Tectonic forcing of global chemical weathering since the mid-Paleozoic
Bibliographic record
Abstract
Weathering of the Earth’s surface has commonly been invoked as a driver of global cooling through geologic time. During the Phanerozoic Eon (541–0 million years ago, Ma), for example, the periodic onset of icehouse conditions has variously been attributed to enhanced weathering fluxes associated with mountain building (e.g. the Himalayas) (1), reductions in the global extent of continental arc volcanoes (e.g. the present-day Andes) (2), and uplift of oceanic crust during arc-continent collisions (e.g. present-day Indonesia and New Guinea) (3). These processes, tied to the global plate tectonic cycle, are inextricably linked. The resulting collinearity (i.e. independent variables are highly correlated) makes it difficult — using conventional statistical techniques — to isolate the contributions of individual geologic processes to global chemical weathering. An example of this is the Late Cenozoic Ice Age (34–0 Ma) that corresponds both to uplift of the Tibetan Plateau and Himalaya, and a gradual reduction in the extent of the global continental arc system. We developed a machine learning framework to analyse the interdependencies between multiple global tectonic and volcanic processes (e.g., continental distribution, extent of volcanic arcs, mid-ocean ridges etc.) and seawater Sr composition (a proxy for weathering flux) over the past 400 million years. We developed a Bayesian network incorporating a novel algorithm that accounts for time lags for each of the predictor variables, and joint conditional dependence (i.e. how variables combine to influence the environmental outcome). Our approach overcomes problems traditionally encountered in geologic time series, such as collinearity and autocorrelation. Our results strongly indicate a first-order role for volcanism in driving chemical weathering fluxes since the mid-Palaeozoic. This is consistent with the strong empirical correlation previously observed between the strontium isotope composition of seawater and continental igneous rocks over the past billion years (4). Our study highlights how geologic processes operate together — not in isolation — to perturb the Earth system over ten to hundred million-year timescales. References (1). M. E. Raymo, W. F. Ruddiman, Tectonic forcing of late Cenozoic climate, Nature 359, 117 (1992). (2). N. R. McKenzie, et al., Continental arc volcanism as the principal driver of icehouse greenhouse variability, Science 352, 444 (2016). (3). F. A. Macdonald, N. L. Swanson-Hysell, Y. Park, L. Lisiecki, O. Jagoutz, Arc-continent collisions in the tropics set Earth’s climate state, Science 364, 181 (2019). (4). C. P. Bataille et al., Continental igneous rock composition: A major control of past global chemical weathering, Science Advances 3, e1602183 (2017).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".