‘Water potential’ is the biophysically relevant measure of water status in vegetation relating to stomatal, canopy and hydraulic conductance, as well as mortality thresholds; yet, this cannot be directly related to measured and modelled fluxes of water at plot‐ to landscape‐scale without understanding its relationship with ‘water content’. The capacity for detecting vegetation water content via microwave remote sensing further...

Understanding the effects of intensification of Amazon basin hydrological cycling—manifest as increasingly frequent floods and droughts—on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest “tipping points”. Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 20...

Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil‐plant‐atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree respon...

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land‐atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat ( H ), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia—along the equator from the Caxiuanã and Tapajós N...

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models ( ESM s). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that requi...

Gross ecosystem productivity ( GEP ) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance‐derived GEP in a central Amazon evergreen forest into two main causes: variation in environm...

To predict forest response to long‐term climate change with high confidence requires that dynamic global vegetation models ( DGVM s) be successfully tested against ecosystem response to short‐term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry‐season intensities and lengths, to determine how well...

Understanding the processes that determine above‐ground biomass ( AGB ) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models ( DGVM s). AGB is determined by inputs from woody productivity [woody net primary productivity ( NPP )] and the rate at which carbon is lost through tree mortality. Here, we test whet...

Determining climate change feedbacks from tropical rainforests requires an understanding of how carbon gain through photosynthesis and loss through respiration will be altered. One of the key changes that tropical rainforests may experience under future climate change scenarios is reduced soil moisture availability. In this study we examine if and how both leaf photosynthesis and leaf dark respiration acclimate following more...