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Number of available datasets: 181
Weather Data 2019, Muencheberg, Germany10.4228/ZALF.DK.166MuenchebergShowOnMapView Sample DataDownload Complete DatasetCreative Commons BY 4.0

Sowa, Dieter

The automatic weather station Müncheberg was installed in 1991 by the Leibniz Centre for Agricultural Landscape Research (ZALF) e.V. and is managed by the Research Platform "Models & Simulation". The station is located within the municipality Müncheberg, district Märkisch-Oderland, state Brandenburg, Germany. Altitude in meter: 62 NN, Geographic latitude: 52,517681 N, Geographic longitude: 14,123200 E,Type: FMA 86. In 2001, the station was replaced by a new system of the same type. In 2018, data have been collected for: soil temperature in 20cm depth (°C); soil temperature in 5cm depth (°C); soil temperature in 50cm depth (°C); soil temperature in 10cm depth (°C); soil temperature in 100cm depth (°C); global radiation (J/cm²); relative humidity (%); air temperature, 2m above ground (°C); precipitation (mm); wind velocity (m/s); evaporation (mm)
Sowa, Dieter (2019): Weather Data 2019, Muencheberg, Germany, Leibniz-Zentrum fuer Agrarlandschaftsforschung (ZALF) e.V. https://www.doi.org/10.4228/ZALF.DK.166

​HostingInstitution: Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany)
DataCollector: Research Platform "Models & Simulation", Leibniz Centre for Agricultural Landscape Research (ZALF)

Continues: 10.4228/ZALF.DK.166

 

Dataset of ecosystem services hot- and coldspots for the utilized agricultural area of the Märkisch-Oderland District-Brandenburg, Germany10.4228/ZALF.DK.161GermanyShow on mapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Ungaro, Fabrizio; Schwartz, Carmen; Piorr, Annette
The dataset contains the indicators of occurrence (0, 1) of hotspots and coldspots for six ecosystem services provision for the utilized agricultural area of the Märkisch-Oderland District (NUTS3) in east Brandenburg, Germany. The six ecosystem services are: i) biomass production (PRO), ii) water storage (WAS), iii) carbon stock total (CST), iv) carbon stock potential (CSP), v) habitat for species (HAB), and vi) landscape attractiveness (LAT). In addition, the dataset contains two composite indicators for the sum of the six ecosystem services’ hotspots and coldspots (range 1-6), which indicate the total number of services of high or low quality, respectively. The data set has 140,116 entries, each one corresponding to a 1 ha size cell (100 m x 100 m), whose centroid coordinates are provided according to the  EPSG:4839 - ETRS89/LCC Germany (N-E) – Projected coordinate system for Germany.  In addition, the dataset provides information about landscape unit, dominant land cover, dominant soil and cadastral parcel (Digitales Feldblockkataster des Landes Brandenburg 2020, DFBK20/BB).
Ungaro, Fabrizio; Schwartz, Carmen; Piorr, Annette (2021) Ecosystem services indicators dataset for the utilized agricultural area of the Märkisch-Oderland District-Brandenburg, Germany. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.161
Researcher: Ungaro, Fabrizio, IBE-CNR, Institute for BioEconomy, National Research Council of Italy, Via Madonna del Piano 10, 50019, Sesto F.no, Italy Researcher: Schwartz, Carmen, Research Area Land Use Decisions in the Spatial and System Context, Working Group Agricultural Landscape Systems, Leibniz Centre for Agricultural Landscape Research, Eberswalder Str. 84, 15374 Müncheberg, Germany Researcher: Piorr, Annette, Research Area Land Use Decisions in the Spatial and System Context, Working Group Agricultural Landscape Systems, Leibniz Centre for Agricultural Landscape Research, Eberswalder Str. 84, 15374 Müncheberg, Germany Contact Person: Annette Piorr Data Collector: Fabrizio Ungaro
Weather Data 2020, Dedelow, Germany10.4228/ZALF.DK.164DedelowShowOnMapView sample dataDownload datasetCreative Commons Attribution-NonCommercial 4.0 International
Verch, Gernot
The agrometeorological weather station Dedelow was installed in 1991 by the Leibniz-Centre for Agricultural Landscape Research (ZALF) e.V. and is managed by the research station of ZALF in Dedelow. The station is located within the municipality Dedelow, district Uckermark, state Brandenburg, Germany. Altitude in meter: 49 NN, Geographic latitude: 53,3665 N, Geographic longitude: 13,8030 E,Type: FMA 86.

