Advertisement

Mycorrhiza

, Volume 29, Issue 3, pp 181–193 | Cite as

Ectomycorrhizal fungal communities are dominated by mammalian dispersed truffle-like taxa in north-east Australian woodlands

  • S. J. NuskeEmail author
  • S. Anslan
  • L. Tedersoo
  • B. C. Congdon
  • S. E. Abell
Open Access
Original Article

Abstract

Mycorrhizal fungi are very diverse, including those that produce truffle-like fruiting bodies. Truffle-like fungi are hypogeous and sequestrate (produced below-ground, with an enclosed hymenophore) and rely on animal consumption, mainly by mammals, for spore dispersal. This dependence links mycophagous mammals to mycorrhizal diversity and, assuming truffle-like fungi are important components of mycorrhizal communities, to plant nutrient cycling and ecosystem health. These links are largely untested as currently little is known about mycorrhizal fungal community structure and its dependence on mycophagous mammals. We quantified the mycorrhizal fungal community in the north-east Australian woodland, including the portion interacting with ten species of mycophagous mammals. The study area is core habitat of an endangered fungal specialist marsupial, Bettongia tropica, and as such provides baseline data on mycorrhizal fungi-mammal interactions in an area with no known mammal declines. We examined the mycorrhizal fungi in root and soil samples via high-throughput sequencing and compared the observed taxa to those dispersed by mycophagous mammals at the same locations. We found that the dominant root-associating ectomycorrhizal fungal taxa (> 90% sequence abundance) included the truffle-like taxa Mesophellia, Hysterangium and Chondrogaster. These same taxa were also present in mycophagous mammalian diets, with Mesophellia often dominating. Altogether, 88% of truffle-like taxa from root samples were shared with the fungal specialist diet and 52% with diets from generalist mammals. Our data suggest that changes in mammal communities, particularly the loss of fungal specialists, could, over time, induce reductions to truffle-like fungal diversity, causing ectomycorrhizal fungal communities to shift with unknown impacts on plant and ecosystem health.

Keywords

Sequestrate fungi Truffle-like fungi Mycophagy Ecosystem interactions Bettongia tropica Ectomycorrhizal fungi 

Introduction

Hypogeous, sequestrate (truffle-like) mycorrhizal fungi are an important component of forest ecosystems and they rely on animals, particularly mammals, for their spore dispersal (Claridge and May 1994). This implies that truffle-like fungal diversity is likely linked to mammal diversity (Vernes 2007). Disruption to complex ecological networks, such as this mammal-fungi-plant interaction, can cause loss of biodiversity. For example, it is logical to assume that reduced spore dispersal via loss of mammal abundance and diversity would reduce gene flow among truffle-like populations, resulting in undocumented impacts on truffle-like fungal community structure and potential species extinctions. Loss of truffle-like species diversity may in turn alter mycorrhizal communities, potentially impacting fungi-plant interactions.

Mammals are also thought to play a pivotal role in plant-mycorrhiza symbioses, and by extension, plant productivity, diversity and ecosystem health (Maser et al. 1978; Malajczuk et al. 1987; Johnson 1996; Vernes 2007). Such a hypothesis assumes that truffle-like taxa are important components of functioning mycorrhizal communities and that the higher the proportion of truffle-like taxa within the overall mycorrhizal community, either in terms of relative abundance or diversity, the higher the potential influence that mammalian spore dispersal has on the structuring of mycorrhizal and plant communities. Yet, these assumed linkages remain largely untested.

To understand the strength of the relationship between mycorrhizal communities and mycophagous mammals, first we must understand how important truffle-like taxa are to functioning mycorrhizal communities. Few studies have identified the fruiting habits of the various components of the Australian mycorrhizal fungal community (or presented data with enough resolution that this can be inferred post hoc; Online Resource 1, Table S1). In three different studies of ectomycorrhizal (ECM) fungal sporocarps in Australia (Reddell et al. 1999; Lu et al. 1999; Adams et al. 2006), between 18 and 27% of taxa found were truffle-like (reported as hypogeous). However, these three surveys are difficult to compare in terms of the richness of hypogeous versus epigeous species because the same methodology was not used for both groups.

It is also important to make the distinction between ECM and arbuscular mycorrhizal (AM) communities as the relative diversity of truffle-like species are quite different in these groups as are their distribution, ecology and interactions with host plants. AM fungi associate with > 80% of global plant diversity and occur in almost every ecosystem where plants are present, while ECM associate with a much smaller proportion (Brundrett 2009). However, ECM trees can dominate forests in terms of biomass (Reddell et al. 1999). The diversity of truffle-like (sporocarpic) AM fungi is much lower compared to ECM fungi; at least two AM genera contain truffle-like species (Glomus and Acaulospora; Goto and Maia 2005) while thousands of species of ECM truffle-like fungi are within Basidiomycota, Ascomycota and Zygomycota (Bougher and Lebel 2001; Trappe et al. 2009). Therefore, any influence that mammals may have on mycorrhizal communities will likely depend on the differences between these groups.

To our knowledge, only one study has quantified the ECM community on natural forest plant host roots and compared this to mycophagous mammalian diets. Izzo et al. (2005) sampled roots from subtropical North America and found at least 21% of taxa were truffle-like and between 25 and 40% of ECM dry root biomass were truffle-like taxa (reported as hypogeous). However, this study was limited to Sanger sequencing of DNA samples from mammalian scats and consequently detected only three truffle-like taxa in mammalian diets. Modern high-throughput sequencing technologies that amplify and sequence DNA from complex communities provide the necessary resolution to examine fungal communities from environmental samples like roots, scats and soil (Lindahl et al. 2013).

Our aim was to address the knowledge gap in the structure and relative proportion of mycorrhizal communities, particularly the truffle-like communities that are interacting with mycophagous mammals. Using high-throughput sequencing (Illumina MiSeq), we compared the mycorrhizal fungal communities (concentrating on ECM fungi) across three sample types including plant roots, soil and scats from mycophagous mammals. We compared our results to reference ITS2 sequences of truffle-like morpho-species collected and characterised from an extensive survey undertaken at one of our sampling sites (Abell-Davis 2008). We collected roots, soil and mammalian scat samples within the habitat of a fungal specialist (the northern bettong; Bettongia tropica) and other mycophagous mammals as this provides a baseline measurement of the interaction between root-associating mycorrhizal fungi and mycophagous mammals where limited known loss of mammal diversity has occurred.

Methods

Field sampling

Sampling was carried out on the Lamb Range in North Queensland in Australia at Davies Creek National Park (17°1′23.28″S, 145°34′55.71″E; elevation 600–730 m) in the late dry season (November to December) in 2014. Additional sampling was carried out at two locations in the early wet season (February to March): Danbulla National Park near Tinaroo Dam (17°9′50.30″S, 145°32′11.56″E; elevation 630–780 m) and Davies Creek in 2015. Six plots (12 × 20 m) at each site were established at least 500 m apart around the animal trapping grid (as used in Nuske et al. 2018) for the collection of soil and root samples. The dominant and putatively ectomycorrhizal tree species were Eucalyptus crebra, E. tindaliae, E. mediocris, Corymbia intermedia, Allocasuarina littoralis, Al. torulosa and Acacia flavescens.

