Introduction

Soil is a vital reservoir of essential nutrients for terrestrial organisms, playing a crucial role in water conservation, organism activity, and diversity. The maintenance of soil fertility is critical for promoting ecosystem stability and regulating climate change1. Moreover, studying the various forms of soil carbon (C) and nitrogen (N) is important for enhancing our understanding of nutrient cycling in terrestrial ecosystems2, which is critical for maintaining soil quality3 and ecosystem health4. Research has shown that during forest ecosystem restoration, the coupling relationship between soil C and N transitions from stable to unstable development, particularly in deep soil layers5,6. The natural restoration of forests or grasslands by the abandonment of farming activity improves the stability and adaptability of these areas further then when compared to artificial restoration through the planting of vegetation. Natural restoration also effectively maintains the coupling relationship between shallow and deep soil C and N7.

Ecosystem multi-functionality (EMF) refers to the ability of an ecosystem to simultaneously provide ecological services and support various forms of biodiversity8. Evaluating multi-functionality is crucial in developing effective conservation and management measures to protect biological, biogeochemical, and physical processes9,10. The species composition of converted farmland is critical as it impacts both the quantity and quality of plant growth, which in turn depends on the environment and soil11. Changes in soil composition will alter its structure and properties, affect soil enzyme cycling, and ultimately influence soil EMF12.

The remediation of land through different restoration patterns has been explored, particularly as it relates to land degradation mitigation and the sustainability of soil C and N13,14. Widespread implementation of the “Grain for Green” project has directed increasing attention towards above-ground vegetation and soil quality, making them focal points of academic research. It has become clear that assessments of soil characteristics in response to the conversion of farmland to natural areas is essential for designing and implementing more sustainable practices15,16. Studies on the ecological effects of farmland conversion have focused predominantly on the restoration of vegetation following various conversion strategies17 and on the soil nutrients carbon, nitrogen and phosphorus. However, our understanding of other nutrient forms, particularly the relationships between soil nutrients and EMF, remains limited18,19. Therefore, a more comprehensive evaluation of the influences of different patterns on soil nutrient functions (i.e. the various forms of C and N), as well as soil EMF in the topsoil, is needed.

The karst peak-depression is a prevalent geomorphic found in southwest China. The region’s karst landscape is particularly susceptible to soil degradation due to its unique geological conditions and fragile ecosystems20,21. The long-term and intense internal dissolution processes have resulted in a distinctive dual structure characterized by hidden regional soils with limited development, sparse and shallow soil cover, and significant erosion of soil and water nutrients. Consequently, land productivity has declined, leading to extensive rocky desertification. Therefore, ecological restoration, reconstruction efforts, and increased biomass and vegetation coverage in karst regions is urgently needed4. The restoration of vegetation can lead to improvements in soil function and ecological environment22. However, there is limited research available on the extent to which land quality and function have been improved. Therefore, further research on the interaction and balance between soil C and N will enhance our understanding of vegetation-soil interactions, nutrient cycling, and the benefits associated with vegetation restoration.

Here, we conducted field investigations to assess the impact of 7 different farmland conversion strategies on soil quality, using farmed maize crop as a reference. Our objectives were to: (i) study the distribution of soil carbon and nitrogen under different farmland conversion patterns, (ii) determine the effects of different farmland conversion patterns on soil EMF, and (iii) evaluate the major soil nutrient factors that influence soil EMF. We hypothesized that (i) converting farmland to forest or grassland would enhance the sequestration of soil carbon and nitrogen, and (ii) converting farmland to forest or grassland would improve soil multi-functionality.

