Search NASA⌕ Search

DOE OSTI · 1908902

Windthrow characteristics and their regional association with rainfall, soil, and surface elevation in the Amazon

Abstract

Abstract Windthrows (trees uprooted and broken by winds) are common across the Amazon. They range in size from single trees to large gaps that lead to changes in forest dynamics, composition, structure, and carbon balance. Yet, the current understanding of the spatial variability of windthrows is limited. By integrating remote sensing data and geospatial analysis, we present the first study to examine the occurrence, area, and direction of windthrows and the control that environmental variables exert on them across the whole Amazon. Windthrows are more frequent and larger in the northwestern Amazon (Peru and Colombia), with the central Amazon (Brazil) being another hot spot of windthrows. The predominant direction of windthrows is westward. Rainfall, surface elevation, and soil characteristics explain the variability (20%–50%) of windthrows but their effects vary regionally. A better understanding of the spatial dynamics of windthrows will improve understanding of the functioning of Amazon forests.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Negron-Juarez, Robinson (ORCID:0000000246912692), Magnabosco-Marra, Daniel (ORCID:0000000312162982), Feng, Yanlei, Urquiza-Muñoz, Jose David (ORCID:0000000200622278), Riley, William J. (ORCID:0000000246152304), Chambers, Jeffrey Q.. 2023-01-11. Windthrow characteristics and their regional association with rainfall, soil, and surface elevation in the Amazon. https://doi.org/10.1088/1748-9326%2Facaf10

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Water4Energy Step-1 Band-M Ready-to-Train Samples for TVA Weeks-to-Years Prediction, Version 0

AI-ready Band-M (monthly) labelled training pack for the Water4Energy Genesis Task-1 project on weeks-to-years prediction of Tennessee Valley temperature and precipitation. The deposit includes leakage-aware issue-time samples (samples_M_v0.nc; N=486), train-only scalers, issue-time split table, supporting monthly panels, and Python generation scripts to recreate the pack from the companion Tier-1 raw observation collection (https://doi.org/10.13139/ORNLNCCS/3398576). Each sample pairs a 12-month lookback of teleconnection indices and SST box anomalies with TVA-mean ERA5 anomaly targets (t2m, tp, msl) at leads 1–3 months.

54 ENVIRONMENTAL SCIENCES↗

Multi-Angle Snowflake Camera, particle analysis

The c1 level data product for the Mutli-Angle Snowflake Camera contains snowflake fall speeds and particle size, among other analysis for images associated with each hydrometeor.

54 ENVIRONMENTAL SCIENCES↗

Multi-Angle Snowflake Camera, time bins

The c1 level data product for the Mutli-Angle Snowflake Camera contains snowflake fall speeds and particle size, among other analysis for images associated with each hydrometeor.

54 ENVIRONMENTAL SCIENCES↗