Soil was collected from 40 cores (0–10 cm deep, 5 cm diameter) per plot. The corers were carefully cleaned with 70% ethanol between plots. Half of the plot (6 × 20 m) was also used to collect putative ECM root-associated taxa by raking the top 10 cm of soil for 60 person-minutes and collecting fine roots. Because the soil was often too compacted and contained large rocks, we were not able to trace fine roots back to the potential host plants. Instead, we collected all fine root material found. When possible, grass roots were eliminated from individual samples by tracing back to the grass plant. Preliminary work also suggested that a higher volume of roots was collected with this more targeted approach compared to sieving roots from soil cores. A high volume of root tip material was necessary to obtain three DNA extraction subsamples per plot (3 × 0. 25 g of wet weight root tips, see below). Soil and roots were frozen (− 4 °C) within 24 h of collection and placed into − 20 °C as soon as possible (up to 4 days).

Fungal diets of mammals were examined by collecting scat samples from trapped individuals. Trapping and animal handling protocols were as outlined in Nuske et al. (2018). Briefly, medium-sized and small mammals trapped for four consecutive nights each, at two locations and two seasons. We identified mammals according to Van Dyck et al. (2013). We marked each individual by either removing a small patch of hair with scissors at the base of the tail or microchipping (B. tropica only; Minichips, Micro Products Australia, Canning Vale, WA or ISO FDX-B Microchips, OzMicrochips, Peakhurst, NSW). Scats were collected from the bottom of Elliot traps or from plastic placed under each cage trap. All traps and plastic were initially cleaned with 70% ethanol and then re-cleaned if an animal was caught. Scats were stored on ice or in a portable fridge (4 °C) in the field and transferred to − 20 °C as soon as possible (within 4 days). Each animal was handled according to James Cook University animal ethical guidelines (Approved ethics application A2044).

Laboratory

Roots were cleaned of excess soil in reverse osmosis water. Fine roots were examined under a dissecting microscope. For each cluster of fine roots collected within a plot, the same volume of root tips of each mycorrhizal morphotype were placed into three subsamples (0. 25 g) for DNA extraction. We did not attempt to verify the colonisation of each ectomycorrhizal morphotype to maintain efficient processing. Therefore, we consider the mycorrhizal community from root samples to be ‘root-associated’. These taxa are more likely to represent functioning mycorrhizal fungi (i.e. those taxa colonised and interacting with plants) compared to that sequenced from soil samples. For soil samples, each of the 40 soil cores per plot were homogenised and pooled. Then three subsamples of fine powdered soil were taken per plot for DNA extraction (0.25 g). We only used scats from the first capture of an individual per trapping session. Each boluse of scat was broken in half and a small sample of faecal material removed from the inside with sterile forceps. Samples were homogenised and 0.25 g was taken for DNA extraction.

DNA extraction, PCR, sequencing protocols and bioinformatics were processed as in Nuske et al. (2018). Briefly, DNA was extracted using PowerLyser PowerSoil DNA Isolation kit (Mo Bio, Carlsbad, CA USA) following manufacturer’s instructions, except that the samples were lysed using a Qiagen Tissue Lyser for 2 × 30 s at 30 Hz, swapping the position of the samples between runs. DNA was amplified with ITS3-Mix1-5 (5′CTAGACTCGTCANCGATGAAGAACGYRG-3′) and barcoded ITS4ngs (5′-TCCTSCGCTTATTGATATGC-3′) primers (Tedersoo et al. 2014). The primers were tagged with 10–11 base unique molecular identifiers (MIDs) to later distinguish samples with sequencing runs (Online Resource 1, Table S1). We used negative (for DNA extraction and PCR) and positive controls (PCR) throughout the experiment. Normalised amplicons were subjected to ligation of Illumina adaptors using the TruSeq DNA PCR-free HT Sample Prep kit (Illumina Inc., San Diego, CA, USA). All samples were sequenced using Illumina MiSeq 2 × 300 paired-end technology. Raw Illumina data is deposited in Sequence Read Archive (SRA; bioproject SRP150847). Bioinformatics were performed using PipeCraft (v1.0; Anslan et al. 2017) as per Nuske et al. (2018). Representative sequences for each operational taxonomic unit (OTU, clustered with CD-HIT at 97% similarity threshold, v4.6; Li and Godzik 2006) were chosen using the mothur ‘abundance’ method and compared against UNITE (v7.0), GenBank ITS and our local truffle-like fungal database (Nuske et al. 2018) to obtain taxonomic affiliation using BLASTn (Camacho et al. 2009). Taxonomic groups were assigned to functional categories using FUNGuild (v1.0; Nguyen et al. 2015a). All Glomeromycota taxa were assigned as arbuscular mycorrhizal.

Statistics

OTU subsetting and statistics were performed using the ‘phyloseq’ package (McMurdie and Holmes 2013) in R (R Core Team 2012). Altogether, six samples were removed from further analyses, because these comprised < 500 filtered sequences. The fungal dataset was examined at three broad levels: at the whole OTU community level, only examining the mycorrhizal OTUs (8.4% of all taxa) and only examining truffle-like taxa (9.3% of mycorrhizal taxa). The mycorrhizal subset of the data included only taxa that were assigned as ‘highly probable’ and ‘probable’ from the FUNGuild output (Nguyen et al. 2015b). Functional guilds are assigned to ECM status by FUNGuild based on genera, with the exception of Russulaceae. Russulaceae is also one of the most OTU-rich families in this dataset; therefore, when comparing mycorrhizal taxa (e.g. as relative richness of mycorrhizal families), Russulaceae are disproportionally over-represented. To make sure ECM taxa were evenly represented at the genus level, ECM OTUs assigned to family level, Russulaceae, were excluded from analyses (note: ECM OTUs assigned to genus and species level within Russulaceae, for example Russula, were retained). Identified truffle-like taxa are listed in Online Resource 2.

The three subsamples per soil or root sample were pooled computationally by mean sequence abundance per OTU as this likely gives the best estimate of richness (Song et al. 2015). To estimate the accumulation of OTUs per sample, we created rarefaction OTU accumulation curves for each sample type with mycorrhizal and truffle OTU data using the “ggrare” function (richness.R, phyloseq extensions; https:// github.com/mahendra-mariadassou/phyloseq-extended with added ggplot2 graphics).

We compared mycorrhizal communities between sample types by tabulating the number of OTUs that were shared and unshared (using ‘limma’ and ‘venneuler’ packages in R). We ranked OTUs according to their relative abundance per sample (based on sequence count) and considered the ‘dominant’ portion of the community to be the highest relative abundance that collectively accounted for > 90% of the relative abundance. The dominant portion accounted for approximately 25% of the taxa present.