Results

Soil carbon properties

The total carbon (TC) content in the different patterns of returning farmland, including GM, GZ, ZI, TS, CM, and AC species, was significantly higher compared to the maize crop controls (Fig. 1a). The TC content in afforestation land patterns (containing ZI, TS, CM, AC) was significantly higher than that in the grassland pattern (P < 0.05). Among the reforestation patterns, the AC pattern had the highest TC content, measuring 28.22 g kg−1. The variation in soil organic carbon (SOC) content followed a similar trend to TC among all the land conversion patterns (Fig. 1b). The SOC content in the CM pattern was highest, reaching 26.25 g kg−1 (Fig. 1b). Furthermore, dissolved organic carbon (DOC) content in the different land conversion patterns were significantly higher than in maize crop (Fig. 1c). All patterns showed significant differences in DOC compared to maize crop (P < 0.05), with the ZI pattern having the highest DOC content.

Figure 1
figure 1

Forms of carbon under different patterns of converted farmland. Error bars correspond to the standard deviation. Letters indicate significant differences among patterns of converted farmland (one-way ANOVA, P < 0.05). TC total carbon, SOC soil organic carbon, AOC active organic carbon.

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Based on the separation of different active soil organic carbon (SOC) components, three components of active organic carbon (AOC) were identified and analyzed (Fig. 1d-f). Overall, the content of the three AOC components decreased significantly from very labile carbon concentration (4.88–10.33 g kg−1) to less labile carbon concentration (2.23–3.49 g kg−1). The content of AOCVL in the different patterns of converted farmland, except the AC pattern, was significantly higher than that of maize crop. The content of AOCL showed a similar trend to AOCLL. Both the afforestation land and abandoned land patterns had significantly higher AOCL and AOCLL compared to the grassland pattern and maize crop. However, no significant difference was observed between the grassland pattern and maize crop (P > 0.05).

Soil nitrogen properties

The TN content of soil from afforestation land and abandoned land was significantly higher than that of grassland and maize crop (P < 0.05). However, there was no significant difference between grassland and maize crop (P > 0.05). Among afforestation land patterns, the TN content was highest in the AC pattern (2.66 g kg−1; Fig. 2a). AN variation between different patterns of converted farmland showed similar results to TN (Fig. 2b), with a significant difference between grassland and afforestation land (P < 0.05), and the AN content was highest in the CM pattern (163.87 mg kg−1) within afforestation land. Overall, TN and AN content were significantly different from maize crop in the afforestation land, but not in grassland.

Figure 2
figure 2

Forms of nitrogen under different patterns of converted farmland. Error bars correspond to the standard deviation. Letters indicate significant differences among different patterns of converted farmland (one-way ANOVA, P < 0.05). TN total nitrogen, AN available nitrogen, NO3–N soil nitrate, NH4 + -N soil ammonium.

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Soil nitrate (NO3--N) content was highest in abandoned land (144.02 mg kg−1), which was significantly different from other land conversion strategies (P < 0.05, Fig. 2c). However, the nitrate content of grassland was significantly higher than that of afforestation land (P < 0.05). The AC pattern had the lowest nitrate content (24.92 mg kg−1). Soil ammonium (NH4+-N) content was highest in the ZI pattern (152.17 mg kg−1), and significantly different from other patterns (P < 0.05, Fig. 2d). Maize crop had the lowest ammonium content (34.61 mg kg−1), while the ZI pattern had the highest (152.17 mg kg−1).

Soil multi-functionality

Ecosystem multi-functionality (EMF) is an overall indicator of soil functional services and found to be strongly influenced by the conversion of farmland to natural ecosystems. The soil EMF of afforestation land showed significant differences compared to the grassland and maize crop (P < 0.05), with a 40.24–86.76% higher EMF than maize crop, wherein the evergreen AC pattern showing the most significant increase (Fig. 3a). The multi-functionality index for carbon followed a similar pattern to soil EMF (Fig. 3b), with afforestation and abandoned land showing greater multi-functionality for carbon compared to grassland and maize crop. By contrast, the multi-functionality index for nitrogen was greater in afforestation land, grassland, and abandoned land compared to maize crop (P < 0.05), but was most pronounced in grassland and afforestation land, with a 111.36–168.24% and 77.73% higher value than that of maize crop, respectively (Fig. 3c).

