Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/73841
Title: ipmr : flexible implementation of integral projection models in R
Author(s): Levin, Sam C.
Childs, Dylan Z.
Compagnoni, Aldo
Evers, Sanne
Knight, Tiffany M.
Salguero-Gómez, Roberto
Issue Date: 2021
Type: Article
Language: English
Abstract: 1. Integral projection models (IPMs) are an important tool for studying the dynamics of populations structured by one or more continuous traits (e.g. size, height, body mass). Researchers use IPMs to investigate questions ranging from linking drivers to population dynamics, planning conservation and management strategies, and quantifying selective pressures in natural populations. The popularity of stage-structured population models has been supported by R scripts and packages (e.g. IPMpack, popbio, popdemo, lefko3) aimed at ecologists, which have introduced a broad repertoire of functionality and outputs. However, pressing ecological, evolutionary and conservation biology topics require developing more complex IPMs, and considerably more expertise to implement them. Here, we introduce ipmr, a flexible R package for building, analysing and interpreting IPMs. 2. The ipmr framework relies on the mathematical notation of the models to express them in code format. Additionally, this package decouples the model parameterization step from the model implementation step. The latter point substantially increases ipmr's flexibility to model complex life cycles and demographic processes. 3. ipmr can handle a wide variety of models, including those that incorporate density dependence, discretely and continuously varying stochastic environments, and multiple continuous and/or discrete traits. ipmr can accommodate models with individuals cross-classified by age and size. Furthermore, the package provides methods for demographic analyses (e.g. asymptotic and stochastic growth rates) and visualization (e.g. kernel plotting). 4. ipmr is a flexible R package for integral projection models. The package substantially reduces the amount of time required to implement general IPMs. We also provide extensive documentation with six vignettes and help files, accessible from an R session and online.
URI: https://opendata.uni-halle.de//handle/1981185920/75793
http://dx.doi.org/10.25673/73841
Open Access: Open access publication
License: (CC BY-NC 4.0) Creative Commons Attribution NonCommercial 4.0(CC BY-NC 4.0) Creative Commons Attribution NonCommercial 4.0
Sponsor/Funder: Publikationsfonds MLU
Journal Title: Methods in ecology and evolution
Publisher: Wiley
Publisher Place: Oxford [u.a.]
Volume: 12
Issue: 10
Original Publication: 10.1111/2041-210X.13683
Page Start: 1826
Page End: 1834
Appears in Collections:Open Access Publikationen der MLU