Mixed plantations of Metasequoia glyptostroboides and Bischofia polycarpa change soil fungal and archaeal communities and enhance soil phosphorus availability in Shanghai, China.

Soil degradation has been found in urban forests in Shanghai, especially in the pure plantations. Mixed plantations are considered to improve soil quality because they can stimulate organic matter cycling and increase soil carbon and nutrient content. Although soil microbes play crucial roles in regulating soil biogeochemical processes, little is known about how mixed plantations affect soil microbial communities, including bacteria, archaea, and fungi. Here, we evaluated soil chemical properties, abundances and compositions of soil bacterial, archaeal, and fungal communities, and enzyme activities in pure and mixed Metasequoia glyptostroboides and Bischofia polycarpa plantations, located in Shanghai, China. The results showed that soil available phosphorus content in the mixed plantation of M. glyptostroboides and B. polycarpa was significantly higher than that in pure plantations, while no significant difference was observed in the content of soil organic carbon, total and available nitrogen, total and available potassium among the three studied plantations. We found higher fungal abundance in the mixed plantation, when compared to both pure plantations. Moreover, fungal abundance was positively correlated with the content of soil available phosphorus. No significant difference was found in the abundance and diversity of bacterial and archaeal community among the three studied plantations. A similarity analysis (ANOSIM) showed that mixed plantation significantly altered the community composition of archaea and fungi, accompanied with an increase of alkaline phosphatase activity. However, ANOSIM analysis of bacterial communities showed that there was no significant group separation among different plantations. Overall, results from this study indicated that fungal and archaeal communities were more sensitive to aboveground tree species than bacterial community. Moreover, mixed plantations significantly increased the activity of alkaline phosphatase and the content of soil available phosphorus, suggesting that afforestation with M. glyptostroboides and B. polycarpa is an effective way to alleviate phosphorus deficiency in urban forests in Shanghai, China.

INTRODUCTION

Urban forest has undergone rapid development in China over the last three decades, especially in the highly developed areas along the East Coast (Wang et al., 2013). Urban forest is becoming an important component of forest ecosystems in China. As one of the most urbanized and developed cities in China, Shanghai showed an increase of urban forest coverage from 3% in the 1990s to 14% in 2014 (class="Chemical">Natioclass="Chemical">nal Forestry & Grasslaclass="Chemical">nd Admiclass="Chemical">nistratioclass="Chemical">n, 2019). Thus, urbaclass="Chemical">n forest provides iclass="Chemical">ncreasiclass="Chemical">ngly profouclass="Chemical">nd ecosystem services at a regioclass="Chemical">nal aclass="Chemical">nd class="Chemical">natioclass="Chemical">nal scale, such as maiclass="Chemical">ntaiclass="Chemical">niclass="Chemical">ng biodiversity, reduciclass="Chemical">ng urbaclass="Chemical">n heat islaclass="Chemical">nd effect, aclass="Chemical">nd cleaclass="Chemical">niclass="Chemical">ng air aclass="Chemical">nd class="Chemical">n class="Chemical">water (Endreny, 2018; Millward et al., 2014; Xiao & McPherson, 2002). However, most of the Chinese urban forests, and especially those established during recent years, are pure plantations. Similar to other monoculture system, pure urban forest stands are facing many problems, such as a decline in ecosystem stability due to soil degradation and higher susceptibility to pests and pathogens (Endreny, 2018; Liu & Li, 2010; Steenberg et al., 2017). In addition, these pure stands have a negative impact on the landscape esthetic (Liu et al., 2004). To resolve these problems and enhance the ecological function of urban forest, afforestation with mixed species has been gradually adopted when establishing new plantations (Liu et al., 2004; Ordóñez & Duinker, 2014).

Given that soil microbes provide crucial roles in soil ecosystem processes, such as the decomposition of the soil organic matter and the mineralization of nutrients, increasing efforts have been made toward better understanding the effects of aboveground tree species on soil microbial biomass and community composition (Gunina et al., 2017; Pereira et al., 2019; Rachid et al., 2013; Wu, Zhang, et al., 2019). As reported, afforestation with mixed species may induce higher biomass and diversity of soil microbes than those in pure plantations (Gunina et al., 2017; Pereira et al., 2019; Thoms et al., 2010; Wen et al., 2014). Recently, Pereira et al. (2017) reported that mixed‐species plantations could influence the community composition of soil bacteria down to 300 cm depth. However, most of these studies were focused on bacteria or fungi, the studies of archaeal community in soil are lacking. Archaea were originally thought to exist only in harsh environments and were often described as “extremophiles,” but we now know they are widely distributed and participate in the circulation of critical element in soil, such as class="Chemical">ammonia oxidatioclass="Chemical">n (Aislabie & Deslippe, 2013). Thus, it is esseclass="Chemical">ntial to iclass="Chemical">nvestigate bacterial, fuclass="Chemical">ngal, aclass="Chemical">nd archaeal commuclass="Chemical">nities simultaclass="Chemical">neously, to elucidate microbial mechaclass="Chemical">nisms that coclass="Chemical">ntribute to improve soil class="Chemical">n class="Chemical">carbon (C) and nutrient dynamics in mixed‐species plantations.

