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The ecology and diversity of wood-inhabiting macrofungiin a native Eucalyptus obliqua forest of southern Tasmania,Australia

Genevieve M. GATESa,b, Caroline MOHAMMEDa, Tim WARDLAWc,David A. RATKOWSKYa,b,*, Neil J. DAVIDSONb

aSchool of Agricultural Science, University of Tasmania, Private Bag 54, Hobart, Tasmania 7001, AustraliabSchool of Plant Science, University of Tasmania, Private Bag 55, Hobart, Tasmania 7001, AustraliacForestry Tasmania, GPO Box 207, Hobart, Tasmania 7001, Australia

a r t i c l e i n f o

Article history:

Received 6 February 2010

Revision received 28 June 2010

Accepted 26 July 2010

Available online 30 October 2010

Corresponding editor:

Jacob Heilmann-Clausen

Keywords:

Coarse woody debris

Eucalyptus

Indicator species

Tasmania

Wildfire

Wood-inhabiting macrofungi

a b s t r a c t

The ecology and diversity of the macrofungal species assemblages associated with woody

material in four plots with differing wildfire histories in a Tasmanian tall, wet, native

Eucalyptus obliqua forest were investigated. The four woody substrata (CWD, other dead

wood ODW, stags and living trees) supported substantially different macrofungal

assemblages, although there was some degree of overlap between CWD and ODW. The

best separation between assemblages occurring on all kinds of wood, or on individual

pieces of CWD, was obtained when the 100 10� 10 m subplots of the study were grouped

into classes based on the most frequently occurring higher vascular plant species within

each subplot. Three polypore species were identified as being possible indicators of bio-

diverse old E. obliqua forests. The sustainable management of these forests will require

retaining dead wood of all sizes, species and decay stages to maintain wood-inhabiting

fungal diversity.

ª 2010 Elsevier Ltd and The British Mycological Society. All rights reserved.

Introduction

Tasmania, the island state ofAustralia, lies between 40� and 43�

400 south of the equator and is separated from the mainland of

Australia by Bass Strait. The most widespread forest type in

Tasmania is wet Eucalyptus obliqua forest (Public Land Use

Commission 1996). E. obliqua forests need disturbance to

regenerate; the most common natural disturbance in this

forest type in Tasmania is wildfire. In the absence of fire the

lowlandwet E. obliqua forests of southern Tasmaniawill, as the

eucalypts die off with age (350e400 yrs), become climax

temperate rainforests (see Jackson 1968) dominated by Notho-

fagus cunninghamii (Fagaceae) and Atherosperma moschatum

(Monimiaceae) with no or very few eucalypts remaining.

Wildfires in these native forests generate deadwood of varying

sizes and in many different stages of decay depending on the

intensity and the frequency of fires. Large dead wood, termed

coarse woody debris (CWD), is well documented as being of

particular ecological importance (see Harmon et al. 1986; Grove

et al. 2002; Wu et al. 2005). E. obliqua trees at maturity range in

height from 15e90 m (Curtis & Morris 1975) and frequently

attain a height of over 70m (Kirkpatrick & Backhouse 1981).

* Corresponding author. School of Agricultural Science, University of Tasmania, Private Bag 54, Hobart, Tasmania 7001, Australia.E-mail address: [email protected] (D.A. Ratkowsky).

ava i lab le a t www.sc iencedi rec t .com

journa l homepage : www.e lsev ie r . com/ loca te / funeco

1754-5048/$ e see front matter ª 2010 Elsevier Ltd and The British Mycological Society. All rights reserved.doi:10.1016/j.funeco.2010.07.005

f u n g a l e c o l o g y 4 ( 2 0 1 1 ) 5 6e6 7


The tall height combined with a large diameter produces

a large volume of large dead wood in a mature E. obliqua forest,

which according to Woldendorp et al. (2002) is amongst the

largest in the world.

The richness and assemblages of wood-inhabiting macro-

fungi have been linked in previous studies to stage of wood

decay and diameter of wood (e.g. Renvall 1995; Høiland &

Bendiksen 1996; Norden et al. 2004), volume (Heilmann-

Clausen & Christensen 2004; Ir�s _enait _e & Kutorga 2007), and

stand structure/age (Norden& Paltto 2001). The species ofwood

also affect the diversity of wood-inhabiting fungi (Jung 1987;

Nakasone 1993; Hood et al. 2004). Furthermore, community

development can be stimulated or inhibited by environmental

factors. For example, Takahashi & Kagaya (2005) found that

a species which usually occurred on CWD of a certain size or

decay class fruited on CWD of other sizes or decay classes

subjected to different temperature and moisture conditions.

Forestry management practices can alter the diversity of

wood-inhabiting fungi (Bader et al. 1995; Siitonen 2001; Sippola

et al. 2001) as habitats are fragmented, leading to changes in

the amounts and proportions of large dead wood to small

dead wood and stages of decay (Lindblad 1998; Fridman &

Walheim 2002; Heilmann-Clausen & Vesterholt 2008).

In Australia, research specifically on wood-inhabiting fungi

has been instigated historically by the economic importance of

timber (Simpson 1996) and concentrated on wood decay in

a pathological sense rather than ecological (see Refshauge 1938;

Rudman 1964; Da Costa 1979). There are no ‘Red data lists’

(rarity, endangerment and distribution), which means that

there are no focal species to aid in conservation and manage-

ment protocols as in Europe and the USA. In the Northern

Hemisphere, polypore species are often a focal point of studies,

not only for biodiversity (e.g. Norstedt et al. 2001; Sippola et al.

2001; Penttila et al. 2004; Hottola & Siitonen 2008), but also for

fungal-invertebrate interactions (e.g. Araya 1993; Kaila et al.

