meteESF {meteR}

meteESF

Description

meteESF Calculates the “ecosystem structure function” R(n,\epsilon) which forms the core of the Maximum Entropy Theory of Ecology

Usage

meteESF(spp, abund, power, S0 = NULL, N0 = NULL, E0 = NULL, minE)

Arguments

spp

A vector of species names

abund

A vector of abundances

power

A vector of metabolic rates

S0

Total number of species

N0

Total number of individuals

E0

Total metabolic rate; defaults to N0*1e6 if not specified or calculated from power to allow one to fit models that do not depend on metabolic rates

minE

Minimum possible metabolic rate

Details

Uses either data or state variables to calculate the Ecosystem Structure Function (ESF). power nor E0 need not be specified; if missing an arbitrarily large value is assigned to E0 (N0*1e5) such that it will minimally affect estimation of Lagrange multipliers. Consider using sensitivity analysis to confirm this assumption. Examples show different ways of combining data and state variables to specify constraints

Value

An object of class meteESF with elements

data

The data used to construct the ESF

emin

The minimum metabolic rate used to rescale metabolic rates

La

Vector of Lagrange multipliers

La.info

Termination information from optimization procedure

state.var

State variables used to constrain entropy maximization

Z

Normalization constant for ESF

Author(s)

Andy Rominger <[e-mail]>, Cory Merow

References

Harte, J. 2011. Maximum entropy and ecology: a theory of abundance, distribution, and energetics. Oxford University Press.

See Also

metePi

Examples

## case where complete data availible
esf1 <- meteESF(spp=arth$spp,
                abund=arth$count,
                power=arth$mass^(.75),
                minE=min(arth$mass^(.75)))
esf1

## excluding metabolic rate data
esf2 <- meteESF(spp=arth$spp,
                abund=arth$count)
esf2

## using state variables only
esf3 <- meteESF(S0=50, N0=500, E0=5000)
esf3
esf4 <- meteESF(S0=50, N0=500)
esf4