Asymmetric response of Amazon forest water and energy fluxes to wet and dry hydrological extremes reveals onset of a local drought-induced tipping point.

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 2001-2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015-2016 El Niño drought and La Niña 2008-2009 wet events. We found that the forest responded strongly to El Niño-Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration (ET) leading to large increases in sensible heat fluxes (H). Partitioning ET by an approach that assumes transpiration (T) is proportional to photosynthesis, we found that water stress-induced reductions in canopy conductance (Gs ) drove T declines partly compensated by higher evaporation (E). By contrast, the abnormally wet La Niña period gave higher T and lower E, with little change in seasonal ET. Both El Niño-Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet-season leaf area index. However, only during El Niño 2015-2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown of Gs and significant leaf shedding). Drought-reduced T and Gs , higher H and E, amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post-drought. Identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin-scale threshold-crossing changes in forest energy and water cycling, leading to slow-down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states.

Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests.

In evergreen tropical forests, the extent, magnitude, and controls on photosynthetic seasonality are poorly resolved and inadequately represented in Earth system models. Combining camera observations with ecosystem carbon dioxide fluxes at forests across rainfall gradients in Amazônia, we show that aggregate canopy phenology, not seasonality of climate drivers, is the primary cause of photosynthetic seasonality in these forests. Specifically, synchronization of new leaf growth with dry season litterfall shifts canopy composition toward younger, more light-use efficient leaves, explaining large seasonal increases (~27%) in ecosystem photosynthesis. Coordinated leaf development and demography thus reconcile seemingly disparate observations at different scales and indicate that accounting for leaf-level phenology is critical for accurately simulating ecosystem-scale responses to climate change.