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Dry grasslands of Germany – call to support an initiative for a consistent, plot-based classification

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We present the plans for a comprehensive, national dry grassland database of Germany, in which vegetation-plot records from different databases will be joined. These data will particularly be used for a plot-based, consistent classification of dry grassland vegetation in Germany. The results of the classification project shall then be published in a special feature contribution to Applied Vegetation Science and in the series Synopsis der Pflanzengesellschaften Deutschlands. We warmly invite persons who have dry grassland relevés to participate in this project by contributing data and/or helping with data analysis.
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435
Dry grasslands of Germany – call to support an initiative
for a consistent, plot-based classication
ute jandt, thomas becker & jürGen denGler
Zusammenfassung
Abstract
We present the plans for a comprehensive, national dry grassland database for Germany, in which
vegetation-plot records from different databases will be collected. These data will particularly be
used for a plot-based, consistent classication of dry grassland vegetation in Germany. The results of
the classication project will then be published in a special feature contribution to Applied Vegeta-
tion Science and in the series Synopsis der Panzengesellschaften Deutschlands. We warmly invite
persons who have dry grassland relevés to participate in this project by contributing data and/or
helping with data analysis.
Trockenrasen in Deutschland – Aufruf zur Mithilfe bei einer Initiative für eine einheitliche,
Aufnahme-basierte Klassikation
Es werden die Pläne für eine einheitliche, nationale Datenbank der Trockenrasen Deutschlands vor-
gestellt, in der die Vegetations-Daten aus verschiedenen Datenbanken zusammengeführt werden
sollen. Hiermit soll zunächst eine Aufnahme-basierte, einheitliche Klassikation der Trockenrasen-
Vegetation in Deutschland erstellt werden. Wir beabsichtigen, die Ergebnisse des Klassikations-
Projektes in der Zeitschrift Applied Vegetation Science sowie in der Reihe Synopsis der Pan-
zengesellschaften Deutschlands zu veröffentlichen. Eigentümer von Vegetationsaufnahmen von
Trockenrasen bitten wir hiermit herzlich um Mithilfe bei der Realisierung dieses Projektes.
Dry grasslands are in the focus of nature conservation throughout Central Europe, as they are extre-
mely diverse and at the same time highly endangered. However, the conservation and protection of
dry grassland habitats in Germany is largely based on traditional subjective classication schemes
developed decades ago (e.g. krAusch 1961, 1968, korneck 1974, 1975, oBerdorfer 1978, jeckel
1984). In general, these studies were based on limited datasets both in terms of geographic coverage
and numbers of relevés, and could not rely on the numerical methods available today. More recently,
there have been a few plot-based studies with transparent numerical methods, such as jAndt (1999)
for the Harz and Kyffhäuser regions and denGler (2004a, 2004b) for Mecklenburg-Vorpommern,
but none covered the whole of Germany. Accordingly, the available country-wide classications
(Pott 1995, schuBert et al. 2001, rennwAld 2002) are basically amalgamations of different, often
incompatible concepts. There is therefore a great need for a consistent syntaxonomic classication of
dry grasslands in Germany to meet the standards of neighbouring countries (e.g. mucinA et al. 1993,
schAminée et al. 1996, chytrý 2007, jAnišoVá 2007). There is also evidence that the discreteness of
some syntaxa is overrated while other units are largely underestimated or even overlooked (e.g. the
acidophilous semi-dry grasslands of the lower mountain ranges in southern Germany; see Becker
et al. 2012).
With the initiative of the German Arbeitsgruppe Trockenrasen presented in this article, we intend to
classify the syntaxa of dry grasslands based on a comprehensive vegetation database covering the
whole territory of Germany and all dry grassland types, characterise the derived syntaxa oristically
and ecologically, and analyse their geographical distribution (for photographic examples of syntaxa
see Figures 2–17). Further, we plan to compile conservation-relevant information for each distingu-
ished syntaxon, e.g. appropriate conservation measures and information on historical development.