Figure 3
figure 3

Effects of agroforestry on soil multi-functionality and multi-functionality for carbon and nitrogen under differentfarmland conversion strategies. Letters indicate significant differences among patterns of converted farmland (one-way ANOVA, P < 0.05).

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Each approach to farmland-to-forest conversion had a different impact on soil surface biochemical properties (Fig. 4). Measures of TC, SOC, DOC, AOCVL, AOCL, TN, and AN content showed a significant increase in the topsoil of afforestation land. This indicates that the conversion of farmland to forest can improve soil carbon and nitrogen content. Pearson correlation analysis revealed that out of the 12 soil factors examined, 6 of them showed highly significant correlations with EMF (Fig. 5, P < 0.05). These relationships suggest that TC, SOC, AOCL, AOCLL, TN, AN soil factors play a crucial role in influencing the ecosystem multi-functionality. Specifically, most soil factors exhibited a positive correlation with EMF, except for NO3--N, which did not show a significant correlation.

Figure 4
figure 4

Radar graph shows the relative responses of soil biochemical properties to different farmland conversion patterns.

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Figure 5
figure 5

Pearson correlation among soil factors and soil multi-functionality (EMF). *p < 0.05, **p < 0.01, ***p < 0.001.

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In Fig. 6, the Random Forest pattern was used to estimate the contributions of different soil indices to ecosystem multi-functionality (EMF). We found that the Random Forest pattern was able to explain 95% of the variation in soil EMF. The main factors contributing to EMF were identified to be AOCL, SOC, TN, AN and TC. According to these results, carbon (represented by AOCL, SOC and TC) accounted for the largest proportion of the contribution to EMF, representing 59.48% of the total variation. Nitrogen (represented by AN and TN) accounted for 32.07% of the variation.

Figure 6
figure 6

Random Forest mean predictor importance (%increase in MSE) of soil factors on EMF. Significance levels of each predictor are as follows: *P < 0.05, **P < 0.01.

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Discussion

The fragility of karst soil in comparison to non-karst soil is primarily attributed to differences in soil formation mechanisms and structural composition23. The results of our study indicate that farmland converted to afforestation land or abandoned land exhibited significantly higher TC and SOC content than when converted to grassland. These findings suggest that during the recovery process, afforestation and abandoned land are more conducive to SOC accumulation compared to grassland24,25. Research has also revealed differences in soil organic carbon sequestration between natural restoration patterns (abandonment) and artificial restoration patterns. The content of topsoil organic carbon is closely related to the accumulation of decomposed litter and biomass26. As a result, reforestation patterns exhibit better organic carbon sequestration27. These findings highlight the importance of afforestation and reforestation efforts in promoting soil organic carbon accumulation and overall ecological restoration in karst areas.

Our results suggested that the various reforestation patterns had different mechanisms of surface soil C accumulation. For instance, vegetation in afforestation land, such as Zenia insignis, Toona sinensis, Castanea mollissima, and Acer cinnamomifolium, plays a role in nutrient release to the soil through biochemical pathways28,29. Among these patterns, the AC pattern, characterized by evergreen species, demonstrates a more prominent effect. The AC pattern exhibits higher plant coverage, maintains a high level of root biomass, and facilitates the decomposition of surface vegetation litter, releasing a large amount of nutrient elements required for plant growth30. This further supports the notion that artificial restoration patterns are more beneficial for soil nutrient retention than naturally abandoned karst areas. The differences in carbon sequestration among the various conversion patterns can be explained by several factors. Firstly, lower fertilizer inputs following the conversion of farmland may slow down carbon sequestration31. Secondly, the accumulation of SOC differs depending on the trees planted after the conversion32. The decomposition of plant litter and the subsequent return of nutrients to the soil contribute to this process. Lastly, in grassland patterns, regular crop harvesting may limit carbon inputs to the soil. A meta-analysis has confirmed the time lag between plant production and SOC accumulation following afforestation33.

