Threat Degree Classification According to Habitat Quality: A Case Study from the Czech Republic

Important sources of information in the field of nature protection are red lists, which define the degree of threat to individual species. In practice, an assessment of the quality of the habitats in which a species occurs is used to a very limited extent in the preparation of red lists of vascular plants. At the same time, this parameter is usually essential to determine their degree of threat. At present, habitat quality data are available for the territory of the Czech Republic; these were obtained during Natura 2000 habitat mapping in the years 2000–2019. In this paper we propose the use of habitat quality data to determine the degree of threat to selected species of vascular plants and to compile a national red list. Nine plant species from three habitat types were selected for this study: meadows and wetland habitats in the alluvium of large rivers (Cardamine matthioli Moretti, Gratiola officinalis L., Teucrium scordium L.), fen habitats (Carex appropinquata Schumach., C. cespitosa L., C. lepidocarpa Tausch) and ecotone shrub habitats (Rosa agrestis Savi, R. micrantha Borrer ex Sm., R. spinosissima L.). For these species, the quality of the habitats in which they occur was analysed and grid maps were created, which present (1) the level of knowledge of habitat quality and (2) the average habitat quality. The results were compared with the degree of threat in the current national red list. Habitat quality analysis should also be used in the future to detect threatened species, which today are outside the red list and this assessment may be useful in compiling another updated red list of vascular plants of the Czech Republic

How to Protect Natural Habitats of Rare Terrestrial Orchids Effectively: A Comparative Case Study of Cypripedium calceolus in Different Geographical Regions of Europe

In this article we present and discuss the main factors that threaten natural populations of Cypripedium calceolus (lady’s slipper orchid) in Europe, and we propose conservation strategies and directions for protective actions of its population on a regional scale. European C. calceolus populations have decreased significantly in the last two decades, in both number and size. A key result of the present study is an evaluation of the effectiveness of the Natura 2000 network across the European Union (EU) countries. Northern and/or mountainous countries present higher percentages of potentially suitable areas within the Natura 2000 network. Finland and the United Kingdom are the exceptions to this rule. It is predicted that, due to global warming, the coverage of niches suitable for C. calceolus will decrease in countries in which now-healthy colonies exist. However, as plant species can occur in micro-sites with suitable environmental conditions (e.g., microclimate, vegetation, soil factors) which cannot be predicted as suitable at coarser spatial resolutions, conservation efforts should be focused on management of local healthy populations. For the effective protection of C. calceolus in Natura 2000 sites, the participation of experts in botany, including orchid biology, is necessary at several stages

Analýza biodiverzity v CHKO Bílé Karpaty jako podklad pro stanovení nové zonace a vhodného managementu cenných území

Cílem projektu je zpracovat návrh nové zonace CHKO Bílé Karpaty včetně optimální péče o nejcennější území na základě síťového mapování cévnatých rostlin a vybraných zoologických taxonů. Výsledkem projektu bude i databáze nálezů s grafickými výstupy, mapa kvality vodotečí a vědecké publikace. Zpráva popisuje práce vykonané v roce 2003: Charakteristika CHKO a BR Bílé Karpaty, síťové mapování cévnatých rostlin, ornitologický průzkum, ichtyologický a hydrobiologický průzkum, lepidopterologický průzkum, carabidologický průzkum

Wagner et al. 2016. R scripts and data

Data and R scripts analyze how species shifts in soil pH niche parameter (optimum, width) are linked to regional changes in mean precipitation, substrate availability and species traits indicative of competitive ability.<br><br>Requirement: R (https://www.r-project.org/) and R packages (see scripts for further specifications)<br><br>Data structure is explained in the R scripts.<br

Plot data from the paper "A modern analogue of the Pleistocene steppe-tundra ecosystem in southern Siberia" (Chytry et al.)

Primary data from 182 plots of 10 m x 10 m sampled in 12 habitat types of the steppe-tundra landscape in the SE Russian Altai Mountains in summers of 2005, 2006 and 2011. The dataset contains species composition of vascular plants, bryophytes, lichens and snails, and environmental data from the same plots including measurements of primary aboveground productivity, nutrient contents in the aboveground biomass and soil chemistry.<div><br></div><div>Sampling methods are described in the paper Chytrý et al.: A modern analogue of the Pleistocene steppe-tundra ecosystem in southern Siberia.</div><div><br></div><div>The dataset is provided in two files, one in the XLSX format for Excel 2013, another in tab-delimited table in the TXT format.</div><div><br></div><div>Plant species data were originally recorded with covers on the nine-degree Braun-Blanquet scale, which has been transformed to percentages as follows: 1, 2, 3, 4, 8, 18, 38, 63, 88. Other values can occur in case when original records of the same species in different layers were merged for the analyses. Snail data indicate species presence (1) or absence (0). NA means absence of measurement in the plot.</div><div><br></div><div><br></div

Benchmarking plant diversity of Palaearctic grasslands and other open habitats

Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m(2) and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file "GrassPlot Diversity Benchmarks" and the web tool "GrassPlot Diversity Explorer" are now available online () and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology

Benchmarking plant diversity of Palaearctic grasslands and other open habitats

Aims Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location Palaearctic biogeographic realm. Methods We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology

Benchmarking plant diversity of Palaearctic grasslands and other open habitats

Abstract Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m² and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology