for review onlynature.berkeley.edu/brunslab/mycorrhizal/papers/fukami...for review only 1 assembly...

For Review O

nly

Assembly history dictates ecosystem functioning: evidence

from wood decomposer communities

Journal: Ecology Letters

Manuscript ID: ELE-00968-2009.R1

Manuscript Type: Letters

Date Submitted by the

Author: 02-Jan-2010

Complete List of Authors: Fukami, Tadashi; Stanford University, Department of Biology Dickie, Ian; Landcare Research Wilkie, J. Paula; Landcare Research Paulus, Barbara; Landcare Research Park, Duckchul; Landcare Research Roberts, Andrea; Landcare Research Buchanan, Peter; Landcare Research Allen, Robert; Landcare Research

Key Words:

assembly rules, biodiversity, carbon sequestration, climate change, community assembly, ecosystem functioning, New Zealand Nothofagus (beech) forests, priority effect, saprotophic fungi, wood

decomposition

Ecology Letters

For Review O

nly

1

Assembly history dictates ecosystem functioning: evidence from wood decomposer communities Tadashi Fukami1,2,3, Ian A. Dickie2, J. Paula Wilkie3, Barbara C. Paulus3, Duckchul Park3, Andrea Roberts3, Peter K. Buchanan3, and Robert B. Allen2 1Department of Biology, Stanford University, Stanford, CA 94305, USA 2Landcare Research, Lincoln 7640, New Zealand 3Landcare Research, Auckland 1142, New Zealand E-mail addresses: [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected] Short running title: carbon dynamics and fungal community assembly Keywords: assembly rules, biodiversity, carbon sequestration, climate change, community assembly, ecosystem functioning, New Zealand Nothofagus (beech) forests, priority effect, saprotophic fungi, wood decomposition Type of article: Letter Number of words in the abstract: 136 Number of words in the manuscript as a whole: 6,170 Number of words in the main text (excluding abstract, acknowledgements, references, table and figure legends): 4,158 Number of references: 50 Number of figures: 5 Number of tables: 0 Corresponding author: Tadashi Fukami, Department of Biology, Stanford University, Stanford, CA 94305, USA. Telephone: +1 650 721 1711, Fax: +1 650 723 6132, E-mail: [email protected]

Page 1 of 31 Ecology Letters

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

2

Abstract 1

Community assembly history is increasingly recognized as a fundamental 2

determinant of community structure. However, little is known as to how assembly history 3

may affect ecosystem functioning via its effect on community structure. Using wood-4

decaying fungi as a model system, we provide experimental evidence that large differences 5

in ecosystem functioning can be caused by small differences in species immigration history 6

during community assembly. Direct manipulation of early immigration history resulted in 7

three-fold differences in fungal species richness and composition and, as a consequence, 8

differences of the same magnitude in the rate of decomposition and carbon release from 9

wood. These effects—which were attributable to the history-dependent outcome of 10

competitive and facilitative interactions—were significant across a range of nitrogen 11

availabilities observed in natural forests. Our results highlight the importance of 12

considering assembly history in explaining ecosystem functioning. 13

Page 2 of 31Ecology Letters

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

3

Introduction 1

Community structure is now considered a key determinant of ecosystem functioning 2

(Loreau et al. 2001; Hooper et al. 2005). For example, recent studies have emphasized the 3

species diversity and composition of producers (e.g., De Deyn 2008; Weedon et al. 2009) 4

and decomposers (e.g., Deacon et al. 2006; Hanson et al. 2008) as a driver of ecosystem 5

carbon dynamics. These studies have helped to integrate two research fields that are closely 6

related, yet, until recently, conceptually separated—community ecology and ecosystem 7

ecology. Nevertheless, understanding how community structure affects ecosystem 8

functioning remains challenging because consequences often appear highly idiosyncratic 9

and difficult to predict (e.g., Lawton 1999; Emmerson et al. 2001; Wardle 2002; Heimann 10

& Reichstein 2008). Despite this difficulty, a clearer understanding of ecosystem 11

functioning is essential both for advancing ecological theory and for solving environmental 12

issues such as mitigating adverse effects of carbon emissions (Heimann & Reichstein 2008). 13

The apparent idiosyncrasies observed in carbon dynamics and other ecosystem 14

functioning may result from a current lack of historical perspectives (Ostfeld & LoGiudice 15

2003). Numerous studies have suggested that community assembly history, or the sequence 16

and timing in which species join an ecological community, can profoundly affect species 17

diversity and composition (e.g., MacArthur 1972; Drake 1991; Chase 2003; Shurin et al. 18

2004; Kennedy et al. 2009). Furthermore, the strength of these historical effects has been 19

shown to depend on predation (e.g., Morin 1984; Steiner & Leibold 2004; Louette & De 20

Meester 2007), disturbance (e.g., Jiang & Patel 2008), productivity (e.g., Steiner & Leibold 21

2004), ecosystem size (e.g., Fukami 2004), and other environmental conditions (Chase 22

2003). However, surprisingly few studies have evaluated the role of assembly history in 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

4

explaining variability in ecosystem functioning. Notably, one microcosm study examined 1

effects of colonization sequence on ecosystem functioning (algal biomass production), but 2

only two species were introduced to each microcosm (Zhang & Zhang 2007). Although 3

another important study used more species, only one measurement of ecosystem 4

functioning (plant biomass) was examined (Körner et al. 2008). 5

We suggest that filling the conceptual gap between assembly history–community 6

structure relationships on one hand, and community structure–ecosystem function 7

relationships on the other, is crucial to achieving a comprehensive understanding of 8

ecosystem functioning. Potential links between assembly history, community structure, and 9

ecosystem functioning are not necessarily straightforward. For example, even a small 10

historical effect on community structure may result in large variation in ecosystem 11

functioning if the small compositional difference is due to one, or a few, functionally 12

important species occupying different communities. On the other hand, if variation in 13

assembly history results in taxonomically divergent, but functionally convergent 14

community structure (e.g., Fukami et al. 2005), assembly history may be important to 15

community structure, but not to ecosystem functioning. These possibilities have rarely been 16

tested. 17

In this paper, we experimentally test the hypothesis that community assembly 18

history affects ecosystem functioning via its effect on community structure, using wood-19

decaying fungi as a model system. Our laboratory study involved direct manipulation of 20

species immigration history, an approach necessary for a rigorous test of the role of biotic 21

historical contingency in community assembly and its consequences for ecosystem 22

functioning. The high level of experimental control afforded in the laboratory would have 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

