Plant functional traits have increasingly been studied as
determinants of ecosystem properties, especially for soil biogeochemical
processes. While the relationships between biological community structures
and ecological functions are a central issue in ecological theory, these
relationships remain poorly understood at the large scale. We selected nine
forests along the North–South Transect of Eastern China (NSTEC) to
determine how plant functional traits influence the latitudinal pattern of
soil microbial functions and how soil microbial communities and functions
are linked at the regional scale. We found that there was considerable
latitudinal variation in the profiles of different substrate use along the
NSTEC. Specifically, we found that the substrate use by microorganisms was
highest in the temperate forest soils (soil microbial substrate use
intensities of 10–12), followed by the subtropical forest soils (soil
microbial substrate use intensities of 7–10), and was least in the
coniferous forest soils (soil microbial substrate use intensities of 4–7).
The latitudinal variation in soil microbial function was more closely
related to plant functional traits (leaf dry matter content, leaf C
concentrations, and leaf N concentrations,
The catabolic diversity of soil microbial communities is a useful indicator of how microbial functions adapt to environmental stress. It can be used to test fundamental questions about soil biological resistance and resilience (Jagadamma et al., 2014; Swallow and Quideau, 2015) and help us understand the role of microbial communities in different environments (Preston-Mafham et al., 2002). Biological community structure and function are intimately linked in ecological processes, and their relationships are a central issue in ecological theory (Talbot et al., 2014). Therefore, a major goal in ecological research is to identify and understand the mechanisms and relationships that control the structure and function of microbial communities over large spatial scales.
Numerous studies have documented how environmental and anthropogenic perturbations impact on the structure, diversity (Tu et al., 2016; Zhou et al., 2016), and enzyme activities (Peng and Wang, 2016; Xu et al., 2017) of soil microbial communities and have reported that forests in the same climatic zone develop similar microbial communities. Other researchers have examined spatial patterns in soil microbial function at different scales. For example, Tian et al. (2015), from their study of Changbai Mountain, China, found that the soil microbial metabolic activity and functional diversity were spatially dependent. Others reported that soil microbial activities varied by forest type, with high local variation and significant separation along regional climate gradients (Brockett et al., 2012; Cao et al., 2016). Soil microbes from different climatic zones have different affinities for carbon substrates. For example, microorganisms from boreal pine forest soils used carboxylic acids more efficiently but decomposed amino acids much less efficiently than microorganisms from temperate forest soils (Klimek et al., 2016). The soil microbial metabolic abilities are also influenced by the dominant tree species, through the production of chemically unique litter and root exudates, and the soil physicochemical properties (Menyailo et al., 2002). Despite this and because of limitations in analytical methods, questions still remain about how soil microbial functions vary at the regional scale.
The functional diversity of soil microbial communities is regulated by physicochemical soil properties (Gartzia-Bengoetxea et al., 2016), climate (Cao et al., 2016), and the composition of plant cover (Sherman and Steinberger, 2012). For example, the geographic patterns in soil microbial activities mainly reflect the climate, soil pH, and total phosphorus concentrations over large geographic scales (Cao et al., 2016). Research has shown that substrate-induced respiration rates were higher in soil microbial communities that developed under beech and holm oak forests than under oak and pine forests (Gartzia-Bengoetxea et al., 2016). Plant functional traits have increasingly been studied as determinants of ecosystem properties, especially for soil biogeochemical processes (De Vries et al., 2012; Pei et al., 2016). Soil bacteria phospholipid fatty acids (PLFAs) were found to be positively correlated with the community-weighted means (CWMs) of plant functional traits (leaf nitrogen (N) concentration) (De Vries et al., 2012). The plant leaf dry matter content and the leaf carbon (C) to nitrogen (N) ratio both influence the multivariate soil microbial community structure, and these factors positively promote the abundances of specific microbial functional groups (Pei et al., 2016). Limited soil resources, particularly in tropical forests, mean that soil microorganisms may be more reliant on plants than soil for C and nutrients via rhizosphere exudation or litter production, which varies among plant species (Russell et al., 2007; Raich et al., 2014; Waring et al., 2015). While soil functional diversity has been used as an indicator of microbial metabolic potential, there have been few studies of the integrated effects of climate, vegetation, and soil substrate availability on large-scale soil microbial functional diversity.
