3,000 species and no end – species richness and community
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8/4/2019 3,000 species and no end – species richness and community
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ORIGINAL ARTICLE
3,000 species and no end – species richness and community
pattern of woodland macrofungi in Mecklenburg-Western
Pomerania, Germany
Martin Unterseher & Benno Westphal &
Norbert Amelang & Florian Jansen
Received: 17 March 2011 /Revised: 18 May 2011 /Accepted: 25 May 2011# German Mycological Society and Springer 2011
Abstract In addition to newly generated and continuously
growing datasets in mycological research, existing compi-lations are of high value to assess the fungi of a wholeregion. In the present study, a private database with ca.65,000 entries of macromycetous fruit body observations inMecklenburg-Western Pomerania, Germany, was analysed.Observed species richness of tree-associated mycorrhizaland saprobic fungi exceeded 3,000 taxa. The total fungalspecies richness could not be determined with confidence
but will possibly exceed 4,000. Distinct species turnover with respect to host trees was observed. However, the rateof community overlap clearly differed between mycorrhizaland saprobic fungi and deciduous and coniferous trees. By
separating the data into abundant core species and rare
satellite taxa potential indicator species are presented,whose preservation will be beneficial to many other fungiand the entire ecosystems they live in.
Keywords Biodiversity survey. Volunteers . Indicator species . Community ecology. Species richness estimation
Introduction
Most terrestrial habitats are known to rely on fungi for key parts in the nutrient recycling process. It is mainly their
decomposing and mineralisation activities that createimportant habitats for many micro-organisms, protists,fungi, and arthropods. Their important trophic role not-withstanding, fungi remain a poorly understood kingdom of the eukaryotic tree of life with respect to species richness,species composition and ecological functionality of species(Molina et al. 2011). Their abundance in virtually allecosystems with wooden substrata has been fully realizedonly in the last few decades (Lonsdale et al. 2008;Ovaskainen et al. 2010).
Apart from biological reasons for this lack of knowledge(cryptic fungal life as subterranean mycelium), further argu-
ments are found in a comparatively low societal relevance of fungi (many fungi, such as moulds and poisonous agarics are
perceived negatively by the European public) and in the politics of science, which are partly responsible for the limitednumber of mycologists with taxonomic expertise that areemployed. Because biodiversity research is generally under-funded with significant lack of manpower, the use of volunteers is becoming increasingly important in thesescientific areas (Lovell et al. 2009). Especially in Germanythere exists a long tradition of high-quality data collection by
Electronic supplementary material The online version of this article(doi:10.1007/s11557-011-0769-7) contains supplementary material,which is available to authorized users.
M. Unterseher (*)Dept. of Systematic Botany, Insitute of Botany and LandscapeEcology, Ernst-Moritz-Arndt University,Grimmer Str. 88,17487 Greifswald, Germanye-mail: martin.unterseher@uni-greifswald.de
B. Westphal
Fachgruppe Mykologie Vorpommern,Potthäger Damm 13,17498 Weitenhagen, Germany
N. Amelang Neuhofer Weg 6,23996 Neuhof/Bobitz, Germany
F. JansenDept. of Landscape Ecology, Insitute of Botany and LandscapeEcology, Ernst-Moritz-Arndt University,Grimmer Str. 88,17487 Greifswald, Germany
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hundreds of amateur mycologists for many decades, leadingto the accumulation of millions of data of macrofungal (fruit
body) occurrence. Such information was, for instance, usedto compile distribution atlases of macrofungi in Germany(Krieglsteiner 1991, 1993), various Red Lists (e.g. Anon1992; Schwik and Westphal 1999; Schmitt 2007), or therecent Funga of Saxony-Anhalt (Täglich 2009).
The analyses of such comprehensive datasets with new andenhanced statistical tools is of particular importance for theurgently needed updates of regional, national and globalspecies richness (Hawksworth 1991; Hawksworth andRossman 1997; Mueller et al. 2007). Nearly all existingextrapolations of fungal species richness are based on a number of assumptions such as ratios of fungi to their associated hosts, anamorph – teleomorph relationships, or theconsideration of understudied fungal groups and habitats(Hawksworth 2001; Fröhlich and Hyde 1999). Consequently,species richness estimations differ strongly, depending on thetaxonomic group, the geographical area under investigation,
and the number of specialists involved in the surveys. Thishas led to sceptical considerations with respect to credibilityof species richness estimations (May 1991). In addition,undersampling might prevent meaningful estimations of anyorganism's species richness (Coddington et al. 2009). Onlyrecently, microbiologists, protistologists and mycologists
became aware of new, promising methods to extrapolatetotal species richness (Bohannan and Hughes 2003; Uglandet al. 2003; Chao et al. 2006) from physical species(Unterseher et al. 2008), molecular operational taxonomicunits (Jumpponen and Jones 2009) or from cultured isolates(Joshee et al. 2009; Unterseher and Schnittler 2010). The
next generation sequencing technologies have, more thanother methodologies, the potential to overcome undersam-
pling thus launching a new era of fungal diversity research(Öpik et al. 2009; Amend et al. 2010; Unterseher et al. 2011).
It is the large number of observed fungal species,especially the many rare and rarest ones (‘rare biosphere’)that further complicates statistical analysis and communi-cation of results (Novotny and Basset 2000; Cunninghamand Lindenmayer 2005; Reeder and Knight 2009). In the1980s, the concept of core and satellite species wasintroduced by Hanski (1982) to cope with the problematicanalysis of too strongly varying abundances of species
within a natural community.In theory, Hanski's approach distinguishes between species
with differing niche requirements: an abundant, enduringgroup of species (the core group) and a more diverse, variableand transient component of the community (the satellite/ occasional group) (Hanski 1982; Magurran and Henderson2003; Ulrich and Zalewski 2006). Recently, this theory was
picked up by Pedrós-Alió (2006), Dolan et al. (2009) andUnterseher et al. (2011) to analyse the 'rare biosphere' of marine bacteria, planctonic ciliates and fungi, respectively.
