Roland Pesch

Mosses as biomonitors of atmospheric heavy metal deposition: Spatial patterns and temporal trends in Europe

In recent decades, mosses have been used successfully as biomonitors of atmospheric deposition of heavy metals. Since 1990, the European moss survey has been repeated at five-yearly intervals. Although spatial patterns were metal-specific, in 2005 the lowest concentrations of metals in mosses were generally found in Scandinavia, the Baltic States and northern parts of the UK; the highest concentrations were generally found in Belgium and south-eastern Europe. The recent decline in emission and subsequent deposition of heavy metals across Europe has resulted in a decrease in the heavy metal concentration in mosses for the majority of metals. Since 1990, the concentration in mosses has declined the most for arsenic, cadmium, iron, lead and vanadium (52-72%), followed by copper, nickel and zinc (20-30%), with no significant reduction being observed for mercury (12% since 1995) and chromium (2%). However, temporal trends were country-specific with sometimes increases being found.

Nitrogen concentrations in mosses indicate the spatial distribution of atmospheric nitrogen deposition in Europe

In 2005/6, nearly 3000 moss samples from (semi-)natural location across 16 European countries were collected for nitrogen analysis. The lowest total nitrogen concentrations in mosses (<0.8%) were observed in northern Finland and northern UK. The highest concentrations (≥ 1.6%) were found in parts of Belgium, France, Germany, Slovakia, Slovenia and Bulgaria. The asymptotic relationship between the nitrogen concentrations in mosses and EMEP modelled nitrogen deposition (averaged per 50 km × 50 km grid) across Europe showed less scatter when there were at least five moss sampling sites per grid. Factors potentially contributing to the scatter are discussed. In Switzerland, a strong (r(2) = 0.91) linear relationship was found between the total nitrogen concentration in mosses and measured site-specific bulk nitrogen deposition rates. The total nitrogen concentrations in mosses complement deposition measurements, helping to identify areas in Europe at risk from high nitrogen deposition at a high spatial resolution.

Country-specific correlations across Europe between modelled atmospheric cadmium and lead deposition and concentrations in mosses

Previous analyses at the European scale have shown that cadmium and lead concentrations in mosses are primarily determined by the total deposition of these metals. Further analyses in the current study show that Spearman rank correlations between the concentration in mosses and the deposition modelled by the European Monitoring and Evaluation Programme (EMEP) are country and metal-specific. Significant positive correlations were found for about two thirds or more of the participating countries in 1990, 1995, 2000 and 2005 (except for Cd in 1990). Correlations were often not significant and sometimes negative in countries where mosses were only sampled in a relatively small number of EMEP grids. Correlations frequently improved when only data for EMEP grids with at least three moss sampling sites per grid were included. It was concluded that spatial patterns and temporal trends agree reasonably well between lead and cadmium concentrations in mosses and modelled atmospheric deposition.

Integrative exposure assessment through classification and regression trees on bioaccumulation of metals, related sampling site characteristics and ecoregions

Abstract The UNECE Heavy Metals in Mosses Surveys measure and spatially predict environmental concentration (PEC) of metals in mosses for ecotoxicological risk assessments. Up to now, no statistical sound investigation was dedicated to those boundary conditions which, aside from the atmospheric depositions of metals from the atmosphere down to the land surface, might influence the bioaccumulation of metals. Thus, the article focuses on the integrative analysis of the data on the bioaccumulation of metals in Germany 1990, 1995 and 2000 on the one hand and of data on conceivable boundary conditions on the other hand. To this end Classification and Regression Trees (CART) were used because CART is a very powerful statistical technique that enables to uncover structures in large data sets containing categorical and continuous data without any transformation of scale dignity. Within the framework of the Metals in Mosses Surveys, moss samples were taken at 592 sites in 1990, at 1026 sites in 1995 and at 1028 sites in 2000 in Germany. At each of them mosses were sampled and the concentrations of up to 40 metals were measured. The sampling, the ecological characteristics of the sampling sites, and the chemical analysis were documented in a metadata base. An ecoregionalisation of Germany was calculated with data on natural vegetation, altitude, soil texture and climate by means of CART. The ecoregions were mapped by GIS and intersected with multi-metal bioaccumulation indices calculated from the monitoring data 1990, 1995 and 2000. These indices were calculated by percentile statistics and the concentrations of As, Cd, Cr, Cu, Fe, Hg, Ni, Pb, V and Zn were integrated. To reach an integrative exposure assessment, for each survey a CART-model was computed encompassing the multi-metal bioaccumulation indices, the metadata and the ecoregionalization. The models describe the multivariate correlations of metal bioaccumulation with site-specific and ecoregional characteristics in a comprehensive and holistic manner over time, space and metal species. This is of crucial importance for the next step in ecological risk assessment, i.e. the interpretation of the exposure data with regard to predicted no effect concentrations (PNEC) and the sensitivity of ecosystems.

Soil monitoring in Germany

Background Aim and ScopeSoil monitoring in Germany should register the current soil condition, monitor its changes and provide a forecast for future development. In order to achieve these goals, the long-term soil monitoring sites in Germany (BDF -Bodendauerbeobachtungsflächen) have been established by the federal states. This has been done according to criteria worked out by soil monitoring experts. In this article a method for the examination of the suitability of Germany’s soil monitoring sites for soil conservation and protection purposes, as well as for environmental monitoring and reporting, is introduced. This method includes the landscape representativity of soil monitoring sites as well as the comparability and spatial validity of collected data.MethodsBDF-criteria are operationalized in a three-step procedure: At first, a metadatabase is established containing information that allows the comparison of monitoring sites by means of measuring parameters, methods and quality assurance as well as quality control of measurements. Secondly, the representativity of the BDF-sites for soil types, land use, vegetation, and climate (air temperature, duration of sunlight, precipitation) by means of frequency statistics and neighborhood analysis is quantified. At last, the spatial validity of soil monitoring data is examined through the application of geostatistical methods. Both data and statistical methods are integrated in a Geoinformationsystem (GIS).ResultsThe analysis of metadata reveals that the soil monitoring is of great importance for environmental analysis because of its ecosystematic concept and its considerable degree of methodical harmonization. Assuming that the number of BDF should be directly proportional to the areal portion of an ecoregion in the entire area of Germany, it can be shown that the geographical distribution of BDF-sites fit quite well according to the areal portions of the ecoregions. The maximum deviation is about ñ 6%. If the number of BDF is not proportional to the area covered by a certain combination of site characteristics, these areas can either be complemented or thinned through MNR-indices derived by neighborhood analysis. Soil monitoring sites can be added where the MNR are highest and removed where MNR are lowest. Throughout the neighborhood analysis, three GISmaps were processed: ecoregionaiization, soil types and land use. Decisions to reduce the spatial density of monitoring sites should not only be based on the landscape representativness of monitoring networks, but on the support of geostatistical analysis of measured data as well. For example, the results of the geostatistical analysis of Pb-concentrations in top soils are compared for a complete and a reduced BDF monitoring network.ConclusionThe investigations show that not only the proportional distribution of monitoring sites in landscape units (landscape representativity) is important for the assessment of environmental monitoring networks; The number of monitoring sites, rather, should be sufficient to guarantee a spatial representation of the respective measurement variable. Their geographical distribution should be based on the spatial model of landscape units. Additionally, particular criteria that are important for the object of investigation, for example the distance to emitters, should also be considered.PerspectiveIt is strongly recommended that activities for the integration of ecological data collected in diverse monitoring networks be intensified. A central German environmental information system should be established in order to realize integrated analysis of environmental data by aspects of harmonization and representativity. Furthermore, Internet and GIS technologies should be used to assist the environmental data acquisition in Germany. A prototype of such an instrument, the socalled Internet and GIS-based Environmental Monitoring System (IGUS) was already established and tested in the moss monitoring program 2000.

Spatial analysis of marine categorical information using indicator kriging applied to georeferenced video mosaics of the deep-sea Håkon Mosby Mud Volcano

The exact area calculation of irregularly distributed data is in the focus of all territorial geochemical balancing methods or definition of protection zones. Especially in the deep sea environment the interpolation of measurements into surfaces represents an important gain of information, because of cost- and time-intensive data acquisition.The geostatistical interpolation method indicator kriging therefore is applied for an accurate mapping of the spatial distribution of benthic communities following a categorical classification scheme at the deep-sea submarine Hakon Mosby Mud Volcano. Georeferenced video mosaics were obtained during several dives by the Remotely Operated Vehicle Victor6000 in a water depth of 1260 m. Mud volcanoes are considered as significant source locations for methane indicated by unique chemoautotrophic communities as Beggiatoa mats and pogonophoran tube worms. For the detection and quantification of their spatial distribution 2840 georeferencedvideo mosaics were analysed by visual inspection. Polygons, digitised on the georeferenced images within a GIS, build the data basis for geostatistically interpolated mono-parametric surface maps. Indicator kriging is applied to the centroids of the polygons calculating surfacemaps.The quality assessment of the surface maps is conducted by leave-one-out cross-validation evaluating the fit of the indicator kriging variograms by using statistical mean values. Furthermore, the estimate was evaluated by a validation dataset of the visual inspection of 530 video mosaics not included within the interpolation, thus, proving the interpolated surfaces independently. With regard to both validating mechanisms, we attained satisfying results and we provided each category applied for the identification of biogeochemical habitats with apercentage probability value of occurrence.

Comparative use of lichens, mosses and tree bark to evaluate nitrogen deposition in Germany

To compare three biomonitoring techniques for assessing nitrogen (N) pollution in Germany, 326 lichen, 153 moss and 187 bark samples were collected from 16 sites of the national N deposition monitoring network. The analysed ranges of N content of all investigated biomonitors (0.32%-4.69%) and the detected δ(15)N values (-15.2‰-1.5‰), made it possible to reveal species specific spatial patterns of N concentrations in biota to indicate atmospheric N deposition in Germany. The comparison with measured and modelled N deposition data shows that particularly lichens are able to reflect the local N deposition originating from agriculture.

Monitoring nitrogen accumulation in mosses in central European forests

In order to assess whether nitrogen (N) loads in mosses reflect different land uses, 143 sites in North Rhine-Westphalia, the Weser-Ems Region and the Euro Region Nissa were sampled between 2000 and 2005. The data were analysed statistically with available surface information on land use and forest conditions. N bioaccumulation in mosses in the Weser-Ems Region with high densities of agricultural land use and livestock exceeded the concentrations in the more industrialised Euro Region Nissa. In all three study areas agricultural and livestock spatial densities were found to be positively correlated with N bioaccumulation in mosses. In North Rhine-Westphalia, the N concentrations in mosses was also moderately correlated with N concentrations in leaves and needles of forest trees. The moss method proved useful to assess the spatial patterns of N bioaccumulation due to land use.

Accounting for canopy drip effects of spatiotemporal trends of the concentrations of N in mosses, atmospheric N depositions and critical load exceedances: a case study from North-Western Germany

