iap: Number of Companion Species (IAP)

In jarioksa/natto: An Extreme 'vegan' Package of Experimental Code

Number of Companion Species (IAP)

Description

Function finds the number of companion species or the average species richness of other species for each species in a community. This is the quality index Q of Index of Atmospheric Purity (IAP) in lichen bioindication (LeBlanc & De Sloover 1970). The non-randomness of low or high Q values is found by randomization.

Usage

iapq(comm, freq.min = 5, permutations = 999)

iap(comm, iapq)

## S3 method for class 'iapq'
plot(x, ...)

## S3 method for class 'iapq'
summary(object, ...)

Arguments

comm	The community data frame.
freq.min	Minimum number of occurrences for analysed species.
permutations	Number of permutations to assess the randomized number of companion species.
iapq	Result of iapq.
x	iapq result object.
...	Other arguments to the function.
object	iapq result object.

Details

Index of Atmospheric Purity (IAP) is used in bioindication with epiphytic lichens and bryophytes (LeBlanc & De Sloover 1970). It derives species indicator scores (Q) as the number of other species in sampling units where each focal species is present, and then finds the IAP values for each sampling unit as scaled weighted sum of species indicator values.

Function iapq finds the Q values for all species in a community data set. Function iap applies these values for a community data set to evalute the IAP values for each site. The species are matched by names. LeBlanc & De Sloover (1970) used scaled abundance values and divided the weighted sum by 10, but this is not done in the current function, but this is left to the user.

Function iapq is a general measure of indicator value for species richness and can well be used outside lichen bioindication. The Q value is the average species richness in sampling units where the species is present, excluding the species itself from the richness. For rare species, Q is based on small sample size, and is therefore more variable than for common species. The iapq function assesses the non-randomness (‘significance’) of Q by taking random samples of the same size as the frequency (number of occurrence) of the focal species and finding the average richness (without the focal species) in these samples. Because species are more likely to be present in species-rich sampling units than in species-poor, the random sampling uses the observed species richness (with the focal species) as weights in random sampling. Testing is two-sided and the number of greater or less random values is multiplied with two. The observed value of Q is included in the random sample of species richness values both in assessing the p-value and in estimating the quantiles.

References

LeBlanc, S.C. & De Sloover, J. (1970) Relation between industrialization and the distribution and growth of epiphytic lichens and mosses in Montreal. Can. J. Bot. 48, 1485–1496.

jarioksa/natto documentation built on March 28, 2024, 12:45 a.m.