1994; Johansson et al. 2006). Some polypore species are consid-

ered to be indicators of old growth forest (Kotiranta & Niemela

1996) and important for the persistence of specialist insects

(Komonen 2001).

The current study provides information on the macro-

fungal communities from living wood to dead standing wood

(stags) to fallen dead wood in a native eucalypt forest after

natural disturbance. This information can be interpreted

ecologically to assess the role of old forests and old trees in

maintaining macrofungal diversity.

The aims of this paper are to: (1) compare the richness and

assemblages of macrofungal species associated with wood

(i.e. CWD, other dead wood, stags and living wood) in four

plots with differing wildfire histories in the same forest type;

(2) determine the relationships between species richness and

the attributes of CWD, viz. diameter, length, decay class and

the derived variables volume and surface area; and (3)

examine species assemblages on CWD.

Methodology and analyses

Study area, mapping of live trees and CWD

For a comprehensive description of the site characteristics, the

plot establishment and the methods of surveying and doc-

umenting the data, see Gates (2009, Chapter 2). Briefly, four

0.25 ha plots of known but differing fire history were chosen

along the ‘Bird Track’ at the Warra Long Term Ecological

Research site in southern Tasmania (Fig 1). The forest type was

a tall, wet, naturally regenerated native forest dominated by E.

obliqua. Documented accounts, maps of fire history and fire

scars on E. obliqua trees were used to determine age since fire

(Turner et al. 2007). The names given to these plots were,

respectively, ‘Old growth’ (unburnt for�200 yr), ‘1898’ (thought

to have been last burnt 108 yr previously, but it was discovered

later in the study that parts of the plot were subjected to

a secondfire in the year 1934), ‘1934’ (last burnt 72 yr previously)

and ‘1898/1934’ (last two fires 72 and 108 yr previously). Each of

the 50� 50m plots was divided into 25 10� 10m subplots. The

standing live trees of each of these 100 subplots were identified

and named according to the nomenclature of Buchanan (2009),

their diameters recorded, and the positions of all trees with

stems �10 cm determined and mapped. In addition, all coarse

woody debris (CWD), defined as pieces of dead wood �1 m

length and �10 cm diameter were mapped. This definition

included stumps, suspendedpieces ofwood, and shards aswell

as fallen trunks and branches on the forest floor. CWD origi-

nating fromallwoodyplant specieswas included in the study. If

a piece of CWD traversed two or more subplots, the portion

within each subplot was numbered as a separate piece of CWD

and its length was measured to the boundary of the subplot.

This facilitatedsubsequent statisticalanalyses conductedat the

subplot level. For each piece of CWD and each stag, its length,

diameter, decay class and bryophyte coverwere recorded. If the

tree species from which the dead wood originated was identi-

fiable, the species was noted. However, only 20 % of the CWD

could be assigned to species level using this visual method.

Decay class was based on exterior appearance, following

Fig 1 e Tasmania, showing the location of the Warra LTER site and the positions of the four plots of this study at that site.

The ecology and diversity of wood-inhabiting macrofungi 57


a classification used by Webber (2006) solely for E. obliqua (see

Gates 2009, Appendix 1, Table 3.A2). As differences were

observed in the way decay progressed among different species

of CWD, the decay classificationwasmodified to accommodate

these differences. The percent bryophyte cover on the surface

of the piece of CWD was estimated by eye.

Dead wood other than CWD

In addition to the fallen CWD, stags (standing deadwood�1 m

height and �10 cm diameter) were mapped prior to surveying

for fungi. The artificial category other dead wood (ODW) was

devised to include all pieces of dead wood<10 cm diameter or

<1 m length, which included small stumps, lumps, fragments,

and small shards. That is, except for stags, this definition

covered all deadwood that failed tomeet the criteria for CWD.

In contrast to the procedure used for CWD and stags, the

quantity of material made it impractical to map ODW prior to

the commencement of the fungal survey. However, diameter

and decay class were recorded when a piece of ODW sup-

ported a macrofungus during the subsequent fungal survey.

Note that the definition of ODWused here includes as a subset

the category fine woody debris (FWD), which, following Kruys

& Jonsson (1999), was defined as dead wood <10 cm diameter

and of unrestricted length. Although Kruys & Jonsson (1999)

had a lower limit of 5 cm diameter for their FWD, our defini-

tion has no lower limit.

Survey and laboratory methods

Macrofungi are distinguished by having fruiting structures

visible to the naked eye (Lodge et al. 2004). We recorded the

presence/absence of all Ascomycota and all gilled and aphyl-

lophoraceous Basidiomycota, including thin, filmy or crustose

species, on all woody substrata, living or dead. The inventories

in each of the 25 subplots of each of the four plots were made

during 30 visits to each plot (excepting one missed visit to

‘1898/1934’) at approximately fortnightly intervals from May

2006 to Jul 2007. Species known to the authors were named

(if validly published) usingMay&Wood (1997),May et al. (2002),

the interactive list of fungi on the website of the Royal Botanic

Gardens Melbourne (http://www.rbg.vic.gov.au) and Index

Fungorum (http://www.speciesfungorum.org). Unpublished

familiar species were recorded using ‘tag names’. Those

species new to the authorswere described from freshmaterial

with written descriptions (colour followed Kornerup &

Wanscher 1978), photographs, drawings and micrographs of

microscopic features. Fruit bodies were then dried for 24 hr in

a Sunbeamª food dehydrator to provide voucher material for

deposit in the Tasmanian Herbarium (HO). Themajority of the

‘tag species’were confidently assigned to genus levelwith very

few unidentified beyond family status.