Apart from generating new and continuously growingdatasets, legacy data are of high value. Many specimensare preserved in stand-alone fungal culture collections,
public exsiccaria at Universities and botanic gardens andlinked to curated online databases and further webresources (Wilkinson and Foster 2004; Crous et al. 2004;Abarenkov et al. 2010). Moreover, there exist dozens of
private exsiccaria and even more voluminous digitaliseddatasets and printed card indices owned and maintained byhighly experienced amateur mycologists.
For the present study, we used existing data about theoccurrence of macromycetes and concentrated on specieswith mycorrhizal, saprobic, pathogenetic and otherwiseunknown modes and degrees of association to woodensubstrata in Mecklenburg-Western Pomerania (MV). Weaimed at testing the following hypotheses: (1) the present data gathered by volunteers allow analyses of fungalcommunity ecology, i.e. of species richness, speciesturnover and host preferences; (2) species richness
estimators allow serious predictions of total speciesrichness of tree-associated macrofungi in MV; and (3)the separate analysis of abundant fungal ‘core’ and rare‘satellite’ species (Magurran and Henderson 2003) helpsto define indicator taxa for species, habitat and landscapeconservation, irrespective of undersampling or an opencommunity structure with a high temporal or spatialspecies turnover.
Materials and methods
Basic geobotanical data of the collection area Mecklenburg-Western Pomerania
The German state Mecklenburg-Western Pomerania (MV)is located in the very northeast of the country (Fig. 1). It covers an area of 23,180 km2 and has the lowest populationdensity of all German states with 72 inhabitants per km2
(1.65 M inhabitants in total). Population is characterised bysmall and middle-sized cities (20,000 – 50,000 inhabitants)The climate is characterised by a transition from maritimeto continental-temperate climate.
The Pomeranian landscape was shaped by the pleisto-
cenian glacial period and has a mean elevation below50 ma.s.l. Three national parks were established in MV:the “Müritz”, the “Vorpommersche Boddenlandschaft ”and the “Jasmund”. In MV, there exist 58 habitat typesaccording to Appendix I of the EU Council Directive onthe conservation of natural habitats and of wild fauna andflora including 15 with priority (Anon 2004). Amongthese, several habitats are of particular importance for the
preservation of regional fungal diversity: (1) nutrient-poor Pinus- and Fagus-rich forests (spine fungi, coralloid
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fungi, agaricoid fungi); (2) calcareous forests of Fagus,Quercus, Pinus (Boletales, Cortinariales, Russula, Lactar-
ius); (3) dunes and dry, sandy grasslands (Geastrales); (4)rough pastures and grasslands ( Hygrocybe, Clavariaceae,Geoglossaceae, Entolomataceae); (5) fens, transitionalmires and raised bogs (bryophilous and peat-inhabitingfungi); (6) wet habitats such as marshland forests with
Alnus, Salix, Populus, Fraxinus (saprobic and mycorrhizalfungi); and (7) old-growth trees, especially of Quercus,
Fagus, Ulmus and Pinus (poroid and corticioid fungi).
Dataset
This study relied on wood-inhabiting, mycorrhizal andsaprobic macrofungi associated with abundant and botheconomical and ecological important deciduous and conif-erous tree species. The data are entirely based on fruitbodyobservations and belonged to the private database of Mr. Benno Westphal. Data were gathered by numeroushonorary mycologists and nature conservationists through-out decades (see Acknowledgements). Data were regularlyverified by B.W. They are currently made available throughthe internet portal “Biological survey databases and
herbaria in Mecklenburg-Vorpommern”1 of the University
of Greifswald, Germany.Fungi associated with herbs, shrubs and further non-tree
plants, parasitic rusts, smuts, mildews as well as myxomycota,asexual taxa (e.g. Coelomycetes) or taxa with tiny fruit bodies(e.g. cyphelloid Agaricales) were removed. The remaining data were then sorted for nutrition strategy (mycorrhiza, sapro-
phyte) at the generic level according to ecological annotations,authors' knowledge and literature (e.g. Breitenbach andKränzlin 1984 – 2005; Horak 2005; Kirk et al. 2008).Additionally, data were filtered with respect to eight treegenera: Abies (minus Picea abies), Acer , Fagus, Fraxinus,
Picea (minus Abies alba), Pinus, Quercus and Tilia.
Analysis of community ecology
Species abundance distribution
To avoid bumbling through dozens of different speciesabundance distribution (SAD) models (McGill et al. 2007),
1 http://geobot.botanik.uni-greifswald.de/portal; last accessed March2011
Fig. 1 The German state Mecklenburg-Western Pomerania ( shaded
area, left ). The right part displays an ordinance survey map(“Messtischblatt ”) of Mecklenburg-Western Pomerania and the loca-tions of the database entries (black dots) as used for the present paper.
Size of the dots correspond to the number of database entries in that grid. (source: map of Germany from http://de.wikipedia.org/wiki/ Mecklenburg-Vorpommern)
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a simple hypothesis was presumed according to current discussions in community ecology (Coddington et al. 2009;Ulrich et al. 2010; Unterseher et al. 2011): the communityof macrofungi in MV follows a log-normal distribution.
In case the fungal data did not follow a log-normal SAD,the core-satellite analysis (Hanski 1982) was applied to test for the possibility of overlapping SADs, e.g. a log-series
pattern overlapping a log-normal SAD (Magurran andHenderson 2003). For this analysis, 20 years (1988 – 2007)were extracted from the dataset and analysed with respect to persistence (number of years in which a species wasrecorded) and abundance (the number of occurrences in a
particular sample or year) of that species according toMagurran and Henderson (2003).
Different methods of separating core from satellitespecies exist (Magurran and Henderson 2003; Ulrich andZalewski 2006; Galand et al. 2009; Dolan et al. 2009)
because it is the organism's ecology and the nature of thedata that deserve particular attention.The following assump-
tions should therefore account for the nature of fungi in core-satellite analysis: fungal species may be well established andabundant in their habitat but grow most of the time asinvisible vegetative mycelium. Fruit body formation mayoccur rarely, e.g. every 5 – 10 years. If, for example, a 50%
persistence threshold would be applied separating satellitetaxa with a persistence of less than 10 years from corespecies rarely fruiting species would then be classified assatellite species by mistake and conclusions might depart from reality. To account for such phenomena, core specieswere defined as those species that were recorded with ≥75%of maximal persistence (more than 15 years) but down to
25% (15 quadrants of ordinance survey maps: MTB-Q) of maximal abundance for any year in MV. The remainingspecies were treated as satellite group and analysedaccordingly. In order to assign possible surrogate species(Favreau et al. 2006), the core group was examined in detail.
