Fig 1.
Location of the study area and distribution of sampling points in the eastern Loess Plateau.
(Boundary data source from Li et al., 2022, and the Natural Earth. Created using ArcGIS 12.3 (ESRI). The coordinates and elevation data of the sample sites field-measured using GPS).
Fig 2.
Plant diversity index changing with elevation gradient.
The black point is the measured data of the sampling point, the line is the fitting line, and the gray range is the 95% confidence interval.
Fig 3.
Relationship between MAT and plant species diversity indices.
The black point is the measured data of the sampling point, the line is the fitting line, and the gray range is the 95% confidence interval.
Fig 4.
The relationship between elevation and plant functional groups.
The black point is the measured data of the sampling point, the line is the fitting line, and the gray range is the 95% confidence interval. (PG-RB, PF-RB, SHS-RB and AB-RB represent the relative biomass of perennial grasses, perennial weeds, shrubs and semi-shrubs, and annual or biennial herbs, respectively, as shown below).
Fig 5.
Relationship between MAT and plant functional groups.
The black point is the measured data of the sampling point, the line is the fitting line, and the gray range is the 95% confidence interval.
Fig 6.
Relationship between plant functional groups and plant species richness.
The black point is the measured data of the sampling point, the line is the fitting line, and the gray range is the 95% confidence interval.
Fig 7.
Plant diversity of grassland and different grassland types in the eastern Loess Plateau.
Different lowercase letters indicate that there are significant differences in the diversity index under different grassland types. (WT: warm tussock, WST: shrub-tussock, MM: temperate montane meadow, TM: temperate meadow).
Fig 8.
Biomass of grassland and different grassland types in the eastern Loess Plateau.
Different lowercase letters indicate that there are significant differences in biomass under different grassland types. (AB: aboveground biomass, UB: underground biomass, LB: litter biomass, TB: total biomass).
Fig 9.
Soil characteristics at different soil layer depths under different grassland types.
Different capital letters indicate significant differences in soil characteristics of the same soil layer under different types of grassland, while different lowercase letters indicate that there are significant differences in soil characteristics among different soil layers under different grassland types. (pH: Soil pH, TC: soil total carbon, TN: Soil total nitrogen, C/N: carbon to nitrogen ratio).
Fig 10.
The influence pathway of elevation, climate, vegetation, and soil factors on plant diversity and biomass within the community.
Black and gray arrows indicate positive and negative relationships, respectively. Solid or dashed lines indicate a significant (P < 0.05) or non-significant relationship. The thickness of the line indicates the size of the path coefficient. The numbers near the path arrows represent the standard path coefficients, with * represented as: ***P < 0.001, **P < 0.01, *P < 0.05. R2 is expressed as the proportion of variance explained for each dependent variable. df = 53, χ2/df = 1.562, GFI = 0.897, TLI = 0.929, RMSEA = 0.090, P = 0.647. Independent samples: n = 70.
Fig 11.
Spatial distribution map of SOCd and ANPP in grassland of the eastern Loess Plateau.
SOCd: Soil organic carbon density, ANPP: Above net primary productivity. The blank part belongs to the non-grassland area. Distribution data of vegetation types in China is based from the “ESA WorldCover 10 m 2021 V200 product” dataset. Created using ArcGIS 12.3 (ESRI).
Table 1.
Summary of soil carbon models.
Table 2.
Summary of plant richness models.
Fig 12.
Predicted spatial distribution pattern of TC and Margalef index in grassland of the eastern Loess Plateau.
The blank part belongs to the non-grassland area. Distribution data of vegetation types in China is based from the “ESA WorldCover 10 m 2021 V200 product” dataset. Created using ArcGIS 12.3 (ESRI).