Collaborative research: rapid: a perfect storm: will the double-impact of 2023/24 EL nino drought and forest degradation induce a local tipping-point onset in the eastern amazon?

This Project Grant award from the National Science Foundation's Biological Sciences program (CFDA 47.074) will support research at the University of Arizona to investigate the potential impacts of drought and forest degradation on the Amazon rainforest's water cycling and susceptibility to tipping points. The $103,764 award, effective from February 2024 to January 2025, will fund field observations, data collection, and analysis to test three key hypotheses related to the Amazon's drought sensitivity and vulnerability to ecosystem-level collapse. The research aims to provide new datasets and insights to improve models for predicting when and how Amazon tipping points may occur, which could have substantial implications for regional weather patterns, water resources, and global climate. The project includes an educational component to connect U.S. high school students with Amazon researchers and real scientific data.

Abstract

The amazon rainforest sustains itself by recycling rainfall: trees pump water from the soil and release IT from their leaves as vapor, which can be recondensed in the atmosphere and fall as rain again. The potential for drought and forest degradation to break this forest-sustaining recycling system, pushing the amazon rainforest past a point of collapse into a degraded or even savanna state, has received much recent attention in the media and scientific literature. However, exactly how the so-called ?tipping point? Occurs in any given forest site is unclear. This project investigates two possible causes of tipping points, both of which are predicted to become more common in the future: severe drought linked to EL NI?o climate conditions, and forest degradation caused by increasingly frequent strong storms and winds. This award capitalizes on a fleeting opportunity to observe how the ongoing drought, amplified by previous forest degradation, shuts down the capacity of trees to transfer water from the soil to the atmosphere, and thereby breaks the water pump that sustains rainfall recycling throughout the amazon. The knowledge produced will help scientists predict when and how amazon-wide tipping points might occur, which would importantly affect weather patterns, water resources, and economic stability in south america, as well as global climate. This study has broad impacts on education, through training of graduate students at public universities and through a custom-designed high school educational program that connects U.S. Students with amazon researchers and real scientific data from trees of the world?s most famous tropical forest. This study focuses on whole-forest and leaf-level observations of transpiration?the transport of water by trees from soil to atmosphere during photosynthesis?through drought and initial recovery. IT tests three key hypotheses at the heart of the amazon forest tipping-point paradigm. H1) whole-forest drought sensitivity is heightened by the legacy of previous droughts. H1 is tested by comparing eddy-flux-tower measured 2023/24 drought response to those of previous droughts, notably the extreme EL NI?o of 2015/16. H2) whole-forest drought sensitivity emerges from individual trees? Differing ecophysiological strategies for drought response. These strategies contribute to ecosystem-scale drought sensitivity and structure the tipping point onset. H2 is tested by observing responses across six dominant species, providing a foundation for individual-to-ecosystem trait-based scaling. H3) forest drought sensitivity is heightened by disturbance-induced forest degradation. H3, widely postulated but never directly tested, explores the tipping point mechanisms relating increased drought sensitivity to altered energy balance from forest cover loss. H3 is tested by comparing tree ecohydrology and microenvironments between forest interior and large windthrow gaps. This research will provide new, hard-to-observe datasets that will allow critical tests (and subsequent improvement) of models of forest drought response and ecohydrologic tipping points this award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.