Observed and estimated species richness
Randomised (rarefied) species accumulation curves (SAC)were calculated in the ‘vegan’ package (Oksanen et al. 2010)of the R environment (R Development Core Team 2011) todisplay the accumulation of species when the number of sites
or individuals increases (Gotelli and Colwell 2001). By theanalysis of the curves' shape (e.g. initial slope, approachingan asymptote or not), it was possible to evaluate basic
patterns of species richness as well as sampling efforts.The species richness estimators Chao1, Jackknife1 and
Bootstrap (e.g. Colwell and Coddington 1994) werecalculated in R. By analysing the estimator curves' shape,only those values were considered as serious extrapolations,that remained stable, i.e. whose curve showed a stableasymptote for a considerable part at the right end of the
diagram. A fourth estimator was used for extrapolationsover the whole of Germany. It was introduced by Ugland et al. (2003) and since then has also been used for fungal data (Unterseher et al. 2008).
Community analyses
Multivariate statistics, such as ordination, and an appropri-ate graphical display of results are of great importance toevaluate and explain any community structure in the light of natural fluctuations (i.e. species turnover betweendifferent habitats, host plants or ecosystems). As for theissue of species richness estimations, there exist different algorithms to analyse such multivariate (multidimensional)community data. All have their strengths and weaknesses(Gauch 1982; McCune and Grace 2002) whose description,however, is beyond the scope of this communiciation. Inany case, it is recommended to apply different methods in
parallel. If the results then show similar patterns, one can
demonstrate and discuss the findings with more confidencethan if only one calculation was done.
In the present study, community structures of macrofungiin MV were traced with the three ordination techniques:canonical correspondence analysis (CCA), detrended cor-respondence analysis (DCA) and non-metric multidimen-sional scaling (NMDS or NMS). Analyses were performedfor those species that were recorded at least at ten different MTB-Q samples. Deleting the rarest species prior toordination is a common procedure to strengthen theapparent differences among habitats by reducing noisefrom very infrequent species (McCune and Grace 2002).
The raw data were not transformed or relativised, thusallowing differences in sample totals to be expressed in theanalyses. Multivariate analysis included (1) detrendedcorrespondence analysis (DCA) with default settings of the 'decorana' command of the R-package 'vegan'; (2) non-metric multidimensional scaling (NMDS) with the 'auttrans-form' option of command 'metaMDS' (also R-package'vegan') set to FALSE; and (3) canonical correspondenceanalysis (CCA) with default settings of the 'cca' commandand the four environmental variables: mycorrhiza, sapro-
phytism, coniferous host and deciduous host.All data used here (Online Resources 1 and 2) as well as
analyses in the R environment (Online Resource 3) are provided as electronic supplementary material.
Results
Observed and predicted species richness
The total dataset used for this study comprised 65,535 geo-referenced observations (counts) with host tree and sub-
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Table 1 Basic data of macrofungal species richness in Mecklenburg-Western Pomerania
Host tree Area (%)a Ecology Counts Samples Species observed b Species estimatedc Validation of estimatorsd
All 76.5% (325,000 ha) 65,535 1,019 3,307/0.1/3.2 3,710 – 4,682 PreliminaryConiferous 51.7 All 11,274 672 1,089/0.1/1.6 1,283 – 1,827 Preliminary
Mycorrhizal 5,272 487 370/0.1/0.8 430 – 602 Preliminary
Saprobic 5,826 606 690/0.1/1.1 820 – 1,178 Preliminary
Abies 0.2 All 526 126 165/0.3/1.3 209 – 464 Preliminary
Mycorrhizal 42 20 22/0.5/1.1 29 – 202 Preliminary
Saprobic 329 85 72/0.2/0.8 89 – 188 Preliminary
Picea 8.6 All 3,344 419 604/0.2/1.4 730 – 1,111 Preliminary
Mycorrhizal 1,219 249 205/0.2/0.8 247 – 358 ±Stablee
Saprobic 2,138 366 393/0.2/1.1 475 – 740 Preliminary
Pinus 42.9 All 7,374 548 802/0.1/1.5 950 – 1,394 Preliminary
Mycorrhizal 4,011 416 289/0.1/0.7 335 – 478 Preliminary
Saprobic 3,359 469 511/0.2/1.1 612 – 913 Preliminary
Deciduous ca. 24.8 All 27,345 1,947 789/0.1/2.5 2,215 – 2,935 Preliminary
Mycorrhizal 9,727 474 523/0.1/1.1 588 – 775 Preliminary
Saprobic 13,297 629 1,066/0.1/1.7 1,224 – 1,655 Preliminary
Acer 1 Saprobic 575 182 218/0.4/1.2 270 – 424 Preliminary
Fagus 11.8 All 15,247 526 1,229/0.1/2.3 1,403 – 1,739 Preliminary
Mycorrhizal 7,135 386 411/0.1/1.1 459 – 582 Preliminary
Saprobic 8,067 464 788/0.1/1.7 907 – 1,229 Preliminary
Fraxinus 3.7 Saprobic 1583 292 384/0.2/1.3 457 – 651 Preliminary
Quercus 8.1 All 4,881 537 775/0.2/1.4 920 – 1,311 Preliminary
Mycorrhizal 2,044 336 289/0.1/0.9 333 – 443 Preliminary
Saprobic 2,780 482 480/0.2/1 580 –
857 PreliminaryTilia 0.2 All 489 145 230/0.5/1.6 292 – 601 Preliminary
Mycorrhizal 215 67 87/0.4/1.3 108 – 169 Preliminary
Saprobic 292 120 151/0.5/1.3 194 – 481 Preliminary
a The percentage of total forest area in MV b Total species number/species per count/species per sample (MTB-Q); values less than 0.1 species per count were rounded up to 0.1c Range of estimators Chao1, Jack1, Bootstrapd Based on the estimators curve's shape (Online Resource 3); if none of the curves displayed a stable value (i.e. levelling off) but continued to rise,
the result of estimators was considered preliminarye According to the Chao estimator
Fig. 2 Species accumulationcurves of macrofungi inMecklenburg-WesternPomerania. Line numbes:1 Fagus; 2 Quercus; 3 Pinus;4 Picea; 5 Fraxinus; 6 Tilia;7 Acer ; 8 Abies
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stratum characteristics. In total, 3,307 species wererecorded from 1,019 MTB-Q. Database entries weredominated by saprobic fungi associated with deciduoustrees (Fig. 2a ). The overall number of saprobic fungi clearlyoutnumbered mycorrhizal fungi (Fig. 2a ). Fagus, Quercus
and Pinus trees harboured the highest absolute numbers of macrofungi, Tilia, Acer and Abies the lowest (Fig. 2b). With
respect to the mean number of species per MTB-Q, Faguswas most species-rich with 2.3, followed by Tilia and Pinus
(Table 1). A third value of observed species richness wascalculated, the number of species per count. The higher those values are (Table 1), the faster fungal speciesaccumulated with increasing number of counts. Here, Tilia
is taking the lead with one new species every two counts,followed by Acer (0.4 species per count).
