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. Author manuscript; available in PMC: 2022 Mar 28.
Published in final edited form as: Oecologia. 2021 Jan 9;195(2):499–512. doi: 10.1007/s00442-020-04838-y

Functional importance and diversity of fungi during standing grass litter decomposition

Matthew B Lodato 1, Jerrid S Boyette 1, Rachel A Smilo 1, Colin R Jackson 2, Halvor M Halvorson 1,3, Kevin A Kuehn 1
PMCID: PMC8959008  NIHMSID: NIHMS1786322  PMID: 33423104

Abstract

Although microbial participation in litter decomposition is widely known within terrestrial soils, the role and significance of microorganisms during the aerial standing litter phase of decomposition remains poorly investigated. We examined the fungi inhabiting standing leaf litter of Schizachyrium scoparium and Schizachyrium tenerum in a Longleaf Pine savanna ecosystem and estimated their contribution to litter decomposition. We identified fungal phylotypes associated with leaf litter and quantified leaf C mass loss, fungal biomass production, and microbial respiration during decomposition. These data were used to construct budgets estimating C flow into and through fungi. Significant losses in S. scoparium (55%) and S. tenerum (67%) leaf C mass were observed during standing decomposition along with concomitant increases in fungal biomass, which reached a maximum of 36 and 33 mgC/g detrital C, respectively. Cumulative fungal production during decomposition totaled 99 ± 6 mgC/g initial detrital C in S. scoparium and 73 ± 5 mgC/g initial detrital C in S. tenerum, indicating that 18 and 11% of the litter C was converted into fungal biomass, respectively. Corresponding estimates of cumulative fungal respiration totaled 106 ± 7 and 174 ± 11 mgC/g initial detrital C in S. scoparium and S. tenerum, respectively. Next generation sequencing identified several fungal phylotypes, with the majority of sequences belonging to the Ascomycota (Dothideomycetes) and Basidiomycota (Agaricomycetes). Fungal phylotypes were similar between litter species and changed over time, showing a successional pattern. These findings extend our understanding of fungal processes to standing litter in terrestrial ecosystems, and highlight the quantitative importance of fungi in C cycling processes.

Keywords: Schizachyrium, Fungal biomass, Productivity, Ecosystem function, Next generation sequencing

Introduction

The production and decomposition of plant matter dominates the flow of carbon (C) and nutrients in most terrestrial and aquatic ecosystems (Cebrian 1999; Hagen et al. 2012). Hence, investigating the natural fate of vascular plant matter is critical to our understanding of detrital pathways that are central to ecosystem energy flow and the cycling of both C and nutrients, such as nitrogen (N) and phosphorus (P). The decomposition of plant matter involves a wide range of transformations that can result in the growth and biomass production of detrital consumers, the formation of CO2 and other mineral substances via mineralization of organic matter, and the formation of intermediate breakdown products, such as dissolved and particulate organic matter (Gessner et al. 2010). From a microbial perspective, the rates of these processes are strongly influenced by the types of microbial decomposers, their response to prevailing environmental conditions, as well as the intrinsic chemical quality of the plant litter substrate (e.g., Aerts 1997; Aerts et al. 2003; Vivanco and Austin 2006; Gessner et al. 2007; Allison et al. 2013; Kuehn 2016).

When investigating plant litter decomposition, an important phenologic attribute to consider is the presence or absence of leaf or shoot abscission following senescence and death (Newell 1993). For many grasses and grass-like plants, abscission and collapse of plant organs (e.g., leaves) to the soil surface does not typically occur following the senescence and death. As a result, significant quantities of standing dead plant litter can accumulate within a variety of ecosystems (e.g., Knapp and Seastedt 1986; Seastedt 1988; Biondini and Manske 1996; Asaeda et al. 2002), where it begins initial microbial decomposition in an aerial standing position. Several recent studies conducted in arid and semiarid grasslands have documented that increases in nighttime relative humidity and subsequent dew formation on standing plant litter can stimulate microbial decomposers and accelerate rates of litter decomposition (Dirks et al. 2010; Jacobson et al. 2015; Gliksman et al. 2017; Wang et al. 2017a; Evans et al. 2019), underscoring the episodic pulse-dynamics of microbial processes in these types of ecosystems (Collins et al. 2008; McHugh et al. 2015). For example, Wang et al. (2017a) reported that standing litter of Cleistogenes squarrosa experienced periods of higher nighttime relative humidity compared to litter at the soil surface, resulting in greater levels of microbial respiratory activity and biomass accrual and higher rates of litter decomposition in comparison to litter placed at the soil surface (see also Liu et al. 2015). Furthermore, microbial preconditioning and transformation of standing C. squarrosa litter also led to a more rapid rate of litter decomposition following the collapse of standing litter to the soil surface (see also Gliksman et al. 2018), thus increasing the efficiency and rate of soil organic matter formation. At the microbial community level, Jacobson et al. (2015) reported that Ascomycete fungi (e.g., Chaetomium) were likely a key decomposer in standing litter of the Namib dune grass, Stipagrostis sabulicola. Fungal communities responded rapidly to periods of increased water availability and were able to survive the extreme daily thermal and desiccation stress experienced in this arid landscape. Furthermore, they also observed that fungal colonization and growth significantly decreased the C:N ratio of standing litter and that the termite detritivore Psammotermes allocerus showed a feeding preference for litter colonized by fungi (see also Silliman and Newell 2003).

Although litter decomposition in grasslands has been extensively studied at the soil surface and in subsurface environments (e.g., Seastedt 1988; Knops et al. 2001; Vivanco and Austin 2006; Allison et al. 2013; Hewins et al. 2013; Suseela et al. 2014; Henry and Moise 2015; Ma et al. 2016; Wang et al. 2017b), the patterns, controls and overall importance of decay processes in standing litter have yet to be fully explored despite its widespread occurrence. Furthermore, standing litter decomposition in grasslands has rarely been examined in relation to the growth and biomass dynamics of the microbial communities that drive C and nutrient cycling pathways. This is particularly true for litter-associated fungi, which are widely regarded as important decomposers in terrestrial ecosystems, yet detailed quantitative knowledge of their contribution to litter decomposition and other ecosystem processes is noticeably scarce (van der Heijden et al. 2008; van der Wal et al. 2013).

