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

<scp>ReSurveyEurope</scp>: A database of resurveyed vegetation plots in Europe

AbstractAimsWe 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.ResultsReSurveyEurope 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.ConclusionsReSurveyEurope 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.</jats:sec

Nitrogen retention and loss from ecosystems of the Bornh&ouml;ved Lake district.

The challenges in ecosystem science encompass a broadening and strengthening of interdisciplinary ties, the transfer of knowledge of the ecosystem across scales, and the inclusion of anthropogenic impacts and human behavior into ecosystem, landscape, and regional models. The volume addresses these points within the context of studies in major ecosystem types viewed as the building blocks of central European landscapes. The research is evaluated to increase the understanding of the processes in order to unite ecosystem science with resource management. The comparison embraces coastal lowland forests, associated wetlands and lakes, agricultural land use, and montane and alpine forests. Techniques for upscaling focus on process modelling at stand and landscape scales and the use of remote sensing for landscape-level model parameterization and testing. The case studies demonstrate ways for ecosystem scientists, managers, and social scientists to cooperate

A comparative review of soil charcoal data: Spatiotemporal patterns of origin and long-term dynamics of Western European nutrient-poor grasslands

International audienceThe nutrient-poor grasslands of Western Europe are of major conservation concern because land use changes threaten their high biodiversity. Studies assessing their characteristics show that their past and ongoing dynamics are strongly related to human activities. Yet, the initial development patterns of this specific ecosystem remain unclear. Here, we examine findings from previous paleoecological investigations performed at local level on European grassland areas ranging from several hundred square meters to several square kilometers. Comparing data from these locally relevant studies at a regional scale, we investigate these grasslands' spatiotemporal patterns of origin and long-term dynamics. The study is based on taxonomic identification and radiocarbon AMS dating of charcoal pieces from soil/soil sediment archives of nutrient-poor grasslands in Mediterranean and temperate Western Europe (La Crau plain, Mont Lozère, Grands Causses, Vosges Mountains, Franconian Alb, and Upper-Normandy region). We address the following questions: (1) What are the key determinants of the establishment of these nutrient-poor grasslands? (2) What temporal synchronicities might there be? and (3) What is the spatial scale of these grasslands' past dynamics? The nutrient-poor grasslands in temperate Western Europe are found to result from the first anthropogenic woodland clearings during the late Neolithic, revealed by fire events in mesophilious mature forests. In contrast, the sites with Mediterranean affinities appear to have developed at earlier plant successional stages (pine forest, matorral), established before the first human impacts in the same period. However, no general pattern of establishment and dynamics of the nutrient-poor grasslands could be identified. Local mechanisms appear to be the key determinants of the dynamics of these ecosystems. Nevertheless, this paleoecological synthesis provides insights into past climate or human impacts on present-day vegetation

