Demographic processes in socially structured populations

2021 ◽  
pp. 341-350
Author(s):  
Maria Paniw ◽  
Gabriele Cozzi ◽  
Stefan Sommer ◽  
Arpat Ozgul

In socially structured animal populations, vital rates such as survival and reproduction, are affected by complex interactions among individuals of different social ranks and among social groups. Due to this complexity, mechanistic approaches to model vital rates may be preferred over commonly used structured population models. However, mechanistic approaches come at a cost of increased modelling complexity, computational requirements, and reliance on simulated metrics, while structured population models are analytically tractable. This chapter compares different approaches to modelling population dynamics of socially structured populations. It first simulates individual-based data based on the life cycle of a hypothetical cooperative breeder and then projects population dynamics using a matrix population model (MPM), an integral projection model (IPM), and an individual-based model (IBM). The authors demonstrate that, when projecting population size or structure, the relatively simpler MPM can outperform both the IPM and IBM. However, mechanistic details parametrised in the more complex IBM are required to accurately project interactions within social groups. The R scripts in this chapter provide a roadmap to both simulate data that best describe a socially structured system and assess the level of model complexity needed to capture the dynamics of the system.

2001 ◽  
Vol 43 (2) ◽  
pp. 157-189 ◽  
Author(s):  
O. Diekmann ◽  
M. Gyllenberg ◽  
H. Huang ◽  
M. Kirkilionis ◽  
J.A.J. Metz ◽  
...  

2014 ◽  
Vol 24 (11) ◽  
pp. 2171-2197 ◽  
Author(s):  
J. A. Carrillo ◽  
P. Gwiazda ◽  
A. Ulikowska

We propose a new numerical scheme designed for a wide class of structured population models based on the idea of operator splitting and particle approximations. This scheme is related to the Escalator Boxcar Train (EBT) method commonly used in biology, which is in essence an analogue of particle methods used in physics. Our method exploits the split-up technique, thanks to which the transport step and the nonlocal integral terms in the equation can be separately considered. The order of convergence of the proposed method is obtained in the natural space of finite non-negative Radon measures equipped with the flat metric. This convergence is studied even adding reconstruction and approximation steps in the particle simulation to keep the number of approximation particles under control. We validate our scheme in several test cases showing the theoretical convergence error. Finally, we use the scheme in situations in which the EBT method does not apply showing the flexibility of this new method to cope with the different terms in general structured population models.


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