Database preparation

For each visit, the species were entered as presence/absence

data irrespective of the number of fruit bodies found. The

statistical methods, discussed below, are largely multivariate

procedures, and operate on a two-dimensional matrix con-

sisting of rows and columns. This required reducing the

database to two dimensions, achieved in one of the following

ways, by: (1) collapsing the database into a ‘species by visits’

matrix in which a species was recorded as either present or

absent during a visit, ignoring the subplot or subplots inwhich

it was found; (2) collapsing the database into a ‘species by

subplots’ matrix in which a species was recorded as either

present or absent in each subplot, ignoring the visit or visits

during which it was found; or (3) for CWD, ignoring visits and

collapsing the database into a ‘species by pieces of CWD’

matrix.

Statistical methods e macrofungi on all kinds of wood

A variety of summary statistics and statistical procedures was

used to examine the macrofungi on each of the four woody

substrates, viz. CWD, ODW, stags and living trees. For species

richness, this included the use of species accumulation curves

calculated using the MaoeTau estimator available in the

package EstimateS (Colwell 2005). This theoretical estimator for

sample-based rarefaction removes seasonality and random

variation among visits, effectively producing a randomized

species accumulation curve (Colwell et al. 2004). For species

assemblages, non-metric multidimensional scaling (nMDS), as

implemented in PRIMER v6 (Clarke & Gorley 2006), was used to

explore whether there were indications of differences among

substrata types without imposing constraints or hypotheses.

Similarity (resemblance) was defined employing the widely

used BrayeCurtis measure (Bray & Curtis 1957), the database

being the ‘speciesbyvisits’matrixwhere subplotswere ignored.

In addition, the possible presence of indicator species (sensu

Dufrene & Legendre 1997) to characterize each of the four

substratawasexaminedusing thepackagePC-ORDVersion4.10

(McCune & Mefford 1999).

Also used were the inferential methods canonical correla-

tions analysis (CAP-CCorA) and distance-based redundancy

analysis (dbRDA andDISTLM), routines in the suite of programs

for multivariate ecological data developed by M.J. Anderson

and available as an add-on (PERMANOVAþ) to PRIMER v6

(Clarke & Gorley 2006; Anderson et al. 2008). Unlike classical

canonical correlations analysis, where a multivariate normal

distribution has to be assumed, CAP-CCorA, like nMDS, oper-

ates on realistic ecologically-based resemblance matrices such

as those defined using the BrayeCurtis measure. The question

that was testedwaswhether therewas an association between

the species lists obtained from the subplots (using the ‘species

by subplots’ matrix where visits are ignored) and the living

vascular plant species present in each subplot. This was ach-

ieved using a two-stage procedure. In the first stage, permu-

tation tests were performed using CAP-CCorA employing the

two data matrices (one containing the resemblances among

the species lists in each of the 100 subplots and the other

containing the abundances of the vascular plant species

present in those same subplots). Significance levels were

provided by permutation trials, using 9 999 random permuta-

tions of the observed data set. If a significant correlation was

obtained, then DISTLMmodelling was used to establish the set

of vascular species that best explained the differences among

the macrofungal species assemblages at the subplot level. In

this stage, the abundances of the 21 vascular plant species (see

Gates 2009, Table 2.2) were transformed using log (Xþ 1) to

58 G.M. Gates et al.


reduce the effect ofmarkedly unequal abundances. To increase

the likelihood of obtaining an ecologically interpretable result,

themodelling was restricted to 88 subplots which could clearly

be identified as being characterized by one of the three vege-

tation types, classified according to their predominant under-

story species. One of these was labelled the ‘Pomaderris’ stand

type, which encompassed subplots from the two plots burnt

72 yr previously, viz. those from ‘1898/1934’ plus subplots from

the ‘1898’ plot that were subjected to a second wildfire in 1934.

This stand type contained abundant living trees of Pomaderris

apetala (Rhamnaceae) on soils derived from dolerite. The

second stand type was labelled ‘Monotoca’, derived exclusively

from subplots of the ‘1934’ plot, and which had an acidic soil

derived from sandstone, promoting the replacement of P. ape-

tala by Monotoca glauca (Ericaceae). The third stand type,

labelled ‘Rainforest’, encompassed subplots from the ‘1898’ and

‘Old growth’ plots that predominantly contained the rainforest

species N. cunninghamii and/or A. moschatum, sometimes

accompanied by one or more of the species Anopterus

glandulosus (Escalloniaceae), Eucryphia lucida (Eucryphiaceae),

Tasmannia lanceolata (Winteraceae) and Phyllocladus aspleniifo-

lius (Podocarpaceae or Phyllocladaceae). If the DISTLM model

proved to be significant, the dbRDA routine was used to visu-

alize the results, with plotting symbols chosen that reflect

a combination of the plot in which the subplot occurs and one

of the three predominant vegetation types described above.

Statistical methods e macrofungi on CWD

One question of interest is whether ‘species richness’, taken to

mean the number of macrofungal species, was a function of

CWD attributes, i.e. decay class, length, diameter, bryophyte

cover aswell as the derived attributes volume and surface area.

To answer this question, multiple linear regression analysis,

with forward and backward elimination procedures, was used

on 814 composite pieces of CWD, derived from piecing together

965 individual pieces of CWD that included pieces measured

separately on each side of the boundary when CWD extended

over the boundary between subplots.

