Introduction

In recent years, fast changes in land-use and cropping systems in the Lesser Himalayas of India (600–2000 m above mean sea level) (Ram et al. 2013) are being witnessed due to a combination of several factors, including increased demographic pressure (Vision 2050, VPKAS 2015). This has resulted high demand for food, fodder, fuel wood and shelter along with much increased industrial activities. The region is endowed with diverse vegetation at altitudes, but acidic soil properties in the region often limit the biomass production. One of the major reasons of decreased biomass productivity is less P availability, due to its fixation in these acidic soils (Khan et al. 2007). Phosphorus fixation and precipitation in soils are generally highly dependent on pH and soil type. Low pH in hills leads to fixation of applied P in arable systems due to high activities of Al and Fe (Bucher et al. 2001).

Microorganisms are also involved in a variety of processes that affect the transformation of soil P. They enhance the P availability to plants by mineralizing organic P in soils and by solubilizing precipitated phosphates (Chen et al. 2006). Thus, management of P solubilizing microorganisms in soils plays a significant role to improve P availability. Furthermore the release of P by phosphate solubilizing microbes from insoluble and fixed/adsorbed forms is extremely important for P availability in soils. Microorganisms increase the availability of native P for plants through a variety of mechanisms, like the release of organic acids and hydrogen ions, production of siderophores and phosphatase enzymes to hydrolyze soil organic P (Surange et al. 1995; Dutton and Evans 1996; Nahas 1996).

To understand P availability, research is needed particularly on the potential phosphate solubilizing organisms, which are environmental friendly and economically feasible to farmers.

The hilly and mountainous areas in India vastly distributed all over the country with a larger area located in the Himalayas, extending up to 2500 km in length and 250–400 km in breadth and is distributed in 23 states. The majority of these areas (35% of the total geographical area of the country) has > 15% slope (Barah 2010). Himalayas having 90% forest and 10% arable land are capable of supporting production of a number of crops, because of varied agro-climatic conditions. Soils of the diverse agro-eco systems of the Indian Himalayas harbor a diverse group of adaptable and potential phosphate solubilizers that can be utilized for making agriculture sustainable in the region (Tomer et al. 2017). However, in recent times, the environmental degradation (due to faster deforestation, unrestricted grazing and destruction of vegetation) poses a threat to hill agriculture (Das et al. 2016).

Many studies in plain lands have confirmed that changes in land cover have an impact on soil biological properties and nutrient cycling, consequently affecting the organic P content (Aguiar et al. 2013; Maranguit et al. 2017; Prakash et al. 2017; Von Sperber et al. 2017). Soil enzyme activities are affected by change in soil management practices and land uses in plain lands (Li et al. 2014; Tian et al. 2016; van Leeuwen et al. 2017). However, limited information is available on the impacts of land use on soil P fractions and P cycling enzymes in the hilly regions, especially in the Indian Himalayas. Hence, the hypothesis was that soil P fractions would differ under different land use systems and management practices in arable systems. The present study aims to investigate oxidizable soil organic C, P fractions and P cycling enzyme activities in 0–15 and 15–30 cm soil layers and to quantify relationships between P cycling enzymes and selected soil chemical properties (CEC, pH, organic C and different P fractions) of different land use systems of Almora district of Uttarakhand, located in Lesser Himalayas of India.

Materials and methods

Site description and soil sampling

All soil samples were collected from different land use systems (viz, uncultivated barren land, organic farming plot, maize–wheat cropping system, undisturbed oak forest and apple orchard) at the Hawalbagh experimental farm (29º36′N, 79º40′E, and altitude: 1250 m amsl), ICAR-Vivekananda Parvatiya Krishi Anusandhan Sansthan (VPKAS; In English: Vivekananda Institute of Hill Agriculture), located in the Indian Himalayas (http://www.vpkas.nic.in/) (Fig. 1). The map presented in Fig. 1 has been prepared with the help of Arc map 10.1 using GIS (Geographic Information System) tool. The Hawalbagh farm is about 13 km away from Almora, Uttarakhand. The climate of the region is sub-temperate, characterized by a moderate summer (May–June), extreme winter (Dec–Jan) and the southwest monsoon season (June–September) (Bhattacharyya et al. 2011). The precipitation ranges from 1000 to 1150 mm and the mean precipitation of the area is 1047 mm (mean of 30 years) (Bhattacharya et al. 2008). Precipitation increases soil moisture content that aids in soil organic matter decomposition process when temperature is optimum. During extreme winter, temperature becomes sub-optimal and gets snowfall at high altitudes. The main crops grown in these areas are wheat (Triticum aestivum L.), rice (Oryza sativa), barley (Hordeum vulgare L.), red kidney bean (Rajma; Phaseolus vulgaris) and black soyabean (Gycine max Merr.) (Bhattacharya et al. 2008). Taxonomically the soils of the study area is Typic Haplaquept (Ram et al. 2013). The agriculture in the area depends mainly on precipitation. The cropping and vegetation pattern of different land use systems are mentioned in Table 1.

