1 Introduction

In an effort to address current ecological concerns, large-scale national projects have been implemented in China over the decades to restore degraded land, primarily through afforestation and reforestation (Zhang et al. 2000). Currently, 31.8%, or 62 million hectares, of forest area in China is planted forest, which is the most of any country in the world (State Forest Administration 2010). The ecological environment has considerably improved through the afforestation. However, it has been recognized that monocultures and unreasonable stand structure of planted forests have inevitable disadvantages, which include low biodiversity, poor stress-resistance and stability, and forest degradation as compared to natural forests (Zhang et al. 2000; Shi et al. 2013). To overcome these disadvantages and improve ecosystem functioning of planted forests, near-natural transformations of planted forests have been implemented in many regions of the world (Lu 2006). This new silvicultural system transforms planted forests into near-native forests according to natural forest succession processes that are designed specifically to enhance biodiversity, improve forest structure, sustain ecosystem functions (diversity, productivity and nutrient cycling), and identifies sustainable levels of use for a broad range of renewable resources (Nakamura et al. 2005; Zhang et al. 2000).

Current management practices used to implement near-natural transformations of planted forests include selective logging (He et al. 2013; Luo et al. 2013), thereby creating gaps (Rouvinen and Kouki 2011; Wang and Liu 2011), and encouraging the establishment of broad-leaved species in mixtures with conifers. The broadleaved trees used in this process are primarily native species (Lu 2006). The near-natural transformation of conifer planted forests can change the composition and structure of forests and enhance biodiversity as has been shown for Pinus massoniana Lamb. (Luo et al. 2013), Cryptomeria japonica (Thunb. ex L. f.) D. Don (Taki et al. 2010), Cunninghamia lanceolata (Lamb.) Hook. (He et al. 2013), and Pinus tabuliformis Carrière (Wang and Liu 2011) plantations.

P. tabuliformis is the main afforestation tree species in large areas north of the Yangtze River basin, and it is also distributed in Japan, Korea, and parts of Russia (Shi et al. 2013). This predominance makes the near-natural transformation of P. tabuliformis forest important. Recently, through the management methods of selective logging and gap creation, the composition, structure, and diversity of P. tabuliformis forests have been improved significantly (Ning et al. 2009; Wang and Liu 2011). How the composition, structure, and diversity of P. tabuliformis planted forests change after 60 years of natural development is not well documented.

Moreover, only a few studies have considered how stand conversion influence soil physical and chemical properties, and microbial communities in these near-natural forests. Soil microorganisms play a key role in the cycling of nutrients and decomposition of soil organic matter in soil ecosystems and are one of the most studied indicators of soil quality (Ritz et al. 2009). One factor that strongly influences soil microbial communities is litter quality (Sayer 2006). A change in litter quality can affect the population dynamics and community structure of soil microorganisms by altering the supply of nutrients, affecting the microclimate and pH at the soil surface, and releasing chemical compounds (Hättenschwiler et al. 2005; Wardle et al. 2006; Sayer 2006; Zhao et al. 2013). Therefore, the effects of changes in litter quality [e.g., carbon (C), nitrogen (N), phosphorus (P), C/N ratio] on soil physicochemical properties, microbial biomass, and community structure were included as part of this investigation.

This study was conducted in the Baxian Mountain National Nature Reserve in North China. The predominant tree species in the secondary forest included Quercus mongolica Fisch. ex Ledeb., Quercus variabilis Blume, Quercus aliena Blume, Juglans mandshurica Maxim., and Carpinus turczaninowii Hance amongst others, whereas P. tabuliformis (planted in the 1950s) was the primary species in the planted forest. After decades of natural development, broadleaved tree species have appeared in the P. tabuliformis forest, forming a coniferous-broadleaved mixed forest (near-natural forest). We tested the effect of increasing proportions of broadleaf tree species on species diversity, nutrient content of the forest floor and soil, and the soil microbial community during 60 years of natural development of P. tabuliformis planted forests. We hypothesized that species diversity, nutrient contents of the forest floor and soil, and soil microbial biomass in the near-natural forests would be higher than in the planted forests, but still lower than in the secondary forest.