5

been impossible to achieve under most field conditions, necessitating the laboratory 1

approach (Cadotte et al. 2005). We will, however, use our results to discuss why we expect 2

fungal community assembly history to influence carbon dynamics in natural forest 3

ecosystems across a wide range of spatial scales. 4

5

Wood-decaying fungi as a model system 6

Decomposition by wood-decaying fungi plays a central role in the storage and 7

release of carbon and nutrients in forest ecosystems (Harmon et al. 1990; Zimmerman et al. 8

1995; Delaney et al. 1998). Furthermore, wood-decaying fungi form an important system 9

for studying immigration history and carbon dynamics, for several reasons. First, fungal 10

species differ markedly in the way they decompose wood (Harmon et al. 1994; Worrall 11

1997), making decomposition rates dependent on fungal community structure (Boddy et al. 12

1989). Second, immigration history can be highly variable in these fungi. Although some 13

species tend to colonize wood earlier than others (Coates & Rayner 1985; Jonsson et al. 14

2008), both spore dispersal and mycelial spread through soil—two main colonization 15

strategies—contribute to stochastic variation in the timing of species immigration among 16

wood substrates (Jonsson et al. 2008). In addition, some fungal species may already be 17

present in functional sapwood or bark as latent propagules (Boddy 2000), which may affect 18

colonization success of fungal species that arrive later. Third, once they colonize a substrate, 19

fungal species affect others through strong antagonistic (combative) and facilitative 20

interactions (Coates & Rayner 1985; Holmer & Stenlid 1997; Heilmann-Clausen & Boddy 21

2005). Strong interactions, coupled with variable immigration history, have the potential to 22


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

6

cause multiple trajectories of fungal community development (Coates & Rayner 1985) and, 1

consequently, wood decomposition. 2

3

Materials and Methods 4

Overview 5

We inoculated 10 species of fungi onto wood disks in laboratory microcosms, 6

manipulating assembly history by inoculating one species four weeks before the remaining 7

nine species, while holding constant the set of species introduced and the spatial position of 8

inoculation. We created seven different assembly histories (logistical limitations prevented 9

all 10 species from being used as initial species). Additionally, in order to test whether 10

assembly history effects vary with environmental conditions, we also manipulated nitrogen 11

availability. Our experiment had a fully factorial design, with three levels of nitrogen 12

addition spanning the natural variability in soil nitrogen found in our study system. We 13

monitored wood decomposition and carbon dynamics for a year after we introduced all 14

fungal species. 15

16

Fungal cultures 17

Pure cultures of 96 fungal species were isolated onto malt extract agar (12.5 g malt 18

extract and 20 g agar in 1000 ml water) from a total of 143 fungal collections made over a 19

two-day period (11-12 May 2006) in a nearly monospecific Nothofagus solandri forest 20

(Allen et al. 2000; Clinton et al. 2002) at Craigieburn Forest Park, South Island, New 21

Zealand (43°8.556S, 171°42.825E, 1000 m elevation). Fungal strains were derived by 22

isolation either directly from fruiting bodies or from supporting substrate immediately 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

7

adjacent to the fruiting body. All of our strains are therefore presumed to be heterokaryotic. 1

Ten of the 96 species were selected for experimental use (Table S1 in Supporting 2

Information) based on feasibility of handling in culture, phylogenetic spread across the 3

Ascomycota and the Basidiomycota, and so as to ensure a minimum 9 base-pair (bp) 4

separation of the nuclear ribosomal internal transcribed spacer (ITS) polymerase chain 5

reaction (PCR) product lengths (final range 522 to 808 bp). Fungal cultures were initially 6

maintained on plates of malt extract agar. The cultures have been archived in liquid 7

nitrogen in the International Collection of Micro-organisms from Plants (ICMP). Collected 8

sporocarps have been accessioned into the New Zealand Fungal Herbarium (PDD; Table 9

S1). We confirmed that when inoculated alone, all species grew on wood under the 10

experimental conditions. 11

12

Wood disks and experimental jars 13

Twenty-eight live trunks of N. solandri were felled in a regenerating stand of mixed 14

beech in the Maruia Valley, South Island, New Zealand. Wood disks (machined wet to 8 15

cm diameter, 1 cm thick, across the grain) were obtained from these trunks. Disks were 16

dried at room temperature for approximately 20 days, oven-dried for 48 hours at 40oC, and 17

individually weighed (initial dry diameter 7.6 ± 0.1 cm, thickness 1.1 ± 0.03 cm, weight 18

28.8 ± 0.08 g; mean ± one standard error of mean). Disks were then soaked in tap water for 19

48 hours prior to placing on dry soil in each jar. 20

Eight-hundred grams of well-mixed dried infertile mineral soil (from the forest 21

where the fungi were collected) and a wet wood disk were placed in each 2-liter glass jar, 22


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

8

and 400 ml of tap water added. Wood disks were randomly assigned to jars. Prior to adding 1

the water, varying amounts of ammonium-nitrate (NH4NO3) were added to the water (see 2

below). The jars were then autoclaved twice for 45 minutes at 121oC with a 24-hour gap 3

between each autoclaving before initial fungal species inoculation. Each of 42 treatments in 4

a factorial design (i.e., 7 immigration histories x 3 levels of nutrient availability x 2 harvest 5

times; see below) was replicated 5 times. Throughout the experiment, the jars were covered 6

by loose lids and stored in the dark in the laboratory, arranged randomly in a block design, 7

at a mean temperature of 20.6oC and a mean relative humidity of 55.9 %. 8

9

Nitrogen availability 10

Initial nitrogen level was manipulated by adding 0, 0.5 or 1.0 g of NH4NO3, 11

dissolved in 400 ml water, to 800g of soil per jar. This range was used so as to capture the 12

spatial variation observed in natural forest soils: the highest amount of NH4NO3 added 13

matched the level of nitrogen in the soil organic layer and exceeded the level of nitrogen in 14

the most fertile mineral soils in the mountain range where the fungi were collected (Allen et 15

al. 2000; Clinton et al. 2002). We used NH4NO3 for nitrogen addition in order to minimize 16

pH changes by using a charge balanced source. Although we do not have information on 17

which of the fungi use NO3, it is relevant as a nitrogen source for the following reasons. 18

