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The collective analysis of long-term field experiments (LTFEs), here defined as agricultural experiments with a minimum duration of 20 years and research in the context of sustainable soil use and yield, can be used for detecting changes in soil properties and yield such as those induced by climate change. However, information about existing LTFEs is scattered, and the research data are not easily accessible. In this study, meta-information on LTFEs in Germany is compiled and their spatial representation is analyzed. The study is conducted within the framework of the BonaRes project, which, inter alia, has established a central access point for LTFE information and research data. A total of 205 LTFEs which fit to the definition above are identified. Of these, 140 LTFEs are ongoing. The land use in 168 LTFEs is arable field crops, in 34 trials grassland, in 2 trials vegetables and in 1 trial pomiculture. Field crop LTFEs are categorized into fertilization (n=158), tillage (n=38) and crop rotation (n=32 ; multiple nominations possible) experiments, while all grassland experiments (n=34) deal with fertilization. The spatial representation is analyzed according to the climatic water balance of the growing season (1 May to 31 October) (CWBg), the Müncheberg Soil Quality Rating (MSQR) and clay content. The results show that, in general, the LTFEs well represent the area shares of both the CWBg and the MSQR classes. Eighty-nine percent of the arable land and 65 % of the grassland in Germany are covered by the three driest CWBg classes, hosting 89 % and 71 % of the arable and grassland LTFEs, respectively. LTFEs cover all six MSQR classes but with a bias towards the high and very high soil quality classes. LTFEs on arable land are present in all clay content classes according to the European Soil Data Centre (ESDAC) but with a bias towards the clay content class 4. Grassland LTFEs show a bias towards the clay content classes 5, 6 and 7, while well representing the other clay content classes, except clay content class 3, where grassland LTFEs are completely missing. The results confirm the very high potential of LTFE data for spatially differentiated analyses and modeling. However, reuse is restricted by the difficult access to LTFE research data. The common database is an important step in overcoming this restriction. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the applicability of the Soil and Water Assessment Tool (SWAT) to predict streamflow, nitrate loadings and crop yields for a small agricultural catchment in northeastern Germany. To this end, a 167 ha catchment was delineated consisting of 10 hydrological response units. Daily data for streamflow and nitrate loadings from 2004 to 2015 were used to calibrate and validate the model, while annual values for crop yields (winter wheat, winter barley, rapeseed, maize silage) were available. In addition, the detailed field maps provided by the local farmer were used to implement exact crop rotations and nitrogen fertilization into the model. Nash-Sutcliffe-Efficiencies for streamflow were 0.54 during the calibration and 0.57 for the validation period. The modeling performance for nitrate loadings were lower with 0.31 for the calibration and 0.42 for the validation period. The average crop yields were reproduced well, while SWAT failed to reproduce the inter-annual crop yield variations. A scenario analysis revealed that a slight decrease of nitrogen fertilization leads to significant reductions in nitrate loadings, while crop yields remained on a high level. The outcome of the study may help practitioners to operate according to an economic and environmental optimal N management. Nevertheless, experimental studies with varying fertilization intensities at catchment scale are needed to underpin the modeling results. [ABSTRACT FROM AUTHOR]

Based on plot scale experiments and simulations we develop and parameterize the new Agro-Forest Crop Atmosphere Soil System model (AFCASS) within the ecosystem modelling framework Expert-N that combines tree growth and crop respectively grass growth models assuming three different field areas: (i) tree strip area, (ii) transition area between trees and crop/grass and (iii) crop/grass land area to simulate the complete field scale agro-forestry system.The model structure of the new model is presented and discussed. Simulations include light attenuation and plant internal water flow, leaf photosynthesis, plant growth and nutrient uptake for the three different agroforest areas for which also soil organic matter turnover and specific crop residue management is modelled by using the models SOILN and CENTURY and the Expert-N surface litter turnover model adapted to include tree litter: twigs, branches and specific fruits.The model is parameterized and tested using experimental data obtained by sub-projects of the BONARES SIGNAL Project that investigates agro-forestry systems at five different sites within different regions of Germany. It is the aim to study scenarios to analyse possible impacts of various management options (tree & crop area, tree & crop species, crop rotations, harvesting intervals, exposition) on soil and ecosystem properties (biodiversity, C-sequestration, nitrate leaching, soil erosion, plant water availability). [ABSTRACT FROM AUTHOR]

Crop rotation is known from millenia as the one of the best agronomical practice in plant cultivation. Rotation of plant crops is beneficial due to erosion prevention, nutrients retention, and many other factors for soil quality and improvement. Mostly, single catch crops are applied, but the benefits of diverse mixtures of catch crops are not yet clear. A long-term field experiment of the CATCHY project (Catch-cropping as an agrarian tool for continuing soil health and yield-increase) with two contrasting crop rotations was established in two different locations in Northern (Asendorf) and Southern (Triesdorf) Germany. Single catch crops (white mustard, Egyptian clover, phacelia and bristle oat), catch crop mixtures (a mixture of the above and a commercial mixture) and main crops (wheat and maize) have been grown. To investigate how catch crops can affect the microbial diversity and community composition, we were studying first the short-term effect of different catch crop mixtures on the microbiomes associated with soils and roots of the next main crop, maize. Roots, rhizosphere and bulk soils were collected from representative samples of triplicate field plots, including fallow treatments. Changes of the bacterial populations in the bulk soil, rhizosphere soil and root microbiomes of maize were investigated by Illumina Miseq amplicon sequencing of the targeted rRNA, and protein encoding nifH genes. Effects of the cover crop cultivation were compared with fallow soil treatment as control, relative abundance, alpha and beta diversity analyses were performed. [ABSTRACT FROM AUTHOR]