Soil microbes participated in soil C and nutrient cycling by secreting extracellular enzymes, which are responsible for controlling different reactions and metabolic processes in the biogeochemical cycling of nutrient elements (Saha et al., 2008). Thus, extracellular enzyme activities have been used widely as sensitive indicators for assessing microbial functionality (Acosta‐Martinez et al., 2007; Phillips et al., 2014; Zhang et al., 2017). Mixed‐species plantations have been found to increase, decrease or have no effect on extracellular enzyme activities (Kooch & Bayranvand, 2017; Lucas‐Borja et al., 2012; Pereira et al., 2019). These contradictory results may be partly attributed to the distinct responses of soil microbes to aboveground tree species. Thus, identifying the effects of aboveground tree species on soil enzyme activities is an important step toward understanding the potential mechanism involved with soil ecological processes.

class="Species">Metasequoia glyptostroboides aclass="Chemical">nd class="Chemical">n class="Species">Bischofia polycarpa are important urban greening tree species in Shanghai, China (Wang et al., 2013). In this study, we evaluated the composition and function of soil bacterial, fungal, and archaeal communities in pure and mixed M. glyptostroboides and B. polycarpa plantations in Shanghai, China. We hypothesized that the mixed plantation would (a) increase the content of soil carbon and nutrients; (b) increase the abundance and diversity of soil bacterial, fungal, and archaeal communities, and change their composition; (c) stimulate soil extracellular enzyme activities. The results of this study would provide a better understanding of the soil microbial communities in mixed and pure plantations.

MATERIALS AND METHODS

Study site and sampling

The study was carried out at ecological public welfare forests, located in Chongming district, Shanghai, China (31°27′00″–31°51′15″class="Chemical">N, 121°09′30″–121°54′00″E). The area is characterized by a subtropical moclass="Chemical">nsooclass="Chemical">n climate with the meaclass="Chemical">n aclass="Chemical">nclass="Chemical">nual temperature of 15.8°C aclass="Chemical">nd aclass="Chemical">nclass="Chemical">nual precipitatioclass="Chemical">n of 1,122 mm. The soil was developed oclass="Chemical">n alluvial materials (Waclass="Chemical">ng et al., 2013). Three iclass="Chemical">ndepeclass="Chemical">ndeclass="Chemical">nt staclass="Chemical">nds were raclass="Chemical">ndomly choseclass="Chemical">n iclass="Chemical">n this study. The latitude aclass="Chemical">nd loclass="Chemical">ngitude of the three staclass="Chemical">nds were 31°37′33″class="Chemical">n class="Chemical">N, 121°42′50″E, 31°37′50″N, 121°41′12″E, and 31°36′42″N, 121°43′42″E, respectively. The study stands were afforested with pure or mixed plantations in 2008. Three fixed 15 × 15 m plots were established in each stand, including (a) a pure M. glyptostroboides plantation, (b) a pure B. polycarpa plantation, and (c) a mixed plantation of the two species. Distances between plots were greater than 150 m. Soil from each plot was collected at a depth of 0–20 cm in November 2017. Soil samples were collected from 8 points at each sampled plot using a soil corer (2.5 cm diameter) and then mixed thoroughly. Impurities such as rocks, plant roots, and other objects were removed. Soil material was sieved through a 2‐mm mesh. Each sample was divided into three parts: One was stored at −20°C for DNA extraction, the second was stored at 4°C for enzyme assays, and the remaining soil was air‐dried to determine the chemical properties.

Determination of soil chemical properties

Soil pH was determined in a 1:2.5 soil/class="Chemical">water (w/v) suspeclass="Chemical">nsioclass="Chemical">n usiclass="Chemical">ng a pH meter. Soil orgaclass="Chemical">nic class="Chemical">n class="Chemical">carbon (SOC) content was determined using the dichromate oxidation method (Cui et al., 2019). Soil total nitrogen (N) content was determined by the Kjeldahl method (Bremner & Mulvaney, 1982). Soil total phosphorus (P) content was determined following H2SO4–HClO4 digestion (Olsen & Sommers, 1982). Soil total potassium (K) content was determined by flame photometry after digestion in nitric acid, perchloric acid, and hydrofluoric acid. Soil available N content was determined by the alkali hydrolysis and diffusion method (Cornfield, 1960). Soil available P and K content were measured using ICP‐MS (NexION 300X) and ICP‐OES (Optima 7000DV), respectively.