2 Materials and methods

2.1 Site description

The study was carried out at the Baxian Mountain National Nature Reserve (117°30′35″–117°36′24″E, 40°7′24″– 40°13′53″N, 270–1052 m a.s.l) in Tianjin, China. The total area covers 5360 ha. The region has a warm, humid continental monsoon climate. The mean annual temperature and precipitation are 8–10 °C and 968.5 mm, respectively. The dominant parent soil material in this area is meso- and neo-proterozoic dolomite and limestone. The typical soils are classified as Eutric Cambisols at the middle mountain area and as Chromic Cambisols at the lower mountain area according to the FAO Taxonomy (FAO-UNESCO 1988). The original forest vegetation in this area was dominated by deciduous broad-leaved forest of a warm temperate zone. However, excessive human activities, such as overgrazing and woodcutting, have caused severe depletions of the original vegetation. According to reserve records and personal communication with retirees, the vegetation in the area was poor, characterized by shrubs (Vitex negundo var. heterophylla (Franch.) Rehder and Ziziphus jujuba var. spinosa (Bunge) H.H. Hu ex H.F. Chow) with scattered small trees, before afforestation and protection. Large areas of P. tabuliformis forests were planted in the 1950s and subsequently protected. In addition, the government implemented the Natural Forest Conservation Program (NFCP) over the last 20 years (Zhang et al. 2000). Currently, the vegetation has largely been replaced by naturally regenerated secondary forest and planted woodland. In addition, some near-natural forests have formed through native development.

2.2 Investigation and sampling

Three forest types were selected for this study that was conducted in September 2014 (Table 1). We established five, six, and six plots respectively in a random design, in a P. tabuliformis forest, a coniferous-broadleaved P. tabuliformis mixed forest, and a Q. mongolica forest. Each plot covered an area of 0.06 ha (20 m × 30 m). The 20 m × 30 m plot was composed of six quadrants, each with a 10 m × 10 m area. Trees within plots that had a diameter at breast height (DBH, 1.3 m) of ≥3 cm were recorded. Diagonal two of the established six quadrants were selected for shrub layer measurement, and a subplot (1 m × 1 m) were randomly established for herbaceous layer measurement in each quadrant. Data collected in each plot included plant species, height, diameter at breast height (trees), basal diameter (shrubs), and coverage (herbs).

Here to after, forest floor refers to the litter and unincorporated humus above the mineral soil. Forest floor samples [encompassing the litter (L) and the fermentation and humus (FH) horizons] were collected from six sites within each plot. Each site measured 20 cm × 20 cm and was located at the center of each quadrant. The two horizons (L and FH) were collected separately. Mineral soil samples were collected from beneath the forest floor at depths of 0–10 cm and 10–20 cm using a stainless steel cylinder (100 cm³). Six forest floor samples and mineral soil from the same horizon for each plot were combined to form one composite sample. Forest floor samples were oven-dried at 65 °C for 72 h, ground, and analyzed for the C, N and P. A portion of the soil samples, from which stones and large plant residues were removed, was frozen at –20 °C prior to phospholipid fatty acid (PLFA) analysis. Another sample was air-dried, sieved through 2 mm mesh, and stored at 4 ℃ for soil parameter analyses.

2.3 Sample analysis

Carbon and nitrogen concentrations of the forest floor and mineral soil samples were measured using a dry combustion method with a Vario EL elemental analyzer (Vario MAX C/N, Elemental Co., Germany). Phosphorus concentration was measured by molybdate colorimetry after digestion by HNO₃-HClO₄; the cation exchange capacity (CEC) was determined by EDTA-CH₃COONH₄ exchange; Soil bulk density was determined using core method following the methods of the Institute of Soil Science (1978). Soil pH was measured with a combination electrode (soil-to-water ratio 1:5). The PLFAs were analyzed with a gas chromatograph (Agilent 7890N GC with an Agilent 5975N mass selective detector) as described by Cao et al. (2014). Concentrations of each PLFA were standardized relative to 19:0 internal reference concentrations. Bacteria biomass was represented by (14:0, 15:0, 16:0, 17:0, 18:0, 20:0, G+, G-), Gram+ bacteria biomass by (i15:0, i16:0, i17:0), Gram- bacteria biomass by (16:1w7c, 18:1w5c, cy17:0, cy19:0), and fungal biomass by (18:1w9c, 18:2w6,9) (Frostegård et al. 1991, 2011; Marshall et al. 2011).

