Spatio-temporal drivers of soil and ecosystem carbon fluxes at field scale in an upland grassland in Germany

Ecosystem carbon (C) fluxes in terrestrial ecosystems are affected by varying environmental conditions (e.g. soil heterogeneity and the weather) and land management. However, the interactions between soil respiration (Rs) and net ecosystem exchange (NEE) and their spatio-temporal dependence on environmental conditions and land management at field scale is not well understood. We performed repeated C flux measurement at 21 sites during the 2013 growing season in a temperate upland grassland in Germany, which was fertilized and cut three times according to the agricultural practice typical of the region. Repeated measurements included determination of NEE, Rs, leaf area index (LAI), meteorological conditions as well as physical and chemical soil properties. Temporal variability of Rs was controlled by air temperature, while LAI influenced the temporal variability of NEE. The three grass cuts reduced LAI and affected NEE markedly. More than 50% of NEE variability was explained by defoliation at field scale. Additionally, soil heterogeneity affected NEE, but to a lower extent (>30%), while Rs remained unaffected. We conclude that grassland management (i.e. repeated defoliation) and soil heterogeneity affects the spatio-temporal variability of NEE at field scale

Zur Verbreitung, Ökologie und Vergesellschaftung des Pillenfarns (Pilularia globulifera L.) im südwestlichen Niedersachsen und nordwestlichen Westfalen

Vom Pillenfarn sind im Untersuchungsgebiet 22 aktuelle Fundorte bekannt; einen Verbreitungsschwerpunkt besitzt er im westfälisch-niedersächsischen Grenzgebiet, im Bereich des Gildehauser Venns und der Brechte. Der Pillenfarn besiedelt heute fast ausschließlich neu angelegte, meist nährstoffärmere, schwach saure bis neutrale, aber auch schwach basische Gewässer. Vorkommen an natürlichen Heideweihern (Witte Venn, Gildehauser Venn) sind heute erloschen. Wichtigste Ursache hierfür dürfte die Gewässerversauerung der letzten Jahrzehnte sein. Wasseranalysen ergaben bei einigen Faktoren recht uneinheitliche Werte. Insbesondere fielen bei einzelnen (z. T. belasteten) Gewässern erhöhte Stickstoff- und Calciumwerte auf. Unter optimalen Bedingungen bildet der Pillenfarn in dichten Rasen wachsend die Pillenfarn-Gesellschaft (Pilularietum globuliferae). Die Ausbildung von kennartenarmen und kennartenreichen Beständen dürfte vor allem auf die floristische Ausstattung des Standortes und seiner näheren Umgebung bei Anlage der Gewässer zurückzuführen sein. Die aus der Abb. 3 ersichtliche Vegetationszonierung kann als typisch für viele nährstoffärmere Pioniergewässer der nordwestdeutschen Sandgebiete angesehen werden

Zur Verbreitung und Bestandssituation des Gagels (Myrica gale L.) in Westfalen und der Grafschaft Bentheim : mit 2 Abbildungen

Klaus Kaplan und Thomas Prolingheue

Analyzing spatiotemporal variability of heterotrophic soil respiration at the field scale using orthogonal functions

Soil CO2 efflux was measured with a closed chamber system along a 180 m transect on a bare soil field characterized by a gentle slope and a gradient in soil properties at 28 days within a year. Principal component analysis (PCA) was used to extract the most important patterns (empirical orthogonal functions, EOFs) of the underlying spatiotemporal variability in CO2 efflux. These patterns were analyzed with respect to their geostatistical properties, their relation to soil parameters obtained from laboratory analysis, and the relation of their loading time series to temporal variability of soil temperature and moisture. A particular focus was set on the analysis of the overfitting behaviour of two statistical models describing the spatiotemporal efflux variability: i) a multiple regression model using the k first EOFs of soil properties to predict the n first EOFs of efflux, which were then used to obtain a prediction of efflux on all days and points: and ii) a modified multiple regression model based on re-sorting of the EOFs based on their expected predictive power. It was demonstrated that PCA helped to separate meaningful spatial correlation patterns and unexplained variability in datasets of soil CO2 efflux measurements. The two PCA analyses suggested that only about half of the total variance of efflux could be related to field-scale spatial variability of soil properties, while the other half was "noise" attributed to temporal fluctuations on the minute time scale and short-range spatial heterogeneity on the decimetre scale. The most important spatial pattern in CO2 efflux was clearly related to soil moisture and the driving soil physical properties. Temperature, on the other hand, was the most important factor controlling the temporal variability of the spatial average of soil respiration. (C) 2012 Elsevier B.V. All rights reserved