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isotracer: an R package for the analysis of tracer addition experiments

Isotope tracer addition experiments are used to answer a wide variety of biological, ecological and evolutionary questions. In these experiments, a labeled element is injected into a biological system and its fate is traced throughout the system to estimate the flux of matter across compartments. Tracer additions can be used across all levels of biological organization from cells and tissues, to organisms and ecosystems. The isotracer package provides tools to analyze data from such experiments.

Getting started

The recommended way to install the package is to get the latest version from CRAN:

install.packages("isotracer")

The documentation for the latest stable version is available online. Start with the Quick Start tutorial!

If you are feeling adventurous, you might want to install the latest development version from GitLab. It might have new features that the stable version on CRAN doesn’t have yet, but it might also be less stable:

devtools::install_gitlab("matthieu-bruneaux/isotracer")

How to cite the package

Running citation("isotracer") will return two references you can use if you want to cite isotracer.

The first reference is the paper describing the original method:

López-Sepulcre A, Bruneaux M, Collins SM, El-Sabaawi R, Flecker AS, Thomas SA (2020). “A new method to reconstruct quantitative food webs and nutrient flows from isotope tracer addition experiments.” The American Naturalist, 195(6), 964-985. doi: 10.1086/708546 (URL: https://doi.org/10.1086/708546).

The second reference is the paper introducing isotracer itself:

Bruneaux M, López-Sepulcre A (2022). “isotracer: An R package for the analysis of tracer addition experiments.” Methods in Ecology and Evolution, 13(5), 1119-1134. doi: 10.1111/2041-210X.13822 (URL: https://doi.org/10.1111/2041-210X.13822).

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Version

Install

install.packages('isotracer')

Monthly Downloads

41

Version

1.1.9

License

GPL-3

Maintainer

Mattieu Bruneaux

Last Published

September 20th, 2026

Functions in isotracer (1.1.9)

Generic for as_tbl_graph()

Return the compartments of a network model

new_networkModel

Create an empty network model

as_tbl_graph.topology

Convert a network topology to a tbl_graph

Define a truncated normal prior (on [0;+Inf])

ggtopo.networkModel

Plot a network topology

print.networkModel

Print method for networkModel objects

Plot a topology

Draw a Sankey plot with basic defaults

select.mcmc.list

Select parameters based on their names

Pretty printing of a prior object

Set the half-life for radioactive tracers

Objects exported from other packages

filter.ppcNetworkModel

Filter method for output of tidy_data_and_posterior_predict()

Define a fixed-value prior

A quick-and-dirty way of visualizing relative flows in a network

posterior_predict.networkModelStanfit

Draw from the posterior predictive distribution of the model outcome

predict.networkModel

Add a column with predictions from a fit

Define a gamma prior

Eelgrass phosphate incorporation data (McRoy & Barsdate 1970)

Calculate DIC from a model output

Define a beta prior (on [0;scale])

plot.networkModel

Plot observations/trajectories/predictions from a network model

Return the tibble containing the priors of a networkModel

pillar_shaft.prior

Function used for displaying prior object in tibbles

Draw a Sankey plot for a network and estimated flows

Calculate the trajectories of a network model

filter_by_group

Filter a tibble based on the "group" column

Convert delta notation to proportion of heavy isotope

Define a half-Cauchy prior (on [0;+Inf])

Return the parameters of a network model

isotracer-package

The 'isotracer' package

print.prior_tibble

Pretty printing of a prior_tibble object

posterior_predict

Draw from the posterior predictive distribution of the model outcome

Function used for displaying prior object in tibbles

Get a table with parameters which are missing priors

Draw a heatmap based on the correlations between parameters

Flag some network compartments as being in a steady state

tidy_trajectories

Build a tidy table with the trajectories for each iteration

Flag some network compartments as being split compartments

plot.ready_for_unit_plot

Plot output from split_to_unit_plot

Return the list of topologies, or a unique topology if all identical

Pretty printing of a topology object

stanfit_to_named_mcmclist

Convert a Stanfit object to a nicely named mcmc.list object

Set initial conditions in a network model

Set observations in a network model

Set the topology in a network model.

tidy_posterior_predict

Draw from the posterior predictive distribution of the model outcome

Return the distribution family for observed sizes

tidy_steady_states

Build a tidy table with the calculated steady states for each iteration

Convert isotopic proportions to delta values

Dataset for nitrogren fluxes in a Trinidadian mountain stream (Collins 2016)

Protein degradation in Arabidopsis plants (Li et al. 2017)

Function used for displaying prior object in tibbles

[.networkModelStanfit

Subset method for networkModelStanfit objects

Define a uniform prior

Run a MCMC sampler on a network model using Stan

sample_from_prior

Sample from a prior object

Generate samples from a network model

Sample parameter values from priors

Prepare tidy data and posterior predictions

Extract a tidy output from an mcmc.list

Extract data from a networkModel object into a tidy tibble.

Build a tidy table with the flows for each iteration

Return the distribution family for observed proportions

set_size_family

Set the distribution family for observed sizes

set_prop_family

Set the distribution family for observed proportions

Set the parameters in a network model

Set prior(s) for a network model

Plot mcmc.list objects

Network model for nitrogen fluxes in Trinidadian streams (Collins et al. 2016)

add_pulse_event

Register a pulse event on one of the compartment of a topology

Ops generics for mcmc.list objects

as.mcmc.list.tidy_steady_states

Convert a tidy_steady_states object to an mcmc.list

as.mcmc.list.tidy_flows

Convert a tidy_flows object to an mcmc.list

A simple aquarium network model, ready to run

Add fixed effects of one or several covariates to some parameters.

Math generics for mcmc.list objects

Ops generics for topology objects

Implementation of the '==' operator for priors

available_priors

List the available priors for model parameters

calculate_steady_state

Calculate steady-state compartment sizes for a network

Define an exponential prior

An MCMC run from a simple aquarium network model

ggtopo.topology

Plot a topology

groups.networkModel

Get the grouping for a networkModel object

Filter (alias for filter function from dplyr)

Combine mcmc.list objects

Pretty formatting of a prior object

format.prior_tibble

Pretty formatting of a prior_tibble object