In the present investigation, we examined the decomposition and fungal decay dynamics associated with naturally standing leaf litter of two perennial grasses, Schizachyrium scoparium (little bluestem) and S. tenerum (slender bluestem), in a Longleaf Pine savanna ecosystem in south Mississippi. Specifically, we identified fungal taxa associated with standing leaf litter and quantified changes in leaf mass C, fungal biomass and production rates, and rates of microbial respiration during leaf senescence and standing litter decomposition. We also examined changes in standing litter C:N and C:P contents in relation to fungal growth dynamics. These data were used to construct a partial organic matter decay budget estimating C flow into and through litter associated fungal decomposers within the standing litter compartment.

Materials and methods

Study site and field procedures

This study was conducted in a Longleaf Pine savanna located near Hattiesburg, Mississippi, USA (31°22′8.32′′ N, 89°25′18.18′′ W). During each sampling period, ten naturally standing leaves of S. scoparium and S. tenerum were randomly collected from individual plants in each of four plots measuring ~ 16 m2 that were at least 15 m apart (n = 40 leaves total for each plant species). Leaf collection began in October while leaves were alive (peak growth, day 0) and continued periodically during leaf senescence and standing litter decomposition on days 13, 27, 39, 74, 111, 144, 180, 214, and 261. Collected leaf samples for each plant were placed individually into clean zip-lock bags, placed on ice in a cooler, and immediately returned to the laboratory and processed to determine losses in leaf C mass, litter nutrient concentrations [nitrogen (N) and phosphorus (P)], litter-associated fungal biomass (ergosterol) and glucosamine (chitin) concentrations, and rates of fungal production and microbial respiration (see below). Air temperatures and relative humidity were continuously monitored using Onset Hobo H8 Pro series data loggers (Onset Computer Corp., Bourne, MA, USA) placed within the standing litter canopy (Fig. S2a, b). Precipitation data was obtained via a permanent NOAA (National Oceanographic and Atmospheric Administration, www.noaa.gov) meteorological data station located near the study site.

Litter mass loss patterns

Mass loss of S. scoparium and S. tenerum leaves was estimated by losses in leaf area-specific C mass (Gessner 2001; Kuehn et al. 2011; Su et al. 2015). In the laboratory, collected leaves were immediately scanned using a Li-COR LI-3100 Area Meter (LICOR Biosciences, Lincoln, NE, USA) to determine leaf surface area. After scanning, two leaves per plot for each species were randomly selected to determine litter-associated fungal biomass (ergosterol) and production and rates of microbial respiration. The remaining eight leaves collected per plot for each species were immediately frozen (− 20 °C) and later lyophilized to dryness and weighed. These eight leaves were then pooled together and ground to 40-mesh using a Wiley mill (Thomas Scientific, Swedesboro, NJ, USA). Subsamples of ground leaf litter were then analyzed for litter C and N concentrations using a Costech elemental analyzer (Costech Analytical Technologies, Valencia, CA, USA) and P concentrations by combustion, digestion in hot hydrochloric acid, and measurement of P–PO4−3 using a SEAL Autoanalyzer 3 (SEAL Analytical, Milwaukee, WI). Subsamples of ground leaf litter were also analyzed for glucosamine (chitin) concentrations and used to assess fungal community structure via next generation sequencing (see below).

The initial leaf area-specific mass of S. scoparium and S. tenerum leaves were determined by dividing the leaf C mass at the initial sampling date, when leaves were still alive (i.e., green), by the corresponding scanned leaf area. Leaf C mass remaining during later sampling dates was estimated as changes in mean leaf area-specific C mass relative to the mean initial leaf area-specific C mass per plot. Mass loss rates (k) of leaf blades were calculated for each plot using a negative exponential decay model (Nt = Noe−kt), where Nt is the percent of leaf area-specific C mass remaining at time (t) in days, No is the estimated initial leaf area-specific C mass. Mass loss rates (k) and estimated initial leaf area-specific C mass were then averaged across plots for both species (mean ± SD, n = 4).

Fungal biomass and production

Living biomass and instantaneous growth rates (μ) of fungi were estimated from concentrations of ergosterol and from rates of [1-14C]acetate incorporation into ergosterol, respectively (Rousk and Bååth 2011; Gessner 2020; Suberkropp et al. 2020). One of the two selected leaves of S. scoparium and S. tenerum was cut into ~ 2-cm long sections, placed into sterile 20 mL glass scintillation vials containing 3.95 ml of sterile water, and allowed to hydrate in darkness for 2 h at 20 °C in a Percival E-36HO plant growth chamber (Percival Scientific, Perry, IA, USA). Afterwards, an aliquot of a Na[1-14C]acetate solution (ViTrax Radiochemicals, Placentia, CA, USA) was added to each sample (final concentration 5 mM Na[1-14C]acetate, specific activity = 48.5 MBq/mmol) and samples incubated in darkness for 5 h at 20°C. Non-biological 14C-acetate incorporation was determined using killed-controls containing formalin (2% v/v). After incubation, incorporation of [1-14C] acetate was stopped by placing sample vials on ice and immediately filtering (0.7 μm Whatman GF/F filters). Filters and litter pieces were rinsed twice with 4 mL sterile water and stored frozen (− 20 °C).

Frozen litter pieces were lyophilized to dryness, weighed, and ergosterol extracted in alcoholic KOH (0.8% KOH in HPLC-grade methanol, extraction volume 10 ml) for 30 min. at 80 °C in tightly capped digestion tubes. The resultant crude extract was partitioned into n-pentane and evaporated to dryness with nitrogen gas. Dried ergosterol residues were then dissolved in methanol and quantified by HPLC. Ergosterol fractions eluting from the HPLC were collected in 20 mL scintillation vials, mixed with 10 mL of Ecolume scintillation fluid (MP Biomedicals LLC, Santa Ana, CA, USA), and radioactivity assayed by using a Beckman LS6500 Scintillation Counter (Beckman Coulter, Indianapolis, IN, USA). Ergosterol concentrations were converted to fungal C assuming a conversion factor of 5 μg ergosterol/mg fungal dry mass and 43% C in fungal dry mass (Kuehn et al. 2011), which is the mean mycelial ergosterol concentration for a range of fungal isolates that have been analyzed (Gessner and Newell 2002). Rates of acetate incorporation into ergosterol were multiplied by 12.6 μg fungal biomass/nmole acetate incorporated to obtain a fungal growth rate (μ, %/h); a conversion factor determined for several fungi inhabiting decaying standing litter (Gessner and Newell 2002).