Total DNA extraction

Total Dclass="Chemical">NA was extracted from 250 mg of fresh soil usiclass="Chemical">ng the PowerSoil® Dclass="Chemical">n class="Chemical">NA Isolation Kit (MoBio Laboratories), according to the manufacturer instructions. DNA quality was checked by agarose gel (0.8%) electrophoresis (5 V cm−1, 45 min). The extracted DNA was stored at −80°C and used for later molecular procedures.

Real‐time PCR assay

Bacterial and archaeal abundances were estimated by assessing the 16S rRclass="Chemical">NA geclass="Chemical">ne copy class="Chemical">numbers usiclass="Chemical">ng real‐time PCR, aclass="Chemical">nd fuclass="Chemical">ngal abuclass="Chemical">ndaclass="Chemical">nce was estimated by assessiclass="Chemical">ng the 18S rRclass="Chemical">n class="Chemical">NA gene copy numbers. Real‐time PCR was performed on a Light Cycler® 96 System (Roche). Bacterial and archaeal 16S rRNA gene were quantified using the primers 338F/518R and 344F/915R, respectively (Guo et al., 2014; Muyzer et al., 1993). Fungal 18S rRNA gene was quantified using SSU‐0817F/SSU‐1196R primers (Borneman & Hartin, 2000). Real‐time PCR assays were carried out in a 25 μl reaction volume using SYBR® Premix Ex Taq™ II (Takara). Amplification specificity was confirmed by melting curve analysis and gel electrophoresis of the amplified fragments. Triplicate reactions were performed for each DNA sample. Standard curves were obtained through 10‐fold serial dilutions of linearized plasmids, which contained the 16S rRNA or 18S rRNA gene fragments. Amplification efficiencies for the bacterial, archaeal, and fungal assays were 103%, 96%, and 93%, respectively. Data are shown as rRNA gene copy numbers per gram of dried soil.

Illumina amplicon sequencing

An aliquot of the extracted Dclass="Chemical">NA from each sample was used as a template for amplificatioclass="Chemical">n. The primers 338F aclass="Chemical">nd 806R were used to amplify the V3−V4 hypervariable regioclass="Chemical">n of the bacterial 16S rRclass="Chemical">n class="Chemical">NA gene (Cui et al., 2019; Huse et al., 2008). The primers 524F‐10‐ext and Arch958R‐mod were used to amplify the archaeal 16S rRNA gene (Pires et al., 2012). The primers ITS1F and ITS2R were used to amplify the ITS1 region of the fungal rDNA (Gardes & Bruns, 1993; White et al., 1990). Amplicon sequencing was performed on an Illumina MiSeq platform (Illumina).

Bioinformatic analysis

Raw fastq files were processed and analyzed using the QIIME pipeline (Caporaso et al., 2010). Chimeric sequences were identified and removed using UCHIME (Edgar et al., 2011). The qualified sequences were clustered into operational taxonomic units (OTUs) at 97% of sequence similarity using Uparse (Edgar, 2013). The singletons were removed before the downstream analyses. The taxonomy of representative sequences for each OTU was determined using an RDP classifier (Wang et al., 2007), against the Silva reference database (http://www.arb‐silva.de) for the 16S rRn class="Chemical">NA geclass="Chemical">nes aclass="Chemical">nd the Uclass="Chemical">nite refereclass="Chemical">nce database (http://uclass="Chemical">nite.ut.ee/iclass="Chemical">ndex.php) for the ITS. To equalize read sizes for their comparisoclass="Chemical">n amoclass="Chemical">ng soil samples, the OTU tables were class="Chemical">normalized to ideclass="Chemical">ntical sequeclass="Chemical">nciclass="Chemical">ng depth for further staclass="Chemical">ndardizatioclass="Chemical">n aclass="Chemical">nalysis. The Shaclass="Chemical">nclass="Chemical">noclass="Chemical">n–Wieclass="Chemical">ner iclass="Chemical">ndex was calculated to evaluate the diversity of the soil microbial commuclass="Chemical">nity usiclass="Chemical">ng Mothur (Schloss et al., 2009).

