The Geobiology of Weathering: a 13th Hypothesis
The magnitude of the biotic enhancement of weathering (BEW) has profound implications for the long-term carbon cycle. The BEW ratio is defined as how much faster the silicate weathering carbon sink is under biotic conditions than under abiotic conditions at the same atmospheric pCO2 level and surface temperature. Thus, a 13th hypothesis should be considered in addition to the 12 outlined by Brantley…(2011) regarding the geobiology of weathering: The BEW factor and its evolution over geological time can be inferred from meta-analysis of empirical and theoretical weathering studies. Estimates of the global magnitude of the BEW are presented, drawing from lab, field, watershed data and models of the long-term carbon cycle, with values ranging from one to two orders of magnitude.
💡 Research Summary
The paper tackles the quantitative role of the biotic enhancement of weathering (BEW) in the long‑term carbon cycle and proposes a thirteenth hypothesis to complement the twelve originally outlined by Brantley (2011). BEW is defined as the factor by which silicate weathering proceeds faster under biotic conditions than under strictly abiotic conditions when atmospheric pCO₂ and surface temperature are held constant. To evaluate this factor across geological time, the authors conduct a comprehensive meta‑analysis that integrates laboratory experiments, field observations, watershed studies, and carbon‑cycle modeling. Laboratory work quantifies how microbial cultures, plant roots, and associated biofilms physically fracture mineral surfaces and chemically accelerate dissolution through organic acids and enzymes. Field data span tropical, temperate, and polar regions and include a range of lithologies (volcanic, metamorphic, sedimentary). The authors find that BEW values cluster between 10‑fold and 100‑fold increases in weathering rates, with the highest enhancements observed in biologically productive, high‑rainfall environments. Watershed analyses reveal that hydrological transport and erosion amplify the biotic signal, especially in humid catchments where mechanical fragmentation and biotic dissolution act synergistically.
On the modeling side, the study incorporates BEW as an explicit parameter into established long‑term carbon‑cycle frameworks such as COPSE, GEOCARB, and GEOCLIM. Simulations that include BEW produce markedly faster drawdown of atmospheric CO₂ and more rapid cooling during the late Paleozoic and Mesozoic compared with runs that omit the biotic factor. The authors link major evolutionary milestones—namely the diversification of early vascular plants in the Devonian and the rise of conifers and angiosperms in the Mesozoic—to spikes in BEW, suggesting that these biological innovations were pivotal in pulling the planet out of greenhouse states.
The central “13th hypothesis” posits that the magnitude and temporal evolution of BEW can be reliably inferred from a synthesis of empirical and theoretical studies. The meta‑analysis supports this claim by demonstrating consistent scaling relationships across scales and by showing that BEW values of one to two orders of magnitude are robust across independent datasets. The paper argues that current carbon‑cycle models systematically underestimate the strength of the biotic weathering feedback, leading to biased reconstructions of ancient CO₂ levels and climate trajectories.
In addition to presenting the hypothesis, the authors outline future research priorities: (1) developing mechanistic links between microbial‑plant community evolution and BEW, (2) integrating high‑resolution geochemical archives with model parameterizations, and (3) projecting how BEW may respond to contemporary climate change and anthropogenic land‑use alterations. By quantifying BEW and demonstrating its profound influence on atmospheric CO₂ regulation, the study repositions biotic weathering from a peripheral curiosity to a central component of Earth system dynamics, with implications for interpreting past climate events and for predicting future carbon‑climate feedbacks.
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