Glucosamine

Glucosamine concentrations (from chitin) in litter samples were also determined as another biochemical-indicator of fungal colonization. Samples were extracted and digested using a modified procedure (Su 2014) originally described by Ekblad and Näsholm (1996). Briefly, subsamples (~ 20 mg) of lyophilized, ground plant litter were initially extracted in 0.2 M NaOH to deproteinate samples and convert litter-containing chitin to chitosan. The resulting litter chitosan was then hydrolyzed to individual glucosamine residues in 8 M HCI at 100°C for 24 h. Glucosamine residues in hydrolyzed samples were then converted to 9-fluorenyl-methylchloroformate (FMOC-Cl) derivatives (Cat. 23,186, Sigma-Aldrich Inc., St Louis, MO, USA) and analyzed by HPLC using fluorescence detection (see Su 2014).

Microbial respiration

The other selected leaf of S. scoparium and S. tenerum was sectioned into ~ 6-cm long subsamples, placed into sterile Petri dishes containing sterile filter paper and wetted with sterile distilled water (Kuehn et al. 2004; Su et al. 2015). Samples were allowed to hydrate for 2 h at 20 °C in a Percival E-36HO plant growth chamber (Percival Scientific Inc., Perry, IA, USA). Afterwards, samples were removed and rates of microbial respiration (CO2 evolution) from plant litter were monitored using a Licor LI-6400 Infrared Gas Analyzer with a coupled LI-6400–89 Insect Respiration Chamber (LICOR Biosciences, Lincoln, NE, USA). All measurements were conducted in darkness. Following respiration measurements, litter samples were stored frozen (− 20 °C) and later lyophilized and weighed. Lyophilized, weighed leaves were also subsampled and ergosterol concentrations determined (as above) as additional sample estimate of fungal biomass within collected leaf material.

Additional experiments with standing S. scoparium and S. tenerum leaf litter were also conducted to estimate the proportion of total microbial respiration attributed to fungal decomposers using selective antibiotic inhibitors (see Supporting Information Appendix S1, Table S1, Fig S1). Thus, daily and cumulative respiration budgets (see below) were constructed to estimate the likely respiratory contribution of both fungal and non-fungal decomposers.

Fungal community composition

Fungal community phylotypes associated with decomposing Schizachyrium scoparium and S. tenerum litter samples were determined on three dates (November-day 27, March-day 144 and July-day 261) using Illumina MiSeq next generation sequencing (V2 chemistry) of the fungal ITS 1 rRNA gene region. Briefly, DNA from ground, frozen stored litter subsamples were extracted using a PowerSoil extraction kit (MoBio, Carlsbad, CA, USA) following procedures outlined by the manufacturer. Sample DNA was amplified and analyzed using a dual index barcoding approach, with primers BITS (5′ ACCTGCGGARGGATCA-3′) and B58S3 (5′GAGATCCRTTGYTRAAAGTT-3′) targeting the fungal ITS 1 rRNA region (Bokulich and Mills, 2013). Each forward and reverse primer included a unique 8-nt barcode (as described by Kozich et al. 2013) to allow sample multiplexing. Amplifications were conducted in 20 μL reactions consisting of 17 μL AccuPrime Pfx Supermix (Invitrogen/ThermoFisher, Carlsbad, CA, USA), 5–30 ng of DNA (1 μL), and 5 pmol of each primer (1 μL each). Reaction conditions were as described in Bokulich and Mills (2013), with annealing temperature reduced from 55 to 53 °C (i.e., 95 °C for 120 s, followed by 35 cycles of 95 °C for 30 s, 53 °C for 30 s, 72 °C for 60 s, and a final extension of 72 °C for 5 min). Two replicate amplifications were conducted for each sample. Amplification products were purified and normalized using a SequalPrep Normalization Plate Kit (Applied Bio-systems/ThermoFisher, Foster City, CA, USA), pooled and then sequenced using the Illumina MiSeq platform (Illumina Inc., San Diego, CA, USA) at the Molecular and Genomics Core Facility at the University of Mississippi Medical Center (UMMC, Jackson, MS, USA). Raw data files (FASTQ) were processed using Mothur bioinformatics pipeline (www.mothur.org) (Schloss et al. 2009) following general procedures outlined in Kozich et al. (2013) and updated on the MiSeq SOP (https://mothur.org/wiki/miseq_sop/) accessed in 2016. Briefly, contigs were assembled using forward and reverse sequence reads, which yielded a total of 2,034,288 sequences from the sequencing run. Sequences were screened to a maximum length of 350 bases, a maximum homopolymer length of 8 bases, and zero ambiguous bases calls (i.e., identical sequences from both forward and reverse reads), which retained 174,402 potentially valid sequences. Sequences were classified to the UNITE 7.0 database (unite.ut.ee) (Kõljalg et al. 2013) using the Bayesian “Wang method” (Wang et al. 2007) with an 80% cut-off. Sequences that could not be classified to any level were removed, leaving 174,268 in the final dataset. Because of inherent difficulties in aligning ITS sequence data, sequences were not clustered into operational taxonomic units based on sequence similarity, but were clustered into phylotypes, defined as sequences identified as the same phylogenetic lineage according to the UNITE 7.0 database. All subsequent diversity analyses were conducted using these phylotypes.

Daily and cumulative fungal production and respiration

Estimates of daily fungal production and microbial respiration (fungal and non-fungal) during S. scoparium and S. tenerum litter decay were calculated using procedures described earlier by Su et al. (2015). Since the conditions for radiolabeled incorporation and respiration assays require submergence or wetting of standing litter samples, respectively, estimates of daily fungal production and respiration were corrected for diel changes in water availability (i.e., relative humidity) as the major controlling variable affecting microbial activities in standing litter (Kuehn and Suberkropp 1998; Kuehn et al. 2004; Wang et al. 2017a; Evans et al. 2019). Field temperature and relative humidity data from Hobo loggers revealed the daily time periods in which standing litter microbial assemblages are metabolically active (i.e., 100% relative humidity—dew formation). Consequently, estimates of daily fungal growth and respiration rates were corrected by multiplying the hourly fungal growth or respiration rate, as determined in the laboratory, by the hours per day in which standing S. scoparium and S. tenerum litter was exposed to ~ 100% relative humidity. Both fungal growth and respiration rates were also temperature adjusted (assumed Q10 = 2) to reflect in situ field temperatures during periods of 100% relative humidity (Kuehn et al. 2004). Rates of daily fungal production were calculated by multiplying the daily growth rate (μ) by the litter-associated fungal biomass (B) (Suberkropp et al. 2020).

