Preamble

J Arid Land (2025) 17(6): 846–864
doi: 10.1007/s40333-025-0101-z; CSTR: 32276.14.JAL.0250101z
Science Press Springer-Verlag

Effect of long-term restoration on soil phosphorus transformation and desorption in the semi-arid degraded land, India

Jyotirmay ROY¹, Dipak Ranjan BISWAS¹, Biraj Bandhu BASAK¹, Ranjan BHATTACHARYYA¹, Shrila DAS¹, Sunanda BISWAS¹, Renu SINGH¹, Avijit GHOSH²*

¹ Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute (IARI), New Delhi 110012, India
² ICAR-Indian Grassland and Fodder Research Institute (IGFRI), Jhansi 284003, India

Abstract: Understanding how different vegetation-based restoration practices alter soil chemical and microbial characteristics is crucial, as restoration practices influence phosphorus (P) transformation and fractions and modify P adsorption behavior during the restoration process of degraded land. This study investigated the impacts of vegetation-based restoration practices on soil chemical and microbial parameters, P fractions, and patterns of P adsorption and desorption, and highlighted the combined influence on P availability. To evaluate the impact of vegetation-based restoration practices on P fractions and adsorption behavior in the semi-arid degraded land in India, this study compared three distinct tree-based restoration systems, including Leucaena leucocephala (Lam.) de Wit-based silviculture system (SCS), Acacia nilotica (L.) Willd. ex Delile-based silvopasture system (SPS), and Emblica officinalis Gaertn-based hortipasture system (HPS), with a natural grassland system (NGS) and a degraded fallow system (FS) as control. The soil samples across various soil depths (0–15, 15–30, and 30–45 cm) were collected.

The findings demonstrated that SCS, SPS, and HPS significantly improved soil organic carbon (SOC) and nutrient availability. Moreover, SCS and SPS resulted in increased microbial biomass phosphorus (MBP) content and phosphatase enzyme activity. The P fractionation analysis revealed that ferrum-associated phosphorus (Fe-P) was the major P fraction, followed by aluminum-associated phosphorus (Al-P), reflecting the dominance of ferrum (Fe) and aluminum (Al) oxides in the semi-arid degraded land. Compared with FS, vegetation-based restoration practices significantly increased various P fractions across soil depths. Additionally, P adsorption and desorption analysis indicated a lower adsorption capacity in tree-based restoration systems than in FS, with FS soils adsorbing higher P quantities in the adsorption phase but releasing less P during the desorption phase.

This study revealed that degraded soils responded positively to ecological restoration in terms of P fraction and desorption behavior, influencing the resupply of P in restoration systems. Consequently, litter rich N-fixing tree-based restoration systems (i.e., SCS and SPS) increased total phosphorus (TP) stock for plants and sustained the potential for long-term P supply in semi-arid ecosystems. With the widespread adoption of restoration practices across degraded landscapes, SCS and SPS would significantly contribute to soil restoration and improve productivity by maintaining the soil P supply in semi-arid ecosystems in India.

Keywords: phosphorus fixation; phosphorus fraction; phosphorus adsorption; phosphorus desorption; land restoration; structural equation model

*Corresponding author: Avijit GHOSH (E-mail: avijit.ghosh@icar.org.in)

Received 2025-01-13; revised 2025-04-22; accepted 2025-05-09
© Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2025

Citation: Jyotirmay ROY, Dipak Ranjan BISWAS, Biraj Bandhu BASAK, Ranjan BHATTACHARYYA, Shrila DAS, Sunanda BISWAS, Renu SINGH, Avijit GHOSH. 2025. Effect of long-term restoration on soil phosphorus transformation and desorption in the semi-arid degraded land, India. Journal of Arid Land, 17(6): 846–864. https://doi.org/10.1007/s40333-025-0101-z; https://cstr.cn/32276.14.JAL.0250101z

