Diversity and habitat relationships of hypogeous fungi. I. Study design, sampling techniques and general survey results

Abstract

Hypogeous fungi are a large yet unknown component of biodiversity in forests of south-eastern mainland Australia. To better define their diversity and habitat relationships, we identified and counted fruit-bodies at 136 study sites sampling the climatic, geological and topographic features of the region. In one year 7451 fruit-bodies representing 209 species were collected in an autumn and spring sampling period. Only 57 of these species were previously described. Within genera, the number of species ranged from 1 to 21. Sites sampled in autumn averaged higher diversity of species and greater number of fruit-bodies than the same sites sampled in spring. Most major taxa occurred at more sites in autumn than in spring, whereas a few occurred more frequently in spring than in autumn. These patterns are consistent with those identified in previous smaller studies and likely reflect seasonal changes in soil moisture and temperature levels. Subsequent papers will explore factors influencing the occurrence, relative abundance and numbers of species of hypogeous fungi at the study sites and their community structure and possible host–plant relationships.

Full text

Biodiversity and Conservation 9: 151–173, 2000.
© 2000 Kluwer Academic Publishers. Printed in the Netherlands.
Diversity and habitat relationships of hypogeous fungi.
I. Study design, sampling techniques and general
survey results
ANDREW W. CLARIDGE1,4,∗, STEVEN J. CORK2and JAMES M. TRAPPE2,3
1Centre for Resource and Environmental Studies, The Australian National University, Canberra ACT
0200, Australia; 2C.S.I.R.O. Division of Wildlife and Ecology, G.P.O. Box 284, Canberra ACT 2601,
Australia; 3Department of Forest Science, Oregon State University, Corvallis, OR 97331-5752, USA;
4Present address: New South Wales National Parks and Wildlife Service, Threatened Species Unit,
Southern Directorate, P.O. Box 2115, Queanbeyan, New South Wales 2620, Australia; ∗Author for
correspondence (fax: +61-2-6299-4281; e-mail: andrew.claridge@npws.nsw.gov.au)
Received 15 January 1999; accepted in revised form 7 June 1999
Abstract. Hypogeous fungi are a large yet unknown component of biodiversity in forests of south-eastern
mainland Australia. To better define their diversity and habitat relationships, we identified and counted
fruit-bodies at 136 study sites sampling the climatic, geological and topographic features of the region.
In one year 7451 fruit-bodies representing 209 species were collected in an autumn and spring sampling
period. Only 57 of these species were previously described. Within genera, the number of species ranged
from 1 to 21. Sites sampled in autumn averaged higher diversity of species and greater number of fruit-
bodies than the same sites sampled in spring. Most major taxa occurred at more sites in autumn than in
spring, whereas a few occurred more frequently in spring than in autumn. These patterns are consistent
with those identified in previous smaller studies and likely reflect seasonal changes in soil moisture and
temperature levels. Subsequent papers will explore factors influencing the occurrence, relative abundance
and numbers of species of hypogeous fungi at the study sites and their community structure and possible
host–plant relationships.
Key words: Australia, forests, fungi, hypogeous, mycorrhizae
Introduction
Australia is well known for its nutrient-poorsoils. To compensate, most forest plants
form mycorrhizal symbioses with a range of fungi that take nutrients and water from
the soil and translocate these to the host plant. The fungus receives carbohydrates,
vitamins and other photosynthates from the host (i.e. Malajczuk et al. 1975; Smith and
Read 1997). Many mycorrhizal fungi produce hypogeous (underground) sporocarps
(spore-laden fruit-bodies) which are dug up and consumed primarily by ground-
dwelling mammals, which then defecate the spores. Spore dispersal of hypogeous
fungi is presumably achieved mainly in this way (Maser et al. 1978; Johnson 1994a).
In Australian temperate forests the most important spore dispersers are potoroos, ban-

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dicoots, native rodents and bettongs, some of which are considered rare or threatened
(Claridge and May 1994). Successful conservation of these fungus-dependentspecies
will depend, in part, on better understandingthe diversity and habitat requirementsof
their fungal food resources. Moreover, interactions among mycophagous (fungus-
feeding) animals, fungi and their mycorrhizal host plants are thought to contrib-
ute importantly to the ecological sustainability and long-term productivity of forest
ecosystems (Maser et al. 1978).
The mycophagous habits of mammals in Australia have been well documented
over the past three decades (Claridge and May 1994). Little is known, however, about
the habitat requirements of hypogeous fungi.Two recent studies have investigateden-
vironmental influences on the fungi over limited areas (Claridge et al. 1993a; Johnson
1994b), but larger-scale studies are needed to allow robust prediction of the relative
importance of different forest habitats for these fungi. In particular, the impacts of
increasing fragmentation of forests through clearing of vegetation need to be under-
stood, as well as the influence of timber harvesting and fires, because all of these
potentially affect dispersal and survival of fungi and in turn that of the animals that
consume them.
Our study had three primary aims: (1) to improve understanding of the broad-scale
distribution of hypogeous fungi in south-eastern mainland Australia; (2) to identify
features of habitat that influence the occurrence, diversity and abundance of different
taxa of hypogeous fungi by species within a given geographic area; and (3) based
on identification of these important factors, identify potential effects of logging and
fire on the distribution of fungal taxa. To achieve these aims, we sampled fruit-bodies
of hypogeous fungi at 136 environmentally stratified study sites, and analysed the
distribution of some of the more commonly recorded taxa and the overall number of
species in relation to measured macro- and micro-scale habitatvariables. In this paper
we describe the study area, the selection of field sites and methods for censusing hy-
pogeous fungi. The range of taxa encountered during these surveys is listed, together
with basic information on seasonal differences in their fruiting. Subsequent papers
will explore factors related to the occurrence,relative abundance and diversity of the
fungi at these sites, and community structure and possible host–plant relationships
among various taxa (see Claridge et al. 1999).
Methods
General study area
The study was established within the eastern part of Victoria (East Gippsland) and ad-
jacent south-eastern New South Wales (Figure 1) because the general environmental
features and hypogeous fungi were relatively well documented(Beaton et al. 1985a;
Bougher and Castellano 1993;Castellano and Trappe 1990, 1992a,b;Castellano et al.