We found significant increases in total nitrogen (TN) and available nitrogen (AN) content after afforestation or abandonment, with values ranging from 47.35% to 98.03% greater and 58.42% to 89.04% greater, for TN and AN, respectively, compared to maize crop. The variation in soil nitrogen (N) is influenced by both N inputs and outputs. In the karst ecosystems following farmland conversion, sources of N inputs include plant litter, biological N fixation, atmospheric N deposition, and weathering of N-rich bedrock, except for maize crop which receives artificial nitrogen fertilization34. The demand for N is usually higher during the active growth phase of forests before canopy closure35,36. However, at later stages, when the input of N is sufficient to compensate for the output of soil N, the N requirement of converted farmland is reduced. As a result, the difference in TN may not be substantial among different plant species in afforestation land. It is worth noting that nitrogen loss was greater in afforestation land, grassland, and the maize crop. This nutrient loss is exacerbated by the fractured soil structure and high rainfall conditions in the karst regions of southwestern China37. Additionally, maize crop and the harvest of pasture in grassland contributes to soil nutrient loss. Therefore, the accumulation of soil N following the conversion of farmland in karst regions can be primarily attributed to reduced soil N outputs and increased N inputs.

Afforestation and abandonment are two distinct approaches to ecosystem remediation that exhibit different soil nitrogen profiles. Variation in management practices, microclimate, species composition, and root quantity and quality between these two restoration strategies may explain this38,39,40. In our study, TN and AN did not show significant differences across the various patterns of converted farmland or abandoned land. However, the ratio of NO3--N in abandoned land was significantly higher compared to the different patterns of returning farmland. On the other hand, the content of NH4+-N was most significant in the ZI conversion pattern, which was 339.75% higher than maize crop. C4 plants, under similar environmental conditions, all exhibit higher nitrogen use efficiency (NUE), resulting in NO3--N accumulation in their leaves compared to C3 plants. The GM pattern showed greater NO3--N content compared to other reforestation patterns, and the corn (C4 plant) content was also higher than that of reforestation patterns (except for ZI and TS). This suggests that different plant species may have varying capacities for NO3--N accumulation. C4 plants can assimilate NH4+-N in mesophyll cells and vascular sheath cells to synthesize amino acids and proteins, contributing to their higher NUE. However, nitrogen reduction in C3 plants occurs only in mesophyll cells, resulting in low NUE. Therefore, reforestation patterns exhibited higher NH4+-N content compared to maize (Fig. 2c). It is important to note that the high nitrogen input from external nitrogen fertilizer applications can lead to high NH4+-N content in herbage and corn. However, due to the harvest of corn fruits and other factors, the increase in NH4+-N content is lower compared to herbage, which could explain the observed differences in NH4+-N content between the two.

The recognition and application of multi-functionality indices in ecological systems has been increasing in various research fields41,42. However, there is a lack of understanding about which conversion practice (afforestation or grassland) and environmental condition is optimal, particularly in terms of restoring soil multi-functionality, which is of great concern. Our results showed that the effects of agroforestry on soil multi-functionality vary across different patterns of converted farmland. The impact of the conversion pattern on soil versatility is influenced by the presence of grassland and the specific species used in afforestation and forest return. Additionally, the multi-functionality of soil for carbon and nitrogen in different patterns of returning farmland demonstrates close interactions. These results highlight the importance of considering specific conversion patterns, including afforestation land and grassland, as well as the selection of appropriate species for afforestation, when aiming to optimize soil multi-functionality. Further research is needed to better understand the relationships between conversion patterns, climate conditions, and the achievement of optimal soil multi-functionality in different patterns of converted farmland.