1 Introduction

Land degradation severely limits agricultural productivity and ecosystem sustainability. Approximately 33.00% of global land degradation results in a 60.00% decline in ecosystem services \cite{Bardgett et al., 2021}. Unsustainable land use, overpopulation, and poor management systems accelerate degradation, leading to biodiversity loss and declining soil productivity. Restoring nutrient cycles, particularly phosphorus (P), is vital for soil health and recovery of degraded ecosystems, as P is often limited due to fixation by metal oxides \cite{Margenot et al., 2016}. Large-scale land restoration offers a sustainable solution by re-establishing vegetation, stabilizing soils, and increasing soil fertility, microbial diversity, and productivity \cite{Hu et al., 2022; Neffar et al., 2022}. Vegetation recovery improves soil structure, water infiltration, and nutrient cycling through surface litter, root exudates, and rhizodeposition \cite{Bandyopadhyay and Maiti, 2022}.

Vegetative ecosystems are crucial in P cycling, as deep tree roots absorb inorganic P from lower soil depths and transfer it to the upper layer via leaf litter and rhizodeposition \cite{Schaap et al., 2021}. P is a critical nutrient for forest productivity in degraded tropical ecosystems \cite{Yang et al., 2021}, with deficiency caused by strong adsorption of H₂PO₄⁻ onto metal oxides \cite{Chakraborty and Prasad, 2023}. Vegetative land use can increase the P supply by altering P forms, reducing interactions with soil components \cite{Roy et al., 2025}, improving soil physical and chemical characteristics \cite{Cui et al., 2019}, and increasing microbial functioning \cite{Padalia et al., 2022}. Soil enzymatic activities are vital for nutrient cycling and P transformation \cite{Sun et al., 2021}, with plant and microbial community shifts facilitating better access to inorganic P and mineralize organic P \cite{Dai et al., 2020}. The recycling of organic and inorganic P reduces the dependence on external inputs. The afforestation of degraded land can increase topsoil available P (AP), with tree and grass species influencing soil chemistry and metal oxide distribution \cite{Tuyishime et al., 2022}. Understanding P transformation and sorption under restoration practices is essential for identifying appropriate vegetation species for degraded lands.

The transformation of P is principally controlled by pH, dissolved oxygen, organic matter, microbial diversity, metal oxides, and hydroxides \cite{Li et al., 2016}. Strongly acidic and weathered soils are typically dominated by amorphous and crystalline ferrum (Fe)-aluminum (Al) associated P \cite{Chen et al., 2024}. Vegetations impact soil chemistry by lowering pH and enhancing legacy P release \cite{Jin et al., 2022}, while also influencing biological factors such as microbial diversity and phosphatase activity, which affect P mineralization \cite{Fu et al., 2020}. The sorption reactions of P are key to environmental P management and occur in two stages: an initial phase dominated by chemical adsorption and a slower phase characterized by incorporation of P into more stable mineral forms \cite{Barrow, 1980}. Calcite, silicate clay edges, Fe and Al oxides, and organic matter can alter P adsorption on soil surfaces \cite{Mabagala and Mng'ong'o, 2022}. In contrast, P desorption releases immobilized P, making it available for reuse. Both adsorption and desorption mechanisms are crucial in determining P bioavailability.

P fractions are crucial indicators of ecosystem restoration. Vegetative land systems improve P solubilization and mobilization by altering microbial biomass and phosphatase activity \cite{Roy et al., 2025}. Compared with shrubland, natural secondary forests present higher-soluble P and organic P contents, indicating the benefits of forest restoration \cite{Fu et al., 2020}. Similarly, restoring native woody and perennial plants increase both the concentration of P and the ratio of organic P to total P (TP) over abandoned exotic grasslands \cite{Zhong et al., 2021}. Broad-leaved tree systems moderately elevate labile P over plantation systems \cite{Zhu et al., 2021}, and rejuvenated forestry systems outperform pasture systems in terms of labile and moderately labile P \cite{Ferreira et al., 2022}. Vegetative cover also increases available phosphorus (AP) levels, reinforcing the positive role of forest restoration \cite{Chen et al., 2021}. Although a meta-analysis of 217 studies revealed that afforestation significantly increases carbon (C) and nitrogen (N) stocks by 37.00% and 28.00%, respectively, while it has no significant effect on the total phosphorus (TP) stock \cite{Luo et al., 2023}.

