VegMV – the vegetation database of Mecklenburg-Vorpommern

Jansen, Florian; Dengler, Jürgen; Berg, Christian

doi:10.7809/b-e.00070

Cited by 7 publications

(6 citation statements)

References 29 publications

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“…Of these, 101 habitat types are defined by plant species in the mapping scheme. This enabled us to compare the occurrence probabilities by habitat type with those from a vegetation database of Mecklenburg–Western Pomerania (VegMV, version 15, Jansen, Dengler, & Berg, , http://www.givd.info/ID/EU-DE-001). We used this vegetation database to safeguard the calculations from the often incomplete 1996–2006 habitat species lists (Figure ).…”

Section: Methodsmentioning

confidence: 99%

“…For a discussion of the representativeness see Jansen et al. (). The number of species needed to assign a vegetation plot to a specific habitat type will influence the occupancy of this species inside versus outside of this habitat type.…”

Section: Methodsmentioning

confidence: 99%

“…This assignment of vegetation plots to habitat types enabled us to calculate probabilities of occurrence also for the area outside of the protected habitats in the normal landscape, using all those plots not assigned to habitat types as a random subset of the remaining landscape. For a discussion of the representativeness see Jansen et al (2012). The number of species needed to assign a vegetation plot to a specific habitat type will influence the occupancy of this species inside versus outside of this habitat type.…”

Section: Data Compilationmentioning

confidence: 99%

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Moderately common plants show highest relative losses

Jansen

Bonn

Bowler

et al. 2019

CONSERVATION LETTERS

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Nature conservation efforts often focus on rare species. Common and moderately common species, however, receive much less attention. Our analysis of occupancy change of flora using a grid survey in 1980 and a habitat mapping survey in 2000 in Northeast Germany revealed significant losses for most of the 355 modeled plant species. Highest losses were recorded for moderately common species. Plant species occurring in 20–40% of grid cells declined on average by 50% in 20 years, although there were some methodological uncertainties. We found no correlation between occupancy decline and Red List category, but habitat loss seems to be a main driver. We suggest to rethink conservation indicators by including previously common species in monitoring. Our approach to estimating trends, using the association of species to habitat types and occupancy–area relationships, can be applied to other regions with heterogeneous resurvey data, but it cannot replace urgently needed monitoring schemes.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Data Compilationmentioning

confidence: 99%

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Moderately common plants show highest relative losses

Jansen

Bonn

Bowler

et al. 2019

CONSERVATION LETTERS

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“…), the UK (Rodwell ), the database of the German federal state Mecklenburg‐Vorpommern (Jansen et al. ) and the Database of Dry Grasslands in the Nordic and Baltic Region (Dengler & Rūsiņa ). At the annual meeting of the European Vegetation Survey in Vienna in May 2012, the EVA Data Property and Governance Rules (http://euroveg.org/download/eva-rules.pdf) were approved, and the EVA Coordinating Board elected.…”

Section: Brief History Of the Eva Initiativementioning

confidence: 99%

European Vegetation Archive (EVA): an integrated database of European vegetation plots

Chytrý

Hennekens

Jíménez-Alfaro

et al. 2015

Applied Vegetation Science

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The European Vegetation Archive (EVA) is a centralized database of European vegetation plots developed by the IAVS Working Group European Vegetation Survey. It has been in development since 2012 and first made available for use in research projects in 2014. It stores copies of national and regional vegetationplot databases on a single software platform. Data storage in EVA does not affect on-going independent development of the contributing databases, which remain the property of the data contributors. EVA uses a prototype of the database management software TURBOVEG 3 developed for joint management of multiple databases that use different species lists. This is facilitated by the SynBioSys Taxon Database, a system of taxon names and concepts used in the individual European databases and their corresponding names on a unified list of European flora. TURBOVEG 3 also includes procedures for handling data requests, selections and provisions according to the approved EVA Data Property and Governance Rules. By 30 June 2015, 61 databases from all European regions have joined EVA, contributing in total 1 027 376 vegetation plots, 82% of them with geographic coordinates, from 57 countries. EVA provides a unique data source for largescale analyses of European vegetation diversity both for fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/evadatabase.

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“…Most data were obtained from large vegetation-plot databases (e.g. Chytrý & Rafajová 2003, Aćić et al 2012, Dengler & Rusiņa 2012, Jandt & Bruelheide 2012, Jansen et al 2012, Kuzemko 2012, Vassilev et al 2018, accessed via the European Vegetation Archive (EVA; . A smaller amount of data was directly provided by co-authors or computerized from literature (see Electronic Appendix 1 for a complete list of the sources).…”

Section: Data Setmentioning

confidence: 99%

Formalized classification of semi-dry grasslands in central and eastern Europe

Willner¹,

Roleček²,

Korolyuk³

et al. 2019

Preslia

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S. (2019) Formalized classification of semi-dry grasslands in central and eastern Europe.-Preslia 91: 25-49 European semi-dry grasslands are among the most species-rich vegetation types in the northern hemisphere and form an important part of the habitat mosaics in the forest-steppe zone. However, there is no comprehensive evaluation of the variation in their composition and the phytosociological classification of these grasslands. For the syntaxonomic revision, we used a dataset of 34,173 vegetation plot records (relevés) from central and eastern Europe, which were assigned to the class Festuco-Brometea using the diagnostic species listed in the EuroVegChecklist. To determine the diagnostic species of the orders, we used a TWINSPAN classification of the whole dataset. Of the total dataset, 15,449 relevés were assigned to the order Brachypodietalia pinnati, which corresponds to semi-dry grasslands. This subset was again classified using TWINSPAN. Formal definitions of the following alliances were established: Mesobromion erecti, Cirsio-Brachypodion pinnati (incl. Fragario-Trifolion montani, Agrostio-Avenulion schellianae, Scabioso ochroleucae-Poion angustifoliae and Adonido vernalis-Stipion tirsae), Scorzonerion villosae and Chrysopogono-Danthonion. Another alliance, Armerion elongatae (= Koelerio-Phleion phleoidis p.p.), is transitional towards the class Koelerio-Corynephoretea and its status needs further evaluation. We also established formal definitions of all of the associations of Mesobromion and Cirsio-Brachypodion within the area studied. Associations were identified using (i) a TWINSPAN classification of the whole order, (ii) TWINSPAN classifications of regionally restricted data sets (usually all Brachypodietalia plots in one country) and (iii) existing national classification schemes. All formal definitions were written in the expert system language of the JUICE program. To obtain a more complete picture of the floristic similarities and gradients, we performed a DCA ordination of the associations. Our results revealed that meadow steppes in the forest-steppe zone in eastern Europe are very similar to semi-dry grasslands in central Europe.

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VegMV – the vegetation database of Mecklenburg-Vorpommern

Cited by 7 publications

References 29 publications

Moderately common plants show highest relative losses

Moderately common plants show highest relative losses

European Vegetation Archive (EVA): an integrated database of European vegetation plots

Formalized classification of semi-dry grasslands in central and eastern Europe

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