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Number of available datasets: 167
Mosquito monitoring data from active (2011-2017) and passive (2012-2017) surveillance10.4228/ZALF.DK.151GermanyShowOnMapView sample dataDownload complete datasetCreative Commons Attribution Non-Commercial Share-Alike 4.0
Pernat, Nadja
Mosquito monitoring data from active surveillance with BG-Sentinel traps from 2011 to 2017 and from passive surveillance - submissions to the "Mückenatlas" - between the years 2012 to 2017. The two different data sets are in one table, but separable by the table column "method". Locations of traps and submissions are not available due to data privacy regulations. The columns "bio.o" and "biocat" are only available for the passive surveillance entries as they depend on the participants notations about find spot that are not given in case of active surveillance by professional scientists.
Pernat, Nadja (2020) Mosquito monitoring data from active surveillance with BG-Sentinel traps from 2011 to 2017. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.151
Datasets from a Germany-wide business survey on voluntary nature conservation commitments10.4228/ZALF.DK.149GermanyShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
​Krause, Marlen Sibylle; Droste, Nils; Matzdorf, Bettina
The data stems from a Germany-wide business survey about voluntary corporate commitments for the protection of biodiversity and natural ecosystems. The main purpose of the survey was to analyse in how far businesses are engaged for nature conservation as well as the factors that influence their actions in this regard. Moreover, the survey investigated business perceptions regarding the concept of an online-marketplace for nature conservation credits. The datasets include information about company characteristics. The complete dataset (i.e. “dataset_complete”) contains information from 747 respondents that logged into the online survey system. Out of those, the first subset (i.e. “subset_1”) comprises the responses from 618 companies that provided sufficiently complete questionnaires, suitable for an analysis of drivers for corporate conservation commitments.
Krause, Marlen Sibylle; Droste, Nils; Matzdorf, Bettina (2020) Datasets from a Germany-wide business survey on voluntary nature conservation commitments. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.149
Groundwater level monitoring, Havelländisches Luch, Germany10.4228/ZALF.DK.150PaulinenaueShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0

​Dietrich, Ottfried

The Leibniz Centre for Agricultural Landscape Research (ZALF) e.V. performs a groundwater monitoring in the Havelländisches Luch near Paulinenaue since 2014. The area is a typical agricultural used grassland site with a groundwater table near surface (0 .. 1.5 m b.s.). The altitude of measurement point is around 28.5 m a.s.l., the coordinates are 52°41'28"N and 12°43'56"E.
Dietrich, Ottfried (2020) Groundwater level monitoring, Havelländisches Luch, Germany. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.150

​Researcher: Dietrich, Ottfried, Leibniz Centre for Agricultural Landscape Research (ZALF)
DataCollector: Weipert, Mario, Leibniz Centre for Agricultural Landscape Research (ZALF)
HostingInstitution: Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany), GRID: 433014.1

Results of two alfalfa pot experiments designed to evaluate the precision and accuracy of closed chamber based CO2 exchange measurements affected by light-inhibited leaf respiration10.4228/ZALF.DK.139MünchebergShow on mapView sample dataDownload complete datasetCreative Commons Attribution 4.0

​Hoffmann, Mathias; Vaidya, Shrijana; Paraje Sanchez, Eva; Buchen, Caroline; Huth, Vytas; Augustin, Jürgen

- To date, it is still unclear whether light inhibition of leaf level autotrophic respiration (LRa(d)) affects the consistency and accuracy of an ecosystems net CO2 exchange (NEE) and thus C sink or source function,
- Within two alfalfa pot experiments we investigated: (1) whether LRa(d) is inhibited by light; (2) how this influences consictency and accuracy of ecosystem respiration (Reco), gross primary production (GPP) and NEE, derived using a commonly applied gap-filling technique.
Hoffmann, Mathias et al. (2020) Results of two alfalfa pot experiments designed to evaluate the precision and accuracy of closed chamber based CO2 exchange measurements affected by light-inhibited leaf respiration. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.139
Weather Data 2017, Dedelow, Germany10.4228/ZALF.DK.144DedelowShowOnMapView sample dataDownload complete 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 2017, 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 (2020): Weather Data 2017, Dedelow, Germany, Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e.V.[doi: 10.4228/ZALF.DK.144]
HostingInstitution:  Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany)
DataManager: Research Information Systems, Leibniz Centre for Agricultural Landscape Research (ZALF)
RegistrationAgency: German National Library of Science and Technology - TIB
DataCollector: Research Station Dedelow, Leibniz Centre for Agricultural Landscape Research (ZALF)
Applicability of a novel robotic chamber system to study the spatio-temporal dynamics of agricultural CO2 exchanges10.4228/ZALF.DK.143Holzendorf near Dedelow, GermanyShowOnMapView sample dataDownload complete datasetCreative Commons Attribution-NonCommercial 4.0