Both NO3 and NH4 are present in New Zealand Nothofagus forest soils (Clinton et al. 1995, 19

Dickie et al. 2009). Furthermore, nitrogen from NO3 and NH4 ends up in similar 20

compounds during organic matter decomposition in these forests (Clinton et al. 1995). 21

Finally, NO3 levels increased following a major disturbance (approximately, from 1/10 to 22


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

9

1/2 of NH4 levels), so arguably, a major dead wood input event might occur along with a 1

NO3 pulse (Dickie et al. 2009). 2

3

Immigration history 4

From colonies on agar plates of each of the 10 fungal species, 5 mm diameter plugs 5

were aseptically removed, and one plug of each species was placed onto a pre-determined 6

location on each wood disk contained within the experimental jars (Fig. 1). One of the 10 7

species was inoculated aseptically by itself, and the other nine inoculated four weeks after 8

the first species inoculation, spaced evenly about the circumference of the disk (Fig. 1). 9

Immigration history was manipulated by varying the species for the first inoculation. Seven 10

of the ten (Fig. 2) were randomly selected for use as initial species. The relative locations of 11

inoculation points of the species were held constant across history treatments (Figs S1-3). 12

Our method of giving a single species a head start facilitated interpretation of how each 13

early-arriving species affected late-arriving species. 14

15

Species occurrence 16

At two harvest dates (4 and 12 months after all species were introduced), fungal 17

community composition was determined at nine pre-determined spatial points on each 18

wood disk. For this purpose, we destructively harvested wood disks (i.e., different wood 19

disks were sampled first at 4 months and then at 12 months). Working inside a laminar flow 20

cabinet, we removed wood disks from the experimental jars and split the disks along eight 21

radial lines, aligned according to the location of the initial fungal inoculation points (see 22

Fig. S1 for sawdust sampling locations), using custom manufactured wood-splitting devices 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

10

to expose internal wood without contamination from the surface of disks. Sterilized 1

(ethanol flamed) 1.5-mm drill bits were used to obtain 5.5 mg (mean; n = 20, range: 2.0 to 2

9.0 mg) of sawdust from the split-edge exposed interior of disks, directly collected into 3

sterile 0.2-ml tubes. Although we do not have data to confirm that the amount of sawdust 4

does not affect the frequency of species occurrence, there was no systematic bias between 5

treatments in the amount of sawdust sampled. A modified length-heterogeneity polymerase 6

chain reaction (LH-PCR) assay was used to identify fungal species. Specifically, DNA was 7

extracted and PCR of the ITS region carried out using the Sigma REDExtract-N-Amp Plant 8

PCR kit, and primers ITS1F-6FAM and ITS4-VIC following standard protocols (Dickie et 9

al. 2009). The length of PCR products was determined by 50-cm capillary electrophoresis 10

in a 3130xl Genetic Analyzer (Applied Biosystems, USA). Results were analyzed with a 11

modified version of TRAMPR software in R (FitzJohn & Dickie 2007). As species had 12

been selected to insure a minimum 9 bp separation in PCR product lengths, this provided a 13

robust method of species identification. 14

15

Carbon and decomposition measurements 16

Respiration rate was measured 0, 2, 4, 6, 9 and 11 months after all fungal species 17

were introduced, by temporarily sealing jar lids closed, then sequentially drawing three 5-18

ml atmospheric samples across a period of 25 min through a gas port inserted into jar lids. 19

The gas headspace volume was approximately 1 liter (i.e., jar volume minus soil volume). 20

Atmospheric CO2 concentrations were determined by injection into a PP Systems EGM-4 21

Environmental Gas Monitor for CO2 (PP Systems, USA). The increase in gas concentration 22

over time (median R2 = 0.98) was used to calculate respiration rate. At the 4- and 12-month 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

11

harvests (4 and 12 months after all species were introduced), nitrogen and carbon 1

concentrations of each wood disk were measured from a combined sawdust sample 2

comprising 8 sub-samples each from a different split-edge interior disk surface using 2-mm 3

drill bits. Also at the 4- and 12-month harvests, percentage wood mass remaining 4

(including fungal biomass in wood) was measured for each disk as the proportion of dry 5

weight at the harvest to initial dry weight (after drying at 40oC). We also measured nitrogen 6

and carbon concentrations of the soil in each jar at the start of the experiment and at the 4- 7

and 12-month harvests. Soil nitrogen and carbon showed little change over time. 8

9

Statistical analysis 10

To evaluate effects of initial species and nitrogen level on fungal community 11

structure, a principal component analysis (PCA) was performed, with the frequency 12

(percentage of wood volume occupied) of each of the 10 species as variables. Species 13

frequency was calculated as the percentage of the sawdust samples in which the species 14

was detected out of the 9 sawdust samples from each wood disk (more than one species 15

may occupy the same sawdust sample concurrently). PCA is a statistical tool to reduce 16

many variables (in this case, species) to a small number of newly derived variables that 17

summarize the original information. Non-metric multidimensional scaling (NMDS), which 18

is also commonly used for the same purpose as PCA but with less restrictive assumptions, 19

yielded qualitatively identical results to the PCA. Multivariate analysis of variance 20

(MANOVA) was also conducted, with initial species, nitrogen level and their interaction as 21

independent variables and the frequency of each of the 10 species as dependent variables. 22

Permutational multivariate analysis of variance using distance matrices (ADONIS) yielded 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

12

qualitatively the same results as the MANOVA. To test for effects of initial species and 1

nitrogen level on individual species frequencies and on ecosystem measurements, analyses 2

of variance (ANOVAs) were performed, with initial species, nutrient level and their 3

interaction as independent variables and species frequencies (Figs 2, 3 and S2-4) or 4

ecosystem measurements (Figs 4 and S5) as dependent variables. 5

6

Results 7

Effects of assembly history on community structure 8

Manipulation of early assembly history during the initial 4-week period of the 9

experiment resulted in substantial variation in fungal community structure, which persisted 10

for at least 12 months (Figs 2, S2 and S3). Across the wide range of nitrogen availabilities 11

observed in natural forests (Allen et al. 2000, Clinton et al. 2002), fungal species richness 12

showed up to three-fold differences between history treatments (Fig. 2), ranging from 1.3 ± 13

