Ann. Bot. Fennici 45: 255–268 ISSN 0003-3847 (print) ISSN 1797-2442 (online) Helsinki 29 August 2008 © Finnish Zoological and Botanical Publishing Board 2008 Classification structure of floodplain forests in Estonia: a comparison of two classification approaches Jaanus Paal1, Normunds Prieditis2, Reet Rannik1 & Eva-Maria Jeletsky1 1) Institute of Ecology and Earth Sciences, University of Tartu, Lai St. 40, 51005 Tartu, Estonia (e- mails: [email protected], [email protected], [email protected]) 2) Gandrs Publishers, Kalnciema St. 28, LV-1046 Riga, Latvia (e-mail: [email protected]) Received 30 July 2007, revised version received 21 Jan. 2008, accepted 31 Mar. 2008 Paal, J., Prieditis, N., Rannik, R. & Jeletsky, E.-M. 2008: Classification structure of floodplain for- ests in Estonia: a comparison of two classification approaches. — Ann. Bot. Fennici 45: 255–268. Flooded forests in 79 sample areas were studied in various parts of Estonia. Using the principal component analysis and cluster analysis, six community types were established: (i) Tilia cordata–Mercurialis perennis, (ii) Ulmus laevis–Allium ursinum, (iii) Populus tremula–Convallaria majalis, (iv) Alnus incana–Cirsium oleraceum, (v) Alnus glutinosa–Filipendula ulmaria and, (vi) Alnus glutinosa–Carex acutiformis. The species composition of these types partly overlaps but the abundance propor- tions of species are clearly different and all types have several significant indicator species. Another classification scheme was established by TWINSPAN analysis. Fol- lowing the phytosociological approach, the communities belong to Querco–Fagetea, Alno–Ulmion (Pruno–Fraxinetum, Ficario–Ulmetum, Pruno padi–Alnetum incanae, the latter subdivided further into P.p.–A.i. var. Frangula alnus and P.p.–A.i. var. Urtica dioica), and to Alnetea glutinosae, Alnion (Carici elongatae–Alnetum, represented with two subassociations: C.e.–A. typicum and C.e.–A. cardaminetosum). Despite different concepts used for establishment of community types by either approach the obtained results are rather similar. The syntaxa of Alno–Ulmion show particularly high internal variability, although all recognised communities have unambiguous affinities with the assemblages described elsewhere from central and northern-central Europe. Key words: indicator species, TWINSPAN, Querco–Fagetea, Alno–Ulmion, Alnetea glutinosae. Introduction in most European countries, floodplain forests have remained in comparatively small areas and Floodplain forests have very specific ecological they are recognised as strongly threatened com- conditions in the temperate zone (Klimo 2001, munities (Paal 1998). According to the Habitat Hager & Schume 2001) and are usually uniquely Directive (EC 1992), floodplain forests belong characterized by a combination of high species to the habitats of great importance (types 91E0 diversity, high density and high productivity and 91F0) for nature protection on the European (Mitsch & Gosselink 2000). In Estonia, like scale. 256 Paal et al. • ANN. BOT. FENNICI Vol. 45 At the same time, Estonian floodplain forests along the Halliste and Raudna rivers in Soomaa have been characterised only sporadically and National Park, (iii) in the Alam-Pedja Nature long time ago by Kull (1925), Lippmaa (1935), Reserve on the banks of the Pedja River and the Lunts (1938) and Marvet (1967). According to ditched Loksu Rivulet, (iv) in the valley of the the forest classification system adopted in Esto- Jänijõgi in northern Estonia and, (v) in the valley nia, these forests are not singled out as an of the Poruni River in the Puhatu Nature Reserve autonomous site type but are dealt with under (Fig. 1). Floodplain forests can be found in sev- the broad swamp forest site type (sensu Lõhmus eral other places along the brooks or rivulets as 2004). Relationship of floodplain forests with well, but there they border the watercourses as other forest types has been treated briefly by very narrow strips, form only small groves and/or Ilves (1969), Masing (1966, 1969), Marvet are intensively attenuated by cuttings. (1970), Paal (1997) and Paal et al. (2006) but not In every stand one round sample plot of ca. in a wider geographical scale or in terms of the 0.1 ha was analysed. A sample plot was estab- phytosociological syntaxonomy largely used in lished using a height and distance measuring western, central and southern Europe. Estonian instrument Suunto: one tree stem was treated forest site type classification follows Cajander’s as a central one and from that a radius of 17.8 concept (Cajander 1909, 1926, 1930, Frey 1973, m was measured in different directions. Ground Lõhmus 2004) and any attempts to connect or vegetation was described by means of randomly compare that with phytosociological classifica- located