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Global vegetation productivity response to climatic oscillations during the satellite era.

Authors :
Gonsamo, Alemu
Chen, Jing M.
Lombardozzi, Danica
Source :
Global Change Biology. Oct2016, Vol. 22 Issue 10, p3414-3426. 13p.
Publication Year :
2016

Abstract

Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30 years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño-Southern Oscillation ( ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global-scale vegetation productivity than previously thought, although continental-scale responses are substantial. There is also clear evidence that other non- ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model ( CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13541013
Volume :
22
Issue :
10
Database :
Academic Search Index
Journal :
Global Change Biology
Publication Type :
Academic Journal
Accession number :
117745953
Full Text :
https://doi.org/10.1111/gcb.13258