0.1 in treatments where Phlebia nothofagi was introduced first to 4.4 ± 0.3 in those where 14

Trametes versicolor was introduced first (means ± 1 standard error of mean; P < 10-5, 15

ANOVA). A principal component analysis (PCA) revealed that species composition was 16

also strongly affected by immigration history, showing in some cases more than a three-17

fold difference in the distance in the PCA multi-dimensional space (Fig. S4A-C). For 18

example, within high nitrogen treatments, wood disks to which Bisporella citrina or 19

Phlebia nothofagi were introduced first were clearly distinct in final species composition 20

from those to which Ascocoryne sarcoides, Calocera cf sinensis or Trametes versicolor 21

were introduced first (Fig. S4C). The effects of immigration history were consistently 22


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

13

significant at all nitrogen levels (MANOVA, P <10-9), even though the distribution of 1

communities in the PCA space differed between nitrogen treatments (Fig. S4A-C). 2

Our data indicate that these differences in community structure resulted from 3

complex inter-specific interactions whose outcome depended on immigration history and 4

nitrogen availability. We highlight the behavior of three species—Phlebia nothofagi, 5

Trametes versicolor and Bisporella citrina—as illustrative examples (Fig. 3). P. nothofagi 6

was ubiquitous, occupying more than 70% of disk volume in most cases (Fig. 3A-C). 7

However, when T. versicolor was introduced first, P. nothofagi occupied less than 5% and 8

40% of disk volume under low (Fig. 3A) and moderate (Fig. 3B) nitrogen levels, 9

respectively. T. versicolor itself was uncommon when introduced after any other species. In 10

contrast, it was widespread when introduced first (Fig. 3D-F). Meanwhile, B. citrina was 11

also unable to establish in the majority of cases (Fig. 3G-I), but when T. versicolor was 12

introduced first, B. citrina occupied more wood volume than otherwise in moderate (Fig. 13

3H) and high (Fig. 3I) nitrogen treatments. These patterns, together with the spatial 14

distribution of the species (Figs S2 and S3), suggest that T. versicolor facilitates B. citrina 15

by becoming dominant and suppressing the otherwise inhibitive P. nothofagi, but that this 16

facilitation is realized only when T. versicolor arrives first, and it is more apparent at higher 17

nitrogen levels. 18

19

Effects of assembly history on carbon dynamics 20

Assembly history also had striking effects on wood decomposition and carbon 21

dynamics. For example, we found as much as three-fold differences between history 22

treatments in the rate of carbon release by fungal activity. Across the nitrogen gradient (Fig. 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

14

4A-C), these differences persisted over time, with significant effects at both initial and final 1

stages of the experiment (Fig. S5). Consistent with this result, wood mass loss—an 2

indicator of cumulative carbon respiration over the course of the experiment—was strongly 3

affected by immigration history (Fig. 4J-L). Although our measure of wood mass included 4

both the wood itself and any fungal biomass accumulated in the wood, wood mass was in 5

some cases reduced to almost half of the initial value by the end of the experiment (Fig. 4J-6

L), indicating that experimental duration encompassed a significant proportion of 7

decomposition and carbon respiration. Historical effects were also significant on wood 8

nitrogen content (Fig. 4D-F) and wood carbon-to-nitrogen ratio (Fig. 4G-I) at all initial 9

nitrogen addition levels. Overall, for all but one (wood nitrogen content) of the ecosystem 10

properties measured, immigration history exerted an equally strong or greater effect than 11

did initial nitrogen availability (Fig. 4), indicating that history affected wood decomposition 12

at least as strongly as the nutrient environment. 13

The relationship between fungal community structure and wood decomposition 14

confirms that the two are indeed tightly linked. Fungal species composition, as measured by 15

the first PCA axis, explains 81% of the variation in decomposition (Fig. S4D-F). Similarly, 16

fungal species richness explains 70% of the variation in decomposition rate across the 17

nutrient levels, showing that high fungal diversity is associated with slow decomposition 18

(Fig. 5). The same significant pattern as in Fig. 5 also holds for respiration rate (i.e., if the 19

y-axis in Fig. 5 is respiration rate shown in Fig. 4A-C instead of decomposition rate). 20

21

Discussion 22


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

15

Taken together, our results show that community assembly history determines the 1

outcome of species interactions (Fig. 3), which in turn influences not just community 2

structure (Figs. 2 and S4A-C), but also ecosystem functioning (Fig. 4), across a broad range 3

of nitrogen conditions. The negative diversity-functioning relationship (Fig. 5) is likely to 4

be a result of inter-specific interactions (Boddy et al. 1989; Boddy 2000). One possibility is 5

that in more diverse communities, fungi invested more in antagonistic interactions, such as 6

production of secondary metabolites (Holmer & Stenlid 1997; Heilmann-Clausen & Boddy 7

2005), than in growth and decomposition. Information on the stage of wood decay at which 8

the species occur in natural forests would facilitate interpretation of our results, but this 9

information is currently not available for our species, except for sporocarps (Allen et al. 10

2000), the occurrence of which is not always correlated with fungal biomass within wood. 11

Regardless of the exact mechanism, however, what is intriguing is that the functionally 12

important gradient of fungal species diversity (Fig. 5) and composition (Fig. S4D-F) 13

emerged from simple manipulation of early immigration history, even with the same set of 14

species introduced to all replicate communities. In this respect, our study contrasts with 15

recent studies in which the set of species introduced was not standardized between 16

treatments (e.g., Stirckland et al. 2009). 17

Decreased decomposition and respiration rates in response to nitrogen addition (Fig. 18

4A-C and 4J-L) are consistent with a recent meta-analysis showing that nitrogen additions 19

generally inhibit decomposition of high-lignin material (Knorr et al. 2005). Several 20

hypotheses have been proposed to explain this effect (Knorr et al. 2005). Our results 21

suggest a new hypothesis by linking nitrogen availability and decomposition rate to 22

assembly history. It has been shown that elevated nitrogen reduces the spatial extent of 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