​Shrijana Vaidya, Marten Schmidt, Peter Rakowski, Gernot Verch, Jürgen Augustin, Michael Sommer, Mathias Hoffmann

Current approaches to measure and quantify CO2 flux dynamics of agricultural landscapes e.g., eddy covariance, manual and automatic chamber systems have limitations in either accounting for small scale spatial heterogeneity (eddy covariance and automatic chambers) or short-term temporal variability (manual chambers). Although automatic chambers are in principle capable to detect small-scale spatial differences of CO2 flux dynamics in a sufficient temporal resolution, they are usually limited to only a few spatial repetitions. To overcome these limitations, a novel robotic chamber system for CO2 gas exchange measurements was developed which is capable to detect short term temporal dynamics and small scale spatial heterogeneity. This datasets contains data of weather conditions, measured CO2 flux(Net Ecosystem Exchange - NEE and ecosystem respiration - Reco) and modelled CO2 exchange obtained from the measurements that were conducted from 08/07/2019 to 9/09/2019 for spring barley within the hummocky ground moraine landscape of northeastern Germany (CarboZALF-D). The soil and erosion stages of the study area are classified as Calcaric Regosol (RZ; extremely eroded), Nudiargic Luvisol (eLL; strongly eroded) and Calcic Luvisol (LL; non-eroded).
Shrijana Vaidya, Marten Schmidt, Peter Rakowski, Gernot Verch, Jürgen Augustin, Michael Sommer, Mathias Hoffmann, Norbert Bonk (2020) A novel robotic chamber system allowing to accurately and precisely determining spatio-temporal CO2 flux dynamics of heterogeneous croplands. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.143
Data set with high temporal resolution for winter wheat grown under rain fed and irrigated conditions for agro-ecosystem modelling10.4228/ZALF.DK.140ShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0

​Mirschel, Wilfried; Meier, Kristin;Lemke, Andreas

Detailed measurements on soil, plant and atmosphere are required for the development and validation of crop growth and agroecosystem models. These measurements should be available with a high temporal resolution. With the aim of creating a growth model for winter wheat, an experiment with winter wheat under integrated cultivation conditions was carried out at the intensive experimental field of the Müncheberg Research Centre for Soil Fertility, Germany, between 1979 and 1981, both with and without irrigation. Field chambers were used for daily measurements of the CO2 balance of the crop stand. The daily evaporation was measured with two different evaporation pans. The different biomass components of the winter wheat crop stand were measured in weekly intervals from April to harvest in July/August. The different biomass components were analysed in the laboratory concerning their carbon, nitrogen, phosphorus and potassium content. Based on this coherent data set, the growth model TRITSIM for winter wheat was developed at the Müncheberg Research Centre for Soil Fertility in the 1980s. TRITSIM was incorporated into the complex agroecosystem model AGROSIM-WHEAT of the Research Institute of Plant Protection Eberswalde, Germany, for the identification of optimal plant protection measures under practical field conditions. The data set presented here can also be the basis for the verification and validation of further winter wheat growth and/or agroecosystem models.
Mirschel, Wilfried; Meier, Kristin;Lemke, Andreas (2020) Data set with high temporal resolution for winter wheat grown under rainfed and irrigated conditions for agro-ecosystem modelling. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.140
Multiyear soil, plant, weather and treatment data from an erosion-affected soil landscape in the Uckermark region, NE Germany10.4228/ZALF.DK.64CarboZALF, Uckermark, Quillow, NE GermanyShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0

​Sommer, Michael; Hoffmann, Mathias; Gerke, Horst H.; Meier, Kristin

Agricultural landscapes represent amajor component in the global carbon (C) cycle. Especially their behavior asCO2 sources or sinks is still under debate. In 2009 a long-term,interdisciplinary field experiment (CarboZALF-D) was established, toquantify all C fluxes at characteristic soil-plant-systems. Our researchfocused on the feedbacks of soil erosion on C fluxes, C balances and relateddrivers. Therefore, experimental plots were designed in a way to represent afull gradient of soil erosion: non-eroded, strongly eroded, extremelyeroded, and depositional soils. Here, we present data on basic physical andchemical soil properties, weather (incl. rainfall chemistry), treatments(farming practice), and crops (incl. LAI dynamics, biomass, yields,nutrients) of four representative plots over a seven-year period(2010-2016). Comprehensive scientific publications on complex interactionsin the soil-plant-atmosphere system are listed below.
Sommer, Michael; Hoffmann, Mathias; Gerke, Horst H.; Meier, Kristin (2020) Multiyearsoil, plant, weather and treatment data from an erosion-affected soillandscape in the Uckermark region https://www.doi.org/10.4228/ZALF.DK.64