Cumulative fungal production, microbial respiration (fungal and non-fungal), and mean fungal biomass over the entire study period were estimated following procedures described earlier (Suberkropp et al. 2010; Kuehn et al. 2011; Su et al. 2015). To determine daily fungal biomass, fungal production or microbial respiration values for days between sampling dates the following criteria was assumed and calculated: (1) the average hourly fungal growth (μ), respiration rate, and litter fungal biomass for the first half of the days during the sampling interval were assumed to be equal to the values obtained on the preceding sampling date, and the hourly fungal growth, respiration rate, and litter fungal biomass for the latter half of days in the sampling interval were assumed to be equal to the corresponding values observed on the next sampling date, (2) daily fungal growth and respiration rates were then determined (as above) by multiplying the hourly fungal growth and respiration rate by the specific number of hours in that day where the relative humidity was 100%. As above, fungal growth and respiration rates were temperature-adjusted (assumed Q10 = 2) to account for observed daily changes in in situ temperatures (Kuehn et al. 2004), (3) Estimates of daily fungal production were subsequently calculated (as above) by multiplying the daily growth rate by the litter-associated fungal biomass. This raw dataset for the entire sampling period was subsequently used to estimate cumulative fungal production, microbial respiration (fungal and non-fungal) and mean fungal biomass using Monte Carlo Simulation (see below). Fungal carbon use efficiency (CUE) (Sinsabaugh et al 2015) defined as cumulative fungal production/cumulative fungal production + cumulative fungal respiration was also estimated.

Data analyses

Statistical analysis of the collected data was conducted using R 3.1.2 (R Core Team, 2020). Data were analyzed using repeated measure ANOVA’s to test the effects of time (within plots) and grass species (across plots); model and function: aov(response − species × time + Error(plots)). If necessary, data were transformed (loge and square root, see Table 1) prior to analysis to ensure normality and reduce heteroscedasticity. Pearson’s correlation analysis was used to determine relationships between selected variables. Nonmetric multidimensional scaling (NMDS) ordinations based on Bray–Curtis dissimilarity scores were used to visualize any similarities or differences in the composition of fungal phylotypes between samples. Such analyses were rarified to 1563 sequences per sample (the number of sequences from the sample with the lowest number of sequences), and based on the mean of 1000 iterations. Analysis of similarity (ANOSIM) was performed to test the effect of decay stage on the composition of fungal phylotypes. A permutational multivariate analysis of variance (PERMANOVA) based on Bray–Curtis dissimilarity of fungal phylotypes was also performed to test the effect of grass species, decay stage and its interaction on fungal phylotype composition. Phylotypes were rarefied at the lowest sequencing depth, 1563, and the PERMANOVA model (phylotype_bray_distance ~ grass*decay_stage) was ran using function adonis2 in the vegan package of R (Oksanen et al. 2019).

Table 1.

Repeated-measures analysis of variance (ANOVA) summary table indicating the effects of time and grass species on losses in leaf area-specific mass, nitrogen and phosphorus concentrations, carbon:nitrogen (C:N) and carbon:phosphorus (C:P) ratios, litter fungal biomass and glucosamine concentrations, and rates of fungal production and total microbial respiration

Across-subjects (plots) Within-subjects (plots)
Factor F value p value Factor F value p value
Response
 Area specific mass (mgC/cm2)a T 82.89,54 < 0.001 S 42.81,6 < 0.001
S × T 8.49,54 < 0.001
 Litter C mass remaining (%)a T 82.89,54 < 0.001 S 1.611,6 0.252
S × T 8.49,54 < 0.001
 Litter nitrogen (mgN/g dwt.)a T 10.09,54 < 0.001 S 0.0021,6 0.963
S × T 3.89,54 0.001
 Litter phosphorus (mgP/g dwt.)b T 35.59,54 < 0.001 S 4.71,6 0.073
S × T 10.09,54 < 0.001
 Litter C:Na T 10.59,54 < 0.001 S 0.051,6 0.838
S × T 3.79,54 0.001
 Litter C:Pa T 28.59,54 < 0.001 S 2.81,6 0.146
S × T 7.89.54 < 0.001
 Fungal biomass (mgC/gC)a T 36.69,54 < 0.001 S 22.51,6 0.003
S × T 1.99,54 0.062
 Glucosamine (mg/gC)a T 33.59,54 < 0.001 S 11.71,6 0.014
S × T 1.39,54 0.275
 Fungal production (mgC/gC/day)b T 57.79,54 < 0.001 S 0.411,6 0.847
S × T 1.09,54 0.458
 Microbial respiration (mgC/gC/day)a T 73.96,36 < 0.001 S 8.61,6 0.026
S × T 4.16,36 0.003
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Factors T = time (days) and S = species (S. scoparium and S. tenerum)

Bold p values indicate significance after Bonferroni adjustment (α = 0.005)

a

Loge—transformed prior to analysis

b

Square—root-transformed prior to analysis

Monte Carlo Simulation Analysis using Microsoft Excel PopTools add-ins was used to estimate cumulative fungal production, respiration (fungal and non-fungal), and mean fungal biomass. The raw dataset of estimated daily rates of fungal production and respiration and mean fungal biomass over the study period was resampled with replacement to produce 10,000 sets, from which the mean ± 1 SD were calculated. Variance of transformed variables, such as production:biomass ratio and fungal yield, were estimated using the delta method (Salkind 2007).