16

initial resource exploration by fungi (e.g., Dickie et al. 1998). Under elevated nitrogen, 1

late-arriving fungi may therefore have a better chance of survival because resource has 2

been captured to a lesser extent by early-arriving species. Consequently, greater nitrogen 3

should promote fungal diversity, a prediction consistent with our results (Fig. 2). As 4

communities develop, however, greater fungal diversity may cause the co-existing species 5

to invest more in antagonistic interactions than in decomposition, as discussed above, 6

ultimately resulting in slower decomposition (Fig. 5). 7

The extent to which our laboratory results apply to natural ecosystem dynamics 8

remains to be investigated. In particular, moisture and temperature have large effects on 9

decomposition rates. It has also been indicated that CO2 levels, which can be higher inside 10

larger pieces of wood, influence the behavior of fungi and the outcome of species 11

interactions. Furthermore, our experiment involved colonization by fungal mycelium from 12

an agar plug, which simulates colonization by mycelium in the field. However, colonization 13

also occurs via infection by a single spore, in which case the resultant colonizing mycelium 14

will be at least initially homokaryotic. As stated in the methods, our strains are presumed to 15

be heterokaryotic. Homokaryotic mycelium might differ in physiological properties (e.g., 16

growth form and enzyme secretion) from the heterokaryon that forms only after mating 17

between two compatible homokaryons. Such physiological differences might influence 18

interspecific interactions. The importance of immigration history relative to these factors 19

remains unknown. 20

Nevertheless, there are several reasons to expect that fungal assembly history 21

influences carbon dynamics in natural forest ecosystems. First, theory predicts that 22

historical effects become more important as the number of potential colonizers is increased, 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

17

owing to more complex species interactions (Chase 2003; Fukami 2009). Our experiment, 1

which used 10 species, may therefore underestimate the role of fungal immigration history 2

in natural forests, which are typically inhabited by many more species of wood-decaying 3

fungi (e.g., Allen et al. 2000). Second, disturbances affecting forests—such as storms, 4

earthquakes and fires—should cause fungal community structure and wood decomposition 5

to follow variable trajectories at a range of spatial scales. For example, forest carbon 6

dynamics may show idiosyncratic variation at the scale of entire forest stands if the timing 7

of large-scale disturbances varies from stand to stand, relative to the seasonal phenology of 8

fruiting, spore dispersal and mycelial spread by wood-decaying fungi. Third, global climate 9

change appears to affect fungal fruiting phenology, with considerable variation between 10

species in their phenological response (Gange et al. 2007; Kauserud et al. 2008). Thus it 11

seems likely that fungal immigration history is being altered around the world, affecting 12

carbon dynamics at both local and global scales. 13

Despite the recent progress in our understanding of carbon dynamics and other 14

ecosystem functioning (Heimann & Reichstein 2008), models that make predictions based 15

on environmental conditions do not fully explain observed ecosystem processes. It is now 16

widely recognized that biotic factors involving decomposers and other organisms limit the 17

usefulness of these models (Bardgett et al. 2008; Wall et al. 2008; Chapin et al. 2009). The 18

novel finding of our study is the possibility that the ecosystem-level effects of biotic factors 19

can be understood only by considering species immigration history. Idiosyncratic historical 20

effects present a major obstacle to predicting ecosystem carbon dynamics and other 21

ecosystem functioning. However, further progress can be made through investigation of the 22

environmental conditions (Chase 2003) and spatial scales (Chase 2003; Shurin et al. 2004; 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

18

Fukami 2009) under which assembly history matters. Moreover, knowledge of historical 1

effects can serve as a useful tool for managing carbon sequestration in restored ecosystems 2

by using specific sequences of species introductions. Given that immigration history affects 3

community structure at multiple scales (Chase 2003; Shurin et al. 2004; Fukami 2009) and 4

not only in fungi, but in bacteria, protists, plants and animals as well (Drake 1991; Chase 5

2003; Shurin et al. 2004; Fukami 2009; Kennedy et al. 2009), we propose that more 6

reliable prediction and management of carbon dynamics, in particular, and ecosystem 7

functioning, in general, require greater attention paid to historical influences of community 8

assembly. 9

10

Acknowledgments 11

We thank Ross Beever, Jacqueline Beggs, Peter Bellingham, Peter Clinton, Wanda 12

Daley, Brian Daly, Richard FitzJohn, Tom Herbert, Karyn Hoksbergen, John Hunt, Peter 13

Johnston, Hilary Kitchen, Chris Morse, Aidan O’Donnell, Duane Peltzer, Susan Wiser and 14

Zeng Zhou for support and assistance, and Melinda Belisle, Lynne Boddy, Matt Knope, 15

Ben Sikes, Jan Stenlid, Peter Vitousek, Lawrence Walker, David Wardle and David 16

Whitehead for comments. This work was supported by the Marsden Fund Council from 17

New Zealand Government funding administered by the Royal Society of New Zealand. 18

19

References 20

Allen, R. B., Buchanan, P. K., Clinton, P. W. & Cone, A. J. (2000). Composition and 21

diversity of fungi on decaying logs in a New Zealand temperate beech (Nothofagus) 22

forest. Can. J. For. Res. 30: 1025-1033. 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

19

Bardgett, R. D., Freeman, C. & Ostle , N. J. (2008). Microbial contributions to climate 1

change through carbon-cycle feedbacks. ISME Journal 2: 805-814. 2

Boddy, L., Owens, E. M. & Chapella, L. H. (1989). Small-scale variation in decay-rate 3

within logs one year after felling – effect of fungal community structure and moisture-4

content. FEMS Microbiol. Lett. 62: 173-184. 5

Boddy, L. (2000). Interspecific combative interactions between wood-decaying 6

basidiomycetes. FEMS Microbiol. Ecol. 31: 185-194. 7

Cadotte, M. W., Drake, J. A. & Fukami, T. (2005). Constructing nature: laboratory models 8

as necessary tools for investigating complex ecological communities. Adv. Ecol. Res. 9

37: 333-353. 10

Chapin, F. S., III, McFarland, J., McGuire, A. D., Euskirchen, E. S., Ruess, R. W. & 11

Kielland, K. (2009).The changing global carbon cycle: linking plant–soil carbon 12

dynamics to global consequences. J. Ecol. 97: 840-850. 13

Chase, J. M. (2003). Community assembly: when should history matter? Oecologia 136: 14

