Do simple models lead to generality in ecology?

Area of Science:

• Ecological modeling
• Systems biology
• Environmental science

Background:

• The prevailing view in ecological and environmental modeling is that simpler models are more general and thus superior.
• This 'simple means general' maxim may hinder scientific progress by limiting the scope and depth of ecological research.

Purpose of the Study:

• To challenge the assumption that simplicity is the only route to generality in ecological modeling.
• To demonstrate the value and generality of complex models in ecological research.
• To propose a framework for integrating simple and complex models for enhanced understanding.

Main Methods:

• Conceptual argument and synthesis of existing modeling approaches.
• Illustrative examples of how complex models can achieve generality.
• Framework for linking diverse model complexities.

Main Results:

• Complex models can be both desirable and general, offering unique insights.
• Integrating simple and complex models can lead to broader-scale understanding.
• A hybrid approach enhances predictive capabilities in ecological systems.

Conclusions:

• Rethinking the 'simple means general' paradigm is crucial for advancing ecological research.
• Complex models are valuable tools for achieving generality and predictive power.
• Linking models of varying complexity provides a robust strategy for systems-level understanding.