A curated ecosystem directory mapping regenerative initiatives worldwide. GaiaNet catalogues organizations, communities, regenerative businesses, governance initiatives, land projects, healing modalities, technologies, and aligned contributors across twelve or more domains: housing, food systems, education, governance, technology, healing, community, energy, economics, arts, media, wildlife, and human consciousness.
What it covers
GaiaNet positions itself as “connective intelligence for humanity,” working on the premise that thousands of regenerative initiatives already exist but remain invisible to one another. The ecosystem page is the directory’s public face: a searchable database of initiatives presented in both list and interactive globe formats. The curation team reviews submissions and organizes entries by domain. A monthly field journal circulates stories, opportunities, and practices from across the regenerative sector.
The platform’s operating language is unity, sovereignty, and regeneration. Its scope is global and cross-domain, which distinguishes it from directories organized around a single sector (ecovillages, cooperatives, land trusts) or a single geography.
Editorial approach
GaiaNet uses curated submission. Contributors submit projects through a dedicated form, and the curation team decides what gets listed. This is a different model from the self-declaration directories (the GEN map, for example, where communities create their own profiles). The curation layer means the directory is smaller but more editorially consistent. It also means coverage reflects the curation team’s network and field of vision, so initiatives outside that network’s reach are less likely to appear.
Where its coverage is strongest
The directory spans multiple domains rather than concentrating in any one. Its strongest signal is in the intersection of governance innovation, regenerative economics, and community-scale coordination, areas where the curators have the deepest editorial engagement. Coverage of land-based ecological work (watershed restoration, soil building, fire management) appears thinner than in sector-specific directories like the GEN map or Bioregioning Earth, which organize around ecological geography.
Traffic between GaiaNet and BioConomy
GaiaNet’s ecosystem directory and the BioConomy corpus address adjacent coordination questions from different starting points. GaiaNet aggregates by initiative type and domain. The BioConomy organizes by bioregion and ecological function. A regenerative food cooperative that appears on the GaiaNet directory might, within the BioConomy frame, be a cohort member inside a BioHub, contributing produce data and soil-health metrics to a commitment pool.
The cross-domain breadth of GaiaNet’s directory is its value to the BioConomy corpus. Where this wiki’s two-factory model distinguishes between the financial factory and the ecological factory, GaiaNet’s listings include initiatives operating in both, without making that structural distinction. A coordinator reading both directories sees which GaiaNet-listed projects are doing ecological-factory work (and could therefore participate in bioregional coordination) and which are doing financial-factory reform (and could therefore align with the BioConomy’s transvestment pathways).
BioConomy pages where GaiaNet is relevant include Cosmo-Local Production (many listed initiatives operate on cosmo-local principles), Commitment Pooling (the platform’s connective function mirrors the discovery phase of commitment pooling), and Bioregional Economics (the economics domain within GaiaNet overlaps the corpus’s central concern).
Related pages
- The Two Factories
- BioHub
- BioRegion
- Cosmo-Local Production
- Commitment Pooling
- Bioregional Economics
- Transvestment
- Global Ecovillage Network Map
- Bioregioning Earth
Provenance
Entry created 20 September 2026. Description and domain categories verified against the live ecosystem page on the same date. The mapping of GaiaNet’s directory function onto the BioConomy corpus’s two-factory and commitment-pooling frameworks is the author’s structural inference.