Results

Litter mass loss and nutrient dynamics

Initial leaf area-specific C mass of S. scoparium and S. tenerum leaves in October (day 0, peak living green mass) averaged 3.78 ± 0.40 and 5.18 ± 0.50 mgC/cm2 (mean ± 1 SE, n = 4), respectively. By the end of the study period (July), leaf area-specific C mass of S. scoparium and S. tenerum leaves had decreased to similar values, averaging 1.63 ± 0.08 and 1.67 ± 0.10 mgC/cm2, respectively (Fig. 1a). Hence, a significant decrease in S. scoparium and S. tenerum leaf C mass were observed over the course of natural senescence and decomposition of standing litter (p < 0.001, Table 1), with 55 and 67% of the initial leaf C lost over the study period, respectively (Fig. 1b). The resulting leaf litter decay rate (k) for S. scoparium was 0.0027 ± 0.0009/day (r2 = 0.84 ± 0.06) and 0.0051 ± 0.0006/day (r2 = 0.86 ± 0.06) for S. tenerum (mean ± SD). The estimated initial leaf masses (No) of S. scoparium and S. tenerum leaves were 89 ± 8 and 97 ± 13%, respectively. Decay rates (k) were significantly different between the Schizachyrium species (t = 7.6, p = 0.0047), with mass loss patterns of S. tenerum occurring at a much faster rate.

Fig. 1.

Fig. 1

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Changes in leaf area-specific mass (a) and percent leaf litter C remaining (b) of standing S. scoparium and S. tenerum leaves during the study period. Symbols indicate the mean ± 1 SE (n = 4)

Nitrogen and P concentrations of Schizachyrium leaves decreased significantly during plant senescence (p < 0.001, Table 1). Initial N and P concentrations of living S. scoparium and S. tenerum leaf blades were similar, averaging 6.53 ± 0.66 and 6.67 ± 1.04 mgN/g litter dwt. and 0.34 ± 0.02 and 0.31 ± 0.03 mgP/g litter dwt., respectively (Supporting Information Fig. S3a & S4a). Following senescence, N and P concentrations of S. scoparium and S. tenerum leaf blades decreased by roughly ~ 50 and ~ 30%, respectively, resulting in a corresponding significant increase in leaf litter C:N and C:P ratios (p < 0.001, Table 1, Fig. 2a, b). Similar patterns were also observed when examined on the basis of leaf area (cm2) versus leaf mass (Supporting Information Table S2, Fig. S3b & S4b). After this decrease, leaf litter N and P concentrations remained relatively stable until the end of the study period when both litter N and P concentrations increased, leading to a decrease in litter C:N and C:P ratios (Fig. 2a, b). No significant differences in the dynamics of N and P concentrations per unit leaf mass were observed between S. scoparium and S. tenerum (p > 0.05, Table 1).

Fig. 2.

Fig. 2

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Changes in the molar carbon:nitrogen (a) and carbon:phosphorus (b) ratios in S. scoparium and S. tenerum leaf litter during standing decomposition. Symbols indicate the mean ± 1 SE (n = 4)

Fungal biomass and glucosamine

Fungal biomass increased significantly in S. scoparium and S. tenerum leaves during plant senescence and standing litter decomposition (p < 0.001, Table 1), with peak fungal biomass accounting for 3.6 and 3.3% of the total detrital mass, respectively (Fig. 3a). Patterns of fungal biomass accrual in standing leaf litter were significantly different between S. scoparium and S. tenerum (p < 0.001, Table 1), with S. tenerum accumulating more fungal biomass during the early phases of standing leaf decomposition. Glucosamine (chitin) concentrations followed a similar pattern as fungal biomass (ergosterol) concentrations in both S. scoparium and S. tenerum leaf litter and were positively correlated (r = + 0.86 and + 0.85, respectively, p < 0.001, Pearson), with glucosamine increasing significantly during standing litter decomposition (p < 0.001, Table 1, Fig. 3b) and exhibiting greater, but not significant, accrual on S. tenerum litter (Table 1) during the early phases of leaf decomposition; similar patterns in ergosterol and glucosamine were also observed when examined on the basis of leaf area (cm2) (Supporting Information Table S2, Fig S5a & b). Changes in mean fungal biomass (mgC/gC) and glucosamine concentrations (mg/gC) within S. scoparium and S. tenerum leaves were negatively correlated with changes in mean area-specific leaf C mass (r ≥ − 0.86, p < 0.001, Pearson).

Fig. 3.

Fig. 3

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Patterns of fungal biomass (a) and glucosamine concentrations (b) in S. scoparium and S. tenerum leaf litter during standing decomposition. Symbols indicate the mean ± 1 SE (n = 4)

Fungal production and microbial respiration

Significant increases in rates of fungal production associated with S. scoparium and S. tenerum leaves were observed during the study period (p < 0.001, Table 1), with a large increase in fungal production occurring in February (111 days) (Fig. 4a). Rates then declined and remained lower until increasing in July at the end of the study period. No significant differences in rates of fungal production were observed between S. scoparium and S. tenerum (p > 0.05, Table 1). Corresponding rates of total microbial respiration (fungal + non-fungal) from S. scoparium and S. tenerum leaf litter, reported only from post leaf senescence onward, increased significantly during the study period (p < 0.001, Table 1) and followed a similar pattern as observed rates in fungal production (Fig. 4b). Rates of total microbial respiration were positively correlated with rates of fungal production in both S. scoparium and S. tenerum (r = + 0.84 and + 0.96, respectively, p < 0.001, Pearson). Throughout decomposition, microbial respiration rates from S. tenerum litter were higher, but not significantly, when compared to those from S. scoparium litter (Table 1). As observed for fungal biomass and glucosamine (above), similar patterns in fungal production and respiration were also noted when examined on the basis of leaf area (cm2) (Supporting Information Table S2, Fig S6a, b).

Fig. 4.