Rewetting does not return drained fen peatlands to their old selves

Peatlands, in particular groundwater-fed fens of the temperate zone, have been drained for agriculture, forestry and peat extraction for a long time and on a large scale. Drainage turns peatlands from a carbon and nutrient sink into a respective source, diminishes water regulation capacity at the landscape scale, causes continuous surface height loss and destroys their typical biodiversity. Over the last decades, drained peatlands have been rewetted for biodiversity restoration and, as it strongly decreases greenhouse gas emissions, also for climate protection. With the dataset published here, we quantified restoration success by comparing 320 rewetted fen peatland sites to 243 near-natural peatland sites of similar origin across temperate Europe with regards to biodiversity (vegetation), ecosystem functioning (hydrology, geochemistry) and land cover characteristics based on remote sensing. Vegetation data comes as species-specific cover values. Hydrology data covers on average 2.3 years and minimally one full year and comes as median, minimum, and maximum water table depth. Geochemistry consists of pH and electrical conductivity of the pore water (0-60 cm), bulk density and organic matter content of the top soil layer (0-30 cm), all sampled in summer for all sites included here alongside the vegetation data sampling. Land cover characteristics contain 208 spectral-temporal metrics for a full annual time series of Copernicus Sentinel-2 A/B data for 2018.Several taxa included in this dataset are at risk from a harmful human activity, in accordance to Chapman 2008 (https://docs.gbif.org/sensitive-species-best-practices/master/en/) we therefore report the georeferences denatured to 0.1 degrees (~10 km). Data may be supplied at finer scales on request under the conditions of a written data agreement. Missing values are coded as NA, zeros are true and measured values. Funding provided by: European Social FundCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100004895Award Number: ESF/14-BM-A55-0027/16 to ESF/14-BM-A55-0035/16Funding provided by: BiodivERsA*Crossref Funder Registry ID: Award Number: DFG JO 332/15-1Funding provided by: BiodivERsA*Crossref Funder Registry ID: Award Number: BELSPO BR/175/A1Funding provided by: BiodivERsA*Crossref Funder Registry ID: Award Number: NCN 2016/22/Z/NZ8/00001Funding provided by: Ministerium für Bildung, Wissenschaft und Kultur Mecklenburg-VorpommernCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100014848Award Number: ESF/14-BM-A55-0027/16 to ESF/14-BM-A55-0035/16Funding provided by: BiodivERsACrossref Funder Registry ID: Award Number: DFG JO 332/15-1See methods section of the accompanying paper for details about data collection and processing; see ReadMe-file for parameter explanation. Potential sites were found through literature search and contacting the respective authors. All such authors providing data were included as co-authors and we included all data from fen ecosystems of temperate Europe which were drained and had a dateable rewetting action and all sites without direct drainage history as confirmed by local experts and remote sensing. We included all sites that provided data for at least two of the following four response clusters in order to obtain comparable datasets for these clusters: (1) vegetation, (2) hydrology, (3) geochemistry, (4) land cover characteristics. We included all available datasets fitting to the definitions laid out above. Sampling for vegetation and geochemistry occurred in summer for all sites. Vegetation sampling consisted of complete lists of vascular plants and bryophytes (539 species in total) based on 16 m² (median, ranging between 12 and 25 m²) with estimates of individual plant species cover. All vegetation data collections included in this study aimed at full species lists and used comparable methodologies, i.e. estimating species-specific cover values. Studies focusing on specific taxa or just reporting the dominant species were excluded from the analyses. Geochemical sampling quantified pH and electrical conductivity of the pore water (0-60 cm) and bulk density and organic matter content of the top soil layer (0-30 cm). Hydrological data relied on on continuous are at least monthly manual sampling for on average, 2.3 years, and a minimum of at least one full year. Land cover characteristics were sampled after the fact for all sites for which the required remote sensing prodcuts were available in the year 2018. Data was collected for different purposes over different years. The data owners are included as co-authors. Vegetation data is the estimated aboveground cover of all vascular plants and bryophytes (539 species in total) within a 16 m² (median, ranging between 12 and 25 m²) plot noted down by experts with pen on paper. Hydrological data is based on 269 piezometers with dataloggers, 91 piezometers related to a datalogger in a transect, 216 piezometers with manual measurements of at least one year and biweekly or monthly readings of the water table depth relative to the peat surface. Geochemical data consisted of pH and electric conductivity of the pore water extracted in the field and measured directly with portable pH-sensors and conductivity sensors. Bulk density was quantfied based on volumetric field samples (0-30cm depth) in relation to their dry weight after drying to constant weight in a drying cabinet. Organic matter was quantified as the loss on ignition of these dry samples. Land cover characteristics: spectral-temporal metrics for a full annual time series of Copernicus Sentinel-2 A/B data for 2018. The Sentinel-2 A/B constellation provides optical imagery of the Earth's surface between ~0.49 - ~2.2 µm in ten spectral bands and at 10 – 20 m ground sampling distance at a theoretical acquisition frequency of 2.5 – 5 days. We here acquired all available Sentinel-2 A/B imagery for 2018 with cloud cover <70% from the ESA API Hub. We used all valid observations to derive spectral-temporal metrics from the time series. Spectral temporal metrics are statistical measures (e.g. average, minimum, maximum, quartiles, …) per spectral band or index (e.g. MNDWI = (green - short wave infrared)/(green + short wave infrared)) using all available cloud- and shadow-free observations over time. The median count of clear-sky-observations per pixel across the sites is 45, while 90% of all sites featured 27 clear-sky observations or more. Both data processing to Analysis Ready Data as well as calculating spectral-temporal metrics was performed through the Framework for Operational Radiometric Correction for Environmental monitoring. Our analysis included data averaged over 3x3 pixels around the center plot location of the site. Different spatial aggregations (e.g. single pixels, 5x5 pixels around the center plot) led to highly similar results, implying that the intra-site variability was robust around locations of the vegetation survey. The inclusion of an annual series of Sentinel-1 synthetic aperture radar data (temporal metrics for VV and VH polarization, IW swath at 10 m resolution) for the same year did not affect the results. Spatial scale: temperate fen ecosystems of Europe. Timing: Data was collected between 1994 and 2019 with sampling for vegetation and geochemistry occurring once per site with known year and time since rewetting for the rewetted sites but different years between sites. Hydrology was monitored for >1 year at each site (see above for details and rationale), again with known time periods per site and different timing for different sites. Land cover characteristics were sampled for all sites for the year 2018 as decribed above

No effect of antihypertensive drugs on severity of anaphylaxis and side-effects during venom immunotherapy

Congress of the European-Academy-of-Allergy-and-Clinical-Immunology (EAACI) -- JUN 01-05, 2019 -- Lisbon, PORTUGALWOS: 000480254002001European Acad Allergy & Clin Immuno