489-498. 15

Clinton, P.W., Newman, R.H., & Allen, R.B. (1995). Immobilization of 15N in forest litter 16

studied by 15N CPMAS NMR spectroscopy. Eur. J. Soil Sci. 46: 551-556. 17

Clinton, P. W., Allen, R. B. & Davis, M. R. (2002). Nitrogen storage and availability 18

during stand development in a New Zealand Nothofagus forest. Can. J. For. Res. 32: 19

344-352. 20

Coates, D. & Rayner, A. D. M. (1985). Fungal population and community development in 21

cut beech logs. III. Spatial dynamics, interactions and strategies. New Phytol. 101: 22

183-198. 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

20

Deacon, L. J., Pryce-Miller, E. J., Frankland, J. C., Bainbridge, B. W., Moore, P. D. & 1

Robinson, C. H. (2006). Diversity and function of decomposer fungi from a grassland 2

soil. Soil Biol. & Biochem. 38: 7-20. 3

De Deyn, G. B., Cornelissen, J. H. & Bardgett, R. D. (2008). Plant functional traits and soil 4

carbon sequestration in contrasting biomes. Ecol. Lett. 11: 516-531. 5

Delaney, M., Brown, S. , Lugo, A. E., Torres-Lezama, A. & Quintero, N. B. (1998). The 6

quantity and turnover of dead wood in permanent forest plots in six life zones of 7

Venezuela. Biotropica 30: 2-11. 8

Dickie, I. A., Koide, R. T. & Stevens, C. M. (1998). Tissue density and growth response of 9

ectomycorrhizal fungi to nitrogen source and concentration. Mycorrhiza 8:145-148. 10

Dickie, I. A., Richardson, S. J. & Wiser, S. K. (2009). Ectomycorrhizal fungal communities 11

in two temperate Nothofagus rainforests respond to changes in soil chemistry after 12

small-scale timber harvesting. Can. J. For. Res. 39: 1069-1079. 13

Drake, J. A. (1990). Community-assembly mechanics and the structure of an experimental 14

species ensemble. Am. Nat. 137: 1-26. 15

Emmerson, M. C., Solan, M., Emes, C., Paterson, D. P. & Raffaelli, D. G. (2001). 16

Consistent patterns and the idiosyncratic effects of biodiversity in marine ecosystems. 17

Nature 411: 73-77. 18

FitzJohn, R. G. & Dickie, I. A. (2007). TRAMPR: An R package for analysis and matching 19

of terminal-restriction fragment length polymorphism (TRFLP) profiles. Mol. Ecol. 20

Notes 7: 583-587. 21

Fukami, T. (2004). Assembly history interacts with ecosystem size to influence species 22

diversity. Ecology 85: 3234-3242. 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

21

Fukami, T. (2009). Community assembly dynamics in space. In: Community Ecology: 1

Processes, Models, and Applications (eds Verhoef, H. A. & Morin, P. J.). Oxford 2

University Press, Oxford, pp 45-54. 3

Fukami, T., Bezemer, T. M., Mortimer, S. R. & Van der Putten, W. H. (2005). Species 4

divergence and trait convergence in experimental plant community assembly. Ecol. 5

Lett. 8: 1283-1290. 6

Gange, A. C., Gange, E. G., Sparks, T. H. & Boddy, L. (2007). Rapid and recent changes in 7

fungal fruiting patterns. Science 316: 71. 8

Hanson, C. A., Allison, S. D., Bradford, M. A., Wallenstein, M. D. & Treseder, K. K. 9

(2008). Fungal taxa target different carbon sources in forest soil. Ecosystems 11: 1157-10

1167. 11

Harmon, M. E., Ferrell, W. K. & Franklin, J. F. (1990). Effects on carbon storage of 12

conversion of old-growth forests to young forests. Science 247: 699-702. 13

Harmon, M. E., Sexton, J., Caldwell, B. A. & Carpenter, S. E. (1994). Fungal sporocarp 14

mediated losses of Ca, Fe, K, Mg, Mn, N, P, and Zn from conifer logs in the early 15

stages of decomposition. Can. J. For. Res. 24: 1883-1893. 16

Heilmann-Clausen, J. & Boddy, L. (2005). Inhibition and stimulation effects in 17

communities of wood decay fungi: exudates from colonized wood influence growth by 18

other species. Microbial Ecol. 49: 399-406. 19

Heimann, M. & Reichstein, M. (2008). Terrestrial ecosystem carbon dynamics and climate 20

feedbacks. Nature 451: 289-292. 21

Holmer, L. & Stenlid, J. (1997). Competitive hierarchies of wood decomposing 22

basidiomycetes in artificial systems based on variable inoculum sizes. Oikos 79: 77-84. 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

22

Hooper, D. U., Chapin, F. S. III, Ewel, J. J., Hector, A., Inchausti, P., Lavorel, S., Lawton, 1

J. H., Lodge, D., Loreau, M., Naeem, S., Schmid, B., Setälä, H., Symstad, A. J., 2

Vandermeer, J. & Wardle, D. A. (2005). Effects of biodiversity on ecosystem 3

functioning: a consensus of current knowledge and needs for future research. Ecol. 4

Monogr. 75: 3-35. 5

Jiang, L. & Patel, S. N. (2008). Community assembly in the presence of disturbance: a 6

microcosm experiment. Ecology 89: 1931-1940. 7

Jonsson, M. T., Edman, M. & Jonsson, B. G. (2008). Colonization and extinction patterns 8

of wood-decaying fungi in a boreal old-growth Picea abies forest. J. Ecol. 96: 1065-9

1075. 10

Kauserud, H., Stige, L. C., Vik, J. O., Okland, R. H., Hoiland, K. & Stenseth, N. C. (2008). 11

Mushroom fruiting and climate change. Proc. Nat. Acad. Sci., USA 105: 3811-3814. 12

Kennedy, P. G., Peay, K. G. & Bruns, T. D. (2009). Root tip competition among 13

ectomycorrhizal fungi: are priority effects a rule or an exception? Ecology 90: 2098 -14

2107. 15

Körner, C., Stöcklin, J., Reuther-Thiébaud, L. & Peláez-Riedl, S. (2008). Small differences 16

in arrival time influence composition and productivity of plant communities. New 17