2.4 Statistical analysis

Standing tree volume was determined by the experimental form factor according to Wu (1992). The important value (IV) for each tree species was calculated as (relative density + relative dominance + relative frequency) / 3 and the IV for shrub and herb species was determined as (relative height + relative coverage + relative frequency) / 3. The dominant species and important values (IVs) in three forests were presented in Table 2. Calculation of vascular plant diversity index [the Richness index (S): Species in the plots, Shannon-Wiener index Simpson index and Pielou index important value of specie i (i = 1,2,3…)] were carried out as described by Fang et al. (2009). To test the significance of the findings, all data were analyzed with one-way ANOVAs. Microbial community composition were analyzed using principal component analysis (PCA) (Zhao et al. 2011, 2013). Data were transformed (natural log, square root, or rank), when required to meet assumptions of normality and homogeneity of variance. Statistical significance was determined at p < 0.05. ANOVAs and PCA were performed with SPSS 19.0 (Chicago, IL, USA). A Duncan’s test was used to determine differences among treatment means.

3 Results

3.1 Tree, shrub and herb species diversity index

Richness of trees, shrubs, and herbs in the coniferous-broadleaved P. tabuliformis mixed forest and the Q. mongolica forest was higher than in the P. tabuliformis forest (Table 3). The Shannon-Wiener index and Simpson index of trees, shrubs, and herbs showed similar trends with Richness. In contrast to the species diversity indices, the evenness index (Pielou index) for herbs in the P. tabuliformis forest was higher than it was in the other two forests, while this was not the case for tree species in this forest.

3.2 Concentrations and contents of C, N, and P and C/N ratio of the forest floor and mineral soil

Carbon and nutrient concentrations of the forest floor and mineral soil were presented in Table 4. In the L-horizon, the C, N, and P concentrations and C/N ratio differed between the forests. The C concentration and C/N ratio of the coniferous-broadleaved P. tabuliformis mixed forest were significantly lower than those of the P. tabuliformis forest, whereas the N and P concentrations were the highest in the coniferous-broadleaved P. tabuliformis mixed forest (p < 0.001; p = 0.010). In the FH-horizons, the C concentration did not differ between forests (p = 0.207). The N concentration in the coniferous-broadleaved P. tabuliformis mixed forest was the highest of all the forests (p = 0.007), resulting in a lower C/N ratio. The P concentration in the P. tabuliformis forest was significantly higher than in the other two forests (p = 0.005). Overall, from the L-horizon to the FH-horizons, the C and P concentrations and C/N ratio decreased between forests, but the N concentration increased. However, the C, N and P content of forest floor decreased in the following order: P. tabuliformis forest > coniferous-broadleaved P. tabuliformis mixed forest > Q. mongolica forest (p < 0.001; p = 0.003; p = 0.002) (Fig. 1).

Fig. 1. Bars marked with different lowercase letters represent significant difference at the forest floor layer under different forest types at the 0.05 level (Duncan test). Bars marked with different uppercase letters represent significant difference at the mineral soil layer (0–20 cm soil depth) under different forest types at the 0.05 level (Duncan test).
Ⅰ: Pinus tabuliformis forest, Ⅱ: coniferous-broadleaved P. tabuliformis mixed forest, Ⅲ: Quercus mongolica forest.

