price.part: Calculate the Price equation partition for two communities

In ctkremer/priceTools: Tools for analyzing biodiversity-ecosystem function relationships

Description

Take a (formatted) list of species and functions for two communities, and calculate the Price equation partition comparing the communities.

Usage

price.part(comm, quiet = F, sps.level = F)

Arguments

comm	A data frame formatted according to the data.setup() function, or if formatting independently, a data frame with the following columns.
quiet	Silence error messages? TRUE/FALSE
sps.level	Provide species-level contributions to 5 Price components? TRUE/FALSE

Details

Extra thoughts on how the interpret the Price equation partitions, which may get relocated into a vignette.

Comments on SIE.L. If a species x' from x is lost in y, SIE.L will increase if x' is less productive on average, and SIE.L will decrease if x' is more productive than average. If a species x' from x is NOT lost in y, SIE.L will increase if x' is more productive on average, and SIE.L will decrease if x' is less productive than average. Overall, high/positive values of SIE.L mean that weak species were lost and good species were retained. Noteably, SIE.L will not be affected by new species that y gains relative to what is shared or lost. Average species have little effect on the value of SIE.L. If either barely any or almost all species occur in common between communities x and y, then the few species that are kept (or lost) will have a particularly large influence on the value of SIE.L. Overall, SIE.L will probably be smaller in this case, and greatly affected by whether the species lost/gained are more or less productive.

Comments on SIE.G. A less productive than average species in y (-1) makes a negative contribution to SIE.G if it is NOT in community x, and a positive contribution to SIE.G if it is in community x. A more productive than average species in y (+1) makes a negative contribution to SIE.G if it is in x, and a positive contribution to SIE.G if it does NOT occur in community x. A positive SIE.G occurs when less productive than average members of y also occured in x, and more productive than average species in y do not occur in x.

Value

If sps.level=FALSE, a data frame of Price equation components.

SRE.L	species richness effect (loss of species)
SRE.G	species richness effect (gain of species)
SIE.L	species identity effect (loss of species)
SIE.G	species identity effect (gain of species)
CDE	context dependent effect
SL	sum of SRE.L and SIE.L
SG	sum of SRE.G and SIE.G
SR	sum of SRE.L and SRE.G
CE	sum of SIE.G, SIE.L, and CDE
x.func	Total function in community X
y.func	Total function in community Y
x.rich	Number of species in community X
y.rich	Number of species in community Y
c.rich	Number of shared species between X and Y

If sps.level=TRUE, a list containing the above information in the first slot, and a data frame of individual species' contributions to each Price component in the second slot.

Examples

formatted.data<-data.setup(list(biomass))
price.part(formatted.data) 

ctkremer/priceTools documentation built on May 28, 2019, 7:49 p.m.