Results

Richness

Soil samples were more OTU-rich than root samples, and both were more OTU-rich than scat samples (6689, 3226 and 2932 OTUs, respectively). There were a total of 9358 filtered OTUs across all samples. Most were not assigned to a functional guild (7508 OTUs) by FUNGuild. Of those that were, most were symbiotrophic (805 OTUs, including 344 ECM OTUs and 428 AM OTUs) followed by saprotrophic (754 OTUs). For mycorrhizal OTUs, at equivalent read count, the OTU richness of scats was ~ 60% of the root-associating taxa (Fig. 1a). We detected a higher truffle-like OTU richness in scat samples than in root or soil samples (Fig. 1b).
Fig. 1

Rarefied accumulation curve ± 95% confidence intervals for a mycorrhizal OTUs and b truffle (truffle-like/sequestrate) OTUs. Orange lines are soil samples (n = 18, each containing three pooled samples), light blue lines are root samples (n = 18, each containing three pooled samples) and dark blue lines are scat samples (n = 61)

Both soil and root samples had AM fungi (Glomeromycota, Glomeraceae and Gigasporaceae) as the most OTU-rich mycorrhizal taxa. However, they made up < 13% of the taxa richness in the mammalian scat samples (Fig. 2, including Diversisporaceae) and constituted < 0.01% of the relative abundance for all samples (Fig. 3). The truffle-like family Mesophelliaceae was the most OTU-rich and highest relative abundance mycorrhizal taxon in mammalian scat samples (Figs. 2 and 3).
Fig. 2

Relative OTU richness of mycorrhizal families in different samples (soil, roots and scats). Only taxa representing greater than 1% of the total OTU richness are shown for clarity

Fig. 3

Relative abundance of mycorrhizal families in different samples (soil, roots and scats) split by mycorrhizal type (AM = arbuscular mycorrhizal) and fruiting habit (n = fruiting habit other than truffle-like taxa, n/y = unknown fruiting habit, y = truffle-like/sequestrate taxa). Black bars are overlapping boundary lines representing OTUs with a relative abundance too small to display

Overall, samples had 21.2% of ECM OTUs as truffle-like taxa (73 OTUs) and 54.1% as taxa with ambiguous fruiting habit (186 OTUs). Scat samples had a higher proportion of OTUs matching truffle-like fungi than root or soil samples (30–90%, depending on site and season, compared to 17–23% for root samples and 7–8% for soil samples). Scat samples from the fungal specialist (B. tropica) had a higher proportion of ECM truffle-like OTUs (30–90%) than all other mammal species with generalist diets combined (18–73%).

Relative abundance

Truffle-like and secotioid taxa (e.g. Cortinariaceae and Hysterangiaceae) constituted higher proportions of the dominant mycorrhizal root-associating communities compared to soil communities (Table 1; Fig. 3). Soil mycorrhizal communities were dominated by taxa with mixed fruiting habits (e.g. truffle-like taxa and mushroom taxa and Russula and Cortinarius that could represent truffle-like, secotioid or mushroom taxa; Table 1 and Fig. 3). These patterns of relative abundance were consistent across the two sites and two seasons we measured (Table 1). Of the dominant mycorrhizal OTUs associating with root samples, three out of four genera were truffle-like from Hysterangiales (Hysterangium, Mesophellia and Chondrogaster; Table 1). Four truffle-like OTUs were shared between dominant root taxa and mammalian diets and five dominant ECM OTUs were shared between soil and scat samples (Table 1). Within taxa, comparisons showed that Cortinarius was more OTU-rich and more relatively abundant in roots and soil compared to scat samples, whereas Malajczukia and Mesophellia (Mesophelliaceae) were more OTU-rich and abundant in scat samples compared to soil and roots (Table 1; Fig. 2). Hysterangium (Hysterangiaceae) and Chondrogaster (Mesophelliaceae) were relatively more abundant in roots.
Table 1

Mycorrhizal OTUs that make up the dominant proportion (cumulatively 90% of sequence abundance) of samples per site (DC = Davies Creek, TD = Tinaroo Dam), sample type and season, with number of replicates (n), total OTUs per sample group (total), percent relative abundance (RA), accession number, e-value, percentage similarity with database sequence (ID), percentage overlap with reference sequence (Cov) and OTU sequence length (SL). Taxa in boldface are truffle-like/sequestrate and underlined are secotioid or higher taxa that include truffle-like/sequestrate or secotioid taxa. When fruiting habit is listed at genus level, it applies to the whole genus. Mycorrhizal status (Myc) is either ectomycorrhizal (ECM), ericoid mycorrhizal (ErM) or arbuscular mycorrhizal (AM). The mammalian specialist scats are from Bettongia tropica. The mammalian generalist scats are from Isoodon macrourus, I. obesulus, Melomys sp., Trichosurus vulpecula, Uromys caudimaculatus and Zyzomys argurus

