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CHAPTER 25

Ind icator Species An alysis

From: McCune, B. & J. B. Grace. 2002. Analysis of Ecological Communities . MjM Software Design,Gleneden Beach, Oregon http://www.pcord.com

Tables, Figures, and Equations

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Then calculate the relative abundance RAkj of species j ingroup k (this measures exclusiveness, the concentration ofabundance into a particular group):

jk

kj

k=1

g

kj RA =

x

x

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Group

Sequence 1 2 3Identifier: 1 2 3

N of items: 18 18 18Species Avg Max

1 Larocc 33 100 0 0 1002 Piceng 33 63 13 63 253 Pincon 33 50 50 25 254 Pinpon 33 100 0 100 05 Acergl 33 100 100 0 06 Adebic 33 86 0 14 86

7 Amealn 33 75 25 75 08 Antluz 33 44 44 19 379 Antmic 33 100 0 0 100

10 Apoand 33 100 0 100 011 Aranud 33 54 30 17 5412 Arncor 33 100 0 100 0

.

etc...

83 Phleum 33 67 67 6 2884 Poapra 33 53 53 5 4285 UnkGr1 33 100 0 100 0

Averages 33 73 31 33 36

Table 25.1. Relative abundance (%) ofeach species in each group defined bytopographic position. The data matrix

contains 54 plots and 85 species. Eachgroup contains 18 items. “Sequence” isthe sequence of occurrence of the groupin the data; “Max” is the maximumrelative abundance of the species.

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2. Calculate the proportional frequency of the species ineach group (the proportion of sample units in each groupthat contain that species).

First transform A to a matrix of presence-absence, B:

ij ij0b = a

Then calculate relative frequency RF kj of species j in group k :

kji=

nijk

k

RF =b

n

k

1

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Group



1 Larocc 2 6 0 0 62 Piceng 15 28 6 28 113 Pincon 6 6 6 6 64 Pinpon 6 17 0 17 05 Acergl 11 33 33 0 06 Adebic 13 33 0 6 337 Amealn 37 72 39 72 08 Antluz 26 39 39 17 229 Antmic 2 6 0 0 6


.etc...


Averages 21 32 20 21 21

Table 25.2. Relative frequency (%)of each species in each group defined

by topographic position. The datamatrix contains 54 plots and 85species. “Max” is the maximumrelative frequency of each species.

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3. Combine the two proportions calculated in steps 1 and 2 by multiplying them. Express the result as a percentage,

yielding an indicator value ( IV kj) for each species j in eachgroup k .

kj kj kj IV = RA RF 100 ( )

Because the component terms are multiplied, both indicatorcriteria must be high for the overall indicator value to behigh. Conversely, if either term is low, then the species isconsidered a poor indicator.

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4. The highest indicator value ( IV max) for a givenspecies across groups is saved as a summary of theoverall indicator value of that species.

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Group



1 Larocc 2 6 0 0 62 Piceng 7 17 1 17 33 Pincon 2 3 3 1 14 Pinpon 6 17 0 17 05 Acergl 11 33 33 0 06 Adebic 10 29 0 1 29

7 Amealn 21 54 10 54 08 Antluz 9 17 17 3 89 Antmic 2 6 0 0 6


.

etc...


Averages 9 20 8 10 10

Table 25.3. Indicator values (% of perfect indication) of eachspecies for each group, rounded

to the nearest whole percentage.These values were obtained bycombining the relativeabundances and relative

frequencies in Tables 25.1 and25.2. The data matrix contains54 plots and 85 species. “Max”is the maximum indicator valueof the species across the threegroups.

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5. Evaluate statistical significance of IV max byrandomly reassigning SUs to groups 1000 times. Eachtime, calculate IV max .

H0: IV max is no larger than would be expected bychance (i.e., that the species has no indicator value).

p (type I error) = proportion of times that the IV max from the randomized data set equals or exceeds the

IV max from the actual data set.

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Observed IV fromIndicator randomized groups

Species Value ( IV ) Mean S.Dev p

1 Larocc 5.6 5.6 0.17 0.999

2 Piceng 17.4 11.6 5.08 0.2373 Pincon 2.8 7.4 3.84 0.9994 Pinpon 16.7 7.2 4.03 0.1105 Acergl 33.3 10.2 4.85 0.0056 Adebic 28.6 10.9 4.69 0.0197 Amealn 54.2 20.5 5.13 0

8 Antluz 17 15.9 5.27 0.2999 Antmic 5.6 5.6 0.17 0.99910 Apoand 44.4 11.5 4.68 011 Aranud 44.8 26.5 5.08 0.00512 Arncor 5.6 5.6 0.17 0.999

.

etc...

83 Phleum 18.5 12.6 4.86 0.13384 Poapra 11.7 12.7 5.1 0.55085 UnkGr1 5.6 5.6 0.17 0.999

Table 25.4. Monte Carlo test of significance of observedmaximum indicator value ( IV )

for each species, based on1000 randomizations. Themeans and standard deviationsof the IV from therandomizations are given alongwith p-values for thehypothesis of no difference

between groups. The p-valueis based on the proportion of

randomized trials withindicator value equal to orexceeding the observedindicator value.

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All Net TowsBosmina longirostris (100)Kellicottia longispina (91)

Polyarthra dolichoptera (91)Asplanchna sp. (67)

Filinia terminalis (44)Divided By Zone

Pelagic Littoral

Kellicottia longispina (81) Lecane sp. (66)Filinia terminalis (76) Unid. Nauplii (51)

Polyarthra dolichoptera (62) Unid. Chironomid (44)Bosmina longirostris (59) Chydorus sphaericus (24)

Asplanchna sp. (45)Synchaeta sp. (41)

Philodina acuticornis (27)Keratella cochlearis (26)

Divided by Depth

Deep SurfacePolyarthra dolichoptera (76) one Significant

Filinia terminalis (72)Kellicottia longispina (65)Bosmina longirostris (61)

Synchaeta sp. (50)Philodina acuticornis (40)

Figure 25.1. Portion of an indicatorspecies hierarchy for freshwaterzooplankton, based on Warncke

(1998). Only statistically significantindicator species are shown. Groupsand subgroups were based on ahierarchical division of sample units.The numbers for each speciesrepresent the percentage of perfectindication ( IV ) of that species in thatsubgroup.

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Informa tion Rem aining (% )100 75 50 25 0

S TA ND 1S TA ND 3

S TA ND 2S TA ND 5S TA ND 7S TA ND 6S TA ND 4S TA N1 0S TA N1 6S TA N1 7

S TA N1 8S TA N1 9S TA ND 8S TA N1 2S TA ND 9S TA N1 3S TA N1 1S TA N1 4S TA N1 5

Figure 25.2. Dendrogram from cluster analysis of the BisonRange data set. Is there an optimum number of clusters?

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0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

234567891011121314151617

Number of clusters

A v e r a g e p

0

2

4

6

8

10

12

14

234567891011121314151617

Number of clusters

S i g n

i f i c a n

t I n d i c a

t o r s

Minimum:(4, 0.177)

Figure 25.3. Use of indicator species analysis as an objectivecriterion for pruning a dendrogram. Left: change in p-valuefrom the randomization tests, averaged across species at eachstep in the clustering. Right: number of species with p 0.05for each step of clustering.

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Figure 25.4. Ordination ofspecies based on indicator

species analysis, contrastingassociation with two mountainranges, the Cascades and theCoast Range (from Peterson &McCune 2001). See text fordetails.

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