Research Initiative

Windthrow Amazon Observatory

WAOSUE: Windthrow Amazon Observatory for Study and Understanding Ecosystems

A collaborative scientific observatory dedicated to investigating large-scale storm disturbances, quantifying rapid canopy changes, and assessing their long-term impacts on carbon dynamics across tropical forest ecosystems.

WAOSUE At A Glance

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Events Mapped & Growing

We have documented a nearly fourfold increase in windthrow frequency since 1985, successfully identifying approximately 5,000 large-scale events across the Amazon and counting.

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Windthrow Hotspots

Disturbance is highly concentrated geographically. Roughly 33% of all detected events occurred in only 3% of the monitored area across the central and western Amazon.

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Rapid NWA Recovery

Northwestern Amazon forests exhibit remarkable resilience, with tree density and basal area recovering to >90% of old-growth values after 20 years. This is ~50% faster than Central Amazon forests.

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Canopy Greening Phase

Following disturbance, the Enhanced Vegetation Index (EVI) steadily increases, often reaching a peak 20% above adjacent undisturbed forest as pioneer species rapidly colonize canopy gaps in the first decade.

Our Mission

To study, quantify, and understand the impacts of large-scale windthrow disturbances and extreme weather events on the structural integrity, carbon dynamics, and long-term ecological resilience of the Amazon rainforest.

Research Scope

Our geographic focus spans from the critical Andean-Amazonian altitudinal gradients down to the central Amazon basin. We seamlessly integrate ground-based biometric censuses, flux tower networks, and high-resolution satellite remote sensing.

Key Objectives

  • • Monitor and map windthrow events using advanced spatial tools.
  • • Assess the cascading impacts of canopy gaps on forest succession.
  • • Champion open science by providing transparent, standardized datasets.
  • • Bridge local observational data with predictive Earth system models.
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Featured Research Overview:

Curious about our core mission and the impact of severe weather events? Check out our recent multimedia publication.

Are extreme storms reshaping the Amazon faster than we realize?

Community Discussion

Leave a comment, ask a question, or discuss our research using your GitHub account.

Our Partners & Institutional Affiliations

Scientific Background

State of the Art: Windthrows in the Amazon

A comprehensive overview of storm-driven forest disturbances, canopy gap dynamics, and their profound implications for the global carbon cycle.

Key Characteristics

  • Trigger: Severe convective storms, squall lines, and microbursts.
  • Impact: Snaps and uproots canopy trees, causing up to 95% mortality in extreme events.
  • Hotspots: 33% of detected events occur in just 3% of the Amazon basin.
  • Detection: Sub-pixel Spectral Mixture Analysis (SMA) quantifying non-photosynthetic vegetation.

The Phenomenon & Meteorological Drivers

Windthrows are a major natural disturbance in the Amazon, generated by powerful downdrafts and downbursts associated with severe convective storms and large-scale squall lines. These intense localized wind gusts can reach speeds sufficient to snap and uproot massive canopy trees, creating forest gaps that range from a few individual trees to thousands of contiguous hectares.

Worryingly, the frequency of these events is escalating. Between 1985 and 2020, there has been a nearly fourfold increase in both the number of large windthrows (≥30 ha) and the total forest area they affect. This increase aligns with a long-term rise in extreme atmospheric instability (the top 95th percentile of afternoon Convective Available Potential Energy, or CAPE). The damage is highly concentrated; roughly 33% of all large events occur within specific "hotspot" regions in the central and western Amazon, which make up only ~3% of the basin's total area.

Carbon Cycle & Biomass Recovery

Intense windthrows instantly transfer enormous amounts of live aboveground biomass (AGB) into the dead wood pool (coarse woody debris), sometimes reducing local biomass by over 60%. As this necromass decomposes, it temporarily shifts affected patches of the forest from net carbon sinks to net carbon sources.

However, the capacity for biomass recovery varies drastically by region. In the highly productive Northwestern Amazon, forests exhibit remarkable resilience, recovering to >90% of old-growth biomass levels in approximately 20 years. This recovery rate is roughly 50% faster than that observed in the Central Amazon, suggesting that Northwestern forests may be evolutionarily adapted to more frequent and severe wind disturbances.

Forest Succession and Canopy Greening

The creation of large canopy gaps drastically increases light availability on the forest floor, triggering a vigorous, multi-decade successional response. By tracking the Enhanced Vegetation Index (EVI) over 32 years, we observe an initial sharp decline in greenness following the disturbance, followed by a rapid "greening" phase.

During the first decade of recovery, EVI steadily increases, often peaking at 20% above the levels of undisturbed old-growth forest. This elevated optical signature reflects the rapid colonization of fast-growing pioneer species, which possess highly reflective, broad leaves. As the forest matures over the next 15 to 30 years, longer-lived, late-successional species begin to dominate and form complex, multi-layered canopies, causing the EVI signal to gradually dampen and decline.

