A pinboard by
Simon Castillo

PhD student, Pontifical Catholic University of Chile


Understanding population persistence from ecology and mathematics in dynamic landscapes

In a changing world is urgent to develop robust frameworks to understand how populations of animals can persist over space and time. Current approaches have been focused on ecological interactions between species, and independently on the role of animal movement in an ever changing landscape (given that this has strong effects on search of food, mates, and shelter). Here we developed a computational model incorporating these two key paradigms: how species compete for space and how they move and use this habitat with dynamic resources. Our results show that the strategy of searching of an animal can influence its persistence over time, and also it can determine the coexistence with other movement strategies. These results highlight the need to develop a more integrative framework to understand animal population persistence, beyond the traditional approaches used so far.


Reconciling classical and individual-based approaches in theoretical population ecology: a protocol for extracting population parameters from individual-based models.

Abstract: The two main approaches in theoretical population ecology-the classical approach using differential equations and the approach using individual-based modeling-seem to be incompatible. Linked to these two approaches are two different timescales: population dynamics and behavior or physiology. Thus, the question of the relationship between classical and individual-based approaches is related to the question of the mutual relationship between processes on the population and the behavioral timescales. We present a simple protocol that allows the two different approaches to be reconciled by making explicit use of the fact that processes operating on two different timescales can be treated separately. Using an individual-based model of nomadic birds as an example, we extract the population growth rate by deactivating all demographic processes-in other words, the individuals behave but do not age, die, or reproduce. The growth rate closely matches the logistic growth rate for a wide range of parameters. The implications of this result and the conditions for applying the protocol to other individual-based models are discussed. Since in physics the technique of separating timescales is linked to some concepts of self-organization, we believe that the protocol will also help to develop concepts of self-organization in ecology.

Pub.: 25 Sep '08, Pinned: 29 Jun '17