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  • 1
    Call number: PIK L 218-04-0113
    Type of Medium: Monograph available for loan
    Pages: 304
    Location: A 18 - must be ordered
    Branch Library: PIK Library
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  • 2
    Publication Date: 2023-06-08
    Description: The data package compiles vegetation data of ten temperate pre-Alpine managed grasslands in southern Germany. The first dataset originates from a sampling campaign in April 2018. A 30 m x 30 m homogenous flat plot was selected at each of the ten grasslands and sampled at nine to twelve 0.25 m x 0.25 m subplots. After determining the bulk canopy height of the subplot, the vegetation was cut at 0.03 m. Afterwards the following parameters of the cut vegetation were determined in the laboratory: weight of the fresh and dry biomass; weight percentage of the plant functional types (PFT) non-green vegetation, legumes, graminoids, other forbs; total green area index (GAI) and PFT-specific GAI; carbon (C) and nitrogen (N) content of the PFT. Water content and mean C and N contents were calculated from measured values. Additional samples around the subplots were taken to determine the leaf mass per area (LMA) of PFTs that occur in the plot. The second data set is based on a vegetation survey from June 2020 at exactly the same ten plots and includes grassland type, plant species richness and species coverage of the plots. The data package was obtained within the framework of the SUSALPS project (https://www.susalps.de/) to provide in-situ data for the estimation of grassland parameters with unmanned aircraft system (UAS)-based and satellite-based remote sensing data.
    Keywords: Biomass; carbon content; forbs; graminoids; green area index; leaf mass per area; legumes; managed grassland; mesic grassland; nitrogen content; plant functional types; plants; SUSALPS; Sustainable use of alpine and pre-alpine grassland soils in a changing climate; temperate grassland; TERENO; Terrestrial Environmental Observatories; vegetation survey
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 3
    Publication Date: 2023-06-08
    Keywords: Biomass; Biomass, dry mass per area; Biomass, wet mass per area; Calculated, see further details: Overview and description of data set variables; Canopy height; Carbon, organic; carbon content; Carbon content of forbs; Carbon content of graminoids; Carbon content of legumes; Carbon content of non-green vegetation; Date/Time of event; Element analyser CNS; Event label; forbs; Forbs; graminoids; Graminoids; green area index; Green area index, forbs; Green area index, graminoids; Green area index, legumes; Green area index, total; Latitude of event; leaf mass per area; Leaf mass per area; legumes; Legumes; Longitude of event; managed grassland; MULT; Multiple investigations; Nitrogen, organic; nitrogen content; Nitrogen content of forbs; Nitrogen content of graminoids; Nitrogen content of legumes; Nitrogen content of non-green vegetation; Non-green vegetation; Planimeter; Plant functional type; plant functional types; Plant water content; Plot; Rising plate meter; RPM; Site; Southern