Enzyme activities and soil basal respiration

We assayed the potential activities of four extracellular enzymes, including cellobiohydrolase, β‐1,4‐class="Chemical">N‐acetyl‐glucosamidase, alkaliclass="Chemical">ne phosphatase, aclass="Chemical">nd pheclass="Chemical">nol oxidase. Eclass="Chemical">nzyme activity was expressed as μmol of products produced per hour per gram of dried soil. The activities of cellobiohydrolase, β‐1,4‐class="Chemical">n class="Chemical">N‐acetyl‐glucosamidase, and alkaline phosphatase were determined using the substrates 4‐nitrophenyl‐β‐D‐cellobioside, 4‐nitrophenyl‐N‐acetyl‐β‐D‐glucosaminide, and p‐nitrophenol phosphate, respectively (Yang et al., 2013; Zhang et al., 2017). For cellobiohydrolase, 1 g soil was incubated for 4 hr (37°C) with 4 ml of universal buffer (pH 8.0) and 1 ml of the appropriate substrate solution. The reaction was terminated by adding 1 ml of 0.5 M CaCl2 and 4 ml of 0.5 M NaOH, and the absorbance of the filtrate was read at 410 nm. The activities of β‐1,4‐N‐acetyl‐glucosamidase were assayed in the same way, except that the reaction mixture was incubated for 1 hr. For alkaline phosphatase, soil was incubated at 37°C for 1 hr with 4 ml of universal buffer (pH 8.0), 0.2 ml of toluene, and 1 ml of the appropriate substrate solution. The activity of phenol oxidase was measured using L‐3,4‐dihydroxyphenylalanine (L‐DOPA) as the substrate (Saiya‐Cork et al., 2002). The reaction mixture contained 2 g soil, 8 ml of 10 mM DOPA, and 6 ml of universal buffer (pH 8.0). The reaction mixture was incubated for 20 min at room temperature; then, the reaction was terminated by centrifugation at 5,000 g for 5 min. The absorbance of the filtrate was read at 460 nm. Soil basal respiration was analyzed by trapping and measuring the evolved CO2 over a 24‐hr period at 25°C (Alef & Nannipieri, 1995). Briefly, soil samples (50 g) were moistened to ~70% of its field water‐holding capacity and then incubated in sealed containers using 10 ml of 0.1 M KOH as a base trap. Three containers without soil samples were used as controls. The evolved CO2 was adsorbed in KOH and measured by HCl (0.05 M) titration, using phenolphthalein as an indicator. Soil basal respiration was expressed as mg CO2–C kg−1 soil per day.

Statistical analyses

One‐way Aclass="Chemical">NOVA was used to test the effects of forest type oclass="Chemical">n soil chemical properties, abuclass="Chemical">ndaclass="Chemical">nce, aclass="Chemical">nd diversity of soil microbial commuclass="Chemical">nity, aclass="Chemical">nd extracellular eclass="Chemical">nzymatic activities. We further aclass="Chemical">nalyzed the correlatioclass="Chemical">ns betweeclass="Chemical">n the microbial abuclass="Chemical">ndaclass="Chemical">nce aclass="Chemical">nd Shaclass="Chemical">nclass="Chemical">noclass="Chemical">n iclass="Chemical">ndex with soil attributes aclass="Chemical">nd extracellular eclass="Chemical">nzymatic activities usiclass="Chemical">ng Pearsoclass="Chemical">n correlatioclass="Chemical">n aclass="Chemical">nalysis. Statistical aclass="Chemical">nalyses were performed usiclass="Chemical">ng SPSS 16.0 software (SPSS Iclass="Chemical">nc.). Differeclass="Chemical">nces at p < 0.05 were regarded as statistically sigclass="Chemical">nificaclass="Chemical">nt. Prior to the aclass="Chemical">nalysis, data were log‐traclass="Chemical">nsformed wheclass="Chemical">n class="Chemical">necessary to meet assumptioclass="Chemical">ns of class="Chemical">normality. To determiclass="Chemical">ne whether microbial commuclass="Chemical">nities differed accordiclass="Chemical">ng to the forest types, a similarity aclass="Chemical">nalysis (Aclass="Chemical">n class="Chemical">NOSIM) was performed using the “vegan” package in R (http://www.r‐project.org). To identify the microbial taxa responsible for the community differentiation among the different forest types, we employed ANOVA on all of the genera at each collection date using STAMP software (Parks et al., 2014). The differential genera with false discovery rate‐corrected p values < 0.05 were identified as indicator genera (Benjamini & Hochberg, 1995). Redundancy analysis (RDA) was conducted based on the relative abundances of bacterial, fungal, and archaeal genera and the activities of extracellular enzymes (Canoco 5.0).

RESULTS

Soil chemical properties

Soil available class="Chemical">phosphorus of the soil iclass="Chemical">n the mixed placlass="Chemical">ntatioclass="Chemical">n of M. glyptostroboides aclass="Chemical">nd B. class="Chemical">n class="Chemical">polycarpa were significantly higher than those in the pure plantations (Figure 1). Soil pH and total phosphorus content in the pure B. polycarpa plantation was significantly lower than the pure M. glyptostroboides plantation and the mixed plantation of M. glyptostroboides and B. polycarpa. Compared to the pure plantation soil, the mixed plantation of M. glyptostroboides and B. polycarpa did not affect soil organic carbon, total N, available N, total K, and available K (Figure 1).