Previous studies have provided evidence that the differences in nutrient uptake, canopy structure, and litter quality among different vegetation types in various patterns of returning farmland can have diverse effects on soil multi-functionality for carbon and nitrogen11. Our study found that soil multi-functionality in afforestation land was significantly higher than that in grassland or maize crop. This could attributed to the stronger rhizosphere effect of afforestation land, which leads to improved soil structure stabilization and reduced loss of soil nutrient elements caused by different vegetation types43. Additionally, the developed roots of returning vegetation in afforestation land may have a higher turnover rate, resulting in higher soil C and N content44. In contrast, the maize crop, which involved foreign fertilization and crop harvest, exhibited adverse reactions in the soil, leading to the loss of soil C and N content. The GZ pattern, which combined forest return and grassland return, showed intermediate soil nutrient retention capacity as compared to pure afforestation land and grassland conversion strategies. Further studies are needed to determine whether this pattern can effectively promote the growth of above-ground vegetation. The abandonment pattern demonstrated significantly higher soil nutrient retention compared to the maize crop and grassland patterns, although it did not differ significantly from afforestation land. The abandonment pattern represents a state of self-repair, with minimal external input and output, and less external interference. This finding supports the notion that abandonment can also serve as a good natural restoration pattern for returning farmland.

The project to return farmland to forest is an important measure in sustainable land management and plays a crucial role in rehabilitating and restoring degraded land45,46. In this study, we observed that different patterns of returning farmland have different effects on soil EMF and multi-functionality for C and N. In particular, different species exhibited significant differences in the reforestation pattern, with the ZI treatment showing the highest multi-functionality for C and N. This could be attributed to species-specific characteristics such as water capture ability and competition effects47. Different species may have different abilities to capture water, leading to variations in their competitive interactions. Additionally, the presence of species with deeper root distributions resulting from below-ground competition may contribute to a decline in the rate of carbon and nutrient accumulation in the topsoil13,48. The deeper root distribution of various species in different returning farmland patterns can promote the above-ground input of organic matter, leading to the production of DOC that can be transported to deeper soil layers and contribute to subsoil carbon storage48. Furthermore, soil multi-functionality in different patterns of returning farmland can be influenced by the quantity and quality of litter49. Different species, especially large trees, can have diverse effects on soil space through shading and other mechanisms, which can result in a decline in C and N inputs into the soil11,50.

The application of afforestation land promoted soil EMF, while grassland did not have a significant effect (Fig. 3). Above-ground vegetation plays a crucial role in influencing soil biochemical characteristics through its growth, biomass accumulation, root absorption, and litter accumulation, thereby enhancing soil versatility19. In our study, vegetation roots and litter from converted farmland to forest species increased access to soil nutrients, promoting the cyclic metabolism of soil nutrients and ultimately enhancing soil EMF. Random forest analysis confirmed that AOCL, SOC, TN, AN and TC were the main drivers of soil EMF (Fig. 6). Soil with higher C and N availabilities support diverse biogeochemical cycles, enzyme production, and nutrient cycling, leading to improved ecological functions19,51. This is further supported by the observation that C and N were the main drivers of soil EMF (Fig. 3ab). Most soil nutrients showed positive correlation with soil EMF (Fig. 4), indicating that various abiotic factors, such as available nutrients, collectively or individually mediate their influence on soil EMF in agricultural soils. A microenvironment with higher C and N can activate microbes, increase their richness and diversity, and create microbial hotspots involved in soil organic matter decomposition and nutrient recycling, further enhancing soil EMF. Moreover, the accumulation of carbon and nitrogen in the soil resulting from different species after afforestation land can promote multiple ecosystems functions.

The overall effect of afforestation land was found to be better than that of grassland in different patterns of converting farmland, and the ZI pattern of afforestation land exhibited particularly positive effects on sustaining soil EMF. However, it is important to recognize that soil function is influenced by multiple factors, including the specific patterns and species within different patterns of returning farmland, root systems, litter, soil chemistry, biodiversity (bacteria, fungi, etc.), and physical properties. These factors interact and contribute to the overall functioning of the soil ecosystem. To gain a comprehensive understanding of the mechanisms underlying the positive effects induced by different patterns of returning farmland on soil, further multi-scale studies are necessary. Such studies can help analyze the complex relationships between the various factors and their impacts on soil functioning. Overall, these findings contribute to our understanding of the effects of different vegetation types and patterns of returning farmland on soil multi-functionality, highlighting the potential benefits of afforestation, grassland, and abandonment patterns in terms of soil nutrient retention and ecosystem restoration.

