Estimate Pollinator Body Size and Co-Varying Ecological Traits

Tools to estimate pollinator body size and co-varying traits. This package contains Bayesian predictive models of pollinator body size (for bees and hoverflies) and bee foraging range, as well as preexisting predictive models for pollinator body size (currently implemented for ants, bees, butterflies, flies, moths and wasps), bee tongue length, foraging range, total field nectar loads and wing loading. An additional GitHub repository < https://github.com/liamkendall/pollimetrydata> provides model objects to use the bodysize and foraging.range functions internally. The Bayesian models are described in Kendall et al. (2019) & Kendall et al. (2022) .

Pollimetry: Robust estimates of body size and co-varying traits in pollinating insects

Tools to estimate pollinator body size and co-varying ecological traits.

To install

if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}
devtools::install_github("liamkendall/pollimetry")
library(pollimetry)

The Bayesian functions use fitted models from pollimetrydata. Installing version 1.0.1 or later is optional and enables offline predictions. Otherwise, only the required models are downloaded from GitHub and reused within the current R session.

# Optional: install all fitted models for offline use
devtools::install_github("liamkendall/pollimetrydata")

Estimating body size

The bodysize() function estimates bee and hoverfly dry body weight from intertegular distance (ITD), sex, taxonomy or phylogeny, and geographical region. It returns back-transformed mean estimates with 95 percent Bayesian credible intervals in milligrams, appended as Est.Weight, CI_Lower and CI_Upper. See the function help for model options and required inputs.

Pre-existing equations for Diptera, Hymenoptera and Lepidopteran taxa using body length (lengthsize), body length * width (lengthwidthsize) and head width (headwidthsize) are also provided.

Supply body length and head width in millimetres; supply length × width in square millimetres. Measurements must be nonempty numeric vectors containing only finite, positive values. Eq selects one equation or a supported group using a single character string. Single equations return numeric vectors; equation groups return matrices with one row per measurement and named equation columns.

See the function help pages for supported equation choices. These equations return point predictions.

Allometric traits

Users can predict, i) bee tongue length (tonguelength) using combined data from Cariveau et al. (2016) and Melin et al. (2019), including Melittidae, ii) bee foraging distances (foragedist) from equations described in van Nieuwstadt and Ruano Iraheta (1996) for Meliponini, Greenleaf et al. (2007) and Guedot et al. (2009) for Osmia spp, iii) wing loading (wingloading) from Bullock (1999) and, iv) field nectar loads (nectarload) from Henry and Rodet (2018).

The foraging.range() function uses the Bayesian models of Kendall et al. (2022) to estimate typical and maximum realized or potential foraging ranges. It returns back-transformed mean estimates with 95 percent Bayesian credible intervals in kilometres, conditional on estimated female body weight. The older foragedist() function is deprecated; its published equations and units are described in its help page.

The package provides three datasets: pollimetry_dataset (body size), forage_dataset (foraging range), and tongue_dataset (combined tongue-length training data).

Example

Explore the body size dataset:

data("pollimetry_dataset", package = "pollimetry")
head(pollimetry_dataset)
?pollimetry_dataset #for metadata.

Let's predict some body sizes from a dataframe using taxonomy:

(example <- cbind.data.frame(ITD = c(1.2, 2.3),
                            Sex = c("Female","Male"),
                            Family = c("Apidae","Andrenidae"),
                            Region = c("NorthAmerica","Europe"),
                            Species = c("Ceratina_dupla","Andrena_flavipes")))

bodysize(x = example, taxa = "bee", type = "taxo")
?bodysize

Now let's estimate realized foraging ranges using ITD:

foraging.range(
  data.frame(ITD = c(2, 3)),
  model.type = "ITD",
  random.effects = "reduced",
  measure.type = "realized"
)

Manuscript R code

Kendall, L. (2018). Pollimetry R code. Figshare. doi:10.6084/m9.figshare.7357217.v1