DOI: 10.5061/dryad.9cnp5hqvp
title: Data from: Contrasting trends in plant diversity and soil carbon mineralization under precipitation-driven vegetation and soil carbon dynamics in the Mongolian plateau

description: Climatic shifts critically regulate soil organic carbon (SOC) dynamics,
 biodiversity, and productivity in grasslands. However, the mechanisms
 linking abiotic/biotic factors to plant diversity–SOC mineralization
 synergies remain unclear. To study this mechanistic relationship, we
 established 12 sampling sites along an east–west precipitation gradient
 across the China-Mongolia steppe. We measured plant diversity and biomass
 for both species and functional groups in 12 grassland sites. In the
 laboratory, we analyzed soil nutrients and microbial communities. We also
 measured the SOC mineralization potential using 28-day incubations. The
 results indicated that: (1) Aboveground biomass (AGB) increased through
 two opposing strategies, enhancing or reducing plant diversity, with
 thresholds at Shannon–Wiener indices of 1.14 (arid west) and 2.19 (humid
 east). AGB shifts altered resource competition and microenvironments,
 directly impacting diversity. (2) Plant diversity was primarily regulated
 by soil pH, SOC, and mean annual temperature (MAT). (3) Perennial grasses
 dominated productivity, while perennial forbs drove diversity via niche
 complementarity. (4) Microbial biomass carbon (MBC) was the direct driver
 of SOC mineralization, modulated by mean annual precipitation (MAP)
 through SOC mediation. (5) SOC mediated contrasting ecosystem effects by
 suppressing plant diversity through pH-driven nutrient limitations while
 simultaneously enhancing mineralization rates via stimulation of microbial
 decomposer activity. SOC properties and precipitation govern divergent
 changes in grassland diversity and carbon cycling. Strategic management of
 SOC pools, coupled with precipitation adaptation and biodiversity
 conservation, can enhance ecosystem resilience under climate change. This
 mechanistic framework advances understanding of grassland responses to
 global change.
description: <strong>Study area</strong> The
 research was carried out in the steppe of Inner Mongolia, located in
 northern China, and serves as a prime example of the Eurasian steppe
 concerning its climate, soil, and vegetation (Bai et al., 2008). The
 geographical coordinates of the study area range from 39°01′ to 49°32′ N
 and 101°37′ to 120°02′ E, with elevations between 653 m and 1,478 m.
 Annual temperature averages fluctuate from 2°C to 8°C, with January
 recording the lowest monthly averages (-9°C to -26°C) and July the highest
 (19°C to 24°C). The region experiences mean annual precipitation varying
 from 100 to 380 mm, with approximately 80% of it falling during the
 growing season (May to August), aligning with peak temperatures (Bai et
 al., 2008). The soil types found here include chestnut, calcareous brown,
 and desert soils. A total of twelve sites across the east-west gradient
 were selected to represent four types of plant communities: meadow
 grassland, typical grassland, desert grassland, and desert, with a trend
 of decreasing annual precipitation. The eastern meadow steppe is
 characterized by dominant species such as <em>Leymus
 chinensis</em>, <em>Stipa baicalensis</em>, and
 <em>Filifolium sibiricum</em>. In contrast, the central
 grasslands feature <em>Leymus chinensis</em>, <em>Stipa
 grandis</em>, and <em>Artemisia frigida</em> as
 predominant species. The desert grasslands are primarily composed of
 <em>Stipa klemenzii</em> and <em>Allium
 polyrhizum</em>, while the western desert areas are characterized by
 <em>Salsola passerina</em>, <em>Hololachna
 songarica</em>, and <em>Nitraria tangutorum</em> (Mi et
 al., 2015). <strong>Study site setup and
 plant-soil sampling methodology</strong> This
 study involved fieldwork and sampling in August 2012. Twelve sites were
 selected along an east-west belt transect (Mi et al., 2015). Each site
 covered an area of 100 m × 100 m, in which ten 1 m × 1 m quadrats were
 systematically positioned. Various measurements were conducted within
 these plots, focusing on species composition, both aboveground and
 belowground biomass, soil microbial communities, and the physical and
 chemical characteristics of the soil. The quantity of
 plant species and their respective abundances were documented in each
 sampling plot. The plant species were classified into four categories
 according to their life forms: annual and biennial herbs (AB), perennial
 grasses (PG), perennial forbs (PF), and shrubs or semi-scrub plants (SHS).
