Metadata-Version: 2.4
Name: fungi-mycel
Version: 1.0.0
Summary: FUNGI-MYCEL: A Quantitative Framework for Decoding Mycelial Network Intelligence
Home-page: https://gitlab.com/gitdeeper07/fungi-mycel
Author: Samir Baladi
Author-email: Samir Baladi <gitdeeper@gmail.com>
Maintainer: Samir Baladi
Maintainer-email: gitdeeper@gmail.com
License: MIT
Project-URL: Homepage, https://fungi-mycel.netlify.app
Project-URL: Documentation, https://fungi-mycel.readthedocs.io
Project-URL: Repository, https://gitlab.com/gitdeeper07/fungi-mycel
Project-URL: Bug Tracker, https://gitlab.com/gitdeeper07/fungi-mycel/-/issues
Project-URL: DOI, https://doi.org/10.14293/FUNGI-MYCEL.2026.001
Keywords: mycology,fungal-intelligence,mycelial-networks,bioelectricity,wood-wide-web,mycorrhiza,ecology,machine-learning
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: author
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python

<div align="center">

# 🍄 FUNGI-MYCEL

### *The Intelligence of Living Networks*

**Fungal Intelligence & Mycelial Communication Engineering:**
*Natural Yield & Ecological Logic*

> *A Quantitative Framework for Decoding Mycelial Network Intelligence, Bioelectrical Communication, and Sub-Surface Ecological Sovereignty*

[![DOI](https://img.shields.io/badge/DOI-10.14293%2FFUNGI--MYCEL.2026.001-blue?style=flat-square)](https://doi.org/10.14293/FUNGI-MYCEL.2026.001)
[![Submitted To](https://img.shields.io/badge/Submitted%20To-Nature%20Microbiology-green?style=flat-square)](https://www.nature.com/nmicrobiol/)
[![Dashboard](https://img.shields.io/badge/Live%20Dashboard-netlify-orange?style=flat-square)](https://fungi-mycel-science.netlify.app)
[![GitLab](https://img.shields.io/badge/GitLab-Repository-FC6D26?style=flat-square&logo=gitlab)](https://gitlab.com/gitdeeper07/fungi-mycel)
[![GitHub](https://img.shields.io/badge/GitHub-Mirror-181717?style=flat-square&logo=github)](https://github.com/gitdeeper07/fungi-mycel)
[![ORCID](https://img.shields.io/badge/ORCID-0009--0003--8903--0029-A6CE39?style=flat-square&logo=orcid)](https://orcid.org/0009-0003-8903-0029)

</div>

---

## 📋 Table of Contents

- [Abstract](#-abstract)
- [Key Results](#-key-quantitative-results)
- [Framework Overview](#-framework-overview)
- [The Eight Parameters](#-the-eight-parameters)
- [Dataset](#-dataset)
- [Research Hypotheses](#-research-hypotheses)
- [Live Dashboard](#-live-dashboard)
- [Repository Structure](#-repository-structure)
- [Citation](#-citation)
- [Author](#-author)

---

## 🌿 Abstract

**FUNGI-MYCEL** introduces the first mathematically rigorous, AI-integrated multi-parameter framework for the quantitative characterization of mycelial network intelligence — the **Mycelial Network Intelligence Score (MNIS)**.

Built on eight orthogonal bio-physical indicators spanning mineral weathering efficiency, adaptive resilience, bioelectrical pulse density, chemotropic navigation, symbiotic exchange fidelity, topological fractal expansion, rhizospheric biodiversity amplification, and biological field stability — FUNGI-MYCEL elevates the study of fungal networks from descriptive mycology to rigorous systems science.

We advance the foundational proposition that **mycelium is not merely a collection of threads, but a distributed computational substrate** — a living intelligence that processes environmental data through bioelectrical spike trains, executes adaptive decisions through branching topology, and communicates ecosystem-wide state through chemical gradients and electrical pulses propagating at speeds of **0.5–5 mm/second** across networks spanning hectares.

The framework is validated against a dataset of **2,648 mycelial network units (MNUs)** spanning 39 protected forest sites across five biome categories, sampled over a **19-year observational period (2007–2026)**.

