Evolvability Meets Predictive Evolution Theory: A Thought Experiment
Exploring the Convergence of Evolvability and Predictive Evolution Theory (PET): Reconciling Anticipatory Genetic Variation with Dynamic Environmental Feedback Loops
M.C. Escher, ‘Bird Fish’. (1938).
What is Predictive Evolution Theory?
Predictive Evolution Theory (PET) redefines the process of adaptation by proposing that organisms do not merely react to environmental changes; they anticipate them. PET suggests that DNA operates as an electromagnetic antenna, receiving and processing signals from environmental fields—both natural and artificial—encoded in electromagnetic and bioelectric fields. These environmental fields serve as information reservoirs, shaped by cosmic, planetary, and ecological processes, storing and transmitting data about changes in the surroundings.
At its core, PET explains adaptation through a twofold mechanism:
Predictive Signal Reception – Organisms decode incoming electromagnetic signals that carry environmental information.
Variant Generation – Organisms respond by producing a wide array of variants within a single generation, allowing for rapid and precise adaptation to predicted changes.
The theory bridges Frequency Wave Theory (FWT) and Electric Universe Theory (EUT) to describe adaptation as an interplay of resonance, feedback loops, and the exchange of energy and information. Importantly, PET challenges the gradualism of traditional evolutionary models by emphasizing the role of sudden evolutionary leaps and speciation. These leaps occur when environmental shifts trigger organisms to express specific, pre-informed adaptations in their variants, leading to the rapid emergence of new species or traits.
Sudden Evolution and Speciation in PET
One of PET’s most groundbreaking aspects is its explanation of sudden evolutionary events and speciation, bypassing the need for slow, incremental changes. When environmental changes or disruptions occur, DNA—acting as an antenna—interprets signals from the surrounding information reservoirs. This information triggers the generation of diverse variants, each embodying potential solutions to environmental challenges. Some variants may express entirely new traits or forms that enable survival in the altered conditions, effectively driving instantaneous speciation within a single generation.
This mechanism accounts for phenomena like the abrupt appearance of species in the fossil record or the rapid adaptation of organisms to extreme environmental pressures. PET situates this process within a larger framework, where resonance with environmental fields and the dynamic coupling between organisms and their environments drive evolutionary innovation at remarkable speed.
Thought Experiment: Can Evolvability Be Reconciled with PET?
Imagine a hypothetical biosphere where species exist within electromagnetic fields that serve as information reservoirs. These reservoirs encode signals from planetary magnetospheres, solar activity, and interspecies interactions. Over generations, organisms within this biosphere evolve the capacity not only to adapt to immediate environmental challenges but to pre-emptively generate variants suited for predicted changes.
This aligns with the concept of evolvability—the ability of populations to adapt more efficiently over time. A recent study in PNAS demonstrates that even in simulated environments, organisms can evolve an enhanced ability to adapt, fine-tuning their responses across generations. In PET, this "evolving evolvability" would be explained as a refinement of the organism's capacity to decode and process environmental signals from electromagnetic fields.
Harmonizing Evolvability with PET
The key reconciliation lies in understanding the source of adaptive precision. While traditional evolvability emphasizes internal genetic mechanisms shaped by selection, PET suggests that adaptation is driven by external information processed through electromagnetic interaction. Variants in PET are not random but informed by environmental signals, creating a predictive, feedback-rich system.
How Does This Work in Practice?
Variant Generation: PET asserts that every generation of an organism produces numerous variants based on its DNA's ability to resonate with environmental information. Evolvability complements this by explaining how organisms fine-tune their variant-generating capacity over time.
Information Feedback Loops: PET highlights how environmental fields encode dynamic data. As organisms decode this information and adapt, they simultaneously contribute to and refine the environmental reservoir, creating a recursive loop.
Complexity Amplification: Evolvability adds to PET by emphasizing that as these feedback loops mature, the system evolves higher adaptability, accelerating the complexity and diversity of life.
A More Complete Model: PET with Evolvability
Reconciling evolvability with PET results in a superior model of evolution—one where adaptation is not merely reactive but anticipatory and self-refining. By incorporating the principle of evolving adaptability, PET explains the emergence of increasingly complex life forms as a natural consequence of information exchange in bioelectric and electromagnetic fields. Variants, central to PET, become the embodiment of this dynamic process, illustrating how life continuously refines its predictive mechanisms to thrive in a changing cosmos.
References:
Arnold, S. J., & Pfrender, M. E. (2009). "The adaptive landscape as a conceptual bridge between micro- and macroevolution." Evolution, 63(3), 517–527.
Carroll, S. B. (2005). "Endless forms most beautiful: The new science of Evo Devo." W.W. Norton & Company.
Levin, M. (2021). "Bioelectricity: A guide for the perplexed." Frontiers in Physiology.
Longo, G., Montévil, M., & Kauffman, S. (2012). "No entailing laws, but enablement in the evolution of the biosphere." Proceedings of the National Academy of Sciences, 109(15), 5982–5987.
Pigliucci, M. (2008). "Is evolvability evolvable?" Nature Reviews Genetics, 9(1), 75–82.
Ridley, M. (2004). Evolution. Blackwell Publishing.
Shapiro, J. A. (2011). Evolution: A view from the 21st century. FT Press Science.
Singh, V. (2023). "Frequency wave theory and biological adaptation." Journal of Electromagnetic Biology.
Snieder, R. (2007). "A Guided Tour of Mathematical Methods for the Physical Sciences." Cambridge University Press.
Wagner, G. P., & Altenberg, L. (1996). "Complex adaptations and the evolution of evolvability." Evolution, 50(3), 967–976.
Kumawat, B., Lalejini, A., Acosta, M. M., and Zaman, L. (2024). "Evolution takes multiple paths to evolvability when facing environmental change." PNAS.
Pappas, S. (2025). "Evolution itself can evolve, new study argues." Live Science.



