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SCIENCE FOR CONSERVATION 306 Using molecular techniques to combine taxonomic and ecological data for fungi Reviewing the Data Deficient fungi list, 2009

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Page 1: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

Science for conServation 306

Using molecular techniques to combine taxonomic and ecological data for fungi

Reviewing the Data Deficient fungi list, 2009

Page 2: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these
Page 3: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

Using molecular techniques to combine taxonomic and ecological data for fungi

Reviewing the Data Deficient fungi list, 2009

Peter Johnston, Duckchul Park, Ian Dickie and Katrin Walbert

Science for conServation 306

Published by

Publishing Team

Department of Conservation

PO Box 10420, The Terrace

Wellington 6143, New Zealand

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Cover: Cortinarius tessiae. Photo: Jerrie Cooper.

Science for Conservation is a scientific monograph series presenting research funded by New Zealand

Department of Conservation (DOC). Manuscripts are internally and externally peer-reviewed; resulting

publications are considered part of the formal international scientific literature.

This report is available from the departmental website in pdf form. Titles are listed in our catalogue on

the website, refer www.doc.govt.nz under Publications, then Science & technical.

© Copyright October 2010, New Zealand Department of Conservation

ISSN 1177–9241 (web PDF)

ISBN 978–0–478–14833–6 (web PDF)

This report was prepared for publication by the Publishing Team; editing by Lynette Clelland and layout

by Frith Hughes and Lynette Clelland. Publication was approved by the General Manager, Research and

Development Group, Department of Conservation, Wellington, New Zealand.

In the interest of forest conservation, we support paperless electronic publishing.

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CONTeNTS

Abstract 5

1. Introduction 6

2. Objectives 7

3. Methods 7

3.1 Data sources 7

3.1.1 ecological datasets 7

3.1.2 Dried herbarium specimens 8

3.1.3 Tissue samples stored in CTAB buffer 8

3.1.4 Updated collection data from PDD herbarium 8

3.2 Molecular methods 9

3.2.1 DNA extraction and amplification 9

3.2.2 DNA analysis 9

4. Results 10

4.1 Molecular data from herbarium specimens 10

4.2 Matching ecological data to herbarium specimens 13

4.3 Reassessment of species on the ‘Data Deficient’ list 13

5. Discussion and Conclusions 14

6. Acknowledgements 16

7. References 17

Appendix 1

Collections with molecular data (ITS and LSU sequences,

and t-RFLP patterns) generated 19

Appendix 2

All species reviewed in this project with notes on recommended

changes to status (if any) 24

Appendix 3

Additions to the Data Deficient list 31

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5Science for Conservation 306

© Copyright October 2010, Department of Conservation. This paper may be cited as:

Johnston, P.; Park, D.; Dickie, I.; Walbert, K. 2010: Using molecular techniques to combine taxonomic

and ecological data for fungi: reviewing the Data Deficient fungi list, 2009. Science for

Conservation 306. Department of Conservation, Wellington. 31 p.

Using molecular techniques to combine taxonomic and ecological data for fungiReviewing the Data Deficient fungi list, 2009

Peter Johnston, Duckchul Park, Ian Dickie and Katrin Walbert

Landcare Research, Private Bag 92170, Auckland 1142, New Zealand

email: [email protected]

A B S T R A C T

A real problem with understanding the distribution of fungal species is a lack

of specimens and associated collecting data. Few people can accurately identify

fungi, and the effort required to collect and store a specimen is high, meaning

even the most common species are poorly represented in New Zealand’s fungal

collections. This, in turn, creates a problem for biodiversity management,

including the assessment of rarity, which requires species distribution data. The

work reported here uses molecular techniques to supplement specimen-based

distribution data with research data collected by fungal ecologists. We authenticate

the ecological data through a molecular comparison with type specimens and

other putatively authentic specimens. To test the practical value of this approach

we focussed on Data Deficient fungi from the New Zealand Threat Classification

System lists 2002, targeting ectomycorrhizal mushrooms, the subject of relatively

intensive and ongoing ecological sampling. Data collected in this report indicate

that 62 species of ectomycorrhizal mushrooms should be shifted from the Data

Deficient category to a non-threatened category. At least one species should be

considered for shifting to a higher threat category. However, balancing this is a

recommendation to add 32 species to the Data Deficient category. Most of the

additions represent newly described species, which were thus not considered

during the 2002 assessment. The DNA sequence data accumulated during this

project provide a first step in developing an authentic molecular data layer for

New Zealand’s fungi and, as such, have a high value beyond this project. They

provide the means for non-experts to identify fungal species using a simple DNA

sequence comparison. The data will also allow ecologists using t-RFLP sampling

methods to match their samples to a species, and so continue to provide species

distribution data through ecological projects. Previously, only three of the species

treated had DNA sequence data available.

Keywords: fungi, ectomycorrhiza, Inocybe, Cortinarius, DNA, t-RFLP, molecular

identification tools, New Zealand, threat classification

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6 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

1. Introduction

effective biodiversity and biosecurity management requires accurate data on the

distribution of species. A real problem with understanding the distribution of

New Zealand’s fungal species is a lack of specimens and associated collecting

data. There are a small number of people who can accurately identify fungi,

and the effort required to collect and store a specimen is high, meaning that

even the most common species are poorly represented in New Zealand’s fungal

collections.

The fungal Threat Classification System lists (Hitchmough 2002), based on

criteria from Molloy et al. (2002), were first developed following a workshop held

during the New Zealand Fungal Foray at Haast in 2002, attended by a group of

experienced mycologists from Landcare Research, Scion, and Otago University.

The lack of distribution data for fungi is a major impediment to assessing the

threat status of New Zealand’s fungi and this is reflected in having more than

1400 species listed in the Data Deficient category.

Distribution records of fungi have traditionally relied solely on direct observation

of the fruiting body. Fruiting bodies are short-lived, and their development

depends on climatic and other conditions, which can lead to under-estimation of

the actual distribution of a species. Practical and inexpensive DNA-based methods

are now available to detect fungal species directly from hyphae, overcoming the

need to observe fruiting bodies.

In this proof-of-concept project we use molecular methods to combine ecological

and taxonomic datasets in an attempt to maximise the distribution data available

for a group of Data Deficient fungal species. ecological projects led by Ian Dickie

(Landcare Research, sampling in beech and tea-tree in the South Island, e.g. Dickie

et al. 2009) and Katrin Walbert (Scion, sampling in tea-tree in the North and South

Islands) are accumulating t-RFLP-based genetic data on ectomycorrhizal fungal

diversity directly from living roots of the host plants. This method is reviewed in

Dickie & Fitzjohn (2007) and implemented in Fitzjohn & Dickie (2007), Dickie

et al. (2009), and Dickie et al. (2010). The t-RFLP data measures changes in

species diversity across sampled sites, but does not provide identification of those

species. To identify the species represented in the ecological datasets requires

a complementary set of molecular data from authentically identified herbarium

specimens. This was provided through specimens in the New Zealand Fungal

Herbarium (PDD), which represent 164 species of ectomycorrhizal mushrooms

in the Data Deficient list.

We review the Data Deficient lists of ectomycorrhizal fungi on the basis of

several other data sources, in addition to the ecological datasets. The publication

of the fungal Threat lists provided a catalyst to encourage additions to the

distribution records for the listed species. Many additional collections of Data

Deficient species have been added to the New Zealand Fungal Herbarium

(PDD) since 2002, through the collecting effort fostered by the annual

New Zealand Fungal Forays (see Foray reports, www.funnz.org.nz). For example,

the Fungal Forays in 2005, 2006, and 2007 reported 44, 57, and 32 Data Deficient

species, respectively. Other projects, funded by the Terrestrial and Freshwater

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7Science for Conservation 306

Biodiversity Information System (TFBIS, see www.biodiversity.govt.nz/land/

nzbs/tfbis/tfbis/), incorporated major historical collections of macrofungi into

the New Zealand Fungal Herbarium and the NZFungi database1. These projects

were based on specimens in the private collections of Marie Taylor, Barbara

Segedin, and Greta Stephenson, and included 75 species on the Data Deficient

lists. In addition, the exotic/indigenous status of several species on the original

list has been reviewed (unpubl. data).

2. Objectives

The objective of this study was to review the ectomycorrhizal species on the

Data Deficient fungi list (Hitchmough 2002) by:

Utilising DNA data to integrate taxonomic and ecological datasets to maximise •

the distribution data available for these fungi.

Reviewing all ectomycorrhizal species on the Data Deficient list on the basis •

of herbarium specimens deposited since 2002.

3. Methods

We used molecular methods to combine ecological and taxonomic datasets for a

group of ectomycorrhizal fungal species listed as Data Deficient in Hitchmough

(2002), so maximising distribution records for these species. Sequences and

t-RFLP patterns from the ITS region are generated from reliably identified

herbarium specimens. The t-RFLP patterns are used to recognise when these

species appear in samples collected in ecological studies, allowing very high

throughput assessment of species composition. Identifications can then be

confirmed by direct sequencing or clone libraries in selected samples (e.g. Dickie

et al. 2010). The sequences are used to provide identifications from sequences

generated directly from ectomycorrhizal roots, as well as for collections of

ectomycorrhizal fungi not identified to species level.

3 . 1 D A T A S O U R C e S

3.1.1 Ecological datasets

Sampling of ectomycorrhizal diversity across ecological gradients using molecular

techniques is being carried out in several independently funded projects

(e.g. Dickie et al. 2009). The method used in these projects has been t-RFLP,

which allows species diversity to be estimated from environmental samples

comprising mycorrhizal tree roots and containing mixed DNA extracts of many

1 ‘Historically important mushroom collections added to the New Zealand Fungal Herbarium’:

www.landcareresearch.co.nz/research/research_details.asp?Research_Content_ID=265

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8 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

species of fungi. each species is characterised by a t-RFLP profile comprising a

set of four fluorescently labelled DNA fragments of standard size. By matching

t-RFLP profiles between samples, the presence or absence of individual species

can be tracked. Detailed technical methods are provided in Dickie et al. (2009).

To identify the species themselves requires a library of standard profiles to be

generated from authentically identified specimens (see sections 3.1.2 and 3.2).

For the Data Deficient project we had access to 1,341 t-RFLP profiles generated

from ecological samples gathered from three Nothofagus sites, two Pinus sites,

and one Kunzea site in the Craigieburn, Granville, and Station Creek (Rakaia)

areas of Canterbury, South Island. In addition, we were provided with 17 ITS

sequences generated directly from Leptospermum scoparium root tips from

four Canterbury high-country sites.

3.1.2 Dried herbarium specimens

To obtain DNA extracts to generate standard t-RFLP profiles for known species,

putatively authentically identified dried herbarium specimens were selected to

represent as many of the Cortinarius and Inocybe species on the Data Deficient

list as possible. Whenever possible, DNA was extracted from type specimens.

A few species from other genera were included, but Cortinarius and Inocybe

were targeted because there are a large number of species of each on the

Data Deficient list and because they are currently being actively studied

taxonomically in complementary projects run by our international collaborators

(K. Soop and e. Horak for Cortinarius; B. Matheny, University of Tennessee, and

e. Horak for Inocybe). Because of the novelty of the DNA analysis approach we

had no precedent from which to estimate the likely number of matches with the

t-RFLP profiles, and thus included a few commonly collected species as a kind of

control (see section 4.1). The specimens treated are listed in Appendix 1.

