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  • 1
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    Online Resource
    sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots
    Wiley ; 2021
    In:  Global Ecology and Biogeography Vol. 30, No. 9 ( 2021-09), p. 1740-1764
    Details
    In: Global Ecology and Biogeography, Wiley, Vol. 30, No. 9 ( 2021-09), p. 1740-1764
    Abstract: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co‐occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open‐access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local‐to‐regional datasets to openly release data. We thus present sPlotOpen, the largest open‐access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots ( n  = 95,104) recording cover or abundance of naturally co‐occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets ( c . 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot‐level data also include community‐weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01–40,000 m². Time period and grain 1888–2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot‐level records. Software format Three main matrices (.csv), relationally linked.
    Type of Medium: Online Resource
    ISSN: 1466-822X , 1466-8238
    URL: Issue
    URL: Article
    DOI: 10.1111/geb.v30.9
    DOI: 10.1111/geb.13346
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 1479787-2
    detail.hit.zdb_id: 2021283-5
    SSG: 12
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  • 2
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    Online Resource
    Modelling the distribution and compositional variation of plant communities at the continental scale
    Wiley ; 2018
    In:  Diversity and Distributions Vol. 24, No. 7 ( 2018-07), p. 978-990
    Details
    In: Diversity and Distributions, Wiley, Vol. 24, No. 7 ( 2018-07), p. 978-990
    Abstract: We investigate whether (1) environmental predictors allow to delineate the distribution of discrete community types at the continental scale and (2) how data completeness influences model generalization in relation to the compositional variation of the modelled entities. Location Europe. Methods We used comprehensive datasets of two community types of conservation concern in Europe: acidophilous beech forests and base‐rich fens. We computed community distribution models ( CDM s) calibrated with environmental predictors to predict the occurrence of both community types, evaluating geographical transferability, interpolation and extrapolation under different scenarios of sampling bias. We used generalized dissimilarity modelling ( GDM ) to assess the role of geographical and environmental drivers in compositional variation within the predicted distributions. Results For the two community types, CDM s computed for the whole study area provided good performance when evaluated by random cross‐validation and external validation. Geographical transferability provided lower but relatively good performance, while model extrapolation performed poorly when compared with interpolation. Generalized dissimilarity modelling showed a predominant effect of geographical distance on compositional variation, complemented with the environmental predictors that also influenced habitat suitability. Main conclusions Correlative approaches typically used for modelling the distribution of individual species are also useful for delineating the potential area of occupancy of community types at the continental scale, when using consistent definitions of the modelled entity and high data completeness. The combination of CDM s with GDM further improves the understanding of diversity patterns of plant communities, providing spatially explicit information for mapping vegetation diversity and related habitat types at large scales.
    Type of Medium: Online Resource
    ISSN: 1366-9516 , 1472-4642
    URL: Issue
    URL: Article
    DOI: 10.1111/ddi.2018.24.issue-7
    DOI: 10.1111/ddi.12736
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 2020139-4
    detail.hit.zdb_id: 1443181-6
    SSG: 12
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  • 3
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    EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats
    Wiley ; 2020
    In:  Applied Vegetation Science Vol. 23, No. 4 ( 2020-10), p. 648-675
    Details
    In: Applied Vegetation Science, Wiley, Vol. 23, No. 4 ( 2020-10), p. 648-675
    Abstract: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location Europe. Methods We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment.
    Type of Medium: Online Resource
    ISSN: 1402-2001 , 1654-109X
    URL: Issue
    URL: Article
    DOI: 10.1111/avsc.v23.4
    DOI: 10.1111/avsc.12519
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2053083-3
    SSG: 12
    SSG: 23
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  • 4
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    Online Resource
    sPlot – A new tool for global vegetation analyses
    Wiley ; 2019
    In:  Journal of Vegetation Science Vol. 30, No. 2 ( 2019-03), p. 161-186
    Details
    In: Journal of Vegetation Science, Wiley, Vol. 30, No. 2 ( 2019-03), p. 161-186
    Abstract: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.
    Type of Medium: Online Resource
    ISSN: 1100-9233 , 1654-1103
    URL: Issue
    URL: Article
    DOI: 10.1111/jvs.2019.30.issue-2
    DOI: 10.1111/jvs.12710
    RVK:
    WA 15000
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2047714-4
    detail.hit.zdb_id: 1053769-7
    SSG: 12
    SSG: 23
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  • 5
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    Online Resource
    Classification of the Mediterranean lowland to submontane pine forest vegetation
    Wiley ; 2021
    In:  Applied Vegetation Science Vol. 24, No. 1 ( 2021-01)
    Details
    In: Applied Vegetation Science, Wiley, Vol. 24, No. 1 ( 2021-01)
    Abstract: Vegetation types of Mediterranean thermophilous pine forests dominated by Pinus brutia , Pinus halepensis , Pinus pinaster and Pinus pinea were studied in various areas. However, a comprehensive formal vegetation classification of these forests based on a detailed data analysis has never been developed. Our aim is to provide the first broad‐scale classification of these pine forests based on a large data set of vegetation plots. Location Southern Europe, North Africa, Levant, Anatolia, Crimea and the Caucasus. Methods We prepared a data set of European and Mediterranean pine forest vegetation plots. We selected 7,277 plots dominated by the cold‐sensitive Mediterranean pine species Pinus brutia , Pinus halepensis , Pinus pinaster and Pinus pinea . We classified these plots using TWINSPAN, interpreted the ecologically and biogeographically homogeneous TWINSPAN clusters as alliances, and developed an expert system for automatic vegetation classification at the class, order and alliance levels. Results We described Pinetea halepensis as a new class for the Mediterranean lowland to submontane pine forests, included in the existing Pinetalia halepensis order, and distinguished 12 alliances of native thermophilous pine forests, including four newly described and three informal groups merging supposedly native stands and old‐established plantations. The main gradients in species composition reflect elevational vegetation belts and the west–east, and partly north–south, biogeographical differences. Both temperature and precipitation seasonality co‐vary with these gradients. Conclusions We provide the first formal classification at the order and alliance levels for all the Mediterranean thermophilous pine forests based on vegetation‐plot data. This classification includes traditional syntaxa, which have been critically revised, and a new class and four new alliances. We also outline a methodological workflow that might be useful for other vegetation classification syntheses. The expert system, which is jointly based on pine dominance and species composition, is a tool for applying this classification in research and nature conservation survey, monitoring and management.
    Type of Medium: Online Resource
    ISSN: 1402-2001 , 1654-109X
    URL: Issue
    URL: Article
    DOI: 10.1111/avsc.v24.1
    DOI: 10.1111/avsc.12544
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2053083-3
    SSG: 12
    SSG: 23
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  • 6
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    European Vegetation Archive (EVA): an integrated database of European vegetation plots
    Wiley ; 2016
    In:  Applied Vegetation Science Vol. 19, No. 1 ( 2016-01), p. 173-180
    Details
    In: Applied Vegetation Science, Wiley, Vol. 19, No. 1 ( 2016-01), p. 173-180
    Abstract: 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 vegetation‐ plot 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 large‐scale analyses of European vegetation diversity both for fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/eva-database .
    Type of Medium: Online Resource
    ISSN: 1402-2001 , 1654-109X
    URL: Issue
    URL: Article
    DOI: 10.1111/avsc.2016.19.issue-1
    DOI: 10.1111/avsc.12191
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 2053083-3
    SSG: 12
    SSG: 23
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