According to Yang et al. (2019), organic matter can significantly improve P availability by reducing adsorption sites and promoting release; though some studies reported no direct effect of organic matter on P adsorption \cite{Borggaard et al., 1990; Guan et al., 2006; Yan et al., 2016}. The conflicting results likely reflect differences in soil composition, including soil texture, pH, organic matter composition, and other chemical properties, emphasizing the complexity of P cycling and the need for site-specific management approaches.

Researchers have advanced the understanding of P dynamics in restoration ecosystems, highlighting the roles of vegetation, soil properties, and microbial activities. While afforestation increases labile P fractions, it does not significantly increase the TP stock, as P is derived solely from parent material and is not replenished atmospherically such as C and N. Therefore, assessing whether high-litter and N-fixing tree species can increase soil TP through nutrient pumping, rapid organic matter decomposition rates, and enhanced microbial activity, is crucial. The role of organic matter in P adsorption across soils and the relationships among P fractions, adsorption, and availability remain unclear. This study addressed the research gaps by comparing native N-fixing tree-based restoration systems with fallow land and evaluating impacts on P fractionation, adsorption, and microbial activity. The experimental site, which is degraded by erosion and extreme climates, is rich in Fe and Al oxides that enhance P fixation \cite{Baradwal et al., 2022}. Although silvopastoral land and grassland improve soil quality \cite{Baradwal et al., 2023}, their effects on P distribution are poorly understood.

Investigating P fractions is crucial for identifying P sources and sinks, guiding efficient P management. A deeper understanding of long-term restoration practices on P transformation and desorption is necessary in semi-arid degraded soils.

With this background, we conducted an experiment in the semi-arid degraded land in India under different vegetation-based restoration practices and analyzed soil samples for P fractions, microbial properties, and P adsorption-desorption. This research aims to investigate two issues: (1) how different land restoration measures impact soil P fractions; and (2) whether the land restoration practices could alter soil adsorption-desorption behavior and reduce P fixation.

2.1 Study area

We conducted the study at the institutional farm of the Indian Council of Agricultural Research (ICAR)-Indian Grassland and Fodder Research Institute (IGFRI) in Jhansi City, Bundelkhand Region, Uttar Pradesh State, India (25°31ʹ11ʺ–25°31ʹ28ʺN, 78°32ʹ32ʺ–78°32ʹ53ʺE; 326.4 m a.s.l.). The climate at the experimental site is typically dry, with scorching summers and cold and foggy winters from late November to mid-March. Although the annual average precipitation is approximately 841 mm, 90.00% of the total precipitation occurs during the southwest monsoon season (June–September). The dry season extends from October to May, with very low precipitation (85 mm). This region often experiences irregular precipitation patterns, resulting in intermittent drought episodes. The air temperature ranges from an average daily maximum of 21.4°C in January to 41.6°C in May, with the highest temperature exceeding 47.8°C in summer. The peak mean daily evaporation rate was recorded in June at 12.7 mm/d. The region experiences high wind velocities (>8 km/h) from May to July, leading to significant wind erosion \cite{Baradwal et al., 2023}. The annual soil loss ranges from 37.00 to 53.00 Mg/(hm²·a) \cite{Baradwal et al., 2023}.

The soil at the experimental site belongs to the hypothermic Typic Haplustepts and is yellowish red to dark brown in color. The geological formations consist of gneisses, granites, ferruginous beds, and intrusions of basic igneous rocks \cite{Baradwal et al., 2022}. The nutrient retention and water holding capacity of the soil are considered moderate, with a saturation water holding capacity of 32.50% \cite{Baradwal et al., 2022}. The poor fertility of the soil (soil organic carbon (SOC): 3.49 g/kg; available nitrogen (AN): 82.52 mg/kg, AP: 3.99 mg/kg, and available potassium (AK): 110.34 mg/kg) restricts conventional agriculture and undermines soil productivity \cite{Roy et al., 2025}. Soils are also high in Fe and Al oxides, with average concentrations of 70.01 (±5.52) and 240.11 (±15.25) g/kg, respectively \cite{Roy et al., 2025}.

