Microhabitats of Collembola (Insecta: Entognatha) in beech and spruce forests and their influence on biodiversity

Eur. J. Soil Biol. 37 (2001) 237−244 © 2001 Éditions scientifiques et médicales Elsevier SAS. All rights reserved S1164556301010901/FLA

Microhabitats of Collembola (Insecta: Entognatha) in beech and spruce forests and their influence on biodiversity Josef Rusek* ˇ eské Budeˇjovice, Czech Republic Institute of Soil Biology, Academy of Sciences of the Czech Republic, Na sádkách 7, C

Received 15 August 2000; accepted 14 April 2001

Abstract − Collembolan communities were studied in 41 microhabitats in beech and spruce forests of south (Zˇofín and Sˇumava) and central (Jevany) Bohemia. The communities of Collembola were analysed using TWINSPAN and CANOCO programs. The aim of this study was to establish differences between patch (microhatitat) communities and the main forest community in spruce and beech forests, the differences between both types of forests and among different regions of Bohemia. Further questions were: is there a difference in microhabitat communities during secondary forest succession? do some species live exclusively in one or few microhabitats? and does microhabitat diversity influence the biodiversity in forest soils? Material comprising 25 590 specimens of Collembola belonging to 142 species was analysed. Highly significant differences were determined between microhabitat communities in beech and spruce forests, as well as among forests in different regions of Bohemia. Significant differences were also found among microhabitats in forests of different ages. Also, some microhabitat communities of Collembola, e.g. moss on boulders, were significantly different from their main forest community. Certain collembolan species existed exclusively in one or two microhabitats. Patches therefore influenced substantially biodiversity in these forest soils. © 2001 Éditions scientifiques et médicales Elsevier SAS beech forests / biodiversity / Collembola communities / microhabitats / spruce forests

1. INTRODUCTION Published descriptions of forest soil animal communities have not focused extensively on microhabitats, although faunal relationships to plant communities and to different chemical and physical soil parameters have been studied. For example, communities of Collembola in Norwegian coniferous forests were described and analysed in relation to plant communities, soil fertility, vertical distribution, and soil chemical parameters [4, 5, 6]. In these studies, the soil Collembola community descriptions were based on randomly collected soil samples. It has been common for such field studies of soil mesofauna communities to be based on randomly collected soil samples, regardless of the heterogeneity of the forest floor. This heterogeneity includes soil surfaces covered by different higher plant groups, an uneven distribution of understory plants, patches of moss cushions, and varying depths of litter layers, all of which could *Correspondence and reprints: Fax number: +420 348 5300133. E-mail address: [email protected] (J. Rusek).

influence animal distribution in the soil. In addition, soil moisture and temperature regimes are influenced by different distance from water bodies and forest edge, as well as by different evapo-transpiration rates of soil and trees and understory plant species. These factors affect the horizontal soil fauna distribution [cf. 18]. Some data are available on microarthropod distribution in ecotones for spruce and mixed forests edges [12, 13, 14], for soil microarthropods inhabiting moss carpets and cushions on boulders, on the soil surface, and on logs, as well as in decaying wood, and soil around tree stems. However, it is only in a few cases that these studies are complemented by soil animal community data that is characteristic for the surrounding forest stand [1, 3, 8, 15]. Despite this general information, the relation of animal communities inhabiting soil below different understory plants, in different moisture regimes, dead organic matter and other patches on the forest floor to the “main” community of a certain forest has not yet been well studied. Soil animal communities inhabiting patchy forest floor structures should play a different role in the ecosystem than the main soil fauna com

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munity, and the species probably display different life strategies [cf. 2, 18]. Almost nothing is known about the role of patches inside the main forest community in secondary succession and in restoration of damaged forest ecosystems. How microhabitats (patches) influence forest biodiversity in soil is another aspect not being actively pursued in soil zoology. Collembola communities from different microhabitats in beech and spruce forests in three regions of Bohemia were analysed to provide answer to the following questions: – Is there a distinct difference between microhabitat communities and the main forest community? – Is there a difference in microhabitat communities between beech and spruce forests? – Is there a difference in microhabitat communities among forests in different regions of Bohemia? – Is there a difference in microhabitat communities during secondary forest succession? – Do certain species live exclusively in one or a few microhabitats? – How does microhabitat diversity influence biodiversity in soil?