BackgroundAtmospheric nitrogen (N) deposition into terrestrial ecosystems is frequently considered as a threat to phyto-diversity. In previous investigations, the atmospheric N inputs enriched in mosses were recorded in 2004 as part of a regional investigation at 54 locations in north-west Germany and in 2005 at 726 locations across the whole country. This article deals with a study conducted in 2012 comparing N concentrations in mosses sampled within 30 forest stands and in 26 adjacent open fields in north-west Germany. The N concentration in mosses were determined and, by the use of a regression model, converted to N atmospheric deposition values. These deposition estimations enabled to calculate N critical load exceedances.ResultsCompared to the average N concentration in mosses sampled in open fields 2012 (7.4 kg/ha*a), the average N concentrations in mosses within adjacent forests were almost four times higher (26.6 kg/ha*a), and the maximum within the stands accounted for approximately 56 kg/ha*a. Compared to 2005, there was a slight decline of the average N deposition by 2.4 kg/ha*a in open fields. However, the average N concentrations in mosses within forests stands in 2012 remained nearly the same since 2004 (29 kg/ha*a). The atmospheric N deposition as estimated from the N concentration in mosses ranged between the minimum and maximum N critical load at 71% of the 56 sites investigated. At 14% of the sites, the N deposition was close to the maximum N critical load value which was exceeded in 11%.ConclusionsThe study at hand revealed statistically significant differences between N concentrations measured in mosses sampled within forests and in open fields. The presented findings should be accounted for both modelling and mapping atmospheric N deposition into terrestrial ecosystems on the one hand and related estimations of N critical load exceedances on the other hand.

Mapping background values of atmospheric nitrogen total depositions in Germany based on EMEP deposition modelling and the European Moss Survey 2005

