Planetary Information Network Theory (PINT): A Theoretical Framework for Interpreting the Biosphere as a Planetary Information System

Planetary Information Network Theory (PINT) proposes a conceptual framework for interpreting the Earth's biosphere as a distributed planetary information system. Within this framework, ecosystems, conscious agents, and technological infrastructures are understood as interconnected components of a dynamic informational network operating at planetary scale. Ecosystems function as the biological informational substrate of the network, storing and transforming information through ecological structure, biodiversity, trophic interactions, and biogeochemical cycles. Conscious organisms—particularly humans—act as advanced cognitive nodes capable of perceiving, integrating, and interpreting environmental information. Technological systems such as digital communication networks, satellite infrastructures, environmental monitoring systems, and artificial intelligence further amplify the informational capacity of the biosphere. A central concept of PINT is Planetary Information Feedback, describing recursive feedback loops between ecosystems, cognition, and technological systems. While currently conceptual in nature, the framework proposes that the Earth's biosphere may be understood as an evolving informational network whose complexity increases through biological evolution, cognitive development, and technological expansion.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-07
DOI
https://doi.org/10.5281/zenodo.18900104
Primary Topic
Space Science and Extraterrestrial Life
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Planetary Information Network Theory (PINT): A Theoretical Framework for Interpreting the Biosphere as a Planetary Information System

Daniel E. Larsow
Zenodo (CERN European Organization for Nuclear Research)
Space Science and Extraterrestrial Life
article

Planetary Information Network Theory (PINT): A Theoretical Framework for Interpreting the Biosphere as a Planetary Information System

Daniel E. Larsow
article en

Abstract

Planetary Information Network Theory (PINT) proposes a conceptual framework for interpreting the Earth's biosphere as a distributed planetary information system. Within this framework, ecosystems, conscious agents, and technological infrastructures are understood as interconnected components of a dynamic informational network operating at planetary scale. Ecosystems function as the biological informational substrate of the network, storing and transforming information through ecological structure, biodiversity, trophic interactions, and biogeochemical cycles. Conscious organisms—particularly humans—act as advanced cognitive nodes capable of perceiving, integrating, and interpreting environmental information. Technological systems such as digital communication networks, satellite infrastructures, environmental monitoring systems, and artificial intelligence further amplify the informational capacity of the biosphere. A central concept of PINT is Planetary Information Feedback, describing recursive feedback loops between ecosystems, cognition, and technological systems. While currently conceptual in nature, the framework proposes that the Earth's biosphere may be understood as an evolving informational network whose complexity increases through biological evolution, cognitive development, and technological expansion.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 33%
Space Science and Extraterrestrial Life
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.