Technical Documentation Β· API Reference Β· Field Protocols

CORAL-CORE

Documentation

Complete guide for the physics-computational framework integrating eight biophysical parameters into a single Reef Health Index.

DOI: 10.5281/zenodo.18913829 Python 3.9+ CC BY 4.0 91.4% Accuracy 8 Parameters
v1.0.0 Β· Stable Released: March 8, 2026 14 Reef Systems 22-Year Validation

First unified framework for coral reef health

"Coral reefs are not passive habitats β€” they are active, physics-governed engineering systems with quantifiable input rates, energy conversion efficiencies, structural tolerances, and failure thresholds."

CORAL-CORE is a comprehensive physics-based framework integrating eight governing parameters to decode the extraordinary engineering capacity of stony coral reefs. The framework characterizes coral reefs as self-assembling chemical-mechanical factories converting dissolved calcium ions into hierarchically structured, wave-resistant aragonite architecture.

91.4%
Accuracy
Bleaching prediction
32d
Lead Time
Before visual onset
97%
Dissipation
Wave energy reduction
0.81
rΒ²
Acoustic-recruitment
14
Sites
Global validation
22yr
Dataset
2003-2025

Coral Reefs (Springer)

CORAL-CORE Research Paper
Submitted to Coral Reefs Β· March 8, 2026
Title: CORAL-CORE: Biomineralization Dynamics & Reef Hydro-Acoustic Buffering β€” A Multi-Parameter Physico-Ecological Framework for Real-Time Analysis of Coral Reef Calcification, Wave Energy Dissipation, and Bio-Acoustic Reef Architecture
Author: Samir Baladi
Affiliation: Ronin Institute / Rite of Renaissance
DOI: 10.5281/zenodo.18913829
License: CC BY 4.0
Status: Under review
Keywords: coral biomineralization, wave energy dissipation, zooxanthellae photosynthesis, ocean acidification, reef acoustics, skeletal bulk density, thermal bleaching

Validation performance metrics

91.4%
Bleaching Accuracy
vs 67.3% SST-only
32d
Lead Time
+20d vs baselines
4.2%
False Positive
4.5Γ— reduction
88.1%
Structural Failure
Prediction accuracy
0.81
Recruitment rΒ²
Acoustic prediction
0.89
Calcification rΒ²
Rate prediction

Physical framework

ParameterSymbolWeightDescription
Calcification RateG_ca0.19Power-law saturation kinetics
Wave Energy DissipationE_diss0.14Depth-integrated energy flux
Quantum YieldΦ_ps0.21PAM fluorometry (highest weight)
Skeletal Bulk Densityρ_skel0.12Open-cell foam mechanics
Acidification LagΞ”pH0.11pH-upregulation capacity
Acoustic SignatureS_reef0.1020 Hz – 48 kHz spectrum
Roughness Indexk_s0.083D photogrammetry
Bleaching ThresholdT_thr0.05Adaptive thermal set-point

Composite index

RHI = Ξ£α΅’ wα΅’ Β· Ο†α΅’* where Ξ£wα΅’ = 1.0, Ο†α΅’* ∈ [0, 1] RHI = 0.21Β·Ξ¦ps* + 0.19Β·Gca* + 0.14Β·Ediss* + 0.12·ρskel* + 0.11Β·Ξ”pH* + 0.10Β·Sreef* + 0.08Β·ks* + 0.05Β·Tthr* // Ξ¦ps carries highest weight β€” most sensitive early warning // Tthr carries lowest weight β€” high inter-site variance
β‰₯0.80
HEALTHY
Normal operations
0.50-0.79
STRESSED
Monitor closely
<0.50
CRITICAL
Intervene immediately

Real-time notifications

LevelRHI RangeDescriptionAction
🟒 HEALTHYβ‰₯0.80Normal conditionsRegular monitoring
🟑 STRESSED0.50-0.79Elevated stressMonitor closely
πŸ”΄ CRITICAL<0.50Bleaching imminentIMMEDIATE INTERVENTION
πŸ”₯ BLEACHING<0.50 + Ξ¦ps<0.25Active bleachingEmergency protocols

Quick setup

# Clone repository git clone https://github.com/gitdeeper8/coralcore.git cd coralcore # Install with pip pip install -r requirements.txt pip install -e . # Or using Docker docker-compose up -d # Verify installation python scripts/verify_installation.py

Python interface

calcification_rate()
Calculate calcification rate using power-law kinetics
from coralcore.parameters.calcification import calcification_rate rate = calcification_rate( omega_a=3.4, phi_ps=0.65, temperature=28.0, t_thr=31.5, species='acropora_millepora' ) print(f"Rate: {rate:.3f} mmol/cmΒ²/day")
ReefHealthIndex()
Compute Reef Health Index from eight parameters
from coralcore.rhi.composite import ReefHealthIndex rhi = ReefHealthIndex() params = { 'g_ca': 1.84, 'e_diss': 91.0, 'phi_ps': 0.67, 'rho_skel': 1.62, 'delta_ph': 0.08, 's_reef': 4.3, 'k_s': 0.15, 't_thr': 31.2 } result = rhi.compute(params, return_full=True) print(f"RHI = {result.rhi:.3f} ({result.status})")

Field validation

πŸ‡ͺπŸ‡¬ Ras Mohammed
Red Sea
31d early warning Β· 23% bleaching reduction
πŸ‡¦πŸ‡Ί GBR
Australia
38d before 2016 declaration
πŸ‡§πŸ‡Ώ Lighthouse
Belize
Ξ”pH = 0.18 Β· +0.9Β°C bleaching
πŸ‡¨πŸ‡Ί Jardines
Cuba
Pristine baseline Β· RHI 0.91

Principal investigator

πŸͺΈ

Samir Baladi

Interdisciplinary AI Researcher β€” Marine Biomineralization & Reef Hydro-Acoustics
Ronin Institute / Rite of Renaissance
Samir Baladi is an independent researcher affiliated with the Ronin Institute, developing the Rite of Renaissance interdisciplinary research program. CORAL-CORE is the latest framework in the series, following OPTICLENS (atmospheric optics) and HADEX (hadal zone exploration).
The framework was developed by an independent researcher. Funding: Ronin Institute Independent Scholar Award. No conflicts of interest declared.
πŸ“§ gitdeeper@gmail.com πŸ”— ORCID: 0009-0003-8903-0029 🦊 GitLab πŸ™ GitHub

How to cite

@software{baladi2026coralcore, author = {Baladi, Samir}, title = {CORAL-CORE: Coral Reef Observation \& Assessment Lab β€” Comprehensive Ocean Reef Evaluation}, year = {2026}, version = {1.0.0}, doi = {10.5281/zenodo.18913829}, url = {https://github.com/gitdeeper8/coralcore}, license = {CC BY 4.0} }
Coral reefs are not passive habitats β€” they are active, physics-governed engineering systems with quantifiable input rates, energy conversion efficiencies, structural tolerances, and failure thresholds.

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