This Repository is Now Deprecated These functions are now part of the velociraptr package.
R Functions for downloading, cleaning, culling, or analyzing fossil data from the Paleobiology Database. Developed and maintained by Andrew Zaffos as part of the Paleobiology Database and Macrostrat Database tech development initiatives at the University of Wisconsin - Madison.
- Creative Commons License # The creative commons license for modules in this repository.
- Version and Change Log # Information about changes to this repository.
- communityMatrix.R # Downloading and cleaning Paleobiology Database (PBDB) data, and making a community matrix.
- cullMatrix.R # Culling a communty matrix of depauperate samples and rare taxa.
- subsampleRichness.R # A set of subsampling functions for standardizing sampled taxonomic richness.
- partitionDiversity.R # A set of functions for calculating alpha, beta, and gamma diversity of a community matrix.
All code within the paleobiologyDatabase.R repository is covered under a Creative Commons License (CC BY-NC 4.0). This license requires attribution to Andrew A. Zaffos and Steven M. Holland, and does not allow for commercial use.
This is v0.03 of the paleobiologyDatabase.R repository. The repository has four functional modules: communityMatrix.R, cullMatrix.R, subsampleRichness.R, and partitionDiversity.R. Two incomplete modules are also currently uploaded: basicStatistics.R and gaussianOccupancy.R. These modules are still under development and their use is discouraged.
The next module will add support for several dual-concept diversity indices (e.g., True Shannon's Entropy) to some of these modules.
- v0.037 - Changed the package names to quantitativeFossils
- v0.036 - Changed the
ageRanges( )function so that it no longer rounds ages to the nearest million years. - v0.035 - Optimized the
presenceMatrix( )andabundanceMatrix( )functions. It now produces an identical output at 30x faster. The arguments have been changed to make it clearer what makes up the rows and columns of the matrix. - v0.034 - Upgraded the
cleanGenus( )function to cleanRank( ), so that it will clean any taxonomic field - e.g., family, order - in addition to genus. - v.0.033 - Added downloadPaleogeography( ) function. Downloads a map of paleocontinent orientation as a shapefile. Accepts an age between 541 and 0 mys.
- v.0.032 - Added ageRanges( ) function, which finds the age range of each taxon. Changed abundanceMatrix( ) and presenceMatrix( ) to accept taxon ranks other than genus.
- v.0.031 - Fixed a bug with the error messages for resampleIndividuals( ) and subsampleIndividuals( )
- v.0.030 - Added partitionDiversity.R module.
- v.0.025 - Upgraded downloadPBDB( ) to use https instead of http.
- v.0.024 - Removed support for basicStatistics.R module until additional functions come online.
- v.0.023 - Removed communityMatrix( ) and replaced it with the identical presenceMatrix( ) function to make it more explicit that it is creating a presence-absence dataset. Added the abundanceMatrix( ) function, which makes a matrix with abundances.
- v.0.022 - Added basicStatistics.R module. Currently only has one supported function, mestimateMean( ), which calculates the least inverse squares M-estimated mean and error. More functions coming soon.
- v.0.021 - Added resampleIndividuals( ) to subsampleRichness.R module.
- v.0.020 - Added subsampleRichness.R module. Changed repository name from CleaningPBDB to paleobiologyDatabase.R. Added new function, softCull( ), to cullMatrix.R module.
- v.0.010 - Added communityMatrix.R and cullMatrix.R modules.
A set of functions for downloading data from the Paleobiology Database, and organizing it into a community matrix of samples by taxa, where "samples" are based on one of the variables in the Paleobiology Database - e.g., Plate ID, Geologic Age.
Can be accessed directly in R using:
source("https://raw.githubusercontent.com/aazaff/paleobiologyDatabase.R/master/communityMatrix.R")# Download data from PBDB by taxonomic group and geologic interval.