The C, N, and P concentrations in the upper mineral soil of the coniferous-broadleaved P. tabuliformis forest did not differ from the Q. mongolica forest (except for the P concentration at a soil depth of 10–20 cm), but they were significantly higher than those of the P. tabuliformis forests. The C/N ratio did not differ between forests at a 0–10 cm soil depth (p = 0.921). At a depth of 10–20 cm, the C/N ratio did not differ between the coniferous-broadleaved P. tabuliformis mixed forest and the P. tabuliformis forest, but were significantly lower than that of the Q. mongolica forest (p = 0.013). However, the C, N, and P contents of mineral soil increased in the following order: P. tabuliformis forest < coniferous-broadleaved P. tabuliformis mixed forest < Q. mongolica forest (p < 0.001; p < 0.001; p = 0.008) (Fig. 1). The C, N and P contents of mineral soil did not differ between the coniferous-broadleaved P. tabuliformis mixed forest and the Q. mongolica forest.

3.3 Soil CEC, pH, and bulk density

In the Q. mongolica forest and the coniferous-broadleaved P. tabuliformis mixed forest, CEC was the highest in the 0–10 cm and 10–20 cm soil depths, respectively (p < 0.001) (Fig. 2). CEC was significantly lower in the P. tabuliformis forest than in the other two forests at the 0–10 cm soil depth. Soil pH was significantly higher in the coniferous-broadleaved P. tabuliformis mixed forest than in the other two forests (p < 0.001). The bulk density increased in the following order: coniferous-broadleaved P. tabuliformis mixed forest < Q. mongolica forest < P. tabuliformis forest at the 0–10 cm soil depth (p < 0.001), and were not significantly different between forests at the 10–20 cm soil depth.

Fig. 2. Cation exchange capacity (CEC), pH, and bulk density in two soil depths under different forest types. Bars marked with the same letters are not significantly different from each other at the 0.05 level (Duncan test).
Ⅰ: Pinus tabuliformis forest, Ⅱ: coniferous-broadleaved P. tabuliformis mixed forest, Ⅲ: Quercus mongolica forest.

3.4 Soil microbial community

Total microbial biomass and bacterial biomass were significantly different between forests at the 0–10 cm soil depth. In decreasing order, bacterial and total microbial biomass of the three forests were Q. mongolica forest > coniferous-broadleaved P. tabuliformis mixed forest > P. tabuliformis forest (Fig. 3a,e), respectively (p < 0.001; p < 0.001). Gram+ biomass and Gram- biomass in the P. tabuliformis forest were significantly lower than in the Q. mongolica forest at the 0–10 cm soil depth (Fig. 3b,c). At the 10–20 cm soil depth, total microbial biomass and Gram- biomass in the Q. mongolica forest were significantly higher than in the P. tabuliformis forest, and Gram+ biomass in the coniferous-broadleaved P. tabuliformis mixed forest was significantly higher than in the P. tabuliformis forest and not significantly different with the Q. mongolica forest (Fig. 3b,c,e). Additionally, the fungal/bacterial ratio (F/B ratio) did not differ at the 10–20 cm soil depth between forests, but the ratio of the Q. mongolica forest was significantly lower than that of the other two forests at the 0–10 cm soil depth (p < 0.001) (Fig. 3f). Overall, bacterial biomass, Gram+ biomass, Gram- biomass, fungal biomass, and total microbial biomass decreased with increasing soil depth in contrast to the F/B ratio. The composition of the microbial community in the 0–10 cm soil depth did not vary between the P. tabuliformis and coniferous-broadleaved P. tabuliformis mixed forests, but it did differ at the 10–20 cm depth among forest types (p < 0.001) (Fig. 4).

Fig. 3. Bacterial biomass (a), Gram+ biomass (b), Gram- biomass (c), fungal biomass (d), total microbial biomass (e), and fungi/bacterial ratio (f) in two soil depths under different forest types. Bars marked with the same letters are not significantly different from each other at the 0.05 level (Duncan test).
Ⅰ: Pinus tabuliformis forest, Ⅱ: coniferous-broadleaved P. tabuliformis mixed forest, Ⅲ: Quercus mongolica forest.

Fig. 4. Principal component analysis (PCA) of microbial species at 0–10 cm and 10–20 cm soil depths under different forest types. Bars indicate the standard errors of means.
Ⅰ: Pinus tabuliformis forest, Ⅱ: coniferous-broadleaved P. tabuliformis mixed forest, Ⅲ: Quercus mongolica forest.