2.2 Land restoration system

The establishment of tree-based restoration system aimed at rehabilitating degraded lands via sustainable practices, including silviculture system (SCS), silvopasture system (SPS), and hortipasture system (HPS). Native tree seedlings were manually planted after preparing the soil by digging holes to support root establishment. Extensive site preparation included debris removal, vegetation clearing, terrain levelling for uneven water distribution, and plowing to improve aeration and root penetration. In addition to the three restoration systems, we included another two land systems for comparison: natural grassland system (NGS), as a reference representing a natural grassland system and fallow system (FS), as a control representing degraded land. The experiment site selection was based on proper spatial distribution across specific land use systems, avoiding proximity to minimize interactions and allowing independent evaluation of each system's impact on soil P properties (Table 1 [TABLE:1]).

The SCS consists of Leucaena leucocephala (Lam.) de Wit with naturally growing grasses such as Cenchrus ciliaris L., Panicum maximum Jacq., Brachiaria decumbens Stapf, and Heteropogon contortus (L.) P. Beauv. ex Roem. & Schult. (Fig. 1 [FIGURE:1]). The SPS consists of Acacia nilotica (L.) Willd. ex Delile with sown grasses such as P. maximum, Stylosanthes seabrana Vogel, and Chrysopogon fulvus (Spreng.) Chiov. The HPS consists of Emblica officinalis Gaertn with sown grasses such as C. ciliaris, P. maximum, Pennisetum pedicellatum Trin., Cenchrus setigerus Vahl, and B. decumbens.

The tree species selection for the three restoration practices (i.e., the L. leucocephala for SCS, the A. nilotica for SPS, and the E. officinalis for HPS) was on the basis of ecological adaptability, environmental benefits, growth performance, and biodiversity. The primary aim of tree planting was ecological restoration, with no commercial exploitation.

The NGS, reference grassland system, consists of naturally growing grasses such as C. ciliaris, Celosia argentea L., Hyptis suaveolens (L.) Poit., Acanthospermum hispidum DC., and Eragrostis cilianensis (All.) Vignolo ex Janch. Indian semi-arid natural grasslands are savanna type (i.e., 10.00%–20.00% area is covered by trees in scattered manner). Vegetation-based restoration practices were compared with FS, which has similar climate, topography, elevation, and soil origin. The FS plots, which have been undisturbed since 1980, serve as long-term control for evaluating ecosystem recovery, with no interventions such as fertilization, irrigation, or planting. The natural vegetation in FS is sparse and consists mainly of hedges and bushes. Therefore, we assumed FS to be devoid of significant vegetation, with no influence on soil P properties, providing a baseline for comparing the influences of restoration practices on P dynamics. Before restoration, SCS, SPS, HPS, and NGS were identical to FS.

2.3 Soil sampling

In December 2022, we collected soil samples from each land system to assess the soil chemical properties and nutrient dynamics. We sampled at three depths: 0–15, 15–30, and 30–45 cm. We subdivided each plot into 8 subplots (30.0 m×30.0 m), spaced at 50.0 m apart to reduce spatial bias. Then, we collected 8 replicates at each depth interval within each plot to ensure robust representation and minimize variability, totalling 120 soil samples. Each replicate was collected from each subplot. We chose all the sampling points on the basis of soil homogeneity, slope, and tree density (considering tree density for the three tree-based restoration system SCS, SPS, and HPS). We separated each sample into two subsets: one subset experienced air-dried, pulverized, and sieved (2 mm) for chemical analysis, and the other subset was refrigerated at 4.0°C for microbial biomass and enzymatic activity assessment.

