5 research outputs found
EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats
Aim: 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
sPlotOpen - An environmentally balanced, open-access, global dataset of vegetation plots
Motivation 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 m(2). 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
Climate and socio- economic factors explain differences between observed and expected naturalization patterns of European plants around the world
The number of naturalized (i.e. established) alien species has increased rapidly over recent centuries. Given the differences in environmental tolerances among species, little is known about what factors determine the extent to which the observed size of the naturalized range of a species and hence the extent to which the observed richness of naturalized species of a region approach their full potential. Here, we asked which region- and species-specific characteristics explain differences between observed and expected naturalizations. Location: Global. Time period: Present. Major taxa studied: Vascular plants. Methods: We determined the observed naturalized distribution outside Europe for 1,485 species endemic to Europe using the Global Naturalized Alien Flora (GloNAF) database and their expected distributions outside Europe using species distribution models. First, we investigated which of seven socio-economic factors related to introduction pathways, anthropogenic pressures and inventory effort best explained the differences between observed and expected naturalized European floras. Second, we examined whether distributional features, economic use and functional traits explain the extent to which species have filled their expected ranges outside Europe. Results: In terms of suitable area, more than 95% of expected naturalizations of European plants were not yet observed. Species were naturalized in only 4.2% of their suitable regions outside of Europe (range filling) and in 0.4% of their unsuitable regions (range expansion). Anthropogenic habitat disturbance primarily explained the difference between observed and expected naturalized European floras, as did the number of treaties relevant to invasive species. Species of ornamental and economic value and with large specific leaf area performed better at filling and expanding beyond their expected range. Main conclusions: The naturalization of alien plant species is explained by climate matching but also by the regional level of human development, the introduction pressure associated with the ornamental and economic values of the species and their adaptation to disturbed environments
sPlotOpen:an environmentally balanced, open-access, global dataset of vegetation plots
Abstract
Motivation: 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