3.1.3 Tissue samples stored in CTAB buffer

At the same time as the Data Deficient project was running, we were given

access to a set of about 230 tissue samples from ectomycorrhizal and saprobic

mushrooms collected in 2001 and stored in CTAB buffer at the time of collecting.

This storage method maximises the likelihood of successful extraction of high-

quality DNA. Dried specimens of each of these specimens were recently deposited

in the PDD herbarium. Many of these specimens were identified only to genus

level. Based on these generic identifications, 104 of the tissue samples were from

ectomycorrhizal species, based on the list of ectomycorrhizal genera provided

by Orlovich & Cairney (2004). Of the specimens that had been identified to

species level, eight represented Data Deficient ectomycorrhizal species. ITS

and LSU sequences generated from the remaining unidentified specimens of

ectomycorrhizal fungi showed that a further nine matched Data Deficient species.

Molecular and distribution data from these specimens were incorporated into

the project.

3.1.4 Updated collection data from PDD herbarium

The numbers of collections and the biostatus of all putatively ectomycorrhizal

species on the 2002 Data Deficient list were updated from the current PDD

collection data in the NZFungi database (http:\\nzfungi.landcareresearch.co.nz).

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9Science for Conservation 306

3 . 2 M O L e C U L A R M e T H O D S

3.2.1 DNA extraction and amplification

DNA was extracted from herbarium specimens using ReDextract-N-Amp Plant

PCR Kits (Sigma, USA) using the Corbett X-tractor Gene System (Corbett Robotics,

Australia). Tiny pieces of mushroom tissue were ground in extraction buffer with

a plastic pestle in the eppendorf tube. Following this, DNA extraction and PCR

were carried out following manufacturer’s instructions. ITS and LSU sequences

were obtained from each extract following the methods of Johnston & Park

(2005). Amplification primers for ITS were ITS1F and ITS4 (White et al. 1990;

Gardes & Bruns 1993) and for an approximately 950 bp fragment of the LSU were

LROR and LR5 (Vilgalys & Hester 1990; Bunyard et al. 1994). Sequences have been

deposited in Genbank, and accession numbers are provided in Appendix 1.

Standard t-RFLP fragment profiles were generated from the same DNA extracts

using the methods of Dickie et al. (2009), to facilitate identification of the putative

taxa in the ecological samples (see section 3.1.1).

3.2.2 DNA analysis

The ITS and LSU sequences were compared against data in Genbank using a

BLAST search to check that they represented the fungus in the herbarium packet,

rather than a chance contaminating mould. All reliable DNA sequences were

aligned using Clustal X (Thompson et al. 1997), and phylogenetic trees generated

from both the ITS and LSU datasets using a simple Neighbour Joining algorithm

using PAUP* (Swofford 2002). The simple nature of these analyses means that the

relative positions of the taxa in the trees has little phylogenetic significance, but

they show clearly where there are multiple samples of the same species.

The t-RFLP patterns generated from the herbarium specimens were compared

with those generated from the earlier ecological surveys, using the R based

program TRAMPR (Dickie & FitzJohn 2007; FitzJohn & Dickie 2007).

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10 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

4. Results

4 . 1 M O L e C U L A R D A T A F R O M H e R B A R I U M S P e C I M e N S

DNA was isolated from 102 dried herbarium specimens. A comparison of ITS

and LSU sequences showed that 78 of these DNA samples represented the fungi

expected, the remainder being various species of contaminating ascomycete

fungi. The success rate for extracting good quality, reliable DNA lowered as

the herbarium specimens got older, especially in those species with small, thin-

fleshed fruiting bodies (Figs 1 & 2; Appendix 1). Most of the pre-1990 specimens

from which good DNA was isolated were of species with large, robust fruiting

bodies. Good quality DNA was successfully isolated from all of the tissue

samples stored in CTAB. The specimens sequenced represented 74 different

ectomycorrhizal species (Fig. 3). High-quality t-RFLP patterns were generated for

all of these species. Several specimens represent Inocybe spp. in the process of

being formally published and are listed as Inocybe sp. 1–12 in Appendix 1 and

Fig. 3. DNA sequences for these species are not yet publicly available.

These data allowed us to:

Recognise misidentified herbarium specimens (Table 1) through ITS sequence •

comparisons. In each case, the accuracy of the redetermination was confirmed

by morphological examination.

Generate additional distribution records for 13 Data Deficient species through •

matches to ecological samples using t-RFLP profiles.

Recognise nine previously unidentified herbarium specimens as representing •

Data Deficient species, through matches to ITS sequences.

Recognise that two species likely to be described in future taxonomic studies •

were common in the ecological samples. In most cases, recently described

species of mushrooms in New Zealand taxonomic studies are based on one or

a few herbarium specimens, the minimal data provided on their distribution

and frequency meaning that they need to be added to the Data Deficient lists

following publication.

Recognise that the Data Deficient• Cortinarius cinnabarinus was incorrectly

recorded as present in New Zealand. The specimen on which this record was

based has been redetermined as Cortinarius veronicae var. dilutus on the

basis of an ITS sequence comparison.

Question whether one of the common species included as a control, •

Astrosporina asterospora, in fact occurs in New Zealand. This fungus was

originally described from north temperate regions, but Horak (1978) noted

that although the Northern Hemisphere–New Zealand distribution is unusual,

this species is found also in New Guinea, the Solomon Islands and Malaysia.

However, the New Zealand specimen we sequenced is genetically distinct

from Genbank records deposited as A. asterospora from Sweden and Denmark

(Genbank accession numbers AJ889950, AJ889951, AM882897).

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11Science for Conservation 306

Figure 1. The proportion of herbarium specimens collected in each decade

from 1960s to present, from which high-quality DNA was

successfully isolated.

Figure 2. PDD 27072, the type specimen for

Camarophyllus patinicolor, collected in 1968. This is one of the Data Deficient species

with small, thin-fleshed fruiting bodies from which DNA was not successfully

isolated.

0

25

50

75

100

1960s (n = 21) 1970s (n = 2) 1980s (n = 10) 1990s (n = 18) 2000s (n = 36)

Decade specimens collected

Pro

porti

on p

rovi

ding

hig

h qu

ality

DN

A (%

)

Decade specimens collected

Pro

porti

on p

rovi

ding

hig

h-qu

ality

DN

A (%

)

1960s (n = 21) 1970s (n = 2) 1980s (n = 10) 1990s (n = 18) 2000s (n = 36)0

25

50

75

100

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12 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

PUTATIVe SPeCIeS SeQUeNCeD IDeNTITy BASeD ON DNA SeQUeNCe DATA

Dermocybe leptospermorum PDD94202—another Dermocybe sp. with no DNA match

Cortinarius aegrotus PDD75275—DNA match to Cortinarius vitreopileatus

Dermocybe cramesina PDD94350—DNA match to Cortinarius papaver

Cortinarius chrysma PDD94351—another Cortinarius sp. with no DNA match

Cortinarius ignotus PDD94177—DNA match to Cortinarius sinapicolor

Cortinarius viscostriatus PDD75709—another Cortinarius sp. with no DNA match

Camarophyllus impurus PDD 81871—doubtfully Camarophyllus

Camarophyllus griseorufescens PDD 87889—doubtfully Camarophyllus

Camarphyllus canus PDD 88851—doubtfully Camarophyllus

TABLe 1. eXAMPLeS OF MISIDeNTIFICATIONS OF SPeCIeS ON THe DATA DeFICIeNT LIST ReVeALeD THROUGH

DNA ANALySIS.

Figure 3. Neighbour joining tree based on ITS sequences. Species represented by their

type specimens are indicated, as are the commonly

collected species. Names in red are of species with

clear matches to t-RFLP environmental samples; names blue have poorly

defined matches with some parts of the profile low and difficult to distinguish from

background signal; names in green match some t-RFLP profiles from environmental

samples but are not unique for a single species. Geographic distribution of the specimens sampled is

indicated by Crosby District codes (Crosby et al. 1998).

0.03

PDD67181_Cortinarius_exlugubris_Holotype_MC

PDD71306_Inocybe_sp_7_GB

PDD72683_Inocybe_strobilomyces_det_Horak_TO_COMMON

PDD27168_Dermocybe_splendida_Holotype_AK

PDD27109_Astrosporina_viscata_Holotype_BR

PDD72788_Cortinarius_sp_det_Horak_TO

PDD71143_Inocybe_sp_2_WD

PDD72861_Astrosporina_asterospora_det_Horak_ND_COMMON

PDD27184_Dermocybe_icterinoides_Holotype_GB

PDD72763_Cortinarius_sp_det_Horak_TO

PDD70509_Cortinarius_collybianus_Holotype_NN

PDD72619_Inocybe_sp_10_TO

PDD72818_Inocybe_sp_3_CL

PDD27272_Cortinarius_viscostriatus_Holotype_NN

PDD72768_Cortinarius_sp_TO

PDD27270_Cortinarius_aegrotus_Holotype_GBPDD71008_Cortinarius_periclymenus_Holotype_NC

PDD27174_Dermocybe_cardinalis_Holotype_NN

PDD70499_Cortinarius_dysodes_Holotype_MC

PDD72665_Cortinarius_singularis_det_Horak_TO

PDD94024_Cortinarius_cf_melimyxa_det_Soop_FD

PDD71314_Cortinarius_veronicae_var_dilutus_det_Soop_BR

PDD27262_Cortinarius_marmoratus_Holotype_NN

PDD71150_Inocybe_sp_5_FD

PDD70501_Cortinarius_picoides_Holotype_MC

PDD72696_Dermocybe_olivaceonigra_det_Horak_BP

PDD75275_Cortinarius_aegrotus_det_Leonard_NN

PDD70507_Cortinarius_persicanus_Holotype_NN

PDD72785_Cortinarius_sp_"badiohepaticus"_ined_TO

PDD72753_Cortinarius_olorinatus_det_Horak_

PDD72806_Cortinarius_caryotis_det_Horak_TO

PDD94177_Cortinarius_ignotus_det_Shirley_AK

PDD94019_Cortinarius_picoides_det_Soop_FD

PDD71009_Cortinarius_rattinus_Holotype_NC

PDD70505_Cortinarius_naphthalinus_Holotype_MC

PDD71010_Cortinarius_viscilaetus_Holotype_SL

PDD72728_Cortinarius_napivelatus_det_Horak_BR

PDD72523_Inocybe_sp_1_OL

PDD72690_Cortinarius_sp_det_Horak_TO

PDD32252_Dermocybe_cardinalis_det_Horak_AK

PDD72655_Cortinarius_cretax_det_Soop_TO

PDD72729_Inocybe_sp_8_GB

PDD72620_Cortinarius_gymnopiloides_det_Horak_TO

PDD82818_Inocybe_sp_11_BR

PDD71166_Inocybe_sp_6_OL

PDD74305_Cortinarius_caryotis_det_Soop_GB

PDD72700_Cortinarius_cf_sinapicolor_det_Horak_BP

PDD72772_Cortinarius_peraureus_det_Soop_TO

PDD27226_Camarophyllus_impurus_Holotype_AK

PDD72611_Cortinarius_rotundisporus_det_Horak_TO_COMMON

PDD68469_Cortinarius_chrysma_Holotype_MC

PDD27269_Cortinarius_castaneiceps_Holotype_CL

PDD94015_Cortinarius_austrocyanites_det_Soop_FD

PDD72794_Cortinarius_sp_ basifibrillosus _ined_TO" "

