Wildfires have become the new norm in many parts of the Amazonian humid forest, an ecosystem that did not co-evolve with this stressor. Large areas of previously undisturbed and human-modified forests are catching fire, jeopardising the future of the largest and most biodiverse tropical rainforest in the world, and potentially acting as a feedback that would further increase regional and global climate change. In recent dry years the extent of fire has greatly exceeded the rate of deforestation in the Brazilian Amazon. These fires result in in about half of the trees dying, and open up the forests to make them more vulnerable to subsequent fires. Despite the growing prevalence of Amazonian wildfires, we still have a very limited understanding of why these low intensity understorey fires cause such high rates of tree mortality, which species functional traits predict vulnerability or survival to these fires, what are the impacts of wildfires on the forest carbon balance and what are the patterns of taxonomic and functional recovery following a fire event. We propose a research plan to achieve major advances in our understanding of such wildfire impacts, including of the underlying mechanisms that cause both short-term and longer-term tree mortality. This work will be based at a field site in Santarem in Eastern Brazilian Amazonia, where we have collected several years of measurements of detailed vegetation ecology and carbon cycle tracking over a range of plots. These include a number of plots which experienced fire during the 2015/16 El Niño. We will implement this project by combining a state-of-the-art forest burn experiment with continued monitoring of a unique set of long-term sampling plots, some of which we have tracked through the 2015-16 wildfire event associated with a strong El Niño. We are uniquely placed to address these fundamental questions given our network of burned and unburned forest plots that is already in place, the strong partnerships we have forged with park managers and federal agencies, and the numerous past datasets that we can use as baseline information. The fire experiment will involve setting fire to limited patch of forest (with the close cooperation of local fire brigades), tracking fire intensity and tracking the physiology and mortality responses of individual trees in the fire plots, including trees that have their root mats or their bark insulated from fire damage. We will also experiment with different fire break methodologies to explore the most effective way to stop such fires. With the intensive carbon cycle studies we will track the carbon cycle responses for up to seven years after the 2015 fires, giving us novel insight into the longer term carbon cycle responses and the ecosystem responses and recovery after a fire event. As well as advancing scientific knowledge about a pervasive and increasing threat to the future of tropical forests in the Anthropocene, our co-designed pathways to impact ensures we will also inform and improve approaches to minimise risk of fire-induced dieback of humid Amazonian forests. We will work closely with local fire managers, and engage with state and national policymakers, to draft recommendations on how to manage forest reserves and forest-agriculture mixed landscapes to minimise the risk of fire spread. If applied at a large scale, these fire prevention strategies are a crucial tool that can help minimise the risk of extensive fire-induced dieback within Amazonian forests.

Tropical rainforests are one of the planets most important stores of carbon, as well as being essential to water cycling at large scales. Within tropical forests the largest trees, with diameters exceeding 70 cm, store between 25-45% of the carbon, yet represent <4% of the total number of trees. These large trees also transport disproportionately more water than smaller individuals do, making them a conservation priority for the future. Large tropical trees are likely to be very old, with many between 200-500 years and some estimated to be >1400 years old. Therefore, they have survived historical extreme climate events, including drought. Yet, recent evidence suggests water transport limitations are likely to make larger trees more vulnerable to the more extreme, more frequent drought events, which are predicted for the future. However, we still do not understand how large trees manage to overcome the huge resistances associated with transporting water such large vertical distances, against gravity, which substantially increase the hydraulic stress the tree experiences in a given climate. This information is essential to understanding how vulnerable these iconic tropical trees will be to the predicted future increases in drought frequency and intensity. Large trees can minimise the effects of increasing resistance to water transport with height through changing multiple leaf and stem hydraulic traits vertically through their stem and canopy. However, data on these vertical changes are rare and do not exist for tropical trees. Consequently, there is limited knowledge concerning whether trees can or cannot compensate for the negative effects being taller has on their water transport capacity and therefore their vulnerability to future drought events. In this project we will combine novel measurements of vertical changes in tree anatomical, structural and hydraulic properties on the world's tallest tropical trees, in two different tropical regions - Amazonia