title: Vegetation dynamics and rainfall sensitivity of the Amazon.
abstract: We show that the vegetation canopy of the Amazon rainforest is highly sensitive to changes in precipitation patterns and that reduction in rainfall since 2000 has diminished vegetation greenness across large parts of Amazonia. Large-scale directional declines in vegetation greenness may indicate decreases in carbon uptake and substantial changes in the energy balance of the Amazon. We use improved estimates of surface reflectance from satellite data to show a close link between reductions in annual precipitation, El Niño southern oscillation events, and photosynthetic activity across tropical and subtropical Amazonia. We report that, since the year 2000, precipitation has declined across 69% of the tropical evergreen forest (5.4 million km(2)) and across 80% of the subtropical grasslands (3.3 million km(2)). These reductions, which coincided with a decline in terrestrial water storage, account for about 55% of a satellite-observed widespread decline in the normalized difference vegetation index (NDVI). During El Niño events, NDVI was reduced about 16.6% across an area of up to 1.6 million km(2) compared with average conditions. Several global circulation models suggest that a rise in equatorial sea surface temperature and related displacement of the intertropical convergence zone could lead to considerable drying of tropical forests in the 21st century. Our results provide evidence that persistent drying could degrade Amazonian forest canopies, which would have cascading effects on global carbon and climate dynamics.
authors.affiliation: College of Forestry, Corvallis, OR 97331; thomas.hilker@oregonstate.edu.
authors.forename: Thomas
authors.initials: T
authors.lastname: Hilker
authors.affiliation: Goddard Space Flight Center, NASA, Greenbelt, MD 20771;
authors.forename: Alexei I
authors.initials: AI
authors.lastname: Lyapustin
authors.affiliation: Goddard Space Flight Center, NASA, Greenbelt, MD 20771;
authors.forename: Compton J
authors.initials: CJ
authors.lastname: Tucker
authors.affiliation: Goddard Space Flight Center, NASA, Greenbelt, MD 20771; Joint Center for Earth System Technology, University of Maryland Baltimore County, Baltimore, MD 21228;
authors.forename: Forrest G
authors.initials: FG
authors.lastname: Hall
authors.affiliation: Department of Earth and Environment, Boston University, Boston, MA 02215; and.
authors.forename: Ranga B
authors.initials: RB
authors.lastname: Myneni
authors.affiliation: Goddard Space Flight Center, NASA, Greenbelt, MD 20771; Joint Center for Earth System Technology, University of Maryland Baltimore County, Baltimore, MD 21228;
authors.forename: Yujie
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Earth and Environment, Boston University, Boston, MA 02215; and.
authors.forename: Jian
authors.initials: J
authors.lastname: Bi
authors.affiliation: Divisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos, 12245-970 São Paulo State, Brazil.
authors.forename: Yhasmin
authors.initials: Y
authors.lastname: Mendes de Moura
authors.affiliation: Goddard Space Flight Center, NASA, Greenbelt, MD 20771;
authors.forename: Piers J
authors.initials: PJ
authors.lastname: Sellers
mesh_terms: D001938:Brazil; D057231:Climate Change; D065948:Grassland; D008954:Models, Biological; D011891:Rain; D065947:Rainforest
keywords: Amazon; MAIAC; MODIS; NDVI; climate change; precipitation