Table 1 further displays values of three different speciesrichness estimators and an assessment of the estimatorsconfidence (rightmost two columns). With exception of the Chao1 estimator for mycorrhizal fungi on Picea, none
of the estimators' curves displayed a stable levelling-off (Online Resource 3). The resulting equation of Ugland'sestimator was y=821.8 × log (x) – 2,401.31 with y=thenumber of predicted species and x=the number of MTB-Q(calculations not shown). For all MTB-Q, Ugland'sformula estimated 3,291 species. Extrapolation to theentire forest area in MV resulted in 3,511 predictedwoodland species.
Fungal communities
Canonical correspondence analysis (CCA) displayed
species scores with respect to the parameters host group (deciduous-coniferous) and ecology (saprophyte-mycorrhiza) in a two-dimensional ordination space(Fig. 3). Table 2 lists taxonomic information, number of occurrences and preferred habitat for the five most distinct species of each community: deciduous-mycorrhiza (upper right of Fig. 3), deciduous-saprophyte (lower right),coniferous-saprophyte (lower left), coniferous-mycorrhiza (upper left). The five species closest to the centroid couldnot be assigned clearly to one of the four groups and arealso considered in Table 2.
Using NMDS and DCA and focusing on host trees
instead of fungal species, the fungal assemblage appearedtripartite (Fig. 4a, b): saprophytes of the five deciduoustrees clearly separated from saprophytes of the threeconiferous hosts. A third group consisted of mycorrhizalfungi of both coniferous and deciduous host trees (right hand side of Fig. 4a, b). Separate analysis of mycorrhizalcommunities (Fig. 4c, d) and saprobes (Fig. 4e, f ) providedfurther details: For mycorrhizae, the eight host trees,representing their respective fungal assemblages, wereclearly separated from each other (Fig. 4c, d). Deciduous
trees and their associated saprobic fungi were overlappingfor DCA on both axes (Fig. 4f ), and separated clearly for
NMDS (Fig. 4e). Coniferous host trees and their fungalcommunities separated clearly from each other and fromthose of deciduous trees. Saprobic fungi of Abies were themost distinct assemblage for both NMDS and DCA(Fig. 4e, f ).
Core-satellite analysis
The 20-year dataset comprised 2,697 macrofungi. Thecore group comprised 100 taxa (4% of total speciesnumber and 25% of total records; Online Resource 1).The remaining 2,597 species (35,055 records) were
treated as occasional species, i.e. satellite group (OnlineResource 1). Visual inspection and statistical testing(Chi-square, Kolmogorov – Smirnov, Shapiro – Wilk andAnderson – Darling) for log-normal SAD of all data werenegative, i.e. not significant (Fig. 5a, b; statistical tests not shown). Analyses of the core group revealed a significant approach to log-normality (Fig. 5c, d; statistical tests not shown). Analysis of satellite taxa resulted in rejection of log-normality (Fig. 5e) and confirmation of a log-linear relationship (Fig. 5f ).
Fig. 3 Position of macrofungi within a two-dimensional ordinationspace after canonical correspondence analysis (CCA). The first two
axes account for 56 and 31% of the constrained variability. Theordination shows species (circles) in sample space according tosubstratum requirement (coniferous-deciduous) and nutrition strategy(mycorrhiza-saprophyte). The five most distinct species for eachgroup (those nearest to the four corners of the ordination) arehighlighted as black dots. Additionally the five species nearest to thecentroid (without clear ecology) are highlighted. All 25 species aredescribed in Table 2. Abbreviations are composed of the first four letters each of genus (upper case) and epithet (normal case), e.g.BOLEreti= Boletus reticulatus
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Table 2 Full species names, abundance and habitat requirements of those fungi highlighted in Fig. 3
Species Occurrence inMV
Member of thecore group
Habitat and ecologya
Deciduous-mycorrhiza in Fig. 3
Boletus reticulatus Schaeff. Common Yes Quercus- and Fagus-rich deciduous forests;ectomycorrhiza with Fagus sylvatica andQuercus robur
Inocybe asterospora Quél. Common No Quercus- and Fagus-rich deciduous forests;ectomycorrhiza with Fagus sylvatica andQuercus robur
Russula velutipes Velen. Scattered Yes Deciduous forests with heavy, loamy soils (not basophil), ectomycorrhiza with Fagus sylvatica
and Quercus robur (and Carpinus)
Russula violeipes Quél. Scattered Yes Deciduous forests with heavy, loamy soils (not basophil), ectomycorrhiza with Fagus
sylvatica, Quercus robur and Carpinus betulus,rarely with Pinus
Russula olivacea (Schaeff.) Fr. Scattered Yes Deciduous forests with basophil, heavy morainesoils, ectomycorrhiza with Fagus sylvatica andCarpinus betulus
Deciduous-saprophyte in Fig. 3 Peniophora limitata (Chaillet ex Fr.)
