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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.
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!
bumbl()
function to model colony growth with
switchpointbumbl()
bumbl()
? (see #58 and notes)Other possible areas of improvement:
bumbl()
to work with GLMMsbumbl()
to work with dates, datetimes, or other
timeseries classes (see #46)You can install bumbl
with:
install.packages("bumbl")
Or install the development version with:
::install_github("Aariq/bumbl", build_vignettes = TRUE) devtools
View the package vignette with:
library(bumbl)
vignette("bumbl")
View the bomubs
dataset
head(bombus)
#> # A tibble: 6 × 10
#> site colony wild habitat date week mass d.mass floral_reso…¹ cum_f…²
#> <fct> <fct> <dbl> <fct> <date> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 PUT2 9 0.98 W 2003-04-03 0 1910. 0.1 27.8 27.8
#> 2 PUT2 9 0.98 W 2003-04-09 1 1940 30.6 27.8 55.5
#> 3 PUT2 9 0.98 W 2003-04-15 2 1938 28.6 27.8 83.3
#> 4 PUT2 9 0.98 W 2003-04-22 3 1976. 67.1 27.8 111.
#> 5 PUT2 9 0.98 W 2003-05-01 4 2010. 101. 7.96 119.
#> 6 PUT2 9 0.98 W 2003-05-07 5 2143 234. 7.96 127.
#> # … with abbreviated variable names ¹floral_resources, ²cum_floral
Using a subset of the bombus
dataframe to estimate the
week (tau) that colonies switch to reproduction
<- bombus[bombus$colony %in% c(9, 82, 98, 35), ]
bombus2 <- bumbl(bombus2, colonyID = colony, t = week, formula = d.mass ~ week)
results
results#> # A tibble: 4 × 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))
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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.