Soil biochemistry analysis in Shorea robusta forests

Description

We hypothesized that: 1) disturbance regimes would negatively affect soil microbial biomass and enzyme stoichiometry by increasing the substrate stress (organic matter) input from under-canopy vegetation (shrubs and herbs) and decline soil properties compared to non-disturbed; 2) moderate disturbance (MD) would reduce the microbial C and P limitation in severely P-limited soil by improving soil nutrients status and key physicochemical properties. The study followed a randomized complete stands design, incorporating 24 treatment combinations based on four disturbance regimes (ND, LD, MD, and HD), three seasons (summer, monsoon, and winter), and two soil depths (0-15 and 15-30 cm). As per Shankar & Garkoti (2023), 45 permanent forest stands (≥ 0.1 ha) were categorized into four ecological zones—ND (8), LD (25), MD (9), and HD (3)—based on disturbance intensity (DI, %) and canopy coverage (CC, %) as illustrated in Fig. 1b. These zones are defined as follows: No Disturbance (ND) with DI ≤ 5% and CC > 70%, Low Disturbance (LD) with 5% < DI ≤ 20% and CC > 50%, Moderate Disturbance (MD) with 20% < DI ≤ 50% and CC < 50%, and High Disturbance (HD) with DI > 50% and CC < 30%. Using a soil corer (15 cm × 5 cm × 5 cm), five soil cores were randomly collected at 1 to 1.5 meters from the base of tree stumps of dominant species, at soil depths of 0-15 cm and 15-30 cm. The soil from each predefined stand at the same depth was combined into one composite sample. This process yielded 48 composite soil samples for further analysis (four disturbance regimes × two replicates × two soil depths × three seasons). The freshly collected soil samples were placed in bags and stored at 4ºC before transportation to the laboratory. The moist samples were sieved through a ≤ 2 mm mesh to remove visible stones, pebbles, plant roots, and debris, and then homogenized. Each homogenized composite sample was divided into two portions: one was stored at 4ºC for soil microbial biomass and enzyme activity analysis, while the other was air-dried for assessing soil physicochemical properties. In each ecological zone, five random quadrats of 5 × 5 m² were established for shrubs, and 1 × 1 m² quadrats (with four points at the corners and one at the diagonal intersection) were used for herbs to assess cumulative understory diversity.

Steps to reproduce

Using a soil corer (15 cm × 5 cm × 5 cm), five soil cores were randomly collected at 1 to 1.5 meters from the base of tree stumps of dominant species, at soil depths of 0-15 cm and 15-30 cm. The soil from each predefined stand at the same depth was combined into one composite sample. This process yielded 48 composite soil samples for further analysis (four disturbance regimes × two replicates × two soil depths × three seasons). The freshly collected soil samples were placed in bags and stored at 4ºC before transportation to the laboratory. The moist samples were sieved through a ≤ 2 mm mesh to remove visible stones, pebbles, plant roots, and debris, and then homogenized. Each homogenized composite sample was divided into two portions: one was stored at 4ºC for soil microbial biomass and enzyme activity analysis, while the other was air-dried for assessing soil physicochemical properties. In each ecological zone, five random quadrats of 5 × 5 m² were established for shrubs, and 1 × 1 m² quadrats (with four points at the corners and one at the diagonal intersection) were used for herbs to assess cumulative understory diversity. Soil pH (1:5 w/v) was analyzed using the glass electrode (model 5 star, Themo Orion) method. Soil organic carbon (SOC) and nitrogen (N) were determined using wet oxidation and the micro Kjeldahl digestion method. Active inorganic nitrogen (N-NH4+ and N-NO3-) concentrations in the soils were extracted using 50 ml of 2M KCl solution, and the extracts were subsequently measured by the colorimetry method (sphectrophotometer). Soil microbial biomass was measured using the fumigation extraction method. Soil C, N, and P acquiring enzymes β-1,4-glucosidase (BG, µg phenol g⁻¹ dry soil h⁻¹), urease (U, µg NH₃-N g⁻¹ soil h⁻¹), and acid phosphatase (AcP, µg phenol g⁻¹ dry soil h⁻¹). The vector analysis and the scatter of enzyme C: N stoichiometry (horizontal and vertical) were employed to assess soil microbial nutrient limitations across different disturbance regimes. A larger vector length (Vector L) signifies a greater microbial carbon (C) limitation, while a larger vector angle (Vector A) greater than 45º indicates phosphorus (P) limitation; angles below 45º suggest nitrogen (N) limitation. All statistical analyses and visualization were performed using R software (version: 4.3.0) (R Core Team, 2023) with the aid of the RStudio interface (version: 2023.6.0.421). Three-factor analysis of variance (ANOVA) was performed using tidyverse, tidyr, and broom package in R. Pearson′s correlation coefficient was used to determine the strength and direction of liner association of soil microbial biomass, enzyme activity, and their stoichiometry and driving environmental factors using the ‘Corrr’ package. RDA was performed using a vegan package in R.

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