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Cited by 814

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Crop and pasture response to climate change

Open access
Tubiello, Francesco N., Soussana, Jean-François, Howden, S. Mark·2007·Proceedings of the National Academy of Sciences

Abstract

We review recent research of importance to understanding crop and pasture plant species response to climate change. Topics include plant response to elevated CO 2 concentration, interactions with climate change variables and air pollutants, impacts of increased climate variability and frequency of extreme events, the role of weeds and pests, disease and animal health, issues in biodiversity, and vulnerability of soil carbon pools. We critically analyze the links between fundamental knowledge at the plant and plot level and the additional socio-economic variables that determine actual production and trade of food at regional to global scales. We conclude by making recommendations for current and future research needs, with a focus on continued and improved integration of experimental and modeling efforts.

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Registry

Crossref · 10.1073/pnas.0701728104

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Metadata

Authors
Tubiello, F. N., Soussana, J.-F., & Howden, S. M.
Venue
Proceedings of the National Academy of Sciences
Published
2007-12-11
Volume
104
Issue
50
Pages
19686-19690
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2167654997
Cited by
814
References
3
FWCI
30.97
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Crop and pasture response to climate change. https://app.cochat.ai/papers/10.1073/pnas.0701728104
The paper
Tubiello, F. N., Soussana, J.-F., & Howden, S. M. (2007). Crop and pasture response to climate change. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0701728104

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.