FIGURE 1

Soil chemical properties in pure and mixed Metasequoia glyptostroboides and Bischofia polycarpa plantations. Error bars indicate standard error of means (n = 3). M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Soil chemical properties in pure and mixed class="Species">Metasequoia glyptostroboides aclass="Chemical">nd class="Chemical">n class="Species">Bischofia polycarpa plantations. Error bars indicate standard error of means (n = 3). M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Quantification of bacteria, archaea, and fungi

The abundance of fungi in the mixed plantation of M. glyptostroboides and B. class="Chemical">polycarpa was sigclass="Chemical">nificaclass="Chemical">ntly higher thaclass="Chemical">n that iclass="Chemical">n the correspoclass="Chemical">ndiclass="Chemical">ng pure placlass="Chemical">ntatioclass="Chemical">ns (Figure 2). The abuclass="Chemical">ndaclass="Chemical">nce of fuclass="Chemical">ngal 18S rRclass="Chemical">n class="Chemical">NA gene in the mixed plantation of M. glyptostroboides and B. polycarpa was twofold greater than those found in the pure plantations of M. glyptostroboides and B. polycarpa. However, no differences were found in soil bacterial and archaeal abundances among the three studied plantations (Figure 2).

FIGURE 2

Abundance of bacterial 16S rRNA, archaeal 16S rRNA, and fungal 18S rRNA genes in pure and mixed Metasequoia glyptostroboides and Bischofia polycarpa plantations. Error bars indicate standard error of means (n = 3). M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Abundance of bacterial 16S rRclass="Chemical">NA, archaeal 16S rRclass="Chemical">n class="Chemical">NA, and fungal 18S rRNA genes in pure and mixed Metasequoia glyptostroboides and Bischofia polycarpa plantations. Error bars indicate standard error of means (n = 3). M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Microbial community composition

Across all the samples, we obtained a total of 210,339, 278,073, and 555,750 high‐quality bacterial, archaeal, and fungal sequences, which were respectively grouped into 1,939, 80, and 1,347 OTUs at the 97% similarity. Shannon index for fungi in the mixed plantation of M. glyptostroboides and B. n class="Chemical">polycarpa was sigclass="Chemical">nificaclass="Chemical">ntly higher thaclass="Chemical">n that iclass="Chemical">n the pure placlass="Chemical">ntatioclass="Chemical">n of M. glyptostroboides (Figure 3). Iclass="Chemical">n coclass="Chemical">ntrast, Shaclass="Chemical">nclass="Chemical">noclass="Chemical">n iclass="Chemical">ndices for bacteria aclass="Chemical">nd archaea were similar amoclass="Chemical">ng the three placlass="Chemical">ntatioclass="Chemical">ns (Figure 3).

FIGURE 3

Shannon index for bacterial, archaeal, and fungal community in pure and mixed Metasequoia glyptostroboides and Bischofia polycarpa plantations. Error bars indicate standard error of means (n = 3). M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Shannon index for bacterial, archaeal, and fungal community in pure and mixed class="Species">Metasequoia glyptostroboides aclass="Chemical">nd class="Chemical">n class="Species">Bischofia polycarpa plantations. Error bars indicate standard error of means (n = 3). M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Bacterial sequences were primarily composed of the phyla Proteobacteria (34.7%), Actinobacteria (22.3%), Acidobacteria (16.5%), and Chloroflexi (9.0%) (Figure 4). Relative abundances of these dominant bacterial phyla were similar among the three plantations. A total number of 437 bacterial genera were classified in this study. The relative abundances of these bacterial genera were similar to each other among the three plantations. An class="Chemical">NOSIM aclass="Chemical">nalysis of bacterial commuclass="Chemical">nities based oclass="Chemical">n the relative abuclass="Chemical">ndaclass="Chemical">nce of OTU showed that there was class="Chemical">no sigclass="Chemical">nificaclass="Chemical">nt group separatioclass="Chemical">n amoclass="Chemical">ng differeclass="Chemical">nt placlass="Chemical">ntatioclass="Chemical">ns (R = 0.1852; p = 0.161).

FIGURE 4

Relative abundances of bacteria (a), fungi (b), and archaea (c) at the phylum or class level in pure and mixed Metasequoia glyptostroboides and Bischofia polycarpa plantations. M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Relative abundances of bacteria (a), fungi (b), and archaea (c) at the phylum or class level in pure and mixed class="Species">Metasequoia glyptostroboides aclass="Chemical">nd class="Chemical">n class="Species">Bischofia polycarpa plantations. M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

The most abundant archaeal phyla were Thaumarchaeota (95.3%) and Euryarchaeota (1.8%) (Figure 4). Relative abundances of these dominant archaeal phyla were similar among the three plantations. Only 12 archaeal genera were identified in this study, and significantly different was observed in the genus Candidatus class="Chemical">Nitrocosmicus. Aclass="Chemical">n class="Chemical">NOSIM analysis of archaeal communities based on the relative abundance of OTU showed that there was significant group separation among different plantations (R = 0.4074; p = 0.029).

The majority of fungal sequences belonged to the phyla Ascomycota (93.0%) and Basidiomycota (3.3%) (Figure 4). Relative abundance of the phyla Ascomycota in the pure plantation of B. class="Chemical">polycarpa was sigclass="Chemical">nificaclass="Chemical">ntly lower thaclass="Chemical">n the pure placlass="Chemical">ntatioclass="Chemical">n of M. glyptostroboides aclass="Chemical">nd the mixed placlass="Chemical">ntatioclass="Chemical">n of M. glyptostroboides aclass="Chemical">nd B. class="Chemical">n class="Chemical">polycarpa. In contrast, the highest relative abundance of the phylum Basidiomycota was observed in the pure plantation of B. polycarpa. Fungal communities were dominated by Sordariomycetes (57.0%), Eurotiomycetes (17.7%), Leotiomycetes (7.4%), and Dothideomycetes (6.1%). Relative abundance of the class Sordariomycetes in the pure plantation of B. polycarpa was significantly lower than the pure plantation of M. glyptostroboides and the mixed plantation of M. glyptostroboides and B. polycarpa. In contrast, the highest relative abundance of the class Eurotiomycetes was observed in the pure plantation of B. polycarpa. Rare classes were also significantly affected by forest types, such as Cystobasidiomycetes, Glomeromycetes, Laboulbeniomycetes, Mortierellomycetes, and Zoopagomycetes. A total number of 403 fungal genera were classified in this study. Neocosmospora (8.3%), Talaromyces (7.5%), Aspergillus (6.7%), Mycoarthris (6.2%), and Trichoderma (5.4%) were the most abundant genera in this study. It should be noted that positive mixed effects were only founded in the rare fungal genera, such as Titaea and Idriella, the highest relative abundance of which were observed in the mixed plantation. ANOSIM analysis of fungal communities based on the relative abundance of OTU showed that there was significant group separation among different plantations (R = 0.5720; p = 0.004).

Enzymatic activity and soil basal respiration

The activity of alkaline phosphatase was significantly higher in the mixed plantation than those in the pure plantations (Figure 5). Specifically, the mixed plantation, when compared with the pure plantations, showed increases in alkaline phosphatase activity of approximately 11%. In contrast, the activities of cellobiohydrolase, β‐1,4‐class="Chemical">N‐acetyl‐glucosamidase, aclass="Chemical">nd pheclass="Chemical">nol oxidase were similar amoclass="Chemical">ng the three studied placlass="Chemical">ntatioclass="Chemical">ns (Figure 5). class="Chemical">n class="Chemical">No significant difference was found in the soil basal respiration among the three studied plantations.

FIGURE 5

Activities of extracellular enzymes and soil basal respiration in pure and mixed Metasequoia glyptostroboides and Bischofia polycarpa plantations. Error bars indicate standard error of means (n = 3). M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Activities of extracellular enzymes and soil basal respiration in pure and mixed class="Species">Metasequoia glyptostroboides aclass="Chemical">nd class="Chemical">n class="Species">Bischofia polycarpa plantations. Error bars indicate standard error of means (n = 3). M: the pure plantation of M. glyptostroboides; MB: the mixed plantation of M. glyptostroboides and B. polycarpa; B: the pure plantation of B. polycarpa

Relationships between the composition and function of microbial community and soil chemical properties

Pearson correlation analysis showed a strong positive correlation between fungal abundance and soil organic class="Chemical">carbon, available P aclass="Chemical">nd K (Table 1). Archaeal abuclass="Chemical">ndaclass="Chemical">nce correlated positively with soil basal respiratioclass="Chemical">n (Table 1). class="Chemical">n class="Chemical">No significant correlation was observed between bacterial abundance and soil chemical properties or enzyme activities. RDA analysis, based on the relative abundance of bacterial, archaeal, and fungal genera and extracellular enzyme activities, showed that the first and second axes extracted 55.60% and 16.56% of the explained variance, respectively (Figure 6). Moreover, the relative abundance of rare fungal genus Idriella and Titaea, and rare archaeal genus Candidatus Nitrocosmicus were positive related to the activity of alkaline phosphatase (Figure 6).

TABLE 1

Pearson's correlation test between microbial abundance and Shannon index with soil attributes and extracellular enzymatic activities

Soil	Microbial abundance			Microbial Shannon index
	Bacteria	Archaea	Fungi	Bacteria	Archaea	Fungi
pH	ns	ns	ns	Ns	ns	ns
Soil organic carbon	ns	ns	0.730*	Ns	ns	ns
Total nitrogen	ns	ns	ns	ns	ns	ns
Available nitrogen	ns	ns	ns	ns	ns	ns
Total phosphorus	ns	ns	ns	ns	ns	ns
Available phosphorus	ns	ns	0.819*	ns	ns	ns
Total potassium	ns	ns	ns	ns	ns	ns
Available potassium	ns	ns	0.726*	ns	ns	ns
Cellobiohydrolase	ns	ns	ns	ns	ns	ns
Β‐1,4‐N‐acetyl‐glucosamidase	ns	ns	ns	ns	ns	ns
Alkaline phosphatase	ns	ns	ns	ns	ns	ns
Phenol oxidase	ns	ns	ns	ns	ns	ns
Soil basal respiration	ns	0.856*	ns	ns	ns	ns

ns means no significant difference.

p < 0.05.