153
Figure 1. Map illustrating extent of study area.
1992; Stewart and Trappe 1985; Trappe 1975; Trappe et al. 1992a,b, 1996a,b; Lebel
1998). The area included a range in soil types and climate, and its forests are used
for biodiversity conservation, recreation and timber production (Land Conservation
Council 1985; Richards et al. 1990).
More specifically, the study area formed a rectangle of approximately 32 281 km2
bounded by the longitudes 147◦300E and 150◦00E, and latitudes 36◦300Sand
38◦00S, encompassing major regions such as the Gippsland Lakes and surrounding
hinterland, north-eastern Alpine Victoria, far East Gippsland, the southern part of
the Monaro Tablelands, and the coast and adjacent escarpment of far south-eastern
New South Wales (Richards et al. 1990). Environmental features (i.e. climate, geo-
logy, flora, fauna and history of human land use) of various portions of it have been
reviewed at length by Richards et al. (1990), Department of Conservation, Forests
and Lands (1991), Lugg et al. (1993) and Department of Natural Resources and
Environment (1995).
Strategy for selecting field sites
Our site selection strategy took account of climate, geology (substrate) and topo-
graphic features of the study area. These have been shown to influence patterns in
the occurrence of various plants and animals (see Margules et al. 1987; Austin and
Heyligers 1989; Neave et al. 1996; Catling and Burt 1995a,b; Lindenmayer et al.

154
1996). Climate served as the primary stratification; a 250 ×250 m2(grid cell size)
digital elevation model (DEM) for south-eastern Australia (developed principally by
Dr M.F. Hutchinson at the Centre for Resource and Environmental Studies, Australian
National University) was linked to the climate prediction system BIOCLIM (Nix
1986; Busby 1991) to derive climatic estimates over the entire study area. These
estimates were based on long-term mean monthly climate data (precipitation and
temperature) derived from a continental network of meteorological stations. Their
accuracy is influenced by the availability of meteorological data and the accuracy of
the DEM (Adomeit et al. 1984). At the time of analysisthe estimated standard errors
were 0.5◦C for monthly mean temperature and less than 10% for mean monthly
precipitation (Hutchinson et al. 1992).
Nine different bioclimatic parameters were estimated for each 250 ×250 m2grid
cell within the DEM; annual mean temperature (◦C), maximum mean temperature
of the warmest month (◦C), minimum mean temperature of the coldest month (◦C),
annual mean moisture index (point scale of 0–1), mean moisture index of the highest
quarter (0–1), mean moisture index of the lowest quarter (0–1), mean precipitation
of the wettest quarter of the year (mm) and mean precipitation of the driest quarter
of the year (mm). A spatial estimate for runoff was generated for each grid cell
by use of the same DEM and metereological data, linked to the computer program
GROCLIM (McMahon et al. 1995). Two of these bioclimatic parameters in particu-
lar (minimum temperature of the coldest month and mean precipitation of the driest
quarter) were chosen because they are limiting factors for a wide range of organisms
(Nix and Switzer 1991; Mackey 1991; Neave et al. 1996).
A non-hierarchical clustering algorithm (ALOB) in the computer software pack-
age PATN (Belbin 1989) was used to determine a series of higher-order climate
groups, based on values for each of the nine climate parameters for each grid cell
within the study area. As part of this process, the Gower (1967) metric measure of
association (similarity) was utilised to construct climate groups, with the threshold
value set at 0.5. One sample object (grid cell), that occurring in the far south-west
corner of our study area, was set as an initial seed point (any object or grid cell
with a minimum value of the Gower metric >0.5 formed a new group). After initial
processing, the hierarchical algorithm FUSE (Belbin 1987) reduced the final number
of climate groups to 20. Thus, each grid cell within the study area was given a cli-
mate group value of between 1 and 20. The spatial pattern of these climate groups
was examined by incorporating the data generated in PATN into the Geographical
Information System ARCINFO (Figure 2). Table 1 illustrates the area (km2) covered
by each of the 20 climate groups within our study area.
Preliminary field inspection confirmed that the boundaries of each mapped cli-
mate group (1:100 000 scale) conformed fairly closely to changes in major veget-
ation communities as defined in Lugg et al. (1993). For example: (i) vegetation in
Climate Group 1 was dry sclerophyll forest dominated by brittle gum (Eucalyptus
mannifera) and red stringybark (E. macroryncha); (ii) vegetation in Climate Groups

155
Figure 2. Climate groups used to stratify field sampling for hypogeous fungi across study area.

156
Table 1. Area (km2) of different climate groupsawithin the study area.
Climate group Area (km2) Climate group Area (km2)
1 606.19 11 546.63
2 762.31 12 352.06
3 444.75 13 3012.81
4 486.75 14 5340.69
5 3305.69 15 1437.94
6 373.31 16 2546.69
7 93.56 17 246.81
8 1213.88 18 3500.69
9 1962.94 19 4115.19
10 1760.56 20 171.50
aClimate groups were differentiated by use of PATN, a computer software
package developed for manipulation, analysis and display of pattern in
multi-variate biological data. Climate groups were based on the values for
each of 9 key climate parameters for each grid cell within our study area.
See text for more information.
6 and 8 was alpine woodland dominated by snow gum (E. pauciflora), mountain gum
(E. dalrympleana) and black sallee (E. stellulata); and (iii) vegetation in Climate
Group 15 was tall wet sclerophyll forest, dominated by either mountain ash
(E. regnans), brown barrel (E. fastigata), or mountain gum (E. dalrympleana).
Stratification based on substrate
The study sites were also stratified by features of the substrate, because at smaller
scales the distribution and relative abundance of hypogeous fungi can be influenced
by changes in soil texture and chemistry (Johnson 1994b). As no soil maps exis-
ted for the study area we looked to geological information. This existed mainly in
hard-copy form as a 1:100000 scale database held by the C.S.I.R.O. Division of
Forestry (Dr Phil Ryan, unpublished data) but was supplemented where necessary
by hard-copy 1:250000 geological maps held by the Victorian and New South Wales
Geological Surveys, respectively (Bairnsdale SJ 55-7; Bega SJ 55-4; Mallacoota SJ
55-8; Tallangatta SJ 55-3). Given the disparity in the scale at which geology had been
mapped across our study area, and its complexity, the total number of geological
classes was reduced to a set of 7, within which the characteristics of the associated
soils were expected to be similar (Table 2). For example, soils developing on Qua-
ternary Sediments were typically deep sandsof poor fertility with little to no horizon
differentiation, and soils developing on Ordovician sediments were typically reddish-
brown, duplex, and of moderate fertility (Lugg et al. 1993). Sites on limestone or
basalt were omitted, because they occurred on little of the total area and mostly had
been cleared for agriculture.
Of the 140 possible climate group-geology combinations, 78 were represented
within the study area. Three of these occurred on cleared land and 20 were not readily