---

## 📊 Key Quantitative Results

| # | Metric | Result |
|---|--------|--------|
| ① | MNIS Prediction Accuracy | **91.8%** (39-site cross-validation, 19 years) |
| ② | Bioelectrical Stress Detection Rate | **94.3%** · False Alert Rate: 4.2% |
| ③ | Mean Early Warning Lead Time | **42 days** before above-ground symptom expression |
| ④ | ρ_e × K_topo Network Intelligence Index | **r = +0.917** (p < 0.001, n = 2,648 MNUs) |
| ⑤ | η_NW Mineral Dissolution Rate | **0.48–2.3 μg** mineral·cm⁻² hyphae·day⁻¹ |
| ⑥ | SER Symbiotic Exchange Fidelity | **87.4%** of host-fungal nutrient transactions within ±12% of predicted optimal stoichiometry |
| ⑦ | ABI Biodiversity Amplification Ratio | H′_rhizosphere = **1.84 ×** H′_bulk soil (mean) |
| ⑧ | BFS Field Stability Half-Time | **τ₁/₂ = 4.1 ± 0.7 years** post-disturbance |
| ⑨ | Dataset Scale | **2,648 MNUs · 39 sites · 5 biomes · 19 years** |

---

## 🧠 Framework Overview

FUNGI-MYCEL is to mycelial biology what the IBR index is to above-ground ecosystem health — a single dimensionless number that encodes the functional state of a complex living system with sufficient precision to guide intervention and forecast ecological outcomes.

```
MNIS = f(η_NW, ρ_e, ∇C, SER, K_topo, ABI, BFS, ARC)
       ────────────────────────────────────────────────
       Composite Intelligence Score ∈ [0, 1]
```

The framework advances through four scientific eras:

| Era | Period | Contribution |
|-----|--------|-------------|
| Morphological | 1860–1950 | Hyphal architecture as information infrastructure |
| Biochemical | 1950–1990 | Quantitative stoichiometry of carbon-phosphorus exchange |
| Bioelectrical | 1990–2015 | Action-potential-like signals in mycelial networks |
| Systems Intelligence | 2015–present | AI-assisted decoding of network-scale information processing |

---

## 🔬 The Eight Parameters

| Parameter | Symbol | Description |
|-----------|--------|-------------|
| Mineral Weathering Efficiency | **η_NW** | Rate of mineral dissolution per unit hyphal surface area |
| Bioelectrical Pulse Density | **ρ_e** | Frequency and structure of electrical spike trains per network node |
| Chemotropic Navigation Gradient | **∇C** | Directional accuracy of hyphal tip navigation toward resource targets |
| Symbiotic Exchange Ratio | **SER** | Fidelity of host-fungal nutrient transactions to predicted optimal stoichiometry |
| Topological Fractal Dimension | **K_topo** | Fractal expansion coefficient encoding carbon sequestration efficiency |
| Adaptive Biodiversity Index | **ABI** | Rhizospheric biodiversity amplification ratio relative to bulk soil |
| Biological Field Stability | **BFS** | Post-disturbance network recovery half-time |
| Adaptive Resilience Coefficient | **ARC** | Network response plasticity under environmental stress gradients |

---

## 🌍 Dataset

```
2,648 Mycelial Network Units (MNUs)
├── 39 Protected Forest Sites
├── 5 Biome Categories
│   ├── Temperate Broadleaf
│   ├── Boreal Conifer
│   ├── Tropical Montane
│   ├── Mediterranean Woodland
│   └── Sub-Arctic Birch
└── 19-Year Observational Period (2007–2026)
```

**Analytical Methods:**
- In-situ microelectrode arrays (bioelectrical recording)
- Scanning electron microscopy (hyphal morphology)
- Mass spectrometry (mineral weathering products)
- Environmental DNA metabarcoding (rhizospheric microbiome)
- Hyperspectral soil mapping

