Jørgen E. Olesen

Prof. Jørgen E. Olesen

Aarhus University, Department of Agoecology

Research Focus & Metrics

Academic Career Length

43Years (1984-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 December 2014 in Nature Climate Change
Verified
Journal Article
Open access
PDF file
SASenthold Asseng
Senthold Asseng
FEF. Ewert
F. Ewert
PMP. Martre
P. Martre
RRReimund Paul Rötter
Reimund Paul Rötter
DLDavid Lobell
David Lobell
YZY. Zhu
Y. Zhu
This study—based on systematic testing of 30 different wheat crop models against field experiments—shows that many wheat models simulate yields well, but with reduced accuracy at higher temperatures. Extrapolation of the model ensemble response indicates that global wheat production will fall by 6% for each 1 °C increase in temperature. Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.

9 July 2020 in Scientific Data
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Journal Article
Open access
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GPGilberto Pastorello
Gilberto Pastorello
CTCarlo Trotta
Carlo Trotta
ECEleonora Canfora
Eleonora Canfora
HCHousen Chu
Housen Chu
DCDanielle Christianson
Danielle Christianson
DPDario Papale
Dario Papale
The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

9 June 2013 in Nature Climate Change
Verified
Journal Article
Closed access
PDF file
SASenthold Asseng
Senthold Asseng
FEF. Ewert
F. Ewert
CRC. Rosenzweig
C. Rosenzweig
JJJ. W. Jones
J. W. Jones
JHJ. L. Hatfield
J. L. Hatfield
JWJonas Michel Wolf
Jonas Michel Wolf

1 June 2002 in European Journal of Agronomy
Verified
Journal Article
Closed access
JOJørgen E. Olesen
Jørgen E. Olesen
MBMarco Bindi
Marco Bindi

1 February 2011 in European Journal of Agronomy
Verified
Journal Article
Closed access
JOJørgen E. Olesen
Jørgen E. Olesen
Miroslav TrnkaMiroslav Trnka
Miroslav Trnka
KKKurt Christian Kersebaum
Kurt Christian Kersebaum
ASA.O. Skjelvåg
A.O. Skjelvåg
BSB. Seguin
B. Seguin
FMF. Micale
F. Micale

30 August 2019 in Global Change Biology
Verified
Journal Article
Open access
PDF file
PSPete Smith
Pete Smith
JSJean‐Francois Soussana
Jean‐Francois Soussana
DADenis Angers
Denis Angers
LSLouis Schipper
Louis Schipper
CCClaire Chenu
Claire Chenu
KKKatja Klumpp
Katja Klumpp
There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international ‘4p1000’ initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long‐term experiments and space‐for‐time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils.