• Energy Research

Tree mortality appears to be increasing in moist tropical forests 1 , with potentially important implications for global carbon and water cycles 2 . Little is known about the drivers of tree mortality in these diverse forests, partly because long-term data are lacking 3 . The relative importance of climatic factors and species functional traits as drivers of tropical tree mortality are evaluated using a unique dataset in which the survival of over 1,000 rainforest canopy trees from over 200 species has been monitored monthly over five decades in the Central Amazon. We found that drought, as well as heat, storms and extreme rainy years, increase tree mortality for at least two years after the climatic event. Specific functional groups (pioneers, softwoods and evergreens) had especially high mortality during extreme years. These results suggest that predicted climate change will lead to higher tree mortality rates, especially for short-lived species, which may result in faster carbon sequestration but lower carbon storage of tropical forests.

AbstractThe tropical forest carbon sink is known to be drought sensitive, but it is unclear which forests are the most vulnerable to extreme events. Forests with hotter and drier baseline conditions may be protected by prior adaptation, or more vulnerable because they operate closer to physiological limits. Here we report that forests in drier South American climates experienced the greatest impacts of the 2015–2016 El Niño, indicating greater vulnerability to extreme temperatures and drought. The long-term, ground-measured tree-by-tree responses of 123 forest plots across tropical South America show that the biomass carbon sink ceased during the event with carbon balance becoming indistinguishable from zero (−0.02 ± 0.37 Mg C ha−1 per year). However, intact tropical South American forests overall were no more sensitive to the extreme 2015–2016 El Niño than to previous less intense events, remaining a key defence against climate change as long as they are protected.

Summary There is a consensus about negative impacts of droughts in Amazonia. Yet, extreme wet episodes, which are becoming as severe and frequent as droughts, are overlooked and their impacts remain poorly understood. Moreover, drought reports are mostly based on forests over a deep water table (DWT), which may be particularly sensitive to dry conditions. Based on demographic responses of 30 abundant tree species over the past two decades, in this study we analyzed the impacts of severe droughts but also of concurrent extreme wet periods, and how topographic affiliation (to shallow ‐ SWTs ‐ or deep ‐ DWTs ‐ water tables), together with species functional traits, mediated climate effects on trees. Dry and wet extremes decreased growth and increased tree mortality, but interactions of these climatic anomalies had the highest and most positive impact, mitigating the simple negative effects. Despite being more drought‐tolerant, species in DWT forests were more negatively affected than hydraulically vulnerable species in SWT forests. Interaction of wet–dry extremes and SWT depth modulated tree responses to climate, providing buffers to droughts in Amazonia. As extreme wet periods are projected to increase and at least 36% of the Amazon comprises SWT forests, our results highlight the importance of considering these factors in order to improve our knowledge about forest resilience to climate change.

Abstract Wood density is a critical control on tree biomass, so poor understanding of its spatial variation can lead to large and systematic errors in forest biomass estimates and carbon maps. The need to understand how and why wood density varies is especially critical in tropical America where forests have exceptional species diversity and spatial turnover in composition. As tree identity and forest composition are challenging to estimate remotely, ground surveys are essential to know the wood density of trees, whether measured directly or inferred from their identity. Here, we assemble an extensive dataset of variation in wood density across the most forested and tree-diverse continent, examine how it relates to spatial and environmental variables, and use these relationships to predict spatial variation in wood density over tropical and sub-tropical South America. Our analysis refines previously identified east-west Amazon gradients in wood density, improves them by revealing fine-scale variation, and extends predictions into Andean, dry, and Atlantic forests. The results halve biomass prediction errors compared to a naïve scenario with no knowledge of spatial variation in wood density. Our findings will help improve remote sensing-based estimates of aboveground biomass carbon stocks across tropical South America.

Summary Species distributions and assemblage composition may be the result of trait selection through environmental filters. Here, we ask whether filtering of species at the local scale could be attributed to their hydraulic architectural traits, revealing the basis of hydrological microhabitat partitioning in a Central Amazonian forest. We analyzed the hydraulic characteristics at tissue (anatomical traits, wood specific gravity (WSG)), organ (leaf area, specific leaf area (SLA), leaf area : sapwood area ratio) and whole‐plant (height) levels for 28 pairs of congeneric species from 14 genera restricted to either valleys or plateaus of a terra‐firme forest in Central Amazonia. On plateaus, species had higher WSG, but lower mean vessel area, mean vessel hydraulic diameter, sapwood area and SLA than in valleys; traits commonly associated with hydraulic safety. Mean vessel hydraulic diameter and mean vessel area increased with height for both habitats, but leaf area and leaf area : sapwood area ratio investments with tree height declined in valley vs plateau species. [Correction added after online publication 29 March 2017: the preceding sentence has been reworded.] Two strategies for either efficiency or safety were detected, based on vessel size or allocation to sapwood. In conclusion, contrasting hydrological conditions act as environmental filters, generating differences in species composition at the local scale. This has important implications for the prediction of species distributions under future climate change scenarios.