CookeCommon Yes Saprobe on dead corticated twigs and branches of
Fraxinus excelsior
Diatrype disciformis (Hoffm.) Fr. Common Yes Saprobe on dying and dead twigs and branches of Fagus sylvatica
Hymenochaete rubiginosa (Dicks.)Lév.
Common Yes Saprobe on old decorticated branches and stumpsof Quercus spp.
Xylaria carpophila (Pers.) Fr. Common Yes Saprobe on lying cupulae of Fagus sylvatica
Lachnum virgineum (Batsch) P. Karst. Common Yes Saprobe on lying Fagus cupulae, also on lyingcones of Larix decidua, Pinus and Pseudotsuga
Coniferous-saprophyte in Fig. 3
Gyromitra esculenta (Pers.) Fr. Scattered tocommon
Yes Saprobe of acidophilic pine ( Pinus) forests,especially on disturbed grounds
Ciboria rufofusca (O. Weberb.) Sacc. Scattered Yes Saprobe on lying cone scales of Abies spp., rarelyon Pseudotsuga cones
Strobilurus tenacellus (Pers.) Singer Common Yes Saprobe on lying pine cones, especially Pinus
sylvestris
Phellinus pini (Brot.) Bondartsev &Singer (current name: Porodaedalea
pini (Brot.) Murrill)
Scattered No Secondary parasite of old pine trees, mainly Pinus sylvestris, seldom Pinus strobus
Auriscalpium vulgare Gray Common No Saprobe of lying cones of Pinus nigra, Pinus
sylvestris, rarely on other coniferes such as Pseudotsuga
Coniferous-mycorrhiza in Fig. 3
Suillus variegatus (Sw.) Kuntze Scattered Yes Poor, old-growth pine forests, quaking bogs,ectomycorrhiza with Pinus sylvestris and
Betula pubescens
Tricholoma imbricatum (Fr.) P.Kumm.
Scattered Yes Acidophile pine forests and special stands, suchas gravel pits, ectomycorrhiza with Pinus
sylvestris
Russula decolorans (Fr.) Fr. Common Yes Old-growth pine forests, on sandy grounds,acidophil, ectomycorrhiza with Pinus sylvestris
Russula drimeia Cooke (current name: Russula sardonia Fr.)
Common Yes Old-growth pine forests, on sandy grounds,acidophil, ectomycorrhiza with Pinus sylvestris
Inocybe lacera (Fr.) P. Kumm. Scattered Yes Pine- and spruce forests, willow coppices, pioneer woods, ectomycorrhiza with Picea
abies, Pinus sylvestris, also Salix and Alnus
spp.
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Fig. 4 Ordination plots of nonmetrical multidimensional scaling(NMDS; upper row) and detrended correspondence analysis (DCA;lower row) display host trees ( grey dots) in fungal species (black
crosses) space. a, b Three distinct groupings of host trees and their associated fungal communities are visible. c, d Patterns from themycorrhizal dataset. The trees' coordinates in ordination space are
separated clearly. This means that each tree houses a uniquecommunity of mycorrhizal fungi. Several fungal species (black
crosses) are located in between thus occurring on several hosts. e, f
Coniferous trees and their fungal saprophytes separate from each other and from deciduous trees. Fungi without clear host preferences arelocated inbetween
Table 2 (continued)
Species Occurrence inMV
Member of thecore group
Habitat and ecologya
Without clear ecology in Fig. 3
Clitocybe nebularis (Batsch) P.Kumm.
Common Yes Saprobe on dead leaf litter and needles, variousdeciduous and coniferous trees
Gymnopus dryophilus (Bull.) Murrill Common Yes Saprobe on dead leaf litter and needles, variousdeciduous and coniferous trees, also in swamps
Hypholoma fasciculare sensu Massee(current name: Hypholoma acutum
(Cooke) E. Horak)
Common No Saprobe on various deciduous and coniferoustrees, dead wood and stumps of all kinds
Laccaria amethystina (Huds.) Cooke Common No Ectomycorrhiza with Fagus sylvatica, Quercus
robur , Carpinus betulus and Abies spp.
Lepista flaccida (Sowerby) Pat. Common Yes Saprobe on dead leaf litter and needles, variousdeciduous and coniferous trees
a The following references were used to validate the authors' knowledge: Horak (2005), Breitenbach and Kränzlin (1984 – 2005), Hansen andKnudsen (1992 – 2000)
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Discussion
Observed and predicted species richness
Despite the long-term voluminous dataset used here,several aspects of fungal diversity could not be resolved.On the basis of the present data, it is hard to tell which host tree supports the richest fungal community (Fig. 1).Without doubt, beech ( Fagus sylvatica) and oak (Quercus
spp.) accommodate very high numbers of fungi (Heilmann-Clausen 2001; Heilmann-Clausen and Christensen 2005;Binion et al. 2008). However, the observed species richnesson the different trees (Fig. 2a ; Table 1) seemed to be rather a function of host tree abundance (column “area ” in Table 1)than of the trees' ability to support high fungal diversity. Byconsidering the number of species per count, other host trees became more important for maintenance of fungaldiversity, such as Tilia (Unterseher et al. 2005) or Acer
(Hein et al. 2009).
Estimations of total species richness ranged widelyfrom 3,710 to 4,682 fungal woodland species (Table 1)and should therefore be communicated with caution.However, somewhat more than 4,000 macrofungal species(not only woodland species) in MV may be a realisticfigure when compared with the recently published Funga of Saxony-Anhalt (Täglich 2009; 3,612 asco- and basi-diomycota), or the Funga of Saxony that currentlycomprise 3,378 Basidiomycota and 1,593 Ascomycota
from about 190,000 observations (Dämmrich, personalcommunication).
Ugland et al. (2003) provided an extrapolation methodthat could also be used with fungal communities(Unterseher et al. 2008), because their species richnessestimator takes into account very diverse communitiesfrom large and heterogeneous environments. Whereas thechosen host trees represent dominant genera and 76.5% of total forest area in MV, extrapolation to 100% increasedspecies numbers to ca. 3,500.
