66 and 0.63, respectively. The organic matter content of soil exerted a double effect on soil structure and crack formation. On the one hand, its water retention and expansive properties made the soil more capable of absorbing and retaining water, leading to soil water expansion and volume increase, which promoted the formation and depth increase of cracks. On the other hand, the colloidal particles and colloidal clay particles in the organic matter bonded with soil particles, forming a stable soil structure, which reduced the occurrence of surface cracking in alpine meadows. Therefore, the overall effect of organic matter content on crack depth was limited. The root length density influenced crack length density, with the highest correlation coefficient (0.88) observed at crack elevation locations. The growth of plant root system increased the area of contact between root system and soil, thus increasing the friction between root and soil and enhancing its ability to resist external forces, thus slowing or inhibiting the formation and development of cracks.

5 Discussion

The formation and development of surface cracks in alpine meadows were affected by the combined effect of multiple factors; and the most intuitive characterization indices of cracks were the length, width, depth, and length density of cracks (López-Bellido et al., 2016; Wang et al., 2017; Niu et al., 2019). Based on intuitive characterization, scholars have used crack length density (Zhang et al., 2013; Wang et al., 2017), crack intensity factor (Tang et al., 2008 and 2011), and crack connectivity index (Xiong et al., 2008) as characterization indices to describe the developmental strength and intensity of cracks. To quantitatively characterize the development of grass cracks in the alpine meadows in Menyuan Hui Autonomous County, under different grazing pressure conditions, we used a combination of in situ measurements and macroscopic analyses of cracks and found that with the intensification of the degree of grass degradation, the changes in the length, width, depth, and length density of cracks in the study area were significantly different. Thus, these four fracture characterization parameters were identified as the characterization indices for the development of the surface cracks in the alpine meadows.

5.1 Relationship between surface cracks and root parameters in alpine meadows

The development of surface cracks in alpine meadow areas was influenced not only by the vegetation species and coverage, and the morphology and quantity of underground root systems, but also by the soil type and structure, making their formation and development distinct from surface cracks in general soils. The vegetation coverage, species types, and structural characteristics were the most intuitive ecosystem response indices for alpine meadows. Due to the grazing of livestock, the coverage of palatable herbaceous plants such as Cyperaceae and Gramineae decreased overall, while the species and coverage of weeds increased, and the aboveground vegetation exhibited low growth and development. The reproduction and growth strategies of different plant populations were different in adapting to environmental changes, and ultimately, the composition and structure of plant communities changed, leading to the formation of a new stage of degraded succession (Cao et al., 2007; Lin, 2017). As the aboveground growth of vegetation was suppressed, it transitioned to underground growth and vigorous development to adapt to the survival environment, exhibiting root aggregation in the surface layer and a decrease in root volume with a greater soil depth (Zhou et al., 2005). Zhou et al. (2005) found that the number of subterranean plant roots in the shallow soil body dramatically increased, the root growth in the horizontal and vertical directions intertwined to regulate each other, and a dense layer of grass felt gradually formed, followed by subsequent thickening. This was consistent with the results of this paper; that is, with increasing degradation, the vegetation coverage decreased, the weed species biomass increased, and the roots aggregated in the surface layer. The presence of fibre roots increased the shear capacity of soil and had a reinforcing and toughening effect on soil (Zhou et al., 2014), which inhibited the growth and development of cracks when the density of root system reached a certain level (Bordoloi et al., 2018a, b). This is consistent with the phenomenon of crack healing during the period of vegetation emergence and growth from May to September, and then the cracks opened when the vegetation wilted from October to May (Niu et al., 2019). Niu et al. (2019) found that cracks appeared in an alpine meadow when the plant biomass was less than 49.56 g/m2 and the vegetation community height was less than 2.43 cm. Zhu et al. (2020) and Zeroual et al. (2024) found that roots or fibres significantly affected crack width and slowed down the rate of soil moisture evaporation, and as the root content and length increased, the root-soil system's resistance to destruction was enhanced, reducing the crack rate. Xiong et al. (2008) observed that with increasing degradation, the root length density in cracks gradually increased. This is consistent with the high correlation between root length density and crack characterization indices found in this study. It is evident that root system parameters were the main factors affecting crack characterization indices, and it was observed that different vegetation types had distinct root morphologies. The root diameter of Gramineae and Cyperaceae plants was significantly smaller than that of weeds, but the tensile strength of their roots was higher than that of weeds.
In addition, the contact areas between root and soil of different species were different, and the toughening effect of degraded plants on soil was lower than that of native plants (Zhu et al., 2020). Therefore, the crack resistance of plant roots in soil was closely related to plant species; the toughening effect of different plant species on soil needs to be further studied.