PDD72766_Cortinarius_chrysma_det_Soop_TO

PDD70502_Cortinarius_carbonellus_Holotype_NC

PDD71267_Inocybe_sp_12_NC

PDD71003_Cortinarius_papaver_Holotype_NN

PDD27263_Cortinarius_porphyrophaeus_Holotype_CL

PDD72542_Austroboletus_lacunosus_Det_Horak_OL_COMMON

PDD72707_Inocybe_sp_4_GB

PDD27180_Dermocybe_alienata_Holotype_AK

PDD27181_Dermocybe_largofulgens_Holotype_AK

PDD27230_Camarophyllus_griseorufescens_Holotype_AK

PDD72661_Cortinarius_cupreonatus_det_Soop_TO

PDD92390_Dermocybe_cardinalis_det_Leonard_NN

PDD71007_Cortinarius_anauensis_Holotype_SL

PDD72521_Inocybe_umbrosa_det_Horak_OL

PDD72618_Inocybe_luteobulbosa_var_luteobulbosa_det_Horak_TO_COMMON

PDD72715_Cortinarius_cupreonatus_det_Soop_GB

PDD67176_Cortinarius_saturniorum_Holotype_MC

PDD72767_Cortinarius_sp_det_Horak_TO

PDD88842_Cortinarius_cf_viscoviridis_det_Leonard_NN

PDD72522_Inocybe_sp_9_OL

PDD27173_Dermocybe_cramesina_Holotype_NN

PDD72692_Dermocybe_splendida_det_Horak_BP

PDD70500_Cortinarius_perelegans_Holotype_MC

PDD27258_Cortinarius_aerugineoconicus_Holotype_NN

PDD71005_Cortinarius_minoscaurus_Holotype_CO

PDD77794_Astrosporina_subclavata_det_Horak_NN

PDD72677_Cortinarius_peraureus_det_Soop_TO

PDD94350_Dermocybe_cramesina_det_Shirley_AK

PDD27271_Cortinarius_vitreopileatus_Holotype_GB

PDD71004_Cortinarius_caryotis_Holotype_MC

PDD72687_Cortinarius_sp_ cucumeris _ined_TO" "

PDD72781_Cortinarius_meleagris_det_Horak_TO_COMMON

PDD72625_Cortinarius_retipes_det_Horak_TO_COMMON

PDD72686_Cortinarius_veronicae_var_dilutus_det_Soop_TO

PDD27183_Dermocybe_leptospermorum_Holotype_FD

PDD94011_Cortinarius_cf_gemmeus_det_Soop_FD

PDD88624_Inocybe_scabriuscula_det_Horak_NN

PDD27177_Dermocybe_egmontiana_Holotype_TK

PDD72637_Tylopilus_formosus_det_Horak_TO_COMMON

PDD82820_Camarophyllus_impurus_det_Horak_BR

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13Science for Conservation 306

4 . 2 M A T C H I N G e C O L O G I C A L D A T A T O H e R B A R I U M S P e C I M e N S

Several of the environmental samples collected through the ecological projects

had t-RFLP profiles matching those from herbarium specimens. However, many

of the matches were tentative, being based on poorly defined profiles where

one or more of the bands was doubtfully present, or where the profiles were

not unique to a single species (Fig. 3). The putatively common species were no

more often matched to the environmental samples than the supposedly rarer

Data Deficient species.

Two of the species with multiple matches to environmental samples have yet to

be formally described. These species are Cortinarius “badiohepaticus”, and the

species represented by the two collections labelled Cortinarius cf. gemmeus and

Cortinarius cf. melimyxa. even though they have not been formally described,

the frequent matches to environmental samples suggest that both species are

reasonably common.

None of the DNA sequences generated directly from mycorrhizal roots of

Leptospermum scoparium matched any of those from herbarium specimens.

Based on results from Genbank BLAST searches, these root samples comprised

six Cortinarius spp., four Tomentella spp., two Russula spp., one Clavulina sp.,

and one Tomentellopsis sp. None closely matched any sequence deposited in

Genbank.

4 . 3 R e A S S e S S M e N T O F S P e C I e S O N T H e ‘ D A T A D e F I C I e N T ’ L I S T

Appendix 2 lists the 164 ectomycorrhizal species in the 2002 Data Deficient list

for which specimens are available in the PDD herbarium. The appendix includes

notes on those species to be removed from the Data Deficient category and

placed in a higher threat category, those to be removed because they are now

considered unthreatened, and those to be retained as Data Deficient.

each name is assessed in relation to additional distribution records based on

dried specimens gathered since 2002, as well as the additional distribution

records provided by molecular matches to ecological samples. Several species

are removed from the category for technical reasons—either they are now

considered to be exotic, they are species now considered doubtfully present

in New Zealand, or they are undescribed species deposited in the herbarium

with informal, unpublished herbarium names and mistakenly categorised as Data

Deficient in 2002.

In summary, we recommend that 62 of the originally listed species should be

moved from the Data Deficient category to a non-threatened category. Cortinarius

pholiotellus should be considered for a higher threat category—it has been

collected only twice, each time from the same locality, beside a river and in a

highly disturbed site with potential to be destroyed in the longer term. Russula

tapawera could be recommended for adding to the Data Deficient category, but

with all four collections from the same locality, should perhaps be considered

for a higher threat status.

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14 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

Counter-balancing the removal of species from the Data Deficient category is a

recommendation to add 32 species (Appendix 3). Most of these species were

described after the original 2002 assessment and are represented by less than

four herbarium specimens.

5. Discussion and Conclusions

In addition to reviewing the status of 164 species of ectomycorrhizal fungi

categorised as Data Deficient, this project provides a proof-of-concept test of the

value that a basic, authentic molecular data layer can provide for understanding

the distribution and diversity of New Zealand’s fungi. This project combines

data from ecological and taxonomic datasets, matching t-RFLP profiles from

mycorrhizal root tips to those from authentic herbarium specimens of fruiting

bodies of the Data Deficient species. On the basis of the DNA data generated

we were able to provide more accurate identifications of herbarium specimens

putatively representing Data Deficient species through ITS sequence comparisons,

and provide additional distribution records for Data Deficient species through

t-RFLP profile matches.

In a broader context, the project has provided a start to the accumulation of a

barcode-like molecular data layer for the ectomycorrhizal fungi of New Zealand.

The information gathered from authentic herbarium specimens will have value

beyond the project. The power of molecular methods for understanding fungal

distributions are three-fold—they allow non-experts to accurately identify

specimens, they allow fungal species to be identified without the need to see

fruiting bodies, and they provide the opportunity to combine data from diverse

taxonomic and ecological projects.

Identification of mushrooms from fruiting body morphology relies also on the

skills and accuracy of the observers. This project showed that even with skilled

and experienced observers, many identifications are likely to be incorrect and

that several past records of Data Deficient species have been based on incorrectly

identified specimens (see Table 1). The DNA sequences now publicly available

through Genbank (see Appendix 1) provide a greater resource for allowing

molecular confirmation of an identification.

To date, the threat lists of fungi have been based only on data from herbarium

specimens. It is well known that the diversity of fungi measured from the

occurrence of fruiting bodies often does not reflect the diversity of fungal hyphae

within that ecosystem (e.g. Gardes & Bruns 1996). To observe a fruiting body

in an ecosystem requires a condition beyond the fungus being present—it also

requires the environmental conditions to be suitable for that fungus to fruit. This

reflects the pattern seen in this study, that species putatively common on the

basis of fruit body observation are no more likely to be matched in datasets based

on diversity of hyphae than are the much less commonly observed Data Deficient

species. Therefore, as well as having the potential to provide huge numbers of

records (the more than 1000 records from t-RFLP patterns available to us in this

project for no cost would have taken a huge effort to generate as traditional

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15Science for Conservation 306

dried specimens), ecological datasets may more accurately reflect actual species

diversity across the landscape. The molecular data gathered during this project

will allow an ongoing accumulation of distribution data from ecological projects

using both t-RFLP and direct sequencing methods.

The t-RFLP method used in this project is time and cost effective for generating

large amounts of distribution data. A disadvantage is that even with a complete

library of t-RFLP fragment sizes, it is unable to distinguish all species. Some

putative matches are known to represent more than one species (e.g. the

Laccaria spp. discussed in Dickie et al. 2009), and the quality of the signal

from environmental samples may preclude a reliable identification (see Fig. 3

and Appendix 2). Using different or additional restriction enzymes may reduce

this problem, but such a change would require whole new libraries of standard

fragment sizes to be accumulated. Another disadvantage is that researchers from

different labs must use exactly equivalent protocols and restriction enzymes for

results to be combined.

One alternative is to sequence directly from individual mycorrhizal root fragments,

but this method is not well suited to Nothofagus due to a high level (> 50%) of

single root fragments being colonised by multiple fungal species (Dickie et al.

2010). While cloning can be used to separate DNA of multiple species, for

cultural reasons, permission to clone DNA extracted from native environments

in New Zealand is difficult to obtain. Tedersoo et al. (2008) attempted to

avoid the problem of mixed DNA extracts by designing sets of taxon-specific

primers targeting the kinds of fungi they expected to be present as mycorrhizas.

However, this is a time-intensive approach that potentially biases results towards

pre-selected groups of taxa.

Technological advances in pyrosequencing are starting to provide practical,

time-efficient alternatives to t-RFLP and cloning. For example, the Life Sciences

GS Junior 454 sequencing machines are suitable for small labs and for a few

thousand dollars allow large numbers of sequences up to about 450 bp in length

to be generated from mixed environmental DNA. Buée et al. (2009) used a similar

system to investigate total fungal diversity in forest soils.

To realise the potential of any of these methods requires a much more complete

library of DNA data matched to authentic specimens, irrespective of whether

those data comprise t-RFLP band sizes, or DNA sequences. For example, in the

454-based study, Buée et al. (2009) were able to identify only 26 of the more

than 1000 putative species detected from oak forest soils. O’Brien et al. (2005)

used cloning to recognise 412 putative fungal taxa from soil on the basis of

ITS sequences. Of the sequences representing Basidiomycota, 36% could not be

identified even to the taxonomic level of Order.

Perhaps the most powerful advantage of a molecular approach is the ability to

take data from a wide range of projects and reanalyse it for alternative purposes.

Projects using DNA sequences rather than t-RFLP have greater potential for

matching data between unrelated projects because the data generated in method-

independent. Most ecological projects using DNA sequences to identify taxa

target the ITS region. The ITS is currently regarded as having the best potential

as a barcoding region for fungi (Seifert 2008) and is routinely collected as part

of many ecological and taxonomic projects. Although not reliable for all groups,

ITS sequences usually distinguish taxa at about the level of species, are easy to

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16 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

generate from samples with even poor quality DNA, and can be searched against

a rapidly expanding dataset. In this project, each case where a redetermination

was based on an ITS sequence comparison was confirmed by a subsequent

morphological examination.

This project provides a direction for the future. Modern fungal taxonomy

demands a molecular approach, even for the most basic alpha-taxonomic study.

The same will soon be true for any study asking questions about fungal diversity

and distribution, rarity, threat, impact and recovery. Useful extensions of this

project could include: generating a complete DNA data layer for New Zealand’s

rare and endangered fungi; developing more reliable protocols for extraction of

DNA from old herbarium specimens; using DNA sequence data to develop probes

to specifically target hyphae of fungal species in high threat categories to better

understand their local, as well as their wider, distributions within ecosystems;

expanding the dataset from ectomycorrhizal fungi to include wood-rotting fungi,

which are also being targeted in ecological studies (D. Peltzer, Landcare Research,

pers. comm.); and developing a web-based tool to allow broad user access to the

authentic, New Zealand-focussed DNA layer being accumulated, so facilitating

more accurate, DNA-based identification of specimens and avoiding data quality

issues with Genbank (e.g. Nilsson et al. 2006; Pennisi 2008).

6. Acknowledgements

This research was funded by the Department of Conservation (IMC-03-4131).

We thank Dr egon Horak (Innsbruck, Austria) for supplying the CTAB-preserved

specimens incorporated into this study, and Dr Karl Soop (Sweden) for feedback

on the identification of some of the collections examined.

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17Science for Conservation 306

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Appendix 1

C O L L e C T I O N S W I T H M O L e C U L A R D A T A ( I T S A N D L S U S e Q U e N C e S , A N D t - R F L P P A T T e R N S ) G e N e R A T e D

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SPe

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21Science for Conservation 306

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site

d in

G

enb

ank

as C

. gym

nopil

oid

es, a

n

ap

par

entl

y u

np

ub

lish

ed n

ame

Cort

ina

riu

s ig

notu

s (i

nd

igen

ou

s en

dem

ic)

2726

4 T

19

81

No

DN

A is

ola

ted

Cort

ina

riu

s lu

bri

can

esce

ns

(in

dig

eno

us

end

emic

) 71

006

T

1997

N

o D

NA

iso

late

d

Cort

ina

riu

s m

arm

ora

tus

(in

dig

eno

us

end

emic

) 27

262

T

1968

G

U23

3330

Cort

ina

riu

s m

elea

gris

(in

dig

eno

us)

72

781*

2001

H

M06

0324

, HM

0603

23

Co

mm

on

co

ntr

ol s

pec

ies

(see

Met

ho

ds)

Cort

ina

riu

s m

elim

yxa

(in

dig

eno

us

end

emic

) 27

267

T

1969

C

on

tam

inat

ing

DN

A

Cort

ina

riu

s m

inosc

au

rus

(in

dig

eno

us

end

emic

) 71

005

T

1999

G

U23

3349

, GU

2333

77

Cort

ina

riu

s n

aph

tha

lin

us

(in

dig

eno

us

end

emic

) 70

505

T

1999

G

U23

3344

, GU

2334

01

Cort

ina

riu

s olo

rin

atu

s (i

nd

igen

ou

s en

dem

ic)

2725

5 T

19

81

No

DN

A is

ola

ted

Cort

ina

riu

s olo

rin

atu

s (i

nd

igen

ou

s en

dem

ic)

7275

3*

20

01

HM

0603

30, H

M06

0331

Cort

ina

riu

s pa

pa

ver

(in

dig

eno

us

no

n-e

nd

emic

) 71

003

T

1999

G

U23

3347

, GU

2333

99

Cort

ina

riu

s pa

pa

ver

(in

dig

eno

us

no

n-e

nd

emic

) 94

350

20

08

GU

2333

75, G

U23

3426

O

rigi

nal

ly id

enti

fied

as

Cort

ina

riu

s

cr

am

esin

a

Cort

ina

riu

s per

eleg

an

s (i

nd

igen

ou

s en

dem

ic)

7050

0 T

19

99

GU

2333

41, G

U23

3398

Cort

ina

riu

s per

icly

men

us

(in

dig

eno

us

end

emic

) 71

008

T

1999

G

U23

3351

, GU

2333

79

Cort

ina

riu

s per

sica

nu

s (i

nd

igen

ou

s n

on

-en

dem

ic)

7050

7 T

19

99

GU

2333

45, G

U23

3392

Cort

ina

riu

s ph

aeo

chlo

rus

(in

dig

eno

us

end

emic

) 27

265

T

1981

N

o D

NA

iso

late

d

Cort

ina

riu

s ph

oli

ote

llu

s (i

nd

igen

ou

s en

dem

ic)

6847

0 T

20

08

Co

nta

min

atin

g D

NA

Cort

ina

riu

s pic

oid

es (

ind

igen

ou

s en

dem

ic)

7050

1 T

19

99

GU

2333

42

Cort

ina

riu

s pic

oid

es (

ind

igen

ou

s en

dem

ic)

9401

9

2008

G

U23

3371

, GU

2334

24

Cort

ina

riu

s porp

hyr

oph

aeu

s (i

nd

igen

ou

s en

dem

ic)

2726

3 T

19

81

GU

2333

31, G

U23

3416

Cort

ina

riu

s ra

ttin

us

(in

dig

eno

us

end

emic

) 71

009

T

1999

G

U23

3352

, GU

2334

19

Cort

ina

riu

s ro

tun

dis

poru

s (i

nd

igen

ou

s n

on

-en

dem

ic)

7261

1*

20

01

HM

0603

17, H

M06

0316

C

om

mo

n c

on

tro

l sp

ecie

s (s

ee M

eth

od

s)

Cort

ina

riu

s sa

turn

ioru

m (

ind

igen

ou

s en

dem

ic)

6717

6 T

19

97

GU

2333

37, G

U23

3388

Cort

ina

riu

s si

na

pic

olo

r (i

nd

igen

ou

s n

on

-en

dem

ic)

7270

0*

20

01

HM

0603

28, H

M06

0329

Cort

ina

riu

s si

na

pic

olo

r (i

nd

igen

ou

s n

on

-en

dem

ic)

9417

7

2008

G

U23

3373

, GU

2333

96

Ori

gin

ally

iden

tifi

ed a

s C

ort

ina

riu

s

ig

notu

s

Cort

ina

riu

s sp

. “ba

dio

hep

ati

cus”

ined

. (in

dig

eno

us)

72

785*

2001

Se

qu

ence

s n

ot

pu

blic

ly a

vaila

ble

U

np

ub

lish

ed h

erb

ariu

m n

ame

for

an

u

nd

escr

ibed

sp

ecie

s

Cort

ina

riu

s sp

. “ba

sifi

bri

llosu

s” in

ed.

7279

4*

20

01

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Un

pu

blis

hed

her

bar

ium

nam

e fo

r an

(in

dig

eno

us

end

emic

)

u

nd

escr

ibed

sp

ecie

s

Con

tin

ued

nex

t pa

ge*

DN

A f

rom

tis

sue

sam

ple

sto

red

in C

TA

B b

uff

er.

Page 24: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

22 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

SPe

CIe

S (B

IOST

AT

US)

P

DD

H

OL

OT

yP

e

ye

AR

t-

RF

LP

, IT

S, L

SU D

AT

A G

eN

eR

AT

eD

N

OT

eS

C

OL

Le

CT

eD

(W

ITH

Ge

NB

AN

K A

CC

eSS

ION

NU

MB

eR

S)

Cort

ina

riu

s sp

. “cu

cum

eris

” in

ed. (

ind

igen

ou

s)

7268

7*

20

01

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Un

pu

blis

hed

her

bar

ium

nam

e fo

r an

u

nd

escr

ibed

sp

ecie

s; s

om

etim

es r

efer

red

to

usi

ng

ano

ther

un

pu

blis

hed

nam

e,

M

yxa

ciu

m c

ucu

mer

is

Cort

ina

riu

s sp

. 75

709

20

02

GU

2333

59, G

U23

3402

O

rigi

nal

ly id

enti

fied

as

Cort

ina

riu

s

vi

scost

ria

tus

Cort

ina

riu

s sp

. 94

202

20

08

GU

2333

74, G

U23

3411

O

rigi

nal

ly id

enti

fied

as

Cort

ina

riu

s

le

pto

sper

moru

m

Cort

ina

riu

s sp

. 94

351

20

08

GU

2333

76, G

U23

3422

O

rigi

nal

ly id

enti

fied

as

Cort

ina

riu

s

ch

rysm

a

Cort

ina

riu

s sp

. no

v. (

fid

e So

op

, per

s. c

om

m.)

94

011

20

08

GU

2333

69, G

U23

3404

O

rigi

nal

ly id

enti

fied

as

Cort

ina

riu

s cf

.

ge

mm

eus

Cort

ina

riu

s sp

. no

v. (

fid

e So

op

, per

s. c

om

m.)

94

024

20

08

GU

2333

72, G

U23

3405

O

rigi

nal

ly id

enti

fied

as

Cort

ina

riu

s cf

.

m

elim

yxa

Cort

ina

riu

s ve

ron

ica

e va

r. d

ilu

tus

7131

4

2000

G

U23

3354

, GU

2334

00

Ori

gin

ally

iden

tifi

ed a

s C

. cin

na

ba

rin

us,

(in

dig

eno

us

end

emic

)

a

spec

ies

do

ub

tfu

lly p

rese

nt

in N

Z

Cort

ina

riu

s vi

scil

aet

us

(in

dig

eno

us

end

emic

) 71

010

T

1997

G

U23

3353

, GU

2333

78

Cort

ina

riu

s vi

scost

ria

tus

(in

dig

eno

us

end

emic

) 27

272

T

1968

G

U23

3335

Cort

ina

riu

s vi

scovi

ridis

(in

dig

eno

us

end

emic

) 27

257

T

1969

C

on

tam

inat

ing

DN

A

Cort

ina

riu

s vi

scovi

ridis

(in

dig

eno

us

end

emic

)?

8884

2

2006

G

U23

3390

D

ou

btf

ully

au

then

tic

for

this

nam

e

Cort

ina

riu

s vi

treo

pil

eatu

s (i

nd

igen

ou

s en

dem

ic)

2727

1 T

19

81

GU

2333

34, G

U23

3397

Cort

ina

riu

s vi

treo

pil

eatu

s (i

nd

igen

ou

s en

dem

ic)

7527

5

2004

G

U23

3357

, GU

2334

03

Ori

gin

ally

iden

tifi

ed a

s C

ort

ina

riu

s

a

egro

tus

Der

mocy

be

ali

ena

ta

2718

0 T

19

69

GU

2333

23, G

U23

3384

Der

mocy

be

au

ran

tiel

la (

ind

igen

ou

s en

dem

ic)

2717

6 T

19

68

Co

nta

min

atin

g D

NA

Der

mocy

be

card

ina

lis

(in

dig

eno

us

end

emic

) 27

174

T

1968

G

U23

3321

, GU

2334

15

Der

mocy

be

card

ina

lis

(in

dig

eno

us

end

emic

) 84

245

19

70

No

DN

A is

ola

ted

Der

mocy

be

card

ina

lis

(in

dig

eno

us

end

emic

) 32

252

19

74

GU

2333

36, G

U23

3414

Der

mocy

be

card

ina

lis

(in

dig

eno

us

end

emic

) 92

390

20

07

GU

2333

68, G

U23

3418

Der

mocy

be

cra

mes

ina

(in

dig

eno

us

no

n-e

nd

emic

) 27

173

T

1968

G

U23

3320

, GU

2334

20

Der

mocy

be

egm

on

tia

na

(in

dig

eno

us

end

emic

) 27

177

T

1968

G

U23

3322

Der

mocy

be

icte

rin

oid

es (

ind

igen

ou

s en

dem

ic)

2718

4 T

19

68

GU

2333

26

Der

mocy

be

larg

ofu

lgen

s (i

nd

igen

ou

s en

dem

ic)

2718

1 T

19

69

GU

2333

24

Der

mocy

be

lepto

sper

moru

m (

ind

igen

ou

s en

dem

ic)

2718

3 T

19

69

GU

2333

25, G

U23

3395

Der

mocy

be

pu

rpu

rata

(in

dig

eno

us

end

emic

) 27

171

T

1968

C

on

tam

inat

ing

DN

A

Der

mocy

be

sple

ndid

a (

ind

igen

ou

s n

on

-en

dem

ic)

2716

8 T

19

69

GU

2333

19, G

U23

3387

Inocy

be

cere

a (

ind

igen

ou

s en

dem

ic)

2712

2 T

19

69

Co

nta

min

atin

g D

NA

Appen

dix

1 c

on

tin

ued

* D

NA

fro

m t

issu

e sa

mp

le s

tore

d in

CT

AB

bu

ffer

.C

on

tin

ued

nex

t pa

ge

Page 25: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

23Science for Conservation 306

SPe

CIe

S (B

IOST

AT

US)

P

DD

H

OL

OT

yP

e

ye

AR

t-

RF

LP

, IT

S, L

SU D

AT

A G

eN

eR

AT

eD

N

OT

eS

C

OL

Le

CT

eD

(W

ITH

Ge

NB

AN

K A

CC

eSS

ION

NU

MB

eR

S)

Inocy

be

des

tru

ens

(in

dig

eno

us

end

emic

) 27

124

T

1968

C

on

tam

inat

ing

DN

A

Inocy

be

des

tru

ens

(in

dig

eno

us

end

emic

)?

