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 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

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

First Europe-wide correlation analysis identifying factors best explaining the total nitrogen concentration in mosses

In this study, the indicative value of mosses as biomonitors of atmospheric nitrogen (N) depositions and air concentrations on the one hand and site-specific and regional factors which explain best the total N concentration in mosses on the other hand were investigated for the first time at a European scale using correlation analyses. The analyses included data from mosses collected from 2781 sites across Europe within the framework of the European moss survey 2005/6, which was coordinated by the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation). Modelled atmospheric N deposition and air concentration data were calculated using the Unified EMEP Model of the European Monitoring and Evaluation Programme (EMEP) of the Convention on Long-range Transboundary Air Pollution (CLRTAP). The modelled deposition and concentration data encompass various N compounds. In order to assess the correlations between moss tissue total N concentrations and the chosen predictors, Spearman rank correlation analysis and Classification and Regression Trees (CART) were applied. The Spearman rank correlation analysis showed that the total N concentration in mosses and modelled N depositions and air concentrations are significantly correlated (0.53 ≤ rs ≤ 0.68, p < 0.001). Correlations with other predictors were lower than 0.55. The CART analysis indicated that the variation in the total N concentration in mosses was best explained by the variation in NH4+ concentrations in air, followed by NO2 concentrations in air, sampled moss species and total dry N deposition. The total N concentrations in mosses mirror land use-related atmospheric concentrations and depositions of N across Europe. In addition to already proven associations to measured N deposition on a local scale the study at hand gives a scientific prove on the association of N concentration in mosses and modelled deposition at the European scale

Relevance of canopy drip for the accumulation of nitrogen in moss used as biomonitors for atmospheric nitrogen deposition in Europe

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First thorough identification of factors associated with Cd, Hg and Pb concentrations in mosses sampled in the European Surveys 1990, 1995, 2000 and 2005

The aim of this study was, for the first time ever, to thoroughly identify the factors influencing Cd, Hg and Pb concentrations in mosses sampled within the framework of the European Heavy Metals in Mosses Surveys 1990–2005. These investigations can be seen as a follow up of a previous study where only the moss data recorded in the survey 2005 was included in the analysis (Schröder et al. 2010). The analyses of this investigation give a complete overview on the statistical association of Cd, Hg and Pb concentrations in mosses and sampling site-specific and regional characteristics, encompassing data from 4661 (1990), 7301 (1995), 6764 (2000) and 5600 (2005) sampling sites across Europe. From the many metals monitored in the European moss surveys, Cd, Hg and Pb were used as examples, since only for these three metals deposition measurements are being recorded in the framework of the European Monitoring and Evaluation Programme (EMEP). As exemplary case studies revealed that other factors besides atmospheric deposition of metals influence the element concentrations in mosses, the moss datasets of the above mentioned surveys were analysed by means of bivariate statistics and decision tree analysis in order to identify factors influencing metal bioaccumulation. In the analyses we used the metadata recorded during the sampling as well as additional geodata on, e.g., depositions, emissions and land use. Bivariate Spearman correlation analyses showed the highest correlations between Cd and Pb concentrations in mosses and EMEP modelled total deposition data (0.62 ≤ rs ≤ 0.73). For Hg the correlations with all the tested factors were considerably lower (e.g. total deposition r s  ≤ 0.24). Decision tree analyses by means of Classification and Regression Trees (CART) identified the total deposition as the statistically most significant factor for the Cd and Pb concentrations in the mosses in all four monitoring campaigns. For Hg, the most significant factor in 1990 as identified by CART was the distance to the nearest Hg source recorded in the European Pollutant Emission Register, in 1995 and 2000 it was the analytical method, and in 2005 it was the sampled moss species. The strong correlations between the Cd and Pb concentrations in the mosses and the total deposition can be used to calculate deposition maps with a regression kriging approach on the basis of surface maps on the element concentrations in the mosse