Earth system change threatens societal well-being via altered land-carbon dynamics, freshwater variability, biodiversity loss, and climate extremes, while integrated data-driven assessments remain scarce. This gap is acute for compound cross-sector risks, where socio-physical interactions affect economies, health, equity, food prices, and migration. Rapid growth of open geospatial, atmospheric, and socioeconomic data enables systemic indicators of these risks. We propose a syndrome-based approach that integrates synchronized biosphere, atmosphere, and socioeconomic changes into co-evolving interdependencies, termed biospheric-atmospheric-socioeconomic syndromes. Using dimensionality reduction and clustering, we extract coupled modes and prototype two syndromes: ecosystem water deficits and urban hot-dry stress. These syndromes identify key cross-sector variables and flag compound extremes missed by single thresholds. A key next step is the collective development of syndromes using finer-scale socioeconomic data and richer indicator sets, enabling regional diagnostics and decision-making across local-to-global scales.
LI Wantong;
DUVEILLER G.;
GANS Fabian;
SMITS Jeroen;
KRAEMER Guido;
FRANK Dorothea;
MAHECHA Miguel;
WEBER Ulrich;
MIGLIAVACCA Mirco;
CEGLAR Andrej;
KEENAN Trevor F.;
REICHSTEIN Markus;
2026-05-12
ELSEVIER
JRC141667
2590-3322 (online),
https://www.sciencedirect.com/science/article/pii/S2590332225003859,
https://publications.jrc.ec.europa.eu/repository/handle/JRC141667,
10.1016/j.oneear.2025.101559 (online),
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