Methodologie integrativer Analyse, Modellierung und Management umweltwissenschaftlicher Daten für landschaftsökologische Forschung und Lehre am Beispiel der Exposition von Wäldern gegenüber atmosphärischen Stoffeinträgen und daraus resultierender Veränderungen der Ökosystemintegrität in Kombination mit dem Klimawandel

Show simple item record Nickel, Stefan Dr.-Ing. 2021-02-10T13:27:40Z 2021-02-10T13:27:40Z 2021-02
dc.description.abstract The cumulative habilitation thesis summarizes 23 articles on the exposure of forests to atmospheric heavy metal and nitrogen deposition and the resulting changes in ecosystem integrity linked to climate change. It comprises a complete research data management and is based on a synoptic systematization of studies that were presented and discussed at international conferences during the years 2014-2018 and published in international peer-reviewed journals. The UNECE European Moss Survey (EMS) of the ICP Vegetation (1990-2015) serves as a central reference framework for six articles on bioindication of atmospheric deposition in Germany. For the 2015 survey, the German biomonitoring network was reduced from 726 to 400 sites compared to the 2005 campaign. The restructured moss network 2015 is still harmonized with other environmental monitoring networks in Germany (ICP Forests, ICP Integrated Monitoring, Environmental Specimen Bank). Its restructuring took place without significant losses in the statistical validity of the measurement results compared to 2005. The results of the German contribution to the EMS 2015 reveal a clear, significant decline in the concentrations of mosses for most of the heavy metals (1990-2015), but not for nitrogen (2005-2015) and mercury (1995-2015, in six federal states). Four studies again demonstrate the suitability of ectohydric mosses as biomonitors for the atmospheric deposition of Cd and Pb (Norway, 1995-2005, Europe, 2010) as well as N and Cu (Europe, 2010). The spatial density of agricultural (As, Cd, Cr, Pb, N), forestral (Hg, Ni, V) and urban-industrial land use (Cu, Zn) within radii between 75 and 100 km around the moss sampling sites, distance to emission sources (As, Ni), precipitation (As, Cd, V), and altitude (As, Pb, Hg, V) were detected as major factors influencing the element concentrations in mosses, in addition to the deposition rate. Similarly, there are significant statistical correlations between heavy metal concentrations in the uppermost 3 cm of the natural surface soil (Norway) and respective atmospheric heavy metal deposition (Cd, Hg, Pb), the spatial density of urban-industrial land use within 5 km radius around the sampling point (Hg), precipitation (Hg) and orographic altitude (Cd). The concentrations of Cd and Pb in the natural surface soil reveal similar correlations with the deposition compared to the heavy metal concentrations in mosses. The correlation behavior of moss with respect to atmospheric deposition (Europe) is clearly element-, and respectively, ecoregion-specific. For Cu, the magnitude of these correlations depends on land uses within smaller radii around the moss sampling sites (<5 km), and for As, Cr, Hg, Pb and V those within larger radii (75-100 km) are of importance. The findings of a seventh study on the German Moss Survey 2015 point to the moss sampling area's Leaf Area Index (LAI) as a strong indicator of the canopy drip effect on element concentrations in moss samples. Quantifications of the statistical relationships between the ratios of elemental concentrations of adjacent sampling sites on the one hand and the corresponding leaf area indices on the other hand allow transformations of the element concentrations in mosses to certain standardized vegetation structures (grassland, deciduous forest, coniferous forest, etc.). If spatially representative information on the vegetation structure at the moss sampling points is available, a regionalization of element concentration in mosses for predefined land use classes is feasible, as shown for Cu, Pb, and N by the example of Germany. The integrative analysis of atmospheric heavy metal exposure of terrestrial ecosystems using biomonitoring and modeling is the subject of six other articles of this thesis. Accordingly, in the European Monitoring and Evaluation Programme (EMEP / MSC East Model, 2005, 2007-2011), 10 to 20% higher Cd depositions and 50 to 230% higher Pb depositions were calculated in Germany compared to estimations made with the chemical transport model LOTOS EUROS (LE). Deviations between the spatial patterns of heavy metal concentrations in mosses in Germany and the depositions calculated with LE give a clear signal for underestimates by the modeled deposition of As in Saxony and Cr in Mecklenburg- West Pomerania as well as overestimation of V deposition in the coastal areas of the North and Methodologie integrativer Analyse, Modellierung und Management umweltwissenschaftlicher Daten VI Baltic Seas. Comparisons between the declining trends in atmospheric Cd and Pb deposition (1998- 2013) calculated by use of the EMEP / MSC East model and the corresponding concentrations in leafs and needles of the German Environmental Specimen Bank revealed the highest correlations in the needles of the Spruce (Picea abies) in comparison to beech (Fagus sylvatica)and poplar (Populus nigra, Italica'), whereby significant trends were only apparent from observation periods of 10 to 12 years. Using the example of Germany, six further studies document the development of a spatially explicit methodology for assessing the integrity of forest ecosystems under the influence of atmospheric deposition of nitrogen in combination with climate change. The concept is based on vegetation data and information on chemical and physical soil properties from a vegetation database kept by the Institute of Forestry Eberswalde with currently about 21,600 sampling sites (as of 2013) as well as data on climate change and atmospheric nitrogen deposition. The central reference is a classification system for forest ecosystems in Germany with up to now 60 ecosystem types whose internal homogeneity is based on the typification of essential features of the ecological structures, factors and processes. The methodology is based on 14 indicators for six ecosystem functions and 60 ecosystem-type specific reference states, which have been defined as a reference system for ecosystem integrity assessments by use of data from the years 1961-1990. The studies also document results of mapping ecosystem types and their validation at the national and regional level (Germany, Kellerwald-Edersee National Park (Hesse)), predictive mapping of changes of their Germany-wide distribution under climate change (1961-2070), site-specific dynamic modeling of future developments of key nutrient and water flux indicators (1961-2070), fuzzy rule-based modeling of soil moisture in spatial and temporal differentiation (Germany, Kellerwald, 1961-2070) as well as a rule-based method for comparisons with the reference state and assessments of ecosystem integrity under the influence of climate change and nitrogen deposition. en
dc.language.iso de de_DE
dc.publisher Universität Vechta de_DE
dc.rights.uri de_DE
dc.subject Biomonitoring en
dc.subject Climate modelling en
dc.subject Deposition modelling en
dc.subject Ecological functions en
dc.subject Ecosystem classification en
dc.subject Mapping en
dc.subject Research Data management en
dc.subject European Moss Survey en
dc.subject ICP Forests en
dc.subject Environmental Specimen Bank en
dc.subject EMEP en
dc.subject LOTOS-EUROS en
dc.subject.ddc DDC Sachgruppen::500 - Naturwissenschaften und Mathematik de_DE
dc.title Methodologie integrativer Analyse, Modellierung und Management umweltwissenschaftlicher Daten für landschaftsökologische Forschung und Lehre am Beispiel der Exposition von Wäldern gegenüber atmosphärischen Stoffeinträgen und daraus resultierender Veränderungen der Ökosystemintegrität in Kombination mit dem Klimawandel de_DE
dc.type DoctoralThesis en
dcterms.medium application/pdf de_DE
ubve.organisationseinheit Fakultät II:Geographie de_DE
thesis.level post-doctoral en
ubve.dnb.pnr Nickel, Stefan; 141711558

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