Upwind terrestrial influences on soil moisture variability across South America

Soil moisture across South America exhibits coherent spatial patterns shaped by upwind terrestrial conditions, yet their downwind propagation remains poorly quantified. We develop an observation-driven framework integrating atmospheric transport trajectories with deep learning to estimate vegetation's contribution to downwind soil moisture. The transport-informed model outperforms a local-only baseline, with upwind information contributing 67% of predictive power, of which vegetation explains 15%. This vegetation-mediated influence is enhanced over agricultural zones, forming hotspots aligned with land-cover change and drought exposure. The cross-regional influence is organized along major transport corridors and varies non-linearly with climate. In humid forests, downwind moisture supply is highly sensitive to vegetation change, with canopy degradation associated with reduced soil moisture; in semi-arid regions, initial greening is associated with increases, but further greening weakens or reverses the effect. These results quantify vegetation-soil moisture teleconnections, with implications for land-atmosphere coupling in Earth system models and hydrological consequences of land-use and climate change.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2026-07-24
DOI
https://doi.org/10.1038/s41467-026-75637-x
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Upwind terrestrial influences on soil moisture variability across South America

Weidong Zhao, Feini Huang, Gustau Camps‐Valls, Yongjiu Dai et al.
Nature Communications
Plant Water Relations and Carbon Dynamics
article

Upwind terrestrial influences on soil moisture variability across South America

Weidong Zhao, Feini Huang, Gustau Camps‐Valls, Yongjiu Dai, Shijie Jiang, Wei Shangguan, Wantong Li, Markus Reichstein, Alexander J. Winkler, Christian Reimers, Grégory Duveiller
article en

Abstract

Soil moisture across South America exhibits coherent spatial patterns shaped by upwind terrestrial conditions, yet their downwind propagation remains poorly quantified. We develop an observation-driven framework integrating atmospheric transport trajectories with deep learning to estimate vegetation's contribution to downwind soil moisture. The transport-informed model outperforms a local-only baseline, with upwind information contributing 67% of predictive power, of which vegetation explains 15%. This vegetation-mediated influence is enhanced over agricultural zones, forming hotspots aligned with land-cover change and drought exposure. The cross-regional influence is organized along major transport corridors and varies non-linearly with climate. In humid forests, downwind moisture supply is highly sensitive to vegetation change, with canopy degradation associated with reduced soil moisture; in semi-arid regions, initial greening is associated with increases, but further greening weakens or reverses the effect. These results quantify vegetation-soil moisture teleconnections, with implications for land-atmosphere coupling in Earth system models and hydrological consequences of land-use and climate change.

Nature CommunicationsVol. 17(1)
Lawrence Berkeley National Laboratory (US), Sun Yat-sen University (CN), Universitat de València (ES), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), Ernst Abbe University of Applied Sciences Jena (DE), Jena Bioscience (Germany) (DE), Max Planck Institute for Biogeochemistry (DE), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (CN), Columbia University (US), University of California, Berkeley (US)
Carl-Zeiss-Stiftung
Climate action
Openalex Percentile: Top 10%
Plant Water Relations and Carbon Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.