Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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The Global Gridded Crop Model Intercomparison phase 1 simulation dataset
Müller, Christoph ; Elliott, Joshua ; Kelly, David ; Arneth, Almut ; Balkovic, Juraj ; Ciais, Philippe ; Deryng, Delphine ; Folberth, Christian ; Hoek, Steven ; Izaurralde, Roberto C. ; Jones, Curtis D. ; Khabarov, Nikolay ; Lawrence, Peter ; Liu, Wenfeng ; Olin, Stefan ; Pugh, Thomas A.M. ; Reddy, Ashwan ; Rosenzweig, Cynthia ; Ruane, Alex C. ; Sakurai, Gen ; Schmid, Erwin ; Skalsky, Rastislav ; Wang, Xuhui ; Wit, Allard de; Yang, Hong - \ 2019
Scientific Data 6 (2019). - ISSN 2052-4463 - 22 p.

The Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset of the Agricultural Model Intercomparison and Improvement Project (AgMIP) provides an unprecedentedly large dataset of crop model simulations covering the global ice-free land surface. The dataset consists of annual data fields at a spatial resolution of 0.5 arc-degree longitude and latitude. Fourteen crop modeling groups provided output for up to 11 historical input datasets spanning 1901 to 2012, and for up to three different management harmonization levels. Each group submitted data for up to 15 different crops and for up to 14 output variables. All simulations were conducted for purely rainfed and near-perfectly irrigated conditions on all land areas irrespective of whether the crop or irrigation system is currently used there. With the publication of the GGCMI phase 1 dataset we aim to promote further analyses and understanding of crop model performance, potential relationships between productivity and environmental impacts, and insights on how to further improve global gridded crop model frameworks. We describe dataset characteristics and individual model setup narratives.

State-of-the-art global models underestimate impacts from climate extremes
Schewe, Jacob ; Gosling, Simon N. ; Reyer, Christopher ; Zhao, Fang ; Ciais, Philippe ; Elliott, Joshua ; Francois, Louis ; Huber, Veronika ; Lotze, Heike K. ; Seneviratne, Sonia I. ; Vliet, Michelle T.H. Van; Vautard, Robert ; Wada, Yoshihide ; Breuer, Lutz ; Büchner, Matthias ; Carozza, David A. ; Chang, Jinfeng ; Coll, Marta ; Deryng, Delphine ; Wit, Allard De; Eddy, Tyler D. ; Folberth, Christian ; Frieler, Katja ; Friend, Andrew D. ; Gerten, Dieter ; Gudmundsson, Lukas ; Hanasaki, Naota ; Ito, Akihiko ; Khabarov, Nikolay ; Kim, Hyungjun ; Lawrence, Peter ; Morfopoulos, Catherine ; Müller, Christoph ; Müller Schmied, Hannes ; Orth, René ; Ostberg, Sebastian ; Pokhrel, Yadu ; Pugh, Thomas A.M. ; Sakurai, Gen ; Satoh, Yusuke ; Schmid, Erwin ; Stacke, Tobias ; Steenbeek, Jeroen ; Steinkamp, Jörg ; Tang, Qiuhong ; Tian, Hanqin ; Tittensor, Derek P. ; Volkholz, Jan ; Wang, Xuhui ; Warszawski, Lila - \ 2019
Nature Communications 10 (2019). - ISSN 2041-1723
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
Global gridded crop model evaluation : Benchmarking, skills, deficiencies and implications
Müller, Christoph ; Elliott, Joshua ; Chryssanthacopoulos, James ; Arneth, Almut ; Balkovic, Juraj ; Ciais, Philippe ; Deryng, Delphine ; Folberth, Christian ; Glotter, Michael ; Hoek, Steven ; Iizumi, Toshichika ; Izaurralde, Roberto C. ; Jones, Curtis ; Khabarov, Nikolay ; Lawrence, Peter ; Liu, Wenfeng ; Olin, Stefan ; Pugh, Thomas A.M. ; Ray, Deepak K. ; Reddy, Ashwan ; Rosenzweig, Cynthia ; Ruane, Alex C. ; Sakurai, Gen ; Schmid, Erwin ; Skalsky, Rastislav ; Song, Carol X. ; Wang, Xuhui ; Wit, Allard De; Yang, Hong - \ 2017
Geoscientific Model Development 10 (2017)4. - ISSN 1991-959X - p. 1403 - 1422.
Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.
Twenty Years of Brassinosteroids : Steroidal Plant Hormones Warrant Better Crops for the XXI Century
Khripach, V. ; Zhabinskii, V. ; Groot, C.P.G.M. de - \ 2000
Annals of Botany 86 (2000)3. - ISSN 0305-7364 - p. 441 - 447.
The discovery of brassinosteroids (BS) just over 20 years ago opened a new era in studies of bio-regulation in living organisms. Previously, the only known role of steroids as hormones was in animals and fungi; now a steroidal hormone in plants had been added. Progress in brassinosteroid research has been very rapid. Only 20 years passed between the discovery of brassinolide, the first member of the series, and the application of brassinosteroids in agriculture. Although the other plant hormones have been studied for a much longer period, there has not been similar development. Within the last couple of years two books on brassinosteroids (Khripach VA, Zhabinskii VN, de Groot A. 1999. Brassinosteroids—a new class of plant hormones. San Diego: Academic Press; Sakurai A, Yokota T, Clouse SD, eds. 1999. Brassinosteroids: steroidal plant hormones. Tokyo: Springer Verlag) have been published, but many new data have appeared since that time. Many of the more recent data is devoted to molecular biological aspects of BS and has helped to create a vision of their role in plants and their mechanisms of action. New discoveries of the physiological properties of BS allow us to consider them as highly promising, environmentally-friendly, natural substances suitable for wide application in plant protection and yield promotion in agriculture. This aspect of BS is the main subject of this Botanical Briefing
Cytochemical and histochemical characterization of cotyledonary bodies from Pharbitis nil seedlings.
Tretyn, A. ; Kendrick, R.E. ; Fujioka, S. ; Sakurai, A. - \ 1996
Protoplasma 191 (1996). - ISSN 0033-183X - p. 205 - 214.
The relationship between lung function, dust exposure and endotoxin exposure in animal feed workers.
Heederik, D. ; Smid, T. - \ 1990
In: Occupational epidemiology / Sakurai, H., Amsterdam : Elsevier Science - p. 161 - 164.
Comparison of the performance of two general job-exposure matrices using the same set of data.
Kromhout, H. ; Heederik, D. - \ 1990
In: Occupational epidemiology / Sakurai, H., Amsterdam : Elsevier Science - p. 43 - 46.
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