157
Table 2. Artificial geological classes used as part of the site stratification process (source Lugg et al.
1993).
Approximate age
Geological class Rock type (million years)
Devonian sediments Conglomerate, mudstone, sandstone and shale 390
Devonian volcanics Rhyolites and rhyodactites 390
Granitics Diorites, granites and granidiorites 380–500
Metamorphic sediments Gneisses and schists 500
Ordovician sediments Slate, siltstone, mudstone, sandstone and quartzite 500
Tertiary sediments Sand, gravel, ironstone and conglomerate 5
Quaternary sediments Silt, sand, mud and sand dunes 2–present
accessible year-round so were not considered for sampling. Given the time required
for sampling hypogeous fungi and the need to impose other forms of stratification
into our survey strategy (see immediately below), we reduced the sample of climate
group–geology classes to 24 (Table 3).
Stratification based on topography
As a final level of stratification, four major topographic positions were located within
each of the 24 climate group–geology classes identified for sampling: (i) ridge/upper
slope, (ii) sheltered slope, (iii) exposed slope, and (iv) gully/lowslope. Previous work
indicated that different suites of fungi preferentially occupied different micro-topo-
graphies and aspects within forested catchments (Claridge et al. 1993a). Combining
climate group–geological class combinations with the four categories of topography
produced a set of 96 sample sites. For the 10 most widely distributed climate group–
geological classes, we replicated sites in each of the topography categories, produ-
cing an additional set of 40 sites. In the field, where possible, these were located
in non-overlapping patches of climate group–geological class. Thus, 136 sites were
designated for sampling (Table 3).
Field site location
Where possible, sites were at least 500 m apart to allow collection of independent
data. To minimise heterogeneity with respect to vegetation and other environmental
features, the dimensions of each site were restricted to a 50 ×20 m2rectangle with
the long axis aligned along the elevation contour. Where possible, sites without recent
evidence of logging were chosen, because previous studies had shown that in at least
the first few post-disturbance years the diversity and relative abundance of hypogeous
fungi may be altered (Vogt et al. 1980; Malajczuk and Hingston 1981; Reddell and
Malajczuk 1984; Luoma et al. 1991; North et al. 1997; Kropp and Albee 1996). In
the field, selected sites were marked with steel star-pickets (centre-point of each plot)

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Table 3. Distribution of the 136 study sites in relation to climate groups and
geological classes.
Climate group Geological class ReplicatesaNo. sitesa
1 Ordovician sediments 1 4
3 Ordovician sediments 1 4
5 Granitics 2 8
5 Ordovician sediments 1 4
6 Devonian volcanics 1 4
8 Metamorphic sediments 1 4
8 Ordovician sediments 1 4
8 Devonian volcanics 2 8
9 Ordovician sediments 1 4
13 Quaternary sediments 1 4
13 Ordovician sediments 1 4
14 Ordovician sediments 2 8
14 Tertiary sediments 1 4
15 Ordovician sediments 2 8
15 Devonian volcanics 1 4
16 Granitics 2 8
16 Metamorphic sediments 1 4
18 Quaternary sediments 2 8
18 Granitics 2 8
18 Ordovician sediments 2 8
18 Tertiary sediments 2 8
19 Devonian sediments 2 8
19 Granitics 1 4
20 Granitics 1 4
aWithin each combination of climate group–geological class we selected sites
in 4 major micro-topography categories. Hence, for each of those combinations
sampled only once, there were 4 sites. For 10 of the more widely distributed
combinations of climate group-geological class, we replicated sites in each of the
topography categories. For these ‘replicated’ combinations there were 8 sites.
and fluorescent flagging tape. The location and elevation of each site were determined
from fine-scale (1:25 000) topographic maps.
Measurement of micro-habitat (on-site) attributes
Several micro-scale (on-site) habitat attributes were recorded for each site, including
measurements of (i) features of topography (slope position, steepness of slope and
aspect), (ii) disturbance history (years since last fire and presence/absence of cut
stumps), (iii) vegetation floristics and structure (emphasising presence and relative
abundance of potential host-plant species), (iv) structure of non-living componentsof
habitat (i.e. standing dead trees, fallen trees and leaf litter layer) and (v) substrate (soil
moisture, texture and nutrient status). These will be outlined in detail in a subsequent
paper on factors influencing occurrence, numbers of species and abundance of the
fungi (Claridge et al. 1999).

159
Sampling hypogeous fungi
Previous studies of the distribution and abundance of hypogeous fungi have been
based on collection of fruit-bodies by raking or excavating and sieving soil from
relatively small, systematically located plots within a study site. This can take several
hours per site and requires many replicate plots to estimate fruit-body abundance
with acceptable precision, because the fungi are patchily distributed and the chances
of finding no fruit-bodiesin small plots is high. To allow sampling of a large number
of sites in an acceptable time, a time-constraint sampling approach was developed.
Each of the 50 ×20 m2plots at the 136 sites was sampled for the same number of
person minutes. Workers sampled by raking as deep as 15 cm with a 4-tined garden
cultivator (Castellano et al. 1989) and were instructed to sample as many different
micro-habitats as possible within the time available. Specimens were collected as
revealed by raking, then identified as described below, counted by species, dried
and later weighed in the laboratory. This method was expected to provide reliable
estimates of species occurrence and diversity and crude estimates of relative numbers
and standing-crop biomassby species and by site.
The person-minutes required to census the range of species fruiting at any given
time in a plot of known dimensions were determined in earlier field trials. In late-
April and early-May 1996 we established fifteen 25 ×20 m2plots across a range
of major forest/woodland types in the Brindabella Ranges near Canberra (Australian
Capital Territory) and Tallaganda State Forest (adjacent southern New South Wales).
The forest types sampled were (i) snow gum (E. pauciflora) – narrow-leaved pep-
permint (E. radiata) – mountain gum (E. dalrympleana) woodland, (ii) brown barrel
(E. fastigata) – monkey gum (E. cypellocarpa) forest, (iii) alpine ash (E. delegatensis)
forest, (iv) broad-leaved peppermint (E. dives) – brittle gum (E. mannifera)forest,
and (v) ribbon gum (E. viminalis) riverine forest, all of which also occurred within
the major study area.
Within each plot, two people sampled for hypogeous fruit-bodies in the array
of available micro-habitats by raking for 10 consecutive 5-min periods. Each timed
census was standardised by an electronictimer with an alarm. The number of species
recovered in each 5 min census was tabulated against time spent searching. In 13 of 15
sites (87%) the full complement of species fruiting were sampled in the first 25 min
or less (50 person-min) (Table 4). At that stage disturbance was estimated at between
10 and 20% of the surface area of the entire plot, a level considered acceptible in
terms of a return to the plot for repeat censusing. In the other two plots it took 60
and 90 person-min, respectively, to record all species. However, in both cases only a
single species was detected after 50 person-min of sampling, despite more extensive
disturbance to the plots.Based on these results, the 50×20 m2plots used in the main
survey (twice the size of those used in the pilot study) were sampled for 100 person-
min. This allowed all 136sites to be sampled in 2.5 weeks, short enough to minimise