🌲 Interactive 3D Canopy Structure (LiDAR)

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Left-click and drag to rotate • Scroll to zoom • Right-click to pan

© Windthrow Inventory Database (WInD) - Urquiza-Muñoz et al., 2024 / MPI for Biogeochemistry

Modern Detection: The Wayra Approach

Traditionally, mapping these remote disturbances required extensive field campaigns. Today, observatories like WAOSUE leverage advanced techniques like Spectral Mixture Analysis (SMA) on optical satellite imagery. SMA decomposes the spectral signal of mixed pixels to estimate the proportional abundance of non-photosynthetic vegetation (NPV), green vegetation (GV), and shade.

The abrupt increase in the NPV fraction serves as a robust proxy for quantifying tree mortality and mapping the distinct "fan-shaped" geometries of severe windthrows. By integrating this physically based remote sensing approach with high-resolution 3D LiDAR and rigorous ground-truthed forest inventories, researchers can accurately bridge the gap between large-scale atmospheric phenomena and local forest ecology.

Foundation Literature

Primary Reference

Urquiza-Muñoz, J. D. (2025). Windthrow in the Amazon Basin: A spatio-temporal analysis of forest disturbances and their recovery. PhD Thesis. Max Planck Institute for Biogeochemistry / Friedrich Schiller University Jena.

Access Full Thesis (PDF)

Negrón-Juárez, R. I., Chambers, J. Q., Guimaraes, G., Zeng, H., Raupp, C. F. M., Ribeiro, G. H. P. M., ... & Higuchi, N. (2010). Widespread Amazon forest tree mortality from a single cross-basin squall line event. Geophysical Research Letters, 37(16).

Magnabosco Marra, D., Chambers, J. Q., Higuchi, N., Trumbore, S. E., Ribeiro, G. H. P. M., Dos Santos, J., ... & Wirth, C. (2014). Large-scale wind disturbances promote tree diversity in a Central Amazon forest. PLoS One, 9(8), e103723.

Espírito-Santo, F. D., Gloor, M., Keller, M., Malhi, Y., Saatchi, S., Nelson, B., ... & Phillips, O. L. (2014). Size and frequency of natural forest disturbances and the Amazon forest carbon balance. Nature Communications, 5(1), 3434.

Interactive Spatial Data

Wayra Tools: Windthrow Monitoring

Inspired by Wayra—the Quechua word for wind—these tools allow you to explore continuous monitoring dashboards visualizing storm-driven disturbance events across the Amazon.

Advanced Statistical Dashboard

Dive deeper into temporal disturbance trends, mortality censuses, and statistical modeling using our dedicated Shiny Application.

Launch Shiny App

Amazon Windthrow Explorer

Explore interactive spatial layers mapping forest disturbance and recovery dynamics across our primary study regions.

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Wayra Windthrow Observatory

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Micrometeorology & Carbon Exchange

Flux Tower Networks

Monitoring tropical ecosystem carbon exchange, Solar-Induced Fluorescence (SIF), Gross Primary Production (GPP), and Net Ecosystem Exchange (NEE) across the Amazon Basin and transition zones.

PanAmazoniaFlux

Coordinating regional research initiatives and flux tower sites across the wider Amazon basin to capture long-term meteorological trends, carbon cycling, and the impact of severe weather events on forest recovery.

  • 📍 Coverage: Amazon Basin ecosystem
  • 📊 Instruments: Ground-based SIF sensors, Eddy Covariance towers

AndesFlux

Focusing on ecosystem functioning along critical Andean-Amazonian elevation gradients, studying the complex atmospheric exchanges, moisture transport, and carbon dynamics in these vital transition zones.

  • 📍 Coverage: Andean-Amazonian gradient
  • 🔬 Focus: Topographic and altitudinal influence on ecosystem exchange

🎥 Flux Tower Operations Overview

Visualizing ground-based meteorological monitoring and data collection.

Open Science, Citizen Monitoring & Contact

Study Sites, Datasets & Collaboration

Contribute field observations, explore our network of monitoring locations, access our open-access datasets, or reach out directly to our team.

🌪️ Citizen Science Network

Report a Windthrow in 30 Seconds

Have you observed fallen trees after a severe storm in the Amazon? Park rangers, local communities, researchers, and drone pilots can report events here to help validate satellite detections across Peru, Brazil, and the wider basin.

📍 Use the GPS button to auto-fill your coordinates.

🛰️ Our team cross-checks reports with Sentinel-2 & Landsat imagery.

Interactive Field Plot & Sensor Map

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Locations of our field plots, flux towers, and active windthrow disturbance monitoring sites.

