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Number of available datasets: 176
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
The effect of cocultivation of Fusarium, Alternaria, and Pseudomonas on the mycotoxin production and growth10.4228/ZALF.DK.155ShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Hoffmann, Annika; Müller, Marina
Mycotoxigenic fungal pathogens Fusarium and Alternaria are a leading cause for loss in cereal production. During their growth in wheat-ears, they oppose bacterial antagonists such as Pseudomonas. Studies on these groups’ interactions often neglect the infection process’s temporal aspect and the associated priority effects. Here, we focus on how the first colonizer affects the subsequent ones. In a climatic chamber experiment, wheat-ears were sprayed successively with a pair of the strains A. tenuissima At625, F. graminearum Fg23, or Pseudomonas simiae Ps9. Over three weeks, microbial abundances and mycotoxin concentrations were analyzed and visualized via Self Organizing Map with Sammon Mapping (SOM-SM). All three strains revealed different characteristics and strategies to deal with co-inoculation: Fusarium, as the first colonizer, suppressed the establishment of Alternaria and Pseudomonas. Nevertheless, primary inoculation of Alternaria reduced all of the Fusarium toxins and stopped Pseudomonas from establishing. Pseudomonas showed priority effects in delaying and blocking the production of the fungal mycotoxins. The SOM-SM analysis visualized the competitive strengths: Fg23 ranked first, At625 second, Ps9 third. Our findings of species-specific priority effects in a natural environment and the role of the mycotoxins involved are relevant for developing biocontrol applications.
Hoffmann, Annika; Müller, Marina (2020) The effect of cocultivation of Fusarium, Alternaria, and Pseudomonas on the mycotoxin production and growth. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.155
Researcher: Müller, Thomas
Researcher: Koch, Mathias
Researcher: Lentzsch, Peter
Weed flora Monitoring dataset for the AgroScapeLab Quillow located in the District “Uckermark” Brandenburg, Germany10.4228/ZALF.DK.156QuillowShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Glemnitz, Michael
The dataset contains data from a yearly monitoring on at all 43 agricultural fields in a typical agricultural landscape located in the North east of the German lowlands. Three different indicators are included in the data: (i) species richness of weed flora, (ii) abundance of single species per plot and year and (iii) data on crop stands structure. The data set contains information on the spatial arrangements of the investigated plots and on the crop stands per investigational plot and year as well as code tables for the used abbreviations in the data tables.
Glemnitz, Michael (2020) Weed flora Monitoring dataset for the AgroScapeLab Quillow located in the District “Uckermark” Brandenburg, Germany. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.156
Researcher: Glemnitz, Michael, ZALF, Müncheberg (Germany) GRID: : 433014.1
Contact Person: Michael Glemnitz, ZALF, Müncheberg (Germany) GRID: : 433014.1
Data Collector: Cornelia Fischer
HostingInstitution: Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany), GRID: 433014.1
Ecosystem services indicators dataset for the utilized agricultural area of the Märkisch-Oderland District-Brandenburg, Germany10.4228/ZALF.DK.154GermanyShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Ungaro, Fabrizio; Schwartz, Carmen; Piorr, Annette
The dataset contains six standardized (0-1) indicators of ecosystem services provision for the utilized agricultural area of the Märkisch-Oderland District (NUTS3) in east Brandenburg, Germany. The six ecosystem services are i) habitat for species (HAB), ii) carbon stock total (CST), iii) carbon stock potential (CSP), iv) biomass production (PRO), v) landscape attractiveness (LAT), and vi) water storage (WAS). 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. Each indicator value is standardized as number in the range of 0 to 1. The maximum value observed in the study area is then set equal to 1, and the value 0 indicates the relative minimum in the area considered. For each entry, 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 (2020) 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.154
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, Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany

Researcher: Piorr, Annette, Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany

Contact Person: Piorr, Annette

Data Collector: Ungaro, Fabrizio
Farmland bird monitoring in North-east Germany from 2013-201510.4228/ZALF.DK.86QuillowShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Glemnitz, Michael
Abstract: 
Farmland birds are used as indicator for the overall biodiversity on agricultural lands summarizing the effects over the whole food pyramide. The composition, frequency and diversity of the bird communities at 117 sample points, representative for a whole landscape have been monitored over a periode of 3 years in 2013-2015. The survey is a repication of the same survey proceed in 1999-2002. The monitoring was carried out over 5 month per year according to the stop-count-method, differntiated between two distances from the counting point.
Glemnitz, Michael (2020) Farmland bird monitoring in North-east Germany from 2013-2015. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.86
Farmland bird monitoring in North-east Germany from 1999-200210.4228/ZALF.DK.85QuillowShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Glemnitz, Michael
Abstract: 
Farmland birds are used as an indicator for the overall biodiversity on agricultural lands summarizing the effects over the whole food pyramide. The composition, frequency and diversity of the bird communities at 117 sample points, representative for a whole landscape have been monitored over a periode of 4 years in 1999-2002. The monitoring was carried out over 5 month per year according to the stop-count-method, differntiated between two distances from the counting point.
Glemnitz, Michael (2020) Farmland bird monitoring in North-east Germany from 1999-2002. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.85
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