Biodiversity Indices Lab

Question 1

What can be measured under the topic of biodiversity?

Answer 1

• Species Richness
• Abundance
• Diversity

Question 2

Define “diversity”

Answer 2

Diversity is the relationship between richness and abundance

Question 3

Biodiversity indices use both…?

Answer 3

Richness and abundance

Question 4

How do biodiversity indices work?

Answer 4

They differ in mathematical methods by giving greater prominence to either richness or abundance.

Question 5

Define “species richness (S)”

Answer 5

• Species richness is the total no. of species identified (incidence/presence data) per unit area.
• It is the simplest descriptor of community structure.

Question 6

Can species richness (S) be used as independent information?

Answer 6

No, alone it is largely uninformative.

Question 7

How is species richness used to assess diversity?

Answer 7

• It uses indices that incorporate information on abundance.
• It controls the effects of sample size (the no. of species is dependent on the samples size).

Question 8

What is the formula for “Menhinick’s Index”?

Answer 8

D = S/ √ N

Question 9

What values do S and N represent in Menhinick’s Index?

Answer 9

S = No. of different species in the sample

N = Total no. of individuals in the sample

Question 10

Menhinick’s Index tried to account for the sample size but is strongly influenced by…?

Answer 10

The sampling effort

Question 11

Dominance indices are measured using the…?

Answer 11

Simpson’s Diversity Index (D) (1/D)

Question 12

Information indices are measured using the…?

Answer 12

Shannon-Weiner Index (H’)

Question 13

Dominance indices are…?

Answer 13

Weighted towards abundant and common species (there are a few rare species that will not affect the diversity).

Question 14

Information indices…?

Answer 14

• Can take into account rare species in a community
• Assume all species are represented in a sample and are sampled randomly

Question 15

What does Simpson’s diversity (1/D) measure?

Answer 15

It measures the probability of any two individuals being conspecifics if randomly drawn from an infinitely large community.

Question 16

Using Simpson’s Index, index increases with…?

Answer 16

Diversity

Question 17

What is Shannon-Weiner (H’) to measure?

Answer 17

Used for t-tests and ANOVAs to compare sites (providing they meet the assumptions of the tests eg. normality etc).

Question 18

What values does the Shannon-Weiner Index (H’) usually provide?

Answer 18

It usually provides values between 1.5 - 3.5

Question 19

What is Everness (sample) measure (E)/ Piou’s (community) everness (J)?

Answer 19

It compares actual diversity values to the maximum diversity while assuming all species are present within the sample.

Question 20

What is the equation for “Everness”?

Answer 20

Everness = H’/H’ max =H’/LnS

Question 21

What equation values do H’ , H’ max and S represent?

Answer 21

H’ = Shannon-Weiner Index

H’ max = Maximum diversity which could occur if all species were equally abundant

S = Total no. of species

Question 22

What do the equation values E/J and J represent?

Answer 22

E/J = constrained between 0-0.1

J = The less variation in communities between species the higher the value

Question 23

What are the Community index of Similarities based on?

Answer 23

They are presence-absence based

i.e. species richness based

Question 24

How is the Community index of similarities measured?

Answer 24

It’s measured using Sorensen’s Coefficient (CC)

Question 25

What is the equation for Sorensen’s Coefficient (CC)?

Answer 25

CC = 2C/S1+S2

Question 26

What do the values C, S1 and S2 represent in Sorensen’s Coefficient (CC)?

Answer 26

C = The no. of species the two communities have in common

S1 = The total no. of species found in community 1

S2 = The total no. of species found in community 2

Question 27

Interpret the values for Sorensen’s Coefficient (CC)

Answer 27

Values will lie between 0 and 1

The closer the value is to 1 the more the two communities (S1 & S2) have in common.

Complete community overlap = 1
Complete community dissimilarity = 0