160
Table 4. Number of additional species of hypogeous fungi collected in relation to sampling effort (min) within 25 ×20 m2plots placed in 15 eucalypt forest
sites.
Time spent sampling (min)
Site no. 0–5 6–10 11–15 16–20 21–25 26–30 31–35 36–40 41–45 46–50 Species Samples % Species
1 1 (1) 3 (4) 3 (5) 2 (3) 0 (0) 0 (1) 0 (3) 0 (0) 0 (3) 0 (1) 9 21 100
2 3 (3) 3 (5) 0 (1) 0 (0) 1 (2) 0 (0) 0 (4) 0 (2) 0 (2) 0 (0) 7 19 100
3 3 (3) 1 (1) 3 (5) 1 (4) 2 (2) 0 (2) 0 (2) 0 (4) 0 (1) 0 (0) 10 24 100
4 1 (1) 2 (2) 2 (4) 0 (0) 1 (1) 1 (3) 0 (3) 0 (0) 0 (0) 0 (0) 7 14 86
5 1 (1) 2 (2) 1 (1) 0 (0) 1 (1) 0 (4) 0 (2) 0 (1) 0 (0) 0 (0) 5 12 100
6 0 (0) 1 (1) 0 (1) 1 (1) 2 (2) 0 (1) 0 (1) 0 (0) 0 (1) 0 (1) 4 9 100
7 0 (0) 1 (1) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 1 1 100
8 2 (2) 3 (5) 0 (0) 0 (1) 0 (0) 0 (1) 0 (0) 0 (0) 0 (0) 0 (0) 5 9 100
9 1 (1) 0 (1) 0 (0) 0 (0) 0 (0) 0 (1) 0 (0) 0 (0) 0 (2) 0 (2) 1 7 100
10 0 (0) 0 (0) 0 (0) 0 (0) 1 (1) 0 (0) 0 (0) 0 (0) 0 (1) 0 (0) 1 2 100
11 1 (1) 1 (1) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 2 2 100
12 0 (0) 0 (0) 1 (1) 0 (1) 3 (3) 0 (0) 0 (1) 0 (0) 1 (1) 0 (2) 5 9 80
13 2 (2) 0 (0) 0 (1) 0 (0) 2 (4) 0 (1) 0 (1) 0 (3) 0 (2) 0 (1) 4 15 100
14 1 (1) 2 (2) 1 (1) 1 (2) 2 (4) 0 (4) 0 (4) 0 (6) 0 (2) 0 (1) 7 27 100
15 2 (2) 1 (3) 1 (2) 1 (1) 0 (0) 0 (2) 0 (2) 0 (1) 0 (2) 0 (1) 5 16 100
Number in brackets ( ) refers to number of samples collected during each time interval. % Species = percentage (%) of total species found within the first
25 min of sampling.

161
effects of weather on the production of hypogeous fruit-bodies across the study area
during each census occasion.
At all sites, hypogeous fungi were censused once each in autumn (late-May and
early-June 1996) and spring (November 1996). Autumn normally provides the
greatest diversity of hypogeous fungi in eucalypt forests in south-eastern mainland
Australia (Bennett and Baxter 1989; Claridge et al. 1993b). The spring census
provided additional information on species that might not normally fruit in autumn
and recorded species that may have been fruiting but were missed during the first
census. More than two censusesare necessary to detect all species of fungi that might
fruit at any given site (see Arnolds 1992; O’Dell et al. 1996; Colgan 1997; Colgan et
al. 1997) so results presented here and in related papers should be assessed with this
in mind.
Taxonomy of hypogeous fungi
Characteristics of fresh fungal fruit-bodies were noted at the end of each field-day,
particularly size range, shape, surface texture and colour, colour changes with bruis-
ing and odour.All but the smallest were cut in vertical slices with a sharp razor-blade
and notes recorded on the thickness and layering of the peridium (outer skin), and
the glebal (spore-bearing tissue) colour and general structure (Beaton et al. 1985a;
Castellano et al. 1989; Lebel 1998). Based on these features, each collection was
ascribed tentatively to genus. Collections were then dried in a food dehydrator (45 ◦C
for 8–10 h), weighed and then placed in labelled paper envelopes. In the laboratory,
these were identified to species by one of us (J.M. Trappe), with assistance from
Efren Cázares and Teresa Lebel of the Department of Forest Science, Oregon State
University (Corvallis, Oregon, USA), and Mike Castellano of the U.S.D.A. Forest
Service, Pacific Northwest Research Station, Forestry Sciences Laboratory (also Cor-
vallis). Some species could be identified with existing published and unpublished
taxonomic literature (Beaton et al. 1985a; Bougher and Castellano 1993; Castellano
and Trappe 1990, 1992a,b; Castellano et al. 1992; Stewart and Trappe 1985; Trappe
1975; Trappe et al. 1992a,b, 1996a,b). Collections which could not be thus determ-
ined were identified to genus and then labelled as sp. nov. 1, sp. nov. 2 and so on.
Some collections did not fit into any described genus. For the purposesof the current
work, these were labelled with a provisional genus name for later formal taxonomic
description.
In accordance with the various collecting permits required to conduct our field
investigations, collections identified to species-level were lodged with relevant State
Herbaria: (i) the National Herbarium of Victoria, Royal Botanic Gardens (MEL),
for collections from Victoria and south-eastern New South Wales, and (ii) the Herb-
arium at the Australian National Botanic Gardens (CAN), for collections from the
Australian Capital Territory.