Although the functional characteristics of soil microorganisms are at least
as important as their patterns of community structure in biogeochemical
studies, the links between microbial community structure and microbial
functions are poorly understood. There are two current hypotheses about how
microbes determine ecosystem process rates. In functional redundancy,
different microbes perform the same function and so changes in the microbial
community structure do not necessarily lead to a change in soil function
(Balser and Firestone, 2005; Strickland et al., 2009). For example, Banerjee
et al. (2016) showed that the abundance of different bacterial and fungal
groups changed by up to 300-fold under straw- and nutrient-amended
treatments but that the decomposition rate remained similar, indicating
possible functional redundancy. The functional redundancy hypothesis has
recently been challenged by a counter-hypothesis, referred to as functional
dissimilarity, which suggests that diversity brings stability and that
every species plays a unique role in ecosystem function (Fierer and Bradford,
2007; Waldrop and Firestone, 2006). Soil microbial community composition
therefore, combined with environmental variables, may ultimately determine
ecosystem process rates. Waldrop and Firestone (2006) showed that Gram-positive bacteria (G
The North–South Transect of Eastern China (NSTEC) extends from a cold temperate coniferous forest in the north to a tropical rainforest in the south and includes almost all the forest types found in the Northern Hemisphere (Zhang and Yang, 1995) (Fig. 1 and Table 1). This transect, therefore, provides the optimal environment for investigating large-scale geographical patterns in microbial communities and their responses to environmental changes. In this study, we examined spatial patterns in soil labile C concentrations, soil organic matter (SOM) decomposition rates, and metabolic activity and functional diversity of microbes in nine forest biomes along the NSTEC. We assessed how abiotic factors, such as climate; soil physical and chemical properties; and biotic factors, in the form of community-weighted means (CWMs) of plant functional traits, contributed to soil functional diversity at the regional scale. We also examined the links between soil microbial community structure (PLFAs) and function (SOM decomposition rate, enzyme activities, and microbial substrate use). We tested four hypotheses in this study, as follows: (1) the profiles of soil microbial substrate use vary along a latitudinal gradient, (2) biogeographical patterns of soil microbial substrate use are constrained by climate and plant functional traits, and (3) different soil microbial communities may have substrate use profiles and SOM decomposition rates.
The main characteristics of the sampling sites along the North–South Transect of Eastern China.
Distribution of typical forest ecosystems along the North–South Transect of Eastern China (NSTEC). The abbreviations for the sampling sites from north to south are as follows: HZ, Huzhong; LS, Liangshui; CB, Changbai; DL, Dongling; TY, Taiyue; SN, Shennong; JL, Jiulian; DH, Dinghu; JF, Jianfeng. These abbreviations are used for the nine forests throughout.
We selected nine forest ecosystems along the NSTEC, namely Huzhong (HZ),
Liangshui (LS), Changbai (CB), Dongling (DL), Taiyue (TY), Shennong (SN),
Jiulian (JL), Dinghu (DH), and Jianfeng (JF) (18
Soil samples were collected from four random plots at each site in July and
August 2013, as described previously by Xu et al. (2017). Briefly, we
established four sampling plots measured
Soil properties of different sampling sites.
