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Large amounts of carbon flow through tropical ecosystems every year, from which a part is sequestered in biomass through tree growth. However, the effects of ongoing warming and drying on tree growth and carbon sequestration in tropical forest is still highly uncertain. Field observations are sparse and limited to a few sites, while remote sensing analysis shows diverging growth responses to past droughts that cannot be interpreted with confidence. To reconcile data from field observations and remote sensing, we collated in situ measurements of stem growth and leaf litterfall from inventory plots across the Amazon region and other neotropical ecosystems. These data were used to train two machine-learning models and to evaluate model performance on reproducing stem growth and litterfall rates. The models utilized multiple climatological variables and other geospatial datasets (terrain, soil and vegetation properties) as explanatory variables. The output consisted of monthly estimates of leaf litterfall (R2= 0.71, NRMSE = 9.4 %) and stem growth (R2= 0.54, NRMSE = 10.6 %) across the neotropics from 1982 to 2019 at a high spatial resolution (0.1 ∘). Modelled time series allow us to assess the impacts of the 2005 and 2015 droughts in the Amazon basin on regional scales. The more severe 2015 drought was estimated to have caused widespread declines in stem growth (- 1.8 σ), coinciding with enhanced leaf fall (+ 1.4 σ), which were only locally apparent in 2005. Regions in the Amazon basin that flushed leaves at the onset of both droughts (+ 0.9 σ∼+ 2.0 σ) showed positive anomalies in remotely sensed enhanced vegetation index, while sun-induced fluorescence and vegetation optical depth were reduced. The previously observed counterintuitive response of canopy green-up during drought in the Amazon basin detected by many remote sensing analyses can therefore be a result of enhanced leaf flushing at the onset of a drought. The long-term estimates of leaf litterfall and stem growth point to a decline in stem growth and a simultaneous increase in leaf litterfall in the Amazon basin since 1982. These trends are associated with increased warming and drying of the Amazonian climate and could point to a further decline in the Amazon carbon sink strength. [ABSTRACT FROM AUTHOR]

Abstract: The ecological consequences of climate change for large tropical forests such as the Amazon are likely to be profound. Amazonian forests strongly influence regional and global climates and therefore any changes in forest structure, such as deforestation or die-back, may create positive feedback on externally forced climate change. Monitoring, modelling and managing the impacts of anthropogenic climate change on forest dynamics is therefore an important objective of forest researchers, and one that requires long-term data on changes at the level of community, populations and phenotypes. In this paper we provide the most comprehensive study yet on the seasonal dynamics of various leaf traits: leaf area index (LAI), leaf mortality (LM), leaf biomass (LB), leaf growth rate (LG), and leaf residence time (TR) from 50 experimental plots in a forest site at Belterra, Pará State, Brazil. From this study we estimate annual mean leaf area index (LAI) to be 5.07m2 m−2 and annual mean leaf dry biomass to be 0.621kgm−2. The typical leaf grew at 0.049kgm−2 month−1 and remained on the tree for 12.7 months. We compare these results to other similar studies and critically discuss the factors driving leaf demographics in Amazonia. [Copyright &y& Elsevier]