162
Statistical analyses
Statistical analysis of data is restricted here to simple comparisons of the
occurrence, relative abundance (number of fruit-bodies) and number of species of
hypogeous fungi between the two sample periods. Subsequent papers will statist-
ically explore factors relating to the same attributes at each study site, as well as
community structure and possible host–plant relationships among the various fungi
sampled.
Seasonal differences in the mean diversity of hypogeousfungi and mean number
of fruit-bodies collected were assessed by Student’s ttests (Mendenhall 1983) applied
to the difference (a−b) between the number of species or number of fruit-bodies
collected in autumn (a) and the number of species or number of fruit-bodies collected
in spring (b). The null hypothesis was that the mean of these values didnot differ from
zero. This was rejected if the calculated tvalue was such that P<0.05.
Seasonal differences in the occurrence of major (those found at >10% of sites)
genera and species of hypogeous fungi at the study sites were assessed by a large-
sample test for a population proportion (p) (Mendenhall 1983, pp. 311–313). For
each genus or species we noted (a) the number of sites where the taxon occurred
in autumn but not spring, and (b) the number of sites where the taxon occured in
spring but not autumn. Sites where a taxon was recorded in both seasons, or not
recorded at all, were disregarded. From the first set of figures, a proportionate value
was calculated (a/a +b). The null hypothesis was that this proportionate value did
not differ from 0.5. This hypothesis was rejected if the calculated zvalue was such
that P<0.05.
Results
Numbers of species
Overall, 209 species of hypogeous fungi were collected across the study sites over the
two sampling sessions. Only 56 were previously described in the literature (Table 5).
Of the 152 undescribed species, two were placed into two new genera of Ascomy-
cotina (tentatively referred to here as Errinundra and Unicava) and 16 into six new
genera of Basidiomycotina (tentatively referred to as Beatonia,Boughera,Claridgea,
Fusicastoreum,Geoinocybe and Pog isp erm a). Across genera, Gymnomyces (21 spe-
cies), Protoglossum (21 species), Thaxterogaster (14 species) and Zelleromyces (12
species) contained the greatest diversity of species. The mean number of species col-
lected across the study sites differedwith respect to season (Table6). Sites sampled in
autumn averaged more species than the same sites in spring (t=17.03, P<0.001).
The minimum number of species recorded at anyone site for both seasons combined
was two, the maximum 17.

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Table 5. Species of hypogeous fungi from described and undescribed (in bold type) genera recorded
during autumn and spring surveys across field study sites.
Ascomycotina
Amylascus tasmanica Hydnoplicata whitei Redellomyces westraliensis
Dingleya verrucosa Hydnotrya sp nov. 1 Ruhlandiella berolinensis
Elaphomyces spp. nov. 1–5 Labyrinthomyces varius Unicava sp. nov. 1
Errinundra sp. nov. 1
Basidiomycotina
Alpova lignicolor Descomyces spp. nov. 1–4 Mesophellia spp. nov. 1–2
Andebbia pachythrix Fusicastoreum spp. nov. 1 Nothocastoreum cretaceum
Arcangeliella glabrella Gallacea sp. nov.1 Octavianina tasmanica
Arcangeliella spp. nov. 1–5 Gautieria spp. nov. 1–2 Octavianina sp. nov. 1
Austrogautieria clelandii Geoinocybe spp. nov. 1–5 Podohydnangium australe
Austrogautieria chlorospora Gummiglobus agglutinosporus Pogisperma spp. nov. 1–4
Austrogautieria costata Gymnomyces megasporus Protoglossum luteum
Austrogautieria macrospora Gymnomyces pallidus Protoglossum spp. nov. 1–20
Austrogautieria rodwayi Gymnomyces seminudus Protubera sp. nov. 1
Austrogautieria spp. nov. 1–2 Gymnomyces spp. nov. 1–18 Quadrispora oblongispora
Beatonia spp. nov. 1–3 Hydnangium carneum Quadrispora spp. nov. 1–3
Boughera spp. nov. 1–2 Hymenogaster levisporus Royoungia sp. nov. 1
Castoreum radicatum Hymenogaster violaceous Scleroderma sp. nov. 1
Castoreum tasmanicum Hysterangium aggregatum Sclerogaster spp. nov. 1–2
Castoreum sp. nov. 1 Hysterangium inflatum Setchelliogaster australiensis
Chamonixia mucosa Hysterangium spp. nov. 1–9 Setchelliogaster tenuipes
Chamonixia vittatispora Hysterogaster fusisporus Setchelliogaster spp. nov. 1–2
Chondrogaster spp. nov. 1–6 Hysterogaster tasmanicus Stephanospora flava
Claridgea sp. nov. 1 Hysterogaster spp. nov. 1–4 Thaxterogaster campbellae
Cortinarius globuliformis Leucogaster meridionalis Thaxterogaster piriformis
Cortinarius sp. nov. 1 Macowanites spp. nov. 1–9 Thaxterogaster redactus
Cystangium phymatodisporum Malajczukia viridigleba Thaxterogaster spp. nov. 1-11
Cystangium rodwayi Mesophellia clelandii Timgrovea spp. nov. 1-5
Cystangium sessile Mesophellia glauca Zelleromyces daucinus
Cystangium spp. nov. 1–7 Mesophellia oleifera Zelleromyces striatus
Descomyces albellus Mesophellia trabalis Zelleromyces sp. nov. 1–10
Descomyces albus
Zygomycotina
Endogone aggregata Glomus australe Glomus pulvinatum
Occurrence of taxa
Taxa of hypogeous fungi differed in frequency of occurrence across the study sites.
Representatives of 20 genera of fungi occurred at more than 10% of the study sites
(Table 7). The most frequently occurring genera were Zelleromyces (99 of 136 sites),
Gymnomyces (93), Chamonixia (74) and Hysterangium (68). Many genera also
differed in frequency of occurrence in relation to season, with most occurring at
more sites in autumn than in spring. With few exceptions, these were genera that
produced soft, desiccation-prone fruit-bodies, including Cystangium,Descomyces,
Hydnangium,Hysterogaster and Thaxterogaster. In contrast, members of genera that