2.4 Soil chemical and microbial properties

In this study, we determined the soil pH via a 0.010 M CaCl₂ suspension and measured it with a Systronics 361 pH meter (Systronics, Ahmedabad, India) \cite{Schofield and Taylor, 1955}. We also measured electrical conductivity (EC) by preparing a 1:2.5 soil-to-water ratio supernatant and measuring it with a Systronics 306 digital EC meter (Systronics, Ahmedabad, India) \cite{Jackson, 1973}. This study employed the Walkley and Black (1934) method to estimate SOC, where K₂Cr₂O₇ oxidizes SOC in the presence of concentrated H₂SO₄, and the unreacted dichromate is titrated to ferrous ammonium sulfate (FAS) to determine SOC content. We determined AN by extracting NO₃⁻ + NH₄⁺ ions using a KCl solution \cite{Jackson, 1973}. We extracted AK with 1.000 M ammonium acetate (pH=7.00), shaken, filtered, and analyzed with a Systronics 128 flame photometer (Systronics, Ahmedabad, India) \cite{Hanway and Heidel, 1952}.

We measured dehydrogenase (DHA) activity by incubating 1.0 g of soil with 2,3,5-triphenyltetrazolium chloride (TTC) and glucose solutions at 27.0°C for 24 h, followed by methanol extraction and measuring the absorbance at 485 nm with a Systronics 167 spectrophotometer (Systronics, Ahmedabad, India) \cite{Casida et al., 1964}. Additionally, we determined acid phosphatase (ACP) and alkaline phosphatase (ALP) activities by incubating 1.0 g of soil with nitrophenol phosphate in Modified Universal Buffer (MUB) at pH=6.50 and 11.00, respectively, at 37.0°C for 1 h. After incubation, we added 0.500 M CaCl₂ and 0.500 M NaOH, and measured the absorbance at 440 nm \cite{Tabatabai, 1994}. We measured microbial biomass carbon (MBC) by fumigating one set of 10.0 g soil samples with chloroform and extracting fumigated and unfumigated sets with 0.500 M K₂SO₄. Then, we digested the extracts with concentrated H₂SO₄ in presence of K₂Cr₂O₇ and titrated the unreacted K₂Cr₂O₇ with 0.005 M FAS. The MBC extraction efficiency of K₂SO₄ from soil was accounted by using a correction factor of 0.45 \cite{Vance et al., 1987}. We determined the microbial biomass phosphorus (MBP) by fumigating one set of 10.0 g soil samples with chloroform and extracting both fumigated and unfumigated sets using 0.500 M NaHCO₃ at pH=8.50. The MBP extraction efficiency of NaHCO₃ from soil was accounted by using a correction factor of 0.40 \cite{Brookes et al., 1982}. We measured the absorbance of MBP at 730 nm with Systronics 167 spectrophotometer.

2.5 P fraction

This study employed the sequential inorganic P fractionation scheme \cite{Kuo, 1996}, which includes soluble and loosely bound phosphorus (Sal-P), Al-associated phosphorus (Al-P), Fe-associated phosphorus (Fe-P), Ca-associated phosphorus (Ca-P), and reductant soluble phosphorus (Res-P) (Table 2 [TABLE:2]). We chose this scheme because of its efficiency and suitability for semi-arid soils in the study area, where P availability is severely influenced by Fe and Al oxides. This method can effectively separate Fe-P and Al-P, which serve as critical indicators of P cycling in degraded and restored ecosystems. We estimated TP using the microwave digestion method, as detailed by \cite{Page et al., 1982}. We also determined organic P by taking the TP content of soil and subtracting the combined inorganic P fractions \cite{Zhang and Kovar, 2009}. This study employed the Bray and Kurtz (1945) method to measure AP. This method involves an acid fluoride extraction (0.030 M NH₄F in 0.025 M HCl) to release P from soil. The Systronics 167 spectrophotometer was used to measure the P concentration in the extract at 730 nm \cite{Murphy and Riley, 1962}.

2.6 P adsorption

We selected the soil samples from 0–15 cm layer of each land system for P adsorption and desorption research, as the soil at this layer is the most active zone for nutrient cycling, and the majority of root activity and microbial processes occur in this layer \cite{Roy et al., 2025}. Deeper layers (15–30 and 30–45 cm) are generally less involved in the P sorption processes, as they are outside the primary zone of root interference and biological activity.

