ET (mm/day)

1. Dry season A. 4.5 Model 4.0 ET (mm/day) 3.5 Data B. 3.0 Data GPP (MgC ha-1 month-1) 2.5 2.0 3.0 C. 2.5 Models 25 2.0 2.0 Litterfall(g m-2 day-1) GEP capacity(mol m-2 s-1) 1.5 20 3.0 1.0 4.0 15 0.5 1000 0.8 PAR(mol m-2 s-1) GEP capacity litterfall 500 DifFraction Jan Jan Apr Apr Jul Jul Oct Oct 0.55 0.3 J F M A M J J A S O N D Figure 1. (A) Evapotranspiration (ET) in the equatorial Santarém forest: observed (mean ± SD across years 2002-2004 of eddy fluxes, K67 site, blue shaded area), and modeled by NCAR GCM+CLM3.0 land model with deep roots and hydraulic lift (blue line, Lee et al., 2005), and (B) Gross Primary Productivity (GPP) at the same site: observed (same period as in A, green shaded area) and modeled by modified NCAR CLM3.0 IBIS (blue line) and by IBIS (brown line, Botta et al., 2002). MODIS EVI (average 2000-2004, black squares) is plotted with GPP in (B). Models show dry-season declines, in contrast to observations from both satellite and eddy tower. (C) Mean annual cycle of canopy photosynthetic capacity (observed GPP when PAR ≈ 800 mol m-2 s-1), litterfall rates (plotted with reverse scale), and mean daily photosynthetically active radiation (PAR). (D) LAI (m2 m-2) (from Brando et al., 2010); (E) Components of Above Ground NPP (AGNPP): wood increment (from dendrometers, Rice et al., 2004); leaf flush (derived from litter fall (in C) and LAI (in D) as: Litterfall + d[LAI]/dt; (F) Above-ground Carbon Use Efficiency (AGCUE) (= AGNPP / GPP); (G) diffuse fraction of radiation; (H) deep soil water (Sept-Dec 2009 only) showing deep penetration of drying front. . Figure 2. Seasonal variations in MODIS-derived GPP (Pg), fpar, and EVI, vs.eddy tower Pg in SE Asia tropical forests (MaeKlong Watershed Research Station, Thailand). (Huete et al. 2008) D. E. AGNPP Productivity Wood incr. Figure 3. Spatial variability in annual Amazon rainfall (1998-2006 mean mm month-1from TRMM satellite data, ranging from <100 in orange areas, to >275 in dark blue areas) and tower site locations for this study (left) Leaf flush F. G. H.

2. Figure 4. Soil pit design (left). At right: photo from surface viewing wall of pit (km 67) showing sensor access holes and minirhizotron tubes.See Fig 1H for preliminary soil moisture data. Figure 5. km67 images: (A) Webcam image (courtesy Fernando Santo); and (B) uncalibrated spectral reflectance images from Tetracam 3-band camera system: red (top), NIR (middle), and 2-band Enhanced Vegetation Index (EVI, bottom). A reference white plate is visible in each (allowing future calibration). 091231Red Figure 6.. True-color image of sky conditions (right) captured by a CMOS-based all-sky imaging system at the time indicated by the red arrow in the graph (left) of diurnal variation in global and diffuse PAR. 091231NIR 1.0 0.8 0.6 0.4 0.2 Figure 7. Student Lissandra Souza using Licor-6400 during canopy access campaign for characterizing canopy leaf traits. 0.0 091231EVI 500 1000 1500 2000

3. Fig 8. Photosynthetic light response curves (left) and reflectance hyperspectra for the young and mature leaves of Moracia spp in eastern Amazonia. Young leaves with stronger photosynthetic response (left), also have a stronger “green” peak (~550 nm) and higher reflectance throughout the red regions (680-730nm), giving a distinctly different vegetation index. Young leaf mature leaf Photosynthesis (mol C m-2 s-1) PAR (mol m-2 s-1) Figure 9. FLiES model simulations of absorbed photosynthetically active radiation (APAR) for tropical forest canopy under broken clouds with high diffuse fraction (left) and clear sky conditions (right) for the same solar zenith angle. 2-D variation in APAR for sample vertical slice through canopy is displayed.