8048

0

2003

G

U23

3361

, GU

2333

80

Do

ub

tfu

lly a

uth

enti

c fo

r th

is n

ame

Inocy

be

late

rici

a (

ind

igen

ou

s n

on

-en

dem

ic)

2712

0 T

19

69

Co

nta

min

atin

g D

NA

Inocy

be

late

rici

a (

ind

igen

ou

s n

on

-en

dem

ic)?

92

382

20

07

GU

2333

67, G

U23

3413

D

ou

btf

ully

au

then

tic

for

this

nam

e

Inocy

be

lute

obu

lbosa

var

. lu

teobu

lbosa

72

618*

2001

H

M06

0318

C

om

mo

n c

on

tro

l sp

ecie

s (s

ee M

eth

od

s)

(In

dig

eno

us

end

emic

)

Inocy

be

lute

obu

lbosa

var

. volv

ata

(in

dig

eno

us

end

emic

) 27

130

T

1968

N

o D

NA

iso

late

d

Inocy

be

men

dic

a (

ind

igen

ou

s en

dem

ic)

2712

5 T

19

68

Co

nta

min

atin

g D

NA

Inocy

be

ph

aeo

squ

arr

osa

(in

dig

eno

us

end

emic

) 27

126

T

1969

C

on

tam

inat

ing

DN

A

Inocy

be

ren

ispora

(in

dig

eno

us

end

emic

) 27

119

T

1968

C

on

tam

inat

ing

DN

A

Inocy

be

sca

bri

usc

ula

(in

dig

eno

us

end

emic

) 27

127

T

1968

C

on

tam

inat

ing

DN

A

Inocy

be

sca

bri

usc

ula

(in

dig

eno

us

end

emic

) 88

624

20

06

GU

2333

65 ,

GU

2334

25

Inocy

be

sp. 1

(in

dig

eno

us

end

emic

) 72

523

20

01

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp. 2

(in

dig

eno

us

end

emic

) 71

143

20

00

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp. 3

(in

dig

eno

us

end

emic

) 72

818

20

01

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp. 4

(in

dig

eno

us

end

emic

) 72

707

20

01

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp. 5

(in

dig

eno

us

end

emic

) 71

150

20

00

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp. 6

(in

dig

eno

us

end

emic

) 71

166

20

00

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp

. 7 (

ind

igen

ou

s en

dem

ic)

7130

6

2000

Se

qu

ence

s n

ot

pu

blic

ly a

vaila

ble

Inocy

be

sp. 8

(in

dig

eno

us

end

emic

) 72

729

20

01

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp. 9

(in

dig

eno

us

end

emic

) 72

522

20

01

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp. 1

0 (i

nd

igen

ou

s n

on

-en

dem

ic)

7261

9*

20

01

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

sp. 1

1 (i

nd

igen

ou

s en

dem

ic)

8281

8

2005

Se

qu

ence

s n

ot

pu

blic

ly a

vaila

ble

Inocy

be

sp

. 12

(in

dig

eno

us

end

emic

) 71

267

20

00

Seq

uen

ces

no

t p

ub

licly

ava

ilab

le

Inocy

be

stro

bil

om

yces

(in

dig

eno

us

end

emic

) 72

683*

2001

H

M06

0322

, HM

0603

21

Co

mm

on

co

ntr

ol s

pec

ies

(see

Met

ho

ds)

Inocy

be

um

bro

sa

2713

1 T

19

68

Co

nta

min

atin

g D

NA

Inocy

be

um

bro

sa (

ind

igen

ou

s en

dem

ic)

7252

1

2001

G

U23

3355

Ph

aeo

collyb

ia lon

gipes

(in

dig

eno

us

end

emic

) 27

100

T

1968

N

o D

NA

iso

late

d

Ph

aeo

collyb

ia m

inu

ta (

ind

igen

ou

s en

dem

ic)

2709

9 T

19

69

Co

nta

min

atin

g D

NA

Ru

ssu

la p

udori

na

(in

dig

eno

us

end

emic

) 26

574

T

1967

C

on

tam

inat

ing

DN

A

Tyl

opil

us

form

osu

s (i

nd

igen

ou

s n

on

-en

dem

ic)

7263

7*

20

01

HM

0603

20, H

M06

0319

C

om

mo

n c

on

tro

l sp

ecie

s (s

ee M

eth

od

s)

Appen

dix

1 c

on

tin

ued

* D

NA

fro

m t

issu

e sa

mp

le s

tore

d in

CT

AB

bu

ffer

.

Page 26: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

24 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

Appendix 2

A L L S P e C I e S R e V I e W e D I N T H I S P R O J e C T W I T H N O T e S O N R e C O M M e N D e D C H A N G e S T O S T A T U S ( I F A N y )

Page 27: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

25Science for Conservation 306

SPe

CIe

S D

NA

DA

TA

Ge

Ne

RA

Te

D?

NO

Te

S

Ast

rosp

ori

na

aeq

ua

lis

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; ret

ain

Ast

rosp

ori

na

am

ygda

lin

a (

ind

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d

Ast

rosp

ori

na

ave

lla

na

(in

dig

eno

us

no

n-e

nd

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Ast

rosp

ori

na

gra

veole

ns

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; sev

eral

rec

ent

colle

ctio

ns,

bu

t m

ust

be

som

e d

ou

bt

ove

r th

eir

iden

tity

;

reta

in o

n li

st

Ast

rosp

ori

na

lep

tosp

erm

i (i

nd

igen

ou

s en

dem

ic)

Se

vera

l co

llect

ion

s re

ferr

ed t

o t

his

sp

ecie

s, b

ut

do

ub

t ab

ou

t so

me

of

the

iden

tifi

cati

on

s, r

etai

n o

n li

st

Ast

rosp

ori

na

ma

nu

ka

nea

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

Ast

rosp

ori

na

pa

race

rasp

hora

(in

dig

eno

us

no

n-e

nd

emic

)

Ret

ain

Ast

rosp

ori

na

str

am

inea

(in

dig

eno

us

end

emic

)

Ret

ain

Ast

rosp

ori

na

su

bcl

ava

ta (

ind

igen

ou

s en

dem

ic)

y

No

tR

FLP

mat

ches

; few

co

llect

ion

s, a

ll co

llect

ion

s in

Nel

son

Dis

tric

t; r

etai

n

Ast

rosp

ori

na

vis

cata

(in

dig

eno

us

end

emic

)

Ret

ain

Bole

tellu

s a

na

na

s (e

xo

tic)

exo

tic;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Bole

tus

nova

e-ze

lan

dia

e (i

nd

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d

Ca

locy

be

on

ych

ina

(in

dig

eno

us

no

n-e

nd

emic

)

Un

pu

blis

hed

info

rmal

her

bar

ium

nam

e; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Ca

locy

be

rea

dia

e (i

nd

igen

ou

s en

dem

ic)

U

np

ub

lish

ed in

form

al h

erb

ariu

m n

ame;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Ca

ma

roph

yllu

s ca

nu

s (i

nd

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d f

rom

typ

e; s

om

e fr

om

a P

at L

eon

ard

co

llect

ion

iden

tifi

ed a

s th

is s

pec

ies,

bu

t in

str

ange

pla

ce o

n I

TS

tree

Ca

ma

roph

yllu

s del

ica

tus

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

Ca

ma

roph

yllu

s gr

iseo

rufe

scen

s (i

nd

igen

ou

s en

dem

ic)

y

No

tR

FLP

mat

ches

; bo

th c

olle

ctio

ns

fro

m A

K

Ca

ma

roph

yllu

s im

pu

rus

(in

dig

eno

us

end

emic

) y

N

o t

RFL

P m

atch

es; f

ou

r w

ides

pre

ad c

olle

ctio

ns

in N

an

d S

Isl

and

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Ca

ma

roph

yllu

s pa

tin

icolo

r (i

nd

igen

ou

s en

dem

ic)

A

no

ther

rec

ent

AK

co

llect

ion

, no

w f

ive

in P

DD

; rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cla

vari

a m

usc

ulo

spin

osa

(in

dig

eno

us

end

emic

)

Per

hap

s o

nly

th

ree

auth

enti

cally

iden

tifi

ed c

olle

ctio

ns;

ret

ain

Cla

vari

a p

hoen

icea

var

. per

sici

na

(in

dig

eno

us

no

n-e

nd

emic

)

Fou

r co

llect

ion

s, b

ut

per

hap

s d

ou

bt

ove

r ac

cura

cy o

f so

me

iden

tifi

cati

on

s; r

etai

n

Cla

vuli

na

alu

tace

osi

cces

cen

s (i

nd

igen

ou

s en

dem

ic)

R

etai

n

Cla

vuli

na

bru

nn

eoci

ner

ea (

Ind

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cla

vuli

na

copio

socy

stid

iata

(in

dig

eno

us

end

emic

)

Ret

ain

Cla

vuli

na

cri

sta

ta v

ar. z

eala

ndic

a (

ind

igen

ou

s en

dem

ic)

N

ow

th

ree

po

ssib

le c

olle

ctio

ns;

ret

ain

Cla

vuli

na

geo

gloss

oid

es (

ind

igen

ou

s n

on

-en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cla

vuli

na

hu

mil

is (

ind

igen

ou

s n

on

-en

dem

ic)

R

etai

n

Cla

vuli

na

lev

eillei

var

. a

tric

ha

(in

dig

eno

us

no

n-e

nd

emic

)

Ret

ain

Cla

vuli

na

pu

rpu

rea

(in

dig

eno

us

end

emic

)

Ret

ain

Cla

vuli

na

sa

mu

elsi

i (i

nd

igen

ou

s en

dem

ic)

Se

vera

l rec

ent

colle

ctio

ns,

bu

t d

ou

bt

ove

r id

enti

ty o

f so

me;

ret

ain

Cla

vuli

na

sep

tocy

stid

iata

(in

dig

eno

us

end

emic

)

Ret

ain

Cla

vuli

na

urn

iger

oba

sidia

ta (

ind

igen

ou

s en

dem

ic)

R

etai

n

Cort

ina

riu

s a

egro

tus

(in

dig

eno

us

end

emic

) y

N

um

ero

us

t-R

FLP

mat

ches

; als

o a

no

ther

DN

A-b

ased

mat

ch; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s a

eru

gin

eoco

nic

us

(in

dig

eno

us

end

emic

) y

So

me

un

cert

ain

t-R

FLP

mat

ches

Cort

ina

riu

s a

na

uen

sis

(in

dig

eno

us

end

emic

) y

N

um

ero

us

t-R

FLP

mat

ches

, do

ub

tfu

lly d

isti

nct

fro

m C

. ma

rmora

tus;

ret

ain

un

til t

axo

no

my

reso

lved

Con

tin

ued

nex

t pa

ge

Page 28: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

26 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

SPe

CIe

S D

NA

DA

TA

Ge

Ne

RA

Te

D?

