Creating a full-fledged, real-time, physics-based ecosystem simulation with all the features you described is a highly complex project that would involve significant development effort, including sophisticated simulation engines, AI, genetic algorithms, and rendering systems. It's beyond the scope of what can be fully implemented in a single response, especially within the constraints of a browser environment without native binaries and the need to handle thousands of entities with complex interactions and physics.

However, I can provide a simplified starting point that demonstrates some core concepts: a basic environment, simple entities (plants and herbivores), fundamental interactions (eating, reproduction, death), and visualization using HTML Canvas. This will lay the groundwork and illustrate how such a simulation might be structured.

We will set up a basic simulation with:

• A canvas for visualization.
• A simple Environment class to manage the grid and resources.
• Base Entity and derived Plant and Herbivore classes with basic behaviors.
• A Simulation loop to update the state.
• A Renderer to draw the state on the canvas.

This example will focus on the core loop and basic interactions, omitting complex physics, genetic evolution, advanced AI behaviors, detailed environmental changes, and a comprehensive interactive UI.

This setup provides a basic simulation where blue herbivores move around, eat green plants, reproduce, and die. Plants grow and also reproduce slowly. The counts of each species are displayed.

To expand this into the full simulation you described would require adding:

• More complex species with different behaviors (predators, different herbivores, etc.).
• A more sophisticated environment model (terrain, water, different resource types).
• Detailed state for each entity (thirst, health, specific traits).
• A genetic system for passing traits and allowing adaptation.
• Environmental factors like weather cycles and their impact.
• Collision detection and resolution (beyond just eating range).
• A UI for interaction and data visualization (graphs, controls).
• Significant performance optimizations for large numbers of entities.*

Certainly, let's expand the simulation to include more features, such as predators, a more defined food chain, and a basic environmental factor like temperature.

This expanded version will include:

• Predator species that hunt herbivores.
• Energy mechanics influenced by temperature.
• Basic reproduction and death cycles for predators.
• An input control to change the environment temperature.
• Updated statistics to track predator population.

While building a simulation with thousands of entities, complex physics, and genetic evolution in full is a massive undertaking beyond the scope of a single response and the practical limits of a browser environment without native code, this provides a more complex and interactive ecosystem model.

This expanded version introduces a predator-prey dynamic and a simple environmental control (temperature) that affects the animals' energy levels. You can observe how changing the temperature impacts the survival rates and population sizes.

To further build upon this towards the full vision, you would need to add:

• More complex movement and AI (e.g., fleeing predators, pathfinding).
• Genetic traits and inheritance.
• More detailed environmental factors (weather, terrain, resources).
• Different species with unique behaviors.
• A more robust physics system if needed (though simple collision/interaction is often sufficient for ecosystem sims).
• Advanced visualization and data tracking (graphs, heatmaps, etc.).
• Optimization techniques for handling thousands of entities efficiently (e.g., spatial partitioning beyond a simple grid, WebAssembly for core logic).