A second question of interest is whether the macrofungal

species assemblages on CWD were correlated with the stand

composition of the subplots in which they were found. The

identification of the living trees showed that 88 of the 100

subplots could be classified into one of three main stand types,

‘Pomaderris’, ‘Monotoca’ or ‘Rainforest’, described in the

previous section. Subplots not assigned to one of these three

stand types were placed in a fourth group, labelled ‘Unclassi-

fied’. As this study is of an exploratory character, without

replication of forest types, an unconstrained ordination was

used to display the positions of the pieces of CWD. As before,

nMDS was used, and implemented in PRIMER v6 (Clarke &

Gorley 2006). This was followed by ANOVA-like analyses to

explore the link between the scores on the ordination axes and

the stand type of the subplot in which the piece of CWD was

found. To examine any association between the positions on

the ordination diagram of the individual pieces of CWD and

their decay classes and diameters, correlation analyses were

carried out between the ordination axes scores and these vari-

ables. To improve computational efficiency, and avoid the

possibility of spurious results due to inadequate number of

records, species occurring oncewere ignored, andonly piecesof

CWDthathadfiveormoremacrofungal recordswereused. This

confined the exercise to 110 macrofungal species on 209 pieces

of CWD.

Results

Species richness of macrofungi on all woody substrates

There were 7 776 macrofungal observations on the combined

woody substrata, representing 410 species, of which 195 were

formally described and 215 were identified using ‘tag names’.

Therewere 295 species onCWD,234onODW,63onstagsand73

on livingwood.Of the total of 410 species, 308 couldbe classified

as ‘wood-preferring’ species, the rest being associated with

non-woody litter, bryophytes or soil coveringwood. Almosthalf

(153 of the 308 wood-preferring species) were recorded only

once. These were predominantly corticioid species that could

not be determined to species level. In addition, 22 species

occurred twice only and 12 species three times only, the

frequencydistributionbeinga typical ‘reverse J’ curve.Themost

commonly encountered species was an unnamed Ascomycete

“white disc bruising orange”, which was found on 139 distinct

pieces of ODW, 64 distinct pieces of CWD, and once each on

a stag and on a living tree (Table 1). The occurrence rates as

percentagesshowthat themajor substrata for virtuallyall of the

most frequently occurring species were either ODW or CWD or

the two substrates jointly (Table 1). The only exceptions were

Collybia eucalyptorum, where living trees were the most

frequently occurring substrata, and Ganoderma australe, where

stags predominated. The list of 41 most common species

contains agarics as the most frequent morphological group,

including seven species of Mycena, but other major morpho-

logical groups are also represented, such as polypores, thele-

phores, jelly fungi anddisc fungi (Table 1). At the early sampling

times, CWDandODWeach accumulates species at a rate of 4e6

times that of living trees or stags (Fig 2). None of the species

accumulation curves showed any sign of reaching a plateau or

asymptote (Fig 2). For a complete list of themacrofungal species

found in this study, see Gates (2009, Appendix 2).

Of the 2 942 macrofungal records on ODW, 2 664 records

(i.e. 90 %) were on wood that could be classified as fine woody

debris (FWD), i.e. having a diameter <10 cm. Examining the

classification FWD in place of ODWdid not lead to anymarked

changes in relationships. For example, FWDhad 225 species of

macrofungi compared with 234 for ODW.

Species assemblages on the four woody substrata

Species assemblages on the four woody substrata in each plot

were different (Fig 3). CWD and ODW overlapped to a greater

extent than any other pair of substrata, indicating that the

species assemblages are more similar on these substrata than

on any other pair of substrata. This overlap was also evident

on ordination Axis 3 (not shown). Despite the overall indica-

tion of assemblage differences, there were no indicator

species, sensu Dufrene & Legendre (1997), that could be iden-

tified to characterize each of the four substrata. Using the

macrofungal species lists on FWD in place of those on ODW



and repeating the nMDS analysis led to a similar ordination

diagram to that of Fig 3.

Polypore species occurrences on the woody substrates

Australoporus tasmanicus was the most frequently occurring

polypore species (Table 2). Fomes hemitephrus was specific to

Nothofagus, and Phellinus wahlbergii, Postia dissecta, Postia pelli-

culosa and Postia punctata were specific to E. obliqua. Except for

Postia caesia, each of the species listed in Table 2 was

encountered at least once on each wood type.

Assemblage composition on wood as a function of thevascular plant community

The CAP-CCorA routine of PERMANOVAþ (Anderson et al.

2008), applied to the ‘species by subplots’ data matrix,

established that the species assemblages on the combined

woody substrata in a subplot were highly correlated

(P< 0.0001) with the vascular plant community present in

that subplot. DISTLM, a routine that models the relation-

ship between a multivariate data cloud and one or more

explanatory variables, established that the most important

vascular plant species characterizing the differences

among the species assemblages were A. moschatum,

P. apetala and M. glauca, all with P-values of <0.0001. The

dbRDA routine visualized this result and a graph was

drawn with plotting symbols that reflected three vegetation

types of which the above species are indicative, viz. ‘Rain-

forest’, ‘Pomaderris’ and ‘Monotoca’, respectively,

combined with the plot in which the subplot occurred (see

Fig 4). The three main vegetation types were clearly sepa-

rated, but within a vegetation type, differences due to plot

were not as marked.

Table 1eMost frequently recordedwood-inhabitingmacrofungal species. Entries represent the number of distinct units ofeach wood type. Percentages of each type are in parentheses

Species binomial No. of distinct pieces of each wood type

Total pieces CWD Living ODW Stag

Ascomycete “white disc bruising orange” 205 64 (31) 1 (0) 139 (68) 1 (0)

Mycena interrupta 200 97 (49) 0 (0) 101 (51) 2 (1)

Mycena mulawaestris 155 87 (56) 1 (1) 64 (41) 3 (2)

Mycena subgalericulata 135 63 (47) 36 (27) 29 (21) 7 (5)

Armillaria novae-zelandiae 114 41 (36) 11 (10) 54 (47) 8 (7)

Psilocybe brunneoalbescens 114 57 (50) 0 (0) 53 (46) 4 (4)

Galerina patagonica 107 37 (35) 0 (0) 66 (62) 4 (4)