For the future, we envision the establishment of an internet-platform, which will enable anyone
interested in dry grassland vegetation to share their data, analytical methods and results. The Ger-
man Dry Grassland Database will be part of the GVRD (German Vegetation Reference Database;
GIVD-ID EU-DE-014, jAndt&Bruelheide 2012), which is the vegetation data research platform
of the newly established German Centre for Integrative Biodiversity Research, iDiv (http://www.
idiv-biodiversity.de/). This database initiative of the German Arbeitsgruppe Trockenrasen within the
European Dry Grassland Group (EDGG; see VrAhnAkis et al. 2013) is meant to support nature con-
servation as well as research on biodiversity patterns and other ecological topics. Its success relies on
the willingness of persons with dry grassland vegetation data to contribute them to a joint database.
1
Introduction
436 jandt et al.: Dry grasslands of Germany – call to support an initiative
The common database format of the already existing database is TURBOVEG (hennekens&schA-
minée 2001), which enables easy data exchange via the comprehensive species reference list Ger-
manSL (jAnsen & denGler 2008). Presently, databases managed by the three initiators comprise
approx. 26,000 dry grassland relevés from Germany (Table 1), mainly from the vegetation classes
Festuco-Brometea, Koelerio-Corynephoretea (incl. Sedo-Scleranthetea), Violetea calaminariae,
Trifolio-Geranietea, and Elyno-Seslerietea. However, the spatial coverage is still incomplete, es-
pecially for the Northwest German lowlands (Northrhine-Westphalia, Lower Saxony and Schles-
wig-Holstein), Saxony and South Germany except the Swabian-Franconian Alb (Fig. 1). Therefore,
further efforts are needed to include data from other (public or private) databases and to digitize
relevés from undersampled regions.
2
Data management
and methods
Table 1:
Contributing databases with dry
grassland relevés from Germany.
Database identiers and names are
given according to the Global In-
dex of Vegetation-Plot Databases
(GIVD; http://www.givd.info/;
denGler et al. 2011, 2012).
Database identier Database name Number of German dry
in GIVD in GIVD grassland plots contained
EU-00-002 Database Dry Grasslands in the Nordic ca. 3,500
and Baltic Region
EU-00-007 VIOLETEA – heavy metal grasslands ca. 600
EU-DE-001 VegMV – the vegetation database of ca. 2,000
Mecklenburg-Vorpommern
EU-DE-013 VegetWeb – the national online-repository ca. 1,000
of vegetation plots from Germany
EU-DE-014 German Vegetation Reference Database (GVRD) ca. 17,000
EU-DE-034 Dry Grassland Central Germany Database ca. 3,000
Fig. 1:
Distribution of the approx. 18.000
dry grassland vegetation plots with
geographic coordinates in the con-
tributing databases. Occurrences
were pooled to central points of
the topographical map grid of
Germany.
steppenlebensräume europas – GefährdunG, erhaltunGsmassnahmen und schutz
437
Fig. 4:
Cirsio-Brachypodion pinnati with Adonis vernalis,
Kyffhäuser, Thuringia (Photo: U. Jandt).
Fig. 5:
Festucion valesiacae, Mainz Basin, Rhineland-Palatinate
(Photo: J. Dengler, JD125289).
Fig. 2:
Bromion erecti, Swabian Alb, Baden-Württemberg
(Photo: J. Dengler, JD080712).
Fig. 3:
Xero-Bromion erecti, Unstrut Valley, Saxony-Anhalt
(Photo: T. Becker).
Fig. 6:
Armerion elongatae, Upper Rhine Valley, Hesse
(Photo: J. Dengler, JD103044).
Fig. 7:
De-alpine grasslands with Sesleria albicans, Franconian Alb,
Bavaria (Photo: J. Dengler, JD093884)
Fig. 8:
Koelerio-Phleion phleoidis. Rheinhesse, Rhineland-Palatinate
(Photo: J. Dengler, JD125060).
Fig. 9:
Festucion pallentis. Southern Harz, Saxony-Anhalt
(Photo: U. Jandt).