Fig. 4

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Rates of fungal production (a) and total microbial respiration (b) associated with S. scoparium and S. tenerum leaf litter during standing-litter decomposition. Note: Fungal production values for October–November (Day 0–27) were estimated based on fungal biomass (ergosterol) accrual. All other dates were determined based on instantaneous rates of 1-14C-acetate incorporation. Microbial respiration rates determined only during the post-senescence period of leaf decomposition. Symbols indicate the mean ± 1 SE (n = 4)

Cumulative fungal production and respiration rates

When integrated over the entire study period, estimated cumulative fungal production using Monte Carlo Simulation Analysis totaled 99 ± 6 and 73 ± 5 mgC/g initial detrital C in S. scoparium and S. tenerum (Table 2), which equated to fungal yields of 18 ± 4% and 11 ± 2%, respectively. Based on controlled antibiotic experiments (Supporting Information, Appendix S1, Fig. S1a, b), corresponding estimates of cumulative fungal respiration from S. scoparium and S. tenerum totaled 106 ± 7 and 174 ± 11 mgC/g initial detrital C, respectively, suggesting that a large portion of Schizachyrium leaf litter C is also mineralized by fungal decomposers during the standing litter phase (Table 2). Based on these estimates of fungal respiratory activity, total fungal assimilation (fungal production + respiration) could account for 37% of the total C losses observed during S. scoparium and S. tenerum standing litter decay (Table 2), respectively, with the remaining C losses occurring through a combination of other processes, such as plant senescence, leaching, photodegradation, or the activities of other microbial decomposers. Estimated carbon use efficiency (CUE) of fungal decomposers during S. scoparium and S. tenerum litter decay were 48% and 30%, respectively. In addition, cumulative increases in both estimated fungal production and fungal respiration were significantly related to cumulative losses in S. scoparium and S. tenerum leaf C mass (Fig S7a & b), which supports that our assumptions and approach to estimate daily and cumulative fungal production and fungal respiration are reasonable.

Table 2.

Total leaf C mass loss, cumulative fungal production, cumulative fungal and non-fungal respiration, mean fungal biomass, P/B ratio, turnover time, fungal carbon use efficiency (CUE) and estimated contribution (yield) of fungal decomposers during standing leaf decay of S. scoparium and S. tenerum

Parameter S. scoparium S. tenerum T. angustifolia T. domingensis
Terrestrial Grassland Freshwater Wetlands
Mississippi, USA Michigan, USA Alabama, USA
Total leaf mass loss (mgC/g initial leaf C) 552 ± 55 666 ± 42 556 ± 60 371 ± 39
Cumulative fungal production (mgC/g initial leaf C) 99 ± 6 73 ± 5 123 ± 10 39 ± 4
Cumulative fungal respiration (mgC/g initial leaf C) 106 ± 7 174 ± 11 – 136 ± 23b
Cumulative non-fungal respiration (mgC/g initial leaf C) 136 ± 9 134 ± 9 – –
Mean fungal biomass (mgC/g initial leaf C) 11 ± 0.3 11 ± 0.2 33 ± 11 17 ± 0.1
P/B ratioa 8.9 ± 0.6 6.8 ± 0.4 3.7 ± 1.3 2.3 ± 0.1
Turnover time (d)a 29 ± 2 39 ± 2 99 ± 34 145 ± 7
Fungal carbon use efficiency (%)a 48 ± 4 30 ± 2 – 23 ± 4
Fungal yield coefficient (%)a 18 ± 4 11 ± 2 22 ± 3 11 ± 1
Fungal contributions to overall leaf C loss (%)a 37 ± 8 37 ± 5 47 ± 5
Open in a new tab

Fungal carbon use efficiency (%) = cumulative fungal production/(cumulative fungal production + cumulative fungal respiration) × 100. Fungal yield coefficient (%) = cumulative fungal production/total leaf C mass loss × 100. The contribution of fungi (%) to overall C loss from standing litter = cumulative fungal production + cumulative fungal respiration/total leaf C mass loss × 100

Values for total leaf mass loss are the means ± 1 SE. Values for mean fungal biomass, cumulative fungal production and cumulative fungal and non-fungal respiration are the mean ± 1 SD, as estimated using Monte Carlo Simulation Analysis. Transformed variables, such as P:B ratio, turnover time, fungal growth efficiency, fungal yield coefficient and fungal contribution are the mean ± 1 SD

a

Error estimates determined using the delta method (Salkind 2007)

b

Assumes that all respiratory activity is due to fungi

Fungal community composition and dynamics

A total of 174,268 sequence reads were obtained from 24 individual litter samples using Illumina MiSeq high-throughput sequencing (mean ± SD = 7261 ± 4489 per sample). Across all samples, a total of 587 fungal phylotypes were detected, with most of the sequences attributed to the phyla Ascomycota and Basidiomycota (Fig. 5a, b). In contrast, only 130 total sequences were attributed to the Mucoromycota, which were almost entirely attributed to a single species, Umbelopsis gibberispora. Thirty phylotypes accounted for ~ 85% of the total sequence reads, whereas 350 phylotypes were each represented by 5 or less sequence reads, and 105 by just 1 sequence. Many of the detected phylotypes were not fully taxonomically resolved (i.e., unclassified) and at times were only partially assigned into a broader fungal lineage (i.e., order or family). Supplemental Table S3 lists the most abundant phylotypes (those > 100 sequence reads) observed from S. scoparium and S. tenerum leaves during early (post-senescence–November), mid (March) and late (July) stages of litter decomposition.

Fig. 5.

Fig. 5

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Relative abundance of major fungal phylotypes identified in S. scoparium (a) and S. tenerum (b) leaf litter based on ITS 1 rRNA gene sequence reads from Illumina MiSeq high-throughput sequencing. Values are expressed as percentages of sequences obtained within each month for S. scoparium and S. tenerum. Stacked bars indicate the mean − 1 SD (n = 4)

Following leaf senescence in November, unclassified Ascomycetes and those classified within the Dothideomycetes (Capnodiales and Pleosporales) and the Sordariomycetes (Glomerellales and Hypocreales) were among the most abundant sequences detected during the early stages of S. scoparium and S. tenerum leaf decomposition (Fig. 5a, b). The most abundant Ascomycete phylotypes identified from S. scoparium leaf litter during this time included Septophoma sacchari, Uwebraunia musae, Toxicocladosporium strelitziae, Colletotrichum sp., Alternaria sp., Teratosphaeria sp., and Microcyclospora quercina (Table S3). Likewise, the most abundant phylotypes identified from S. tenerum leaf litter included Uwebraunia musae, Colletotrichum sp., and Alternaria sp. (Table S3).