Site

Sample

Season

n

Total

RA

Fungal taxa

Myc

Accession

e-value

ID

Cov

SL

DC

roots

dry

6b

84

64.4

Hysterangium aggregatum

ECM

KY697566-7

2.21E-133

100

97.9

333

17.2

Cortinarius globuliformis

ECM

AF325582

2.50E-141

99

100

350

5.7

Hysterangium aggregatum

ECM

KY697566-7

2.16E-129

98

97.9

335

5.3

Cortinarius globuliformis

ECM

AF325582

3.24E-142

99

100

349

roots

wet

6b

102

44.1

Cortinarius

ECM

FR731477

1.53E-143

100

99.7

350

12.5

Hysterangium c

ECM

KC222660

1.00E-144

94

100

340

11.8

Hysterangium cf gardneri a

ECM

KY697590

3.96E-139

100

99.7

340

11.4

Hysterangium aggregatum

ECM

KY697566-7

2.21E-133

100

97.9

333

7.1

Mesophellia oleifera c

ECM

KY697602-3

4.15E-177

100

100

425

3.9

Cortinarius

ECM

KJ421051

4.44E-112

91

100

358

TD

roots

wet

6b

99

53.1

Cortinarius

ECM

FR731477

1.53E-143

100

99.7

350

12.5

Mesophellia c

ECM

GQ981511

2.00E-111

91

98

298

12.4

Cortinarius

ECM

KF732610

5.34E-105

89

100

353

9.3

Mesophellia oleifera c

ECM

KY697602-3

4.86E-166

97

100

420

4.4

Chondrogaster spB/spF a

ECM

KY697582-5

4.75E-151

100

100

366

DC

specialist diet

dry

7

51

31.0

Mesophellia c,d

ECM

GQ981511

2.00E-111

91

98

298

19.5

Malajcukia ingrattissima d

ECM

KY697598

6.60E-156

100

100

377

19.3

Mesophellia oleifera c

ECM

KY697602-3

4.15E-177

100

100

425

17.1

Mesophellia glauca

ECM

GQ981510

9.13E-147

98

99

376

5.8

Mesophellia glauca

ECM

GQ981511

1.00E-162

97

99

354

specialist diet

wet

6

24

34.7

Russula d

ECM

LC006943

3.99E-138

91

100

426

32.9

Mesophellia c,d

ECM

GQ981511

2.00E-111

91

98

298

17.5

Russula

ECM

UDB016041

6.92E-129

93

100

376

7.0

Cortinarius

ECM

FJ157098

8.08E-118

92

100

371

TD

specialist diet

wet

16

70

26.4

Malajcukia ingrattissima d

ECM

KY697598

6.60E-156

100

100

377

16.6

Mesophellia c,d

ECM

GQ981511

2.00E-111

91

98

298

15.2

Mesophellia

ECM

GQ981511

2.00E-110

91

99

295

12.8

Mesophellia glauca

ECM

GQ981510

9.13E-147

98

99

376

7.2

Russula d

ECM

LC008293

3.95E-138

91

100

422

6.1

Scleroderma spB/spC a , d

ECM

KY697606-7

3.41E-146

100

100

355

3.4

Mesophellia oleifera c

ECM

KY697602-3

4.86E-166

97

100

420

3.0

Mesophellia oleifera c

ECM

KY697602-3

4.15E-177

100

100

425

DC

generalist diets

dry

11

27

68.8

Malajcukia ingrattissima d

ECM

KY697598

6.60E-156

100

100

377

18.7

Mesophellia c,d

ECM

GQ981511

2.00E-111

91

98

298

9.6

Mesophellia

ECM

GQ981511

2.00E-110

91

99

295

generalist diets

wet

8

29

35.3

Mesophellia

ECM

GQ981511

2.00E-110

91

99

295

30.0

Russula d

ECM

LC006943

3.99E-138

91

100

426

16.8

Russula

ECM

UDB016041

6.92E-129

93

100

376

11.5

Lactarius rufus

ECM

KT165272

4.86E-170

100

100

409

TD

generalist diets

wet

8

24

71.4

Rhizopogon pseudoroseolus

ECM

AJ810040

2.84E-168

100

100

405

9.2

Mesophellia c,d

ECM

GQ981511

2.00E-111

91

98

298

7.9

Malajcukia ingrattissima d

ECM

KY697598

6.60E-156

100

100

377

2.6

Hysterangium c

ECM

KC222660

1.00E-144

94

100

341

DC

soil

dry

6b

196

22.4

Russula

ECM

UDB016041

1.08E-122

92

100

370

19.9

Russula d

ECM

LC006943

3.99E-138

91

100

426

11.5

Russula

ECM

UDB016041

4.05E-127

92

100

373

6.4

Russula anthracina

ECM

UDB011194

5.00E-151

97

100

382

4.9

Amanita

ECM

KP071067

2.94E-126

94

100

356

3.6

Inocybe

ECM

FJ904133

1.39E-100

88

100

344

3.5

Hysterangium aggregatum

ECM

KY697566-7

2.21E-133

100

97.9

333

3.1

Russula

ECM

EU019930.1

1.63E-104

93

80.4

382

2.7

Inocybe

ECM

JQ085932

1.01E-91

87

100

346

2.3

Mesophellia d

ECM

GQ981511

2.00E-111

91

98

298

2.1

Lactarius

ECM

HQ318282

2.43E-129

94

100

368

1.3

Inocybe

ECM

JX178624

2.40E-98

86

100

359

1.3

Auritella serpentinocystis

ECM

KJ729858

3.63E-150

100

100

364

1.2

Cortinarius globuliformis

ECM

AF325582

2.50E-141

99

100

350

0.9

Russula

ECM

UDB016041

2.40E-125

92

100

373

0.8

Hysterangium aggregatum

ECM

KY697566-7

2.60E-122

97

97.9

330

0.8

Russula

ECM

AB509981

3.49E-138

94

99.7

380

0.7

Cortinarius

ECM

KR011131

2.92E-122

93

100

363

0.6

Cortinarius globuliformis

ECM

AF325582

3.24E-142

99

100

349

soil

wet

6b

251

24.8

Russula

ECM

UDB016041

4.05E-127

92

100

373

13.7

Cortinarius

ECM

GU233352

1.41E-96

88

100

357

9.6

Russula d

ECM

LC006943

3.99E-138

91

100

426

8.0

Auritella chamaecephala

ECM

KT378201

9.00E-138

97

100

358

7.5

Inocybe

ECM

JQ085932

1.01E-91

87

100

346

4.7

Cortinarius

ECM

KJ421051

4.44E-112

91

100

358

4.5

Malajcukia ingrattissima d

ECM

KY697598

6.60E-156

100

100

377

2.5

Russula

ECM

UDB016041

1.08E-122

92

100

370

2.3

Lactarius

ECM

HQ318282

2.43E-129

94

100

368

1.8

Mesophellia d

ECM

GQ981511

2.00E-111

91

98

298

1.5

Amanita

ECM

JF899547

4.64E-112

89

100

371

1.1

Cantharellus

ECM

AB509732

8.03E-106

85

99.7

398

0.9

Russula

ECM

UDB016041

3.12E-126

92

100

373

0.8

Auritella serpentinocystis

ECM

KJ729858

3.63E-150

100

100

364

0.7

Russula

ECM

KM373243

3.51E-134

93

100

391

0.7

Hysterangium aggregatum

ECM

KY697566-7

2.21E-133

100

97.9

333

0.6

Scleroderma spB/spC a , d

ECM

KY697606-7

3.41E-146

100

100

355

0.5

Oidiodendron

ErMe

AF062808.1

1.51E-105

95

100

291

0.5

Glomeromycetes

AM

JF276264

4.84E-128

96

100

348

0.4

Auritella

ECM

KT378201

4.51E-116

92

100

354

0.4

Glomerales

AM

AY394681

3.63E-76

81

100

380

0.3

Glomerales

AM

HE794042

2.00E-117

93

100

338

0.3

Glomeraceae

AM

KM226647

1.20E-115

97

88.6

343

0.3

Inocybe

ECM

JX178624

2.40E-98

86

100

359

0.3

Glomerales

AM

KP235575

1.87E-101

90

97.5

354

0.3

Oidiodendron

ErMe

KX640607

3.00E-131

96

99.7

289

0.2

Russula

ECM

UDB016041

8.38E-122

91

99.5

373

0.2

Glomerales

AM

JX276895

4.56E-124

95

100

340

0.2

Glomerales

AM

KM226647

3.30E-80

86

88.6

343

0.2

Glomerales

AM

AY394681

1.72E-81

82

100

374

TD

soil

wet

6b

289

12.2

Cortinarius globuliformis

ECM

AF325582

6.96E-141

99

100

351

11.5

Cortinarius globuliformis

ECM

AF325582

3.24E-142

99

100

349

9.2

Inocybe alienospora

ECM

KP171105

1.88E-140

99

100

343

6.9

Cortinarius

ECM

FR731477

1.53E-143

100

99.7

350

6.5

Amanita egregia

ECM

KP012748

2.82E-134

100

100

328

5.6

Lactarius

ECM

AB509713

4.60E-112

90

99.7

369

5.0

Inocybe

ECM

KP308804

6.00E-135

89

94

359

4.8

Inocybe

ECM

KP308804

3.05E-99

87

100

352

4.4

Lactarius eucalypti

ECM

UDB002671

1.70E-162

96

100

420

3.2

Clavulina

ECM

JQ724058

3.49E-103

85

100

383

3.1

Austroboletus subvirens

ECM

KP242209

5.04E-155

100

100

375

2.8

Zelleromyces spE

ECM

KY697617-9

8.92E-153

96

100

