Download Diversity of Stream Organisms

Stream Diversity 1
Diversity of Stream Organisms
Some of the most interesting questions in science are so simple that they have a
childlike quality to them. One such question: Why are there so many species? There
appears to be millions of species of animals and plants on this planet; why aren't there
only thousands, or even just hundreds? A related issue concerns the difference in
richness of species at different locations. A tropical rainforest contains a huge number
of species when compared to a temperate forest. Why? Ecologists have long pondered
these issues and have developed the study of community ecology in an attempt to
understand the forces that shape the structure of communities. By community structure
we mean the number of species (species density or species richness), the relative
abundance of each species, the taxonomic composition of the community, and the
stability properties of the community.
In this lab you will examine the species diversity of a community of animals that live in a
Vermont stream. Strictly speaking you will study only a portion of the overall community,
just the large invertebrates and perhaps some vertebrates as well. Few ecologists ever
attempt to study any complete community!
The diversity of life in streams is interesting to study for theoretical reasons, and also
because it can be a measure of the health of the habitat. Many years ago ecologists
discovered that the species diversity of streams usually declines when they are polluted.
We say usually because there are some cases in which the diversity actually may
increase because addition of nutrients may encourage an entire new assemblage of
organisms. Thus, the study of stream communities takes on a practical
significance...one that may prove vital in our efforts to clean up our waterways.
In this lab we might compare two streams, perhaps one that is polluted with a clean
stream. Instead we will attempt to calibrate the methods of stream sampling by
comparing samples from the same stream. We would expect, if our methods are sound,
to get the same results if we repeatedly sample from the same stream. Also important,
we might want to know if the different groups of researchers get the same results using
the same techniques. If results differ among groups, this suggests the techniques are
not easy to standardize when different people use them.
Methods
You will travel in a group to a stream approximately 30 miles from the UVM campus.
There will be a supply of boots for everyone to spend some time in the stream. You
should come prepared to get wet and dirty. You will use a Serber Sampler and forceps
to collect stream organisms. Your Laboratory Instructor will demonstrate the technique.
Although the technique looks simple, there are lots of ways to get nonstandard results
so you should watch closely how to use the sampler.
Bring the sampler back to shore and those not in the water can sort the organisms.
Dump the contents in a pan with enough water to keep the animals alive so you can find
them easily.
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Stream Diversity 2
Sort the specimens by OTU, or operational taxonomic unit. This means sort them by
your best guess as to their family or other taxonomic group.
One student should be a record keeper to keep track of the number of samples that
were made. This may be important when comparing results among lab sections. You
should do at least 4-5 samples. For the later lab sections, you don’t want to resample
the same location as earlier sections. Your Laboratory Instructor will know where you
should be sampling.
Some aquatic insects you might see are:
Order:
Diptera
Plecoptera
Ephemeroptera
Coleoptera
Hemiptera
Odonata
Lepidoptera
Megaloptera
Trichoptera
Common Name:
flies
stoneflies
mayflies
beetles
true bugs
damselflies
butterflies
dobsonflies
caddisflies
Analysis
Use your data set showing number of individuals of each species to conduct the
following analysis:
Species density.
This is strictly the number of species (or families) found in the sample. Perhaps you
might want to restrict this to only insects...why?
Relative abundance curve.
See Figure 1. The so-called species importance curve or relative abundance curve
simply plots up the species in order of their abundance against their percent abundance
in the sample. First calculate the percent of all organisms that fall into each of the
species collected. Next pick the most abundant species and plot that one as “species 1”
on the horizontal axis of your graph. Take the next most common species and call that
“species 2” and so forth. On the vertical axis you plot the percent abundance of each
species. We calculate percent abundance as the percent of all individuals in the
community that fall into each species. That is, if pi is the percentage of all individuals
who fall into species i, then:
pi =
number of individuals of species i
total number of individuals collected
When you construct this graph you will see that the points on the graph must either stay
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Stream Diversity 3
100
Lognormal
75
Percentage of
individuals
50
Broken Stick
level (if all species
are equally
abundant) or must
drop. The points
cannot go up
because of the
way you
constructed the
graph.
Ecologists have
determined that
there are several
Rank of Species
basic forms of the
(1,2,…n)
species
abundance curve,
Figure 1. Relative abundance of species
suggesting there
are different forces
at work in different communities that shape the relative abundance of species. These
different forms of the curve have been called (a) lognormal distribution in which species
richness and species diversity is high; (b) geometric series in which species diversity
tends to be low and one or a few species are very common and all others are rare; and
(c) the broken stick distribution which often fits subcommunities of species that divide up
resources, such as bird communities.
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Geometric
Species diversity
This measure combines both species richness and the relative abundance of the
species. High species diversity measures can mean either more species in the
community, more even abundance of the species that are there, or both. There are a
variety of ways to combine information on both numbers of species and their relative
abundance. Two formulae are in common use; ecologists argue about which is better,
but probably there is no “best” way to calculate the species diversity of a community.
The first measure of species diversity is the Shannon Index which is derived from
information theory (Shannon was interested in how information is transmitted through
phone lines!) Suppose we draw an individual organism from the community at random.
If we could guess the identity of that species in advance most of the time because either
there were few species or one or two species were very abundant, then species
diversity would be low and the Shannon Index would be low. If, on the other hand, we
have a small chance of guessing the identity of the species because there were many,
many species all more-or-less equally abundant, then the Shannon Index would be
high. Perhaps now you might begin to see why the Shannon Index is sometimes called
an index of “information” or “uncertainty”.
To calculate the Shannon Index we first must calculate the relative abundances of each
species (pi) as described above and then plug those values into this equation:
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Stream Diversity 4
s
H = −∑ [ pi × ln( pi )]
i =1
What do we do once we have the value of the Shannon measure? Suppose one stream
has a H of 3.5 and another has a H of 5.6, is the species diversity different for the two
streams? We would have to know the distribution of each of these values, similar to the
way we determined the distribution of Chi Square. This has been worked out for the
Shannon index, but there remains a major problem. We can’t even begin to say what
the biological difference is between an index of 3.5 and 5.6, or any other values. Usually
the measures are used in other ways. Perhaps 25 clean streams are sampled, then
sampled again five years later. Then the 25 earlier samples can be compared with the
25 later samples to see if there was a change in the values. For our purposes, we must
“eyeball” the results.
Quantifying Biodiversity
Once we have sampled an assemblage of species, how do we quantify its biodiversity?
There are many components of diversity that we could choose to measure, but the most
important are species richness and species evenness.
Species Richness
Species richness refers to the total number of species in the community. This seems
straightforward enough, until we realize that the more individuals we examine, the more
species we are likely to find. Obviously, this sampling curve will eventually reach an
asymptote that represents the true number of species in the community (Figure 2).
Species
Number
Sampling
Effort
Figure 2. Species number as a function of
sampling effort
The problem is that, without a great deal of work, it is difficult to know where a particular
sample falls on the sampling curve. Fortunately, we can take advantage of some recent
developments in probability theory to answer this question (Colwell and Coddington
1994). Use the following equations to estimate the total species number and its
variance:
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S total = S observed +
σ S2
total
a2
2b
 a / b  4  a  3  a / b  2 
= b 
 