# Argument Taxa must be a vector of one or more taxon names (as a character string), no default.
# Argument StartInterval must be a single interval name accepted by the PBDB, default is "Pliocene"
# Argument StopInterval must be a single interval name accepted by the PBDB, default is "Pleistocene"
DataPBDB<-downloadPBDB(Taxa=c("Bivalvia","Gastropoda"),StartInterval="Cambrian",StopInterval="Pleistocene")# Download Timescale definitions from Macrostrat.
# Argument Timescale must be a timescale recognized by the macrostrat API, no default
# A list of Timescale defs can be seen here https://macrostrat.org/api/defs/timescales?all
Epochs<-downloadTime(Timescale="international epochs")# Download a map of paleocontinents for a specific age from Macrostrat as a shapefile.
# Note that this makes use of the rgdal package and its dependencies.
# Argument Age is a numerical value ranging from 541 to 0 mys ago.
PaleoMap<-downloadPaleogeography(Age=0)# Assign fossil occurrences to different ages, then remove occurrences that are not temporally
# constrained to a single interval.
# Argument DataPBDB is a dataset downloaded from the PBDB - i.e., using downloadPBDB( )
# Argument Timescale is a dataset downloaded from Macrostrat - i.e., using downloadTime( )
ConstrainedAges<-constrainAges(DataPBDB=DataPBDB,Timescale=Epochs)# Find the age range (min and max age) based on occurrence data in the PBDB for
# A particular level of the taxonomic hierarchy (e.g., genus, family, order)
# Argument DataPBDB is a dataset downloaded from the PBDB - i.e., using downloadPBDB( )
# Argument Taxonomy is a level of the taxonomic hierarchy - e.g., "genus"
AgeRanges<-ageRanges(DataPBDB=DataPBDB,Taxonomy="genus")# Cleans the a taxonomic rank field of the PBDB data by removing NA's. It also removes subgenera from the genus rank.
# This is an upgraded version of the now deprecated cleanGenus( ) function.
# Argument DataPBDB is a dataset downloaded from the PBDB - i.e., using downloadPBDB( )
# Argument Rank is a taxonomic rank - i.e., "genus".
CleanedPBDB<-cleanRank(DataPBDB,Rank="genus")# Create a community matrix of samples v. species, using elements within one of the PBDB columns
# (e.g., geoplate, early_interval) as the definition of a sample. This creates a presence-absence
# matrix of 1's (presence) and 0's (absence).
# This is just a renamed version of the now deprecated function communityMatrix( ).
# Argument DataPBDB is a dataset downloaded from the PBDB - i.e., using downloadPBDB( )
# Argument Rows is the column name defining samples
# Argument Columns is the column name defining taxa
CommunityMatrix<-presenceMatrix(DataPBDB,Rows="geoplate",Columns="genus")# Create a community matrix of samples v. species, using elements within one of the PBDB columns
# (e.g., geoplate, early_interval) as the definition of a sample. This creates an "abundance"
# matrix, which uses the number of occurrences a genus has within the "sample" as its abundance.
# Because the theoretical and operational meaning of occurrences in the Paleobiology Database is ill-defined
# I recommend using presenceMatrix( ) instead if possible.
# Argument DataPBBDB is a dataset downloaded from the PBDB - i.e., using downloadPBDB( )
# Argument Rows is the column name defining samples
# Argument Columns is the column name defining taxa
CommunityMatrix<-abundanceMatrix(DataPBDB,Rows="geoplate",Columns="genus")A set of functions for removing depauperate and rare taxa from community matrices of samples by taxa.
Can be accessed directly in R using:
source("https://raw.githubusercontent.com/aazaff/paleobiologyDatabase.R/master/cullMatrix.R")# Cull a community matrix of depauperate samples and rare taxa. Written by S.M. Holland.