​ProjectLeader: Augustin, Jürgen
ProjectLeader: Sommer, Michael
DataCollector: Gerke, Horst H.
DataCollector: Hierold, Wilfried
DataCollector: Onasch, Ingrid
DataCollector: Rakowski, Peter
DataCollector: Rieckh, Helene
DataCollector: Schmidt, Marten
DataCollector: Wypler, Norbert
DataCollector: Zindler, Nico
DataManager: Moritz, Ute
DataManager: Verch, Gernot
DataManager: Völker, Lidia
ContactPerson: Sommer, Michael
DataCurator: Meier, Kristin
HostingInstitution: Leibniz Centre for Agricultural Landscape Research (ZALF)

Longterm effects of different mineral and organic fertilizer and soil cultivation on the yield in a crop rotation (Northeast Germany)10.4228/ZALF.DK.63DedelowShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0

​Verch, Gernot

The data set contains yield data from a longterm field experiment. Thetreatments were tillage (ploughing/no-ploughing), mineral nitrogenfertiliser (70/120 kg N/ha a ) and organic fertiliser (100 t to 150t/ha acattle slurry). The crop rotation were sugar beet-springbarley-potato-winter wheat (1981-1990) and sugar beet-winter wheat-maize-triticale (1991-2001).
Verch, Gernot (2020) Longterm effects of different mineral and organic fertilizer and soil cultivation on the yield in a crop rotation (Northeast Germany). Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.63

​DataCollector: Verch, Gernot (ZALF, Müncheberg (Germany), GRID: 433014.1)
ContactPerson: Verch, Gernot (ZALF, Müncheberg (Germany), GRID: 433014.1)
HostingInstitution: Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany), GRID: 433014.1

Data on the effect of cultivars and irrigation on soybean yield and rotational effects10.4228/ZALF.DK.103Site Muencheberg, GermanyShowOnMapView sample dataDownload complete datasetCreative Commons Attribution 4.0
Abstract: This data set reports measurements and observations from a soybean cropping system experiment (2015-2018) investigating the effects of cultivars and irrigation on soybean yield and rotational effects on a subsequent cereal crop. The objective was to design novel soybean-supported cropping systems in north-eastern Germany. The data supports agronomic analyses, as well as dynamic simulation modelling and includes details on crop growth, soil characteristics and weather. In the first part of the experiment different soybean cultivars and the effect of irrigation were compared in a split block design with six replicates and the factors cultivar and irrigation during three consecutive years (2015-2017). The treatments included with and without irrigation and three early maturing soybean cultivars of maturity group 000 (cv. Merlin and cv. Sultana for feed use and cv. Protibus for human food use). Buckwheat and Narrow-leafed lupin (cv. Probor) were cultivated as references. Seeds were inoculated with HISTICK® soybean (BASF, Germany). Measurements included whole plant biomass, grain yield, one thousand seed weigh, macro nutrients (N, P, K) in the biomass and grain, and additional agronomic observations including number of plants and plant phenology. Irrigation water was applied with a sprinkler system using the Web-BEREST model (Mirschel et al., 2014) to determine the amounts and timing (data on the amounts and dates are provided). In the second part of the experiment, the pre-crop effect of soybean (without cover crop), narrow-leafed lupin (followed by turnip rape as a cover crop), and buckwheat (without cover crop) was tested on the grain yield and nutrient content in the following oat crop and on the nitrogen dynamics in the soil. Before winter (November) and in the subsequent spring (March), mineral nitrogen was measured in the soil at three depths (0-30 cm, 30-60 cm, and 60-90 cm) after the different pre-crops. A spring oat was established following the different pre-crops with 6 replicates during three consecutive years (2016-2018).
Reckling, Moritz; Rosner, Gunhild (2019) Data on the effect of cultivars and irrigation on soybean yield and rotational effects. Leibniz Centre for Agricultural Landscape Research (ZALF) https://www.doi.org/10.4228/ZALF.DK.103

​IsSupplementedBy DOI: https://doi.org/10.4228/ZALF.DK.105 (Weather data 2018 Muencheberg)
IsSupplementedBy DOI: https://doi.org/10.4228/ZALF.DK.104 (Weather data 2017 Muencheberg)
IsSupplementedBy DOI: https://doi.org/10.4228/ZALF.2016.331 (Weather data 2016 Muencheberg)
IsSupplementedBy DOI: https://doi.org/10.4228/ZALF.2015.330 (Weather data 2015 Muencheberg)
Documents DOI: https://doi.org/10.1016/j.eja.2019.125951 (Re-designing organic grain legume cropping systems using systems agronomy)

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