and Borneo - to achieve the following aims: Aim 1: Determine how vertical changes in tree hydraulic and anatomical traits regulate the capacity of tall trees to maintain water transport to their leaves under different environmental conditions. Aim 2: Determine if key structural and architectural properties of tropical trees control the vertical gradients of plant hydraulic and anatomical properties. Aim 3: Determine how accounting for vertical gradients in hydraulic properties in tall tropical trees alters predictions of tropical forest water and carbon cycling. To achieve these aims we will study the tallest tropical trees in the world. This will include trees in Amazonia discovered in 2019 that reach 88.5 m tall, ~30m taller than any other tree recorded in the neotropics. We will compare these to equivalent sized trees in Borneo from the dipterocarp family, the family containing the tallest angiosperm species in the world. On these trees we will measure vertical gradients in hydraulic and anatomical traits on 60 trees varying in height from 20-90 m. These trees will come from eight dominant species in Brazil and Borneo, allowing us to contrast the hydraulic adaptations of trees species from drier, more seasonal climates (Brazil), to those of species that have evolved in wetter, a-seasonal climates (Borneo). To realise the three aims above, our novel vertical hydraulic trait measurements will be combined with measures of whole-tree water transport and storage, tree architectural data derived from state-of-the-art ground-based laser scanning and vegetation models. Combining these techniques will allow us to make a step-change in our current understanding of the limits to water transport in the world's tallest tropical trees and the impact this may have on carbon and water cycling under future climate scenarios.

SUMMARY The Amazon is the most important biome of South America, harbouring extraordinarily high levels of biodiversity and providing important ecosystems services. This biome is particularly notable for evolving independently from fire and in a moist, warm climate. In recent decades, altered fire regimes and an increasingly hotter and drier climate has pushed this key biome towards ecological thresholds that will likely lead to major losses in biodiversity and ecosystem services. Similarly, the ecotonal forests at the Amazon-Cerrado transition are unique ecosystems in terms of form and function, but they may be the first to suffer large-scale tree mortality and species loss due to the combined effects of increased anthropogenic disturbance, altered fire regimes and a drier climate. Vulnerability of fire and droughts are closely intertwined in Amazonian and transitional forests because fires in this region only occur when there is water stress and a human ignition source. Thus, drought increases vulnerability to fire, but we do not yet understand the magnitude and spatial variation of these vulnerabilities. Once a forest burns there is immediate tree mortality, but recent evidence also shows a significant time-lagged mortality that can last for decades, becoming an important carbon source. However, the mechanistic processes that lead to time-lagged tree mortality in this myriad of forest ecosystems encompassing the Amazon biome and the Amazon-Cerrado transition are still poorly understood. We also lack knowledge on how these processes might vary spatially across the biome and its transition. A better understanding of the mechanisms that lead to tree mortality after fires and droughts is needed to design future policies that emphasise nature-based solutions including restoration and natural regeneration. This proposal presents a multi-level approach that aims at deciphering the mechanisms that underly vulnerability to fire and time-lagged post-fire mortality across the tropical forests in Amazon and Amazon-Cerrado transition. To achieve this aim, we will quantify fire vulnerability at three different scales and link them through an upscaling approach. First, we will identify the ecological mechanisms, reflected through functional traits, that explain why individuals and species die after fires occur. For this, we will focus on poorly understood traits that can be related to fire and/or hydraulic functioning. Second, at the community scale, we will examine how vegetation structure, community traits and microclimate affect the probability to burn, through an intensive characterisation of different vegetation types with multispectral and light detection and ranging (LIDAR) imagery. Third, we will use our our unique ground-dataset on functional traits, vegetation structure and moisture dynamics, and the latest state-of-art remotely sensed information on structure and water stress to predict the vulnerability of the Amazon forests and Amazon-Cerrado transitional forests. This information will be directly applicable for the detection of sensitive hotspots (areas particularly vulnerable to fire) through satellite products. We will deliver quantifiable early-warning metrics of ecosystem vulnerability to fire that can be mapped and incorporated into fire management policies. This is a revised version of a NERC proposal that was rejected with a score of 7 by the NERC Panel in July 2020, and we have carefully addressed the Panel's comments. Specifically, we have clarified the methodology and we have reformulated the hypotheses, so they address vulnerability to fire and not drought fire-interactions.