Optimal canopy light-use strategy shapes global greenness dynamics

“Greenness” is a key indicator of the functional state of vegetation. However, the physiological processes behind seasonal patterns in greenness are diverse and incompletely understood, hindering the predictability of climate-driven shifts in global foliage phenology. Optimality principles suggest that plants invest in canopy architecture to maximize light capture. Therefore, we hypothesize that, irrespective of specific physiological mechanisms, greenness (fAPAR: fractional canopy light absorption) commonly tracks the seasonal dynamics of potential production (A0: theoretical canopy carbon uptake with all light absorbed). In other words, plants tend to display foliage when it is most productive. We show that observations confirm this hypothesis and develop a model predicting fAPAR from the seasonal cycle of A0, with a phenological lag that increases (from 2 weeks to 3 months) with increasing moisture. This model captures 81% of observed variations in fAPAR and shows that light and environmentally regulated biophysical constraints shape global patterns of vegetation greenness, its seasonal cycle, and its recent increase. Plants tend to display foliage when conditions are most productive. The optimality-based model presented here captures this behavior and predicts global vegetation patterns better than existing dynamic vegetation models.

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Publication Details

Journal
Nature Communications
Published
2026-08-21
DOI
https://doi.org/10.1038/s41467-026-76896-4
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Optimal canopy light-use strategy shapes global greenness dynamics

Wenjia Cai, Ziqi Zhu, Boya Zhou, Martin De Kauwe et al.
Nature Communications
Remote Sensing in Agriculture
article

Optimal canopy light-use strategy shapes global greenness dynamics

Wenjia Cai, Ziqi Zhu, Boya Zhou, Martin De Kauwe, I. Colin Prentice, Sandy P. Harrison, Han Wang
article en

Abstract

“Greenness” is a key indicator of the functional state of vegetation. However, the physiological processes behind seasonal patterns in greenness are diverse and incompletely understood, hindering the predictability of climate-driven shifts in global foliage phenology. Optimality principles suggest that plants invest in canopy architecture to maximize light capture. Therefore, we hypothesize that, irrespective of specific physiological mechanisms, greenness (fAPAR: fractional canopy light absorption) commonly tracks the seasonal dynamics of potential production (A0: theoretical canopy carbon uptake with all light absorbed). In other words, plants tend to display foliage when it is most productive. We show that observations confirm this hypothesis and develop a model predicting fAPAR from the seasonal cycle of A0, with a phenological lag that increases (from 2 weeks to 3 months) with increasing moisture. This model captures 81% of observed variations in fAPAR and shows that light and environmentally regulated biophysical constraints shape global patterns of vegetation greenness, its seasonal cycle, and its recent increase. Plants tend to display foliage when conditions are most productive. The optimality-based model presented here captures this behavior and predicts global vegetation patterns better than existing dynamic vegetation models.

Nature Communications
University of Bristol (GB), Department of Archaeology (LK), Imperial College London (GB), University of Reading (GB), Tsinghua University (CN)
Climate action
Openalex Percentile: Top 37%
Remote Sensing in Agriculture
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Optimal canopy light-use strategy shapes global greenness dynamics — Wenjia Cai, Ziqi Zhu, et al. · Nature Communications (2026) | TGRS Research Map | TGRS