In 2020, data have been collected with SYMNET-LOG for: relative humidity (%); air temperature, 20cm above ground (°C); air temperature, 2m above ground (°C); precipitation (mm); wind velocity (m/s), wind direction (°), evapotranspiration (mm), precipitation (mm), air pressure (hPa) and solar radiation (J/m2).
Verch, Gernot (2021): Weather Data 2020, Dedelow, Germany, Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e.V.[doi: 10.4228/ZALF.DK.164]
HostingInstitution:  Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany)
Weather Data 2019, Dedelow, Germany10.4228/ZALF.DK.163DedelowShowOnMapView sample dataDownload datasetCreative Commons Attribution-NonCommercial 4.0 International
Verch, Gernot
The agrometeorological weather station Dedelow was installed in 1991 by the Leibniz-Centre for Agricultural Landscape Research (ZALF) e.V. and is managed by the research station of ZALF in Dedelow. The station is located within the municipality Dedelow, district Uckermark, state Brandenburg, Germany. Altitude in meter: 49 NN, Geographic latitude: 53,3665 N, Geographic longitude: 13,8030 E,Type: FMA 86.

In 2019, data have been collected with SYMNET-LOG for: relative humidity (%); air temperature, 20cm above ground (°C); air temperature, 2m above ground (°C); precipitation (mm); wind velocity (m/s), wind direction (°), evapotranspiration (mm), precipitation (mm), air pressure (hPa) and solar radiation (J/m2).
Verch, Gernot (2021): Weather Data 2019, Dedelow, Germany, Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e.V.[doi: 10.4228/ZALF.DK.163]
HostingInstitution:  Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany)
Weather Data 2018, Dedelow, Germany10.4228/ZALF.DK.145DedelowShowOnMapView sample dataDownload datasetCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Verch, Gernot
The agrometeorological weather station Dedelow was installed in 1991 by the Leibniz-Centre for Agricultural Landscape Research (ZALF) e.V. and is managed by the research station of ZALF in Dedelow. The station is located within the municipality Dedelow, district Uckermark, state Brandenburg, Germany. Altitude in meter: 49 NN, Geographic latitude: 53,3665 N, Geographic longitude: 13,8030 E,Type: FMA 86.

In 2018, data have been collected with SYMNET-LOG for: relative humidity (%); air temperature, 20cm above ground (°C); air temperature, 2m above ground (°C); precipitation (mm); wind velocity (m/s), wind direction (°), evapotranspiration (mm), precipitation (mm), air pressure (hPa) and solar radiation (J/m2).
Verch, Gernot (2021): Weather Data 2018, Dedelow, Germany, Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e.V.[doi: 10.4228/ZALF.DK.145]

