Counterfactual & future simulations
This family includes methods that generate hypothetical or forward-looking scenarios, often by simulating system behavior under altered conditions (e.g. no intervention, future climate).
These methods are often used in climate change attribution, ecosystem projections, or to produce synthetic counterfactuals.
They are grounded in ecological, processes and are used to generate what would happen under different counterfactual or future assumptions.
Overlap: Strongly interacts with Ecology-Guided Modelling (for embedding process knowledge), Causal ML (when learning-based simulators are used), and Adjusted Methods (when outputs are interpreted causally)
Key feature: Focus on “what-if” scenarios
Usage: Used for scenario building, forecasting, or producing synthetic data to compare against real outcomes