Eleven years’ data of grassland management in Germany

By

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

Type

Article

Date of Publication

2019-09-27

Original Publication

Biodiversity data journal

Volume

7

Pages

1--9

Subjects

Biodiversity-Exploratories , farming practice , fertilisation , grassland maintenance , Grassland management survey , Grazing , intensification of grassland use , livestock units , mowing , Nitrogen , questionnaire , temporal variation

Contributed by

Pensoft Publishers

Language

English

Published by

Sofia Pensoft Publishers [2013]-

Identifiers

DOI: https://doi.org/10.3897/BDJ.7.e36387
eLocator: e36387

 

Abstract

The 150 grassland plots were located in three study regions in Germany, 50 in each region. The dataset describes the yearly grassland management for each grassland plot using 116 variables.<br> General information includes plot identifier, study region and survey year. Additionally, grassland plot characteristics describe the presence and starting year of drainage and whether arable farming had taken place 25 years before our assessment, i.e. between 1981 and 2006. In each year, the size of the management unit is given which, in some cases, changed slightly across years.<br> Mowing, grazing and fertilisation were systematically surveyed:<br> Mowing is characterised by mowing frequency (i.e. number of cuts per year), dates of cutting and different technical variables, such as type of machine used or usage of conditioner.<br> For grazing, the livestock species and age (e.g. cattle, horse, sheep), the number of animals, stocking density per hectare and total duration of grazing were recorded. As a derived variable, the mean grazing intensity was then calculated by multiplying the livestock units with the duration of grazing per hectare [LSU days/ha]. Different grazing periods during a year, partly involving different herds, were summed up to an annual grazing intensity for each grassland.<br> For fertilisation, information on the type and amount of different types of fertilisers was recorded separately for mineral and organic fertilisers, such as solid farmland manure, slurry and mash from a bioethanol factory. Our fertilisation measures neglect dung dropped by livestock during grazing. For each type of fertiliser, we calculated its total nitrogen content, derived from chemical analyses by the producer or agricultural guidelines (Table 3).<br> All three management types, mowing, fertilisation and grazing, were used to calculate a combined land use intensity index (LUI) which is frequently used to define a measure for the land use intensity. Here, fertilisation is expressed as total nitrogen per hectare [kg N/ha], but does not consider potassium and phosphorus.<br> Information on additional management practices in grasslands was also recorded including levelling, to tear-up matted grass covers, rolling, to remove surface irregularities, seed addition, to close gaps in the sward.<br> Investigating the relationship between human land use and biodiversity is important to understand if and how humans affect it through the way they manage the land and to develop sustainable land use strategies. Quantifying land use (the ‘X’ in such graphs) can be difficult as humans manage land using a multitude of actions, all of which may affect biodiversity, yet most studies use rather simple measures of land use, for example, by creating land use categories such as conventional vs. organic agriculture. Here, we provide detailed data on grassland management to allow for detailed analyses and the development of land use theory. The raw data have already been used for &amp;gt; 100 papers on the effect of management on biodiversity (e.g. Manning et al. 2015).