Functional relationships between wood density and measures of xylem hydraulic safety and efficiency are ambiguous, especially in wet tropical forests. In this meta‐analysis, we move beyond wood density per se and identify relationships between xylem allocated to fibers, parenchyma, and vessels and measures of hydraulic safety and efficiency. We analyzed published data of xylem traits, hydraulic properties and measures of drought resistance from neotropical tree species retrieved from 346 sources. We found that xylem volume allocation to fiber walls increases embolism resistance, but at the expense of specific conductivity and sapwood capacitance. Xylem volume investment in fiber lumen increases capacitance, while investment in axial parenchyma is associated with higher specific conductivity. Dominant tree taxa from wet forests prioritize xylem allocation to axial parenchyma at the expense of fiber walls, resulting in a low embolism resistance for a given wood density and a high vulnerability to drought‐induced mortality. We conclude that strong trade‐offs between xylem allocation to fiber walls, fiber lumen, and axial parenchyma drive drought resistance in neotropical trees. Moreover, the benefits of xylem allocation to axial parenchyma in wet tropical trees might not outweigh the consequential low embolism resistance under more frequent and severe droughts in a changing climate.

Fires can be ignited by people or by natural causes, which are almost exclusively lightning strikes. Discriminating between lightning and anthropogenic fires is paramount when estimating impacts of changing socioeconomic and climatological conditions on fire activity. Here we use reference data of fire ignition locations, cause and burned area from seven world regions in a machine-learning approach to obtain a global attribution of lightning and anthropogenic ignitions as dominant fire ignition sources. We show that 77% (uncertainty expressed as one standard deviation = 8%) of the burned area in extratropical intact forests currently stems from lightning and that these areas will probably experience 11 to 31% more lightning per degree warming. Extratropical forests are of global importance for carbon storage. They currently experience high fire-related forest losses and have, per unit area, among the largest fire emissions on Earth. Future increases in lightning in intact forest may therefore compound the positive feedback loop between climate change and extratropical wildfires.

Detailed information about tree species composition is critical to forest managers and ecologists. In this study, we used Sentinel-2 imagery in combination with a canopy height model (CHM) derived from airborne laser scanning (ALS) to map individual tree crowns and identify them to species level. Our study area covered 140 km² of a mainly mixed temperate forest in the Veluwe area in The Netherlands. Ground truth data on tree species were acquired for 2460 trees. Tree crowns were automatically delineated from the CHM model. We identified the delineated tree crowns to species and phylum level (angiosperm vs. gymnosperm) using a random forest (RF) classification. The RF model used multitemporal spectral variables from Sentinel-2 and crown structural variables from the CHM and was validated using an independent dataset. Different combinations of variables were tested. After feature reduction from 25 to 15 features, the RF model identified tree crowns with an overall accuracy of 78.5% (Kappa value 0.75) for tree species and 84.5% (Kappa value 0.73) for tree phyla whilst using the combination of all variables. Adding crown structural and multitemporal spectral information improved the RF classification compared to using only a Sentinel image from one season as input data. The producer’s accuracies varied between 43.8% for Norway spruce (Picea abies) to 95.3% for Douglas fir (Pseudotsuga menziesii). The RF model was extrapolated to generate a tree species map over a study area (140 km²). The map showed high abundances of common oak (Quercus robur; 35.5%) and Scots pine (Pinus sylvestris; 22.8%) and low abundances of Norway spruce (Picea abies; 1.7%) and Douglas fir (Pseudotsuga menziesii; 2.8%). Our results indicate a high potential for individual tree classification based on Sentinel-2 imagery and automatically derived tree crowns from canopy height models.

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 (−1.8σ), coinciding with enhanced leaf fall (+1.4σ), which were only locally apparent in 2005. Regions in the Amazon basin that flushed leaves at the onset of both droughts (+0.9$\mathit{\sigma }\sim +$ 2.0σ) 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.

The effects of future warming and drying on tropical forest functioning remain largely unresolved. Here, we conduct a meta-analysis of observed drought responses in Neotropical humid forests, focusing on carbon and water exchange. Measures of leaf-, tree- and ecosystem-scale performance were retrieved from 145 published studies conducted across 232 sites in Neotropical forests. Differentiating between seasonal and episodic drought, we find that (1) during seasonal drought the increase in atmospheric evaporative demand and a decrease in soil matric potential result in a decline in leaf water potential, stomatal conductance, leaf photosynthesis and stem diameter growth while leaf litterfall and leaf flushing increase. (2) During episodic drought, we observe a further decline in stomatal conductance, photosynthesis, stem growth and, in contrast to seasonal drought, a decline also in daily tree transpiration. Responses of ecosystem-scale processes, productivity and evapotranspiration are of a smaller magnitude and often not significant. Furthermore, we find that the magnitude and direction of a drought-induced change in photosynthesis, stomatal conductance and transpiration reported in a study is correlated to study-averaged wood density. Although wood density is often not functionally related to plant hydraulic properties, we find that it is a good proxy for hydraulic behaviour and can be used to predict leaf- and tree-scale responses to drought. We present new insights into the functioning of tropical forest in response to drought and present novel relationships between wood density and tropical-tree responses to drought.