Fig. 1
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Location of different land use systems

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Table 1 Description of different land use systems
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Soil collection

The soil samples of two different depths (0–15 cm and 15–30 cm) were collected from all five different land use systems. Three composite soil samples were collected from each site for each depth. For making one composite sample, at least five soil cores were collected and pooled. Each sample was divided into two parts; first part of which was stored in refrigerator at 4 °C for determination of P cycling enzyme activities, and the second part was processed for other selected chemical analyses as detailed below. These samples were first air- dried in shade, ground with wooden pestle and mortar, and passed through a 2 mm sieve. After grinding by wooden pastle, the samples were preserved in plastic containers for analyses.

Soil chemical analysis

Soil samples were analyzed for pH in a soil:solution of 1:2.5, using a glass electrode (Jackson 1973); oxidizable soil organic C (SOC) following Walkley and Black (Walkley and Black 1934); available P following Olsen et al. (Olsen et al. 1954); mechanical composition of experimental soils i.e., proportion of sand, silt and clay size particles following hydrometer method (Bouyoucos 1962) and cation exchange capacity (CEC) of the soil following ammonium acetate method as described by Jackson (1973). Total P (TP) in soils was determined by digestion method (Olsen and Sommers 1982); total organic P (Po) by ignition method (Saunders and Williams 1955; Walker and Adams 1958); inorganic P (Pi) content by subtracting organic P from total P in the sample; microbial biomass P (MBP) following the method proposed by Brookes et al. (1982). For estimation of available P, acidic soil was extracted with Bray’s P-I (Bray and Kurtz 1945) reagent and alkaline soil was extracted with 0.5 M NaHCO3 (Olsen et al. 1954). Physico-chemical characteristics of surface as well as sub-surface soil are given in Table 2.

Table 2 General characteristics of the surface soil (0–15 cm) and sub-surface (15–30 cm) soil in different land use systems (each value is the mean of triplicate soil samples)
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Analyses of soil biological properties

Enzymatic assay

Soil enzymes namely phosphatase (acid and alkaline) and phytase activities were assessed in the collected soil samples. Phosphatase activity was assayed by the method of Tabatabai and Bremner (1969) using substrate p-nitrophenyl phosphate and phytase activity by the method of Ames (1966).

Microbial population count

Serial dilution and plating technique was employed for enumerating the microbial population of soils as described by Rolf and Bakken (1987) and Chhonkar et al. (2007). Indigenous phosphate solubilizing bacteria was isolated from soil samples by enrichment culture techniques (Gaind and Gaur 1991) amended with 5% Mussourie rock phosphate (MRP). Phosphate solubilizing fungi was enumerated in rhizosphere soil samples by dilution plate count technique in Pikovskaya’s agar medium (Ndiaye et al. 2000), modified by adding filter sterilized streptomycin (0.003%) and rose bengal (0.007%), to inhibit bacterial growth.

Detection of the phosphate solubilization ability of microorganisms

Phosphate solubilizing ability of microorganisms was detected using plate-screening method, in which, phosphate solubilizers produce clearing zones around the microbial colonies in media, and these were isolated (Pikovskaya 1948). Then, colonies were isolated and was put in petri-plates containing Pikovskaya’s agar medium along with bromo-phenol blue, which produced yellow halos following a pH drop.

Statistical analysis

Data were assessed by Duncan’s multiple range tests (P < 0.05). Differences between mean values were evaluated by a two-way analysis of variance (ANOVA) (Gomez and Gomez 1984), using the software SAS 9.1.3. Pearson correlation analyses were performed using the SPSS programme (SPSS version 16.0).

Result and discussion

Soil P fractions

Total P

Mean of total P for 0–15 and 15–30 cm soil layers for all land use systems varied significantly (P < 0.05). Soils (0–15 and 15–30 cm layers) under oak forest (3405 kg ha−1) had the highest TP followed by organic farming (2783 kg P ha−1), and the lowest was in soils under uncultivated land (Fig. 2a). Similar type of results were obtained by Prakash et al. (2017), who observed significantly higher total P fractions in agroforestry system than maize–wheat and cotton-wheat cropping systems (Prakash et al. 2017). The study clearly revealed that surface soil (0–15 cm) had higher TP than sub surface soil (15–30 cm) by 12.4, 18.6, 19.9, 23.9 and 7.4% for uncultivated barren land, apple plantation, oak forest, organic farming and maize–wheat, respectively. Among major nutrients, P is the least mobile element. This is one of the main reasons for its low availability in the 15–30 cm soil layer, as organic matter inputs and fertilizer application activities are done at soil surface.