164
Table 6. Diversity of species of hypogeous fungi found at the 136 study sites over the two
sample periods.
Average number of Minimum number Maximum number
Sample period species (mean ±SE) of speciesaof speciesb
Autumn 7.11 ±0.24 1 14
Spring 2.92 ±0.17 0 9
Overallc9.08 ±0.29 2 17
aMinimum number of species = least number of species found at any one site.
bMaximum number of species = largest number of species found at any one site.
cOverall = autumn + spring.
Table 7. Occurrence of genera of hypogeous fungi recorded at >10% of the 136 study sites over the
two sample periods.
Number of sites Number of sites Total number
Fungal genus found in autumn found in spring of sites found at zP
Arcangeliella (B) 14 2 15 3.22 0.01
Austrogautieria (B) 14 10 21 0.93 n.s.d
Castoreum (B) 10 12 16 −0.63 n.s.d
Chamonixia (B) 69 16 74 6.67 0.001
Cortinarius (B) 45 17 48 4.78 0.01
Cystangium (B) 42 19 52 3.35 0.001
Descomyces (B) 56 26 63 4.48 0.001
Gymnomyces (B) 84 40 93 13.38 0.001
Hydnangium (B) 40 20 42 4.11 0.001
Hydnoplicata (A) 29 7 33 3.85 0.001
Hymenogaster (B) 29 2 31 4.79 0.001
Hysterangium (B) 54 31 68 3.14 0.01
Hysterogaster (B) 23 8 27 3.16 0.01
Labyrinthomyces (A) 7 10 16 −0.77 n.s.d
Mesophellia (B) 12 32 35 −3.97 0.001
Protoglossum (B) 26 12 33 2.64 0.05
Stephanospora (B) 13 3 15 20.16 0.001
Thaxterogaster (B) 26 9 33 3.00 0.01
Timgrovea (B) 22 11 28 2.30 0.05
Zelleromyces (B) 97 24 99 8.25 0.001
A = Ascomycota, B = Basidiomycota, n.s.d = no significant difference between autumn and spring.
produced rubbery or hard, desiccation-resistant fruit-bodies (Castoreum,Labyrintho-
myces and Mesophellia) either showed no patternin frequency of occurrence with re-
spect to season, or occurredat more sites in the spring sample session (Mesophellia).
When species within the common genera were considered separately, the same sorts
of trends were generally apparent, with few exceptions (Table 8). Notably, the soft
fruit-bodies of Cystangium sessile and Descomyces albellus did not differ signific-
antly in frequency between autumn and spring.

165
Table 8. Occurrence of species of hypogeous fungi recorded at >10% of the 136 study sites over the two
sample periods.
Number of sites Number of sites Total number of
Fungal species found in autumn found in spring sites found at zP
Castoreum radicatum (B) 9 10 14 −0.36 n.s.d
Chamonixia vittatispora (B) 58 16 65 13.32 0.001
Cortinarius globuliformis (B) 41 17 44 4.38 0.001
Cystangium sessile (B) 20 14 32 1.09 n.s.d
Descomyces albellus (B) 32 21 43 1.84 n.s.d
Descomyces albus (B) 14 2 16 3.04 0.01
Gymnomyces seminudus (B) 24 15 34 1.62 n.s.d
Gymnomyces sp. nov. 2 (B) 18 7 22 2.64 0.05
Gymnomyces sp. nov. 5 (B) 20 4 23 3.37 0.01
Hydnangium carneum (B) 40 20 42 4.12 0.001
Hydnoplicata whitei (A) 29 7 33 3.79 0.001
Hymenogaster levisporus (B) 29 1 30 4.95 0.001
Hysterangium inflatum (B) 25 12 33 2.36 0.05
Hysterangium sp. nov. 9 (B) 24 9 30 2.91 0.01
Labyrinthomyces varius (A) 7 10 16 −0.65 n.s.d
Mesophellia glauca (B) 10 17 23 −1.57 n.s.d
Stephanospora flava (B) 13 3 15 2.69 0.05
Zelleromyces daucinus (B) 19 2 20 3.39 0.01
Zelleromyces striatus (B) 44 6 45 5.56 0.001
Zelleromyces sp. nov. 6 (B) 15 0 15 3.87 0.01
Zelleromyces sp. nov. 7 (B) 43 10 46 5.12 0.001
A = Ascomycota, B = Basidiomycota, n.s.d = no significant difference between autumn and spring.
Abundance of fruit-bodies
In all, 7451 fruit-bodies of hypogeous fungi were collected across the two sample
sessions: 5938 in autumn and 1513 in spring. The mean number of fruit-bodies col-
lected differed with respect to season (Table 9). On average, sites sampled in autumn
had more fruit-bodies than in spring (t=13.81,P < 0.001). The minimum number
recorded at any one site for both sample seasons combined was three, the maximum
129. Biomass (dry weight) of fruit-bodiesshowed similar trends in relation to season
but those data will be presented in a later paper.
Table 9. Number of fruit-bodies of hypogeous fungi found at the 136 study sites over the two
sample periods.
Average number of Minimum number Maximum number
Sample period fruit-bodies (mean ±SE) of fruit-bodiesaof fruit-bodiesb
Autumn 43.66 ±2.32 2 120
Spring 11.13 ±1.03 0 72
Overallc54.79 ±2.69 3 129
aMinimum number of fruit-bodies = least number of fruit-bodies found at any one site.
bMaximum number of fruit-bodies = largest number of fruit-bodies found at any one site.
cOverall = autumn + spring.

