Leaf phenology in the humid tropics largely regulates the seasonality of forest carbon and water exchange. However, it is inadequately represented in most global land surface models due to limited understanding of its controls. Based on intensive field studies at four Amazonian evergreen forests, we propose a novel, quantitative representation of tropical forest leaf phenology, which links multiple environmental variables with the seasonality of new leaf production and old leaf litterfall. The new phenology simulates higher rates of leaf turnover (new leaves replacing old leaves) in dry seasons with more sunlight, which is then implemented in ORCHIDEE, together with recent findings of ontogeny‐associated photosynthetic capacity, and is evaluated against ground‐based measurements of leaf phenology (canopy leaf area index and litterfall), eddy covariance fluxes (photosynthesis and latent heat), and carbon allocations from field observations. Results show the periodical cycles of solar radiation and vapor pressure deficit are the two most important environmental variables that are empirically related to new leaf production and old leaf abscission in tropical evergreen forests. The model with new representation of leaf phenology captures the seasonality of canopy photosynthesis at three out of four sites, as well as the seasonality of litterfall, latent heat, and light use efficiency of photosynthesis at all tested sites, and improves the seasonality of carbon allocations to leaves, roots, and sapwoods. This study advances understanding of the environmental controls on tropical leaf phenology and offers an improved modeling tool for gridded simulations of interannual CO₂ and water fluxes in the tropics.

Relationships among productivity, leaf phenology, and seasonal variation in moisture and light availability are poorly understood for evergreen broadleaved tropical/subtropical forests, which contribute 25% of terrestrial productivity. On the one hand, as moisture availability declines, trees shed leaves to reduce transpiration and the risk of hydraulic failure. On the other hand, increases in light availability promote the replacement of senescent leaves to increase productivity. Here, we provide a comprehensive framework that relates the seasonality of climate, leaf abscission, and leaf productivity across the evergreen broadleaved tropical/subtropical forest biome. The seasonal correlation between rainfall and light availability varies from strongly negative to strongly positive across the tropics and maps onto the seasonal correlation between litterfall mass and productivity for 68 forests. Where rainfall and light covary positively, litterfall and productivity also covary positively and are always greater in the wetter sunnier season. Where rainfall and light covary negatively, litterfall and productivity are always greater in the drier and sunnier season if moisture supplies remain adequate; otherwise productivity is smaller in the drier sunnier season. This framework will improve the representation of tropical/subtropical forests in Earth system models and suggests how phenology and productivity will change as climate change alters the seasonality of cloud cover and rainfall across tropical/subtropical forests.

The 2015/16 El Niño brought severe drought and record-breaking temperatures in the tropics. Here, using satellite-based L-band microwave vegetation optical depth, we mapped changes of above-ground biomass (AGB) during the drought and in subsequent years up to 2019. Over more than 60% of drought-affected intact forests, AGB reduced during the drought, except in the wettest part of the central Amazon, where it declined 1 y later. By the end of 2019, only 40% of AGB reduced intact forests had fully recovered to the predrought level. Using random-forest models, we found that the magnitude of AGB losses during the drought was mainly associated with regionally distinct patterns of soil water deficits and soil clay content. For the AGB recovery, we found strong influences of AGB losses during the drought and of γ . γ is a parameter related to canopy structure and is defined as the ratio of two relative height (RH) metrics of Geoscience Laser Altimeter System (GLAS) waveform data—RH25 (25% energy return height) and RH100 (100% energy return height; i.e., top canopy height). A high γ may reflect forests with a tall understory, thick and closed canopy, and/or without degradation. Such forests with a high γ ( γ ≥ 0.3) appear to have a stronger capacity to recover than low- γ ones. Our results highlight the importance of forest structure when predicting the consequences of future drought stress in the tropics.

Amazonian evergreen forests show distinct canopy phenology and photosynthetic seasonality but the climatic triggers are not well understood. This imposes a challenge for modeling leaf phenology and photosynthesis seasonality in land surface models (LSMs) across Amazonian evergreen forest biome. On continental scale, we tested two climatic triggers suggested by site observations, vapor pressure deficit (VPD), and short‐wave incoming radiation (SW) for defining leaf shedding and incorporated VPD‐ and SW‐triggered new canopy phenology modules in the ORCHIDEE LSM (hereafter VPD‐AP and SW‐AP versions). Our results show that both VPD and SW are plausible precursors of large scale litterfall seasonality across the basin by comparing againstin situdata from 14 sites. Specially, both VPD‐AP and SW‐AP correctly capture the increases in litterfall during the early dry season, followed by a flush of new leaves with increasing photosynthetic rates during the later dry season. The VPD‐AP version performs better than the SW‐AP version in capturing a dry‐season increase of photosynthesis across the wet Amazonia areas where mean annual precipitation exceeds 2,000 mm yr⁻¹, consistent with previous satellite data analysis. Both VPD‐AP and SW‐AP model versions perform well in northern, central and southern Amazon regions where the SW seasonality is unimodal, but miss the seasonality of satellite GPP proxies in the eastern region off the coast of Guyana shield where SW seasonality is bimodal. Our findings imply that atmospheric dryness and sunlight availability likely explain the seasonality of leaf shedding and leaf flush processes, respectively, and consequently control canopy photosynthesis in Amazonian evergreen forests.