Description

Squamatabase is a database of prey items recorded in diet samples from the world's snakes, compiled by me, during my time as a PhD student at the University of Michigan.

Data archives

Each new release (corresponding to the addition of new data or new functionality) is archived in the Zenodo data repository and receives a DOI. Users who simply want the raw data without bothering with package installation can download the diet.csv file in the inst/ directory. The current archive contains around 30,000 predator-prey records sampled from around the world and many different snake lineages. Each point on the globe below represents a georeferenced predation event, and the bar graph to the left shows the snake family level distribution of those records.

Installation

Squamatabase can be installed from an R session using the following command

remotes::install_github("blueraleigh/squamatabase")

Alternatively, the tarball for this repository can be downloaded and installed via R CMD INSTALL.

Getting started

library(squamatabase)

# For a list of available functions
?squamatabase

# For documentation of database structure
?diet

# To load the full record set we can do ...
data(diet)

# ... or we can do
diet = squamatabase::filter_records()

# To reproduce the graph above:

# Fetch the full record set
diet = squamatabase::filter_records()

# Filter the record set to weed out any miscellaneous non-snakes
diet = squamatabase::filter_records(diet, predator_taxon="Serpentes")

# Collapse all identified snakes to the level of taxonomic family
diet = squamatabase::collapse_ranks(diet, "family")

# Compute family-level counts
counts = pmin(diet$predator_count, diet$prey_count, na.rm=TRUE)
family_counts = sort(tapply(counts, diet$predator, sum, na.rm=TRUE))

# And finally the labor for the plot
dev.new(width=10.5, height=5)
close.screen(all.screens=TRUE)
split.screen(c(1, 3))
screen(2)
par(mar=c(0,0,0,0), oma=c(0,0,0,1))
plot.new()
plot.window(xlim=c(-1,1), ylim=c(-1, 1), asp=1)
maps::map(
    interior=FALSE, 
    proj="ortho", 
    orient=c(15, -90, 0),
    fill=TRUE, 
    col="#f6e8c3",
    mar=c(0,0,0,0), 
    add=TRUE
)
theta = seq(0, 2*pi, length.out=512)
polygon(cos(theta), sin(theta), col="#91bfdb")
maps::map(
    interior=FALSE, 
    proj="ortho", 
    orient=c(15, -90, 0), 
    fill=TRUE, 
    col="#f6e8c3", 
    add=TRUE
)
coords = mapproj::mapproject(
    diet$locality_longitude, 
    diet$locality_latitude, 
    proj="ortho", 
    orient=c(15, -90, 0)
)
points(coords$x, coords$y, col="#8c510a", pch="+", cex=0.8)
screen(3)
par(mar=c(0,0,0,0), oma=c(0,0,0,0))
plot.new()
plot.window(xlim=c(-1,1), ylim=c(-1,1), asp=1)
maps::map(
    interior=FALSE, 
    proj="ortho", 
    orient=c(15, 70, 0), 
    fill=TRUE, 
    col="#f6e8c3", 
    add=TRUE
)
polygon(cos(theta), sin(theta), col="#91bfdb")
maps::map(
    interior=FALSE, 
    proj="ortho", 
    orient=c(15, 70, 0), 
    fill=TRUE, 
    col="#f6e8c3", 
    add=TRUE
)
coords = mapproj::mapproject(
    diet$locality_longitude, 
    diet$locality_latitude, 
    proj="ortho", 
    orient=c(15, 70, 0)
)
points(coords$x, coords$y, col="#8c510a", pch="+", cex=0.8)
screen(1)
par(oma=c(0, 2, 0, 0), mar=c(5.1, 4.1, 2.1, 0.1))
barplot(family_counts, horiz=TRUE, cex.names=0.7, log='x', las=1, xaxt="n")
axis(1, at=c(1, 10, 100, 1000, 10000))
mtext("Number of prey items", 1, 2.5)

Database compilation

I compiled Squamatabase from numerous articles published in scientific journals. I located material both through the use of keyword queries in academic search engines and by systematic review of table of contents for well-known herpetological journals (e.g. Herpetological Review, Herpetology Notes). I also located additional relevant articles by consulting the references in reviewed articles. My goal was simply to track down as many relevant sources as possible. The current compilation includes data from approximately 1700 different sources but remains incomplete in many ways (e.g., geographically and taxonomically).