399

2.6

Lactifluus

ECM

KM282287

1.36E-127

95

100

351

2.1

Inocybe

ECM

AM882711

2.72E-99

90

100

321

2.0

Russula

ECM

UDB016041

1.08E-122

92

100

370

1.5

Scleroderma spB/spC a , d

ECM

KY697606-7

3.41E-146

100

100

355

1.4

Russula d

ECM

LC006943

3.99E-138

91

100

426

1.1

Pisolithus croceorrhizus

ECM

JN847473

8.64E-157

100

100

379

0.8

Inocybe violaceocaulis

ECM

KP641643

4.75E-151

100

100

366

0.8

Amanita

ECM

GU222312

3.39E-111

92

94.1

356

0.6

Pisolithus croceorrhizus

ECM

JN847473

6.64E-156

99

100

379

0.5

Cortinarius globuliformis

ECM

AF325582

3.25E-142

99

100

350

0.5

Amanita

ECM

AB015702

8.29E-95

87

100

355

0.5

Glomerales

AM

JN195694

5.02E-132

96

100

350

0.5

Mesophellia

ECM

GQ981511

8.00E-116

92

97

301

0.4

Russula d

ECM

LC008293

3.95E-138

91

100

422

aIndicates taxa that are indistinguishable from ITS2 sequences (within 3% similarity) from morphological groups identified in Abell-Davis (2008), Online Resource 2

bIncludes three subsamples per sample pooled computationally

cIndicates OTUs that are shared between root and scat samples

dIndicates OTUs that are shared between scat and soil samples

eThe ericaceous shrub, Melichrus urceolatus, was present at low abundance at this site

Shared taxa between samples

The percentage of shared taxa between fungal specialist diets and ECM communities on roots (36.6%) and in soil (28%) was slightly higher than that for fungal generalist diets (26 and 14.7%, respectively; Fig. 4). The percentage of shared truffle-like OTUs from roots and soil and fungal specialist diets was much higher (87.5 and 78.8%, respectively; Fig. 4). In contrast, just over half of the truffle-like taxa from root and soil samples overlapped with fungal generalist diets (52–53%). Arbuscular mycorrhizal (AM) OTU richness was highest from soil samples and AM communities from roots did not overlap significantly with mammalian scat samples (< 1.8%; Fig. 4).
Fig. 4

Venn diagrams; the size of a circle represents the relative OTU richness of each sample type (soil, roots or scats) within each subsample of data (ectomycorrhizal = ECM, arbuscular mycorrhizal = AM, sequestrate/truffle-like = truffles and all OTUs). Overlapping areas represent the proportion of OTUs shared between sample types, whereas the non-overlapping areas represent OTUs unique to specified substrate. The total number of OTUs is 9358, 428 for AM fungi, 344 for ECM fungi and 116 for sequestrate/truffle-like fungi. Specialist scats are from fungal specialist Bettongia tropica, and generalist scats are from Isoodon macrourus, I. obesulus, Melomys sp., Trichosurus vulpecula (ECM only) and Zyzomys argurus. Note: for AM fungi, scats and roots shared 1.8% of taxa and scats and soil shared 0.8% of taxa and this is not shown because there were no taxa shared by all samples

Almost all Hysterangiaceae, Mesophelliaceae and Tuberaceae truffle and truffle-like taxa sequenced from roots and soil were also recovered from mammalian scats (Fig. 5). Hysterangiaceae and Mesophelliaceae made up between 28 and 71% of the ECM sequence abundance of root samples (depending on site and season; Table 1). Of the families sequenced from root samples, over half (59%) of Russulaceae, 20% of Inocybaceae and 7% of Cortinariaceae were also in scat samples (Fig. 5).
Fig. 5

Venn diagrams; the size of a circle represents the relative OTU richness of each sample type (soil, roots or scats) within each family of fungi (Hysterangiaceae [26 OTUs], Mesophelliaceae [59 OTUs] and Tuberaceae [15 OTUs] contain only truffle and truffle-like/sequestrate species; Cortinariaceae [128 OTUs], Russulaceae [159 OTUs] and Inocybaceae [132 OTUs] contain truffle-like and/or secotioid species as well as mushroom species). Overlapping areas represent the proportion of OTUs shared between sample types, whereas the non-overlapping areas represent OTUs unique to specified substrate

Discussion

The hypothesis that mammal communities are important for plant-mycorrhizal relationships, and indirectly are also contributing to the health of mycorrhizal host trees and nutrient cycling (Johnson 1996) assumes that mammal-dispersed truffle-like fungi are an important part of mycorrhizal communities. Our data support this assumption, at least in north-east Australian woodlands with a diverse mammalian community including the fungal specialist, B. tropica. Dominant components of the root-associating mycorrhizal community were ECM truffle-like taxa dispersed by mammals. In another study of tropical ECM communities, truffle-like taxa (Hysterangiales; Hysterangium and Nothocastoreum) were also found in the dominant portion as sporocarps and on roots (Reddell et al. 1999). This indicates that mammals can potentially have a substantial influence on the functioning ECM community. Additionally, the fungal specialist, B. tropica, has previously found to consume a higher diversity and more unique truffle-like taxa than the combined diets of fungal generalists in the same community (Nuske et al. 2018). Indeed, most truffle-like taxa associating with roots were within the fungal specialists’ diet. By dispersing a high diversity of ECM inocula, these mammals, particularly fungal specialists, appear to indirectly contribute to plant productivity and nutrient cycling in these ecosystems.

The hypothesis linking mycophagous mammals to plant health and ecosystem functioning also implies that if the mammal community were to be altered, then the inoculum available for new colonising roots is also altered (over time, potentially lowering truffle-like fungal diversity). If dispersal of these taxa were reduced via changes to the mammal community, then the ECM community is likely to experience major shifts, with unknown consequences for plant health and nutrient cycling. Within Australia, altered ECM communities and decreases in ECM colonisation rates have previously been associated with Eucalypt dieback and decreased crown health (Scott et al. 2012; Ishaq et al. 2013; Horton et al. 2013). Additionally, Australia has experienced high rates of mammal extinction and decline (Short and Smith 1994; Woinarski et al. 2015). Combined with our results, these observations raise concerns of major alterations of landscape-level ecosystem function, underscoring the need for further research. Firstly, further studies are needed to confirm whether this ECM community structure is typical for Australian woodlands. Secondly, future studies should utilise areas where fungal specialists have recently gone extinct or a reduction of mammal diversity has occurred and compare to areas with higher mammal diversity to measure any changes in ECM communities. Thirdly, studies are needed to investigate the functional redundancy of ECM taxa between truffle-like and epigeous taxa for aspects that interact with plant health and nutrient cycling.