NO

Te

S

Cort

ina

riu

s a

ura

nti

ofe

rreu

s (i

nd

igen

ou

s en

dem

ic)

N

ow

fiv

e w

ides

pre

ad c

olle

ctio

ns

fro

m b

oth

N a

nd

S I

slan

ds;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s a

ust

rocy

an

ites

(in

dig

eno

us

no

n-e

nd

emic

) y

O

ne

ten

tati

ve t

-RFL

P m

atch

; now

four

col

lect

ion

s w

ides

pre

ad in

S I

slan

d; r

emo

ve f

rom

Dat

a D

efic

ien

t ca

tego

ry

Cort

ina

riu

s bel

lus

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s ca

rbon

ellu

s (i

nd

igen

ou

s en

dem

ic)

y

Som

e d

ou

btf

ul t

-RFL

P m

atch

es; r

etai

n

Cort

ina

riu

s ca

ryoti

s (i

nd

igen

ou

s en

dem

ic)

y

Ten

tati

ve t

RFL

P m

atch

es, b

ut

per

hap

s n

ot

un

iqu

e; r

ecen

t co

llect

ion

s fr

om

Tau

po

(p

revi

ou

sly

mis

iden

tifi

ed, r

edet

erm

ined

on

th

e b

asis

of

DN

A)

and

Gis

bo

rne;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry,

mo

re t

han

fo

ur

colle

ctio

ns,

fro

m s

ever

al C

rosb

y d

istr

icts

Cort

ina

riu

s ca

sta

nei

ceps

(in

dig

eno

us

end

emic

) y

N

o t

RFL

P m

atch

es; k

no

wn

on

ly f

rom

nea

r th

e su

mm

it o

f H

autu

ru/L

ittl

e B

arri

er I

slan

d

Cort

ina

riu

s ch

rysm

a (

ind

igen

ou

s en

dem

ic)

y

Der

mocy

be

ali

ena

ta a

nd

C. c

hry

sma

wit

h s

ame

tRFL

P, m

any

mat

ches

to

th

is; C

. ch

rysm

a a

lso

mat

ches

P

DD

727

67 (

TO

) o

n b

asis

of

DN

A c

om

par

iso

n, w

ith

at

leas

t th

ree

oth

er c

olle

ctio

ns

in P

DD

, an

d S

oo

p (

2006

)

n

ote

d a

s co

mm

on

; rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s co

llyb

ian

us

(in

dig

eno

us

end

emic

) y

O

ne

tRFL

P m

atch

, sev

eral

rec

ent

colle

ctio

ns;

So

op

(20

06)

con

sid

ered

it c

om

mo

n; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry; P

DD

727

18 id

enti

fied

by

Ho

rak

as C

. collyb

ian

us

is s

om

eth

ing

else

; PD

D 8

9033

,

id

enti

fied

(in

corr

ectl

y?)

as C

. ver

on

ica

e m

atch

es b

y t-

RFL

P

Cort

ina

riu

s cr

emeo

lin

us

(in

dig

eno

us

end

emic

)

Nu

mer

ou

s re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s cu

cum

eris

(in

dig

eno

us

end

emic

) y

U

np

ub

lish

ed in

form

al h

erb

ariu

m n

ame

(so

met

imes

ref

erre

d t

o a

s M

yxa

ciu

m c

ucm

eris

, an

oth

er

info

rmal

, un

pu

blis

hed

nam

e); s

ever

al d

ou

btf

ul t

-RFL

P m

atch

es; s

ever

al r

ecen

t co

llect

ion

s fr

om

man

y

regi

on

s h

ave

bee

n t

agge

d w

ith

th

is n

ame;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s cu

pre

on

atu

s (i

nd

igen

ou

s en

dem

ic)

y

No

au

then

tic

DN

A, n

o t

RFL

P m

atch

es, b

ut

Soo

p (

per

s. c

om

m.)

iden

tifi

ed t

wo

ad

dit

ion

al H

ora

k sp

ecim

ens

(ex

TO

, GB

); a

no

ther

nin

e co

llect

ion

s in

PD

D; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s cy

cneu

s (i

nd

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s dys

odes

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es; o

nly

tw

o a

uth

enti

c co

llect

ion

s; r

etai

n

Cort

ina

riu

s ex

lugu

bri

s (i

nd

igen

ou

s en

dem

ic)

y

Som

e d

ou

btf

ul t

RFL

P m

atch

es; o

nly

on

e au

then

tic

colle

ctio

n in

PD

D

Cort

ina

riu

s ge

mm

eus

(in

dig

eno

us

end

emic

)

No

au

then

tic

DN

A; a

Cort

ina

riu

s cf

. gem

meu

s co

llect

ion

rep

rese

nts

a d

isti

nct

, un

des

crib

ed s

pec

ies

Cort

ina

riu

s ig

notu

s (i

nd

igen

ou

s en

dem

ic)

D

NA

do

ub

tfu

lly a

uth

enti

c (g

ot

no

ne

fro

m t

he

typ

e); r

etai

n

Cort

ina

riu

s in

doli

cus

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s lu

bri

can

esce

ns

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; bu

t n

ow

fiv

e co

llect

ion

s in

PD

D w

ides

pre

ad t

hro

ugh

S I

slan

d; r

emo

ve

fr

om

Dat

a D

efic

ien

t ca

tego

ry

Cort

ina

riu

s m

arm

ora

tus

(in

dig

eno

us

end

emic

) y

N

um

ero

us

t-R

FLP

mat

ches

, bu

t d

ou

btf

ully

dis

tin

ct f

rom

C. a

na

uen

sis;

ret

ain

un

til t

axo

no

my

reso

lved

Cort

ina

riu

s m

elim

yxa

(in

dig

eno

us

end

emic

)

No

au

then

tic

DN

A (

a C

ort

ina

riu

s cf

. mel

imyx

a c

olle

ctio

n r

epre

sen

ts a

n u

nd

escr

ibed

sp

ecie

s)

Cort

ina

riu

s m

inosc

au

rus

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es; p

erh

aps

mo

ve

to h

igh

er t

hre

at c

ateg

ory

Cort

ina

riu

s n

aph

tha

lin

us

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es; s

ingl

e co

llect

ion

; ret

ain

Cort

ina

riu

s olo

rin

atu

s (i

nd

igen

ou

s en

dem

ic)

y

DN

A n

ot

succ

essf

ully

am

plif

ied

fro

m T

ype,

bu

t so

me

fro

m a

sp

ecim

en id

enti

fied

as

this

by

Ho

rak

(no

t

yet

in P

DD

); n

o t

RFL

P m

atch

es; s

ever

al c

olle

ctio

ns

in P

DD

bu

t so

me

do

ub

tfu

l id

enti

fica

tio

ns;

ret

ain

Cort

ina

riu

s pa

pa

ver

(in

dig

eno

us

no

n-e

nd

emic

) y

N

o t

-RFL

P m

atch

es; o

ne

add

itio

nal

co

llect

ion

fro

m A

K (

red

eter

min

atio

n b

ased

on

DN

A c

om

par

iso

n);

ret

ain

Cort

ina

riu

s per

au

reu

s (i

nd

igen

ou

s en

dem

ic)

N

o a

uth

enti

c D

NA

; man

y re

cen

t co

llect

ion

s (i

ncl

ud

ing

on

ex

Ho

rak

iden

tifi

ed b

y So

op

, per

s. c

om

m.)

;

re

mo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s per

eleg

an

s (i

nd

igen

ou

s en

dem

ic)

y

On

e te

nta

tive

tR

FLP

mat

ch; S

oo

p (

2006

) n

ote

d a

s ‘f

airl

y co

mm

on

’, b

ut

few

au

then

tica

lly id

enti

fied

co

llect

ion

s in

PD

D; r

etai

n o

n li

st

Appen

dix

2 c

on

tin

ued

Con

tin

ued

nex

t pa

ge

Page 29: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

27Science for Conservation 306

SPe

CIe

S D

NA

DA

TA

Ge

Ne

RA

Te

D?

NO

Te

S

Cort

ina

riu

s per

icly

men

us

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es; S

oo

p (

2006

) n

ote

d a

s ‘f

airl

y co

mm

on

’ bu

t o

nly

tw

o c

olle

ctio

ns

in P

DD

; ret

ain

Cort

ina

riu

s per

sica

nu

s (i

nd

igen

ou

s n

on

-en

dem

ic)

y

Seve

ral t

-RFL

P m

atch

es, b

ut

cou

ld b

e o

ne

of

seve

ral s

pec

ies;

on

ly t

wo

co

llect

ion

s P

DD

; ret

ain

Cort

ina

riu

s ph

aeo

chlo

rus

(in

dig

eno

us

end

emic

)

Sin

gle

AK

co

llect

ion

Cort

ina

riu

s ph

oli

ote

llu

s (i

nd

igen

ou

s en

dem

ic)

T

wo

co

llect

ion

s fr

om

a s

ingl

e lo

calit

y; p

erh

aps

mo

ve

to h

igh

er t

hre

at s

tatu

s

Cort

ina

riu

s pic

oid

es (

ind

igen

ou

s en

dem

ic)

y

Tw

o p

oss

ible

t-R

FLP

mat

ches

, an

oth

er D

NA

mat

ch t

o t

wo

Tau

po

sp

ecim

ens,

to

geth

er w

ith

fo

ur

oth

er

Sou

th I

slan

d c

olle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s porp

hyr

oph

aeu

s (i

nd

igen

ou

s en

dem

ic)

y

On

e d

ou

btf

ul t

-RFL

P m

atch

; kn

ow

n f

rom

tw

o f

ar-a

par

t C

rosb

y D

istr

icts

; few

au

then

tica

lly id

enti

fied

co

llect

ion

s; r

etai

n f

or

no

w

Cort

ina

riu

s ra

ttin

us

(In

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es; a

sin

gle

auth

enti

c co

llect

ion

; ret

ain

Cort

ina

riu

s ro

tun

dis

poru

s su

bsp

. noth

ofa

gi (

ind

igen

ou

s en

dem

ic)