Bisporella “green-yellow” 100 33 (33) 0 (0) 67 (67) 0 (0)

Mycena kurramulla 96 44 (46) 0 (0) 52 (54) 0 (0)

Gymnopilus ferruginosus 87 64 (74) 2 (2) 21 (24) 0 (0)

Clavicorona piperata 83 38 (46) 1 (1) 44 (53) 0 (0)

Collybia eucalyptorum 82 32 (39) 45 (55) 3 (4) 2 (2)

Pluteus atromarginatus 75 36 (48) 1 (1) 35 (47) 3 (4)

Mycena sanguinolenta 74 41 (55) 4 (5) 26 (35) 3 (4)

Mycena carmeliana 73 38 (52) 2 (3) 32 (44) 1 (1)

Armillaria hinnulea 71 24 (34) 12 (17) 29 (41) 6 (8)

Marasmiellus affixus 67 12 (18) 0 (0) 54 (81) 1 (1)

Calocera guepinioides 65 21 (32) 0 (0) 43 (66) 1 (2)

Hypholoma fasciculare 85 46 (54) 3 (4) 34 (40) 2 (2)

Australoporus tasmanicus 61 40 (66) 3 (5) 7 (11) 11 (18)

Vibrissea dura 61 21 (34) 4 (7) 36 (59) 0 (0)

Stereum ostrea 53 15 (28) 0 (0) 36 (68) 2 (4)

Mollisia cinerea 47 31 (66) 0 (0) 14 (30) 2 (4)

Stereum illudens 46 8 (17) 2 (4) 36 (78) 0 (0)

Gymnopilus allantopus 44 8 (18) 0 (0) 35 (80) 1 (2)

Sirobasidium brefeldianum 43 9 (21) 1 (2) 33 (77) 0 (0)

Hypoxylon aff. placentiforme 42 11 (26) 0 (0) 30 (71) 1 (2)

Bisporella citrina 41 3 (7) 0 (0) 36 (88) 2 (5)

Gymnopilus tyallus 39 22 (56) 1 (3) 15 (38) 1 (3)

Hypoxylon bovei var. microsporum 39 11 (28) 1 (3) 26 (67) 1 (3)

Stereum rugosum 39 4 (10) 0 (0) 35 (90) 0 (0)

Heterotextus peziziformis 35 0 (0) 0 (0) 35 (100) 0 (0)

Hypholoma brunneum 34 24 (71) 1 (3) 9 (26) 0 (0)

Hypocrea aff. sulphurea 34 6 (18) 1 (3) 27 (79) 0 (0)

Pholiota multicingulata 34 10 (29) 2 (6) 22 (65) 0 (0)

Ganoderma australe 33 10 (30) 3 (9) 3 (9) 17 (52)

Psathyrella echinata 31 18 (58) 0 (0) 13 (42) 0 (0)

Fomes hemitephrus 30 15 (50) 3 (10) 3 (10) 9 (30)

Mycena maldea 30 14 (47) 1 (3) 15 (50) 0 (0)

Panellus stipticus 29 3 (10) 0 (0) 26 (90) 0 (0)

Phanerochaete filamentosa 29 3 (10) 0 (0) 25 (86) 1 (3)



The effect of size of CWD on species richness

Of the four measurements that reflect the size of composite

CWD (diameter, length, surface area and volume), surface area

had the highest correlation with species richness (r¼ 0.696,

P< 0.0001). Decay class was marginally and negatively associ-

ated with richness (r¼�0.078, P¼ 0.0256), and the square of

decay class, included to allow for the possibility of a maximum

in richness at an intermediate decay stage, was non-significant

(P> 0.05). Percentage bryophyte cover was also non-significant

(P> 0.05). In a forward stepwise regression, after inclusion of

surface area in the first step (R2¼ 0.484), the remaining size and

decay class variables increased the explained variation only to

R2¼ 0.523. As surface area was the most influential variable, it

was investigated further. Using percentages to remove the

effect of unequal numbers of pieces of CWD in each surface

area class, the larger the surface area, the greater the number of

macrofungal species (Fig 5). For example, for CWDwith surface

area>50m2, ca. 60 % of the CWDhadmore than 10 species and

none had less than four species, whereas themajority of pieces

of CWD <5 m2 had three or less species.

Species assemblages of macrofungi on CWD

There was a clear separation of the ‘Rainforest’ and ‘Monotoca’

types on the three axes of the nMDS ordination, with ‘Poma-

derris’ somewhat intermediate (Fig 6). Significant separations

(P� 0.01 or less) were obtained on each axis, with the mean for

‘Rainforest’ being significantly different from ‘Monotoca’ in

each case, with ‘Pomaderris’ occupying an intermediate posi-

tion (Table 3). In addition, CWD diameter was significantly

correlated (P� 0.0001) with the ordination scores from Axes 1

and 2, and CWD decay class was significantly correlated

(P� 0.01) with the ordination scores from Axes 2 and 3.

Discussion

Species identification and richness

Approximately 50 % of all the macrofungi species recorded on

wood could be identified to species level, agreeing with other

ecological macrofungal studies in Australia, which have

a range from 39 to 51 % of all species able to be formally iden-

tified (Robinson & Tunsell 2007). The exceptionally large

number (i.e. 410) of wood-inhabiting species are due in part to

themild climatic conditions conducive to fruit body emergence

for most of the year in Tasmania, which enabled macrofungal

surveying to be carried out on a fortnightly basis. The forest

type produces large amounts of dead wood (Woldendorp &

Keenan 2005; Gates 2009), predominantly from eucalypts,

available to support large numbers of wood-inhabiting fungi.

Resupinate fungi, generally omitted from Australian studies

(apart from Fryar et al. 1999) because Australia lacks taxono-

mists who specialize in their identification, were included in

this study and may have contributed to the higher numbers of

wood-inhabiting macrofungi recorded.

