Final answer:
Using simulation to solve complex problems that are challenging to address analytically is indeed true. Simulation models are ideal for complex systems, like ecosystems, by providing a dynamic platform for understanding and visualization that goes beyond the capabilities of analytical modeling.
Step-by-step explanation:
The statement that simulation should be used for solving large and complex problems that cannot be solved analytically is true. Simulations are beneficial in circumstances where analytical models fall short due to the complexity or size of the problem. For example, ecosystems comprise numerous interacting components that make analytical solutions difficult. Additionally, computer simulations allow for the visualization of complex systems and handling non-linear dynamics which are common in real-world scenarios.
Analytical models rely on mathematical equations and can simplify complex systems, but this can lead to limitations in accuracy. Conversely, simulation modeling is well-suited to capture the intricacies of such systems and can make use of large data sets and compute calculations that would be impractical manually. It's also worth noting that while experiments provide valuable insights into cause-and-effect relationships, simulations can offer a risk-free environment for testing hypotheses that may not be feasible or ethical in real-world experiments.
Therefore, while analytical methods have their place, particularly where problems are simpler and linear, simulation models are indispensable tools for exploring the complexities of large-scale or complex systems that defy straightforward analytical approaches.