4 Discussion

Certain regions have experienced moderate success in the near-natural transformation of planted forest through selective logging and creating gaps (Luo et al. 2013; Taki et al. 2010; He et al. 2013; Wang and Liu 2011). Although these methods have resulted in positive changes to some forests, in other cases, simply allowing the course of natural development to take place can also result in comparable transitions. The current study focused on near-natural and secondary forests that have existed with P. tabuliformis planted forest that has undergone natural development for 60 years. This transition in forest type has resulted in changes to species diversity, forest floor and soil properties, and microbial community characteristics.

4.1 Influence of forest type on litter and soil properties

The present study revealed that the C concentration in the L-horizon in the P. tabuliformis forest was significantly higher than in the Q. mongolica forest, whereas the N and P concentrations in the P. tabuliformis forest were lower than in the Q. mongolica forest. Only the litter quality (N and P) of the P. tabuliformis forest was significantly higher when deciduous broadleaved species were present and thus formed the coniferous-broadleaved mixed forest. Polyakova and Billor (2007) also indicated that mixed pine-deciduous litter had a higher nutrient concentration than pure pine litter. In the current study, from the L-horizon to the FH-horizons, C and P concentrations exhibited a decreasing trend, whereas the N concentration increased. During litter decomposition, a large amount of C is released to the atmosphere in the form of carbon dioxide through microbial respiration, and N acts as an immobilizer due to microorganisms colonization of decaying litter (Chapin et al. 2002; Fioretto et al. 2005). Plant litter quality is an important influence on soil nutrient cycling, particularly because the C/N ratio, which is the most common index of litter quality, modifies the decomposition rate (Cao et al. 2014; Szanser et al. 2011; Polyakova and Billor 2007). In the current study, the C, N, and P concentrations of soil in the P. tabuliformis forest were significantly lower than in the Q. mongolica forest likely because the lower C/N ratio in the Q. mongolica forest litter coupled with a higher nutrient concentration improved soil fertility. Furthermore, changes in litter composition due to the distinct effects of diverse plant species have direct (or indirect) consequences on further decomposition by altering microhabitat structure and food availability for litter-feeding animals (Hättenschwiler et al. 2005). Klemmedson (1987) reported that mixed pine (Pinus ponderosa P. Lawson & C. Lawson)-oak (Quercus gambelii Nutt.) litter accelerated rates of litter decay and nutrient release and improved soil fertility compared to a pure pine forest. Our research showed that the C, N, and P concentrations of soil in a coniferous-broadleaved P. tabuliformis mixed forest were significantly higher than those in the P. tabuliformis forest. This was why the N and P contents of forest floor in the P. tabuliformis forest were significantly higher those of the coniferous-broadleaved P. tabuliformis mixed forest, but those of mineral soil showed the opposite tendency. Although the C content in the soil increased from the pure pine forest to the near-natural forest, further studies will be needed to determine the stability of the soil C pool (Wang et al. 2015) in the P. tabuliformis planted forest after 60 years of natural development.

CEC is an important indicator of soil nutrient content, pH-related buffer ability (the capacity to control the input and release of nutrients), and quality assessment (Troeh and Thompson 1993). Research has shown that CEC improves with restoration time in a degraded landscape (Negash and Kagnew 2013). The CEC of the 0–10 cm soil depth in the coniferous-broadleaved P. tabuliformis mixed forest was significantly higher than that of the P. tabuliformis forest. However, the CEC of the 0–10 cm soil depth in the Q. mongolica forest was the highest among all forests. Soil organic matter may provide the bulk of exchange sites in soils, and therefore strongly influence CEC (Sayer 2006; Jiang et al. 2012), whereas the nutrient contents at the 0–10 cm soil depth in the Q. mongolica forest were the highest among the three forest types. Our research was consistent with that of a previous study (Van Nevel et al. 2014) in that the topsoil in the oak stands had significantly higher CEC than in that of the pine stands.