We added 3.0 g of soil to 50 mL centrifuge tubes in the P adsorption experiment. This process involved adding a solution of 0.010 M CaCl₂ and varying P concentrations (5, 10, 20, 30, 40, 50, 60, and 80 mg/L) along with two drops of toluene to achieve a 1:10 soil to solution ratio. Then, we shook the tubes for 24 h at 25.0°C and centrifuged at 10,000 r/min for 10 min. Next, we transferred 25 mL of the supernatant from centrifuge tubes for P analysis using the ascorbic acid method through Systronics 167 spectrophotometer at 730 nm \cite{Murphy and Riley, 1962}. The calculation of P adsorbed by the soil involved subtracting the remaining P in the equilibrium solution from the initial amount added. To evaluate the P adsorption characteristics of the soils in different ecosystems, we applied two isotherm models. The Langmuir model assumes monolayer adsorption on a finite number of homogeneous sites, making it useful for estimating maximum adsorption capacity. The Freundlich model is empirical and better suited for heterogeneous surfaces with variable adsorption energies.

The Langmuir linear equation can be expressed mathematically by the following equation \cite{Langmuir, 1918}:

$$\frac{C}{X} = \frac{1}{b \times k} + \frac{C}{b}$$

where C is the equilibrium phosphorus concentration (mg/L); X is the phosphorus adsorbed per unit mass of soil (µg/g); b is the maximum phosphorus adsorption capacity (µg/g); k is the phosphorus binding affinity (mL/µg); and y is the maximum phosphorus buffering capacity (mL/g).

The Freundlich linear equation can be represented mathematically by the following equation \cite{Freundlich, 1907}:

$$\log(X) = \log(a) + n \times \log(C)$$

where a is the number of phosphorus adsorption sites; and n is the phosphorus bonding energy.

2.7 P desorption

For the desorption study, soil samples previously equilibrated with the highest P concentration from the adsorption study (80 mg/L) served to examine P release. The process began by decanting 25 mL of the supernatant and replacing it with 0.010 M CaCl₂ solution to simulate natural soil solution conditions. Then centrifuge tubes were shaken for 6 h and centrifuged at 10,000 r/min for 10 min. After that, we collected 25 mL of the supernatant for P analysis. Lastly, we measured the desorbed P concentration with Systronics 167 spectrophotometer at 730 nm \cite{Murphy and Riley, 1962}. The desorption process was repeated three times, as no significant amount of P was released thereafter \cite{Roy et al., 2025}.

$$P_r = P_a - P_d$$

where P_r is the amount of P retained in the soil (mg/kg); P_a is the amount of P initially adsorbed during the adsorption phase (mg/kg); and P_d is the amount of P desorbed during the desorption phase (mg/kg).

2.8 Measurement of aboveground biomass, litterfall, and root biomass

We estimated aboveground biomass in tree-based restoration systems (i.e., SCS, SPS, and HPS) non-destructively using allometric equations. We measured tree height and diameter at breast height for all individuals within randomly selected subplots \cite{Chave et al., 2014}. In other land systems (i.e., NGS and FS), we estimated aboveground biomass by clipping all herbaceous vegetation within 1 m² quadrats and oven-drying the samples at 65°C to constant weight \cite{Anderson and Ingram, 1993}. We collected the litterfall using litter traps (0.5 m×0.5 m) placed randomly within each subplot and oven-dried the collections at 60°C \cite{Hairiah et al., 2001}. Traps were emptied monthly over a 12-month period. We determined root biomass by extracting soil cores using a 10 cm diameter soil sampler (Precision Balance, Kolkata, India). After sieving and hand-sorting, the roots were separated with soil; and then the roots were washed and oven-dried at 65°C until constant weight \cite{Bohm, 1979; Jackson et al., 1997}.

