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ecology of phasmids - KLUEDO - Universität Kaiserslautern

ecology of phasmids - KLUEDO - Universität Kaiserslautern

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Community structure & host range 13<br />

phasmid community structure (e.g., niche breadth or niche overlap) for three reasons: 1) these data were<br />

biased towards collection on specific host plants and hence towards focal phasmid species; 2) rare<br />

phasmid species were underrepresented in these field records; and 3) species abundances would be<br />

underestimated because <strong>of</strong> the collection (i.e., removal) <strong>of</strong> specimens from the community. To calculate<br />

relative abundances <strong>of</strong> phasmid species data from line-transects in the understory and at forest edges<br />

were pooled (for each habitat per monitor date) due to too many zero counts, especially in the<br />

understory.<br />

This data also built the pool for the calculation <strong>of</strong> diversity, eveness and similarity <strong>of</strong> phasmid<br />

communities for the specific habitat. All measures <strong>of</strong> community structure were based on methods<br />

described by Krebs (1989). To facilitate comparison among studies, I decided to use the most common<br />

measures (applicability to the dataset presupposed).<br />

Similarity in species composition between habitats was calculated with the index <strong>of</strong> Morisita Cλ:<br />

Equation 2-1<br />

C<br />

λ<br />

2<br />

= ∑<br />

n<br />

X<br />

ij<br />

X<br />

ik<br />

( λ1<br />

+ λ2<br />

) N j N k<br />

where Cλ = Morisita’s index <strong>of</strong> similarity between samples j and k<br />

Xij, Xik = Number <strong>of</strong> individuals <strong>of</strong> species i in samples j and k<br />

Nj, Nk = ∑Xij, ∑Xik = Total number <strong>of</strong> individuals in sample j and in sample k respectively<br />

[ X ij ( X ij −1)<br />

]<br />

( N −1)<br />

1 = ∑<br />

n<br />

λ and<br />

N<br />

j<br />

j<br />

2 = ∑<br />

n<br />

λ<br />

N<br />

[ X ik ( X ik −1)<br />

]<br />

( N −1)<br />

The Morisita index <strong>of</strong> similarity is a quantitative measure for similarity and ranges from 0 for no<br />

similarity in species composition to 1 for identical species composition.<br />

Species diversity and eveness were calculated on the base <strong>of</strong> the Shannon-Wiener Function:<br />

Equation 2-2<br />

H<br />

'<br />

=<br />

s<br />

∑<br />

i=<br />

1<br />

( p )(log<br />

i<br />

2<br />

where H’ = Index <strong>of</strong> species diversity measured by the Shannon–Wiener function<br />

s = Number <strong>of</strong> species<br />

pi = Proportion <strong>of</strong> total sample belonging to the species i<br />

The Shannon–Wiener index <strong>of</strong> species diversity expresses the uncertainty <strong>of</strong> predicting the species <strong>of</strong><br />

the next individual sampled. Thus if H’ = 0 then all individuals in a sample belong to one species. H’ is<br />

increasing with the number <strong>of</strong> species in a sample and with increasing eveness <strong>of</strong> these species. The<br />

most common approach to measure eveness is to scale the observed index <strong>of</strong> species diversity relative to<br />

its maximum value when each species in the sample is represented by the same number <strong>of</strong> individuals.<br />

In case <strong>of</strong> the Shannon Wiener Function maximum diversity occurs when p = 1/S and can be calculated<br />

as:<br />

Equation 2-3<br />

'<br />

H MAX =<br />

log 2<br />

S<br />

p )<br />

i<br />

k<br />

k

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