R package for modelling stage-structured populations
StagePop is a tool for predicting the deterministic dynamics and interactions of stage-structured populations (i.e. where the life cycle consists of distinct stages, for example eggs, juveniles and reproductive adults) using a continuous time formulation.
What does stagePop do?
For a full description of stagePop's capability see Kettle and Nutter 2015 (and the supporting information); a brief overview is given below.
- stagePop simulates the dynamics and interactions of multiple populations by solving a system of time-delay ordinary differential equations that are constructed automatically based on a description of the system.
- The system can consist of any number of interacting species which may or may not have stage structure.
- The continuous-time formulation enables stagePop to easily simulate time-varying stage durations, overlapping generations and density-dependent vital rates.
- The package can be used to predict predator-prey interactions, host-parasitoid interactions, resource competition, intra-specific competition and the effects of environmental change on stage-structured (and non stage-structured) species.
- It can be used for predicting the effects of bio-control and climate change, investigating mechanisms for maintaining diversity, predicting the dynamics of complex food webs following perturbation and so on.
- The code is based on the formulation by Nisbet and Gurney (Theoretical Population Biology, 23, 1983, 114) using delay-differential equations, which are solved using the R packages deSolve or PBSddesolve.
What is it?
How do I install it?
To use stagePop simply download R and when in R type install.packages('stagePop').
Testimonials for stagePop
"Although there are many packages available for systems with DDEs that have fixed time delays, there are none known to me that focus on the particular, and challenging, form of DDE with time dependent delays that occur in stage structured population dynamics. R is increasingly the default environment used by ecologists for both modeling and statistics, so it should prove accessible to many researchers (especially graduate students) with sufficient mathematical expertize to formulate and interpret the models, but without the skill to program the systems of equations reliably." -- Roger Nisbet
"The package appears to be extremely versatile in that it allows multiple scenarios of varying complexity to be modelled, and I congratulate the authors for making the complicated functions accessible to a broad user community by preparing a well-documented package"-- anonymous reviewer