5.2 Relationship between surface cracks and soil properties in alpine meadows

The disparity in fine grain content may be the primary factor controlling the degree of soil shrinkage (Niu et al., 2019). The clay content of soil determines its relative shrinkage, which in turn dictates the enlargement of soil pores and the generation of cracks under frequent freeze-thaw cycles and dry conditions prevalent in alpine regions (Li et al., 2016; Gao et al., 2020). The results of single-factor experiment indicated that among the soil physical properties, the fine particle content has the highest correlation with crack characterization indices. This is because soil cracking intensifies the evaporation of water from soil, leading to a reduction in the soil moisture content, soil shrinkage, and an increase in the tensile stress among soil particles. This enlarges inter-particle voids, forming larger pores and potentially leading to cracks and thereby reducing soil compactness. As pores expand at crack locations, soil particles aggregate toward the raised areas of cracks, the porosity at crack protrusions decreases, and the compactness and overall stability of soil increase, thereby reducing deformation and cracking. This is consistent with the findings of Niu et al. (2019), that is, porosity is significantly higher at cracks than in raised areas. When soil is dense and porosity reduces, its deformability decreases, which affects soil permeability and root growth, leading to the gradual death of surface vegetation and ultimately resulting in the formation of bare patches. Therefore, the degraded grassland in grazing conditions, livestock trampling with soil pore structure tightening, underground root reduction, and the shallow surface of superposition effects make it easy for surface cracking to occur in alpine meadows with low deformability, and once cracks form, they are difficult to heal (Niu et al., 2019). Cracks damage original soil structure and open priority surface water flow channels, allowing water and fertiliser to accumulate at the location of crack, resulting in increased soil moisture and organic matter contents (Niu et al., 2021). The water flow carries fine particles into cracks, and they may be deposited at the bottom of cracks. This is accompanied by the redistribution of fine particles, affecting the overall gradation of soil and thus influencing soil porosity and stability. The presence of cracks alters the surface water and thermal conditions, increasing soil surface area, thereby accelerating the evaporation of water and the exchange of heat. This leads to the depletion of deep soil moisture and significantly lower surface temperatures at cracks compared with non-cracked areas (Niu et al., 2019). The results of grey relation analysis suggested that the changes in soil gradation composition, structure, water, and thermal dynamics, as well as vegetation effects, were the primary driving forces of the formation and development of soil cracks. In summary, the existence of soil cracks altered the physical properties and environmental conditions of soil, which in turn influenced the development of cracks, thereby exacerbating the degradation of alpine meadows.
Therefore, understanding the interactions between the relevant environmental factors and crack characterization indices as well as establishing the relationships between the plant root system mechanical properties and crack characterization indices are crucial for predicting and controlling soil cracking in alpine meadows. This knowledge will help to mitigate the negative impacts of cracks on soil function and land use and is essential for devising effective management and restoration strategies for degraded alpine meadows.

6 Conclusions

As the degradation degree of alpine meadows changed from mild to moderate and then to severe, and the soil's physical, chemical, and mechanical properties changed accordingly. The total vegetation coverage in the study area decreased, and the aboveground biomass and the number of species generally decreased, as the increasing degradation of alpine meadow. The root system gathered and developed in the range of 0-10 cm underground, leading to increased grassland soil compactness. Based on the fracture development morphology of different degradation degrees of alpine meadow surfaces in the study area, the process can be divided into three stages. In the fracture occurrence stage, the fracture morphology presented a single linear shape; in the fracture development stage, two or more fractures intersected into a dendritic type; and in the fracture stability stage, multiple fractures intersected and closed to form a polygonal structure. In addition, the length, width, depth, and length density of grassland cracks were determined to be the key indices to describe the characteristics of cracks by statistical analysis. Comparative analysis showed that the crack characterization indices had a relatively high correlation with root parameters (root-soil ratio, root volume ratio, and root length density), in which root length density had the strongest correlation with the crack characterization indices, followed by root volume ratio. In future research, it is necessary to establish a model relating the crack characterization indices to the types, morphologies, and mechanical properties of roots.

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This study was funded by the National Natural Science Foundation of China (42062019, 42002283) and the Project of Qinghai Science & Technology Department (2021-ZJ-927). We thank all the anonymous reviewers and editors for providing helpful comments for this manuscript.

Author contributions

Conceptualization: WU Yuechen, ZHU Haili; Methodology: WU Yuechen, ZHANG Yu, ZHU Haili; Field test guidance: LIU Yabin, LI Guorong; Indoor test guidance: HU Xiasong; Indoor and outdoor tests: WU Yuechen, ZHANG Hailong, LIU Guosong, ZHANG Yu; Data curation: WU Yuechen, ZHANG Hailong, ZHANG Yu; Writing - original draft preparation: WU Yuechen; Review and editing: ZHU Haili. All authors approved the manuscript.

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