Publication Details
Category Text Publication
Reference Category Journals
DOI 10.1111/2041-210X.13683
Licence creative commons licence
Title (Primary) ipmr: Flexible implementation of Integral Projection Models in R
Author Levin, S.C.; Childs, D.Z.; Compagnoni, A.; Evers, S.; Knight, T.M.; Salguero-Gómez, R.
Source Titel Methods in Ecology and Evolution
Year 2021
Department BZF; iDiv
Volume 12
Issue 10
Page From 1826
Page To 1834
Language englisch
Topic T5 Future Landscapes
Data and Software links https://doi.org/10.5281/zenodo.5095062
Supplements https://besjournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F2041-210X.13683&file=mee313683-sup-0001-Case1.pdf
https://besjournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F2041-210X.13683&file=mee313683-sup-0002-Case2.pdf
https://besjournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F2041-210X.13683&file=mee313683-sup-0003-Supinfo.pdf
Keywords elasticity, integral projection model, life history, population dynamics, population growth rate, sensitivity, structured populations
Abstract
  • 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, analyzing, and interpreting IPMs.
  • 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.
  • 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).
  • 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.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=24909
Levin, S.C., Childs, D.Z., Compagnoni, A., Evers, S., Knight, T.M., Salguero-Gómez, R. (2021):
ipmr: Flexible implementation of Integral Projection Models in R
Methods Ecol. Evol. 12 (10), 1826 - 1834 10.1111/2041-210X.13683