# Argument x is a community matrix, no default.
# Argument minOccurrences is the minimum number of occurrences for each taxon, default = 2
# Argument minDiversity is the minimum number of taxa within each sample, default=2
CulledMatrix<-cullMatrix(CommunityMatrix,minOccurrences=5,minDiversity=5)# A variant of cullMatrix( ) that returns NA when there are no samples or taxa left
# rather than throwing an error. Useful when culling multiple matrices in a loop,
# and you would rather skip depauperate matrices than break the loop.
# Not recommended otherwise.
# Argument x is a community matrix, no default.
# Argument minOccurrences is the minimum number of occurrences for each taxon, default = 2
# Argument minDiversity is the minimum number of taxa within each sample, default=2
CulledMatrix<-softCull(CommunityMatrix,minOccurrences=5,minDiversity=5)Functions for standardizing taxonomic richness. The multicore versions use the doMC package and its dependencies. This package is currently not available for windows.
Can be accessed directly in R using:
source("https://raw.githubusercontent.com/aazaff/paleobiologyDatabase.R/master/subsampleRichness.R")# A function that subsamples richness based on evenness. Often referred to as "Shareholder Quorum Subsampling".
# An optimized version of John Alroy's original function by Steven M. Holland.
# Argument Abundance is a vector of abundances.
# Argument Quota is a value between 0 and 1, the default is set to 0.9.
# Argument Trials determines how many iterations of the bootstrap are performed, default = 100
# Argument IgnoreSingletons determines whether or not to ignore singletons, default is FALSE.
# Argument ExcludeDominant determines whether or not to ignore the most dominant taxon
# Excluding the abundant taxon is recommended by Alroy, but the default is set to FALSE.
SubsampledRichness<-subsampleEvenness(Abundance,Quota=0.5,Trials=100,IgnoreSingletons=FALSE,ExcludeDominant=FALSE)# A multicore version of subsampleEvenness( ). Be warned that multicoreEvenness( ) is not automatically
# faster than subsampleEvenness( ), particularly for a low number of trials. Its use is not recommended
# for small abundance vectors or a small numbers of trials. Requires the doMC package.
# Argument Abundance is a vector of abundances.
# Argument Quota is a value between 0 and 1, the default is set to 0.9.
# Argument Trials determines how many iterations of the bootstrap are performed, default = 1000
# Argument IgnoreSingletons determines whether or not to ignore singletons, default is FALSE.
# Argument ExcludeDominant determines whether or not to ignore the most dominant taxon
# Excluding the dominant taxon is recommended by Alroy, but the default is set to FALSE.
# Argument Cores sets the number of processor cores, default = 4.
SubsampledRichness<-multicoreEvenness(Abundance,Quota=0.5,Trials=100,IgnoreSingletons=FALSE,ExcludeDominant=FALSE,Cores=4)# A function that subsamples richness based on a fixed number of individuals. Often referred to as "rarefaction".
# Argument Abundance is a vector of abundances.
# Argument Quota is the number of individuals to be subsampled. If the Quota is greater than
# the number of individuals, the function will print a warning and return the unstandardized richness.
# Argument Trials determines how many iterations of the bootstrap are performed, default = 100
SubsampledRichness<-subsampleIndividuals(Abundance,Quota,Trials=100)# A multicore version of subsampleIndividuals( ). Be warned that multicoreIndividuals( ) is not automatically
# faster than subsampleIndividuals( ), particularly for a low number of trials. Its use is not recommended
# for small abundance vectors or a small numbers of trials. Requires the doMC package.
# Argument Abundance is a vector of abundances.
# Argument Quota is the number of individuals to be subsampled. If the Quota is greater than
# the number of individuals, the function will print a warning and return the unstandardized richness.
# Argument Trials determines how many iterations of the bootstrap are performed, default = 1000
# Argument Cores sets the number of processor cores, default = 4.
SubsampledRichness<-multicoreIndividuals(Abundance,Quota,Trials=1000,Cores=4)# A specialized variant of subsampleIndividuals( ). If the quota is greater than the number of individuals
# it will switch to sampling with replacement. This allows for diversity in those samples to be lower
# than the quota.
# Caution: This is a non-standard approach.
# Argument Abundance is a vector of abundances.
# Argument Quota is the number of individuals to be subsampled.
# Argument Trials determines how many iterations of the bootstrap are performed, default = 100
ResampledIndividuals<-resampleIndividuals(Abundance,Quota,Trials=100)Functions for calculating alpha, beta, and gamma richness of a community matrix. See communityMatrix.R for functions to make such a matrix with Paleobiology Database data and cullMatrix.R for functions to cull and prepare such a dataset.