FIGURE 6

Redundancy analysis of the relative abundances of bacterial, fungal, and archaeal genera and enzymatic activities (a, b). Black circles: the pure Metasequoia glyptostroboides plantation; red circles: the mixed M. glyptostroboides and Bischofia polycarpa plantation; green circles: the pure B. polycarpa plantation. PNC: cellobiohydrolase; NAG: β‐1,4‐N‐acetyl‐glucosamidase

Redundancy analysis of the relative abundances of bacterial, fungal, and archaeal genera and enzymatic activities (a, b). Black circles: the pure class="Species">Metasequoia glyptostroboides placlass="Chemical">ntatioclass="Chemical">n; red circles: the mixed M. glyptostroboides aclass="Chemical">nd class="Chemical">n class="Species">Bischofia polycarpa plantation; green circles: the pure B. polycarpa plantation. PNC: cellobiohydrolase; NAG: β‐1,4‐N‐acetyl‐glucosamidase

DISCUSSION

Effects of mixed tree species on soil chemical properties

Compared to monospecific plantations, afforestation with mixed tree species typically results in an increase in soil C and nutrient content and an improvement in soil quality (Wen et al., 2014). However, our study showed that the content of SOC, total and available class="Chemical">N, aclass="Chemical">nd total aclass="Chemical">nd available K were class="Chemical">not sigclass="Chemical">nificaclass="Chemical">ntly affected by the forest types. These results coclass="Chemical">ntradict our hypothesis that the mixed tree species caclass="Chemical">n iclass="Chemical">ncrease the coclass="Chemical">nteclass="Chemical">nt of soil C aclass="Chemical">nd class="Chemical">nutrieclass="Chemical">nts. A Previous study has showed that the mixed placlass="Chemical">ntatioclass="Chemical">ns sequestrated more soil orgaclass="Chemical">nic class="Chemical">n class="Chemical">carbon and nitrogen than pure plantations, and admixing effects enhanced with stand ages (Liu et al., 2017). Therefore, a possible explain for our results was that our study was conducted in young forests, and the soil C, N, and K content appeared to be less sensitive to above tree species composition during early stages of tree growth. In contrast, the mixed plantation of M. glyptostroboides and B. polycarpa exhibited significantly higher content of soil available P than pure plantations, which is consistent with other studies. Firn et al. (2007) has reported that the available P in the top soil was positively related to the aboveground tree species diversity. There are several potential reasons for the increase of soil available P in the mixed plantations, including a greater P inputs from litter and root, changes in root exudation (i.e., organic acids), and soil microbial activities (Forrester et al., 2005; Inagaki et al., 2011; Rachid et al., 2013). Compared to pure plantations, the mixed plantation significantly increased the content of soil available P rather than the soil C, N, and K content, which may be also relevant to the low available P level of the study sites. It should be noted that P is a very demanding nutrient in subtropical urban forests, and most urban forests in Shanghai were limited by P. Therefore, the significantly higher available P content in the soil found in the mixed plantations highlights the potential of afforestation with mixed tree species for alleviating phosphorus deficiency.

Effects of mixed tree species on microbial community and extracellular enzyme activity

In this study, the mixed plantation did not alter the abundance and diversity of archaea and bacteria but significantly increase the abundance and diversity of fungi. This finding is not consistent with studies of subtropical forest ecosystems showing that mixed plantations can increase both soil bacterial and fungal biomass compared to pure plantations (Huang et al., 2014; Lucas‐Borja et al., 2012). The Aclass="Chemical">NOSIM test showed that bacterial commuclass="Chemical">nity structure iclass="Chemical">n the upper soil was class="Chemical">not sigclass="Chemical">nificaclass="Chemical">ntly altered by mixed placlass="Chemical">ntatioclass="Chemical">ns. Iclass="Chemical">n coclass="Chemical">ntrast, the commuclass="Chemical">nity compositioclass="Chemical">n of fuclass="Chemical">ngi aclass="Chemical">nd archaea had sigclass="Chemical">nificaclass="Chemical">nt respoclass="Chemical">nses to abovegrouclass="Chemical">nd tree species. Our hypothesis that a mixed placlass="Chemical">ntatioclass="Chemical">n caclass="Chemical">n alter soil microbial commuclass="Chemical">nities was class="Chemical">not fully coclass="Chemical">nfirmed. Previous study has democlass="Chemical">nstrated that both abovegrouclass="Chemical">nd tree species aclass="Chemical">nd soil characteristics play vital roles iclass="Chemical">n shapiclass="Chemical">ng soil microbial commuclass="Chemical">nity (Pei et al., 2016). Soil bacterial commuclass="Chemical">nity, iclass="Chemical">ncludiclass="Chemical">ng the abuclass="Chemical">ndaclass="Chemical">nce, diversity, aclass="Chemical">nd compositioclass="Chemical">n, was class="Chemical">not sigclass="Chemical">nificaclass="Chemical">ntly affected by the mixiclass="Chemical">ng of M. glyptostroboides aclass="Chemical">nd B. class="Chemical">n class="Chemical">polycarpa, which may be due to the fact that most of bacteria can well adapt to various environments (Hemmat‐Jou et al., 2018; Sul et al., 2013; Zhang et al., 2017). The results indicated that bacteria appeared to be less sensitive to aboveground tree species than archaea and fungi in this study.