Many mycophagy studies have found spores of sporocarpic AM fungi (truffle-like) in mammalian diets, mostly Glomus spp. (Janos et al. 1995; Vernes and Dunn 2009; Nuske et al. 2017). Indeed, these spores have been shown to be viable by inoculating bioassay seedlings with scats containing AM spores (McGee and Baczocha 1994; Reddell et al. 1997). However, our data from an Australian sclerophyll forest show that mammalian diets do not overlap significantly with AM fungi associating with roots or the general soil environment. This indicates that, at least in terms of species diversity, mammal dispersal of AM spores does not have a significant effect on the structure of AM communities in this system. This does not discount other affects mammals may indirectly have on AM communities through physical disturbances or altering plant communities (Gehring and Whitham 1994; Gehring et al. 2002). Other mycophagy studies focusing on AM fungi need to consider the whole community in the soil and on plant roots in order to place appropriate emphasis on these dispersal events for the whole AM fungal community. Nevertheless, mammal dispersal may significantly affect the population structure of sporocarpic AM fungi such as Glomus spp.

Previous ECM community studies in Australia classified between 3 and 27% of taxa as truffle-like (Online Resource 1, Table S1). We report a percentage of truffle-like taxa within this range (21%). We also found that truffle-like taxa comprise dominant portions of the community. Russula and Cortinarius were the most OTU-rich taxa and were included in the relatively abundant groups from our sequencing data and in other ECM surveys in Australia (Online Resource 1, Table S1). However, as many OTUs matching these genera did not match known species, there was not enough taxonomic resolution to discern fruiting habit as these genera contain truffle-like species and mushroom species (e.g. Peintner et al. 2001; Lebel and Tonkin 2007). This limits our capacity to draw conclusions about how truffle-like fungi form part of ECM diversity, and ultimately the overall influence of mycophagous mammals on the ECM community. It also emphasises the need for further targeted truffle-like fungal surveys and taxonomic work on these groups, coupled with continuous updating of online sequence databases.

While we took precautions in this study by removing OTUs present in negative and positive controls, contaminant DNA could still be present and errors in OTU assignment to samples can occur via tag-switching (Carlsen et al. 2012; Nguyen et al. 2015a). For this reason, we consider the proportion of overlapping taxa between sample types to be estimates. Also, taxa we observe at low relative abundances may be indistinguishable from contamination. Amplicon sequencing data are considered ‘semi-quantitative’ in that relative abundances of sequences within rather than between taxa can be more meaningful as PCR procedures may selectively amplify certain taxa more than others (among other reasons) (Amend et al. 2010). Nevertheless, Nguyen et al. (2015a) argue that relative abundances of taxa may still have ecological value, provided the sequencing errors are appropriately handled and recognised. While we cannot verify whether dominant truffle-like taxa observed were selectively amplified, comparisons within truffle-like taxa (e.g. Hysterangium) show that they have a higher abundance in root-associated communities. OTUs matching truffle-like taxa Malajczukia/Mesophellia, which have a high relative abundance in scats, are also present in root-associating communities. As our results were consistent across two sites and seasons, we consider our assessment of the ECM community structure sufficiently accurate to be confident in the conclusion that truffle-like taxa, and their mammalian dispersers, are important to ECM communities in this system.

Unexpectedly, some OTUs matched truffle sequences of non-Australian taxa (Tuber sp. and Rhizopogon pseudoroseolus). No Tuber species are known to occur natively in Australia, or have associations with native flora (Bonito et al. 2013). Introduced Tuber species associate with introduced trees (mainly on Quercus and Corylus) in temperate regions of Australia (Linde and Selmes 2012; Thomas 2014) and are also known to associate with Pinaceae (Bonito et al. 2013). Rhizopogon species also associate with Pinaceae and other non-native Australian trees (Ivory and Munga 1983; Tedersoo et al. 2007) and have been recorded in Australian pine plantations (Bell and Adams 2004). Incidentally, there is a plantation of Pinus caribaea ca. 10 km from one of the study sites (Tinaroo Dam) (Applegate and Nicholson 1988). Rhizopogon was found in highest abundance in U. caudimaculatus and Per. nasuta scats at Tinaroo Dam (Nuske et al. 2018); both mammal species have been known to have home ranges within this distance (Scott et al. 1999; Streatfeild 2009). Therefore, it is possible that the OTUs matching R. pseudoroseolus or Tuber sp. resulted from native mammals consuming a non-native, introduced ectomycorrhizae associated with local Pinus plantations. Alternatively, they may have resulted from a contamination from laboratory processing. Nevertheless, the five OTUs identified are unlikely to alter the main findings of this study.

Conclusion

Diverse ectomycorrhizal fungal communities are vital for healthy ecosystems because of their intimate interactions with plants and pivotal role in nutrient cycling. These fungi also provide food sources for many animals, including the endangered and threatened fungal specialists; species like B. tropica. Little is known about how disturbances to these ecosystems can change ECM fungal communities. Our data show that mammal dispersed truffle-like taxa can form a dominant proportion of root-associating ECM fungal communities. This suggests that changes in the mammal community could, over time, induce changes in functioning ECM fungal communities, which may in turn impact plant health and nutrient cycles on a large scale. Australia has already lost many mammal species and many species are in decline (Woinarski et al. 2015). Conservation of mammal diversity may not only be imperative for ecosystem function at higher trophic levels, but also for maintaining fungal diversity and healthy mycorrhizal-plant relationships.

Notes

Acknowledgements

Sincere thanks to Queensland Parks and Wildlife Service staff Rob Miller, Lana Little, Jack Cosgrove, Karl Goetze, Chris White, Julie Bunny and Miki Bradley, World Wildlife Fund Australia staff Jessica Koleck, James Cook University students and staff Tegan Whitehead, Stephanie Todd, Naomi Bowie and Elise Chatterton and many field volunteers for help with field work and collection of samples.

Funding sources

This research was supported by an Australian Postgraduate Award, Wet Tropics Management Authority (Student Grant 916), Australasian Mycological Society Research Award (2014), North Queensland Wildlife Trust (2014) and Australian Government Caring for our Country 2 Target Area Grant 2013/14 (Project ID: TAG14-00542) Bettongia tropica population status, viability and impact of fire with project partners James Cook University, Queensland Parks and Wildlife Service, Department of Environment and Heritage Protection and World Wildlife Fund Australia (WWF-Australia).

Authors’ contributions

Nuske, Susan J: designed study; collected data; sequenced DNA; analysed data; wrote manuscript.

Anslan, Sten: preformed bioinformatics; edited manuscript.

Tedersoo, Leho: contributed laboratory space, primers and reagents; provided advice on high-throughput sequencing; edited manuscript.

Congdon, Bradley C: provided advice on design of study and data analysis; edited manuscript.

Abell, Sandra E: provided advice on design of study and data analysis; edited manuscript.

Compliance with ethical standards

This research was performed under permits granted by the Queensland Government, EHP (WISP15227914, WITK14639614 and WITK11258712). All wildlife was handled according to JCU Animal Ethics Guidelines (approval number: A2044). The authors declare that they have no conflict of interest.

