Despite early speculation to the contrary, all tropical forests studied to date display seasonal variations in the presence of new leaves, flowers, and fruits. Past studies were focused on the timing of phenological events and their cues but not on the accompanying changes in leaf area that regulate vegetation-atmosphere exchanges of energy, momentum, and mass. Here we report, from analysis of 5 years of recent satellite data, seasonal swings in green leaf area of Ϸ25% in a majority of the Amazon rainforests. This seasonal cycle is timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of net leaf flushing during the early to mid part of the light-rich dry season and net leaf abscission during the cloudy wet season. These seasonal swings in leaf area may be critical to initiation of the transition from dry to wet season, seasonal carbon balance between photosynthetic gains and respiratory losses, and litterfall nutrient cycling in moist tropical forests.remote sensing ͉ tropical forests phenology ͉ vegetation climate interaction T he trees of tropical rainforests are known to exhibit a range of phenological behavior, from episodes of ephemeral leaf bursts followed by long quiescent periods to continuous leafing, and from complete intraspecific synchrony to complete asynchrony (1). Several agents (e.g., herbivory, water stress, day length, light intensity, mineral nutrition, and flood pulse) have been identified as proximate cues for leafing and abscission in these communities (1-8). These studies were focused on the timing of phenological events but not on the accompanying changes in leaf area. Leaves selectively absorb solar radiation, emit longwave radiation and volatile organic compounds, and facilitate growth by regulating carbon dioxide influx and water vapor efflux from stomates. Therefore, leaf area dynamics are relevant to studies of climatic, hydrological, and biogeochemical cycles.The sheer size and diversity of rainforests preclude a synoptic view of leaf area changes from ground sampling. We therefore used data on green leaf area of the Amazon basin (Ϸ7.2 ϫ 10 6 km 2 ) derived from measurements made by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Na- Results Seasonality in LAI Time Series.Leaf area data for the Amazon rainforests exhibit notable seasonality, with an amplitude (peakto-trough difference) that is 25% of the average annual LAI of 4.7 (Fig. 1A). This average amplitude of 1.2 LAI is about twice the error of a single estimate of MODIS LAI, and thus is not an artifact of remote observation or data processing (see SI Materials and Methods). The aggregate phenological cycle appears timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of leaf flushing and abscission. These patterns result in leaf area leading solar radiation during the entire seasonal cycle, with higher leaf area during the shorter dry season when solar radiation loads are hig...

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Scatterometers have provided continuous synoptic microwave radar coverage of the Earth from space for nearly a decade. NASA launched three scatterometers: the current SeaWinds scatterometer onboard QuikSCAT (QSCAT, 13.4 GHz) launched in 1999; the NASA scatterometer (NSCAT, 14.0 GHz), which flew on the Japanese Space Agency's ADEOS‐1 platform during 1996–1997; and the Seasat‐A scatterometer system (SASS, 14.6 GHz), which flew in 1978. The European Space Agency's (ESA) 5.3‐GHz scatterometer (ESCAT) has been carried onboard both the ERS‐1 and ERS‐2 satellites since 1991. properties, including the phase state, of a particular surface type. Varying response from the surface also results from different polarizations, viewing angles and orientations, and radar frequencies. The wide swath of scatterometers provides near daily global coverage at intrinsic sensor resolutions that are generally between 25–50 km.

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Abstract. We use a general ecosystem process model (BIOME-BGC) coupled with remote sensing information to evaluate the sensitivity of boreal forest regional evapotranspiration (ET) and net primary production (NPP) to land cover spatial scale. Simulations were conducted over a 3 year period (1994)(1995)(1996) d-•). Factors responsible for differences in scaling behavior between ET and NPPincluded compensating errors for ET calculations and boreal forest spatial and temporal NPP complexity. Careful consideration of landscape spatial and temporal heterogeneity is necessary to identify and mitigate potential error sources when using plot scale information to understand regional scale patterns. Remote sensing data integrated within an ecological process model framework provides an efficient mechanism to evaluate scaling behavior, interpret patterns in coarse resolution data, and identify appropriate scales of operation for various processes. IntroductionThe boreal forest has received increasing attention from the scientific community in recent years because of its importance as a major reservoir of the world's carbon and mounting evi-