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enaR (version 2.9.1)

enaUtility: Utility Analysis of Ecological Networks

Description

Performs the flow and storage based utility analysis developed for input-output network models of ecosystems. It returns a set of matrices for the direct and integral utilities as well as a set of utility based network statistics.

Usage

enaUtility(x,type=c("flow","storage"),eigen.check=TRUE,balance.override=FALSE,tol=10)

Arguments

x
a network object. This includes all weighted flows into and out of each node. For the storage utility analysis this must also include the amount of energy--matter stored at each node (biomass).
type
Determines whether the flow or storage utility analysis is returned.
eigen.check
LOGICAL: should the dominant eigenvalue be checked. Like enaFlow and enaStorage analyses, enaUtility analysis considers the utility propigated over path lengths ranging for zero to infinity. For utility analysis to work properly, the path sequence must converge. enaUtility checks to see if the utility path sequence is convergent by finding the dominant eigenvalue of the direct utility matrix. If this eigenvalue is less than 1, the sequence is convergent and the analysis can be applied; if the dominant eigenvalue is greater than one, then the anlysis cannot be applied. By default, the function will not return utility values if the eigenvalue is larger than one; however, if eigen.check is set to FALSE, then the function will be applied regardless of the mathematic validity.
balance.override
LOGICAL: should model balancing be ignored. enaUtility assumes that the network model is at steady-state. The default setting will not allow the function to be applied to models not at steady-state. However, when balance.override is set to TRUE, then the function will work regardless.
tol
The integral utility matrix is rounded to the number of digits specified in tol. This approximation eleminates very small numbers introduced due to numerical error in the ginv function. It does not eliminate the small numerical error introduced in larger values, but does truncate the numbers.

Value

D
Direct flow utility intensity matrix. (fij-fji)/Ti for i,j=1:n
U
Nondimensional integral flow utility
Y
Dimensional integral flow utility
ns
If type is set to 'flow', this is a list of flow utility network statistics including: the dominant eigenvalue of D (lambda\_1D), flow based network synergism (synergism.F), and flow based network mutualism (mutualism.F).
DS
Direct storage utility intensity matrix. (fij-fji)/xi for i,j=1:n
US
Nondimensional integral storage utility
YS
Dimensional integral storage utility
ns
If type is set to 'storage', this is a list of storage utility network statistics including: the dominant eigenvalue of DS (lambda_1DS), storage based network synergism (synergism.S), and storage based network mutualism (mutualism.S).

References

Fath, B.D. and Patten, B.C. 1998. Network synergism: emergence of positive relations in ecological systems. Ecol. Model. 107:127--143.

Fath, B.D. and Borrett, S.R. 2006. A Matlab function for Network Environ Analysis. Environ. Model. Soft. 21: 375--405.

Patten, B.C. 1991. Network ecology: Indirect determination of the life-environment relationship in ecosystems. In: Higashi, M. and Burns, T. (eds). Theoretical Studies of Ecosystems: The Network Perspective. Cambridge University Press. New York.

See Also

enaFlow,enaStorage,enaMTI

Examples

Run this code
data(troModels)
U <- enaUtility(troModels[[6]],type="flow",eigen.check=FALSE)
attributes(U)
US <-enaUtility(troModels[[6]],type="storage",eigen.check=FALSE)

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