Phytol. 177: 698-705. 18

Knorr, M., Frey, S. D. & Curtis, P. S. (2005). Nitrogen additions and litter decomposition: 19

a meta-analysis. Ecology 86: 3252–3253 20

Lawton, J. H. (1999). Are there general laws in ecology? Oikos 84: 177-192. 21

Loreau, M., Naeem, S., Inchausti, P., Bengtsson, J., Grime, J. P., Hector, A., Hooper, D. U., 22

Huston, M. A., Raffaelli, D., Schmid, B., Tilman, D. & Wardle, D. A. (2001). 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

23

Biodiversity and ecosystem functioning: current knowledge and future challenges. 1

Science 294: 804-809. 2

Louette G. & De Meester L. (2007). Predation and priority effects in experimental 3

zooplankton communities. Oikos 116: 419–426. 4

MacArthur, R. H. (1972). Geographical Ecology. Harper and Row, New York. 5

Morin, P. J. (1984). Odonate guild composition: experiments with colonization history and 6

fish predation. Ecology 65: 1866–1873. 7

Ostfeld, R. S. & LoGiudice, K. (2003). Community disassembly, biodiversity loss, and the 8

erosion of an ecosystem service. Ecology 84: 1421–1427. 9

Shurin, J. B., Amarasekare, P., Chase, J. M., Holt, R. D., Hoopes, M. F. & Leibold, M. A. 10

(2004). Alternative stable states and regional community structure. J. Theor. Biol. 227: 11

359-368. 12

Steiner, C. F. & Leibold, M. A. (2004). Cyclic assembly trajectories and scale-dependent 13

productivity-diversity relationships. Ecology 85: 107-113. 14

Strickland, M. S., Lauber, C., Fierer, N. & Bradford, M. A. (2009). Testing the functional 15

significance of microbial community composition. Ecology 90: 441-451. 16

Wall, D.H., Bradford, M.A., St. John, M. G., Trofymow, J. A., Behan-Pelletier, V. M., 17

Bignell, D. E., et al. (2008). Global decomposition experiment shows soil animal 18

impacts on decomposition are climate-dependent. Global Change Biol. 14: 2661-2677. 19

Wardle, D. A. (2002). Communities and Ecosystems: Linking the Aboveground and 20

Belowground Components. Princeton University Press, Princeton. 21


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

24

Weedon, J. T., Cornwell, W. K., Cornelissen, J. H. C., Zanne, A. E., Wirth, C. & Coomes, 1

D. A. (2009). Global meta-analysis of wood decomposition rates: a role for trait 2

variation among tree species? Ecol. Lett. 12: 45-56. 3

Worrall, J. J., Anagnost, S. E. & Zabel, R. A. (1997). Comparison of wood decay among 4

diverse lignicolous fungi. Mycologia 89: 199-219. 5

Zhang, Q.-G. & Zhang, D.-Y. (2007). Colonization sequence influences selection and 6

complementarity effects on biomass production in experimental algal microcosms. 7

Oikos 116: 1748-1758. 8

Zimmerman, J. K., Pulliam, W. M., Lodge, D. J., Quinones-Orfila, V., Fetcher, N., 9

Guzmán-Grajales, S., Parrotta, J. A., Asbury, C. E., Walker, L. R. & Waide, R. B. 10

(1995). Nitrogen immobilization by decomposing woody debris and the recovery of 11

tropical wet forest from hurricane damage. Oikos 72: 314-322. 12

13

Supporting Information 14

The following Supporting Information is available for this article: 15

Table S1. Species used. 16

Figure S1. Sawdust sampling locations. 17

Figure S2. Spatial species distribution 4 months after all species were introduced. 18

Figure S3. Spatial species distribution 12 months after all species were introduced. 19

Figure S4. Effect of fungal immigration history on fungal community structure, and 20

relationship between fungal community structure and wood decomposition rate. 21

Figure S5. Rates of carbon release from experimental microcosms over time. 22


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

25

Figure Legends 1

Figure 1. Representative example of the experimental setting, viewed from above the jar, 2

showing the 8 cm diameter disk, the agar plugs placed on the disk for species inoculation, 3

and the mineral soil on which the disk was placed. In each jar, 10 plugs were used to 4

introduce 10 species. This photograph was taken 6 weeks (upper panel) and 18 weeks 5

(lower panel) after the initial species (in this case, Bisporella citrina, indicated by arrow) 6

was introduced, and 2 weeks and 14 weeks (respectively) after the 9 other species were 7

introduced. 8

Figure 2. Effect of fungal immigration history on fungal species richness. Species richness 9

(mean ±1 standard error of mean) was measured 12 months after all species were 10

introduced. P values from ANOVAs are provided for effect of immigration history (H), 11

effect of initial nutrient level (N), and their interactive effect (H*N). Asterisks indicate P < 12

0.05 (*), < 0.01 (**) and < 0.001 (***). 13

Figure 3. Effect of fungal immigration history on wood volume occupied (mean ± 1 14

standard error of mean) by Phlebia nothofagi, Trametes versicolor and Bisporella citrina 15

12 months after all 10 fungal species were introduced. Wood volume occupied is the 16

percentage of the sawdust samples in which the species was detected out of the 9 sawdust 17

samples from each wood disk (more than one species may occupy the same sawdust sample 18

concurrently). P values are as in Fig. 2. 19

Figure 4. Effect of fungal immigration history on wood decomposition and carbon 20

dynamics. Respiration rate (A-C) was measured 11 months after introduction of all fungal 21

species (see also Fig. S5). Other measures (D-L) were taken 12 months after all species 22

were introduced. P values are as in Fig. 2. 23


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

26

Figure 5. Relationship between fungal species richness and wood mass loss 12 months 1

after all fungal species were introduced. Data presented are means for history treatments. 2

Letters indicate the first two letters of the species used as initial species. White, gray and 3

black circles indicate low, medium and high initial nutrient levels, respectively. Linear 4

regression line is shown (R2 = 0.70, P < 0.001). 5


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

27

Fig. 1


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

28

Fig. 2


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

29

Fig. 3

A

D E

B C

G H I

F

A

D E

B C

G H I

F


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

30

Fig. 4


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

For Review O

nly

31

Fig. 5

0

10

20

30

40

50

0 1 2 3 4 5 6Fungal species richness

Wood m

ass loss (

%)