Supplementary material

572_2019_886_MOESM1_ESM.pdf (161 kb)
Table S1 (PDF 161 kb)

References

  1. Abell-Davis SE (2008) Tropical hypogeous fungal sporocarp distribution in time and space. Implications for an endangered specialist mycophagous marsupial, Bettongia tropica. PhD thesis. School of Marine and Tropical Biology. James Cook UniversityGoogle Scholar
  2. Adams F, Reddell P, Webb M, Shipton W (2006) Arbuscular mycorrhizas and ectomycorrhizas on Eucalyptus grandis (Myrtaceae) trees and seedlings in native forests of tropical North-Eastern Australia. Aust J Bot 54:271–281CrossRefGoogle Scholar
  3. Amend AS, Seifert KA, Bruns TD (2010) Quantifying microbial communities with 454 pyrosequencing: does read abundance count? Mol Ecol 19:5555–5565.  https://doi.org/10.1111/j.1365-294X.2010.04898.x CrossRefGoogle Scholar
  4. Anslan S, Bahram M, Hiiesalu I, Tedersoo T (2017) PipeCraft: flexible open-source toolkit for bioinformatics analysis of custom high- throughput amplicon sequencing data. Mol Ecol Resour May:online first 17:e234–e240.  https://doi.org/10.1111/1755-0998.12692 CrossRefGoogle Scholar
  5. Applegate GB, Nicholson DI (1988) Caribbean pine in an agroforestry system on the Atherton tableland in north East Australia. Agrofor Syst 7:3–15.  https://doi.org/10.1007/BF01890466 CrossRefGoogle Scholar
  6. Bell TL, Adams MA (2004) Ecophysiology of ectomycorrhizal fungi associated with Pinus spp. in low rainfall areas of Western Australia. Plant Ecol 171:35–52.  https://doi.org/10.1023/B:VEGE.0000029372.78102.9d CrossRefGoogle Scholar
  7. Bonito G, Smith ME, Nowak M, Healy RA, Guevara G, Cázares E, Kinoshita A, Nouhra ER, Domínguez LS, Tedersoo L, Murat C, Wang Y, Moreno BA, Pfister DH, Nara K, Zambonelli A, Trappe JM, Vilgalys R (2013) Historical biogeography and diversification of truffles in the Tuberaceae and their newly identified southern hemisphere sister lineage. PLoS One 8:e52765.  https://doi.org/10.1371/journal.pone.0052765 CrossRefGoogle Scholar
  8. Bougher NL, Lebel T (2001) Truffle-like (truffle-like) fungi of Australia and New Zealand. Aust Syst Bot 14:439–484CrossRefGoogle Scholar
  9. Brundrett MC (2009) Mycorrhizal associations and other means of nutrition of vascular plants: understanding the global diversity of host plants by resolving conflicting information and developing reliable means of diagnosis. Plant Soil 320:37–77CrossRefGoogle Scholar
  10. Camacho C, Coulouris G, Avagyan V et al (2009) BLAST plus: architecture and applications. BMC Bioinformatics 10:421.  https://doi.org/10.1186/1471-2105-10-421 CrossRefGoogle Scholar
  11. Carlsen T, Bjørnsgaard Aas A, Lindner D et al (2012) Don’t make a mista(g)ke: is tag switching an overlooked source of error in amplicon pyrosequencing studies? Fungal Ecol 5:747–749.  https://doi.org/10.1016/j.funeco.2012.06.003 CrossRefGoogle Scholar
  12. Claridge AW, May TW (1994) Mycophagy among Australian mammals. Aust J Ecol 19:251–275CrossRefGoogle Scholar
  13. Gehring CA, Whitham TG (1994) Interactions between aboveground herbivores and the mycorrhizal mutualists of plants. Trends Ecol Evol 9:251–255CrossRefGoogle Scholar
  14. Gehring CA, Wolf JE, Theimer TC (2002) Terrestrial vertebrates promote arbuscular mycorrhizal fungal diversity and inoculum potential in a rain forest soil. Ecol Lett 5:540–548.  https://doi.org/10.1046/j.1461-0248.2002.00353.x CrossRefGoogle Scholar
  15. Goto BT, Maia LC (2005) Sporocarpic species of arbuscular mycorrhizal fungi (Glomeromycota), with a new report from Brazil. Acta Bot Bras 19:633–637.  https://doi.org/10.1590/S0102-33062005000300025 CrossRefGoogle Scholar
  16. Horton BM, Glen M, Davidson NJ, Ratkowsky D, Close DC, Wardlaw TJ, Mohammed C (2013) Temperate eucalypt forest decline is linked to altered ectomycorrhizal communities mediated by soil chemistry. For Ecol Manag 302:329–337.  https://doi.org/10.1016/j.foreco.2013.04.006 CrossRefGoogle Scholar
  17. Ishaq L, Barber PA, Hardy GESJ, Calver M, Dell B (2013) Seedling mycorrhizal type and soil chemistry are related to canopy condition of Eucalyptus gomphocephala. Mycorrhiza 23:359–371.  https://doi.org/10.1007/s00572-012-0476-5 CrossRefGoogle Scholar
  18. Ivory MH, Munga FM (1983) Growth and survival of container-grown Pinus caribaea infected with various ectomycorrhizal fungi. Plant Soil 71:339–344CrossRefGoogle Scholar
  19. Izzo AD, Meyer M, Trappe JM (2005) Hypogeous ectomycorrhizal fungal species on roots and in small mammal diet in a mixed-conifer forest. For Sci 51:243–254Google Scholar
  20. Janos DP, Sahley CT, Emmons LH (1995) Rodent dispersal of vesicular-arbuscular mycorrhizal fungi in Amazonian Peru. Ecology 76:1852–1858CrossRefGoogle Scholar
  21. Johnson CN (1996) Interactions between mammals and ectomycorrhizal fungi. Trends Ecol Evol 11:503–507CrossRefGoogle Scholar
  22. Lebel T, Tonkin JE (2007) Australasian species of Macowanites are truffle-like species of Russula (Russulaceae, Basidiomycota). Aust Syst Bot 20:355–381.  https://doi.org/10.1071/SB07007 CrossRefGoogle Scholar
  23. Li W, Godzik A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22:1658–1659.  https://doi.org/10.1093/bioinformatics/btl158 CrossRefGoogle Scholar
  24. Lindahl BD, Nilsson RH, Tedersoo L, Abarenkov K, Carlsen T, Kjøller R, Kõljalg U, Pennanen T, Rosendahl S, Stenlid J, Kauserud H (2013) Fungal community analysis by high-throughput sequencing of amplified markers–a user’s guide. New Phytol 199:288–299CrossRefGoogle Scholar
  25. Linde CC, Selmes H (2012) Genetic diversity and mating type distribution of Tuber melanosporum and their significance to truffle cultivation in artificially planted truffiéres in Australia. Appl Environ Microbiol 78:6534–6539.  https://doi.org/10.1128/AEM.01558-12 CrossRefGoogle Scholar
  26. Lu X, Malajczuk N, Brundrett M, Dell B (1999) Fruiting of putative ectomycorrhizal fungi under blue gum (Eucalyptus globulus) plantations of different ages in Western Australia. Mycorrhiza 8:255–261.  https://doi.org/10.1007/s005720050242 CrossRefGoogle Scholar
  27. Malajczuk N, Trappe JM, Molina R (1987) Interrelationships among some ectomycorrhizal trees, hypogeous fungi and small mammals: Western Australian and northwestern American parallels. Aust J Ecol 12:53–55CrossRefGoogle Scholar