Conclusions

The returning of farmland to forest and grassland has proven to be an important strategy for addressing land degradation. Our analysis of the soil in different types of converted land revealed that afforestation and abandoned lands contained higher levels of carbon and nitrogen compared to grasslands and maize crop land, reflecting high soil quality. However, grasslands exhibited higher NO3--N and NH4+-N soil content compared to afforestation land, and all converted land patterns had higher contents of these forms of nitrogen compared to maize crop controls. Afforestation and abandoned land showed enhanced soil ecosystem multi-functionality compared to the maize crop controls, and reflecting a positive effect on the ecological functions of soil. Thus, our studies reveal that multiple land conversion strategies can restore soil nutrient quality and ecosystem multi-functionality. The evergreen species Acer camphora demonstrated the best performance during the returning of farmland to forest, while abandoned land also proved to be a valuable natural conversion pattern. These findings underscore the importance of implementing an appropriate strategy for converting farmland in a manner that maximizes soil nutrient retention and enhances overall ecosystem functioning.

Materials and methods

Study area

The study site was located in the Guzhou Village (24°44′–25°33′ N, 107°55′–108°43′ E), located in the karst area of Maonan Autonomous Region, Huanjiang County, northwest Guangxi Zhuang Autonomous Region, southwest China. The village is situated at an altitude ranging from 375 to 816 m. The area features a typical karst peak-depression landscape with a subtropical monsoon climate. The annual average temperature ranges from 16.5 to 20.5 ℃, and the average rainfall is approximately 1389 mm. The rainy season lasts for around 130–140 days, while the frost-free period extends for about 290 days each year. The dominant soil type in the area is calcareous lime soil with carbonate rock. The soil depth in the depressions is shallow, with some areas as thin as 10 cm, and exposed stones are widespread.

In the study area there is a noticeable trend of rocky desertification due to soil erosion, making the ecological environment extremely fragile. Prior to the 1980s, the research area experienced significant disturbance from farming and logging activities. Beginning in 1996, some residents began relocating, and the policy of “afforestation land and grassland” was implemented, which further affected the sloping farmlands. The Huanjiang Karst Experimental Station initiated a project in 1999 to implement afforestation and grassland practices, where various ecosystem conversion patterns were applied to the tillage lands in the depressions and hillslopes, including converting farmland to grassland, afforestation land, grassland and afforestation land combined, abandoned land, and maize crop plots. With the introduction of the ‘Grain for Green’ project in 2002, more tillage lands in the depression and hillslopes were converted into forage or natural grasslands and plantation forests. Additionally, pockets of tillage land abandoned in the 1950s and 1980s and have naturally regenerated to shrub lands and secondary forests.

Experimental design and soil sampling

We carefully selected eight types of conversion patterns (experimental treatments) for our study. The first pattern was the conversion of farmland to grassland, where Guimu-1 elephant grass (GM) was planted (Pennisetum americanum (L.) × Pennisetum purpureum Schumach) and ploughed every 5 years, fertilized with inorganic fertilizers and farm manure. Typically, the grass was harvested 3–5 times per year and used as fodder for beef production. The second pattern involved returning farmland to a combination of forest and grassland. Guimu-1 elephant grass and Zenia insignis (GZ) were planted to establish this pattern. The third to sixth patterns involved areas that had undergone deforestation and cultivation before their protection in 1959 and had naturally recovered to form new secondary forests. The dominant tree species in these forests included Zenia insignis (ZI), Toona sinensis (TS), Castanea mollissima (CM), and Acer cinnamomifolium (AC). The seventh pattern was abandonment fields (AB), which were previously cultivated but left undisturbed before the 1980s. We also included a control area where Zea mays Linn. (ZL), also known as maize farmland. Since the forage grasslands and plantation forests (planted after the abandonment of tillage land) have been affected by human activity, they are considered to be “managed vegetation restoration”. By contrast, the natural grasslands, shrublands, and secondary forests (regenerated naturally following the abandonment of tillage lands) have experienced little human disturbance for at least 9 years and are considered “natural vegetation restoration” (Table 1).