The majority of observations in the database result from papers describing (1) dissections of fluid preserved museum specimens and (2) direct encounters with snakes in the field that were actively consuming a prey or had recently consumed a prey item that could be regurgitated by forced palpation. Glaudas et al. (2017) have noted that these sources of information can provide different pictures of the prey spectrum for Bitis arietans (Puff Adder).

Database fields

Each record in the database describes a snake specimen eating or attempting to eat a prey specimen. Note that due to the nature of the published data a "specimen" does not necessarily correspond to a single individual. In all cases, however, a specimen refers to a set of individuals that belong to the same taxon. The following fields are associated with each record:

• predator_verbatim

  The scientific name of the predator as reported by the original authors.

• predator

  The scientific name the predator according to the 2016 Catalogue of Life taxonomy.

• predator_rank

  The Linnean rank of the predator. Typically this will be "species" or "infraspecies".

• predator_taxon

  A semicolon separated list of the higher taxonomic names that apply to the predator.

• predator_count

  The number of individual predator organisms involved in the interaction.

• predator_voucher

  A unique identifier for the specimen that is either (1) a bona fide museum voucher number or (2) a randomly generated alphanumeric code. The rationale for this field is that same predator specimen may have eaten multiple prey specimens that carry unique identifying information (e.g. taxonomic identities, distinct ages, etc.), in which case each prey specimen requires its own row, thus necessitating duplication of the predator specimen across rows. Having a unique identifier for the predator specimen allows one to identify the same predator specimen appearing in multiple rows, although this rarely happens due to the tendency of snakes to only have a single prey item in their gut. A caveat needs to be mentioned. In many cases, the results of museum studies are reported in summarized tabular form. For example, a museum study of snake X may report that 12 specimens had eaten 14 individuals of prey Y and that 8 specimens had eaten 8 individuals of prey Z. These data will be represented in SquamataBase as two rows, and each row will have a unique randomly generated predator_voucher. This is because there is no way, without further information, to know whether any of the individuals eating prey Y also ate prey Z.

• predator_sex

  The sex of the specimen. Typically only used when the predator_count field is 1.

• predator_age

  The age of the specimen.Typically only used when the predator_count field is 1.

• predator_svl

  The snout-vent-length (in mm) of the specimen. Typically only used when the predator_count field is 1.

• predator_tl

  The total length (in mm) of the specimen. Typically only used when the predator_count field is 1.

• predator_mass

  The mass (in grams) of the specimen. Typically only used when the predator_count field is 1.

NOTE

All of the above fields with the exception of the svl field are also recorded for the prey specimen, and hence take the prefix "prey". Additionally, the following field is unique to the prey specimen:

• prey_ingested

  The orientation in which the prey specimen was swallowed. Typically only used when the prey_count field is 1.

• locality_adm0_name

  The country where the predation event occurred.

• locality_adm1_name

  The state where the predation event occurred.

• locality_adm2_name

  The county where the predation event occurred.

• locality_longitude

  Decimal longitude where the predation event occurred.

• locality_latitude

  Decimal latitude where the predation event occurred.

• event_basis

  Evidentiary basis for the reported predation event. Typically "direct_observation" or "dissected_gut_contents".

• event_setting

  A note indicating whether the predation event was observed in a natural or a captive setting. Almost all records in the database are recorded from natural settings. Observations resulting from dissections of museum specimens are assumed to have occurred in a natural setting.

• event_date

  YYYY-MM-DD formatted date when the predation event was observed. If the observation resulted from an examination of gut contents this field is the collection date of the specimen.

• event_start

  HH:MM formatted time when the predation event was first noted, measured on a 24 hour clock to avoid AM and PM designations.

• event_end

  HH:MM formatted time when the predation event ended, measured on a 24 hour clock to avoid AM and PM designations.

• event_outcome

  If the predation event was successful this field takes the value "prey_eaten". This is always the case if the observation is based on dissections of museum specimens. However, for observations based on encounters with snakes in the field other outcomes are possible and the values in this field are self-explanatory (e.g. "predation_interrupted_by_observer").

• event_habitat

  A simple habitat descriptor indicating whether the predation occurred in a terrestrial, fossorial, arboreal, or aquatic setting.

• event_habitat_verbatim

  Habitat description in the words of the original authors.

• event_remark

  Miscellaneous narrative information regarded as potentially relevant.

• reference

  Bibliographic citation to the original source of the record.