  28. Maser C, Nussbaum RA, Trappe JM (1978) Fungal-small mammal interrelationships with emphasis on Oregon coniferous forests. Ecology 59:799–809.  https://doi.org/10.2307/1938784 CrossRefGoogle Scholar
  29. McGee PA, Baczocha N (1994) Sporocarpic Endogonales and Glomales in the scats of Rattus and Perameles. Mycol Res 98:246–249CrossRefGoogle Scholar
  30. McMurdie PJ, Holmes S (2013) Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8:e61217.  https://doi.org/10.1371/journal.pone.0061217 CrossRefGoogle Scholar
  31. Nguyen NH, Smith D, Peay K, Kennedy P (2015a) Parsing ecological signal from noise in next generation amplicon sequencing. New Phytol 205:1389–1393CrossRefGoogle Scholar
  32. Nguyen NH, Song Z, Bates ST, Branco S, Tedersoo L, Menke J, Schilling JS, Kennedy PG (2015b) FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol 20:1–8.  https://doi.org/10.1016/j.funeco.2015.06.006 Google Scholar
  33. Nuske SJ, Anslan S, Tedersoo L, Bonner MTL, Congdon BC, Abell SE (2018) The endangered northern bettong, Bettongia tropica, performs a unique and potentially irreplaceable dispersal function for ectomycorrhizal truffle fungi. Mol Ecol 27:4960–4971.  https://doi.org/10.1111/mec.14916
  34. Nuske SJ, Vernes K, May TW, Claridge AW, Congdon BC, Krockenberger A, Abell SE (2017) Data on the fungal species consumed by mammal species in Australia. Data Br 12:251–260.  https://doi.org/10.1016/j.dib.2017.03.053 CrossRefGoogle Scholar
  35. Peintner U, Bougher NL, Castellano MA, Moncalvo JM, Moser MM, Trappe JM, Vilgalys R (2001) Multiple origins of truffle-like fungi related to Cortinarius (Cortinariaceae). Am J Bot 88:2168–2179CrossRefGoogle Scholar
  36. R Core Team (2012) R: A Language and Environment for Statistical ComputingGoogle Scholar
  37. Reddell P, Gordon V, Hopkins MS (1999) Ectomycorrhizas in Eucalyptus tetrodonta and E. miniata forest communities in tropical northern Australia and their role in the rehabilitation of these forests following mining. Aust J Bot 47:881–907.  https://doi.org/10.1071/bt97126 CrossRefGoogle Scholar
  38. Reddell P, Spain AV, Hopkins M (1997) Dispersal of spores of mycorrhizal fungi in scats of native mammals in tropical forests of northeastern Australia. Biotropica 29:184–192CrossRefGoogle Scholar
  39. Scott LK, Hume ID, Dickman CR (1999) Ecology and population biology of long-nosed bandicoots (Perameles nasuta) at north head, Sydney harbour National Park. Wildl Res 26:805–821CrossRefGoogle Scholar
  40. Scott PM, Shearer BL, Barber PA, Hardy GESJ (2012) Relationships between the crown health, fine root and ectomycorrhizae density of declining Eucalyptus gomphocephala. Australas Plant Pathol 42:121–131.  https://doi.org/10.1007/s13313-012-0152-4 CrossRefGoogle Scholar
  41. Short J, Smith A (1994) Mammal decline and recovery in Australia. J Mammal 75:288–297CrossRefGoogle Scholar
  42. Song Z, Schlatter D, Kennedy P, Kinkel LL, Kistler HC, Nguyen N, Bates ST (2015) Effort versus reward: preparing samples for fungal community characterization in high-throughput sequencing surveys of soils. PLoS One 10:e0127234.  https://doi.org/10.1371/journal.pone.0127234 CrossRefGoogle Scholar
  43. Streatfeild C (2009) The effects of habitat fragmentation on the demography and population genetic structure of Uromys caudimaculatus. PhD thesis. School of Natural Resource Sciences. Queensland University of TechnologyGoogle Scholar
  44. Tedersoo L, Bahram M, Põlme S et al (2014) Global diversity and geography of soil fungi. Science (80-) 346:125668–1–1256688–10.  https://doi.org/10.1126/science.aaa1185 CrossRefGoogle Scholar
  45. Tedersoo L, Suvi T, Beaver K, Kõljalg U (2007) Ectomycorrhizal fungi of the Seychelles: diversity patterns and host shifts from the native Vateriopsis seychellarum (Dipterocarpaceae) and Intsia bijuga (Caesalpiniaceae) to the introduced Eucalyptus robusta (Myrtaceae), but not Pinus caribea (Pinaceae). New Phytol 175:321–333.  https://doi.org/10.1111/j.1469-8137.2007.02104.x CrossRefGoogle Scholar
  46. Thomas PW (2014) An analysis of the climatic parameters needed for Tuber melanosporum cultivation incorporating data from six continents. Mycosphere 5:137–142.  https://doi.org/10.5943/mycosphere/5/1/5 CrossRefGoogle Scholar
  47. Trappe JM, Molina R, Luoma DL, et al (2009) Diversity, ecology, and conservation of truffle Fungi in forests of the Pacific northwest. United States Department of Agriculture, Forest Service, Pacific northwest Research Station. Portland, OregonGoogle Scholar
  48. Van Dyck S, Gynther I, Baker A (eds) (2013) Field companion to the mammals of Australia. New Holland Publishers, SydneyGoogle Scholar
  49. Vernes K (2007) Are diverse mammal communities important for maintaining plant-fungal associations and ecosystem health? Australas Plant Conserv 15:16–18Google Scholar
  50. Vernes K, Dunn L (2009) Mammal mycophagy and fungal spore dispersal across a steep environmental gradient in eastern Australia. Austral Ecol 34:69–76.  https://doi.org/10.1111/j.1442-9993.2008.01883.x CrossRefGoogle Scholar
  51. Woinarski JCZ, Burbidge AA, Harrison PL (2015) Ongoing unraveling of a continental fauna: decline and extinction of Australian mammals since European settlement. Proc Natl Acad Sci U S A 112:4531–4540.  https://doi.org/10.1073/pnas.1417301112 CrossRefGoogle Scholar

Copyright information

© The Author(s) 2019

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.College of Science and Engineering, Centre for Tropical Environmental and Sustainability Science, Australian Tropical HerbariumJames Cook UniversityCairnsAustralia
  2. 2.Department of Forest Ecology and ManagementSwedish University of Agricultural SciencesUmeåSweden
  3. 3.Zoological InstituteBraunschweig University of TechnologyBraunschweigGermany
  4. 4.Natural History Museum and Institute of Ecology and Earth SciencesUniversity of TartuTartuEstonia
  5. 5.College of Science and Engineering, Centre for Tropical Environmental and Sustainability ScienceJames Cook UniversityCairnsAustralia

Personalised recommendations