N

ow

cal

led

C. t

essi

ae;

sev

en c

olle

ctio

ns

in P

DD

; So

op

(20

06)

rega

rded

as

com

mo

n; r

emo

ve

fro

m D

ata

D

efic

ien

t ca

tego

ry

Cort

ina

riu

s sa

turn

ioru

m (

ind

igen

ou

s en

dem

ic)

y

Seve

ral t

-RFL

P m

atch

es, b

ut

can

no

t d

isti

ngu

ish

Der

mocy

be

larg

ofu

lgen

s an

d C

. sa

turn

ioru

m; n

ow

fiv

e

co

llect

ion

s in

PD

D; r

emo

ve

C. s

atu

rnio

rum

fro

m D

ata

Def

icie

nt

cate

go

ry a

nd

leav

e D

. la

rgofu

lgen

s

(t

he

Typ

e, f

rom

AK

, is

the

on

ly k

no

wn

sp

ecim

en)

Cort

ina

riu

s si

na

pic

olo

r (i

nd

igen

ou

s n

on

-en

dem

ic)

y

On

e co

llect

ion

iden

tifi

ed b

y H

ora

k, D

NA

mat

ches

an

oth

er c

olle

ctio

n m

isid

enti

fied

as

C. i

gnotu

s;

no

t-R

FLP

mat

ches

; ret

ain

Cort

ina

riu

s ta

ylori

an

us

(in

dig

eno

us

end

emic

)

Six

colle

ctio

ns fr

om N

and

S Is

land

s, S

oop

(20

06)

tage

d as

‘fai

rly

com

mon

’; re

mo

ve f

rom

Dat

a D

efic

ien

t ca

tego

ry

Cort

ina

riu

s u

rsu

s (i

nd

igen

ou

s en

dem

ic)

Se

vera

l rec

ent

colle

ctio

ns,

bu

t fe

w id

enti

fied

by

Soo

p; S

oo

p (

2006

) re

gard

ed a

s ra

re; r

etai

n f

or

mea

nti

me

Cort

ina

riu

s ve

ron

ica

e (i

nd

igen

ou

s n

on

-en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Cort

ina

riu

s vi

scil

aet

us

(in

dig

eno

us

end

emic

) y

O

ne

do

ub

tfu

l tFR

LP m

atch

; ret

ain

Cort

ina

riu

s vi

scost

ria

tus

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

; no

w t

wo

co

llect

ion

s; r

etai

n

Cort

ina

riu

s vi

scovi

ridis

(in

dig

eno

us

end

emic

)

Do

ub

tfu

l th

at D

NA

is a

uth

enti

c; n

o t

RFL

P m

atch

es; f

ew r

elia

bly

iden

tifi

ed c

olle

ctio

ns;

ret

ain

Cort

ina

riu

s vi

treo

pil

eatu

s (i

nd

igen

ou

s en

dem

ic)

y

On

e t-

RFL

P m

atch

; sev

eral

rec

ent

colle

ctio

ns,

an

oth

er m

isid

enti

fica

tio

n r

evea

led

by

DN

A s

equ

ence

s;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Der

mocy

be

ali

ena

ta (

ind

igen

ou

s en

dem

ic)

y

Der

mocy

be

ali

ena

ta a

nd

Cort

ina

riu

s ch

rysm

a w

ith

sam

e t-R

FLP

; man

y m

atch

es t

o t

his

; D. a

lien

ata

fro

m

six

co

llect

ion

s fr

om

fiv

e C

rosb

y D

istr

icts

; rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Der

mocy

be

au

ran

tiel

la (

ind

igen

ou

s en

dem

ic)

T

wo

co

llect

ion

s, a

uth

enti

city

of

on

e is

do

ub

tfu

l; re

tain

Der

mocy

be

au

rata

(in

dig

eno

us)

Un

pu

blis

hed

info

rmal

her

bar

ium

nam

e; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Der

mocy

be

card

ina

lis

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es, b

ut

oth

er D

NA

co

mp

aris

on

s re

veal

sev

eral

rec

ent

colle

ctio

ns,

in s

ever

al C

rosb

y

dis

tric

ts; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Der

mocy

be

cin

na

ba

rin

a (

ind

igen

ou

s n

on

-en

dem

ic)

y

Rec

ent

colle

ctio

ns

refe

rred

to

this

(eu

rop

ean

) n

ame

iden

tifie

d b

y So

op (

per

s. c

omm

.) a

s C

orti

nari

us

vero

nic

ae

var.

dil

utu

s; r

emo

ve

D. c

inn

aba

rin

a f

rom

Dat

a D

efic

ien

t ca

tego

ry; o

ccu

rren

ce in

New

Zea

lan

d u

nce

rtai

n.

Der

mocy

be

cra

mes

ina

(in

dig

eno

us

no

n-e

nd

emic

) y

N

o t

-RFL

P m

atch

es; r

etai

n

Der

mocy

be

egm

on

tia

na

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es; r

etai

n

Der

mocy

be

icte

rin

oid

es (

ind

igen

ou

s en

dem

ic)

y

Seve

ral d

ou

btf

ul t

-RFL

P m

atch

es; s

ingl

e co

llect

ion

in P

DD

; ret

ain

Der

mocy

be

indota

ta (

ind

igen

ou

s en

dem

ic)

Se

vera

l rec

ent

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Der

mocy

be

larg

ofu

lgen

s (i

nd

igen

ou

s en

dem

ic)

y

t-R

FLP

can

no

t d

isti

ngu

ish

D. l

arg

ofu

lgen

s an

d C

ort

ina

riu

s sa

turn

ioru

m; o

ne

add

itio

nal

D. l

arg

ofu

lgen

s

colle

ctio

n e

x T

O (

ID b

ased

on

DN

A c

om

par

iso

n o

f u

nid

enti

fied

Cort

ina

riu

s) t

o a

dd

to

th

e ty

pe

ex A

K

Der

mocy

be

lepto

sper

moru

m (

ind

igen

ou

s en

dem

ic)

y

t-R

FLP

no

t d

isti

nct

; no

ex

tra

dat

a; r

etai

n

Appen

dix

2 c

on

tin

ued

Con

tin

ued

nex

t pa

ge

Page 30: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

28 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

SPe

CIe

S D

NA

DA

TA

Ge

Ne

RA

Te

D?

NO

Te

S

Der

mocy

be

oli

vace

on

igra

(in

dig

eno

us

end

emic

) y

Se

vera

l ten

tati

ve t

-RFL

P m

atch

es; s

ever

al r

ecen

t co

llect

ion

s fr

om

No

rth

an

d S

ou

th I

slan

ds;

rem

ove

fro

m

Dat

a D

efic

ien

t ca

tego

ry

Der

mocy

be

pu

rpu

rata

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

bu

t n

ow

fo

ur

colle

ctio

ns

wid

esp

read

aro

un

d N

ew Z

eala

nd

; re

mo

ve

fro

m

Dat

a D

efic

ien

t ca

tego

ry

Der

mocy

be

sple

ndid

a (

ind

igen

ou

s n

on

-en

dem

ic)

y

Seve

ral t

-RFL

P m

atch

es b

ut

no

t u

niq

ue

(D. l

arg

ofu

lgen

s th

e sa

me)

; fo

ur

colle

ctio

ns,

all

in N

ort

h I

slan

d,

per

hap

s N

ort

h I

slan

d r

estr

icte

d, s

o f

urt

her

co

llect

ing

effo

rt n

eed

ed; r

etai

n

Der

mocy

be

vin

icolo

r (i

nd

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Der

mocy

be

visc

ida

(in

dig

eno

us)

Un

pu

blis

hed

info

rmal

her

bar

ium

nam

e; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Der

molo

ma

hem

isph

aer

icu

m (

ind

igen

ou

s en

dem

ic)

R

etai

n

Der

molo

ma

mu

rin

um

(in

dig

eno

us

end

emic

)

No

w t

hre

e co

llect

ion

s, d

ou

bt

abo

ut

iden

tity

of

som

e; r

etai

n

Gig

asp

erm

a c

rypti

ca (

ind

igen

ou

s en

dem

ic)

R

etai

n

Gli

oph

oru

s fu

moso

gris

eus

(in

dig

eno

us

end

emic

)

Ret

ain

Gli

oph

oru

s gr

am

inic

olo

r (i

nd

igen

ou

s n

on

-en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Gli

oph

oru

s li

laci

pes

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Gli

oph

oru

s lu

teogl

uti

nosu

s (i

nd

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Gli

oph

oru

s ost

rin

us

(in

dig

eno

us

end

emic

)

On

ly t

wo

au

then

tica

lly id

enti

fied

co

llect

ion

s; r

etai

n

Gli

oph

oru

s su

bh

eter

om

orp

hu

s (i

nd

igen

ou

s n

on

-en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Gli

oph

oru

s vi

sca

ura

nti

us

(in

dig

eno

us

end

emic

)

No

w f

ive

colle

ctio

ns

in P

DD

; rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Heb

elom

a m

edio

rufu

m (

ind

igen

ou

s en

dem

ic)

M

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

bla

nda

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

ceri

nolu

tea

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

eleg

an

s (i

nd

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

fuli

gin

ata

(in

dig

eno

us

end

emic

)

No

w f

ive

colle

ctio

ns

in P

DD

; geo

grap

hic

ally

wid

esp

read

; rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

fusc

oa

ura

nti

aca

(in

dig

eno

us

end

emic

)

No

w f

ive

colle

ctio

ns

in P

DD

; rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

juli

eta

e (i

nd

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

min

iata

(in

dig

eno

us

no

n-e

nd

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

min

icep

s (i

nd

igen

ou

s en

dem

ic)

A

t le

ast

six

co

llect

ion

s in

PD

D; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

rocy

be

stri

ato

lute

a (

ind

igen

ou

s en

dem

ic)

R

etai

n

Hyg

roph

oru

s ca

rch

ari

as

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; ret

ain

Hyg

roph

oru

s gl

ori

ae

(in

dig

eno

us

end

emic

)

Ret

ain

Hyg

roph

oru

s in

volu

tus

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Hyg

roph

oru

s se

greg

atu

s (i

nd

igen

ou

s en

dem

ic)

R

etai

n

Hyg

roph

oru

s w

aik

an

aen

sis

(in

dig

eno

us

end

emic

)

Ret

ain

Hys

tera

ngi

um

neg

lect

um

(in

dig

eno

us

no

n-e

nd

emic

)

Red

eter

min

atio

n o

f th

e si

ngl

e N

Z c

olle

ctio

n, n

ow

no

evi

den

ce t

hat

th

is s

pec

ies

occ

urs

in N

Z;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry?

Hys

tera

ngi

um

ru

pti

cuti

s (e

xo

tic)

exo

tic;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Inocy

be

cere

a (

ind

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; s

ever

al c

olle

ctio

ns

bu

t d

ou

bt

abo

ut

seve

ral o

f th

e id

enti

fica

tio

ns

Appen

dix

2 c

on

tin

ued

Con

tin

ued

nex

t pa

ge

Page 31: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

29Science for Conservation 306

SPe

CIe

S D

NA

DA

TA

Ge

Ne

RA

Te

D?