 Counts and biomass measurements were recorded according to plant
 functional groups, and relative abundance and biomass were subsequently
 calculated. Plant specimens within the sample plots
 were clipped at ground level. After collecting the above-ground biomass,
 three soil cores were randomly collected using a 7 cm diameter root auger
 and placed into a root bag in each sample plot. Samples were obtained from
 three different soil depths: 0-5 cm, 5-10 cm, and 10-20 cm. Soil in the
 root bags was washed with running water. Roots were separated using a 1 mm
 sieve, eliminating dead roots and other debris. Aboveground biomass and
 root samples were dried in an oven at 65°C for 48 hours until they reached
 a constant weight, after which they were weighed. Using
 a soil auger with a 5 cm diameter, soil samples were taken. The cores from
 three augers were merged to create a composite sample, which was
 subsequently sieved through a 2 mm mesh, air-dried, and cleaned of gravel
 and other impurities prior to analyzing the physical and chemical
 properties. The pH of the soil was determined with a potentiometric
 method, using a 2.5:1 liquid-to-soil ratio and the FE28 pH meter (Mettler
 Toledo, Switzerland). Total carbon (TC) and total nitrogen (TN) content
 (g/kg of dry soil) were measured by a CHON elemental analyzer (Elementar
 VARIO EL III, Hanau, Germany). Inorganic carbon (IC) was determined using
 a calcium carbonate analyzer (Eijkelkamp, Giesbeek, Netherlands). Soil
 organic carbon (SOC) was then calculated by subtracting IC from TC. The
 carbon-to-nitrogen ratio (C/N) was obtained by dividing SOC by
 TN. Microbial biomass carbon (MBC) was assessed through
 the chloroform
 fumigation-K<sub>2</sub>SO<sub>4</sub> extraction
 technique, while the analysis of the soil microbial community was
 conducted using the phospholipid fatty acid (PLFA) method.
 <strong>Meteorological data and soil organic carbon
 mineralisation</strong> Meteorological data were
 sourced from nearby meteorological stations at the sampling locations
 within the study area. Precipitation and temperature readings for each
 sampling site were derived and processed using kriging spatial
 interpolation within the Geographic Information System (ArcGIS). Data on
 soil organic carbon mineralisation and carbon dioxide accumulation from
 incubated soils under conditions of 25°C and 60% water-filled pore space
 (WFPS) across the 12 sampling sites were retrieved from our prior research
 for additional analysis (Mi et al., 2015).
 <strong>Statistic analysis</strong>
 Data organization was carried out using Excel 2021. A one-way
 regression analysis was performed to correlate the Simpson diversity
 index, Shannon-Wiener diversity index, and Margalef richness index of all
 sample plots with the total and aboveground biomass using SPSS version
 23.0. The regression equation was fitted by selecting the function that
 yielded the highest coefficient of determination
 (R<sup>2</sup>). Mantel test and Pearson’s test were used to
 investigate the correlation between diversity indices as well as soil
 organic carbon mineralisation accumulation and environmental variables
 through using R version 4.1.2 (Lucent Technologies, Jasmine Mountain, New
 Jersey, USA). Pathway analysis of the effects of climatic factors,
 vegetation traits, soil physico-chemical traits and soil microbial
 properties on biodiversity and soil organic carbon mineralisation
 accumulation was analysed using structural equation modelling (SEM). The
 SEM analysis incorporated MAP, MAT, aboveground and belowground biomass,
 soil organic carbon (SOC), the carbon-to-nitrogen ratio (C:N), microbial
 biomass carbon (MBC), the fungal-to-bacterial ratio (F:B), and pH levels.
 The SEM analyses were performed using Amos version 17.0.2 (Amos
 Development Corporation, Chicago, IL, USA), applying chi-square
 (<em>χ</em><sup>2</sup>) tests, comparative fit
 indices (CFI), root mean square error of approximation (RMSEA), and
 goodness-of-fit index (GFI) to evaluate model performance.
 Species diversity is frequently assessed using the Simpson index,
 Shannon-Wiener diversity index, and richness index, with the formulas for
 each being: Simpson index:
 D=1-∑Pi<sup>2</sup>
 Shannon-Wiener diversity index: H′=-∑Pi lnPi
 Margalef richness index: R=(S-1)/lnN
 where S denotes the total number of species within the community;
 N represents the overall count of individuals across all species in the
 community; N<sub>i</sub> indicates the number of individuals
 for each specific species, and P<sub>i</sub> =
 N<sub>i</sub>/N. The variable i signifies the relative density
 of plant species, calculated as the number of individuals of a particular
 species divided by the total number of individuals of all
 species.
description: # Data from: Contrasting trends in plant diversity and soil carbon
 mineralization under precipitation-driven vegetation and soil carbon
 dynamics in the Mongolian plateau
 [https://doi.org/10.5061/dryad.9cnp5hqvp](https://doi.org/10.5061/dryad.9cnp5hqvp) ### Files and variables #### File: raw_data.xlsx **Description:** Contains raw data from the related manuscript ##### Variables MAT      °C   Mean annual temperature MAP      mm Mean annual precipitation AGB      g/m2 Above-ground biomass BGB      g/m2 Below-ground biomass SOC       mg/g       Soil organic carbon TN  mg/g       Total soil nitrogen pH   --     Soil pH value MBC      mg/kg     Microbial biomass carbon C:N mg/mg    Soil carbon to nitrogen ratio Fungi      mol%     Fungi content in soil microbial biomass Bacteria  ×10-2mol%   Bacteria content in soil microbial biomass Cumulative CO2-C from mineralised soil organic carbon mg kg-1 d-1       Cumulative CO2-C from mineralised soil organic carbon by laboratory incubation under 25°C and 60% water filled pore space (WFPS) ## Access information Other publicly accessible locations of the data: * none Data was derived from the following sources: * none ### Change Log **Version 2**: Updated title