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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Record number 317435
Title Simulating the effect of elevated CO2 on crops : approaches and application for climate change
Author(s) Tubiello, F.N.; Ewert, F.
Source European Journal of Agronomy 18 (2002). - ISSN 1161-0301 - p. 57 - 74.
DOI http://dx.doi.org/10.1016/S1161-0301(02)00097-7
Department(s) Plant Production Systems
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2002
Abstract Several crop models may be used to simulate the effects of elevated CO2 on crop productivity. Yet no summary exists in the literature attempting to describe differences among models and how simulations might differ under climate change conditions. We provide an introductory review focusing on simulating the impacts of elevated CO2 on crops. We describe and discuss modeling approaches, component modules, applications to climate change and model validation and inter-comparison studies. By searching the recent peer-reviewed literature from 1995 to present, we found that about 20 f published crop modeling studies have focused on climate change impacts. About half of these studies explicitly analyzed the effects of elevated CO2 on crop growth and yield. Our analysis further suggested that the crop models that have been used the most in climate change assessments are also those that have been evaluated the least using available data from elevated CO2 experiments. Based on our review, we identify a set of recommendations aimed at improving our confidence in predictions of crop production under elevated CO2 and climate change conditions. These include continued model evaluation with existing field experiment data; increased focus on limiting factors such as pest, weeds, and disease; and attention to temporal and spatial scaling issues.
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