The generalized ideal free distribution model: Merging current ideal free distribution models into a central framework

Density-dependent habitat selection is a central theme in ecology. Empirical studies collect data with increasing resolution and provide greater opportunities for its testing. However, several different density-dependent habitat selection models exist in the literature incorporating many different scenarios. We attempt to unify some of these models in a single framework, to increase our predictive power, and assist researchers in making predictions from combinations of these models. To achieve this, we created the generalized ideal free distribution, an expansion of the ideal free distribution model. With this model, we synthesize many of the previous theoretical developments in habitat selection to better incorporate temporal dynamics. By using community matrices to represent the interaction between individuals, we demonstrated that thirteen scenarios represented in other studies can be combined into a single model. In addition, for four of these scenarios, our predictions are similar to the original studies that developed these scenarios. Additionally, we derived four novel predictions that take advantage of using community matrices to represent distribution. We discuss how this model creates a connection between community interactions and the distribution of individuals, and its uses in other subjects in ecology.