Ph

PhPh

Pl

Pl

Pl

Ca

Ca

Ca

TrTr

Tr

As

As

As

Da

Da

Da

Bi

Bi

Bi


123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

Table S1. Species used. ____________________

Species name* ICMP† PDD‡ GenBank§

Armillaria sp.¶ 16996 91742 GQ411506

Artomyces candelabrum (Massee) Jülich 16999 91743 GQ411509

Ascocoryne sarcoides (Jacq.) J. W. Groves & D. E. Wilson 17040 91613 GQ411510

Bisporella citrina (Hedw.) Korf & S. E. Carp 16997 91609 GQ411507

Calocera cf sinensis 16998 91741 GQ411508

Daldinia novae-zelandiae 17078 91744 GQ411513

Phlebia nothofagi (G. Cunn.) Nakasone 17043 91610 GQ411511

Pleurotus purpureoolivaceus (G. Stev.) Segedin, P. K. Buchanan & J. P. Wilkie 17077 91612 GQ411512

Sistotrema cf brinkmannii 17079 91614 GQ411514

Trametes versicolor (L.) Lloyd 17460 91611 GQ411515

*Author names are provided where applicable.

†International Collection of Micro-organisms from Plants (ICMP) voucher number

‡New Zealand Fungal Herbarium (Plant Diseases Division [PDD] herbarium) specimen number

§GenBank accession number

¶Unnamed fourth species from New Zealand, cited in: Pildain, M. B., Coetzee, M. P. A., Rajchenberg, M., Petersen, R. H., Wingfield, M.

J., & Wingfield, B. D. (2009). Molecular phylogeny of Armillaria from the Patagonian Andes. Mycological Progress 8, 181-194.

At Am

Bl

Ca

Da

AsTr

Si

Pl

Ph

Fig. S1. Sawdust sampling locations. Large circle indicates the wood disk. Small circles

indicate the 9 sampling locations. Dotted lines indicate where the wood disk was cut for

sawdust sampling. After the disk was cut, sawdust was removed by drilling into the freshly

exposed side of each segment at the locations indicated by small circles. Letters indicate

inoculation points of species (see Fig. 1), marked by the first two letters of the genus names

(see Table 1), except for Artomycetes (indicated as At) and Armillaria (indicated as Am). See

also Figs. S2 and S3.

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

s ut or uel P

Pleu

rotu

s

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

ai bel h P

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

all er opsi B

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

ai ni dl a D

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

s et e mar T

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

ar ec ol a C

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

enyr oc ocs A

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Phle

bia

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Bisp

orel

la

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Dal

dini

a

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Tram

etes

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Calo

cera

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Asc

ocor

yne

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Sist

otre

ma

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Art

omyc

es

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Arm

illar

ia

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

s ei c epS l aiti nI

Spec

ies

Freq

uenc

y

Fig.

S2.

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

s ut or uel P

Pleu

rotu

s

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

ai bel h P

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

all er opsi B

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

ai ni dl a D

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

s et e mar T

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

ar ec ol a C

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

enyr oc ocs A

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Phle

bia

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Bisp

orel

la

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Dal

dini

a

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Tram

etes

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Calo

cera

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Asc

ocor

yne

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Sist

otre

ma

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Art

omyc

es

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Arm

illar

ia

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

Pl

Ph

At

Am

Bi

Ca

Da

As

Tr

Si

s ei c epS l aiti nI

Spec

ies

Freq

uenc

y

Fig.

S3.

Spa

tial d

istri

butio

n of

spe

cies

on

woo

d di

sks

12 m

onth

s af

ter a

ll 10

spe

cies

wer

e in

trodu

ced.

Sym

bols

are

as

in F

ig. S

2.

−10

−5

0

5

low

PC

A a

xis

2A

medium

B

high

C

−8 −6 −4 −2 0 2 4 6

0

10

20

30

40

50

Woo

d m

ass

loss

(%)

D

−8 −6 −4 −2 0 2 4 6

E

−8 −6 −4 −2 0 2 4 6

F

PCA axis 1

Initial nutrient level

History treatmentPhlebiaPleurotusAscocoryneCaloceraDaldiniaBisporellaTrametes

Fig. S4. Effect of fungal immigration history on fungal community structure (A-C), and relationship between fungal community structure and wood decomposition rate (D-F). Data points represent replicate communities. History treat-ments indicate the species used as the initial species. Results in a-c are from a single common PCA performed on the percentage of the wood volume occupied by each species 12 months after all fungal species were introduced. The first and second principal components (PCA axes 1 and 2) explain 56% and 24% of total variation, respectively. Results in D-F show the relationship between PCA axis 1 (index of fungal community structure) and wood mass remaining (index of wood decomposition rate), both measured 12 months after all species were introduced.

lowshtno

m 0

0.00

0.05

0.10

0.15

0.20

medium high

H = <0.001*** N = <0.001*** H*N = <0.001***

shtnom 2

0.00

0.05

0.10

0.15

0.20

H = 0.715 N = 0.593 H*N = 0.675

shtnom 4

0.00

0.05

0.10

0.15

0.20

H = <0.001*** N = <0.001*** H*N = 0.214

shtnom 6

0.00

0.05

0.10

0.15

0.20

H = 0.13 N = 0.009** H*N = 0.961

shtnom 9

0.00

0.05

0.10

0.15

0.20

H = 0.216 N = 0.102 H*N = 0.611

suto rue lP

aibelhP

al leropsiB

ain id laD

setemarT

arecolaC

enyrococsA

shtnom 11

0.00

0.05

0.10

0.15

0.20

sutorue lP

aibelhP

a l le rops iB

a inidlaD

setemarT

a recolaC

enyrococsA

sutoruelP

aibelhP

a l le rops iB

a inid laD

setemar T

a reco laC

enyrococsA

H = 0.032* N = 0.023* H*N = 0.684

Res

pira

tion

rate

µµg

C s−−1

Initial species

Initial nutrient level

Fig. S5. Rates of carbon release from experimental microcosms over time. Months indicate the number of months after all 10 species were introduced. Symbols are as in Fig. 2.

for review onlynature.berkeley.edu/brunslab/mycorrhizal/papers/fukami...for review only 1 assembly...

Documents