RInSp (version 1.2.5)

pop.diet: Calculate population diet

Description

This function calculates the population diet using two different approaches: the “sum” or the “average” method.

Usage

pop.diet(dataset, prop = "sum")

Arguments

dataset

Object of class RInSp with data.

prop

Option specifying the type of calculation. Two types: “sum” or “average”.

Value

Returns a list of information:

popdiet

Vector of the specified population diet.

popdtype

The type of population diet.

richness

The richness of resources (for now it has sense only for integer data type).

D

The Levins' D index for resources.

Details

The “sum” approach is the most straightforward. One sums up all resource counts within a category across all individuals to get the population's use, then determine the proportion of each resource category in the population's repertoire. The proportion \(q_j\) of the resource j in the population's diet is:

$$q_j = \frac{\sum_i{n_{ij}}}{\sum_{ji}{n_{ij}}}$$

The drawback of this approach is that individuals that eat large numbers of items, or larger total mass of items, will bias the population to look more like them.

The “average” method (average proportion) circumvents this problem by first converting individual diets into proportions \(p_{ik}\), then averaging these proportions for each resource k.

Along with the population's diet the procedure calculates the Levins' D index (Levins 1968) of diversity as:

$$ D = 1 - \frac{1}{\sum{q_{j}^2}}$$

References

Bolnick, D.I., L.H. Yang, J.A. Fordyce, J.M. Davis, and Svanback, R. 2002. Measuring individual-level resource specialization. Ecology 83: 2936-2941.

Levins R. 1968. Evolution in Changing Environments: Some Theoretical Explorations. Princeton Univ. Press.

See Also

Function Null.Hp.RInSp.

Examples

# NOT RUN {
data(Stickleback)
# Select a single spatial sampling site (site D)
GutContents_SiteD <- import.RInSp(Stickleback, row.names = 1, info.cols = c(2:13),
subset.rows = c("Site", "D"))
PopDiet <- pop.diet(GutContents_SiteD, prop = "average")
rm(list=ls(all=TRUE))
# }