As standing leaf decomposition commenced (mid-March), the relative abundance of these initial Ascomycete phylotypes decreased, whereas the relative abundance of other fungal phylotypes within both the Ascomycetes and Basdiomycetes increased, in particular Catenulostroma hermanusense and Mycena sp. During later stages of leaf decomposition (late July), the abundance of sequences identified as Basidiomycete phylotypes in the Agaricomycetes (Agaricales and Polyporales) increased dramatically (Fig. 5a, b). The major phylotypes identified from leaf litter during this time were Mycena sp., Xenasmatella christiansenii, Marchandiomyces corallinus, Clitocybula sp., an unclassified phylotype within the Agaricales (Marasmiaceae) (Table S3).

Two-dimensional NMDS ordinations based on Bray–Curtis dissimilarity scores were sufficient to account for phylotype differences in S. scoparium and S. tenerum (stress = 0.12), yielding a consistent pattern showing temporal changes in the observed fungal phylotype community during early, mid and late decay stages of litter decomposition (Fig. 6a, b). Analysis of similarity (ANOSIM) confirmed that there was a significant temporal difference in the fungal community detected in both S. scoparium and S. tenerum (R value = 0.476, p = 0.001). However, subsequent post hoc comparisons examining fungal phylotypes between specific dates (November, March and July) were not statistically significant when α < 0.05 was Bonferroni-corrected for multiple pairwise comparisons. The permutational multivariate analysis of variance (PERMANOVA) confirmed that there was a significant difference in fungal phylotypes between plant species (F = 3.181,18 p = 0.005), decay stage (F = 6.152,18 p = 0.001), and plant species × decay stage interaction (F = 2.362,18 p = 0.001).

Fig. 6.

Fig. 6

Open in a new tab

Non-metric multidimensional scaling (NMDS) ordinations (stress 0.12) of community dissimilarity patterns in S. scoparium (a) and S. tenerum (b) leaf litter during standing decomposition as determined from relative abundance-based sequence metrics

Discussion

In the present study, significant changes in Schizachyrium leaf C and nutrients (N and P) were observed during standing litter decay, which concurs with recent research findings that appreciable transformation and decomposition of terrestrial grass litter can occur during the standing-dead phase (Liu et al. 2015; Wang et al. 2017a; Evans et al. 2019). In Schizachyrium, rapid losses in leaf C mass and nutrients were observed during the transition of plant leaves from a living green to fully brown (dead) condition. During this senescence phase, fungal biomass and growth within plant leaves were noticeably low, suggesting that these initial declines in Schizachyrium leaf C mass were likely a result of plant translocation and reabsorption to belowground rhizomes during plant senescence or through leaching losses (Vergutz et al. 2012; Burke et al. 2017). Losses in leaf C mass continued following senescence, which were accompanied by a concomitant increase in the production and biomass accumulation of fungal decomposers and the respiration rates of the collective litter inhabiting microbial community (fungal and non-fungal). These observed patterns for S. scoparium and S. tenerum underscores that studying plant decomposition is not a simple matter in grassland systems, as complex changes in mass loss, nutrient concentrations, and microbial colonization and production typically occur during the natural progression of plant matter through senescence and early standing litter decomposition, prior to its collapse to the soil surface environment.

Collectively, these findings from terrestrial grasslands are not particularly surprising to researchers investigating standing litter decomposition in wetland ecosystems, where strikingly similar spatial and temporal microbial decay patterns have been known for nearly three decades. A number of studies conducted in both salt and freshwater emergent marshes have firmly established that microbial communities, particularly fungi, are well-adapted to life in the harsh standing litter environment (e.g., Kuehn et al. 1998), where they rapidly shift (< 5 min.) their metabolism from an inactive to a fully active state when water becomes available (e.g., Gallagher et al. 1984; Newell et al. 1985; Kuehn and Suberkropp 1998; Kuehn et al. 1999, 2004; Welsch and Yavitt 2003). Furthermore, studies have also documented that a sizable fraction of the plant litter C is channeled into and through litter-inhabiting fungal decomposers, with cumulative fungal production and respiratory loss, which is likely fungal (see Jacobson et al. 2015), accounting for a significant portion of the observed losses in standing litter mass (Newell 1996; Newell et al. 1996; Newell and Porter 2000; Gessner 2001; Kuehn et al. 2011; Su et al. 2015).

For example, Su et al. (2015) observed significant increases in both fungal biomass (ergosterol) and glucosamine (chitin) during standing leaf litter decomposition of Typha domingensis. During that study, cumulative fungal production within leaf litter totaled 39 mg fungal C/g initial detrital C (Table 2), indicating that 11% of the observed leaf C lost was transformed into fungal biomass (see also Kuehn et al. 2011). Corresponding estimates of cumulative microbial respiration from decaying T. domingensis leaves totaled 133 mg C/g initial detrital C, indicating that a significant fraction of the standing Typha litter C (~ 36%) was also mineralized. When integrated over the entire study period, cumulative increases in both fungal production and microbial respiration were significantly related to cumulative losses in T. domingensis leaf C mass, providing evidence that a significant fraction of the plant detrital C is channeled into and likely through litter-associated fungi during standing litter decomposition.

Similar findings were observed in the present study, with S. scoparium and S. tenerum leaf litter losing 55% and 67% of their leaf C during standing decomposition, respectively. During this time, rates of fungal production associated with S. scoparium and S. tenerum leaves increased, averaging 1.52 mgC/g detrital C/d and 1.21 mgC/g detrital C/d, respectively, which are similar to rates of fungal production reported from standing emergent macrophyte litter in wetlands ecosystems (Newell 2001a, b; Newell et al. 1995, 2000; Kuehn et al. 2011; Su et al. 2015; Kuehn 2016, references therein). When integrated over the study period, estimated cumulative fungal production associated with S. scoparium and S. tenerum averaged 99 and 73 mgC/g initial detrital C, respectively, which translated into 18% and 11% of the leaf C being transformed and converted into fungal biomass. Likewise, estimates of fungal respiration from S. scoparium and S. tenerum leaf litter also indicated that a sizable fraction (19% and 26%, respectively) of the leaf C was also respired by litter-inhabiting fungal decomposers. Estimated fungal carbon use efficiencies were within the range reported for fungal decomposers in other studies (e.g., Sinsabaugh et al. 2015), providing support that our approach for estimating fungal respiration is reasonable. Similar to Su et al. (2015), when integrated over the entire study period, cumulative increases in both fungal production and estimated fungal respiration were significantly related to cumulative losses in standing S. scoparium and S. tenerum leaf C. This evidence, together with prior research from wetland systems, implies that fungi may play a key role in the transformation and decomposition of standing litter within a variety of ecosystems, prior to its collapse and continued microbial decay at or within the soil/sediment environment (Kuehn 2016).