Note: ST: temperature of 0–10
Soil pH was measured at a
The Biolog EcoPlates were purchased from Biolog, US. The substrates for BG,
NAG, AP, and LAP were 4-methylumbelliferyl-
We established four sampling plots (
We also calculated the community-weighted mean (CWM) values of the tree
traits using the cover of each tree. As described by Xu et al. (2018), we
collected litter and sun-exposed and mature leaves (leaf blades for trees)
from between 5 and 10 individuals of each plant species at each site and
determined their TN and total carbon (TC) concentrations. We calculated the specific leaf
area (SLA, the one-sided area of a fresh leaf divided by its oven-dried
mass,
Microbial functional diversities were determined using a Biolog
EcoPlates™ (Biolog Inc., Hayward, California, USA) as described by
Garland and Mills (1991). Briefly, approximately 10
The richness (
Four replicates from each sampling site with a 60 % water-holding capacity
were incubated at 20
One-way analysis of variance (ANOVA) followed by a post hoc Tukey honestly significant difference test
were used to test the significance of the differences among the soil
properties, C use, functional diversity, and SOM decomposition rates in the
different forest ecosystems. We tested the relationships between labile C,
soil microbial community structure, microbial function, and the SOM
decomposition rates with the Pearson correlation test. Differences were
considered significant when
We used redundancy analysis (RDA) to examine the relationship between the
environmental variables and soil microbial substrate use. The environmental
variables were the same as those described in Xu et al. (2018), including
climate, soil properties, litter properties, and plant functional traits.
Before RDA, we conducted forward selection of the environmental variables
that were significantly correlated with variations in the microbial
substrate use profile using stepwise regression and the Monte Carlo
permutation test. We used CANOCO software 4.5 (Ter Braak and Smilauer, 2000)
for the RDA and stepwise regression. The environmental properties, which
were significantly correlated with the microbial substrate use in the RDA,
were stressed in the plots. Path analysis was conducted to examine the
direct and indirect effect of biotic and abiotic factors on soil microbial
use of carbon sources. All ANOVA, regression analyses, and path analysis
were performed using SPSS 19.0 for Windows. Data are reported as the
Variations in soil microbial substrate use during a 240
There was no obvious latitudinal pattern for the soil total microbial
metabolic intensity (Fig. 2). Of the forests along the NSTEC, the C metabolic
intensity of soil microbes was lowest in HZ and LS; the C metabolic
intensity of soil microbes differed significantly between JF and the other
forests (Fig. 2), which indicates that the color development was
significantly higher in the tropical forest soils than in the subtropical
and temperate forest soils and is consistent with the variations in the AWCD
(Fig. S1 in the Supplement). The average values of
Functional diversity of soil microbial communities in forest ecosystems along the NSTEC.
Indices were calculated based on the optical density values after incubation
for 96
Characteristics of microbial use of
Across the nine forests, soil microorganisms used the six substrate groups in the same order; the carboxylic acid substrate was used most, followed by amino acids, carbohydrates, polymers, amines, and miscellaneous substrates (Fig. 3). Microorganisms in the boreal and temperate forests mainly metabolized carbohydrates, amino acids, and carboxylic acids, while those from the subtropical and tropical forests used the substrates in equal proportions. The substrate microbial use ability was highest in the coniferous broad-leaved mixed forest and tropical forest soils and lowest in the coniferous forest soil (Fig. 3).
Overall, soil MBC concentrations in the boreal and temperate forests were
3 to 8 times higher than those of the subtropical and tropical
forests. In contrast, the average DOC concentrations in the tropical and
subtropical forest soils, which ranged from 311 to 458
Redundancy analysis showed that the variations in soil microbial substrate use were strongly and positively correlated with the CWM values of LDMC, leaf N, and leaf C and strongly and negatively correlated with the soil silt content and SMC (Fig. 4). The RDA2 of soil microbial substrate use was strongly positively correlated with TN and SOC, but negatively correlated with the mean annual precipitation (MAP) (Fig. 5). RDA1 mainly represented the plant functional traits, soil texture, and micrometeorological conditions, while RDA2 represented climate and soil nutrients. Overall, the soil silt content and the CWM values of plant functional traits were the main predictors of the latitudinal variation in the soil microbial substrate use along the NSTEC.
Redundancy analysis (RDA) ordination biplot of soil microbial carbon sources use efficiency and environmental properties. The representatives of different colors are shown in Fig. 2. The dotted lines and solid lines represent the environmental variables and lipid signatures and carbon sources, respectively. The abbreviations of the variables in this figure are as follows: MAP, mean annual precipitation; LDMC, leaf dry matter weight; leaf C, leaf carbon content; leaf N, leaf nitrogen content; and SLA, specific leaf area. Soil properties included SMC, soil moisture content; Silt, soil silt content; TN, soil total nitrogen; and SOC, soil organic carbon. The abbreviations of the sampling sites are given in Table 1.