Germany; Subplot; SUSALPS; SUSALPS-RS2018_EL1-01; SUSALPS-RS2018_EL1-02; SUSALPS-RS2018_EL1-03; SUSALPS-RS2018_EL1-04; SUSALPS-RS2018_EL1-05; SUSALPS-RS2018_EL1-06; SUSALPS-RS2018_EL1-07; SUSALPS-RS2018_EL1-08; SUSALPS-RS2018_EL1-09; SUSALPS-RS2018_EL1-10; SUSALPS-RS2018_EL1-11; SUSALPS-RS2018_EL1-12; SUSALPS-RS2018_EL2-01; SUSALPS-RS2018_EL2-02; SUSALPS-RS2018_EL2-03; SUSALPS-RS2018_EL2-04; SUSALPS-RS2018_EL2-05; SUSALPS-RS2018_EL2-06; SUSALPS-RS2018_EL2-07; SUSALPS-RS2018_EL2-08; SUSALPS-RS2018_EL2-09; SUSALPS-RS2018_EL2-10; SUSALPS-RS2018_EL2-11; SUSALPS-RS2018_EL2-12; SUSALPS-RS2018_EL3-01; SUSALPS-RS2018_EL3-02; SUSALPS-RS2018_EL3-03; SUSALPS-RS2018_EL3-04; SUSALPS-RS2018_EL3-05; SUSALPS-RS2018_EL3-06; SUSALPS-RS2018_EL3-07; SUSALPS-RS2018_EL3-08; SUSALPS-RS2018_EL3-09; SUSALPS-RS2018_EL3-10; SUSALPS-RS2018_EL3-11; SUSALPS-RS2018_EL3-12; SUSALPS-RS2018_FE1-01; SUSALPS-RS2018_FE1-02; SUSALPS-RS2018_FE1-03; SUSALPS-RS2018_FE1-04; SUSALPS-RS2018_FE1-05; SUSALPS-RS2018_FE1-06; SUSALPS-RS2018_FE1-07; SUSALPS-RS2018_FE1-08; SUSALPS-RS2018_FE1-09; SUSALPS-RS2018_FE1-10; SUSALPS-RS2018_FE1-11; SUSALPS-RS2018_FE1-12; SUSALPS-RS2018_FE2-01; SUSALPS-RS2018_FE2-02; SUSALPS-RS2018_FE2-03; SUSALPS-RS2018_FE2-04; SUSALPS-RS2018_FE2-05; SUSALPS-RS2018_FE2-06; SUSALPS-RS2018_FE2-07; SUSALPS-RS2018_FE2-08; SUSALPS-RS2018_FE2-09; SUSALPS-RS2018_FE2-10; SUSALPS-RS2018_FE2-11; SUSALPS-RS2018_FE2-12; SUSALPS-RS2018_FE3-01; SUSALPS-RS2018_FE3-02; SUSALPS-RS2018_FE3-03; SUSALPS-RS2018_FE3-04; SUSALPS-RS2018_FE3-05; SUSALPS-RS2018_FE3-06; SUSALPS-RS2018_FE3-07; SUSALPS-RS2018_FE3-08; SUSALPS-RS2018_FE3-09; SUSALPS-RS2018_FE3-10; SUSALPS-RS2018_FE3-11; SUSALPS-RS2018_FE3-12; SUSALPS-RS2018_FE4-01; SUSALPS-RS2018_FE4-02; SUSALPS-RS2018_FE4-03; SUSALPS-RS2018_FE4-04; SUSALPS-RS2018_FE4-05; SUSALPS-RS2018_FE4-06; SUSALPS-RS2018_FE4-07; SUSALPS-RS2018_FE4-08; SUSALPS-RS2018_FE4-09; SUSALPS-RS2018_FE4-10; SUSALPS-RS2018_FE4-11; SUSALPS-RS2018_FE4-12; SUSALPS-RS2018_RB1-01; SUSALPS-RS2018_RB1-02; SUSALPS-RS2018_RB1-03; SUSALPS-RS2018_RB1-04; SUSALPS-RS2018_RB1-05; SUSALPS-RS2018_RB1-06; SUSALPS-RS2018_RB1-07; SUSALPS-RS2018_RB1-08; SUSALPS-RS2018_RB1-09; SUSALPS-RS2018_RB1-10; SUSALPS-RS2018_RB1-11; SUSALPS-RS2018_RB1-12; SUSALPS-RS2018_RB2-01; SUSALPS-RS2018_RB2-02; SUSALPS-RS2018_RB2-03; SUSALPS-RS2018_RB2-04; SUSALPS-RS2018_RB2-05; SUSALPS-RS2018_RB2-06; SUSALPS-RS2018_RB2-07; SUSALPS-RS2018_RB2-08; SUSALPS-RS2018_RB2-09; SUSALPS-RS2018_RB2-10; SUSALPS-RS2018_RB2-11; SUSALPS-RS2018_RB2-12; SUSALPS-RS2018_RB3-01; SUSALPS-RS2018_RB3-02; SUSALPS-RS2018_RB3-03; SUSALPS-RS2018_RB3-04; SUSALPS-RS2018_RB3-05; SUSALPS-RS2018_RB3-06; SUSALPS-RS2018_RB3-07; SUSALPS-RS2018_RB3-08; SUSALPS-RS2018_RB3-09; SUSALPS-RS2018_RB3-10; SUSALPS-RS2018_RB3-11; SUSALPS-RS2018_RB3-12; Sustainable use of alpine and pre-alpine grassland soils in a changing climate; temperate grassland; TERENO; Terrestrial Environmental Observatories
    Type: Dataset
    Format: text/tab-separated-values, 3480 data points
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  • 4
    Publication Date: 2024-04-20
