WET-RISK: Basin-wide assessment of amazon wetland forests sensitivity to extreme climatic events and its ecological consequences
Lead Research Organisation:
University of Leeds
Abstract
The Amazon rainforest, the most biodiverse ecosystem on Earth, plays a crucial role in global climate regulation. Within this vast landscape, large meandering rivers and seasonally flooded forests are iconic ecosystems, where people, plants, and animals are adapted to flooding seasonality and their survival depends on the regularity of this rhythmic pulse. However, climate change is altering these patterns, bringing more frequent extreme floods, droughts, and heatwaves. These changes threaten wetland tree species from both sides - demanding resistance to longer floods as well as extreme droughts. Understanding the physiological mechanisms driving tree responses to climatic extremes across different wetland forest types at large spatial scale is essential to predicting the future of Amazonian flooded forests, their biodiversity, and their role in carbon cycling.
Our knowledge of the physiology of these ecosystems is currently restricted to a handful local studies, therefore our research question is: How does the sensitivity to extreme drought and flooding across different types of Amazonian flooded forests modulate Amazon forest resilience and carbon cycling at basin-wide scale? My main aims are to:
Aim 1) Build the first large-scale dataset of tree physiological traits that determine water and thermal stress resistance across Amazonian wetland forests, spanning the full range of flooding and nutrient conditions.
Aim 2) Identify the ecophysiological mechanisms that allow trees to survive extreme hydrological and climatic stress, revealing how different wetland forests may cope with climate change.
Aim 3) Assess the consequences for biodiversity, forest demography, and carbon cycling, determining whether these forests are resilient to increasing environmental extremes or at risk of collapse.
To achieve this, we will integrate cutting-edge approaches, including tree physiology measurements, 3D laser scanning, and long-term forest monitoring across the Amazon basin. With this integrative frame-work we will upscale tree nano-structures to ecosystem level, predicting for the first time the impact of changes in climate across all types of Amazonian flooded forests and if these ecosystems may cope or collapse under increasingly changing conditions.
This research will generate an unprecedented dataset, delivering major contributions to tropical forest ecology and climate resilience science. Beyond academia, the findings have direct practical applications. Understanding which tree species are most resilient to climate stress can, for example, inform forest restoration efforts, helping select species that can withstand future conditions. But my findings will not just benefit science - through my partnership with the Mamirauá Institute I also have a strong pathway to inform climatic risk assessment and support the practices and decisions of local communities, conservation managers, and policymakers. Furthermore, through my ongoing partnership with the National Geographic Society and Instituto Serrapilheira (Brazil) I have clear and strong pathways to reach a vast global public, promoting and supporting the development of some approaches for climate change adaptation and conservation of Amazonia and other tropical biomes.
Our knowledge of the physiology of these ecosystems is currently restricted to a handful local studies, therefore our research question is: How does the sensitivity to extreme drought and flooding across different types of Amazonian flooded forests modulate Amazon forest resilience and carbon cycling at basin-wide scale? My main aims are to:
Aim 1) Build the first large-scale dataset of tree physiological traits that determine water and thermal stress resistance across Amazonian wetland forests, spanning the full range of flooding and nutrient conditions.
Aim 2) Identify the ecophysiological mechanisms that allow trees to survive extreme hydrological and climatic stress, revealing how different wetland forests may cope with climate change.
Aim 3) Assess the consequences for biodiversity, forest demography, and carbon cycling, determining whether these forests are resilient to increasing environmental extremes or at risk of collapse.
To achieve this, we will integrate cutting-edge approaches, including tree physiology measurements, 3D laser scanning, and long-term forest monitoring across the Amazon basin. With this integrative frame-work we will upscale tree nano-structures to ecosystem level, predicting for the first time the impact of changes in climate across all types of Amazonian flooded forests and if these ecosystems may cope or collapse under increasingly changing conditions.
This research will generate an unprecedented dataset, delivering major contributions to tropical forest ecology and climate resilience science. Beyond academia, the findings have direct practical applications. Understanding which tree species are most resilient to climate stress can, for example, inform forest restoration efforts, helping select species that can withstand future conditions. But my findings will not just benefit science - through my partnership with the Mamirauá Institute I also have a strong pathway to inform climatic risk assessment and support the practices and decisions of local communities, conservation managers, and policymakers. Furthermore, through my ongoing partnership with the National Geographic Society and Instituto Serrapilheira (Brazil) I have clear and strong pathways to reach a vast global public, promoting and supporting the development of some approaches for climate change adaptation and conservation of Amazonia and other tropical biomes.
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ORCID iD |
| Julia Tavares (Principal Investigator / Fellow) |