Wood size and species richness

Most Northern Hemisphere studies have concluded that decay

and diameter class of individual logswere the best explanatory

variables for species richness (e.g. Nakasone 1993; Kuffer &

Senn-Irlet 2005). Høiland & Bendiksen (1996) determined that

long logs with a high degree of decay have the greatest species

diversity but surface area was not considered in their analyses.

In the present study, it was found that surface area was the

most important size variable influencing species richness. A big

log presenting a large surface area has a higher chance of being

colonized by fungal spores and advancing mycelial strands

(rhizomorphs) than a small log. Species that produce large fruit

bodies require a large spatial domain (Rayner & Boddy 1988).

Commonly, these species are the heart-rot fungi that are

dependent on a long and diverse infection history (Heilmann-

Clausen & Christensen 2004) and are therefore usually

confined to fruiting onold, large diameter trees and the ensuing

CWD. On the other hand, fungi with small fruit bodies and that

0

50

100

150

200

250

300

0 5 10 15 20 25 30

Visit number

se

ic

ep

sf

o.

oN

CWD

ODW

Stags

Living trees

Fig 2 e Randomized species accumulation curves for the

four categories of wood, with data pooled over four plots

(1 ha area).

nMDS, all plots combined, stress=0.12

-2

-1

0

1

2

-2 -1 0 1 2

Axis 1

2 si

xA

CWD

ODW

Stags

Living trees

Fig 3 e The first two axes of a 3D nMDS ordination

(stress[ 0.12) on species assemblage data, using pooled

data from the four plots combined. Each point depicts

one of the 30 visits to the total area of 1 ha.



occupy a small spatial domain are able to colonize wood of

small or large diameter. For example, Vibrissea dura and Asco-

mycete ‘white disc bruising orange’ were commonly found on

very largeCWD(up to260 cmindiameter) but also on fragments

of dead wood.

The number of species supported by CWD was not very

different to that supported by ODW, and all the commonly-

occurring species were found on both substrata (see Table 1).

The CWD cut-off point of 10 cm diameter is arbitrary and is of

less ecological importance than other variables, e.g. tree

species. Non-uniform shapeswill have a different surface area

per unit volume in contact with or close to the soil (depending

-40

-30

-20

-10

0

10

20

30

-30 -20 -10 0 10 20 30 40

Axis 1

2si

xA

'Old Growth' Rainforest

'1898' Pomaderris

'1898' Rainforest

'1934' Monotoca

'1898/1934' Pomaderris

Fig 4 e dbRDA graph of best DISTLM model, the points

representing the macrofungal species assemblages of 88

subplots in five vegetation groups that combine vegetation

type with plot of occurrence.

Fig 5 e Species richness vs. surface area of CWD, expressed

as the percentage of the number of pieces of wood in each

surface area category.

Table

2e

Main

non-resu

pin

ate

polypore

species,

withro

ttype,habitatandsu

bstra

tum

inform

ation

Fungalsp

ecies(w

ithitsassociatedro

ttype)

No.ofdistinct

piece

sofwood

Habitatin

whichsp

ecies

wasfound

No.ofdistinct

piece

sofeach

woodtype

CW

DODW

Stags

Livingtrees

Australoporustasm

anicus(w

hiteheart

rot)

61

Old

forestsoronlegacy

logs

inyoungerforests

40

711

3

Fomes

hem

itep

hrus(w

hiteheart

rot)

30

Old

forestsoronlegacy

logs,

exclusiveto

Nothofagu

s

15

39

3

Ganod

ermaaustrale

(whiteheart

rot)

34

Old

forests,

onNothofagu

sandE.ob

liqua

10

318

3

Phellinuswahlbergii(w

hiteheart

rot)

16

Old

forestsorlargediameterliving

treesin

youngerforests,

onE.ob

liqua

32

110

Postiacaesia

(bro

wncu

boidalheart

rot)

14

70e110yrandold

forests

59

00

Postiadissecta(bro

wncu

boidalheart

rot)

26

70e110yrandold

forests,

onE.ob

liqua

17

33

3

Postiapellicu

losa

(bro

wncu

boidalheart

rot)

20

70e110yrandold

forests,

onE.ob

liqua

14

11

4

Postiapunctata

(bro

wncu

boidalheart

rot)

13

70e110yrandold

forests,

onE.ob

liqua

53

14



on their shape) and are likely to be invaded differently by

invertebrates and soil-borne fungal mycelium. Because of its

small diameter, FWD (virtually synonymous with ODW in this

study) decays more quickly than large diameter wood (Stone

et al. 1998; Tarasov & Birdsey 2001), exists in each decay

class for a short time only, and did not have the array of decay

classes exhibited by CWD in the present study. In addition,

FWD is more susceptible to the effects of extremes of

temperature and moisture. The effuse fruit bodies of most

corticioid fungi do not require a large spatial domain. Thus,

they are able to occupy the ecological niche provided by small

diameter wood (Junninen et al. 2006). Furthermore, the fruit

bodies of many corticioid species often show some anatom-

ical feature that are an adaptation to desiccation and rehy-

dration as a result of inhabiting a substratum prone to such

conditions (Rayner & Boddy 1988; Nunez & Ryvarden 1997).

Thin, filmy species, e.g. Peniophora spp., show a rapid

resumption of activity under moist conditions (Rayner &

Boddy 1988). They occupy a very thin part of the wood so

that the whole life cycle from latent infections to fructifica-

tions may be quite rapid, a significant survival strategy for

taking advantage of suitable conditions. Comparatively, CWD

offers a more stable environment for fungal growth, and

would be favored by those fungi with larger fruit bodies that

take a longer time to develop, especially in drier conditions

(Amaranthus et al. 1989).