Fig. 5 Species abundance distributions (SADs) of all fungi (left
column), core species (middle column) and satellite group (right
column) of a 20-year dataset. a, c, e ‘Binned’ species abundancesoverlaid with a fitted truncated log-normal SAD. Inserts showWhittaker plots (rank-log-abundance plots) which are better suited
for identification of SAD other than log-normal. b, d The probability
plots additionally test for log-normality of the data. The better the grey
line in a probability plot fits to the plotted abundances ( open circles)the better is the fit to a log-normal species abundance distribution. f
Satellite taxa follow a log-linear SAD: only a few species had highnumbers of counts whereas most fungi were rarely recorded
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Fungal communities and the benefit of surrogate speciesfor biodiversity and conservation
Multivariate statistics revealed distinct mycorrhizal com-munities of both coniferous and deciduous trees. Sapro-
phytes seemed to behave in a more complex manner thanmycorrhizal fungi. They showed clearly overlapping spe-
cies composition on deciduous wood with DCA (Fig. 4f ), but well-separated groups with NMDS (Fig. 4e). In bothcases, deciduous hosts clearly separated from coniferoustrees with respect to their fungal species composition(Fig. 4e, f ).
Throughout various studies applying the core – satellitetheory, core taxa were discussed as species that are
biologically related to the habitat they live in (Magurranand Henderson 2003) or having the largest impact on their ecosystem (Ulrich and Zalewski 2006). Furthermore,changes in core species composition may be translatableto changes in environmental conditions (e.g. climate
change, habitat disturbance), when new core species, drawnfrom the pool of satellite species, will replace existing ones(Magurran and Henderson 2003). Such interpretation of core species is close to the concept of surrogate species(Favreau et al. 2006) that comprises flagship (Dietz et al.1994), focal (Lambeck 1997), indicator (Landres et al.1988; Noss 1999) or keystone (Power et al. 1996) species.According to Rolstad et al. (2002), the biology of indicator species should be, among others, fairly well known. Thiswould be the case for those four species groups in Fig. 3,which are located close to the four corners of theordination. Except for 3 species, all those 20 fungi
belonged to the core group (Online Resource 1).Among the actual core group, Amanita muscaria, A.
phalloides, Boletus edulis or Fomes fomentarius canwithout doubt be considered flagship species, given their charismatic appearance and their high level of publicawareness that might support the protection of that species' entire habitat. Focal species are, e.g., thoseectomycorrhizal taxa that are especially threatened byoverfertilisation of forest soils (Gryndler and Lipavsky1995) and deforestation (Zhang et al. 2004; Tedersoo et al.2007). In order to protect focal species, such threatening
processes should be eliminated so that further species will
also benefit. The indicator species approach itself iscomplex and applicable in a hierarchical manner (Noss1990). Fungal indicators can be assigned to plant communities and ecotypes (e.g. fungi associated withconiferous trees), ecosystem processes (e.g. litter andwood decay by the core group species Mycena galericu-
lata, Auriscalpium vulgare, Fomitopsis pinicola, Hypoxy-
lon fragiforme or Oudemansiella mucida) or to healthassessment of major plant groups (e.g. Armillaria spp.,
Heterobasidion annosum). Additional to their significant
role in forest ecosystems, all core species are common inMV, fruit regularly, are well known to most mycologists,and many of them are well represented in scientificliterature (Kirk et al. 2008). They further represent allhost trees and all ecologies considered in the present study.
Whereas more than 75% of total forest area inMecklenburg-Western Pomerania were considered in the
present study, numerous, from a fungal perspective,important host trees were neglected, such as Populus, Salix,Corylus, Larix, Pseudotsuga or the wooden rosids Malus,Sorbus and Prunus. These substrata surely provide richsources for fungal species, and studies incorporating thosetrees will unravel further, so far unknown and unpredict-able, patterns of fungal diversity.
Acknowledgements We are grateful to Hanns Kreisel for many veryhelpful comments on the manuscript and for providing access to hisunpublished Funga of Mecklenburg-Western Pomerania. Many thanksgo to numerous honorary mycologists, especially Ria Bütow, Joe Duty,Hanns Kreisel, Siegmund Olm, Torsten Richter, Katrin Richter,
Gerhard Rüdiger, Ingeborg Schmidt, Manfred Schubert, BrigitteSchurig and Jürgen Schwik as well as the Arbeitsgruppe MykologieHamburg for professional mapping of fungal occurrences in MV. The“Landesforstanstalt Mecklenburg-Vorpommern” is thanked for provid-ing areal data of host trees. Hans-Jürgen Hardtke and Frank Dämmrichare thanked for providing basic fungal data from Saxony. Thereprocessing of fungal data for public access within the “Biologicalsurvey databases and herbaria in Mecklenburg-Vorpommern”
(programming by Florian Jansen and Falco Glöckler) is currentlyfunded by the “Landesamt für Umwelt, Naturschutz und Geologie(LUNG)”, the “ Norddeutsche Stiftung für Umwelt und Entwicklung”,the Institute of Botany and Landscape Ecology, the “Institut für Dauerhaft Umweltgerechte Entwicklung von Naturräumen der Erde(DUENE)”, and coordinated by the working group “MykologieMecklenburg-Vorpommern” (responsibility Norbert Amelang) andthe Institute of Botany and Landscape Ecology (responsibility FlorianJansen). Two anonymous reviewers are thanked for valuable com-ments on a previous manuscript.
References
Abarenkov K, Nilsson RH, Larsson K-H et al (2010) The UNITEdatabase for molecular identification of fungi - recent updates andfuture perspectives. New Phytol 186:281 – 285
Amend AS, Seifert KA, Bruns TD (2010) Quantifying microbialcommunitites with 454 pyrosequencing: does read abundancecount? Mol Ecol 19:5555 – 5565
Anon (1992) Rote Liste der gefährdeten Grosspilze in Deutschland.Deutsche Gesellschaft für Mykologie e.V., NaturschutzbundDeutschland e.V. (NABU)
Anon (2004) Fauna-Flora-Habitat-Richtlinie, Anhang I Auszug der inMecklenburg-Vorpommern vorkommenden Lebensraumtypen.Landesamt für Umwelt, Naturschutz und Geologie Mecklenburg-Vorpommern, Güstrow (http://www.lung.mv-regierung.de/dateien/ eu_codes_ffh_lrt.pdf ; last accessed Mar 2011).