    Description: The transition zone between the Southern Eastern Alps and the Dinarides is situated in western Slovenia and northeastern Italy. Here, a system of mainly NW-SE trending, right-lateral strike-slip faults accommodates the shortening between the Adriatic Plate and Eurasia. Due to the low deformation rates, geodetic techniques and seismology provide only limited insights into the activity of those faults. Geomorphological studies are confronted with problems arising from the low fault slip rates, distributed deformation, and unfavourable conditions due to the karst environment. One way to overcome these problems is the use of paleoseismology, i.e. the excavation of active faults to study their earthquake history and slip behaviour. A prerequisite for paleoseismological trenching is knowledge on the precise location of the fault trace and the availability of a suitable sediment record. We performed geophysical surveys across the potentially active faults in Slovenia and Italy to select sites for paleoseismic trenching. We used a ground-penetrating radar (GPR) system from Geophysical Survey Systems Inc (GSSI) with monostatic 100 MHz, 270 MHz, and 400 MHz antennas and a Pulse EKKO Pro Sensors & Software system equipped with bistatic 250 MHz antennas. All data were processed with the ReflexW software (Sandmeier Geophysical Research). Processing included frequency bandpass filtering, background removal, gain adjustments, and topographic corrections. The topographic data were extracted from the 1 m DEM. Electric resistivity tomography (ERT) was performed with a 4-point-light system (Lippmann Geophysikalische Messgeräte). We used up to 80 electrodes with varying electrode spacing for Wenner, Schlumberger, and Dipole-Dipole arrays, depending on target resolution and depth. Data inversion was done with Res2DInv (Geotomo Software) and included manual de-spiking and topographic corrections. Along several profiles we measured the vertical gradient of the geomagnetic field and the total magnetic field strength with a proton magnetometer GSM - 19T (GEM Systems). The system consists of a rover and a base station, which allows correcting the data for diurnal variation. Depending on the equipment used and the survey parameters, these methods allow insights into the first few metres of the subsurface with a resolution of few centimetres (georadar) to a few metres (ERT). We focussed on sites that host Quaternary sediments. Most of the data in this dataset are 2D profiles perpendicular to the mapped traces of active faults. Several promising sites were investigated in 2.5D, i.e. the profile line spacing was dense enough to compute a pseudo-3D dataset. We collected the data in May and June, 2018. This dataset contains ~2.5 km of magnetic data, ~20 km of GPR data, and ~1.7 km of ERT data. This work was undertaken for the DFG project "Earth surface response to Quaternary faulting and shallow crustal structure in the eastern Adria-Alpine collision zone and the Friulian plain" within the DFG-funded priority programme SPP2017 - Mountain building processes in 4D.
    Keywords: Active Tectonics; ERT; fault; georadar; GPR; Italy; magnetics; Priority Programme 2017 4D-MB SPP: Mountain Building Processes in Four Dimensions (MB-4D); Slovenia; SPP2017
    Type: Dataset
    Format: application/zip, 2.3 GBytes
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  • 5
    ISSN: 0009-286X
    Keywords: Chemistry ; Industrial Chemistry
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Additional Material: 6 Ill.