2. MATERIAL AND METHODS 2.1. Localities and microhabitats Field studies were conducted in three different regions of Bohemia, Czech Republic: at the Zˇ ofínsky´ Prales Nature Reserve in the Novohradské hory Mountains in south-east Bohemia (48° 43’ N; 14°45’ E), at Smrcˇ ina Mount in the Sˇ umava Biosphere Reserve in south Bohemia ( 48° 45’ N; 13° 54’ E), and at Jevany near Prague in the Vodeˇ radské Bucˇ iny Nature Reserve in central Bohemia (49° 58’ N; 14°48’ E). Henceforth these three sites are abbreviated as Zˇ ofín, Sˇ umava, and Jevany, respectively. Microhabitats were selected in spruce and beech stands in all three Reserves and in each forest type. To date, only spruce forest samples have been evaluated from the Sˇ umava stands. The number of microhabitats increased as: Sˇ umava (5) >Jevany (10)> Zˇ ofín (14). The following different types of microhabitats were studied: 1 - soil covered with litter only, 2 – soil not covered with litter on a slope near (underneath) to beech stems, 3 - soil not covered with litter on a slope near (above) to beech stems, 4 - soils close to spruce stems foot, 5 - soils below the beech canopy, 6 - soils outside the beech canopy, 7 - soils without litter and understory plant cover, 8 - soils below Luzula pilosa tufts, 9 - soils below ferns, 11 - soils with mosses, 13 - soils below Calamagrostis villosa, 15 - soil below Vaccinium myrtillus, 16 - mosses on boulders, 17 - mosses on logs, 18 - black decaying wood of logs, 20 - soil and spruce litter without understory plants, 21- litter and shallow soil on boulders. Microhabitats 10, 12, 14, and 19, missing from the above list, refer to unprocessed samples from the beech stand at Sˇ umava. Other environmental variables are given in table I.

2.2. Sampling Ten random samples, each 10 cm2 in soil surface area and 5 cm deep, were taken from each microhabitat and extracted in Tullgren funnels. The extracted material of Collembola and other microarthropods was preserved in 95% ethanol. When necessary, specimens were mounted for identification on permanent slides [10], determined to species and counted. A total of 25 590 specimens of Collembola from 41 microhabitats were evaluated in this study.

2.3. Data analysis The quantitative species data were entered into an Excel data table and used for calculation of Shannon’s index of diversity (H), evenness (E), richness (S) and other evaluations using TWINSPAN and CANOCO programs. To classify the samples, a polythetic classification was produced by Two Way Indicator Species Analysis (TWINSPAN version 2.1. [7]). This program was performed for: 1. qualitative 0;1 (absence – presence) data, and 2. log (n + 1)-transformed quantitative data. The first classification separated data according to faunistic similarity; the second one emphasised coenotical similarity. To order the species and samples in relation to environmental variables, the direct gradient analysis program of Canonical Correspondence Analysis (CCA) was performed for log (n + 1)-transformed data using CANOCO version 3.1 [17] with Monte Carlo testing to evaluate the statistical significance of the outcome. Stepwise selection of environmental variables was performed. Detrended Correspondence Analysis (DCA) was performed for log (n + 1)transformed data, down-weighting of rare species and detrending-by-segments using CANOCO version 3.1 [16, 17] as a supplement to the TWINSPAN analysis.

3. RESULTS 3.1. Abundance of species in microhabitats A total of 142 species of Collembola were recorded in the 41sample sets from the microhabitats at Zˇ ofín, Sˇ umava and Jevany (table II). The quantitative results are given in table I. The highest densities were established in sample set 25 (247 800 ind.m-2) with mosses on the soil surface in spruce forest, sample set 5 (103 300 ind.m-2) in beech forest soil below the canopy, and sample set 6 (91 000 ind.m-2) in mosses on a boulder. The lowest density was present in sample set 17 (2 200 ind.m-2) in beech forest close to the tree stem. The highest species richness was in sample sets 22 and 29 (S = 32), 1 and 9 (S = 31), and the lowest one in sample set 6 (S = 5). The highest Shannon’s diversity index was obtained for sample sets 29 (H = 2.721), 31 (H = 2.616) and 13 (H = 2.607), the lowest index in sample set 25 (H = 0.493). The highest

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Table I. Microhabitats–environmental variables and some community parameters.

Locality Nos.

