Relationship between site-specific nitrogen concentrations in mosses and measured wet bulk atmospheric nitrogen deposition across Europe

To assess the relationship between nitrogen concentrations in mosses and wet bulk nitrogen deposition or concentrations in precipitation, moss tissue and deposition were sampled within a distance of 1 km of each other in seven European countries. Relationships for various forms of nitrogen appeared to be asymptotic, with data for different countries being positioned at different locations along the asymptotic relationship and saturation occurring at a wet bulk nitrogen deposition of ca. 20 kg N ha−1 yr−1. The asymptotic behaviour was more pronounced for ammonium-N than nitrate-N, with high ammonium deposition at German sites being most influential in providing evidence of the asymptotic behaviour. Within countries, relationships were only significant for Finland and Switzerland and were more or less linear. The results confirm previous relationships described for modelled total deposition. Nitrogen concentration in mosses can be applied to identify areas at risk of high nitrogen deposition at European scale

Spatially valid data of atmospheric deposition of heavy metals and nitrogen derived by moss surveys for pollution risk assessments of ecosystems

For analysing element input into ecosystems and associated risks due to atmospheric deposition, element concentrations in moss provide complementary and time-integrated data at high spatial resolution every 5 years since 1990. The paper reviews (1) minimum sample sizes needed for reliable, statistical estimation of mean values at four different spatial scales (European and national level as well as landscape-specific level covering Europe and single countries); (2) trends of heavy metal (HM) and nitrogen (N) concentrations in moss in Europe (1990–2010); (3) correlations between concentrations of HM in moss and soil specimens collected across Norway (1990–2010); and (4) canopy drip-induced site-specific variation of N concentration in moss sampled in seven European countries (1990–2013). While the minimum sample sizes on the European and national level were achieved without exception, for some ecological land classes and elements, the coverage with sampling sites should be improved. The decline in emission and subsequent atmospheric deposition of HM across Europe has resulted in decreasing HM concentrations in moss between 1990 and 2010. In contrast, hardly any changes were observed for N in moss between 2005, when N was included into the survey for the first time, and 2010. In Norway, both, the moss and the soil survey data sets, were correlated, indicating a decrease of HM concentrations in moss and soil. At the site level, the average N deposition inside of forests was almost three times higher than the average N deposition outside of forests

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

Background: This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey. Results: Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of < 40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (= above-average) or low (= below-average) correlation coefficients. Conclusions: LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites

Modelling and mapping heavy metal and nitrogen concentrations in moss in 2010 throughout Europe by applying Random Forests models

Objective: This study explores the statistical relations between the concentration of nine heavy metals(HM) (arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb),vanadium (V), zinc (Zn)), and nitrogen (N) in moss and potential explanatory variables (predictors)which were then used for mapping spatial patterns across Europe. Based on moss specimens collected in 2010 throughout Europe, the statistical relation between a set of potential predictors (such as the atmospheric deposition calculated by use of two chemical transport models (CTM), distance from emission sources, density of different land uses, population density, elevation, precipitation, clay content of soils) and concentrations of HMs and nitrogen (N) in moss (response variables) were evaluated by the use of Random Forests (RF) and Classification and Regression Trees (CART). Four spatial scales were regarded: Europe as a whole, ecological land classes covering Europe, single countries participating in the European Moss Survey (EMS), and moss species at sampling sites. Spatial patterns were estimated by applying a series of RF models on data on potential predictors covering Europe. Statistical values and resulting maps were used to investigate to what extent the models are specific for countries, units of the Ecological Land Classification of Europe (ELCE), and moss species. Results: Land use, atmospheric deposition and distance to technical emission sources mainly influence the element concentration in moss. The explanatory power of calculated RF models varies according to elements measured in moss specimens, country, ecological land class, and moss species. Measured and predicted medians of element concentrations agree fairly well while minima and maxima show considerable differences. The European maps derived from the RF models provide smoothed surfaces of element concentrations (As, Cd, Cr, Cu, N, Ni, Pb, Hg, V, Zn), each explained by a multivariate RF model and verified by CART, and thereby more information than the dot maps depicting the spatial patterns of measured values. Conclusions: RF is an eligible method identifying and ranking boundary conditions of element concentrations in moss and related mapping including the influence of the environmental factors

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

BackgroundThis paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.ResultsCorrelations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75-100km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=above-average) or low (=below-average) correlation coefficients.ConclusionsLDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites

The Bryophyte Flora of Vienna

The bryophyte flora of Vienna is documented only in parts. Old finds often appeared in publications about Lower Austria; only one study addressed the bryophytes of the inner city. Here, we present a bryophyte flora of Vienna, including historical reports and the results of recent investigations. From 1998 to 2023, we recorded 329 bryophyte taxa in Viennese urban territory. Fifty-six of these were liverworts, and 273 were mosses. Sixty-seven taxa are new for Vienna. Forty-nine taxa, given in historical studies, could no longer be found. If we also count these, 378 taxa occurred in Vienna to date. Of the current occurring bryophytes, 67 species have an endangerment classification. Rich in bryophytes were the dry grasslands of the Lobau, the oxbow lakes of the Lobau and the Prater, and large parts of the Wienerwald. But flat roofs and inner-city areas also showed more than 100 species. Compared to other European cities, Vienna is decidedly species-rich and highly responsible for some species in Austria. Reasons for this are the extensive green spaces and the pronounced climatic gradient from the sub-oceanic west to the sub-continental east of Vienna. Awareness raising for bryophytes we recommend in addition to the existing biotope protection

The Fate of Bryophyte Sporophytes—Phenology and Vectors of Buxbaumia viridis in the Kalkalpen National Park, Austria

Knowledge about the epixylic moss Buxbaumia viridis has increased significantly due to the monitoring obligation under the Habitats Directive. However, there are still open questions about its dispersal, as the wind plays a limited role in forest ecosystems, and vectors have been suspected but not yet studied systematically for this species. Here, we present data on potential vectors of Buxbaumia viridis collected for the first time with the help of cameras, completed by monitoring the fate of sporophytes during their life cycle in the Limestone Alps National Park in Austria over a period of two years. Young, green sporophytes appeared mainly in autumn, with the highest number in October. Most of them survived winter and spring but did not exceed the age of 14 months. The sharpest decline in capsules occurred in summer when mature, and the lowest number of sporophytes appeared at the end of August. Most likely, mice seem to be responsible for this loss, as the photos from the wildlife cameras suggest, and should be considered both as predators and vectors. Birds should be considered as vectors, too. In summary, most of the reproductive biomass is sacrificed in favor of more effective dispersal, including over longer distances

Climate Variables Outstrip Deadwood Amount: Desiccation as the Main Trigger for Buxbaumia viridis Occurrence

Deadwood is a biodiversity hotspot and habitat for numerous highly endangered species. Buxbaumia viridis has been assessed as a flagship species for deadwood-rich forests and is subject to monitoring under the Habitats Directive, yet we lack a solid understanding of the factors controlling its distribution. The study aimed to specify the climate and habitat preferences of Buxbaumia viridis and identify the best predictor variables. We collected presence-absence data of the species at 201 sites between 2016 and 2020. Study sites cover three biogeographic regions (Pannonian, Continental, and Alpine). They also represent a deadwood gradient ranging from managed forests to natural forest reserves and virgin forests. Our results suggest that desiccation and deadwood amount are the best predictor variables. The amount of deadwood at the colonized sites ranged from 1 m3/ha to 288 m3/ha, with a median of 70 m3/ha. The maximum desiccation, i.e., consecutive days without rain and at least 20 &deg;C was 9.6 days at colonized sites. The results of logistic regression models suggest that desiccation limits Buxbaumia viridis occurrence on deadwood in the drier continental parts of eastern Austria. Derived details on climate and habitat requirements of Buxbaumia viridis can specify management and conservation. They clearly show how strongly the species is dependent on climate, which can counteract deadwood measures

Metal accumulation in mosses across national boundaries: uncovering and ranking causes of spatial variation.

This study aimed at cross-border mapping metal loads in mosses in eight European countries in 1990, 1995, and 2000 and at investigating confounding factors. Geostatistics was used for mapping, indicating high local variances but clear spatial autocorrelations. Inference statistics identified differences of metal concentrations in mosses on both sides of the national borders. However, geostatistical analyses did not ascertain discontinuities of metal concentrations in mosses at national borders due to sample analysis in different laboratories applying a range of analytical techniques. Applying Classification and Regression Trees (CART) to the German moss data as an example, the local variation in metal concentrations in mosses were proved to depend mostly on different moss species, potential local emission sources, canopy drip and precipitation