Windthrow Disturbance Dataset

DOI: 10.5281/zenodo.11168104
Access Data on Zenodo

All detected windthrows (3,170) were organized, structured, and stored in our Windthrow Inventory Database, Version 1.0 (WInD V.1). The WInD V.1 includes a complete catalog of windthrows detected in the 33 years we studied, and a detailed summary of their attributes (e.g., area, windthrow severity and the spatial distribution of pixels). The data in other formats, such as shapefile or CSV, can be made available upon request to the following email address: jurquiza@bgc-jena.mpg.de

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Get in Touch

Contact & Collaboration

Interested in our research, datasets, or exploring collaboration opportunities? Reach out to our team.

Direct Inquiries

Email Address

jurquiza@bgc-jena.mpg.de

Primary Locations

Universidad Nacional de la Amazonía Peruana
Iquitos, Peru

Max Planck Institute for Biogeochemistry
Jena, Germany

Data Requests: WInD V.1 data in formats like shapefile or CSV are available upon request. Please email us with a brief description of your intended research use.

Literature

Recent Publications

Selected peer-reviewed articles generated by WAOSUE researchers.

Our People

Researchers & Network

Founders

Jose David Urquiza Muñoz

Jose David Urquiza Muñoz

Principal Investigator & Founder

Forest Inventory • Data Science • Remote Sensing

Faculty member and researcher at Universidad Nacional de la Amazonía Peruana, leading the forest attributes laboratory. Research affiliate with the Max Planck Institute for Biogeochemistry.

Universidad Nacional de la Amazonía Peruana (UNAP) Max Planck Institute for Biogeochemistry
Susan Trumbore

Susan Trumbore

Co-Founder

Atmosphere Science

Director at the Max Planck Institute for Biogeochemistry and Professor of Earth System Science at the University of California, Irvine. Dedicated to understanding ecosystem dynamics and global carbon cycling.

Max Planck Institute for Biogeochemistry UC Irvine
Daniel Magnabosco Marra

Daniel Magnabosco Marra

Co-Founder

Forest Monitoring • Disturbance Dynamics • Data Science

Staff Scientist at the Julius Kühn Institute (JKI) for Forest Protection. He investigates ecosystem responses to disturbances and how tree mortality alters forest functions to inform climate-adaptive management and protection strategies.

Julius Kühn Institute (JKI) Max Planck Institute for Biogeochemistry Instituto Nacional de Pesquisas da Amazônia (INPA)
Robinson Negron

Robinson Negrón-Juárez

Co-Founder

Atmosphere Science • Data Science

Research Scientist at Lawrence Berkeley National Laboratory (LBNL). Expert in spatial analysis and climate sciences supporting Amazonian ecosystem observations and meteorological interactions.

Berkeley Lab (LBNL)

Collaborators

WAOSUE works closely with a network of international scientists and data specialists.

Prof. Dr. Alexander Brenning
Prof. Dr. Alexander Brenning

Research Collaborator

Spatial Statistics

Friedrich Schiller University Jena, Germany
Vitus Benson
Vitus Benson

Research Collaborator

Machine Learning • Early Warning Systems

Max Planck Institute for Biogeochemistry
Alexander Kühling
Alexander Kühling

Research Collaborator

Machine Learning

Max Planck Institute for Biogeochemistry
Yanlei Feng
Yanlei Feng

Research Collaborator

Atmosphere Science • Remote Sensing

Environmental Specialist Department of Ecology, Washington State
Luciano Emmert
Luciano Emmert

Research Collaborator

Forest Inventory • Remote Sensing

Julius Kühn Institute (JKI)
Rodil Tello
Rodil Tello

Research Collaborator

Forest Inventory

UNAP
Jorge Solignac
Jorge Solignac

Research Collaborator

Forest Inventory

UNAP
Waldemar Alegria
Waldemar Alegria

Research Collaborator

Forest Inventory

UNAP
Adriana Simonetti Lopes Peixoto
Adriana Simonetti Lopes Peixoto

Research Collaborator

Drone Survey

Instituto Nacional de Pesquisas da Amazônia (INPA)
Santiago Botia
Santiago Botia

Research Collaborator

Atmosphere & Data Science

Max Planck Institute for Biogeochemistry
Michael Vasquez
Michael Vasquez

Research Collaborator

Drone Survey

UNAP Frankfurt Zoological Society
Jhostin Rengifo
Jhostin Rengifo

Research Collaborator

Drone Survey

UNAP
Roy Rubio
Roy Rubio

Research Collaborator

Drone Survey

UNAP
Segundo Cordoba
Segundo Cordoba

Research Collaborator

Forest Inventory

UNAP
Alan Mosquera
Alan Mosquera

Research Collaborator

Drone Survey

UNAP