438 jandt et al.: Dry grasslands of Germany – call to support an initiative
Fig. 12:
Hyperico perforati-Scleranthion perennis, Lahn-Dill High-
lands, Hesse (Photo: J. Dengler, JD102744).
Fig. 13:
Corynephorion canescentis, Elbe Valley, Lower Saxony
(Photo: J. Dengler, JD080650).
Fig. 10:
Koelerion glaucae, Mainz Basin, Rhineland-Palatinate
(Photo: T. Becker).
Fig. 11:
Alysso alyssoidis-Sedion, Unstrut Valley, Saxony-Anhalt
(Photo: T. Becker).
Fig. 14:
Armerion halleri, Harz Mts., Lower Saxony
(Photo: T. Becker).
Fig. 15.:
Veronicion dillenii, Unstrut Valley, Thuringia
(Photo: T. Becker).
Fig. 16:
Sileno conicae-Cerastion semidecandri, Upper Rhine Valley,
Hesse (Photo: J. Dengler, JD102903).
Fig. 17:
Thero-Airion, Upper Rhine Valley, Hesse
(Photo: J. Dengler, JD103011).
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439
We would like to encourage colleagues who have dry grassland relevés not yet in our databases
(check with author search on the GVRD homepage, http://www.biologie.uni-halle.de/bot/vegetati-
on_db/ or ask authors), to enter contribute to the database project. Interested researchers may also
join the classication project. Numerical methods will be applied for data classication, like cluster
analysis (e.g. roleček et al. 2009), and delity analyses (e.g. chytrý et al. 2002, tichý&chytrý
2006), and denition of species groups with the Cocktail method (Bruelheide 1995). We intend
to publish the results in a special feature contribution in Applied Vegetation Science (denGler et
al. 2013) and in the German series Synopsis der Panzengesellschaften Deutschlands (http://www.
tuexenia.de/index.php?id=58). Vegetation-plot data gathered within the German Dry Grassland Da-
tabase will be made available for further research, environment protection and teaching purposes via
iDiv’s database portal (under construction).
We thank all the people who have recorded vegetation-plot data and let us include their records into
the databases. Thanks also to the many student helpers, who have devoted time and effort to the
digitization of vegetation relevés. Gunnar Seidler (Halle/Saale) designed the map of Germany with
dry grassland coordinates (Fig. 1). Parts of our work have been funded by the DFG Priority Program
1374 “Infrastructure-Biodiversity-Exploratories” (DFG BR 1698/11-1).
Acknowledgements
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Addresses of authors
Dr. Ute Jandt
Martin Luther University Halle Wittenberg
Institute of Biology / Geobotany and Botanical Garden
Am Kirchtor 1
06108 Halle
GERMANY
E-Mail: ute.jandt@botanik.uni-halle.de
German Centre for Integrative Biodiversity Research (iDiv)
University of Leipzig
Deutscher Platz 5e
04103 Leipzig
GERMANY
Dr. Thomas Becker
Regional and Environmental Sciences / Geobotany
University of Trier
Behringstr. 21
54296 Trier
GERMANY
E-Mail beckerth@uni-trier.de
PD Dr. Jürgen Dengler
Disturbance Ecology
University of Bayreuth
Universitätsstr. 30
95447 Bayreuth
GERMANY
E-Mail juergen.dengler@uni-bayreuth.de
German Centre for Integrative Biodiversity Research (iDiv)
University of Leipzig
Deutscher Platz 5e
04103 Leipzig
GERMANY
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The aim of this article is to introduce the dry grasslands of Europe and to report on the activities of the European Dry Grassland Group (EDGG), a network of dry grassland scientists and conservationists. Dry grassland are defined here as herbaceous vegetation types, mostly dominated by grasses, that inhabit climatically or edaphically dry sites. They comprise zonal steppes, alpine dry grasslands above the timberline, azonal/extrazonal dry grasslands on sites where peculiarities of soil or relief prevent forest growth, and semi-natural dry grasslands derived from centuries of low-intensity land use. Dry grasslands in most taxa host a proportion of Europe’s biodiversity that by far exceeds their spatial distribution and some of them are the richest plant communities worldwide at spatial scales < 100 m². Today, both natural steppes and semi-natural dry grasslands of Europe are highly endangered through transformation into arable fields, afforestation, land use intensification or abandonment, eutrophication or biotic invasions. The EDGG with more than 800 members from over 50 countries acts by facilitating information exchange, cooperation and joint projects towards better understanding and more effective conservation of Europe’s dry grasslands. To this end, EDGG organises annual conferences and research expeditions, publishes an online electronic Bulletin, edits Dry Grassland Special Features in international journals, and plays an active role in the science-policy interface.