sample squares of 1 ¥ 1 m, their number tion approach are almost lacking. was 15 per stand. The total cover percentage The aims of the current study are: (i) to estab- of the herb and moss layers as well as of every lish a phytosociological classification of Estonian plant species was estimated. For further char- floodplain forests, (ii) to evaluate its correspond- acterization and classification of a respective ence to the classification scheme elaborated ear- stand (plant community) for ground vegetation lier on the basis of cluster and discriminant anal- the averaged values of 15 sample squares were yses (Paal et al. 2006, 2007) and, (iii) to compare used. If some species were recorded in a sample the syntaxa of the Estonian floodplain forests plot but were not found in the squares, they were with corresponding phytosociological units on a included in the community species list condi- wider geographical scale. tionally with a coverage of 0.01%. The number of shrub layer species stems was registered on five randomly located 2 ¥ Material and methods 2 m sample squares in every stand. Young trees (saplings) with a height of < 4 m and/or with Field study a diameter of < 5 cm at breast height (1.3 m) were also interpreted as belonging to the shrub In the current study we regarded as floodplain layer and treated as “species”. Shrub species forests stands where floods occur regularly almost outside the randomly situated squares were taken every year and last at least for a couple of weeks, into account with number 1. The tree layer was while the amount of alluvial sediments was not characterised by the mean basal area of every a decisive criterion (Ellenberg 1996, Hager & species, obtained as an average result of 3–5 Buchleitner 2001, Oszlányi 2001). All in all, 79 measurements. subnatural stands (= plant communities) were The nomenclature of vascular plant species studied in the country, representing considerably follows Leht et al. (1999) and the nomencla- well preserved floodplain forests with an area ture of bryophytes follows Ingerpuu and Vellak not smaller than 0.5 ha, and not having obvious (1998). human activities impact (only a little decaying stumps, even age tree layer, ditches, roads, lines). Forests satisfying these criteria are located in Data processing Estonia in five regions: (i) on the banks of the Rannametsa River in southwestern Estonia, (ii) Our first floodplain forest classification (Paal et ANN. BOT. FENNICI Vol. 45 • Floodplain forests in Estonia 257 NARVA RAKVERE TALLINN IV KOHTLA-JÄRVE V KÄRDLA RAPLA HAAPSALU PAIDE JÕGEVA PÕLTSAMAA III PÄRNU II TARTU VILJANDI KURESSAARE I PÕLVA VÕRU VALGA Fig. 1. Location of sample regions and sample plots. 50 km al. 2006, 2007) was based on a cluster analysis A null hypothesis of absence of difference where ten first principal components of plant between corresponding vegetation types, estab- communities’ data (relevés) were used as input. lished with the use of MISSQ and TWINSPAN These described 72% of the total variation in methods, was tested using a multi-response per- the data. A cluster analysis was performed using mutation procedure (MRPP) (McCune & Mef- the minimal incremental sum of squares algo- ford 1999). Communities were ordinated by rithm — MISSQ (Podani 2000), employing the means of a detrended correspondence analysis chord distance as the measure of dissimilarity. (DCA) (ter Braak & Šmilauer 2002); down- Objectivity of clustering of every relevé was weighting of rare species was applied. tested with a classificatory discriminant analysis (StatSoft Inc. 2001). The second classification was carried out Results using the TWINSPAN algorithm (Hill 1979, Gauch & Whittaker 1981). Values 0, 2, 5, 10 MISSQ analysis and 20 were used as pseudospecies cut levels, corresponding to the default settings of the PC- Six clusters (community types) were established ORD package (McCune & Mefford 1999). The with the MISSQ analysis: (i) Tilia cordata–Mer- obtained clusters were further interpreted in curialis perennis type, (ii) Ulmus laevis–Allium terms of phytosociology. ursinum type, (iii) Populus tremula–Convallaria Indicator values of the species in clusters majalis type, (iv) Alnus incana–Cirsium oler- were calculated using the Dufrêne and Legren- aceum type, (v) Alnus glutinosa–Filipendula dre (1997) method. According to that, for each ulmaria type, (vi) Alnus glutinosa–Carex acuti- species its relative abundance and relative fre- formis type. quency in every group (= community type) was Species composition, their indicator values, calculated. Multiplication of these two values, mutual relationships between types, as well expressed as a percentage, yields an indica- as growth conditions of respective communi- tor value for a particular species in a particular