Distribution maps of vegetation alliances in Europe

Aim The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

Distribution maps of vegetation alliances in Europe

Aim The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

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

ReSurveyEurope: A database of resurveyed vegetation plots in Europe

Abstract Aims We introduce ReSurveyEurope — a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions. Results ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover–abundance classes such as variants of the Braun‐Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020. Conclusions ReSurveyEurope is a new resource to address a wide range of research questions on fine‐scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well‐established European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome

ReSurveyEurope : A database of resurveyed vegetation plots in Europe

Aims: We introduce ReSurveyEurope — a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We de- scribe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions. Results: ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual sur- veys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover–abun- dance classes such as variants of the Braun- Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020. Conclusions: ReSurveyEurope is a new resource to address a wide range of re- search questions on fine-scale changes in European vegetation. The initiative is de- voted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well-established European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcom

Distribution maps of vegetation alliances in Europe

Aim: The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location: Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods: We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results: Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions: The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

Comparison of the living standards in North Moravia region and Prague in the 70s and 80s of the 20th century

The Czechoslovakian economy and standard of living of the population in Czechoslovakia in the 70's and 80's of the last century, can be evaluated, in comparison with the developed countries of the former Western World, as lagging behind. However, in this comparison, has to be taken into account the different political systems of each country. The bachelor thesis deals with the analysis of living standards of citizens in selected regions of Czechoslovakia and the subsequent comparison of this two selected areas. The theoretical part includes not only an introduction into the issue of standard of living, but also the general outline of the political and economic situation in the former Czechoslovakia. Based on empirical research, the thesis is trying to find meaningful data on this issue. A comparison of expenditures and incomes of households, availability of medical and social services, equipment or free time spending -- this all is included in this research, which first analyzes the data in this two regions, which is beeing comparing in the last part. The specified hypothesis, that residents of the North Moravia region had a comparable, if not higher standard of living, than in Prague, thanks to at that time very supported steel industry, was in the framework of certain investigated factors partly confirmed. A particularly due to higher total industrial employment and the associated higher wages in this sector. The citizens of the North Moravia region had better results in the context of household equipment too. On the other hand, the people of Prague had better conditions in the availability of health and social services and richer leisure activities in the field of cultural life

Comparison of the living standards in North Moravia region and Prague in the 70s and 80s of the 20th century

Ekonomiku ČSSR a životní úroveň obyvatel v Československé republice v 70. a 80. letech minulého století lze hodnotit v porovnání s vyspělými zeměmi tehdejšího západního světa jako zaostávající. Ve srovnání však je potřeba brát v potaz rozdílné politické systémy jednotlivých zemí. Bakalářská práce se zabývá analýzou životní úrovně občanů ČSSR ve vybraných krajích a následnou komparací těchto dvou vybraných území. Teoretická část práce obsahuje nejen úvod do problematiky životní úrovně obyvatel, ale také obecný nástin politicko-ekonomické situace v tehdejším Československu. Na základě empirického výzkumu se práce pokouší najít vypovídající data o této problematice. Srovnání výdajů a příjmu domácností, dostupnost zdravotních a sociálních služeb, vybavenost spotřebiči či trávení volného času - to vše je zahrnuto ve výzkumu, který nejdříve analyzuje data v obou regionech, jež jsou následně porovnány v poslední části práce. Zadaná hypotéza, že obyvatelé Severomoravského kraje měli srovnatelnou, ne-li vyšší životní úroveň než v Praze, především díky v té době podporovanému hutnímu průmyslu, byla v rámci některých zkoumaných faktorů zčásti potvrzena. A to zejména z důvodu vyšší celkové průmyslové zaměstnanosti a s tím spojenými vyššími mzdami v tomto odvětví. Lépe na tom byli občané Severomoravského kraje také v rámci vybavenosti domácností. Na druhou stranu měli ovšem Pražané lepší podmínky v dostupnosti zdravotních a sociálních služeb a bohatší možnosti trávení volného času v oblasti kulturního vyžití.The Czechoslovakian economy and standard of living of the population in Czechoslovakia in the 70's and 80's of the last century, can be evaluated, in comparison with the developed countries of the former Western World, as lagging behind. However, in this comparison, has to be taken into account the different political systems of each country. The bachelor thesis deals with the analysis of living standards of citizens in selected regions of Czechoslovakia and the subsequent comparison of this two selected areas. The theoretical part includes not only an introduction into the issue of standard of living, but also the general outline of the political and economic situation in the former Czechoslovakia. Based on empirical research, the thesis is trying to find meaningful data on this issue. A comparison of expenditures and incomes of households, availability of medical and social services, equipment or free time spending -- this all is included in this research, which first analyzes the data in this two regions, which is beeing comparing in the last part. The specified hypothesis, that residents of the North Moravia region had a comparable, if not higher standard of living, than in Prague, thanks to at that time very supported steel industry, was in the framework of certain investigated factors partly confirmed. A particularly due to higher total industrial employment and the associated higher wages in this sector. The citizens of the North Moravia region had better results in the context of household equipment too. On the other hand, the people of Prague had better conditions in the availability of health and social services and richer leisure activities in the field of cultural life

Transcaucasian Vegetation Database – a phytosociological database of the Southern Caucasus

The Caucasus is a hotspot of global biodiversity. However, even in the era of big data, this region remains underrepresented in public vegetation-plot databases. The Transcaucasian Vegetation Database (GIVD code AS-00-005) is a novel dataset which primarily aims to compile, store and share vegetation-plot records sampled by the Braun-Blanquet approach and originating from Transcaucasia (the Southern Caucasus), i.e. the countries of Armenia, Azerbaijan and Georgia. The database currently contains 2,882 vegetation plots. The oldest plots originate from 1929, the newest from 2022, and their collection is ongoing. The data include mesophilous forests (phytosociological class Carpino-Fagetea) and various alpine and subalpine communities (e.g. Carici-Kobresietea, Loiseleurio-Vaccinietea) – selected other habitats are also represented. Most of the plots (84%) are georeferenced, 36% with high precision of 25 m or less. The database includes 2,500 taxon names; Asteraceae, Poaceae, Fabaceae and Rosaceae represent the most common families. Vascular plants are recorded in all plots, while data on species composition of bryophytes are available for 11% of plots. The database intends to contribute to the complex biodiversity research of this biologically unique territory. The data might be used in diverse projects in botany, biogeography, ecology and nature protection. Taxonomic reference: The Plant List (http://www.theplantlist.org/ [Accessed 10 Jan 2023]). Syntaxonomic reference: Mucina et al. (2016). Abbreviations: TVD = Transcaucasian Vegetation Database