Measuring penetration resistance (PR) is a common technique for evaluating the effects of field management on soils. This study focuses on the effects of long-term tillage on the spatial distribution of PR, comparing reduced and conventional tillage (CT) practices. The study site, located in Lower Saxony (Germany), has been subdivided into three plots, with one plot having been managed conventionally, whereas reduced tillage (RT) practices have been applied to the other two. In total, PR was measured at 63 randomly selected points. The PR data were stepwise interpolated using kriging with external drift. Core samples have been taken at 20 additional sites. The results show significant differences in PR between the different tillage practices. Within the conventionally managed plot, PR ranges to 2.3 MPa less in the topsoil than under RT. However, measured saturated hydraulic conductivity and amount of biopores at the depth of 30-35 cm are significantly greater under RT, indicating improved soil properties under RT. Comparisons between the headlands (HL) and the inner field point out the effects of intense field traffic in the HL, where maximum PR values of about 6 MPa have been measured. The spatial prediction of PR values show that long-term effects of different tillage practices result in clearly structured patterns between CT and RT and the HL. Combining extensive PR measurements and point measurements of additional soil properties supports an adequate interpretation of PR data and can lead to fieldwide derivation of soil functions influenced by field management.
The increasing use of biogas, produced from energy crops like silage maize, is supposed to noticeably change the structures and patterns of agricultural landscapes in Europe. The main objective of our study is to quantify this assumed impact of intensive biogas production with the example of an agrarian landscape in Northern Germany. Therefore, we used three different datasets; Corine Land Cover (CLC), local agricultural statistics (Agrar-Struktur-Erhebung, ASE), and data on biogas power plants. Via kernel density analysis, we delineated impact zones which represent different levels of bioenergy-generated transformations of agrarian landscapes. We cross-checked the results by the analyses of the land cover and landscape pattern changes from 2000 to 2012 inside the impact zones. We found significant correlations between the installed electrical capacity (IC) and land cover changes. According to our findings, the landscape pattern of cropland—expressed via landscape metrics (mean patch size (MPS), total edge (TE), mean shape index (MSI), mean fractal dimension index (MFRACT)—increased and that of pastures decreased since the beginning of biogas production. Moreover, our study indicates that the increasing number of biogas power plants in certain areas is accompanied with a continuous reduction in crop diversity and a homogenization of land use in the same areas. We found maximum degrees of land use homogenisation in areas with highest IC. Our results show that a Kernel density map of the IC of biogas power plants might offer a suitable first indicator for monitoring and quantifying landscape change induced by biogas production.
“The Anthropocene” currently serves as a framework to acknowledge global human influences on the earth systems. Different prominent authors call for geographers and especially physical geographers to intensify their involvement in the discussions on the theme. A bibliometric analysis shows that geographers are already one of the leading contributors to the keyword Anthropocene in journal articles. While we generally support the standpoint of increased engagement with the topic, we want to emphasize that we need to do more than only attaching the “Anthropocene” label to our daily research practice. A critical engagement with and reflection of the research questions and contexts is needed to play a vital role as discussant in the debate. We should take advantage of the diverse themes, topics and viewpoints of our subject by actively following a more critical approach to our research practices in order to find those geographic ties that join us and our discipline and that enable us to contribute more substantially to the Anthropocene debate.
Heat demand of buildings and related CO2 emissions caused by energy supply contribute to global climate change. Spatial data-based heat planning enables municipalities to reorganize local heating sectors towards efficient use of regional renewable energy resources. Here, annual heat demand of residential buildings is modeled and mapped for a German federal state to provide regional basic data. Using a 3D building stock model and standard values of building-type-specific heat demand from a regional building typology in a Geographic Information Systems (GIS)-based bottom-up approach, a first base reference is modeled. Two spatial data sets with information on the construction period of residential buildings, aggregated on municipality sections and hectare grid cells, are used to show how census-based spatial data sets can enhance the approach. Partial results from all three models are validated against reported regional data on heat demand as well as against gas consumption of a municipality. All three models overestimate reported heat demand on regional levels by 16 to 19%, but underestimate demand by up to 8% on city levels. Using the hectare grid cells data set leads to best prediction accuracy values at municipality section level, showing the benefit of integrating this high detailed spatial data set on building age.
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