Tools for modeling bumblebee colony growth

R build status Codecov test coverage Lifecycle: stable CRAN status DOI

bumbl implements a model for bumblebee colony growth described in Crone and Williams 20161. It models colony growth as having a switchpoint at some time, tau, where the colony switches from growth and worker production to gyne production and decline. Currently bumbl() works by fitting a separate switchpoint model to each colony, optimizing the switchpoint, tau. It returns the optimal switchpoint, growth, and decline rates for each colony. Because the current version of bumbl() works by fitting a separate GLM to each colony, if covariates are included, their estimates could vary significantly among colonies. Stay tuned for future developments that may allow estimating a single value of a covariate but different values of growth and decline rates and tau for each colony.

Collaboration

I’m looking for collaborators who know (or are willing to let me teach them) how to use git and GitHub and who have an interest in helping to develop and maintain this package long-term. I’m not a bumblebee biologist, so I would especially love a collaborator who works on bumblebees or other organisms with a similar growth, switch, decline lifecycle.

I also welcome contributions including bug-fixes, improvement of documentation, additional features, or new functions relating to bumblebee ecology and demography from anyone!

Roadmap

Other possible areas of improvement:

Installation

You can install this development version of bumbl with:

devtools::install_github("Aariq/bumbl", build_vignettes = TRUE)

Getting started

View the package vignette with:

library(bumbl)
vignette("bumbl")

View the bomubs dataset

head(bombus)
#> # A tibble: 6 x 10
#>   site  colony  wild habitat date        week  mass d.mass floral_resources
#>   <fct> <fct>  <dbl> <fct>   <date>     <int> <dbl>  <dbl>            <dbl>
#> 1 PUT2  9       0.98 W       2003-04-03     0 1910.    0.1            27.8 
#> 2 PUT2  9       0.98 W       2003-04-09     1 1940    30.6            27.8 
#> 3 PUT2  9       0.98 W       2003-04-15     2 1938    28.6            27.8 
#> 4 PUT2  9       0.98 W       2003-04-22     3 1976.   67.1            27.8 
#> 5 PUT2  9       0.98 W       2003-05-01     4 2010.  101.              7.96
#> 6 PUT2  9       0.98 W       2003-05-07     5 2143   234.              7.96
#> # … with 1 more variable: cum_floral <dbl>

Example use

Using a subset of the bombus dataframe to estimate the week (tau) that colonies switch to reproduction

bombus2 <- bombus[bombus$colony %in% c(9, 82, 98, 35), ]
results <- bumbl(bombus2, colonyID = colony, t = week, formula = d.mass ~ week)
results
#> # A tibble: 4 x 7
#>   colony converged   tau logN0 logLam  decay logNmax
#>   <chr>  <lgl>     <dbl> <dbl>  <dbl>  <dbl>   <dbl>
#> 1 35     TRUE       9.37  3.65  0.214 -0.296    5.60
#> 2 82     TRUE       7.34  2.91  0.407 -0.512    5.82
#> 3 9      TRUE       6.52  2.45  0.579 -0.660    6.19
#> 4 98     TRUE       6.37  1.27  0.570 -0.578    4.90

Plot the results

par(mfrow = c(2, 2))
plot(results)
#> Creating plots for 4 colonies...

par(mfrow = c(1, 1))

References

1Crone, E. E., and Williams, N. M. (2016). Bumble bee colony dynamics: quantifying the importance of land use and floral resources for colony growth and queen production. Ecol. Lett. 19, 460–468. https://doi.org/10.1111/ele.12581


Please note that the bumbl project is released with a Contributor Code of Conduct. By contributing to this project you agree to abide by its terms.