PSPManalysis: Steady‐state and bifurcation analysis of physiologically structured population models

Open Access
Authors
Publication date 02-2021
Journal Methods in Ecology and Evolution
Volume | Issue number 12 | 2
Pages (from-to) 383-390
Organisations
  • Faculty of Science (FNWI) - Institute for Biodiversity and Ecosystem Dynamics (IBED)
Abstract

1. How environmental conditions affect the life history of individuals and how these effects shape population and community dynamics on ecological and evolutionary time-scales is a central question in many eco-evolutionary studies.
2. Physiologically structured population models (PSPMs) allow to address this question theoretically as PSPMs are built on a function-based life-history model, which explicitly describes how life history depends on individual traits and environmental factors. PSPMs furthermore explicitly account for population feedback on these environmental factors, which translates into density-dependent effects on life history.
3. PSPManalysis is an R package that allows to simulate ecological dynamics of PSPMs, compute their ecological steady states as a function of model parameters and detect bifurcation points in the computed curves where dynamics change drastically. It furthermore allows for analysing evolutionary dynamics and evolutionary singular states of PSPMs based on Adaptive Dynamics theory. The package only requires a relatively straightforward specification of the life-history functions as input.
4. Compared to dynamic simulations alone, PSPManalysis uses methods from bifurcation analysis to gain a more complete and comprehensive understanding of model behaviour which is much less dependent on particular parameter values or initial model conditions. Given the central role of the individual life history in many studies, there is substantial scope for using PSPManalysis in fields as diverse as ecology, ecotoxicology, conservation biology and evolutionary biology.

Document type Article
Note With supplementary file
Language English
Published at https://doi.org/10.1111/2041-210X.13527
Other links https://www.scopus.com/pages/publications/85096955937
Downloads
2041-210X.13527 (Final published version)
Supplementary materials
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