bioRxivEcologyPreprint
ipmr: Flexibly implement Integral Projection Models in R
S. C. Levin, D. Z. Childs, A. Compagnoni, S. Evers, T. Knight, R. Salguero-Gomez
Abstract
O_LIIntegral projection models (IPMs) are an important tool for studying the dynamics of populations structured by one or more continuous traits (e.g. size, height, color). Researchers use IPMs to investigate questions ranging from linking drivers to plant 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. C_LIO_LIThe 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 ipmrs flexibility to model complex life cycles and demographic processes. C_LIO_LIipmr can handle a wide variety of models, including 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). C_LIO_LIipmr 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. C_LI
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Rpadrino: an R package to access and use PADRINO, an open access database of Integral Projection Models
S. C. Levin, S. Evers, … R. Salguero-Gomez·bioRxiv·Mar 2, 2022
- Integrated integral population models
P. Portillo-Tzompa, P. R. Martin-Cornejo, E. J. Gonzalez·bioRxiv·Oct 24, 2023
- Integration of individual and population data to improve predictions of structured population dynamics
Malcolm S. Itter·bioRxiv·Aug 3, 2026
- Towards robust evolutionary inference with integral projection models
Maria Joao Janeiro, Marco Festa-Bianchet, … Michael B Morrissey·bioRxiv·Aug 29, 2016
- Individual-based Integral Projection Models: The role of size-structure on extinction risk and establishment success
Sebastian Schreiber, Noam Ross·bioRxiv·Oct 15, 2015
- Improving Joint Estimation of Vital Rates in IPMs via Gaussian Processes and ABC
Zhixiao Zhu, Maria D. Christodoulou, David Steinsaltz·bioRxiv·Jul 2, 2025