An AI-powered ecosystem modeling platform that simulates species reintroduction and predicts long-term ecological outcomes using Monte Carlo simulations, climate scenarios, and food-web interactions.
Rewilding Impact Simulator is an interactive web application that enables users to explore ecosystems around the world and evaluate the impact of reintroducing extinct species into existing habitats. The simulator models population dynamics, species interactions, climate change effects, uncertainty, and ecosystem stability to generate data-driven recommendations for conservation strategies.
- 🌎 Explore different regions and ecosystems
- 🦣 Reintroduce extinct species into existing habitats
- 📈 Run Monte Carlo ecosystem simulations
- 🌡️ Simulate multiple climate scenarios
- 🌿 Analyze population trajectories over time
- 📊 Visualize uncertainty bands and survival probabilities
- 🕸️ Generate food-web interaction graphs
- 💚 Evaluate ecosystem health and stability
- 🤖 Produce recommendation messages for conservation planning
- 🔬 Validate simulations using historical case studies
- ⚙️ Inspect the complete simulation pipeline
- React 18
- TypeScript
- Vite
- Tailwind CSS
- React Router DOM
- Framer Motion
- Recharts
- Lucide React
- TanStack Query
- Vitest
- Playwright
src/
│
├── pages/ # Application pages
├── components/ # UI Components
├── components/ui/ # Reusable UI elements
├── lib/ # Core simulation logic
├── regionsData.ts # Ecosystem and species datasets
├── simulationEngine.ts # Monte Carlo simulation engine
├── recommendationEngine.ts
├── dataPipeline.ts
└── validationScenarios.ts
Users browse regions and ecosystems and select species already present in the habitat.
Extinct species can be added to the ecosystem to simulate rewilding scenarios.
The platform models:
- Birth and death rates
- Carrying capacity
- Climate adaptation
- Species interactions
- Competition and predation
- Environmental noise
- Extreme climate events
- Genetic fitness
using Monte Carlo simulations.
The simulator generates:
- Population trends
- Survival probabilities
- Ecosystem health scores
- Stability metrics
- Trophic interactions
- Conservation recommendations
Models species populations over time using:
- Logistic growth
- Interaction coefficients
- Climate survival modifiers
- Environmental noise
- Allee effects
Supports future climate projections and temperature changes to analyze ecosystem resilience.
Automatically generates trophic interactions including:
- Predation
- Competition
- Ecosystem relationships
Multiple Monte Carlo runs provide:
- Confidence intervals
- Uncertainty bands
- Survival probabilities
Generates AI-assisted conservation strategies based on:
- Ecosystem stability
- Population viability
- Climate conditions
- Species survival probability
Includes scenario-based validation using historical ecological restoration examples such as:
- Yellowstone Wolf Reintroduction
This allows comparison between simulated and known ecological outcomes.
The platform provides:
- Population charts
- Ecosystem health metrics
- Food-web graphs
- Survival probability analysis
- Recommendation panels
- Data pipeline visualizations
- Monte Carlo Simulation
- Logistic Population Growth
- Species Interaction Modeling
- Trophic Network Analysis
- Climate-Aware Population Dynamics
- Ecosystem Stability Assessment
- Recommendation Generation
Clone the repository:
git clone https://github.com/yourusername/rewilding-impact-simulator.gitInstall dependencies:
npm installRun locally:
npm run devBuild for production:
npm run build- Graph Neural Networks for food-web analysis
- Real biodiversity datasets integration
- Satellite and climate data APIs
- Multi-agent ecosystem modeling
- Reinforcement learning for conservation optimization
- Species migration simulations
- Genetic evolution and adaptation modules
- AI-powered policy recommendation system
Divya Dahiya
B.Tech Biotechnology — SRM Institute of Science and Technology
Focused on biotechnology, life sciences, and sustainable ecosystem and conservation solutions.
Harshit Chaturvedi
B.Tech Computer Science and Engineering — SRM Institute of Science and Technology
Focused on software development, artificial intelligence, and building technology-driven solutions for real-world problems.