Forest complexes location

Forest type

Forest age

Nos. of microhabitats

Species richness

Evenness

Shannon’s index Density of diversity (individuals·100 cm–2)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 2 2 2 2 1 2 2 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1

3 2 3 3 3 3 3 3 3 3 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 2 2 3 3 3 1 2 3 3 3 3 3

1 1 18 17 9 16 20 11 13 15 1 18 13 21 16 16 2 5 3 3 6 20 13 15 11 18 20 4 11 20 11 1 7 8 1 1 2 5 3 5 6

31 24 26 17 23 5 24 31 27 29 20 17 22 17 17 13 19 22 20 19 18 32 25 30 18 25 26 27 32 27 32 28 17 23 26 25 23 28 26 26 26

.517 0.564 0.721 0.742 0.533 0.360 0.813 0.694 0.647 0.719 0.726 0.540 0.844 0.324 0.504 0.337 0.812 0.727 0.683 0.584 0.708 0.706 0.704 0.714 0.171 0.630 0.792 0.755 0.785 0.721 0.755 0.753 0.708 0.515 0.546 0.782 0.613 0.673 0.550 0.767 0.734

1.775 1.794 2.347 2.101 1.670 0.579 2.585 2.384 2.131 2.422 2.176 1.530 2.607 0.917 1.429 0.865 2.390 2.248 2.046 1.720 2.446 2.448 2.267 2.430 0.493 2.029 2.580 2.488 2.721 2.378 2.616 2.508 2.006 1.615 1.778 2.516 1.922 2.241 1.791 2.498 2.393

823 617 296 654 505 1241 280 710 691 426 338 1527 271 928 540 1246 97 178 246 308 138 612 686 583 2743 463 565 672 470 521 728 491 316 783 491 421 810 341 805 657 372

Forest locations: 1 - Jevany, 2 - Zˇ ofín, 3 - Sˇ umava. Forest type: 1 - beech, 2 - spruce. Forest age: 1 - young (1–10 years), 2 - medium (10–30 years), 3 - old (climax). Nos of microhabitat: see section 2.1. Localities and microhabitats.

evenness was obtained in sample set 13 (E = 0.844), and the lowest one in sample set 25 (E = 0.171).

3.2. Two way indicator species analysis The TWINSPAN dendrogram of sample classification using the presence-absence data of collembolan communities indicated the faunistic similarity of sites and microhabitats (figure 1). At the first level, the 41 microhabitats divided into a left branch – i.e. cluster (26) containing 26 microhabitats – with Protaphorura triparallata as the indicator species, and a right branch comprising cluster (15) with indicator species Folso-

mia penicula and Deharvengiurus denisi . Cluster (15) contained all sample sets from Jevany, whereas cluster (26) contained all sample sets from Zˇ ofín and Sˇ umava. At the second level, cluster (15) divided into cluster (5) without indicators, and cluster (10) with Folsomia quadrioculata as indicator. At the third level, cluster (5) divided into two groups: sample set 37 without indicators and sample sets 38-41 with Parisotoma notabilis as indicator. Also at the third level, cluster (10) divided into cluster (3) with sample sets 32-34 and Mesaphorura yosii as indicator, and cluster (7) without indicators. At the fourth level, cluster (7) divided into sample set 29, 31, 35 and 36 with

