Claas Nendel (0000-0001-7608-9097)

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Biography

Claas Nendel is co-head of the ZALF Research Area 4 „Simulation & Data Science“, in which he also leads the working group on „Landscape Modelling“. A studied geo-ecologist (University of Technology Carolo-Wilhelmina, Braunschweig, Germany; Agricultural University of Norway, Ås), he received his PhD from Braunschweig in 2002 and qualified for lecturer (Habilitation) at Berlin University of Technology in 2014. Since 2020 he is jointly appointed professor of Landscape Systems Analysis with the University of Potsdam. He has been working for more than 25 years in agricultural research on applied integrated modelling of water, nitrogen and carbon dynamics, organic matter decomposition, crop growth, product quality, pest and disease impact on crops, and farm economics in major agricultural crops. His main focus is the carry-over effect within crop rotations and the consequences for yield and product quality. Prof. Nendel is the principal developer of the MONICA model for biophysical processes in agro-ecosystems, which was established in the context of a national research project on foresight and potentials in rural areas under regional climate change. Prof. Nendel has served as the president of the European Society for Agronomy and is currently spokesman of the German Soil Science Society plant nutrition section and of the German Agricultural Research Alliance (DAFA) 's Climate Change Platform. He hosted the International Crop Modelling Symposium in Berlin in 2016 (320 participants), the German Society of Agronomy meeting in Berlin in 2019 (175 participants), the European Society for Agronomy Congress in Potsdam in 2022 (250 participants) and the DAFA conference on Agriculture under Climate Change in 2024 (500 particpants), and published more than 160 peer-reviewed journal articles, eleven book chapters and more than 250 contributions to national and international conferences.

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University of Potsdam: Potsdam, DE

2020-04-01 to present | Professor of Landscape Systems Analysis (Institute of Biochemistry and Biology)

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Claas Nendel

https://orcid.org/0000-0001-7608-9097

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Biography

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Employment (6)

University of Potsdam: Potsdam, DE

Leibniz Centre for Agricultural Landscape Research: Müncheberg, DE

Global Change Research Institute: Brno, CZ

Leibniz Centre for Agricultural Landscape Research: Müncheberg, DE

Leibniz Institute of Vegetable and Ornamental Crops: Großbeeren, DE

Rhineland-Palatinate State Education and Research Centre for Agriculture, Viticulture and Horticulture: Neustadt an der Weinstraße, DE

Education and qualifications (3)

Technical University of Berlin: Berlin, DE

Technische Universität Braunschweig: Braunschweig, Niedersachsen, DE

Technische Universität Braunschweig: Braunschweig, Niedersachsen, DE

Professional activities (8)

Integrated Research Institute on Transformations of Human-Environment Systems (IRI THESys): Berlin, DE

German Society for Agronomy: Bonn, DE

German Soil Science Society: Göttingen, DE

European Society for Agronomy: Conthey, CH

German Soil Science Society: Göttingen, DE

European Society for Agronomy: Conthey, CH

European Society for Agronomy: Conthey, CH

German Soil Science Society: Göttingen, DE

Works (50 of 145)

Future area expansion outweighs increasing drought risk for soybean in Europe

Effects of temperature on the movement and feeding behaviour of the large lupine beetle, Sitona gressorius

Expected effects of climate change on the production and water use of crop rotation management reproduced by crop model ensemble for Czech Republic sites

Improving the simulation of permanent grasslands across Germany by using multi-objective uncertainty-based calibration of plant-water dynamics

Machine learning in crop yield modelling: A powerful tool, but no surrogate for science

Mapping grassland mowing events across Germany based on combined Sentinel-2 and Landsat 8 time series

Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany

Modeling Intra‐ and Interannual Variability of BVOC Emissions From Maize, Oil‐Seed Rape, and Ryegrass

Probabilistic modeling of crop-yield loss risk under drought: a spatial showcase for sub-Saharan Africa

Estimating the Evaporative Cooling Effect of Irrigation within and above Soybean Canopy

Agricultural Landscapes in Brandenburg, Germany: An Analysis of Characteristics and Spatial Patterns

Biotic Yield Losses in the Southern Amazon, Brazil: Making Use of Smartphone-Assisted Plant Disease Diagnosis Data

Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils

Methodology to assess the changing risk of yield failure due to heat and drought stress under climate change

Performance of 13 crop simulation models and their ensemble for simulating four field crops in Central Europe

Quantifying sustainable intensification of agriculture: The contribution of metrics and modelling

Yield Response of an Ensemble of Potato Crop Models to Elevated CO<sub>2</sub> in Continental Europe

Modelling Agroforestry’s Contributions to People—A Review of Available Models

Mapping Crop Types and Cropping Systems in Nigeria with Sentinel-2 Imagery

Detection and Quantification of Irrigation Water Amounts at 500 m Using Sentinel-1 Surface Soil Moisture

Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China

Corrigendum to “Future yields of double-cropping systems in the Southern Amazon, Brazil, under climate change and technological development” [Agricultural Systems 177 (2020) 102707] (Agricultural Systems (2020) 177, (S0308521X18312617), (10.1016/j.agsy.2019.102707))

Crop growth and soil water fluxes at erosion-affected arable sites: Using weighing lysimeter data for model intercomparison

Future yields of double-cropping systems in the Southern Amazon, Brazil, under climate change and technological development

No perfect storm for crop yield failure in Germany

Testing and Application of the AquaCrop Model for Wheat Production Under Different Field Management Conditions in South-Eastern Australia

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Supplementary material to "Using SHAP to interpret XGBoost predictions of grassland degradation in Xilingol, China"

Using SHAP to interpret XGBoost predictions of grassland degradation in Xilingol, China

Towards national-scale characterization of grassland use intensity from integrated Sentinel-2 and Landsat time series

Why do crop models diverge substantially in climate impact projections? A comprehensive analysis based on eight barley crop models

Sustainable intensification of crop residue exploitation for bioenergy: Opportunities and challenges

Climate change impact and adaptation for wheat protein

Cost-effective prevention of greenhouse gas emissions by means of fertilizer reduction: Site-specific analysis with simulated yield functions,Kosteneffiziente Vermeidung von Treibhausgasemissionen durch Düngereduktion: Standortspezifische Analyse mit simulierten Ertragsfunktionen

Decline in climate resilience of european wheat

Effects of input data aggregation on simulated crop yields in temperate and Mediterranean climates

Estimating the contribution of crop residues to soil organic carbon conservation

Genetic response diversity to provide yield stability of cultivar groups deserves attention

Global wheat production with 1.5 and 2.0°C above pre-industrial warming

Growth and yield response of faba bean to soil moisture regimes and sowing dates: Field experiment and modelling study

Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations

Management and spatial resolution effects on yield and water balance at regional scale in crop models

Simulation of maize evapotranspiration: An inter-comparison among 29 maize models

Identifying drivers of land degradation in Xilingol, China, between 1975 and 2015

Microclimate and matter dynamics in transition zones of forest to arable land

The nitrogen nutrition potential of arable soils

Temporal Sensitivity Analysis of the MONICA Model: Application of Two Global Approaches to Analyze the Dynamics of Parameter Sensitivity

Intra-annual reflectance composites from Sentinel-2 and Landsat for national-scale crop and land cover mapping

Modeling Yields Response to Shading in the Field-to-Forest Transition Zones in Heterogeneous Landscapes

A model-based assessment of the environmental impact of land-use change across scales in Southern Amazonia