Binion DE, Stephenson SL, Roody WC, Burdsall HH, Miller OK,Vasilyeva LN (2008) Macrofungi associated with oaks of eastern
North America. West Virginia Univ. Press.Bohannan BJM, Hughes J (2003) New approaches to analyzing
microbial biodiversity data. Curr Opin Microbiol 6:282 – 287
Mycol Progress
8/4/2019 3,000 species and no end – species richness and community
http://slidepdf.com/reader/full/3000-species-and-no-end-species-richness-and-community 11/12
Breitenbach J, Kränzlin F (1984 – 2005) Pilze der Schweiz Bd. 1 – 6.Edition Mykologia, Luzern
Chao A, Chazdon RL, Colwell RK, Shen T-J (2006) Abundance-basedsimilarity indices and their estimation when there are unseenspecies in samples. Biometrics 62:361 – 371
Coddington JA, Agnarsson I, Miller JA, Kuntner M, Hormiga G(2009) Undersampling bias: the null hypothesis for singletonspecies in tropical arthropod surveys. J Anim Ecol 78:573 – 584
Colwell RK, Coddington JA (1994) Estimating terrestrial biodiversity
through extrapolation. Philos Trans R Soc Lond B 345:101 – 118Crous PW, Gams W, Stalpers JA, Robert V, Stegehuis G (2004)
MycoBank: an online initiative to launch mycology into the 21st century. Stud Mycol 50:19 – 22
Cunningham RB, Lindenmayer DB (2005) Modeling count data of rare species: Some statistical issues. Ecology 86:1135 – 1142
R Development Core Team (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing,Vienna, Austria (http://www.R-project.org/ last accessed Mar 2011).
Dietz JM, Dietz LA, Nagagata EY (1994) The effective use of flagshipspecies for conservation of biodiversity: the example of liontamarins in Brazil. In: Olney PJS, Mace GM, Feistner ATC (eds)Creative Conservation: Interactive Management of Wild andCaptive Animals. Chapman and Hall, London, pp 32 – 49
Dolan JR, Ritchie ME, Tunin-Ley A, Pizay M-D (2009) Dynamics of
core and occasional species in the marine plankton: tintinnidciliates in the north-west Mediterranean Sea. J Biogeo 36:887 – 895
Favreau JM, Drew CA, Hess GR, Rubino MJ, Koch FH (2006)Recommendations for assessing the effectiveness of surrogatespecies approaches. Biodivers Conserv 15:3949 – 3969
Fröhlich J, Hyde KD (1999) Biodiversity of palm fungi in the tropics:are global fungal diversity estimates realistic? Biodivers Conserv8:977 – 1004
Galand PE, Casamayor EO, Kirchman DL, Lovejoy C (2009) Ecologyof the rare microbial biosphere of the Arctic Ocean. Proc NatlAcad Sci USA 106:22427 – 22432
Gauch HG (1982) Multivariate analysis in community ecology.Cambridge University Press, Cambridge
Gotelli NJ, Colwell RK (2001) Quantifying biodiversity: proceduresand pitfalls in the measurement and comparison of speciesrichness. Ecol Lett 4:379 – 391
Gryndler M, Lipavsky J (1995) Effect of phosphate fertilization on the populations of arbuscular mycorrhizal fungi. Rost Vyroba 41:533 – 540
Hansen L, Knudsen H (1992 – 2000) Nordic Macromycetes Vol. 1 – 3. Nordesvamp, Copenhagen.
Hanski I (1982) Dynamics of regional distribution: the core andsatellite species hypothesis. Oikos 38:210 – 221
Hawksworth DL (1991) The fungal dimension of biodiversity:magnitude, significance, and conservation. Mycol Res 95:641 – 655
Hawksworth DL (2001) The magnitude of fungal diversity: the 1.5million species estimate revisited. Mycol Res 105:1422 – 1432
Hawksworth DL, Rossman AY (1997) Where are all the undescribedfungi? Phytopathology 87:888 – 891
Heilmann-Clausen J (2001) A gradient analysis of communities of macrofungi and slime moulds on decaying beech logs. MycolRes 105:575 – 596
Heilmann-Clausen J, Christensen M (2005) Wood-inhabiting macro-fungi in Danish beech-forests – conflicting patterns and their implications in a conservation perspective. Biol Conserv122:633 – 642
Hein S, Collet C, Ammer C, LeGoff N, Skovsgaard J-P, Savill P(2009) A review on growth and stand dynamics of sycamore( Acer pseudoplatanus L.) in Europe: implications for silviculture.Forestry 82:361 – 385
Horak E (2005) Röhrlinge und Blätterpilze in Europa. Elsevier,Heidelberg
Joshee S, Paulus BC, Park D, Johnston PR (2009) Diversity anddistribution of fungal foliar endophytes in New ZealandPodocarpaceae. Mycol Res 113:1003 – 1015
Jumpponen A, Jones KL (2009) Massively parallel 454 sequencingindicates hyperdiverse fungal communities in temperate Quercus
macrocarpa phyllosphere. New Phytol 184:438 – 448Kirk P, Cannon PF, Minter DW, Stalpers JA (2008) Ainsworth
&Bisby’s Dictionary of the Fungi, 10th edn. CAB International,Wallingford, UK
Krieglsteiner GJ (1991) Verbreitungsatlas der Großpilze Deutschlands(West). Band 1: Ständerpilze, Teil A: Nichtblätterpilze. Ulmer,Stuttgart.
Krieglsteiner GJ (1993) Verbreitungsatlas der Großpilze Deutschlands(West). Band 2: Schlauchpilze. Ulmer, Stuttgart.