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Table II. List of species and their abbreviations from the 41 forest microhabitats. Allacma fusca (Linné, 1758) Anurida granaria (Nicolet, 1847) Anurida granulata Agrell, 1943 Anurida sensillata Gisin, 1953 Anurophorus atlanticus Fjellberg, 1974 Archaphorura sp. n. Arrhopalites cochlearifer Gisin, 1947 Arrhopalites sp. Ceratophysella armata (Nicolet, 1841) Ceratophysella bengtssoni (Agren, 1904) Ceratophysella denticulata (Bagnall, 1941) Ceratophysella granulata (Stach, 1949) Ceratophysella sp. Cryptopygus sp. Deharvengiurus denisi (Stach, 1934) Deutonura conjuncta (Stach, 1926) Dicyrtoma fusca (Lucas, 1842) Dicyrtomina minuta (O. Fabricius, 1783) Dicyrtomina ornata (Nicolet, 1841) Doutnacia sp.n. Entomobrya corticalis (Nicolet, 1841) Entomobrya nivalis (Linné, 1758) Entomobrya sp. Folsomia inoculata Stach, 1947 Folsomia lawrencei Rusek, 1984 Folsomia manolachei Bagnall, 1939 Folsomia nana Gisin, 1957 Folsomia penicula Bagnall, 1939 Folsomia quadrioculata (Tullberg, 1871) Folsomia sensibilis Kseneman, 1936 Folsomia tesari Dunger, 1970 Friesea atypica Cassagnau, 1958 Friesea cf. mirabilis (Tullberg, 1871) Friesea sp. Friesea sp.n. Friesea truncata Cassagnau, 1958 Heteromurus nitidus (Templeton, 1835) Heteronychiurus stiriacus (Stach, 1946) Hypogastrura socialis (Uzel,1891) Isotoma hiemalis Schött, 1893 Isotoma nivalis Carl, 1910 Isotoma sp. Isotoma violacea Tullberg, 1876 Isotomiella minor (Schäffer, 1896) Karlstejnia sp.n. Lepidocyrtus curvicollis Bourlet, 1839 Lepidocyrtus cyaneus Tullberg, 1871 Lepidocyrtus lignorum (Fabricius, 1781) Lepidocyrtus sp. Lepidocyrtus vexillosus Loksa & Bogojevic, 1967 Lepidocyrtus violaceus (Lubbock, 1873) Lipothrix lubbocki (Tullberg, 1872) Megalothorax minimus Willem, 1900 Mesaphorura critica Ellis, 1976 Mesaphorura hylophila Rusek, 1982 Mesaphorura italica (Rusek, 1971) Mesaphorura jarmilae Rusek, 1982 Mesaphorura jevanica Rusek, 1996 Mesaphorura krausbaueri Börner, 1901 Mesaphorura macrochaeta Rusek, 1976 Mesaphorura rudolfi Rusek, 1987 Mesaphorura sp. Mesaphorura sylvatica (Rusek, 1971) Mesaphorura tenuisensillata (Rusek, 1974) Mesaphorura yosii (Rusek, 1967) Micranurida anophthalmica Stach, 1949 Micranurida sp. Micraphorura absoloni (Börner, 1901) Neanura parva (Stach, 1951) Neanura pseudoparva Rusek, 1963 Neelides folsomi Caroli, 1912

All fus Anu grn Anu gra Anu sen Anu atl Arc spn Arr coc Arr sp. Cer arm Cer ben Cer den Cer gra Cer sp. Cry sp. Deh den Deu cjt Dic fus Dic min Dic orn Dou spn Ent cor Ent niv Ent sp. Fol ino Fol law Fol man Fol nan Fol pen Fol qua Fol sen Fol tes Fri aty Fri mir Fri sp. Fri spn Fri tru Het nit Het sti Hyp soc Iso hie Iso niv Iso sp. Iso viol Iso min Kar spn Lep cur Lep cya Lep lig Lep sp. Lep vex Lep vio Lip lub Meg min Mec cri Mes hyl Mes ita Mes jar Mes jev Mes kra Mes mac Mes rud Mes sp. Mes syl Mes ten Mes yos Mic ano Mic sp. Mic abs Nea par Nea pse Nee fol