    Type of Medium: Electronic Resource
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  • 6
    Publication Date: 2015-05-15
    Description: During the Soviet Virgin Lands Campaign, approximately 23 million hectares (Mha) of Eurasian steppe grassland were converted into cropland in Northern Kazakhstan from 1954 to 1963. As a result Kazakhstan became an important breadbasket of the former Soviet Union. However, the collapse of the Soviet Union in 1991 triggered widespread agricultural abandonment, and much cropland reverted to grasslands. Our goal in this study was to reconstruct and analyze agricultural land-cover change since the eve of the Virgin Lands Campaign, from 1953 to 2010 in Kostanay Province, a region that is representative of Northern Kazakhstan. Further, we assessed the potential of currently idle cropland for re-cultivation. We reconstructed the cropland extent before and after the Virgin Lands Campaign using archival maps, and we mapped the agricultural land cover in the late Soviet and post-Soviet period using multi-seasonal Landsat TM/ETM+ images from circa 1990, 2000 and 2010. Cropland extent peaked ...
    Print ISSN: 1748-9318
    Electronic ISSN: 1748-9326
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering
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  • 7
    Publication Date: 2016-01-12
    Description: Rapid and ongoing change creates novelty in ecosystems everywhere, both when comparing contemporary systems to their historical baselines, and predicted future systems to the present. However, the level of novelty varies greatly among places. Here we propose a formal and quantifiable definition of abiotic and biotic novelty in ecosystems, map abiotic novelty globally, and discuss the implications of novelty for the science of ecology and for biodiversity conservation. We define novelty as the degree of dissimilarity of a system, measured in one or more dimensions relative to a reference baseline, usually defined as either the present or a time window in the past. In this conceptualization, novelty varies in degree, it is multidimensional, can be measured, and requires a temporal and spatial reference. This definition moves beyond prior categorical definitions of novel ecosystems, and does not include human agency, self-perpetuation, or irreversibility as criteria. Our global assessment of novelty was based on abiotic factors (temperature, precipitation, and nitrogen deposition) plus human population, and shows that there are already large areas with high novelty today relative to the early 20th century, and that there will even be more such areas by 2050. Interestingly, the places that are most novel are often not the places where absolute changes are largest; highlighting that novelty is inherently different from change. For the ecological sciences, highly novel ecosystems present new opportunities to test ecological theories, but also challenge the predictive ability of ecological models and their validation. For biodiversity conservation, increasing novelty presents some opportunities, but largely challenges. Conservation action is necessary along the entire continuum of novelty, by redoubling efforts to protect areas where novelty is low, identifying conservation opportunities where novelty is high, developing flexible yet strong regulations and policies, and establishing long-term experiments to test management approaches. Meeting the challenge of novelty will require advances in the science of ecology, and new and creative conservation approaches.
    Print ISSN: 1051-0761
    Electronic ISSN: 1939-5582
    Topics: Biology
    Published by Wiley on behalf of The Ecological Society of America (ESA).
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  • 8
  • 9
    Publication Date: 2013-05-21
    Print ISSN: 0020-7128
    Electronic ISSN: 1432-1254
    Topics: Geography , Physics
    Published by Springer
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  • 10
    Publication Date: 2020-09-28
    Description: The data set contains information on aboveground vegetation traits of 〉 100 georeferenced locations within ten temperate pre-Alpine grassland plots in southern Germany. The grasslands were sampled in April 2018 for the following traits: bulk canopy height; weight of fresh and dry biomass; dry weight percentage of the plant functional types (PFT) non-green vegetation, legumes, non-leguminous forbs, and graminoids; total green area index (GAI) and PFT-specific GAI; plant water content; plant carbon and nitrogen content (community values and PFT-specific values); as well as leaf mass per area (LMA) of PFT. In addition, a species specific inventory of the plots was conducted in June 2020 and provides plot-level information on grassland type and plant species composition. The data set was obtained within the framework of the SUSALPS project (“Sustainable use of alpine and pre-alpine grassland soils in a changing climate”; https://www.susalps.de/) to provide in-situ data for the calibration and validation of remote sensing based models to estimate grassland traits.
    Electronic ISSN: 2052-4463
    Topics: Nature of Science, Research, Systems of Higher Education, Museum Science
    Published by Springer Nature
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