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Advances in Meteorology
Volume 2017 (2017), Article ID 2149479, 16 pages
Research Article

Response of South American Terrestrial Ecosystems to Future Patterns of Sea Surface Temperature

1Department of Physics, Federal University of Paraná (UFPR), 81531-990 Curitiba, PR, Brazil
2Department of Agricultural and Environmental Engineering, Federal University of Viçosa (UFV), Av. P. H. Rolfs, s/n, Campus Universitário, 36570-000 Viçosa, MG, Brazil
3Institute of Biological and Health Sciences, Federal University of Alagoas (UFAL), Av. Lourival Melo Mota, s/n, Tabuleiro do Martins, 57072-900 Maceió, AL, Brazil

Correspondence should be addressed to Marcos Paulo Santos Pereira; moc.liamtoh@arierepspsocram

Received 2 December 2016; Revised 20 May 2017; Accepted 31 May 2017; Published 17 July 2017

Academic Editor: Anthony R. Lupo

Copyright © 2017 Marcos Paulo Santos Pereira et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Global warming in the first half of the 21st century is likely to have profound influences on South American vegetation and climate. Although coupled atmosphere-biosphere models have been widely used to forecast future vegetation patterns under various scenarios of global warming, they have not been used to assess the potentially critical role of variations in sea surface temperature (SST) in modifying the climate-vegetation interactions. Here, we use monthly output of a 100-year coupled model run to investigate the relationship between SST, precipitation, and productivity of vegetation. Specifically, we assess statistical correlations between SST variability and vegetation in six different South America regions: Northern South America, Western Amazonia, Eastern Amazonia, Northeast Brazil, Central Brazil, and Patagonia. Our model robustly simulates changes in mean precipitation, net primary production (NPP), upper canopy leaf area index (LAI), and lower canopy LAI under warming and nonwarming scenarios. Most significantly, we demonstrate that spatial-temporal variability in SST exerts a strong influence over the vegetation dynamics in all six South American regions.