Fig. 2
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a Total P (kg ha−1), b total inorganic P (kg ha−1), c total organic P (kg ha−1), d available P (kg ha−1) in soils under two depths as influenced by different land use systems in the Lesser Himalayan region of India. Bars with different letters are significant at P < 0.05, according to DMRT

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Total inorganic P

Mean of Pi under different land use systems varied from 1137 to 2764 kg ha−1 in the 0–15 cm soil layer (Fig. 2b). Soils (0–15 cm) under organic farming contained more Pi (2457 kg ha−1) than both apple plantation (1686 kg ha−1) and maize–wheat (2227 kg ha−1). Significantly lower proportion of Pi in soils under apple plantation may be due to relatively lower fertilizer P application than the other land-uses (Table 1) and higher uptake of P by apple trees (Prakash et al. 2017). Another reason might be immobilization of P in the apple rhizosphere by microorganisms for their structural build up to mineralize the organic residues added into the soil (Xavier et al. 2011). All land use systems showed significant differences in Pi in the 0–15 cm depth, whereas the differences were non-significant in the 15–30 cm depth. Surface soil contained significantly higher Pi than sub-surface soil and the differences were 12.3, 22.8, 25.7 and 6.2% for barren land, oak forest, organic farming and maize–wheat, respectively. Only soils under apple plantation and uncultivated land had similar Pi in surface and sub-surface soils.

Total organic P

Organic phosphorus (Po) content varied widely in the 0–15 cm soil layer under different land use systems (Fig. 2c). Surface soil contained 13.2, 99.2, 8.9, 12.2 and 19.7% higher Po than sub-surface soil (15–30 cm) for barren land, apple plantation, oak forest, organic farming and maize–wheat, respectively. The Po in the 0–15 cm depth layer followed the order: apple plantation > oak forest > organic farming > maize–wheat > barren land. Continuous deposition of root and leaf litters on the surface and the reduced tillage makes the forest and apple plantation soil richer in terms of Po than plots under organic farming (which is only 15 years old and cultivated) (Lobato et al. 2014). On the other hand, barren land without planting remained low in terms of Po.

Available P

Mean data of available P content showed wide variations (from 5.9 kg ha−1 in barren land to 48.7 kg ha−1 in oak forest) under different land use systems in the soil surface (Fig. 2d). Oak forest had the highest available P, followed by apple plantation (45.6 kg ha−1). Soils under oak forest, apple plantation, organic farming and maize–wheat system contained 721, 669, 333 and 295% more available P, respectively, than uncultivated land in the 0–15 cm surface soil. Available P content for surface soil in all land use systems were in the moderate to high range (Singh et al. 2005). However, for sub-surface soil, it was in the medium range. Possibly swift rates of P cycling in oak forest at surface via decomposition and the mineralization of more P rich litter helps to maintain greater concentrations of available P in the forest system (Bunemann et al. 2004), until uptake and accumulation in living biomass and leaching removes P from this cycle.

Microbial biomass P

Microbial biomass P (MBP) showed wide variations under different land use systems. Mean data of MBP varied from 2.5 (uncultivated land) to 27.1 µg P g−1 soil (oak forest) in soil surface (Fig. 3a). Organic farming system showed ~ 31% higher MBP than apple plantation (14.7 µg P g−1 soil) in soil surface. Surface soils contained 29, 84, 33, 75 and 339% higher MBP than sub-surface soils for barren land, apple plantation, oak forest, organic farming and maize–wheat, respectively.