Onychiuroides granulosus (Stach, 1930) Orchesella bifasciata Nicolet, 1841 Orchesella flavescens (Bourlet, 1839) Paratullbergia callipygos (Börner, 1902) Parisotoma notabilis (Schäffer, 1896) Parisotoma sp. Pogonognathellus flavescens (Tullberg, 1871) Proisotoma minima (Absolon, 1901) Protaphorura armata (Tullberg, 1869) Protaphorura austriaca (Butschek, 1948) Protaphorura cancellata (Gisin, 1956) Protaphorura cf. armata (Tullberg, 1871) Protaphorura cf. gisini (Haybach, 1960) Protaphorura cf. pannonica (Haybach, 1960) Protaphorura cf. parallata (Gisin, 1952) Protaphorura cf. subarmata (Gisin, 1957) Protaphorura cf. subparallata (Selga, 1962) Protaphorura cf. vontoernei (Gisin, 1957) Protaphorura conlata (Gisin, 1962) Protaphorura illaborata (Gisin, 1952) Protaphorura parallata (Gisin, 1952) Protaphorura pseudovanderdrifti (Gisin, 1957) Protaphorura silesiaca Pomorski, 1998 Protaphorura sp. Protaphorura sp.1 Protaphorura sp.2 Protaphorura sp.3 Protaphorura sp.4 Protaphorura sp.5 Protaphorura sp.6 Protaphorura sp.n. Protaphorura subcancellata (Gisin, 1963) Protaphorura subhumata (Selga, 1963) Protaphorura subparallata (Selga, 1962) Protaphorura subuliginata (Gisin, 1956) Protaphorura tricampata (Gisin, 1956) Protaphorura triparallata (Gisin, 1960) Protaphorura vanderdrifti (Gisin, 1952) Pseudachorutella asigillata (Börner, 1901) Pseudachorutes boerneri (Schött, 1902) Pseudachorutes parvulus (Börner, 1901) Pseudachorutes subcrassus Tullberg, 1871 Pseudanurophorus binoculatus (Kseneman, 1934) Pseudisotoma sensibilis (Tullberg, 1876) Pseudosinella alba (Packard, 1873) Pseudosinella bohemica Rusek, 1979 Pseudosinella hercynica Rusek, 1979 Pseudosinella zygophora (Schille, 1908) Sminthurides parvulus (Krausbauer, 1898) Sminthurides schoetti (Axelson, 1903) Sminthurides signatus (Krausbauer, 1898) Sminthurinus alpinus Gisin, 1953 Sminthurinus aureus (Lubbock, 1862) Sminthurinus concolor (Meinert, 1896) Sminthurinus igniceps (Reuter, 1881) Sminthurinus niger (Lubbock, 1868) Sminthurinus sp. Sphaeridia pumilis Krausbauer, 1898) Stenaphorura quadrispina Börner, 1901 Tetracanthella fjellbergi Deharveng, 1987 Tetracanthella stachi Cassagnau, 1959 Tomocerus minor (Lubbock, 1862) Tomocerus minutus Tullberg, 1876 Vertagopus cinereus (Nicolet, 1841) Willemia anophthalma Börner, 1901 Willemia aspinata Stach, 1949 Willemia scandinavica Stach, 1949 Willovsia nigromaculata (Lubbock, 1873) Xenylla boerneri Axelson, 1905 Xenylla brevisimilis Stach, 1949 Xenylla corticalis Börner, 1901

Ony gran Orc bif Orc fla Par cal Par not Par sp. Pog fla Pro min Pro arm Pro aus Pro can Pro car Pro gis Pro pan Pro cpa Prot sua Pro sur Pro von Pro cnl Pro ill Pro par Pro psv Pro sil Pro sp. Prot sp1 Pro sp2 Pro sp3 Pro sp4 Pro sp5 Pro sp6 Pro spn Pro suc Pro suh Pro sup Pro suu Pro tri Pro tri Pro van Pse asi Pse boe Pse par Pse sub Pse bin Pse sen Pse alb Pse boh Pse her Pse zyg Smi par Smi sch Smi sig Smi alp Smi aur Smi col Smi ign Smi nig Smi sp. Sph pum Ste qua Tet fje Tet sta Tom mir Tom min Ver cin Wil ano Wil asp Wil sca Wil nig Xen boe Xen bre Xen cor

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Figure 1. TWINSPAN dendrogram of presence-absence (1;0) data. For the species abbreviation see table II and for the microhabitat numbers see table I.

Figure 2. TWINSPAN dendrogram of log-transformed quantitative data. For the species abbreviation see table II and for the microhabitat numbers see table I.

Folsomia manolachei, Anurida granulata and Pseudachorutes parvulus as indicator species, and sample sets 27, 28 and 30 without indicators. Cluster (26), positioned at the first level of the left branch in figure 1, subdivided at the second level into clusters (5) and (21). Cluster (5) had Xenylla boerneri, Entomobrya corticalis and Xenylla brevisimilis as indicators, then divided at the third level into sample sets 14-16 with Isotomiella minor as indicator, and sample sets 6 and 12 without indicators. Cluster (21) had Pseudanurophorus binoculatus and Lepidocyrtus curvicollis as indicators. At the third level, cluster (21) divided into cluster (5) containing all sample sets from Sˇ umava with Sminthurinus signatus as indicator, and at the fourth level had sample sets 22-25 with Pseudanurophorus binoculatusas as indicator. Cluster (16), with Isotoma violacea as indicator, divided at the fourth level into sample sets 17-21 with Folsomia manolachei as indicator, and sample sets 1-5, 7-11 and 13 without indicator species. The TWINSPAN dendrogram, which represented coenotical similarity of samples [11], was based on log-transformed quantitative data of collembolan communities (figure 2). The 41 microhabitats divided at the first level into a right branch, cluster (24) with Protaphorura triparallata as indicator species, and a left branch, cluster (17) with Folsomia penicula and Deharvengiurus denisi as indicators. Cluster (24) contained all samples from Zˇ ofín and sample sets 22, 23 and 25 from Sˇ umava, whereas cluster (35) comprised all sample sets from Jevany and sample set 24 from Sˇ umava. At the second level, cluster (24) divided into cluster (6) with Xenylla boerneri as indicator, and cluster (18) without indicators. At the third level, cluster (6) divided into sample sets 6 and 12 without indicators, and sample sets 14-16 and 25 with Isotomiella minor as indicator. Cluster (18) divided at the third level into cluster (5) with