The heatmap of the Pearson's correlation coefficients between the use
of individual substrates and microbial PLFAs and soil enzyme activities.
Note the abbreviations of the variables: actino-, actinomycetes;
Microbial carbohydrate use was positively related to bacterial biomass and
actinomycic biomass (Fig. 5). Microbial polymer use was negatively related
with bacterial biomass and actinomycic biomass. Microbial amine use was
negatively related to G
The abundance of G
The SOM decomposition rates were significantly and positively related to soil MBC concentrations but significantly and negatively related to soil DOC concentrations (Fig. 6a and b). Except for amino acid and amine substrates, the SOM decomposition rates were significantly and positively related to microbial metabolic activities (AWCD) and carbohydrate substrate use (Fig. 6c and d) and negatively related to carboxylic acid, polymer, and miscellaneous substrate use (Fig. 6e, g, and i).
Relationships between soil carbon mineralization rates (
The SOM decomposition rates were significantly and positively correlated
with total PLFAs (
Relationships between soil carbon mineralization rates (
Soil organic matter is one of the most important C pools in terrestrial ecosystems. The concentrations of soil DOC in the temperate forests were lower than those in subtropical forests, but the soil MBC concentrations were higher in temperate forests than in subtropical forests. This reflects the results of previous regional and global studies (Tian et al., 2010; Xu et al., 2013) and shows that the production to consumption ratio of soil DOC was lower but that microbial C immobilization was higher in the high-latitude forests than closer to the tropics (Fang et al., 2014). Soil DOC, as a labile SOM fraction with a rapid turnover, is one of the primary energy sources for microorganisms. The higher temperatures and precipitation in subtropical and tropical forests lead to higher turnover rates (Fang et al., 2014), so soil DOC concentrations were highest in subtropical forests and MBC concentrations were lowest in tropical forests. However, in temperate forests, more C is assimilated into microbial biomass so that less C is lost through chemical and physical processes (Liu et al., 2010). Also, because the decomposition ability of different microbe groups varies, the differences in soil microbial communities in different forest ecosystems may also be responsible for the spatial variations in the soil DOC and MBC concentrations along the NSTEC (Hagedorn et al., 2008).
Heterotrophic soil respiration is sustained by the decomposition of SOM. The
SOM decomposition rates along the NSTEC were greater in temperate forests
than in subtropical forests, which was consistent with the variations in the
soil MBC and SOC concentrations. These results indicate that, as found in
other studies, large-scale SOM decomposition rates are driven by the amounts
of substrate available (Yu et al., 2010). Changes in the availability of C
in SOM may affect the microbial resource strategies, which may in turn
influence the SOM decomposition rate. Some forest soils were intermittently
saturated (such as CB, Table 2) or high with mean annual precipitation.
Under the anaerobic conditions, soil organic decomposition is mediated by a
complex suite of microbial processes (Megonigal et al., 2004). The
fermentation products including low-molecular-weight alcohols, fatty acids,
and dihydrogen can serve as substrates for anaerobic respiration using a
variety of alternative terminal electron acceptors in place of oxygen to
mineralize organic carbon to carbon dioxide (
The AWCD reflects the sole C source use ability of the soil microbial community (Garland and Mills, 1991). Of the six groups of C substrates, microbial communities in the temperate forests mainly used carbohydrates, carboxylic acids, and amino acids, which suggests that microorganisms in temperate forests probably use high-energy substrates that degrade easily (Kunito et al., 2009). The carbon substrate use was lowest in the boreal coniferous forest (HZ). This shows that, compared with coniferous species, broad-leaved tree species produce root exudates and litter high in water-soluble sugars, organic acids, and amino acids that are more favorable for microbial activity (Priha et al., 2001).