Fig. 3
figure 3

a Microbial biomass P (kg ha−1), b ratio of microbial P to total P (%), c ratio of microbial P to organic P (%) in soils under two depths as influenced by different land use systems in the Lesser Himalayan region of India. Bars with different letters are significant at P < 0.05, according to DMRT

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Oak forest system had highest microbial P to total P ratio than the other land use systems (Fig. 3b). But, in the sub-surface layer, the ratio became more in soils under uncultivated land than the maize–wheat system. The significance of the microbial biomass as a pool for organic P is apparent from the microbial P to organic P ratios. Ratio of microbial P to organic P under different land use systems varied from 1.7 to 6.0% in the 0–15 cm soil (Fig. 3c). Soils under organic farming were having more ratio than apple plantation, oak forest and maize–wheat. All land use systems showed significant differences in the ratio in both depths. In apple plantation, P application near to apple tree along with FYM might have resulted in multiplication of microbes, which is known to swiftly immobilize substantial amounts of P when labile C is easily available (Silveira et al. 2010). Litter inputs and chemical composition of the litter may be crucial driver to alter the soil P concentrations in oak forest due to natural litter-fall and its recycling. Highest MBP in oak forest might be due to the deciduous nature of such type of forest. This enables microorganisms to decompose easily the leaf-litters, which are low in alkaloid content and easy to assimilate more and more P. It is also possible that the P mineralized was immediately fixed by the soil microbial community (Silveira et al. 2010) and also it can be attributed to nutrient pumping effect of trees bringing the nutrients from lower soil horizons, which are redistributed to the surface soil through leaf fall (Farley and Kelly 2004).

P cycling enzyme activities

Mean data of acid phosphatase activity in the surface soil layer ranged from 90.1 µg PNP g−1 h−1 in the uncultivated land to 310.8 µg PNP g−1 h−1 in soils under organic farming system (Fig. 4a). All land use systems showed higher acid phosphatase activity in the 0–15 cm depth and a significant decrease in lower depth (15–30 cm) was observed. Thus, the acid phosphatase activities under different land use systems in the 0–30 cm soil depth (pooled data of two layers) followed the order: Organic farming > apple plantation > maize–wheat > oak forest > barren land. In the present investigation, acid phosphatase activity was found to be much higher than the alkaline phosphatase activity. This is due to the acidic reaction of the soils. Previous studies also verified that the phosphatase activity was strongly affected by soil pH (Mandal et al. 2007). Usually higher plants and microorganisms lack alkaline phosphatase (Kramer and Green 2000). Okur et al. (2009) reported that improved activity of soil enzymes in organic soils with FYM was due to the effects of increased organic C concentration in these soils on the size of the soil microbial population (Böhme and Böhme 2006). Masto et al. (2006) similarly reported that FYM addition to soil aids for C source, greater microbial biomass and phosphatase activity. Acid phosphatase activity was more in those systems, which received manure and it was supported by Saha et al. (2008) and Haynes and Swift (1988), who reported decreased acid phosphatase activity of soils with fertilization.

Fig. 4
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Depth-wise distribution of a acid phosphatase activity, b alkaline phosphatase activity and c phytase activity in soils under different land use systems. Bars with different lowercase letters are significant at P < 0.05, according to DMRT

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The average alkaline phosphatase activity ranged from 10.1 µg PNP g−1 h−1 in the uncultivated land to 140.2 µg PNP g−1 h−1 in soils under organic farming system (Fig. 4b). Alkaline phosphatase activities under different land use systems in the 0–15 cm soil depth followed the order: organic farming > oak forest > apple plantation > maize–wheat > barren land. The significantly greater activities of alkaline phosphatase in the organic farming systems and forests were due to enhanced microbial activity and diversity caused by organic matter inputs over the years. Manure addition to soils changes the persistence of soil enzymes (Parham et al. 2002). The decreased activities of both enzymes with increasing depth may be due to the declined microbial activity with depth. The declined activity with depth was highest in case of maize–wheat cropping system. This may be due to decreased rhizospheric effect with small increase in soil depth. Population of PSM was highest in oak forest system. This is in agreement with earlier studies conducted in Garhwal Himalayas, where the number of potential PSM varied depending on the soil characteristics, and the highest number was in oak forest (Pal 1998).

Oak forest system had higher phytase activity than apple plantation, organic farming and maize–wheat system (Fig. 4c) in the surface soil layer. All land use systems showed higher phytase activity in the 0–15 cm soil depth and the activity significantly decreased with increasing depth. The phytase activities under different land use systems in the 0–30 cm soil depth followed the order: oak forest > apple plantation > organic farming > maize–wheat > barren land. Phytases play an important role in the mineralization of P. Phytic acid is the prime storage form of P in many seeds and pollen (Mega 1982). Phytase is important in mobilizing organic P reserves for the growing seedlings and pollen germination (Walker 1974). The overall phytase activity is higher in oak forest followed by other land use systems. The forest system can be compared to a no-till condition, which promotes storage of water and nutrients in soils (Havlin et al. 1990), but also increased phytase activities, thereby increasing the P cycling in soils. This is supported by the results showing that microbial growth is favored in this kind of soil environment, resulting in greater enzyme activities (Dick 1994).