Some of these functions were presented in Holland, SM (2010) Additive diversity partitioning in palaeobiology: revisiting Sepkoski’s question. Paleontology 53:1237-1254. Namely, taxonAlphaContributions( ), taxonBetaContributions( ), and sampleBetaContributions( ).
Other methods of beta calculation come from the equations presented in Tuomisto, H (2010) A diversity of beta diversities: straightening up a concept gone awry. Part 1. Defining beta diversity as a function of alpha and gamma diversity. Ecography 33:2-22.
Can be accessed directly in R using:
source("https://raw.githubusercontent.com/aazaff/paleobiologyDatabase.R/master/partitionDiversity.R")# Returns vector of each taxon’s contribution to alpha diversity. Written by S.M. Holland.
# Argument x is a community matrix of presence-absence data.
TaxonAlpha<-taxonAlphaContributions(x=PresenceMatrix)# Returns vector of each taxon’s contribution to beta diversity.
# Be warned that if you are using a hierarchichal partitioning scheme
# that this function *always* calculates between-sample beta,
# with sample being defined by your matrix. You must pre-aggregate samples
# in the community matrix before you can calculate the beta
# diversity of a higher level in the hierarchy. Written by S.M. Holland.
# Argument x is a community matrix of presence-absence data.
TaxonBeta<-taxonBetaContributions(x=PresenceMatrix)# Returns vector of each sample’s contribution to beta diversity. Written by S.M. Holland.
# Argument x is a community matrix of presence-absence data.
TaxonBeta<-sampleBetaContributions(x=PresenceMatrix)# Returns mean alpha diversity (richness) of samples. Written by S.M. Holland.
# Argument x is a community matrix of presence-absence data.
AlphaDiversity<-meanAlpha(x=PresenceMatrix)# Returns beta diversity (richness) of samples. Written by S.M. Holland.
# Argument x is a community matrix of presence-absence data.
BetaDiversity<-beta(x=PresenceMatrix)# Returns gamma (total) diversity (richness) of matrix. Written by S.M. Holland.
# Argument x is a community matrix of presence-absence data.
GammaDiversity<-gamma(x=PresenceMatrix)# Calculate alpha diversity in the traditional manner, averaging sample richness.
# Should always be equal to meanAlpha( ) function.
# Argument x is a community matrix of presence-absence data.
AlphaDiversity<-traditionalAlpha(x=PresenceMatrix)# Calculate beta diversity in the traditional manner ADP manner Beta = Gamma - Alpha
# Should always be equal to beta( ) function.
# Argument x is a community matrix of presence-absence data.
BetaDiversity<-traditionalBeta(x=PresenceMatrix)# Calculate beta diversity in the traditional multiplicative manner. Beta = Gamma/Alpha
# Argument x is a community matrix of presence-absence data.
BetaDiversity<-multiplicativeBeta(x=PresenceMatrix)# Calculate Whittaker's effective species turnover, the number of complete effective species
# turnovers among samples in the dataset.
# Beta = (Gamma-Alpha)/Alpha
# Argument x is a community matrix of presence-absence data.
BetaDiversity<-completeTurnovers(x=PresenceMatrix)# Proportional effective species turnover, the proporition of species in the region
# not limited to a single sample - i.e., the
# proportion of "non-endemic" taxa. Beta = (Gamma-Alpha)/Gamma
# Argument x is a community matrix of presence-absence data.
BetaDiversity<-proportionNonendemic(x=PresenceMatrix)
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