There was no significant latitudinal pattern in the soil total microbial
metabolic intensity (
A growing number of studies reported that vegetation type, land use, soil nutrients, and soil organic matter quality and quantity can determine large-scale patterns of microbial communities (de Vries et al., 2012; Tu et al., 2016). Plant functional traits that are related to growth may determine a tree species' ability to contribute to the soil carbon pool via leaf litter inputs. For example, it was previously reported that plant traits such as the leaf N content, SLA, and LDMC could explain variations in soil nutrients and litter decomposition rates (Eichenberg et al., 2014; Laughlin, 2011). Therefore, we examined how these plant traits influenced the soil microbial function by latitude. We found that changes in the soil microbial C substrate use with latitude were mainly related to the soil silt contents and the CWMs of LDMC, and leaf C and leaf N concentrations, which indicates that the quality of nutrients from plants had a major influence on microbial carbon use efficiency (hypothesis 2). Plant species with high SLA, high leaf N concentrations, and low LDMC can produce bacteria-dominated soil microbial communities in grasslands (Orwin et al., 2010). Looking beyond individual traits, related tree species may cultivate microbial communities with similar preferences for carbon sources through coevolution of plants and microbes (X. Liu et al., 2012; Buscot, 2015).
As hypothesized, the soil microbial community composition was explained by the CWMs of plant traits at the regional scale. Carbon substrate use was negatively correlated with the CWM of leaf N concentrations (Table S2, Fig. S2). Bacterially dominated soil microbial communities develop from leaf litter comprised of N-rich leaves from fast-growing species (De Vries et al., 2012), while leaves with low N concentrations will promote fungal domination (Orwin et al., 2010; De Vries et al., 2012). In line with this, fungal biomass decreased, and bacterial biomass increased, as the CWM leaf N content increased and is associated with fast-growing N-exploitative plants (Xu et al., 2018). Leaf N concentrations are considered indicators of plant growth and resource uptake (Wright et al., 2004). The results from this study show that, along the NSTEC, high leaf N restrained microbial C substrate use (Fig. S2) and was a good indicator of the competition between plants for soil N (Pei et al., 2016). Soil microbes and nearby plants may have been competing for N in the soil.
We also found that the C substrate use was negatively correlated with the CWM of leaf C concentrations (Table S2, Fig. S2). Plants at high latitudes may have higher leaf C concentrations than plants at lower latitudes so that they can balance the osmotic pressure of cells and resist freezing (Millard et al., 2007). The increased C was most likely in the form of an increase in nonstructural C, including starch, low-molecular-weight sugars, and storage lipids that are easy to break down. Therefore, soil microorganisms from the temperate forests mainly metabolized high-energy substrates such as carbohydrates, carboxylic acids, and amino acids.
The LDMC is the ratio of the leaf dry matter weight to the fresh weight and has
been used as a proxy for the ratio of structural compounds to assimilatory
tissue (mesophyll and epidermis; Van Arendonk and Poorter, 1994). High
values of LDMC indicate large amounts of vascular tissue, cellulose,
insoluble sugars and leaf lignin that are difficult to decompose (Poorter
and Bergkotte, 1992); C substrates such as carbohydrates, carboxylic acid,
and amino acid are, however, easy to decompose (Myers et al., 2001). In line
with this, the use of carbohydrate, carboxylic acid, and amino acid
substrates was negatively related to the CWMs of the LDMC (Table S2). Pei et
al. (2016) reported that the LDMC was an important driver of multivariate
soil microbial community structure and G
Soil texture regulates soil biological processes and so affects the soil microbial community structure (Sessitsch et al., 2001). In the present study, microbial C substrate use was significantly and positively related to the soil silt content. Soil types and textures varied along the NSTEC. Soil texture influences how microbes use organic matter and has a strong influence on soil moisture, nutrient availability, and retention (Veen and Kuikman, 1990). Fine-textured soils with a higher silt content are known to be more favorable for bacterial growth than soils with a lower silt content because of their greater water-holding capacity and nutrient availability, and because they are better protected from bacterial grazers (Carson et al., 2010). We found that the microbial C substrate use was higher in LS, CB, SN, and JL than in the other forests, reflecting their fine-grained soils and high silt contents, which ranged from 60 % to 80 %.