NO

Te

S

Inocy

be

des

tru

ens

(in

dig

eno

us

end

emic

)

No

au

then

tic

DN

A; o

ne

colle

ctio

n e

x C

live

Shir

ley

Inocy

be

late

rici

a (

ind

igen

ou

s n

on

-en

dem

ic)

D

NA

fro

m L

eon

ard

co

llect

ion

on

ly, d

ou

btf

ully

au

then

tic;

no

tR

FLP

cu

ttin

g si

tes;

th

ree

colle

ctio

ns

bu

t

tw

o d

ou

btf

ully

iden

tifi

ed

Inocy

be

lute

obu

lbosa

var

. lu

teobu

lbosa

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Inocy

be

lute

obu

lbosa

var

. volv

ata

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; ret

ain

Inocy

be

men

dic

a (

ind

igen

ou

s en

dem

ic)

K

no

wn

fro

m t

ype

on

ly; r

etai

n

Inocy

be

ph

aeo

squ

arr

osa

(in

dig

eno

us

end

emic

)

Ret

ain

Inocy

be

ren

ispora

(in

dig

eno

us

end

emic

)

Ret

ain

Inocy

be

sca

bri

usc

ula

(in

dig

eno

us

end

emic

) y

N

o t

-RFL

P m

atch

es; r

etai

n

Inocy

be

um

bro

sa (

ind

igen

ou

s en

dem

ic)

y

DN

A n

ot

succ

essf

ully

am

plif

ied

fro

m T

ype,

bu

t go

od

fro

m a

no

ther

Ho

rak

spec

imen

; no

tR

FLP

mat

ches

;

so

me

do

ub

t o

ver

iden

tifi

cati

on

of

som

e co

llect

ion

s; r

etai

n

Neo

hyg

rocy

be

inn

ata

(in

dig

eno

us

end

emic

)

Ret

ain

Neo

hyg

rocy

be

squ

arr

osa

(in

dig

eno

us

end

emic

)

Ret

ain

Ph

aeo

collyb

ia lon

gipes

(in

dig

eno

us

end

emic

)

Seve

ral r

ecen

t, w

ides

pre

ad c

olle

ctio

ns,

ret

ain

fo

r n

ow

, will

pro

bab

ly b

e re

mo

ved

late

r

Ph

aeo

collyb

ia m

inu

ta (

ind

igen

ou

s en

dem

ic)

Se

vera

l rec

ent

colle

ctio

ns

bu

t d

ou

bts

ove

r id

enti

fica

tio

ns;

ret

ain

Ple

uro

collyb

ia c

rem

ea (

ind

igen

ou

s en

dem

ic)

Se

vera

l rec

ent

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Porp

olo

ma

am

yloid

eum

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

Ra

ma

ria

am

big

ua

(in

dig

eno

us

end

emic

)

Seve

ral r

ecen

t co

llect

ion

s; p

erh

aps

do

ub

t ab

ou

t id

enti

fica

tio

n; r

etai

n

Ra

ma

ria

an

zia

na

(in

dig

eno

us

end

emic

)

Ret

ain

Ra

ma

ria

gig

an

tea

f. t

enu

ispora

(in

dig

eno

us

end

emic

)

Seve

ral r

ecen

t co

llect

ion

s fr

om

No

rth

an

d S

ou

th I

slan

ds;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Ra

ma

ria

pa

nca

ribbea

(in

dig

eno

us

no

n-e

nd

emic

)

Th

ree

colle

ctio

ns,

geo

grap

hic

ally

wid

esp

read

; ret

ain

fo

r m

ean

tim

e

Ra

ma

ria

per

flu

opu

nic

ea (

ind

igen

ou

s en

dem

ic)

R

etai

n

Ra

ma

ria

pu

rpu

reopa

llid

a (

ind

igen

ou

s en

dem

ic)

Si

x P

DD

co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Ra

ma

ria

rotu

ndis

pora

(in

dig

eno

us

end

emic

)

Ret

ain

Ra

ma

ria

sa

mu

elsi

i (i

nd

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Ra

ma

ria

zip

pel

ii f

. aer

ugi

nosa

(in

dig

eno

us

no

n-e

nd

emic

)

Ret

ain

Ra

ma

ria

zip

pel

ii f

. zip

pel

ii (

ind

igen

ou

s n

on

-en

dem

ic)

Se

vera

l rec

ent

PD

D c

olle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Ra

ma

riopsi

s a

gglu

tin

ata

(in

dig

eno

us

end

emic

)

Ret

ain

Ra

ma

riopsi

s a

luta

cea

(in

dig

eno

us

end

emic

)

Ret

ain

Ra

ma

riopsi

s cr

emic

olo

r (i

nd

igen

ou

s en

dem

ic)

R

etai

n

Ra

ma

riopsi

s cr

oce

a (

ind

igen

ou

s n

on

-en

dem

ic)

N

ow

th

ree

colle

ctio

ns;

ret

ain

Ra

ma

riopsi

s dep

oken

sis

f. p

ersi

cin

a (

ind

igen

ou

s en

dem

ic)

R

etai

n

Ra

ma

riopsi

s ju

nqu

ille

a (

ind

igen

ou

s en

dem

ic)

R

etai

n

Ra

ma

riopsi

s lo

ngi

pes

(in

dig

eno

us

end

emic

)

Ret

ain

Ra

ma

riopsi

s ovi

spora

(in

dig

eno

us

end

emic

)

Ret

ain

Ra

ma

riopsi

s ra

ma

rioid

es (

ind

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Rh

odocy

be

an

tipoda

(in

dig

eno

us

end

emic

)

DN

A n

ot

succ

essf

ully

am

plif

ied

; man

y re

cen

t co

llect

ion

s; r

emo

ve

fro

m D

ata

Def

icie

nt

cate

go

ry

Appen

dix

2 c

on

tin

ued

Con

tin

ued

nex

t pa

ge

Page 32: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

30 Johnston et al.—Using molecular techniques to combine taxonomic and ecological data for fungi

SPe

CIe

S D

NA

DA

TA

Ge

Ne

RA

Te

D?

NO

Te

S

Rh

odocy

be

con

cha

ta (

ind

igen

ou

s en

dem

ic)

R

etai

n

Rh

odocy

be

din

gley

ae

(in

dig

eno

us

end

emic

)

Per

hap

s n

ow

tw

o c

olle

ctio

ns;

ret

ain

Rh

odocy

be

fuli

gin

ea (

ind

igen

ou

s n

on

-en

dem

ic)

R

etai

n

Rh

odocy

be

pip

erit

a (

exo

tic)

exo

tic;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Ru

ssu

la m

ult

icys

tidia

ta (

ind

igen

ou

s en

dem

ic)

D

NA

no

t su

cces

sfu

lly a

mp

lifie

d; m

any

rece

nt

colle

ctio

ns;

rem

ove

fro

m D

ata

Def

icie

nt

cate

go

ry

Th

axt

eroga

ster

vio

la (

ind

igen

ou

s en

dem

ic)

R

etai

n

Tim

grove

a r

etic

ula

ta (

ind

igen

ou

s n

on

-en

dem

ic)

N

ow

tw

o c

olle

ctio

ns;

ret

ain

Appen

dix

2 c

on

tin

ued

Page 33: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

31Science for Conservation 306

SPeCIeS DNA DATA? NOTeS

Cortinarius anisodorus (indigenous endemic) Three collections; add to Data Deficient category

Cortinarius atrolazulinus (indigenous endemic) Three collections, North and South Islands; Soop (2006)

considered it rare; add to Data Deficient category

Cortinarius atroviolaceus (indigenous non-endemic) One or two collections; add to Data Deficient category

Cortinarius coneae (indigenous endemic) One or two collections; add to Data Deficient category

Cortinarius dulciolens (indigenous endemic) Only two collections; add to Data Deficient category

Cortinarius dulciorum (indigenous endemic) Single collection; add to Data Deficient category

Cortinarius flavidulus (indigenous endemic) Single collection; add to Data Deficient category

Cortinarius gymnocephalus (indigenous endemic) Two collections; add to Data Deficient category

Cortinarius incensus (indigenous endemic) Only two collections; add to Data Deficient category

Cortinarius lamproxanthus (indigenous endemic) Two collections, one area; add to Data Deficient category

Cortinarius leucocephalus (indigenous non-endemic) Few collections, add to Data Deficient category

Cortinarius luteobrunneus (indigenous endemic) Few collections; add to Data Deficient category

Cortinarius melleomitis (indigenous non-endemic) Three collections; add to Data Deficient category

Cortinarius myxenosma (indigenous endemic) Two collections; add to Data Deficient category

Cortinarius nivalis (indigenous endemic) Few collections; add to Data Deficient category

Cortinarius ohauensis (indigenous endemic) Few collections; add to Data Deficient category

Cortinarius orixanthus (indigenous) Few certain IDs; add to Data Deficient category

Cortinarius paraonui (indigenous endemic) Three collections; add to Data Deficient category

Cortinarius pectochelis (indigenous endemic) Three collections; add to Data Deficient category

Cortinarius pisciodorus (indigenous endemic) Two collections; add to Data Deficient category

Cortinarius sarchinochrous (indigenous endemic) Now four collections; because these truffle-like species are

intensively sought but rarely found; add to Data Deficient

category

Cortinarius suecicolor (indigenous endemic) Four collections, some uncertainty over identity of some;

add to Data Deficient category

Cortinarius thaumastus (indigenous endemic) Few collections; add to Data Deficient category

Cortinarius tigrellus (indigenous endemic) Few collections; add to Data Deficient category

Cortinarius violaceovolvatus (indigenous endemic) Three collections; add to Data Deficient category

Inocybe strigiceps (indigenous non-endemic) y No t-RFLP matches; two, perhaps three, collections in PDD;

add to Data Deficient category

Labyrinthomyces varius (indigenous non-endemic) Three collections; add to Data Deficient category

Laccaria amethystina (indigenous non-endemic) Several collections PDD, but uncertain identifications;

add to Data Deficient category

Ramaria sclerocarnosa (indigenous endemic) Few collections; add to Data Deficient category

Ramariopsis luteotenerrima (indigenous non-endemic) Several collections, but doubt over identifications;

add to Data Deficient category

Ramariopsis novohibernica (indigenous non-endemic) Few collections; add to Data Deficient category

Russula pudorina (indigenous endemic) Five collections, all in AK; add to Data Deficient category

Russula rubrolutea (indigenous endemic) Three collections; add to Data Deficient category

Russula tapawera (indigenous endemic) Four collections but all from same locality; either add to Data

Deficient category or consider for higher threat status;

macroscopically distinctive species of intensively targeted group

Appendix 3

A D D I T I O N S T O T H e D A T A D e F I C I e N T L I S T

Most of these species were described after the original 2002 assessment. In most

cases, recently described species of mushrooms in New Zealand taxonomic

studies are based on one or a few herbarium specimens.

Page 34: Using molecular techniques to combine taxonomic and ... · • Utilising DNA data to integrate taxonomic and ecological datasets to maximise the distribution data available for these

Novel taxonomic methods enable better understanding of fungal distributions for threat classification system lists

Molecular methods were used to combine ecological and taxonomic data sets for a group of ectomycorrhizal fungal species. Sequences and t-RFLP patterns from the ITS region were generated from reliably identified herbarium specimens and used to recognise when these species appeared in samples collected in ecological studies, so providing large numbers of additional distribution records for these species. A new listing of Data Deficient ectomycorrhizal fungal species was produced.

Johnston, P.; Park, D.; Dickie. I.; Walbert, K. 2010: Using molecular techniques to combine taxonomic and ecological data for fungi: reviewing the Data Deficient fungi list, 2009. Science for Conservation 306. Department of Conservation, Wellington. 31 p.