Gravity as a Biological Control Parameter: A Coherence-Based Framework
Abstract
Gravity is one of the most persistent physical conditions experienced by terrestrial life, yet it is rarely treated as an explicit biological variable. In most biological models, gravity is assumed as a static background rather than a governing parameter. This work proposes a coherence-based theoretical framework in which gravity functions as a biological control parameter shaping organism-level function through multi-system integration. Biological function is modeled as a coherence-weighted quantity that depends on gravitational acceleration and metabolic rhythm. Rather than failing through isolated organ dysfunction, organisms exposed to altered gravity are predicted to experience degradation through loss of coordinated coupling among physiological systems. This framing explains the non-linear and threshold-like responses observed in reduced-gravity and spaceflight environments that are not captured by linear or component-based models. The framework introduces a formal Gravity–Life equation that treats biological performance as an emergent property of coupled physiological systems operating within an evolved gravitational regime. From this formulation, falsifiable predictions follow, including the existence of critical gravity thresholds for Earth-evolved life and the expectation that partial gravity environments yield disproportionately reduced organism-level function. This work is purely theoretical. It presents no experimental results and proposes no medical, genetic, or technological interventions. Its purpose is to establish a rigorous conceptual foundation for treating gravity as a fundamental biological parameter, to unify existing observations in space physiology, and to guide future experimental and observational research.
Fields of Study & Subjects
Spaceflight effects on biology
Space Science and Extraterrestrial Life
Physiological and biochemical adaptations
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 14 January 2026
- Document type
- Preprint