Understanding how terrestrial plant functional strategies (Competitive, Stress-tolerant, Ruderal; CSR) respond to environmental conditions is crucial for predicting ecosystem dynamics under global climate change, yet remains unexplored at the global community level. Leveraging a machine learning approach, and utilizing multi-source satellite remote-sensing and field-collected sPlotOpen measurements data, we generated the first global community-level map of CSR functional strategy variations. Results show that S-selected strategies are globally dominant (C: S: R = 23.66 : 62.40 : 13.94%), with substantial spatial variations across biomes. This variability is strongly influenced by climatic variables (e.g. mean annual precipitation, diurnal temperature range) and soil properties (e.g. cation exchange capacity, total nitrogen). Future projections show that climate change favours S- (+0.33%) and R- (+0.31%) at the expense of C-selected strategy (-0.64%), alongside marked biome-specific shifts. Despite potential underestimation of localized climate uncertainties, these findings provide critical insights into global plant community dynamics under challenging abiotic conditions.

Facing a harsh climate: terrestrial plant functional strategies in a changing world / J. Wang, S.P.. - In: NATIONAL SCIENCE REVIEW. - ISSN 2095-5138. - (2026). [Epub ahead of print] [10.1093/nsr/nwag416]

Facing a harsh climate: terrestrial plant functional strategies in a changing world

S. Pierce
Secondo
Writing – Review & Editing
;
2026

Abstract

Understanding how terrestrial plant functional strategies (Competitive, Stress-tolerant, Ruderal; CSR) respond to environmental conditions is crucial for predicting ecosystem dynamics under global climate change, yet remains unexplored at the global community level. Leveraging a machine learning approach, and utilizing multi-source satellite remote-sensing and field-collected sPlotOpen measurements data, we generated the first global community-level map of CSR functional strategy variations. Results show that S-selected strategies are globally dominant (C: S: R = 23.66 : 62.40 : 13.94%), with substantial spatial variations across biomes. This variability is strongly influenced by climatic variables (e.g. mean annual precipitation, diurnal temperature range) and soil properties (e.g. cation exchange capacity, total nitrogen). Future projections show that climate change favours S- (+0.33%) and R- (+0.31%) at the expense of C-selected strategy (-0.64%), alongside marked biome-specific shifts. Despite potential underestimation of localized climate uncertainties, these findings provide critical insights into global plant community dynamics under challenging abiotic conditions.
ecosystem dynamics; plant functional traits; future projection; global mapping; machine learning; plant strategy
Settore BIOS-01/C - Botanica ambientale e applicata
2026
14-lug-2026
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1263740
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