Table 1 Vegetation types and characteristics of plots surveyed in the present study.
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The experiment adopted a randomized block design with eight treatments and three replicates, resulting in 24 plots of 400 m2 (20 × 20 m). The sampling plots were strategically located along the contour line of the middle and lower slope, where the slopes and aspects were similar across plots. Field sampling was carried out in June 2022. The topsoil (0–15 cm) was collected with soil corer at 10 points within each plot. Stones and roots were carefully removed using forceps, and the soil sample was air-dried and sieved through 20 and 100 mesh sieves to measure its physical and chemical properties.

Laboratory analysis

Methods for extraction and analysis of soil chemistry parameters are detailed in a previous study6. In brief, after weighing the soil samples, carbon (C) and nitrogen (N) content were determined using an elemental analyzer. An inductively coupled plasma emission spectrometer was used to measure calcium (Ca) and magnesium (Mg)52. Soil organic carbon (SOC) content was determined by the heating oxidation method of potassium dichromate potassium dichromate (K2Cr2O7) in an oil bath. Soluble organic carbon (DOC) was evaluated by a total organic carbon analyzer53. Soil active organic carbon (AOC) was determined by potassium permanganate oxidation at three different concentrations to assess varying levels of oxidation: 33 mmol L−1, 167 mmol L−1, and 333 mmol L−1. Thus, AOC measurements were divided into three categories: very labile carbon (AOCVL) at 33 mmol L−1, labile carbon (AOCL) at 167 mmol L−1, and less labile carbon (AOCLL) at 333 mmol L−1. Nitrate nitrogen (NO3--N) and ammonium nitrogen (NH4+-N) levels were determined using an auto-analyzer (FIAstar 5000; FOSS Tecator, Höganäs, Sweden), which involved initial soil extraction using 2 M KCl (10 g soil to 50 mL KCl) followed by measurement with an automated system. Total phosphorous (TP) was determined by HClO4–H2SO4 digestion followed by the Mo–Sb colorimetric method. Available phosphorous (AP) was measured by NaHCO3 extraction-molybdenum antimony chromo-UV spectrophotometry. Total potassium (TK) was determined using the NaOH melting-atomic absorption method, available nitrogen (AN) was determined by diffusion absorption assay, and available potassium (AK) was determined by the NH4Ac extraction-atomic absorption method.

Quantifying soil multi-functionality

To obtain soil a multi-functionality index (EMF) for each plot, we calculated the Z-scores for each soil variable (TC, SOC, DOC, AOCVL, AOCL, AOCLL, TN, AN, NO3--N, NH4+-N, Ca, Mg) and averaged Z-scores to represent EMF. The Z-score described in Eq. (1) was used to standardize soil indices after averaging to acquire a multi-functionality index based on the methods described54,55. We also tested multi-functionality for carbon (C EMF) and nitrogen (N EMF) variables separately56.

$${\text{Z - score}}\,{ = }\,\left( {\text{x - meani}} \right){\text{/SDi}}$$
(1)

where x is the measured soil variables, mean is the average of soil variables i, and SD is the standard deviation of soil variables i.

Statistical analysis

All data were subjected to a one-way analysis of variance (ANOVA) followed by Fisher’s Least Significant Difference (LSD) test to determine significant differences (P < 0.05) among the various afforestation land and grassland conversion patterns. Prior to conducting the analysis, the normality and homogeneity of variance were tested using the Shapiro–Wilk’s test. Statistical analyses were performed using IBM SPSS Statistics software version 26.0. To examine the relationships between soil indices and soil EMF, Pearson correlations were calculated using the “corrplot” package in R (Version 4.1.2). Rhe “Random Forest” package in R was employed to identify the main factors influencing soil EMF among the various soil factors.