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Eleven years’ data of grassland management in Germany

Juliane Vogt, Valentin Klaus, Steffen Both, Cornelia Fürstenau, Sonja Gockel, Martin Gossner, Johannes Heinze, Andreas Hemp, Nobert Hölzel, Kirsten Jung, Till Kleinebecker, Ralf Lauterbach, Katrin Lorenzen, Andreas Ostrowski, Niclas Otto, Daniel Prati, Swen Renner, Uta Schumacher, Sebastian Seibold, Nadja Simons, Iris Steitz, Miriam Teuscher, Jan Thiele, Sandra Weithmann, Konstans Wells Orcid Logo, Kerstin Wiesner, Manfred Ayasse, Nico Blüthgen, Markus Fischer, Wolfgang Weisser

Biodiversity Data Journal, Volume: 7

Swansea University Author: Konstans Wells Orcid Logo

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DOI (Published version): 10.3897/BDJ.7.e36387

Abstract

The 150 grassland plots were located in three study regions in Germany, 50 in eachregion. The dataset describes the yearly grassland management for each grassland plotusing 116 variables.General information includes plot identifier, study region and survey year. Additionally,grassland plot character...

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Published in: Biodiversity Data Journal
ISSN: 1314-2836 1314-2828
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa52171
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Abstract: The 150 grassland plots were located in three study regions in Germany, 50 in eachregion. The dataset describes the yearly grassland management for each grassland plotusing 116 variables.General information includes plot identifier, study region and survey year. Additionally,grassland plot characteristics describe the presence and starting year of drainage andwhether arable farming had taken place 25 years before our assessment, i.e. between1981 and 2006. In each year, the size of the management unit is given which, in somecases, changed slightly across years.Mowing, grazing and fertilisation were systematically surveyed:Mowing is characterised by mowing frequency (i.e. number of cuts per year), dates ofcutting and different technical variables, such as type of machine used or usage ofconditioner.For grazing, the livestock species and age (e.g. cattle, horse, sheep), the number ofanimals, stocking density per hectare and total duration of grazing were recorded. As aderived variable, the mean grazing intensity was then calculated by multiplying thelivestock units with the duration of grazing per hectare [LSU days/ha]. Different grazingperiods during a year, partly involving different herds, were summed up to an annualgrazing intensity for each grassland.For fertilisation, information on the type and amount of different types of fertilisers wasrecorded separately for mineral and organic fertilisers, such as solid farmland manure,slurry and mash from a bioethanol factory. Our fertilisation measures neglect dung droppedby livestock during grazing. For each type of fertiliser, we calculated its total nitrogencontent, derived from chemical analyses by the producer or agricultural guidelinesAll three management types, mowing, fertilisation and grazing, were used to calculate acombined land use intensity index (LUI) which is frequently used to define a measure forthe land use intensity. Here, fertilisation is expressed as total nitrogen per hectare [kg N/ha], but does not consider potassium and phosphorus.Information on additional management practices in grasslands was also recorded includinglevelling, to tear-up matted grass covers, rolling, to remove surface irregularities, seedaddition, to close gaps in the sward.New informationInvestigating the relationship between human land use and biodiversity is important tounderstand if and how humans affect it through the way they manage the land and todevelop sustainable land use strategies. Quantifying land use (the ‘X’ in such graphs) canbe difficult as humans manage land using a multitude of actions, all of which may affectbiodiversity, yet most studies use rather simple measures of land use, for example, bycreating land use categories such as conventional vs. organic agriculture. Here, we providedetailed data on grassland management to allow for detailed analyses and thedevelopment of land use theory. The raw data have already been used for > 100 papers onthe effect of management on biodiversity (e.g. Manning et al. 2015).
College: Faculty of Science and Engineering