---

## 🧪 Research Hypotheses

| ID | Hypothesis | Test Method |
|----|-----------|-------------|
| H1 | MNIS prediction accuracy > 90% across all five biome types | Leave-one-site cross-validation, 39 sites |
| H2 | ρ_e × K_topo correlation r > 0.90 | Microelectrode recordings vs. fractal dimension from confocal imaging |
| H3 | η_NW weathering rate varies >10× between intact and degraded networks | ICP-MS mineral dissolution assays at 156 rhizosphere sampling points |
| H4 | SER deviation > 25% at sites with AES encroachment score > 0.55 | ¹³C/³¹P isotope tracing at 87 paired root-mycelium interfaces |
| H5 | ∇C navigates hyphae within ±8° of optimal trajectory (p<0.001) | Time-lapse confocal microscopy, 2,400 hyphal tip tracking events |
| H6 | ABI ratio H′_rhizo/H′_bulk > 1.5 at all intact sites | 16S eDNA sequencing, 312 paired rhizosphere/bulk soil samples |
| H7 | BFS half-time τ correlates with K_topo at disturbance (r > 0.75) | 23 documented post-fire/logging sites with sequential monitoring |
| H8 | AI ensemble MNIS exceeds single-parameter ρ_e prediction by >12% | Model ablation study, 397 held-out MNU-years |

---

## 🖥️ Live Dashboard

Explore the data interactively at:

**[fungi-mycel-science.netlify.app](https://fungi-mycel-science.netlify.app)**

---

## 📁 Repository Structure

```
fungi-mycel/
├── 📄 README.md
├── 📊 data/
│   ├── mnu_dataset/          # 2,648 MNU records across 39 sites
│   ├── bioelectrical/        # Microelectrode array recordings
│   ├── hyphal_morphology/    # SEM image datasets
│   └── rhizosphere_edna/     # 16S metabarcoding sequences
├── 🧮 models/
│   ├── mnis_core/            # Core MNIS scoring engine
│   ├── ai_ensemble/          # AI prediction models
│   └── ablation_study/       # H8 model comparison experiments
├── 📈 analysis/
│   ├── cross_validation/     # 39-site leave-one-out validation
│   ├── hypothesis_tests/     # H1–H8 statistical analyses
│   └── biome_comparisons/    # Cross-biome MNIS distributions
├── 🌐 dashboard/
│   └── src/                  # Netlify dashboard source
├── 📝 paper/
│   └── FUNGI-MYCEL_Research_Paper.docx
└── 📋 supplementary/
    └── methods/              # Extended analytical protocols
```

---

## 📖 Citation

```bibtex
@article{baladi2026fungiMycel,
  title     = {FUNGI-MYCEL: A Quantitative Framework for Decoding Mycelial Network Intelligence, 
               Bioelectrical Communication, and Sub-Surface Ecological Sovereignty},
  author    = {Baladi, Samir},
  journal   = {Nature Microbiology (Submitted)},
  year      = {2026},
  month     = {March},
  doi       = {10.14293/FUNGI-MYCEL.2026.001},
  type      = {Original Research Framework}
}
```

---

## 👤 Author

<table>
<tr>
<td>

**Samir Baladi** ✦ *Principal Investigator*

📍 Ronin Institute / Rite of Renaissance
🔬 Interdisciplinary AI Researcher — Fungal Intelligence & Ecological Systems Division

[![Email](https://img.shields.io/badge/Email-gitdeeper%40gmail.com-D14836?style=flat-square&logo=gmail)](mailto:gitdeeper@gmail.com)
[![ORCID](https://img.shields.io/badge/ORCID-0009--0003--8903--0029-A6CE39?style=flat-square&logo=orcid)](https://orcid.org/0009-0003-8903-0029)
[![GitLab](https://img.shields.io/badge/GitLab-gitdeeper07-FC6D26?style=flat-square&logo=gitlab)](https://gitlab.com/gitdeeper07)
[![GitHub](https://img.shields.io/badge/GitHub-gitdeeper07-181717?style=flat-square&logo=github)](https://github.com/gitdeeper07)

*Corresponding Author*

</td>
</tr>
</table>

---

## 🔗 Related Projects

| Project | Description | Link |
|---------|-------------|------|
| **BIOTICA** | Integrated Biotic Resilience Index (IBR) — above-ground ecosystem health | [`@gitdeeper07/biotica`](https://gitlab.com/gitdeeper07) |
| **AEROTICA** | Aerial & atmospheric ecological sensing framework | [`@gitdeeper07/aerotica`](https://gitlab.com/gitdeeper07/aerotica) |

---

<div align="center">

*"There is a brain beneath every forest. FUNGI-MYCEL makes it visible."*

🍄 · **FUNGI-MYCEL** · March 2026 · DOI: [10.14293/FUNGI-MYCEL.2026.001](https://doi.org/10.14293/FUNGI-MYCEL.2026.001)

</div>
