TU Darmstadt / ULB / TUbiblio

Eleven years' data of grassland management in Germany.

Vogt, Juliane and Klaus, Valentin H. and Both, Steffen and Fürstenau, Cornelia and Gockel, Sonja and Gossner, Martin M. and Heinze, Johannes and Hemp, Andreas and Hölzel, Nobert and Jung, Kirsten and Kleinebecker, Till and Lauterbach, Ralf and Lorenzen, Katrin and Ostrowski, Andreas and Otto, Niclas and Prati, Daniel and Renner, Swen and Schumacher, Uta and Seibold, Sebastian and Simons, Nadja and Steitz, Iris and Teuscher, Miriam and Thiele, Jan and Weithmann, Sandra and Wells, Konstans and Wiesner, Kerstin and Ayasse, Manfred and Blüthgen, Nico and Fischer, Markus and Weisser, Wolfgang W. (2019):
Eleven years' data of grassland management in Germany.
In: Biodiversity data journal, pp. e36387, 7, ISSN 1314-2828,
DOI: 10.3897/BDJ.7.e36387,
[Article]

Abstract

Background

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.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.Mowing, grazing and fertilisation were systematically surveyed: 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.For , 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.For , 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).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.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.

New information

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 > 100 papers on the effect of management on biodiversity (e.g. Manning et al. 2015).

Item Type: Article
Erschienen: 2019
Creators: Vogt, Juliane and Klaus, Valentin H. and Both, Steffen and Fürstenau, Cornelia and Gockel, Sonja and Gossner, Martin M. and Heinze, Johannes and Hemp, Andreas and Hölzel, Nobert and Jung, Kirsten and Kleinebecker, Till and Lauterbach, Ralf and Lorenzen, Katrin and Ostrowski, Andreas and Otto, Niclas and Prati, Daniel and Renner, Swen and Schumacher, Uta and Seibold, Sebastian and Simons, Nadja and Steitz, Iris and Teuscher, Miriam and Thiele, Jan and Weithmann, Sandra and Wells, Konstans and Wiesner, Kerstin and Ayasse, Manfred and Blüthgen, Nico and Fischer, Markus and Weisser, Wolfgang W.
Title: Eleven years' data of grassland management in Germany.
Language: English
Abstract:

Background

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.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.Mowing, grazing and fertilisation were systematically surveyed: 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.For , 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.For , 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).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.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.

New information

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 > 100 papers on the effect of management on biodiversity (e.g. Manning et al. 2015).

Journal or Publication Title: Biodiversity data journal
Volume: 7
Divisions: 10 Department of Biology
10 Department of Biology > Ecological Networks
Date Deposited: 15 Oct 2019 06:17
DOI: 10.3897/BDJ.7.e36387
Identification Number: pmid:31598068
Export:
Suche nach Titel in: TUfind oder in Google

Optionen (nur für Redakteure)

View Item View Item