2.9 Statistical analysis

This study evaluated the statistical significance of the impacts of the various land restoration systems on soil characteristics using a one-way analysis of variance (ANOVA) within a randomized block experimental design. We identified differences among treatments using the Duncan post-hoc test. A structural equation model was adopted to evaluate the direct and indirect effects of soil chemical properties, microbial activities, and P adsorption parameters on P dynamics across all kinds of land systems. The structural equation model included four latent variables: soil chemical properties (pH, EC, SOC, AN, and AK), soil microbial parameters (DHA activity, ACP activity, ALP activity, MBC, and MBP), soil P fractions (Sal-P, Al-P, Fe-P, Res-P, Ca-P, organic P, AP, and TP), and P adsorption properties (maximum phosphorus buffering capacity, number of phosphorus adsorption sites, maximum phosphorus adsorption capacity, phosphorus bonding energy, and phosphorus binding affinity). We estimated the path coefficients by using maximum likelihood estimation. All variables were z-standardized (mean=0.000, standard deviation (SD)=1.000) prior to analysis to obtain standardized path coefficients. Only paths with P<0.05 were retained in the final model. We evaluated the model's adequacy using the χ² test, goodness of fit (GIF), and root mean squared error of approximation (RMSEA). In this study, the standard of a good model fit was set as P<0.05, GIF>0.90, and RMSEA<0.080. The SPSS v.29.0 software (International Business Machines Corporation, Armonk, USA) performed all the statistical analyses.

3.1 Soil chemical property and nutrient availability

Soil pH across the different land systems was slightly acidic, ranging between 4.60 and 5.90. Across all depths, the pH values for SCS, SPS, and HPS were significantly higher over FS (Table 3 [TABLE:3]). In the case of EC, FS showed a lower EC value than SCS, SPS, HPS, and NGS across all depths. The SOC within the 0–45 cm soil layer varied between 1.56 and 9.05 g/kg, with a decreasing pattern as soil depth increased. The SCS showed 4.50-, 3.29-, and 2.78-fold increase than FS in SOC at 0–15, 15–30, and 30–45 cm soil depths, respectively. Moreover, SCS showed 99.42%, 91.36%, and 89.56% higher AN than FS at 0–15, 15–30, and 30–45 cm soil depths, respectively. Meanwhile, SPS showed 85.62%, 91.36%, and 89.62% higher AN than FS at 0–15, 15–30, and 30–45 cm soil depths, respectively. The AK was the highest in SCS and the lowest in SPS. Both the NGS and HPS could not increase AK content over FS at 15–30 and 30–45 cm soil depths. Nutrient availability was higher at soil depth of 0–15 cm than at 15–45 cm.

3.2 Soil biological parameter

Microbial parameters showed a significant improvement across different restoration practices as compared with FS (Table 4 [TABLE:4]). Also, similar to nutrient, the biological parameters exhibited the highest content or activity at 0–15 cm soil depth than at 15–30 and 30–45 cm soil depths. The DHA activity exhibited the highest in SCS, followed by SPS, which was statistically similar to HPS and NGS across respective soil depths. The SCS obtained 2.48 and 1.99 times higher DHA activity than FS at 0–15 and 15–30 cm soil depths, respectively. The lowest DHA activity was observed in FS. For various land systems, ACP activity was higher than ALP activity. The ACP activity was the highest in SCS, which was 3.15-, 4.16-, and 5.91-fold higher than FS at 0–15, 15–30, and 30–45 cm soil depths, respectively. The SCS, SPS, and HPS showed 4.83-, 2.71-, and 2.76-fold increase in ALP activity than FS, respectively, at 0–15 cm soil depth. The SCS, SPS, and HPS showed significant increases in MBC content than FS. At 0–15 cm soil depth, SCS and SPS obtained 116.69% and 87.94% increments in MBC content than FS, respectively. Also, at 15–30 cm soil depth, SCS, SPS, and HPS showed 124.38%, 96.49%, and 106.66% increments than FS, respectively. The NGS increased 59.50% and 59.29% in MBC content than FS at 0–15 and 15–30 cm soil depths, respectively. The SCS, SPS, and HPS increased 98.65%, 84.20%, and 26.19% in MBP content than FS, respectively, at 0–15 cm soil depth. The highest MBP content was contained by SCS, followed by SPS and HPS. The HPS and NGS obtained the lowest increment in MBP content, statistically similar to FS.

3.3 P fraction

The proportion of different P fractions under various restoration practices followed this order: Sal-P (16.30%–27.68%)