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Discussion
Diversity of hypogeous fungi in eucalypt forests
A major highlight of our study is the high diversity of hypogeous fungi encountered.
Two hundred and nine species were recorded, more than three-quarters of which were
undescribed, including representatives of at least eight new genera. Due to the high
proportion of unidentified taxa, over 12 months were required to classify samples to
species level. Despite this considerable effort, we consider our initial sorting to be
preliminary. More rigorous examination of samples may reveal additional taxa. The
overwhelming number of novel taxa was unexpected because the taxonomic know-
ledge of species in the study area was thought to be reasonably good. The diversity of
hypogeous fungi found here ideally would be compared with that of similarly-sized
regions in Australia and overseas. However, relatively few data exist for comparisons,
mainly because studies to date have generally focussed on measuring productivity
of hypogeous fungi at relatively few sites (i.e. Fogel 1976; Hunt and Trappe 1987;
Luoma et al. 1991; Claridge et al. 1993a; Johnson 1994b). The only previously pub-
lished work on a comparable scale is that of Castellano and Bougher (1994), who
provided a synthesis of the species of hypogeous fungi known to occur in Queens-
land (149 species) and Tasmania (132 species), respectively. Notably, their data came
from a preliminary evaluation of opportunistic collections over six years. This was to
gain a taxonomic understandingof hypogeous fungi in Australia, rather than develop
ecological insight into patterns of occurrence. As such, no information is provided
on the spatial extent of their surveys, or how well major environmental gradients
within the geographic areas of interest were sampled. Nevertheless, their numbers
together with our data re-inforce the notion that hypogeous fungi are a significantly
underestimated component of the biodiversity in Australian eucalypt forests.
Our sampling produced species from 47 of the 63 genera of hypogeous fungi
described from Australia (Table 10). Of the remaining 16 genera, 12 have never been
reported from Victoria or New South Wales. For example, Mycoamaranthus has been
reported only from Queensland (Castellano et al. 1992), Horakiella only from Tas-
mania (Castellano and Trappe 1992). Only two genera, Muciturbo and Richoniella,
have been reported from within the study area, with fruit-bodies being collected only
of the latter but outside the plots (A.W. Claridge, unpublished data 1997).
The diversity of species within some of the genera of hypogeous fungi recorded
is much higher than previously known. For example, the number of species of Gym-
nomyces was 21, far in excess of the three species previously described from the
general geographic region in which we worked (Beaton et al. 1984). Similarly, at
least 21 different species of Protoglossum, a genus previously thought to be mono-
specific, were found (Beaton et al. 1985b). To some extent, this reflects the poor
taxonomic understanding of these groups of fungi, combined with deficient survey
data. The factors which have caused such speciation among hypogeous fungi are un-

167
Table 10. Genera of described hypogeous fungi native to Australia.
Genus Genus
Alpova (B) + Hysterogaster (B) +
Amylascus (A) + Labyrinthomyces (A) +
Andebbia (B) + Leucogaster (B)
Arcangeliella(B) + Macowanites (B) +
Austrogautieria (B) + Malajczukia (B) +
Boughera (B) + Martellia (B)
Castoreum (B) + Mesophellia (B) +
Chamonixia (B) + Muciturbo (A)
Choiromyces (A) Mycoamaranthus (B)
Chondrogaster (B) + Mycoclelandii (A)
Cortinarius (B) + Neogelopellis (B)
Cribbea (B) Nothocastoreum (B) +
Cystangium (B) + Octavianina (B) +
Descomyces (B) + Podohydnangium (B) +
Dingleya (A) + Protoglossum (B) +
Elaphomyces (A) + Protubera (B) +
Endogone (Z) + Quadrispora (B) +
Gastroboletus (B) Radiigera (B)
Gautieria (B) + Reddellomyces (A) +
Gelopellis (B) + Richoniella (B)
Genea (A) + Royoungia (B) +
Gigasperma (B) Ruhlandiella (A) +
Glomus (Z) + Scleroderma (B) +
Gummiglobus (B) + Sclerogaster (B) +
Gymnohydnotrya (A) Setchelliogaster (B) +
Gymnomyces (B) + Stephanospora (B) +
Horakiella (B) Stephensia (A)
Hydnangium (B) + Thaxterogaster (B) +
Hydnoplicata (A) + Timgrovea (B) +
Hydnotrya (A) + Torrendia (B)
Hymenogaster (B) + Zelleromyces (B) +
Hysterangium (B) +
Genera recorded in the current study are indicated by a cross (+).
A = Ascomycota, B = Basidiomycota, Z = Zygomycota.
known. Flannery (1995) proposed that the nutrient-poor soils characteristic of much
of Australia encouraged special adaptations that lead to increased diversity. Also,
in a summary of the evolutionary pathway of hypogeous fungi from their epigeous
(above-ground fruiting) relatives, Johnson (1996) suggested that long-term climate
change, in which continental Australia experienced repeated cooling and drying as-
sociated with relatively recent glacial periods, was the driving force for speciation
among closely related taxa. Such a process parallels similar radiations that occurred
among the endemic flora.

168
Patterns in occurrence and relative abundance of fungal taxa
The current study included only one autumn and spring sampling, but the large num-
ber of sites in our study provides insight into seasonal variation in occurrence of
different taxa. Taxa with soft, desiccation-prone, fruit-bodies (i.e. members of the
genera Chamonixia,Cortinarius,Descomyces,Gymnomyces,Hymenogaster,Thax-
terogaster and Zelleromyces) occurred at more sites in the autumn census when soil
moisture levels averaged high (A.W. Claridge, unpublished data). In constrast, taxa
with rubbery or hard, desiccation-resistant, fruit-bodies (i.e. Castoreum,Labyrintho-
myces and Mesophellia) either showed no pattern in frequency of occurrence from
autumn to spring, or occurred at more sites in the spring period when soil condi-
tions were relatively dry. These findings are consistent with the results of Claridge
et al. (1993a), who monitored production of hypogeous fruit-bodies in a mixed-
species eucalypt forest in East Gippsland, Victoria. They also support observations
by Johnson (1994b) in a dry sclerophyll eucalypt forest in Tasmania, that some soft-
bodied hypogeous taxa occurred in greatest abundance immediately after rain while
other hard-bodied taxa fruited more abundantly after prolonged periods without rain-
fall.Patterns in the overall abundance of fungi on our study sites also agree in gen-
eral with observations by others. Fruit-body production averaged higher on sites in
autumn than in spring. Similar differences in seasonal abundance were recorded by
Claridge et al. (1993a) in East Gippsland. Bennett and Baxter (1989) and Claridge
et al. (1993b) observed that the proportion of fungus in the diet of highly myco-
phagous mammals such as potoroos is highest in autumn. Most likely this reflects
increased production by hypogeous fungi that produce large numbers of soft fruit-
bodies in response to enhanced soil moisture conditions following dry summers.
Similar seasonal variation in production of fruit-bodies is evident among hypogeous
fungi in the Pacific Northwestern United States (Fogel 1976; Hunt and Trappe 1987;
Luoma et al. 1991).
Strengths and weaknesses of study
This is the first study that has attempted to describe the distribution of hypogeous
fungi at a large geographic scale through systematic sampling. Previous systematic
samplings of these organisms have either been conducted at single or relatively few
study sites (i.e. Fogel 1976; Hunt and Trappe 1987; Luoma et al. 1991; Claridge
et al. 1993a; Johnson 1994b). In those studies, temporal and spatial differences in
the abundance of fruit-bodies of hypogeous species were explained in relation to
prevailing weather conditions or major changes in vegetation communities and/or
disturbance regimes. Such findings, while invaluable in increasing knowledge about
the ecology of hypogeous fungi, are limited in application because they are based
on largely site-specific research. Our data from across a large number of sites will