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Full-text available
The aim of this article is to introduce the dry grasslands of Europe and to report on the activities of the European Dry Grassland Group (EDGG), a network of dry grassland scientists and conservationists. Dry grassland are defined here as herbaceous vegetation types, mostly dominated by grasses, that inhabit climatically or edaphically dry sites. They comprise zonal steppes, alpine dry grasslands above the timberline, azonal/extrazonal dry grasslands on sites where peculiarities of soil or relief prevent forest growth, and semi-natural dry grasslands derived from centuries of low-intensity land use. Dry grasslands in most taxa host a proportion of Europe’s biodiversity that by far exceeds their spatial distribution and some of them are the richest plant communities worldwide at spatial scales < 100 m². Today, both natural steppes and semi-natural dry grasslands of Europe are highly endangered through transformation into arable fields, afforestation, land use intensification or abandonment, eutrophication or biotic invasions. The EDGG with more than 800 members from over 50 countries acts by facilitating information exchange, cooperation and joint projects towards better understanding and more effective conservation of Europe’s dry grasslands. To this end, EDGG organises annual conferences and research expeditions, publishes an online electronic Bulletin, edits Dry Grassland Special Features in international journals, and plays an active role in the science-policy interface.
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The project "Die Pflanzengesellschaften Mecklenburg-Vorpommerns und ihre Gefährdung" (The plant communities of Mecklenburg-Vorpommern and their vulnerability) is published as a two-volume series consisting of a table volume (2001) and a text volume (2004). Based on a huge vegetation-plot database and a consistent and well-documented methodology, the complete vegetation of this federal state in NE Germany was phytociolociologally classified de novo. The result are 34 phytosociological classes, 12 subclasses, 70 orders, 6 suborders, 125 alliances and 284 associations. This text volume contains detailed descriptions, nomenclatural revisions, diagnostic species and conservation assessments of all syntaxa of Mecklenburg-Vorpommern. The Introductory section provides detailed insights into the natural history of the study region as well as the methodology of the project. The concluding Conservation section summarizes the outcomes of the unique conservation assessment methodology applied in the project. An Introduction and summary for English-speaking readers (M. Isermann & J. Dengler; pp. 16–21 of the text volume 2004) makes most of the content of both volumes accessible to persons not comprehending German.
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In the lower siliceous uplands of Central Europe, various types of nutrient-poor grasslands are widespread and grow intermingled. These species-rich grasslands, often dominated by taxa of the Festuca ovina aggregate, comprise various phytosociological classes. They are remnants of a historic rural lands -cape and are of conservation importance. Few studies on such grasslands are available and there has been disagreement in assigning them to appropriate habitat types or syntaxa. We investigated such nutrient-poor grasslands in the lower Aar valley (Middle Hesse, Rhenish Massif). We surveyed 104 vegetation plots distributed throughout the valley and identified syntaxa to (sub)association level. We carried out supervised classification combining cluster analysis, a priori assignment to classes based on prevailing diagnostic species, and regional refinement based on phi-value maximisation of the units. As a result, we classified five associations within four classes: Polytricho piliferi-Festucetum tenuifoliae/Galio harcynici-Deschampsietum flexuosae and Festuco rubrae-Genistelletum sagittalis (Calluno-Ulicetea), Jasiono montanae-Festucetum ovinae (Koelerio-Corynephoretea), Gentiano-Koelerietum pyramidatae (Festuco-Brometea) and Arrhenatheretum elatioris (Molinio-Arrhenatheretea). Ecologically, soil acidity (resulting from Ca concentrations of the bedrock) was the main cause of floristic dissimilarity of the grasslands and thus community differentiation. Many stands grew on soils with intermediate pH and showed a peculiar mixture of basiphilous and acidophilous species. We conclude that (i) our approach of supervised classification yields convincing reproducible results when a syntaxonomic system is adapted top-down to a geographically restricted area, (ii) nutrient-poor siliceous grasslands dominated by taxa of the Festuca ovina aggregate can be well assigned to ecologically meaningful syntaxa, and (iii) the nutrient-poor siliceous grasslands of the Lahn-Dill Highlands are of high conservation relevance and in urgent need of protection.