P solubilizing microorganisms

Population of phosphate solubilizing microorganisms (PSM) has been recorded from their growth on the culture media in petri-plates (Fig. 5). In the surface soil, PSB counts of apple plantation system (83 × 103 CFU g−1 soil) and organic farming system (85 × 103 CFU g−1 soil) were similar, but that was greater than maize–wheat and uncultivated land (Table 3). All land use systems showed higher PSB counts in the 0–15 cm layer and a significantly decreased in the lower layer.

Fig. 5
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Appearance of colonies of different groups of phosphate solubilizing microorganisms on Pikovskaya’s agar plate (selective medium) in soils (0–15 cm depth) of different land use systems of the north-western Indian Himalayan region

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Table 3 Total phosphate solubilizing bacteria (PSB) and phosphate solubilizing fungi (PSF) population in soils under different land use systems in the north-western Indian Himalayan region
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The average PSF count ranged from 4.1 × 103 CFU g−1 soil in barren land to 30 × 103 CFU g−1 soil in oak forest in surface soil layer (Table 3). Organic farming system (28 × 103 CFU g−1 soil) had higher PSF count than maize–wheat system (17 × 103 CFU g−1 soil) and apple plantation (10 × 103 CFU g−1 soil). Organic matter addition in the form of green manure fertilization increased the fungal biomass as well as its diversity in the soil, when compared with chemical fertilizer addition (Kataoka et al. 2017). Therefore, the variations of PSF in different soils may be due to differences in organic matter contents in different ecosystems. The reasons for higher PSMs in the apple plantation systems is not clear from this study, thus warrants further investigation.

Relationships among soil P fractions, P cycling enzymes and P solubilizing bacteria

Correlation studies of soil enzyme activities with soil P fractions have shown a significant relationship (P < 0.01) between soil P fractions and enzyme activities, excepting for alkaline phosphatase in surface soils (Tables 4, 5). Soil bacteria, actinomycetes, and fungi hydrolyze organic P compounds and release phosphatases there. The enzyme activities significantly correlated with each other. Soil P fractions were significantly correlated with acid phosphatase, phytase and dehydrogenase in soil surface. Microbial biomass P was significantly correlated with all enzyme activities and other P fractions at both soil depths. Phosphate solubilizing bacteria and fungi were significantly correlated with enzyme activities, except for alkaline phosphatase in the surface soil; reasons being all studied soils were acidic. PSB is highly correlated with P fractions in both depths and significant correlation between acid phosphatase activity and organic P was observed. The results are very similar to the findings observed by Tarafdar and Jungk (1987) in wheat and clover rhizospheric soils. Acid phosphatase and total P content in different land use systems were significantly correlated. These results are in agreement with the earlier findings by Gianfreda et al. (2005). Soil P was apparently related closely to soil phosphatase activity. Generally soil microorganisms and plants produce extracellular phosphatase, which mineralizes and organically bound P and when available P is deficient in soils, micro-biota increase the production of extracellular phosphatase to enhance supply of inorganic P. However, higher P concentration inhibits the organisms to produce phosphatase enzyme. Such relationship has been explained that soil P supply and phosphatase activities were regulated by the negative feedback mechanisms (Olander and Vitousek 2000).

Table 4 Pearson correlation matrix among P solubilizing organisms, P pools and soil enzyme activities in the surface soil (0–15 cm layer) under different land uses
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Table 5 Pearson correlation matrix among P solubilizing organisms, P pools and enzyme activities in the 15–30 cm soil layer under different land uses
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Conclusions

Thus, all P fractions viz., total P, inorganic P, organic P, available P and microbial biomass P in soils were significantly affected by different land uses. Changes in enzyme activities in different systems were much higher than P fractions, indicating that enzymes activities are much more sensitive to land use changes. Soils under Oak forest were best in terms of having the enzyme activities, P fractions and PSB. Regularly manured apple orchard and organic farming were next to oak forest. Correlation matrices among different parameters of enzyme activities, P pools and PSM were positive, indicating that these were strongly associated in soils irrespective of land use and crop management practices. A good population of PSM has been observed almost in all systems. Thus, this study has generated information on the extent of P pools, enzyme activities and P solubilizers of different land use systems of Almora district of Uttarakhand, located in the Lesser Himalayas of India. Further research may concentrate on impacts of other land use systems on soil P dynamics in winter and summer seasons of the Indian Himalayas with sampling in more area. Also there is need for isolation and identification of PSM in this area to provide information of new species, which may have high potential to enhance P solubilization from the fixed or mineral- P in the acid soils of the region, and subsequent use as P-biofertilizers.