The effect of wood attributes on species richness

Species richness, as measured by total species numbers, was

scarcely affected by decay class (DC) in this study. This is in

contrast to other studies that have found that decaying wood

in DC3eDC4 supports more species fruiting (e.g. Renvall 1995;

Høiland & Bendiksen 1996; Edmonds & Lebo 1998; Heilmann-

Clausen & Christensen 2003). Edmonds & Lebo (1998)

revealed that whilst most species of the fruiting fungi were

on DC3 logs, most of the 47 logs in their study were also in

DC3. No attempt was made to adjust for this factor in their

results. More convincing results were obtained from a study of

465 conifer logs by Høiland & Bendiksen (1996). That study

found that long logs in a high decay class had the greatest

species diversity and they concluded that the number of

species increased both with increasing degree of decay and

size of log. Renvall (1995) studied a total of 844 conifer logs and

recorded 166 species of wood-inhabiting basidiomycetes. He

suggested that the increase in species numbers from his

DC1eDC4 reflected an increase in the number of available

niches during wood decay as the decomposition process

changed the chemical and physical properties of the wood.

Although Heilmann-Clausen & Christensen (2003) found that

their DC3 had the greatest species richness, they restricted the

70 logs of their study to have a minimum diameter of 70 cm,

making it unwise to compare that study to the present study

which used a 10 cm minimum diameter.

Few fungi were associated with a particular decay class. In

fact, several species of Mycena (in particular M. interrupta) and

the ascomycete ‘white disc bruising orange’, were found

across the different decay categories, which echoes von Runge

(1975) that there is no strict boundary between fungal groups

of allied decay classes and that the same species can be found

Fig 6 e nMDS ordination diagram (stress[ 0.11) for 110

macrofungal species found on 209 pieces of CWD, with

plotting symbols chosen to reflect the stand type of the

subplot in which each piece of CWD was found.

Table 3 e Ordination axis means for four vegetationtypes, that result from an nMDS on 209 pieces of CWDcontaining 110 macrofungal species (see Fig 6)

Vegetationtype

No. ofpieces ofCWD

Axis 1 Axis 2 Axis 3

‘Monotoca’ 39 0.312a �0.178b 0.208a

‘Pomaderris’ 50 0.133ab �0.038ab 0.089ab

‘Unclassified’ 47 0.0160b �0.070b �0.025bc

‘Rainforest’ 73 �0.269c 0.167a �0.157c

P-value for

ANOVA

<0.0001 0.0086 0.0007

Note: For each axis separately, means sharing a common letter are

not significantly different at the P¼ 0.05 significance level,

following an ANOVA test.



on wood of several decay stages. In the current study, four

species of the fleshy, soft-bodied genus Pluteus were associ-

ated with wood in the later decay stages, although there were

also a few records on wood of lower decay stages. Fukasawa

et al. (2009) suggested that while the association of Pluteus

spp. for well-decayed wood may be due to the wood’s high

water content, the wood-degrading abilities of Pluteus spp.

have not yet been revealed. Soft-bodied species of Entoloma

and Hygrocybe that are usually found on soil were able to

inhabit wood in the late stages of decay, as the decaying wood

becamemore humus-like. There was no species that could be

described as strictly indicative of any decay class. Decay is

a combination ofmany factors including the amount of fungal

resistant compounds (e.g. tannins) present in the wood,

infection sites and decay trajectories. These factors are

affected by wood species and climatic conditions which are

different in the Northern Hemisphere studies described above

to the current study. The CWD in the current study was not

monospecific, originating from rainforest species such as

A. moschatum, N. cunninghamii and E. lucida, as well as from

E. obliqua, Acacia spp. and P. apetala. This may have contrib-

uted to the differences between the results of this study and

those that found that decay class was correlated with species

richness.

Macrofungal assemblage composition reflects stand type

There is a firm indication of the importance of the underlying

vascular plant vegetation in influencing the macrofungal

species assemblages thatwere found in each of the 88 subplots

that could be assigned to one of three major vegetation types.

The best DISTLM model, which related the resemblance

matrix (obtained from the macrofungal species lists) to the

abundances of the tree species A. moschatum, P. apetala andM.

glauca in the subplots, showed a clear separation of the vege-

tation types. The partial overlap within the ‘Pomaderris’ type

of the points representing subplots from the ‘1898’ plot with

those from the ‘1898/1934’ plot, and the partial overlap within

the ‘Rainforest’ type of the points representing subplots from

‘1898’ with those from ‘Old growth’, suggest that the under-

lying vegetation may strongly determine the wood-inhabiting

macrofungi in the subplots. This result reflects, to some extent

at least, the local site factors such as rainfall, landform, aspect,

soil type, etc. that help to determine which macrofungal

species are present.

A further opportunity to observe the effect of the

underlying vascular vegetation was provided by the mac-

rofungi recorded on pieces of CWD during 30 repeated visits

over the period of 14 months. The unconstrained ordination

diagram (Fig 6) and subsequent ANOVA-like analyses

(Table 3) strongly suggest a linkage between subplot vege-

tation and the macrofungal species assemblages, the

greatest contrast being between the ‘Monotoca’ and ‘Rain-

forest’ types, with the ‘Pomaderris’ type being intermediate.

It would, of course, have been best if the species identity of

each piece of CWD had been known, but to identify 814

pieces of CWD would have been too time-consuming and

too costly a task, requiring expert skills in wood fiber iden-

tification, or molecular work. Nevertheless, the link

between the underlying vascular vegetation and the

macrofungal assemblages implied by the results obtained

here, from the ordination procedure, suggests that cata-

loguing the standing vegetation may be a useful surrogate to

identifying each piece of fallen wood. This is not to suggest

that stand type totally determines the macrofungal

composition, as correlation analysis showed that CWD

diameter was significantly correlated with the ordination

scores from Axes 1 and 2 of Fig 6. Also, species richness is

strongly associated with CWD surface area, to which

diameter contributes, so it is possible that diameter may

have some explanatory role for species assemblages.