Next generation sequencing identified a diverse assemblage of decomposer fungi associated with standing Schizachyrium litter, which exhibited a distinct successional pattern during standing litter decay. Such a pattern is consistent with the sequential senescence, death and decay of Schizachyrium litter since the enzymatic degradation and assimilation of the litter substrate by microbial assemblages, which is most likely fungi (Schneider et al. 2012), often leads to a progressive change in its chemical composition (i.e., increasing recalcitrant C). However, seasonal effects (i.e., temperature) may have also partially influenced this successional pattern, as standing litter was collected throughout the year. Chemical changes are frequently accompanied by a shift in fungal taxa (Frankland 1998), favoring taxa that can catabolically compete, via their degradative enzyme capabilities (Kjøller and Struwe 2002), for acquisition of litter C and nutrients to support their maintenance, growth and reproduction (i.e., sporulation). In the present study, Ascomycetes were the most prevalent taxa (e.g., Alternaria sp., Colletotrichum sp.) associated with standing Schizachyrium litter during the early stages of litter decomposition, which were then followed by an increased presence of Basidiomycetes (e.g., Mycena sp., Xenasmatella christiansenii) during more advanced stages of decomposition. Similar patterns of fungal succession have been reported for litter at the soil surface (e.g., Vorísková and Baldrian 2013; Bödeker et al. 2016; Purahong et al. 2016), implying that fungal decomposers in standing litter may share similar dynamics as plant litter at or within the soil environment.

Collectively, the patterns in fungal communities assessed using modern genomic methods align remarkably well with the classical 3-stage view of fungal succession proposed over 50 years ago (Garrett 1963; Hudson 1968), where a succession of fungal groups (e.g., guilds, see Bödeker et al. 2016) takes place as the litter substrate becomes progressively decomposed and depleted in carbon (i.e., increasing recalcitrant litter C fractions). Using classical morphological-based identification techniques, previous researchers observed that initial fungal colonizers of plant litter (stage 1) comprised a group of “sugar fungi” that metabolize simple sugars and other labile carbon compounds that remain following plant senescence. These fungi were eventually replaced (stage 2) by other fungal taxa (e.g., Ascomycetes) capable of hydrolyzing cellulose and other plant structural polymers. Lignin-degrading fungal taxa, particularly members of the Basidiomycetes like Mycena and X. christiansenii, dominate the later stages of litter decomposition (stage 3) due to their greater ligninolytic capabilities (Osono 2007).

In grasslands, as well as most other terrestrial ecosystems, water availability is frequently identified as the critical factor influencing microbial activities (Borken and Matzner 2009; Manzoni et al. 2012). A growing number of studies have now established that microbial decomposers inhabiting standing litter, particularly fungi, can rapidly shift their metabolic activities during alternating periods of water availability (e.g., Gallagher et al. 1984; Newell et al.1985; Kuehn and Suberkropp 1998; Kuehn et al. 2004; Jacobson et al. 2015; Evans et al. 2019). For example, under field conditions and in the absence of precipitation, Kuehn and Suberkropp (1998) observed that rates of microbial respiration (CO2 evolution) from standing litter of the freshwater emergent macrophyte Juncus effusus exhibited a pronounced diel periodicity, with the highest rates coinciding with nighttime increases in relative humidity and subsequent dew formation on the surfaces of standing plant litter. In contrast, rates of microbial respiration virtually ceased during the day as a result of increased daytime temperatures, litter drying and ensuing microbial desiccation stress (see also Kuehn et al. 1998). Similar patterns of microbial respiratory activity (CO2 evolution) observed in terrestrial standing grass litter (Dirks et al. 2010; Jacobson et al. 2015; Gliksman et al. 2017; Wang et al. 2017a; Evans et al. 2019), and affirmed by our quantitative assessment showing significant fungal contributions to standing litter decay, suggest that temperature-driven increases in nighttime relative humidity and dew formation is likely a key physiological strategy for fungal survival and growth in the standing litter environment (Kuehn 2016). Here, fungal decomposers can rapidly take advantage of even short-term periods of water availability to exploit detrital resources.

Conclusions

Our findings indicate that paradigms of senescence, microbial colonization and decomposition of standing plant litter are not just restricted to humid wetland ecosystems, but may be a typical decay sequence observed in standing litter within a variety of ecosystems, whereby fungi are a key microbial participant in standing litter decomposition. Such fungal-mediated processes should be recognized and integrated into conceptual C and nutrient cycling models (e.g., Newell and Porter 2000) for ecosystems that possess a natural standing litter component.

Supplementary Material

SuppMat

Acknowledgements

We would like to extend our gratitude to Dr. Gene Saucier for allowing access to his property where this study was conducted. We also thank Stephanie Koury for providing assistance in both the field and laboratory. This research was supported from grants from the National Science Foundation (DBI 0923063) and (EPS-0909787) through a subaward from Mississippi State University (190200.362492.05). The UMMC Molecular and Genomics Facility utilized in the study is supported, in part, by funds from the National Institute of General Medical Sciences (NIGMS), including the Mississippi IDea Networks of Biomedical Science (INBRE) (P20GM103476), Center for Psychiatric Neuroscience - Centers of Biomedical Research Excellence (CPN)-COBRE (P30GM103328), Obesity, Cardiorenal and Metabolic Diseases—COBRE (P20GM104357) and Mississippi Center of Excellence in Perinatal Research (MS-CEPR)-COBRE (P20GM121334).

Footnotes

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s00442-020-04838-y.

Data availability

Data included in this manuscript may be found in the Dryad Digital Repository (https://doi.org/10.5061/dryad.t76hdr801). Fungal sequence data generated from this project are available in the NCBI Sequence Reads Archive under BioProject PRJNA683919.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

SuppMat
NIHMS1786322-supplement-SuppMat.pdf (1.4MB, pdf)

Data Availability Statement

Data included in this manuscript may be found in the Dryad Digital Repository (https://doi.org/10.5061/dryad.t76hdr801). Fungal sequence data generated from this project are available in the NCBI Sequence Reads Archive under BioProject PRJNA683919.

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