@phdthesis{Kersebaum2004,
  author    = {Kersebaum, Kurt-Christian},
  title     = {Modellierung der Stickstoffdynamik in Agrar{\"o}kosystemen : ein Instrument zur Beratung und Beurteilung von Nutzungs- und Bewirtschaftungseffekten f{\"u}r Land- und Wasserwirtschaft},
  address   = {Potsdam},
  pages     = {getr. Z{\"a}hlung},
  year      = {2004},
  language  = {de}
}
@article{WernerWernerWielandetal.2014,
  author    = {Werner, Andrea and Werner, Andreas and Wieland, Ralf and Kersebaum, Kurt-Christian and Mirschel, Wilfried and Ende, Hans-Peter and Wiggering, Hubert},
  title     = {Ex ante assessment of crop rotations focusing on energy crops using a multi-attribute decision-making method},
  series = {Ecological indicators : integrating monitoring, assessment and management},
  volume    = {45},
  journal   = {Ecological indicators : integrating monitoring, assessment and management},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {1470-160X},
  doi       = {10.1016/j.ecolind.2014.03.013},
  pages     = {110 -- 122},
  year      = {2014},
  abstract  = {The cultivation of plants for use as energy resources is an agricultural and industrial sector with potentially synergistic benefits related to protecting the environment and generating income. Against the background of increasing land-use changes and new agricultural approaches to the production of energy crops, we present a method for identifying future-oriented crop rotations that supports both the economic and environmental components of decision-making strategies with respect to agriculture-related policy decisions (regional mission statements). The conflicting aspects of these objectives can be addressed with the analytic hierarchy process (AHP), a multi-attribute decision-making method that was integrated here. Three models are used to generate simulations of the defined objectives over a planning period of 30 years under the current climate scenario and provide input data for the multi-attribute assessment of several crop rotations. Based on the entire evaluation process, dimensionless global priority vectors are used to indicate how well the crop rotations meet the requirements of the defined mission statement. The method is tested in a municipality in NE Germany. (C) 2014 Elsevier Ltd. All rights reserved.},
  language  = {en}
}
@misc{SchmidtJochheimKersebaumetal.2017,
  author    = {Schmidt, Martin and Jochheim, Hubert and Kersebaum, Kurt-Christian and Lischeid, Gunnar and Nendel, Claas},
  title     = {Gradients of microclimate, carbon and nitrogen in transition zones of fragmented landscapes - a review},
  series = {Agricultural and forest meteorology},
  volume    = {232},
  journal   = {Agricultural and forest meteorology},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0168-1923},
  doi       = {10.1016/j.agrformet.2016.10.022},
  pages     = {659 -- 671},
  year      = {2017},
  abstract  = {Fragmentation of landscapes creates a transition zone in between natural habitats or different kinds of land use. In forested and agricultural landscapes with transition zones, microclimate and matter cycling are markedly altered. This probably accelerates and is intensified by global warming. However, there is no consensus on defining transition zones and quantifying relevant variables for microclimate and matter cycling across disciplines. This article is an attempt to a) revise definitions and offer a framework for quantitative ecologists, b) review the literature on microclimate and matter cycling in transition zones and c) summarise this information using meta-analysis to better understand bio-geochemical and bio-geophysical processes and their spatial extent in transition zones. We expect altered conditions in soils of transition zones to be 10-20 m with a maximum of 50 m, and 25-50 m for above-ground space with a maximum of 125 m.},
  language  = {en}
}
@article{GrohDiamantopoulosDuanetal.2022,
  author    = {Groh, Jannis and Diamantopoulos, Efstathios and Duan, Xiaohong and Ewert, Frank and Heinlein, Florian and Herbst, Michael and Holbak, Maja and Kamali, Bahareh and Kersebaum, Kurt-Christian and Kuhnert, Matthias and Nendel, Claas and Priesack, Eckart and Steidl, J{\"o}rg and Sommer, Michael and P{\"u}tz, Thomas and Vanderborght, Jan and Vereecken, Harry and Wallor, Evelyn and Weber, Tobias K. D. and Wegehenkel, Martin and Weiherm{\"u}ller, Lutz and Gerke, Horst H.},
  title     = {Same soil, different climate: Crop model intercomparison on translocated lysimeters},
  series = {Vadose zone journal},
  volume    = {21},
  journal   = {Vadose zone journal},
  number    = {4},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1539-1663},
  doi       = {10.1002/vzj2.20202},
  pages     = {25},
  year      = {2022},
  abstract  = {Crop model intercomparison studies have mostly focused on the assessment of predictive capabilities for crop development using weather and basic soil data from the same location. Still challenging is the model performance when considering complex interrelations between soil and crop dynamics under a changing climate. The objective of this study was to test the agronomic crop and environmental flux-related performance of a set of crop models. The aim was to predict weighing lysimeter-based crop (i.e., agronomic) and water-related flux or state data (i.e., environmental) obtained for the same soil monoliths that were taken from their original environment and translocated to regions with different climatic conditions, after model calibration at the original site. Eleven models were deployed in the study. The lysimeter data (2014-2018) were from the Dedelow (Dd), Bad Lauchstadt (BL), and Selhausen (Se) sites of the TERENO (TERrestrial ENvironmental Observatories) SOILCan network. Soil monoliths from Dd were transferred to the drier and warmer BL site and the wetter and warmer Se site, which allowed a comparison of similar soil and crop under varying climatic conditions. The model parameters were calibrated using an identical set of crop- and soil-related data from Dd. Environmental fluxes and crop growth of Dd soil were predicted for conditions at BL and Se sites using the calibrated models. The comparison of predicted and measured data of Dd lysimeters at BL and Se revealed differences among models. At site BL, the crop models predicted agronomic and environmental components similarly well. Model performance values indicate that the environmental components at site Se were better predicted than agronomic ones. The multi-model mean was for most observations the better predictor compared with those of individual models. For Se site conditions, crop models failed to predict site-specific crop development indicating that climatic conditions (i.e., heat stress) were outside the range of variation in the data sets considered for model calibration. For improving predictive ability of crop models (i.e., productivity and fluxes), more attention should be paid to soil-related data (i.e., water fluxes and system states) when simulating soil-crop-climate interrelations in changing climatic conditions.},
  language  = {en}
}