karawoo / bumbl

R package for modeling bumblebee colony growth.

Tools for modeling bumblebee colony growth

bumbl implements a model for bumblebee colony growth described in Crone and Williams 2019¹. The brkpt function models colony growth as having a change point at some time, tau, where the colony switches from growth and worker production to gyne production. The bumbl function applies this model to a data frame of data from multiple colonies, allowing for each colony to have it’s own tau and returns the original data augmented with coefficients from the changepoint model.

This is still in very early development, so use at your own risk.

More bumblebee related functions to come…

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), ]
bumbl(bombus2, colonyID = colony, t = week, formula = d.mass ~ week)
#> Warning: glm.fit: algorithm did not converge

#> Warning: glm.fit: algorithm did not converge
#> # A tibble: 4 x 6
#>   colony   tau logN0 logLam  decay logNmax
#>   <chr>  <dbl> <dbl>  <dbl>  <dbl>   <dbl>
#> 1 35      9.49  3.68  0.209 -0.295    5.61
#> 2 82      7.43  2.97  0.394 -0.503    5.83
#> 3 9       6.43  2.30  0.610 -0.690    6.18
#> 4 98      6.37  1.27  0.570 -0.578    4.90

Keep the original data and plot the results

results <- bumbl(bombus2, colonyID = colony, t = week, formula = d.mass ~ week, augment = TRUE)
#> Warning: glm.fit: algorithm did not converge

#> Warning: glm.fit: algorithm did not converge
par(mfrow = c(2, 2))
bumbl_plot(results)

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