Folsomia manolachei as indicator, and cluster (13) without indicators. Cluster (5) divided at the fourth level into sample sets 17 and 20 without indicators, and sample sets 18, 19 and 21 with Tomocerus minutus as indicator. Cluster (13) divided at the fourth level into sample sets 1, 5, 7-11, 13, 22 and 23 without indicators, and sample sets 2-4 with the juvenile Entomobrya sp. as indicator. The main left branch of figure 2, cluster (17), divided at the second level into cluster (6) without indicators, and cluster (11) with Folsomia quadrioculata as indicator. Cluster (6) divided at the third level into sample set 24 with Protaphorura triparallata as indicator, and a left cluster without indicators which at the fourth level divided into sample sets 38, 40 and 41 without indicators, and sample sets 37 and 39 with Pseudisotoma sensibilis as indicator. Cluster (11) divided at the third level into cluster (8) without indicators, and cluster (3) comprising sample sets 32-34 with Mesaphorura yosii as indicator. Cluster (8) divided at the fourth level into sample set 26 with Protaphorura triparallata as indicator, and sample sets 27-31, 35 and 36 without indicators.

3.3. Canonical correspondence analysis The log-transformed data and down-weighting of rare species were used in the CCA. The stepwise selection of environmental variables showed the greatest dissimilarity of species data among the geographically different sites (figure 3). Microhabitat 16 (mosses on boulder) was significantly different from other microhabitats (P < 0.01) (figure 4). This was followed by a significant difference between beech and spruce forests (P < 0.01) (figure 5), and between age of forests (P < 0.05) (figure 6), and the indicators of all of the other microhabitats, but their contribution was no longer significant. The first two CCA axes explain

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Figure 5. CCA for log-transformed quantitative species data and Fagetum and Piceetum environmental variables. For the species abbreviation see table II.

Figure 3. CCA for log-transformed quantitative species data and Zˇ ofín, Sˇ umava and Jevany environmental variables. For the species abbreviation see table II.

Figure 6. CCA for log-transformed quantitative species data and Forest Age as environmental variables. For the species abbreviation see table II.

(S. alpinus, S. concolor, E. corticalis), hemiedaphic (F. nana) and xerophilous ( A. atlanticus) forms also have specific microhabitat requirements.

5. DISCUSSION Figure 4. DCA for log-transformed quantitative microhabitat communities data and Zˇ ofín, Sˇ umava, Jevany, Fagetum and Piceetum environmental variables. For microhabitats numbers see table I.

21.2% of variability of the species data, with the first CCA axis contributing 14%. This 21.2% of variability represents 61% of the sum that was explained by all canonical axes.

3.4. Species living in one or two microhabitats Only 11.6% of the 142 species had densities of 10 individuals.100 cm–2, or higher, in one or two patches (table III). Most of such highly specialized species belong to euedaphic life forms, but some epigeic

Collembolan communities in soils of different forests have been studied by many authors, but only a few of these have dealt with the communities in forest microhabitats. For example, Kopeszki [8] studied the micro-distribution of individual collembolan species around beech trees in areas influenced by acid rain. Near beech stems, the soil pH was very low (< 3) and this influenced negatively the density or occurrence of most species of Collembola. Only the acidotolerant Mesaphorura hylophila survived the extreme acidity near beech stems, whereas the acidophobes Isotomiella minor, Parisotoma notabilis and Onychiuroides granulosus occurred farther away from the trees where the soil was less acidic (pH > 4). I could not establish such soil pH differences in the Bohemian forests of the present study, nevertheless some species were bound

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Table III. Species living in higher density in one or two patches only No. / A – micro habitat No. / density A.