Raster and modelling data10.4228/ZALF.DK.153GermanyShowOnMapView sample dataDownload complete datasetCreative Commons Attribution Non-Commercial Share-Alike 4.0
Pernat, Nadja
The data available in connection with the publication are the data for the respective raster maps as well as the data table for modelling. (1) Raster data (count_covar_raster.grd): The data are stored as a raster stack with 9 layers. The layers are named as follows: Layer 1: "subs", the number of submissions Layer 2: "pop", the number of inhabitants Layer 3: "age", the average age of the population Layer 4: "fem", the percentage of the female population Layer 5: "temp", the average temperature in °C from March to November (2012-2017) Layer 6: "preci" the average rainfall in mm from March to November (2012-2017) Layer 7: "wind", the average wind speed in m/s Layer 8: "water", the presence of a larger, standing water body (yes=1, no=0) Layer 9: "east", the location of the grid cell in former political East Germany (yes=1, no=0) in the respective grid cell. (2) Raster data with complete cases for the predictors respected in the Automated modelling selection as data table (model_compl_cases.csv). The column names correspond to the raster data layer names. The variables are additionally described in the "Table Structure" section. The data used for the submission counts are an export of the nationwide database "CULBASE" that contained all data from mosquito monitoring since start of the nationwide monitoring programme in 2011. The CULBASE merged into the new database VECTORBASE in September 2020. Both databases are not public.
Pernat, Nadja (2021) Raster and modelling data. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.153
Walther, Doreen; Kampen, Helge
Microclimatic data along a gradient from kettle holes to agricultural fields in the AgroScapeLabs Quillow 202010.4228/ZALF.DK.158QuillowShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
von der Waydbrink, Grit; Müller, Marina; Pätzig, Marlene; Glemnitz, Michael
Ten kettle holes within six agricultural fields (crop: winter wheat) were selected for monitoring microclimatic conditions around the kettle holes. For this purpose we have established a gradient starting from the edge of the kettle holes up to 50 m into the surrounding wheat fields. Along these gradients microclimatic observation stations were installed at 4 different distances (1m, 5 m, 20 m, 50 m). At each point air temperature, air humidity, leaf wetness and soil moisture were monitored during the growing season of wheat plants (between March and July 2020).
von der Waydbrink, Grit; Müller, Marina; Pätzig, Marlene; Glemnitz, Michael (2020) Microclimatic data along a gradient from kettle holes to agricultural fields in the AgroScapeLabs Quillow 2020. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.158
Long-term crop yields in Germany at NUTS 3 level10.4228/ZALF.DK.157GermanyShow on mapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Sommer, Michael; Völker, Lidia
The dataset compiles official long-term yield statistics (1996-2019) of four major crops in Germany: winter wheat, winter barley, silage maize, winter canola. Spatial aggregation represents the EU NUTS 3 level, which corresponds to districts in Germany. We used the actual district geometry which did not change in Germany since 2011.
Völker, Lidia; Sommer, Michael (2020) Long-term crop yields in Germany at NUTS 3 level. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.157
ZALF Dataset: Measures for yield stability analysis10.4228/ZALF.DK.148no locationShowOnMapView sample dataDownload datasetCreative Commons Attribution 4.0
Döring, Thomas F.; Reckling, Moritz
In the face of a changing climate, yield stability is becoming increasingly important for farmers and breeders. There are no commonly accepted guidelines for assessing yield stability and the large diversity of options impedes comparability of results and reduces confidence in conclusions. Here, we compile a unique list of measures available for yield stability analysis that can be used in agronomy and other disciplines. This data set is linked to the review paper “Methods of yield stability analysis in long-term field experiments. A review” that provides guidelines for quantifying yield stability in different settings. Consistent use of the suggested guidelines including the appropriate use of the measures listed in this data set may provide a basis for robust analyses of yield stability, and to subsequently design stable cropping systems that are better adapted to a changing climate.
Döring, Thomas F.; Reckling, Moritz (2020) Measures for yield stability analysis. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.148

Citation from DataCite
ZALF Dataset: Intra- and interspecific trait variation and abundance of dry grassland plants10.4228/ZALF.DK.146QuillowShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Kober, Klarissa; Schmidt, Kristina
One of the few laws in ecology is that communities consist of few common and many rare taxa.
Functional traits may help to identify the underlying mechanisms of this community pattern, since they correlate with different niche dimensions. However, comprehensive studies are missing that investigate the effects of species mean traits (niche position) and intraspecific trait variability (ITV, niche width) on species abundance. In this study, we tested three predictions: species abundance a)
increases (or decreases) with species mean traits, b) is highest for intermediate species mean traits, and c) increases with ITV. We measured three plant functional traits (specific leaf area, leaf dry matter content, plant height) at 21 local dry grassland communities (10m x 10m) and analyzed the effect of these traits and their variation on species abundance at the local and regional scale.
Kober, Klarissa; Schmidt, Kristina (2020) Intra- and interspecific trait variation and abundance of dry grassland plants. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.146
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