The acidification of forest soils remains an important concern because this process leads to numerous adverse effects on forest ecosystems, such as the depletion of essential base cations (Mg²⁺, Ca²⁺, K⁺, Na⁺) and increased availability of potentially toxic elements (Al³⁺) (Marlow and Peart 2014; Van Nevel et al. 2014). Atmospheric deposition of acidifying emissions of N and sulfur (S) and other potentially acidifying compounds (e.g., NH_x) unequivocally drives forest soils towards more acidic conditions, but the rate of soil acidification is also modified by litter quality and litter decomposition rates (De Schrijver et al. 2012). Lower C/N ratios potentially facilitate litter decomposition and base cation release to soils, which in turn increases soil buffering capacity (Cornelissen and Thompson 1997; Clarholm and Skyllberg 2013). In the present study, soil pH in the coniferous-broadleaved P. tabuliformis mixed forest stand was significantly higher than in the P. tabuliformis forest stand. However, soil pH in the Q. mongolica forest stand was not significantly different with the P. tabuliformis forest stand. It might be due to the difference of sort and percentage composition of litter between the coniferous-broadleaved P. tabuliformis mixed forest stand and the Q. mongolica forest stand. This finding suggested that the presence of deciduous broadleaved species improved the buffering capacity of pine forest soil via a change in litter quality and ameliorated soil pH to some extent.

4.2 Influence of forest type on soil microbial biomass and community structure

Litter quality is often a strong determinant of soil microbial communities. Changes in litter quality can affect the population dynamics and community structure of soil microorganisms by supplying nutrients, changing the microclimate at the soil surface, and releasing chemical compounds (Zhao et al. 2013; Wardle et al. 2006; Sayer 2006; Hättenschwiler et al. 2005). Our research showed that total microbial biomass in the Q. mongolica forest was significantly higher than in the other two forests, but when deciduous tree species were added to the P. tabuliformis forest, total microbial biomass was significantly improved in the coniferous-broadleaved P. tabuliformis mixed forest. Lower C/N ratios and higher litter nutrients not only improve the decomposition rate and increase soil nutrients, but also enhance the total microbial biomass and influence the composition of soil microbial community (Tu et al. 2012; Chen et al. 2011). Bacteria and fungi are the most important functional communities in soil (Coleman 2008; Holtkamp et al. 2008; Fierer et al. 2009), and high nutrient contents may be favorable to bacterial communities (Bardgett and Cook 1998; Fioretto et al. 2005). In the present study, bacterial biomass significantly differed among the three forests, and decreased in the following order: Q. mongolica forest > coniferous-broadleaved P. tabuliformis mixed forest > P. tabuliformis forest. In order to enlarge the absorbing area of fine roots and increase nutrient uptake efficiency, Pinus and Quercus commonly form a symbiotic relationship with ectomycorrhizal fungi (Wang et al. 2012; Makoto et al. 2010). This was likely the main reason why fungal biomass did not differ among the forests in the 0–10 cm soil depth in our study. However, the F/B ratio (Fungal/Bacterial ratio) in the Q. mongolica forest soil was lower than in the other two forests, and the ratio in the 0–10 cm soil depth reached significant levels. Our data showed that the composition of the soil microbial community in the 0–10 cm soil depth did not differ between the P. tabuliformis forest and coniferous-broadleaved P. tabuliformis mixed forest, but it did vary significantly in the 10–20 cm soil depth among the three forests.

5 Conclusion

Overall, our results suggest that a change in forest type influenced soil microbial biomass and community structure. However, previous research indicated that belowground communities (microorganisms and animals) actually play a major role in shaping aboveground biodiversity (Bardgett and van der Putten 2014), which can include varieties of tree species. Therefore, the contribution of soil microorganisms to the process of a near-natural transformation of planted forest merits further study. Meanwhile, this study can act as a reference for management of the near-natural transformation of P. tabuliformis planted forests and for the choice of the tree species used.

Acknowledgements

This study was financially supported by The 111 Project, The Basic Work of the Ministry of Science and Technology, China (No. 2011FY110300), The Basic Work of Baxian Mountain National Nature Reserve (No. 2015239), and The Ph.D. Candidate Research Innovation Fund of Nankai University.

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