169
enable exploration of factors which influence the distribution of hypogeousfungi at a
landscape scale.
Because sampling effort was standardised and conducted within relatively short
time-frames at each sampling season, the occurrence and number of fungal taxa
across sites can be meaningfully compared. Further, the use of time-constraint
sampling of fruit-bodies provides confidence that virtually all species fruiting at each
site were recorded. Earlier sampling methods based on smaller plots within a given
area are far more time-consuming and would not providesimilarly accurate counts of
species occurrence and numbers of species without protracted effort (A.W. Claridge,
unpublished data). This is mainly because of the patchy distribution of the fungi and
the considerable effort devoted to processing plots that yield no fruit-bodies (Claridge
et al. 1993a; Johnson 1994b).
Our study relied heavily on censusing fruit-bodies to ascertain the presence and
relative abundance of different species of hypogeous fungi at each site. Using fruit-
bodies to determine species presence does have trade-offs, the most obvious being
that existing sampling techniques may severely disturb the thallus and surrounding
soil. Moreover, fruit-bodies of most species are ephemeral, and their abundance may
vary significantly in relation to recent climatic events (Johnson 1994a). Not all species
fruit each year, and some may fruit infrequently. Accordingly,it may take some time
to record all species within a given area of forest. For example, despite sampling on
a near monthly basis over a period of 3 years, Hunt and Trappe (1987) continued to
collect additional speciesof hypogeous fungi from a 1.5 ha Douglas-fir stand through-
out the course of their study. Colgan et al. (1999) report a similar experiencealso in a
series of Douglas fir stands. In the present study, the total species count increased at
nearly three-quarters of the sites after the second (spring) census. How many further
visits to each site would be necessary to detect all species remains to be seen.
Two less destructive alternatives to raking for fruit-bodies of hypogeous fungi
are currently under development for assessment of fungal populations in the soil.
Both involve sampling the mycorrhiza themselves, usually by excavating small soil
cores. One approach is to differentiate individual morphotypes of ectomycorrhizae
and, where possible, relate themto the causal fungus (Agerer 1994). This techniqueis
extremely labour intensive and related fungal species may form mycorrhizal morpho-
types so similar that differentiationis difficult, if not impossible, by morphologyalone
(Luoma and Eberhart 1997). DNA analysis offers a more sure and less labour in-
tensive route to identifying the fungal component of the individual mycorrhizae than
does mycorrhiza morphotyping(Tommerup 1992; Martin et al. 1994), but currently
is too expensive to be applied to large numbers of samples. Moreover, thousands
of fungi, both epigeous and hypogeous, form ectomycorrhizae (Trappe 1962), but
only a relative few are currently available in DNA sequence databases needed to
match the fungus on a mycorrhiza to a species in the database. Morphotyping used
in conjunction with DNA analysismay offer a useful compromise (Gardesand Bruns
1993; Cannon 1997).

170
Which approach or combination of approaches is appropriate for a given study
will depend on the objectives of that study. The fungal taxonomy on which study of
fungal populations and productivity must be based requires initial collection of fruit-
bodies. Studies of fungi as a food resource for animals similarly requires collection of
fruit-bodies (i.e. Claridge et al. 1993a). Studies of fungal populations in the soil, on
the other hand, can be better done by sampling mycorrhizaeand differentiating them
by morphotyping or DNA analysis (Trappe and Jumpponen 1995;Cannon 1997), but
limitations in presently available databases will still require collection of fruit-bodies
as sources of DNA and as voucher specimens.
Acknowledgements
In Victoria field research was conducted under the provisions of National Parks and
Wildlife Permit No. 967/046, in the Australian Capital Territory under the provisions
of A.C.T. Parks and Conservation Service ‘Licence to Take’ (LT 96022) and in New
South Wales in compliance with the provisions of State Forests ‘Special Purposes
Permit’ (05078) and National Parks and Wildlife Service ‘Scientific Investigation
Licence’ (A1693). Personnel of the New South Wales National Parks and Wild-
life Service, State Forests of New South Wales and the Victorian Department of
Natural Resources and Environment helped locate the study sites. Drs Ari Jump-
ponen, Efrén Cázares and Wes Colgan III, Shane Bobbin, Ryan Chick, Debbie Clar-
idge, David Claridge, Tony Claridge, Wes Colgan II, Will Cramer, Ben Gunn, Brad
Halasz, Helen Lawlor, Doug Mills, Andy Murray, Donna Nunan, Andrew Peachey,
Bob Peck, Phillip Smith and Phil Tennant assisted with fieldwork. The U.S.D.A.
Forest Service, Pacific Northwest Research Station Forest Mycology Team provided
support for identification of the fungi, specific thanks go to Drs Mike Castellano,
Cázares and Teresa Lebel. June McMahon and Janet Stein at C.R.E.S. assisted with
various computing tasks necessary to derive climate surfaces. Dr Mick Tanton at
the Department of Forestry, The Australian National University, provided laborat-
ory space for processing fungal samples. Funding for fieldwork was provided by the
Australian Nature Conservation Agency under the National Forests Program (Project
FBNP5), the NSW National Parks and Wildlife Service andthe Victorian Department
of Natural Resources and Environment. Participation in this project by J.M. Trappe
was funded in part by a McMasters Fellowship awarded by the C.S.I.R.O. Division
of Wildlife and Ecology.
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