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

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