Lambeck RJ (1997) Focal species: a multi-species umbrella for natureconservation. Conserv Biol 11:849 – 856
Landres PB, Verner J, Thomas JW (1988) Ecological uses of vertebrate indicator species - a critique. Conserv Biol 2:316 – 328
Lonsdale D, Pautasso M, Holdenrieder O (2008) Wood-decaying fungiin the forest: conservation needs and management options. Eur JFor Res 127:1 – 22
Lovell S, Hamer M, Slotow R, Herbert D (2009) An assessment of the
use ofvolunteers for terrestrial invertebrate biodiversity surveys.BiodiversConserv 18:3295 – 3307
Magurran AE, Henderson PA (2003) Explaining the excess of rarespecies in natural species abundance distributions. Nature422:714 – 716
May RM (1991) A fondness for fungi. Nature 352:475 – 476McCune B, Grace JB (2002) Analysis of ecological communities.
MjM Software Design, Gleneden Beach, Oregon, USAMcGill BJ, Etienne RS, Gray JS et al (2007) Species abundance
distributions: moving beyond single prediction theories tointegration within an ecological framework. Ecol Lett 10:995 – 1015
Molina R, Horton TR, Trappe JM, Marcot BG (2011) Addressinguncertainty: How to conserve and manage rare or little-knownfungi. Fungal Ecol 4:134 – 146
Mueller GM, Schmit JP, Leacock PR et al (2007) Global diversity anddistribution of macrofungi. Biodivers Conserv 16:37 – 48
Noss RF (1990) Indicators for monitoring biodiversity - a hierarchicalapproach. Conserv Biol 4:355 – 364.
Noss RF (1999) Assessing and monitoring forest biodiversity: Asuggested framework and indicators. For Ecol Manag 115:135 – 146
Novotny V, Basset Y (2000) Rare species in communities of tropicalinsect herbivores: pondering the mystery of singletons. Oikos89:564 – 572
Oksanen J, Blanchet FG, Kindt R, et al. (2010) Vegan: communityecology package. Ordination methods, diversity analysis andother functions for community and vegetation ecologists.Available at http://cran.r-project.org/web/packages/vegan/index.html (last accessed March 2011).
Öpik M, Metsis M, Daniell TJ, Zobel M, Moora M (2009) Large-scale parallel 454 sequencing reveals host ecological group specificityof arbuscular mycorrhizal fungi in a boreonemoral forest. NewPhytol 184:424 – 437
Ovaskainen O, Nokso-Koivisto J, Hottola J et al (2010) Identifyingwood-inhabiting fungi with 454 sequencing – what is the
probability that BLAST gives the correct species? Fungal Ecol3:274 – 283
Pedrós-Alió C (2006) Marine microbial diversity: can it be deter-mined? Trends Microbiol 14:257 – 263
Power ME, Tilman D, Estes JA et al (1996) Challenges in the quest for keystones. Bioscience 46:609 – 620
Mycol Progress
8/4/2019 3,000 species and no end – species richness and community
http://slidepdf.com/reader/full/3000-species-and-no-end-species-richness-and-community 12/12
Reeder J, Knight R (2009) The 'rare biosphere': a reality check. Nat Methods 6:636 – 637
Rolstad J, Gjerde I, Gundersen VS, Saetersdal M (2002) Use of indicator species to assess forest continuity: a critique. ConservBiol 16:253 – 257
Schmitt J (2007) Rote Liste der Pilze des Saarlandes – TabellarischeZusammenstellungen der Taxa in den verschiedenen Gefährdung-skategorien. Landesamt für Umwelt- und Arbeitsschutz, Zentrumfür Biodokumentation, Schiffweiler. (http://www.saarland.de/
dokumente/thema_naturschutz/06_Rote_Liste_Pilze-188-205. pdf ; last accessed Mar 2011).
Schwik J, Westphal B (1999) Rote Liste der gefährdeten GroßpilzeMecklenburg-Vorpommerns. Das Umweltministerium des LandesMecklenburg-Vorpommern, Schwerin. (http://www.uni-greifswald.de/~mycology/rl-mv.htm; last accessed Mar 2011)
Täglich U (2009) Pilzflora von Sachsen-Anhalt. Ascomyceten,Basidiomyceten, Aquatische Hyphomyceten. Leibniz-Institut für Pflanzenbiochemie, Halle (Saale).
Tedersoo L, Suvi T, Beaver K, Kõljalg U (2007) Ectomycorrhizalfungi of the Seychelles: diversity patterns and host shifts from thenative Vateriopsis seychellarum (Dipterocarpaceae) and Intsia
bijuga (Caesalpiniaceae) to the introduced Eucalyptus robusta
(Myrtaceae), but not Pinus caribea (Pinaceae). New Phytol175:321 – 333
Ugland KI, Gray JS, Ellingsen KE (2003) The species-accumulationcurve and estimation of species richness. J Anim Ecol 72:888 – 897
Ulrich W, Zalewski M (2006) Abundance and co-occurrence patternsof core and satellite species of ground beetles on small lakeislands. Oikos 114:338 – 348
Ulrich W, Ollik M, Ugland KI (2010) A meta-analysis of species – abundance distributions. Oikos 119:1149 – 1155
Unterseher M, Schnittler M (2010) Species richness analysis and ITSrDNA phylogeny revealed the majority of cultivable foliar endophytes from beech ( Fagus sylvatica). Fungal Ecol 3:366 – 378
Unterseher M, Otto P, Morawetz W (2005) Species richness andsubstrate specificity of lignicolous fungi in the canopy of a temperate, mixed deciduous forest. Mycol Prog 4:117 – 132
Unterseher M, Schnittler M, Dormann C, Sickert A (2008) Applica-tion of species richness estimators for the assessment of fungaldiversity. FEMS Microbiol Lett 282:205 – 213
Unterseher M, Jumpponen A, Öpik M et al (2011) Species abundancedistributions and richness estimations in fungal metagenomics -lessons learned from community ecology. Mol Ecol 20:275 – 285
Wilkinson FA, Foster MS (2004) Institutions with significant collections of fungi or fungal allies and fungus-related websites.In: Mueller GM, Bills GF, Foster MS (eds) Biodiversity of Fungi – Inventory and Monitoring Methods. Elsevier, Amster-dam, pp 619 – 626
Zhang Y, Guo L-D, Liu RJ (2004) Survey of arbuscular mycorrhizal
fungi in deforested and natural forest land in the subtropicalregion of Dujiangyan, southwest China. Plant Soil 261:257 – 263
Mycol Progress
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