BackgroundIn order to map exceedances of critical atmospheric deposition loads for nitrogen (N) surface data on the atmospheric deposition of N compounds to terrestrial ecosystems are needed. Across Europe such information is provided by the international European Monitoring and Evaluation Programme (EMEP) in a resolution of 50 km by 50 km, relying on both emission data and measurement data on atmospheric depositions. The objective of the article at hand is on the improvement of the spatial resolution of the EMEP maps by combining them with data on the N concentration in mosses provided by the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation) of the United Nations Economic Commission for Europe (UNECE) Long-range Transboundary Air Pollution (LTRAP) Convention.MethodsThe map on atmospheric depositions of total N as modelled by EMEP was intersected with geostatistical surface estimations on the N concentration in mosses at a resolution of 5 km by 5 km. The medians of the N estimations in mosses were then calculated for each 50 km by 50 km grid cell. Both medians of moss estimations and corresponding modelled deposition values were ln-transformed and their relationship investigated and modelled by linear regression analysis. The regression equations were applied on the moss kriging estimates of the N concentration in mosses. The respective residuals were projected onto the centres of the EMEP grid cells and were mapped using variogram analysis and kriging procedures. Finally, the residual and the regression map were summed up to the map of total N deposition in terrestrial ecosystems throughout Europe.Results and discussionThe regression analysis of the estimated N concentrations in mosses and the modelled EMEP depositions resulted in clear linear regression patterns with coefficients of determination of r2 = 0.62 and Pearson correlations of rp = 0.79 and Spearman correlations of rs = 0.70, respectively. Regarding the German territory a nationwide mean of 18.1 kg/ha/a (standard deviation: 3.49 kg/ha/a) could be derived from the resulting map on total N deposition in a resolution of 5 km by 5 km. Recent updates of the modelled atmospheric deposition of N provided a similar estimate for Germany.ConclusionsThe linking of modelled EMEP data on the atmospheric depositions of total N and the accumulation of N in mosses allows to map the deposition of total N in a high resolution of 5 km by 5 km using empirical moss data. The mapping relies on the strong statistical relationship between both processes that are physically and chemically related to each other. The mapping approach thereby relies on available data that are both based on European wide harmonized methodologies. From an ecotoxicological point of view the linking of data on N depositions and those on N bioaccumulation can be considered a substantial progress.ZusammenfassungHintergrundFür die Kartierung kritischer Eintragsraten (Critical Loads, CL) für Stickstoff (N) werden flächendeckende Depositionsdaten benötigt. Diese werden europaweit im EMEP-Programm und auf nationalstaatlicher Ebene in Forschungsprojekten zur Verfügung gestellt. Es handelt sich um Ergebnisse aus Modellierungen, die u.a. auf Messwerten der N-Emissionen und der atmosphärischen N-Deposition beruhen. Dieser Artikel stellt am Beispiel der Daten zur N-Deposition aus dem European Monitoring and Evaluation Programme (EMEP) dar, wie deren räumliche Auflösung durch Kombination mit Daten der N-Anreicherung in Moosen aus dem International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation) der United Nations Economic Commission for Europe (UNECE) Long-range Transboundary Air Pollution (LTRAP) Convention.erhöht werden kann.MethodenDie in einer Auflösung von 50 km mal 50 km vorliegende EMEP N-Depositionskarte wurde mit geostatistich validen Kriging-Karten über die Anreicherung von N in Moosen in einem Geografischen Informationssystem (GIS) verknüpft. Anschließend wurden die Mediane aller 5 km mal 5 km großen Rasterzellen der N-Anreicherungskarte innerhalb der jeweiligen 50 km mal 50 km abdeckenden EMEP-Rasterzellen berechnet. Die Mediane der geschätzten Elementkonzentrationen im Moos sowie die Depositionswerte wurden ln-transformiert und korrelations- und regressionsanalytisch untersucht. Sodann wurden die Regressionsfunktionen auf die Kriging-Flächenkarten der N-Anreicherungen in Moosen angewendet. Die Residuen der Regressionsfunktion wurden bestimmt, entlogarithmiert, auf die Mittelpunkte der entsprechenden EMEP-Rasterzellen projiziert, variogrammanalytisch auf räumliche Strukturen untersucht und mit Lognormal-Kriging flächenhaft interpoliert. Die Kriging-Karte der Residuen wurde abschließend mit der regressionsanalytisch berechneten N-Depositionsflächenkarte verrechnet.Ergebnisse und DiskussionDie Regressionsanalyse zeigt, dass die N-Anreicherung in den Moosen aus Hintergrundgebieten mit der N-Gesamtdeposition europaweit mit Pearson Korrelationen von rp = 0.79 sowie Spearman Korrelationen von rs = 0.70 korreliert ist. Das Bestimmtheitsmaß des Regressionsmodells beträgt r2 = 0,62. Die statistische Auswertung der auf dieser Grundlage berechneten Karte der N-Gesamtdeposition ergibt einen deutschlandweiten Mittelwert der von 18.1 kg/ ha / a (Standardabweichung 3.49 kg / ha / a). Vergleicht man die Ergebnisse dieser Berechnungen mit Ergebnissen aus anderen Verfahren, so zeigen sich z.T. Unterschiede. Die am Ende des Jahres 2009 anlässlich eines Workshops zur Modellierung von Schadstoffeinträgen und ihren Wirkungen auf Ökosysteme veröffentlichten N-Gesamtdepositionsmodellierungen entsprechen allerdings ungefähr denen, die anhand der Daten aus dem EMEP und ICP Vegetation in dieser Untersuchung berechnet wurden.SchlussfolgerungenDie Verknüpfung der Daten zur N-Gesamtdeposition (EMEP) und der N-Anreicherungen in Moosen (ICP Vegetation) ermöglicht eine empirisch validierte, räumlich differenzierte Kartierung der N-Gesamtdeposition. Die ausgeprägte, statistisch hoch signifikante Korrelation zwischen den beiden physikalisch und chemisch miteinander verbundenen Prozessen der atmosphärischen Deposition und der Bioakkumulation bilden die Grundlage der Kartierung. Die Karten nutzen vorhandenes Datenmaterial, das auf der Grundlage europaweit harmonisierter Methoden in zwei qualitätskontrollierten Messprogrammen erhoben wurde. Aus dem Blickwinkel der Ökotoxikologie ist die Verknüpfung von Daten über Stoffeinträge in terrestrische Ökosysteme und N-Anreicherungen in deren Moosbiomasse ein Fortschritt.