Species Anurophorus atlanticus Neelides folsomi Micranurida anophthalmica Paratullbergia callipygos Protaphorura austriaca Protaphorura sp. 2 Protaphorura sp. 6 Sminthurinus alpinus Sminthurinus concolor Entomobrya corticalis Folsomia inoculata Folsomia nana Karlstejnia sp.n. Protaphorura subparallata Protaphorura cf. subparallata

locality:

No./A

No./A

37/325 5/23 8/18 31/24 23/11 9/27 40/10 12/42 6/156 12/16 13/20 5/19 1/111 24/20 25/10

– – – – – – – – – 15/13 26/158 9/49 2/62 25/18 26/21

Higher density is A ≥ 10 ind·100 cm–2. For locality No. and their characteristics see table I.

to the vicinity of trees, too (e.g. Anurophorus atlanticus). This species seems to be well adapted to high temperature and moisture fluctuation near the tree. Climatic conditions greatly influence the occurrence of collembolan species. The high density of some epigeic species in ecotones is, in most cases, influenced by climatic conditions [14]. Pseudachorutella clavata (Börner, 1901) is rare and widespread in Europe, but it reaches high epigeic density and activity in a forest-grassland ecotone [14]. The “moss on boulders” microhabitat was separated with a high significance from all other microhabitats under study. This microhabitat has many species in common with some collembolan communities on granite boulders in north Austria [1]. Typical species there were connected with early stages of soil development and high temperature and moisture fluctuation [2]. The microhabitats on boulders and rock outcrops with advanced soil development below the moss cushions were closer to other forest floor microhabitats in the present study. Similar results were published for oribatid mite communities inhabiting saxicolous moss cushions with less and more developed humus horizons [9]. In the Bohemian forests, secondary forest succession was linked to a group of microhabitats and species that were significantly separated from other microhabitat communities. Conversely, some usually rare species, e.g. in the genera Karlstejnia and Neelides, were dominant or frequent in some microhabitats in climax forests. Stumps and decaying wood represent another microhabitat partly connected to secondary forest succession. Folsomia sp.? macroseta Ford, 1962 was typical for older stumps in Douglas-fir forests on Vancouver Island, Canada [15], and Folsomia inoculata occurred

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in very high density in black decaying wood microhabitat in South Bohemia at Zˇ ofín and Sˇ umava. The microarthropods living in such microhabitats could play an important role in forest succession as suggested by the present study. The significant faunistic and coenotic differences among the three forest complexes in different parts of the Czech Republic was very surprising. This may have been caused by the different zoogeographical origins of the collembolan species composing the microhabitat communities, and the invasion rate of these forests to Central Europe since the last glacial period. From the Carpathian refugium, soil fauna has invaded together with the whole beech forest ecosystem up to the eastern banks of the Vltava River during the humid Atlantic and Epiatlantic Periods [11]. Thus the beech forest at Jevany exhibited Carpatho-Sudetic collembolan elements, as Deharvengiurus denisi, Tetrodontophora bielanensis (Waga, 1842), and Tetracanthella fjellbergi, whereas the south Bohemian beech and spruce forests contained many species from the Alps, e.g. Tetracanthella stachi, Folsomia nana, Sminthurinus alpinus, and Heteronychiurus stiriacus. The results have shown that patches influence substantially the biodiversity of forest soil. In Zˇ ofín with 14 microhabitats the species richness was 90, whereas in Jevany with 10 microhabitats it was only 78, and it might even be less in managed forests, which was not included in this study. Therefore in soil biodiversity research in forests or other habitats with heterogeneous soil surface, different microhabitats should be incorporated into the sampling scheme to get more realistic results. Forest management and nature protection practices should support microhabitat richness to ensure high functional biodiversity in soil and whole ecosystems.

Acknowledgements. This work was supported by grant project No. A6066702 from the Grant Agency of the Academy of Sciences of the Czech Republic and grant project No. 206/99/1416 from the Grant Agency of the Czech Republic. Permission for the research in the Natural Protected Areas was kindly obtained from the Ministry of Environment of the Czech Republic. I thank Dr. V.G. Marshall (Victoria, BC, Canada) for critical comments and English improvement of the manuscript.

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