Phosphatase activity has been suggested as an indicator of P availability in soils (Chen et al., 2008). In this study, compared to the pure plantations, the higher activity of alkaline phosphatase observed under the mixed plantation indicated the greater mineralization of organic P under the mixed plantation. Our results confirmed that tree diversity could promote soil enzyme activities and improve soil P condition (Kooch & Bayranvand, 2017). It is well known that microorganisms play important roles in soil P transformation (Rachid et al., 2013). Fungi, especially saprotrophic fungi, had more dominant roles in the mobilization of organic P than bacteria via the exudation of phosphatases (Wu, Xiang, et al., 2019). As reported, the most abundant fungal genera observed in this study, including Talaromyces, Aspergillus, and Trichoderma, have the ability to product and release the phosphatases; and the activity of phosphatase increased with the fungal biomass (Della Mónica et al., 2018; Plante, 2007). In addition, previous study showed that Thaumarchaeota may play an unexplored role in biogeochemical cycling of river class="Chemical">phosphorus (Hu et al., 2016), aclass="Chemical">nd archaea are more seclass="Chemical">nsitive to class="Chemical">n class="Chemical">phosphate depletion than bacteria and fungi (Ragot et al., 2016). The results in this study provided evidence that the increase in soil alkaline phosphatase activity in the mixed plantation may be associated with the increased fungal abundance and the changes in the community composition of soil fungi and archaea.

In this study, archaeal abundance showed a positive correlation with soil basal respiration, which was a major process that controlled the C loss from terrestrial ecosystem. This result suggested that archaea, instead of bacteria and fungi may play crucial roles in soil C mineralization in urban forests in Shanghai, China (Wang et al., 2020; Yu et al., 2021).

CONCLUSION

This study provides novel evidence that mixed plantations of M. glyptostroboides and B. class="Chemical">polycarpa promote soil fuclass="Chemical">ngal abuclass="Chemical">ndaclass="Chemical">nce aclass="Chemical">nd chaclass="Chemical">nge the commuclass="Chemical">nity compositioclass="Chemical">n of fuclass="Chemical">ngi aclass="Chemical">nd archaea. Specifically, we showed that mixed placlass="Chemical">ntatioclass="Chemical">ns of M. glyptostroboides aclass="Chemical">nd B. class="Chemical">n class="Chemical">polycarpa significantly increased the abundance and diversity of soil fungal community. In contrast, the abundance and diversity of bacterial and archaeal community were not significantly affected by the aboveground tree species. Moreover, mixed plantations significantly altered the community composition of fungi and archaea, but not bacteria. These results indicated that the response of fungal and archaeal community to aboveground tree species was more sensitive than bacterial community. Thus, composition and abundance of fungi and archaea in mixed plantations could be used as important parameters for assessing soil restoration in urban forests. In addition, mixed plantations significantly increased the activity of alkaline phosphatase and the content of soil available phosphorus. These results indicated that the mixed plantations may enhance soil P cycling, and afforestation with M. glyptostroboides and B. polycarpa proves to be an effective way to alleviate phosphorus deficiency in urban forests in Shanghai, China.

CONFLICT OF INTEREST

The authors declare no conflicts of interest.

AUTHOR CONTRIBUTIONS

Weiwei Zhang: Conceptualization (lead); Data curation (lead); Formal analysis (lead); Funding acquisition (supporting); Investigation (lead); Methodology (lead); Project administration (lead); Resources (lead); Software (lead); Supervision (lead); Validation (lead); Visualization (lead); Writing‐original draft (lead); Writing‐review & editing (lead). Wen Liu: Data curation (supporting); Methodology (supporting); Resources (supporting); Software (supporting). Shanwen He: Data curation (supporting); Formal analysis (supporting); Resources (supporting); Software (supporting). Qingchu Chen: Data curation (supporting); Formal analysis (supporting); Resources (supporting); Software (supporting). Jigang Han: Conceptualization (lead); Data curation (supporting); Funding acquisition (lead); Investigation (equal); Methodology (equal); Project administration (lead); Supervision (supporting); Validation (supporting); Visualization (supporting); Writing‐original draft (supporting); Writing‐review & editing (supporting). Qingfei Zhang: Conceptualization (equal); Formal analysis (equal); Funding acquisition (supporting); Investigation (equal); Project administration (supporting); Supervision (supporting); Validation (supporting); Writing‐original draft (supporting); Writing‐review & editing (supporting).