Global self-similar scaling of terrestrial carbon with aridity

TL;DR

This paper reveals a universal self-similar scaling law linking global terrestrial carbon stocks to aridity, enabling simplified predictions of carbon distribution based on water availability across diverse ecosystems.

Contribution

It uncovers a novel self-similar scaling behavior of carbon stocks with aridity using global data, advancing quantitative understanding of ecosystem carbon patterns.

Findings

Carbon stock statistics scale with aridity via a universal exponent.

Normalized carbon distributions collapse onto a single curve across regimes.

Scaling enables robust predictions of carbon stocks based solely on aridity.

Abstract

While it is well known that water availability controls vegetation growth and soil microbial activity, how aridity affects ecosystem carbon patterns is not completely understood. Towards a more quantitative assessment of terrestrial carbon stocks, here we uncover a remarkable self-similar behavior of the global carbon stock. Using international survey and remote sensing data, we find that the key statistics (e.g., mean, quantiles, and standard deviation) of carbon stock tend to scale with the hydrological regime (i.e., aridity) via a universal exponent. As a result, when normalized by its averages in the corresponding hydrological regime, the carbon stock distributions collapse onto a single curve. Such a scaling reflects the strong coupling between hydrological cycle and biogeochemical process and enables robust predictions of carbon stocks as a function of aridity only.