isotracer: Isotopic Tracer Analysis Using MCMC

Implements Bayesian models to analyze data from tracer addition experiments. The implemented method was originally described in the article "A New Method to Reconstruct Quantitative Food Webs and Nutrient Flows from Isotope Tracer Addition Experiments" by López-Sepulcre et al. (2020) <doi:10.1086/708546>.

Version: 1.0.4
Depends: R (≥ 3.6.0)
Imports: coda (≥ 0.19-3), data.table, dplyr (≥ 0.8.5), latex2exp (≥ 0.4.0), magrittr, methods (≥ 3.6.0), pillar (≥ 1.4.3), purrr (≥ 0.3.3), Rcpp (≥ 1.0.4), rlang (≥ 0.4.5), rstan (≥ 2.19.3), rstantools (≥ 2.0.0), tibble (≥ 3.0.0), tidyr (≥ 1.0.2), tidyselect (≥ 1.0.0)
LinkingTo: BH (≥ 1.72.0), Rcpp (≥ 1.0.4), RcppEigen (≥, StanHeaders (≥ 2.19.2), rstan (≥ 2.19.3)
Suggests: bayesplot, covr, ggdist, ggplot2, ggraph, gridBase, gridExtra, here, igraph, knitr, lattice, readxl, rmarkdown, testthat, tidygraph, tidyverse, viridisLite
Published: 2021-09-27
Author: Andrés López-Sepulcre ORCID iD [aut], Matthieu Bruneaux ORCID iD [aut, cre]
Maintainer: Matthieu Bruneaux <matthieu.bruneaux at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: isotracer citation info
Materials: README NEWS
CRAN checks: isotracer results


Reference manual: isotracer.pdf
Vignettes: Case study: Trinidadian streams (Collins et al. 2016)
Quick start
Handling replication
Setting steady-state compartments
Defining pulse or drip events
Including fixed effects of covariates
Units and priors
Prior predictive checks
MCMC output format
Post-run diagnostics and analyses
Posterior predictive checks
Calculating derived parameters
How to simulate experiments
Testing parameter identifiability


Package source: isotracer_1.0.4.tar.gz
Windows binaries: r-devel:, r-devel-UCRT:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): isotracer_1.0.4.tgz, r-release (x86_64): isotracer_1.0.4.tgz, r-oldrel: isotracer_1.0.4.tgz


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