Furthermore, CWD decay class may also be a predictor, as it

was correlated with the ordination scores from Axes 2 and 3

of Fig 6. Note that in the previous section we dismissed the

possibility of a significant contribution of CWD decay class

to species richness, but that does not preclude decay class

as a factor in determining species assemblages. The most

likely scenario is one in which all of these factors, viz.

vegetation type, diameter (and other size components) and

decay class play a role in influencing the macrofungal

composition.

A preference for wood size or wood species?

A high proportion of the small diameter wood in the ‘1898’

and ‘1898/1934’ plots was of P. apetala origin, this species

being present either as dead wood or as living trees and only

in these two plots. Junghuhnia rhinocephala, J. nitida, Steccher-

inum ochraceum and Polyporus gayanus were confined to

P. apetala. Although in Patagonia P. gayanus occurs only on

Nothofagus (Cwielong & Rajchenberg 1995), it is not host

specific in Tasmania as it has been reported on eucalypt

(Ratkowsky & Gates 2002) and isolated from E. obliqua

(Hopkins 2007). The early colonizer Chondrostereum purpur-

eum (Rayner & Boddy 1988; Andersen & Ryvarden 1999) was

also only found on Pomaderris present in the ‘1898’ plot of the

current study. Similarly, it has been confined to this tree

genus in other surveys in Tasmania with one record from an

apricot tree, although May & Simpson (1997) list it as

a common wood-rotter of eucalypt. Knowledge of the

ecology of the macrofungi found on P. apetala and the

properties of P. apetala wood are limited, so it is difficult to

know which of the two factors, wood size or wood species, is

the major driver for the fungal community. Some species of

fungi have been shown to prefer corticated and others

decorticated wood (Renvall 1995). The physical and chemical

barriers of the bark can affect colonization (Boddy &

Heilmann-Clausen 2008). P. apetala has a very thin, smooth

bark compared to E. obliqua and may present a more favor-

able surface for colonization by spores. Most of the P. apetala

wood was in a low decay stage, which further complicates

an interpretation of the factors affecting the fungal

community. However, in the present study P. apetala wood

provided a substratum for 85 species and increased the

diversity of wood-inhabiting macrofungi (33 species were

found only on P. apetala). This is similar to the situation in

a beech (Fagus sylvatica) forest (Holec 1992) where the small

admixture of spruce (Picea) and fir caused a considerable

increase in the number of species even though the amount

of beech wood in the plots was always higher.



Potential indicator species of stand age

Fruit bodies of most polypores are large and clearly visible,

often with very specialized habit requirements (Renvall 1995;

Lindblad 1998) and make for an excellent group on which to

focus ecological studies and to study the effects of forestry (see

Norstedt et al. 2001; Sippola et al. 2001, 2005; Christensen et al.

2004; Junninen et al. 2006). Although it could be argued that

the relatively low number of polypore species in Tasmania

perhaps precludes them from being the focal point of a study, it

is possible that individual species can reflect habitat changes

(see Stokland & Kauserud 2004). The fact that A. tasmanicus, F

hemitephrus and P. wahlbergii in the current study were found

fruiting either in older stands or on biological legacies (i.e. large

diameter living trees or legacy logs that had escapedwildfire) in

younger stands suggests that these three polyporoid species

may be restricted to old trees and old forests. Such forests are

considered crucial for biological conservation, as numerous

studies have shown that they provide refugia for species

sensitive to modern forestry methods.

Conclusions

This study found that: (1) the four woody substrata supported

different, but to some degree, overlapping wood-inhabiting

macrofungi; (2) macrofungal species richness on CWD was

affected by surface area; (3) dead wood of all sizes and in all

stages of decay supported a large and diverse assemblage of

saproxylic macrofungal species, making it important to

maintain an array of dead wood in different sizes and decay

classes in native wet eucalypt forest; and (4) the ‘Pomaderris’,

‘Rainforest’ and ‘Monotoca’ forest types had significantly

different macrofungal species assemblages both on the

combined woody substrata and on CWD, which may reflect

the influence of their different stand compositions.

Although wood in the wet E. obliqua forests of southern

Tasmania supports very diverse macrofungal assemblages,

the true diversity of all higher wood-inhabiting fungi, as

defined by Webster (2007), is still unknown. The results of the

present study represent a snapshot in the lifetime of these

forests, providing benchmark data on wood-inhabiting fungi.

These data can be used in more extensive wide-ranging

studies to investigate the effects of decreasing areas of old

native forests and the large-scale reduction in the amount of

dead wood due to natural disturbance such as wildfire, land

clearing for agriculture and urban development, and intensive

forest management.

Acknowledgements

Financial and logistic support for the field work was provided

by Forestry Tasmania. One of the authors (GMG) received

additional financial support from an Australian Postgraduate

Award, the Holsworth Wildlife Endowment Fund, the Coop-

erative Research Centre (CRC) for Forestry, CSIRO Sustainable

Ecosystems and the Bushfire CRC. The Schools of Agricultural

Science and Plant Science of the University of Tasmania

provided additional logistic support. We thank reviewer Jenni

Hottola, an anonymous reviewer, and Editorial Board Member

Jacob Heilmann-Clausen for their useful comments on an

earlier version of the manuscript.

Supplementary data

Supplementary data associated with this article can be found

in the online version, at doi:10.1016/j.funeco.2010.07.005.

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