The soil microbial community structure and functions were significantly
correlated along the NSTEC. Soil carbohydrate and polymer substrate use were
mainly related to soil G
Shifts in microbial community composition may influence enzyme production
(DeForest et al., 2012; Waldrop et al., 2000; Brockett et al., 2012).
Different microbial groups require different amounts of nutrients to
construct biomass or have enzymes that differ in their affinity for
nutrients. We found that the relative abundances of the G
The quality and amounts of SOM are influenced by the biomass, vegetation coverage, root distribution, and microbial species (Raich and Schlesinger, 1992). The SOM decomposition rates were higher in temperate forests than in tropical forests and may reflect the higher soil microbial biomass (Q. Wang et al., 2016). In line with this, SOM decomposition rates were positively related to soil MBC concentrations and different groups of PLFAs. The inverse relationships between SOM decomposition rates and DOC, carboxylic acids, polymers, and miscellaneous along the NSTEC, indicate a shift in the soil C turnover from open to closed with increases in the soil labile C concentrations (Fang et al., 2014). Soil DOC and MBC influence SOM decomposition rates indirectly by regulating microbial properties (Boberg et al., 2014; Wei et al., 2014). In our study, SOM decomposition rates were positively related to bacterial PLFAs but negatively with fungal PLFAs. Because different communities of microbes have different SOM use efficiencies (Balser and Wixon, 2009; Lipson et al., 2009; Monson et al., 2006), changes in the microbial community structure may influence the microbial activities and the decomposition rates of organic matter (Lipson et al., 2009; Keiblinger et al., 2010). The functional dissimilarity of microbes and fungi may help explain these results. However, we did not measure some key variables, such as the microbial competition and interactions, and relationship between the microbial diversity and the decomposition rates. Therefore, in the future, we will use different experimental techniques that will help us gain an improved understanding of the mechanisms that drive the relationships between the structure and function of microbial communities.
In this study, we examined the patterns in labile C concentrations, SOM decomposition rates, microbial substrate use, and functional diversity and identified a combination of abiotic and biotic factors that influenced soil microbial functional diversity at the regional scale. The MBC concentration and SOM decomposition rates were significantly lower and the soil DOC concentrations were higher in the subtropical and tropical forests than in the temperate forests. There was no obvious latitudinal pattern for the soil total microbial metabolic intensity. However, soil microbial use of the different carbon sources varied with the latitude except the amines carbon source. Soil microbial use of carbon sources was relatively higher in tropical climatic areas. For the first time, we showed that CWM values of plant traits explained variations in soil microbial C substrate use at the regional scale. Additionally, the fine-grained soils with high silt contents were higher in the microbial C substrate use. Climate factors affected the soil microbial uses of carbon sources indirectly by influencing the soil temperature (ST) and soil nutrition. Soil microbial community structure and function were strongly related, which suggests that the loss of soil microbial groups may have consequences for overall ecosystem functioning.
Requests for data and materials should be addressed to Nianpeng He (henp@igsnrr.ac.cn) and Guirui Yu (yugr@igsnrr.ac.cn).
Abbreviations.
The supplement related to this article is available online at:
ZX, GY, and XZ planned and designed the research. ZX, NH, RW, and NZ conducted fieldwork. ZX, GY, XZ, and QW wrote the article. All authors contributed critically to the drafts and gave final approval for publication.
The authors declare that they have no conflict of interest.
This research was jointly supported by the National Natural Science Foundation of China (41601084 and 41571251), the Fundamental Research Funds for the Central Universities (2412019FZ001), Science and Technology Research Project of Jilin Province (JJKH20190283KJ), the National Key R&D Program of China (2016YFA0602301), and the China Postdoctoral Science Foundation (2018M631850).
This research has been supported by the National Natural Science Foundation of China (41601084 and 41571251), the Fundamental Research Funds for the Central Universities (2412019FZ001), Science and Technology Research Project of Jilin Province (JJKH20190283KJ), the National Key R&D Program of China (2016YFA0602301), and the China Postdoctoral Science Foundation (2018M631850).
This paper was edited by Yakov Kuzyakov and reviewed by four anonymous referees.