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With this Editorial, we introduce a series of articles devoted to the classification of European grasslands that will appear as a Virtual Special Feature (VSF). 'Virtual' means that each paper accepted for this Special Feature will be pub-lished separately in a standard journal issue, but when the last paper is published, all of them will be presented as a single Special Feature on the journal's website, together with a synthesis-and-outlook paper. This VSF is a joint ini-tiative of two Working Groups of the International Associ-ation for Vegetation Science: the European Dry Grassland Group (EDGG; www.edgg.org) and the European Vegetation Survey (EVS; www.euroveg.org). By organizing this VSF, we want to (1) initiate the preparation and publication of international classifications for European grasslands and (2) stimulate the necessary methodological developments for producing such studies.
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Statistical measures of fidelity, i.e. the concentration of species occurrences in vegetation units, are reviewed and compared. The focus is on measures suitable for categorical data which are based on observed species frequencies within a vegetation unit compared with the frequencies expected under random distribution. Particular attention is paid to Bruelheide's u value. It is shown that its original form, based on binomial distribution, is an asymmetric measure of fidelity of a species to a vegetation unit which tends to assign comparatively high fidelity values to rare species. Here, a hypergeometric form of u is introduced which is a symmetric measure of the joint fidelity of species to a vegetation unit and vice versa. It is also shown that another form of the binomial u value may be defined which measures the asymmetric fidelity of a vegetation unit to a species. These u values are compared with phi coefficient, chi-square, G statistic and Fisher's exact test. Contrary to the other measures, phi coefficient is independent of the number of relevés in the data set, and like the hypergeometric form of u and the chi-square it is little affected by the relative size of the vegetation unit. It is therefore particularly useful when comparing species fidelity values among differently sized data sets and vegetation units. However, unlike the other measures it does not measure any statistical significance and may produce unreliable results for small vegetation units and small data sets. The above measures, all based on the comparison of observed/expected frequencies, are compared with the categorical form of the Dufrêne-Legendre Indicator Value Index, an index strongly underweighting the fidelity of rare species.
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Aim: To propose a modification of the TWINSPAN algorithm that enables production of divisive classifications that better respect the structure of the data. Methods: The proposed modification combines the classical TWINSPAN algorithm with analysis of heterogeneity of the clusters prior to each division. Four different heterogeneity measures are involved: Whittaker's beta, total inertia, average Sørensen dissimilarity and average Jaccard dissimilarity. Their performance was evaluated using empirical vegetation datasets with different numbers of plots and different levels of heterogeneity. Results: While the classical TWINSPAN algorithm divides each cluster coming from the previous division step, the modified algorithm divides only the most heterogeneous cluster in each step. The four tested heterogeneity measures may produce identical or very similar results. However, average Jaccard and Sørensen dissimilarities may reach extreme values in clusters of small size and may produce classifications with a highly unbalanced cluster size. Conclusions: The proposed modification does not alter the logic of the TWINSPAN classification, but it may change the hierarchy of divisions in the final classification. Thus, unsubstantiated divisions of homogeneous clusters are prevented, and classifications with any number of terminal clusters can be created, which increases the flexibility of TWINSPAN.