 +  +
 4   b   4  
In these Equations Stotal is the total number of species in the community, which is what
we are trying the estimate. Sobserved is the number of species that we have counted in
our data. The variable a is the number of species represented by exactly one individual
“singletons”, and b is the number of species represented by exactly 2 individuals
“doubleons”. If a= 0 or b= 0, substitute a=1 or b= 1. σ2 is the variance of Stotal.
For example, suppose we sample a marine fish community with a trawl, and count the
following numbers of individuals from our trawl:
Species
anchovies
surf perch
rock bass
ling cod
amberjack
sculpin
flatfish
porcupine fish
Number of Individuals
75
25
8
2
2
1
1
1
For these data the Sobserved is 8 species. The variable a equals 3, because there are 3
species represented by only one individual each (sculpin, flatfish, porcupine fish). The
variable b equals 2, because there are 2 species represented by 2 individuals each (ling
cod and amberjack). From the equations, the estimate of Stotal is 10.25, and the
estimate of variance is 7.91.
These equations can be used to estimate the total species richness for your stream
diversity data. Before making the calculation, take a guess at how many species that
you did not sample are actually present in these communities. How close is your guess
to the estimate of Stotal? Under what circumstances do you think your estimate might be
seriously incorrect?
Species Evenness
In addition to species richness, a second component of the diversity of a community is
species evenness. Calculating species evenness is more challenging. By evenness, we
mean the relative numbers of individuals in the sample. For example, consider the
following two hypothetical samples form different tree communities. Each sample has
100 individuals and 4 tree species:
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Species
sugar maple
red maple
red oak
paper birch
Community
1
25
25
25
25
Community
2
97
1
1
1
Most ecologists would agree that the first sample has a higher diversity than the second
because the distribution of individuals among species is relatively even. For many years
the Shannon-Wiener index was the standard index used to estimate diversity of
samples. The index measured the amount of “information” contained in a sample.
However, the index was sensitive to both the number of species and the evenness of
the sample. Also, there was no easy way to interpret the size of a particular index.
A better way to measure the evenness is to use the index PIE (Probability of an
Interspecific Encounter). PIE measures the probability that two individuals randomly
chosen form a community represent different species (Hulbert 1971). The larger this
probability is, the more even the distribution of individuals among the samples. PIE is
calculated according to the following formula
( )
s
 N 
2 
PIE = 
 1 − ∑ pi  :
 N − 1   i =1

In this formula, N is the total number of individuals in the collection, S is the number of
species, and pi is the proportion of individuals represented by species i. The following
table illustrates the calculation of PIE for both of the hypothetical communities listed
above:
Community 1:
Species
sugar maple
red maple
red oak
paper birch
ni
25
25
25
25
N = 100
i
1
2
3
4
PIE = 0.7576
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pi
0.25
0.25
0.25
0.25
pi2
0.0625
0.0625
0.0625
0.0625
∑ = 0.25
Stream Diversity 7
Community 2:
Species
sugar maple
red maple
red oak
paper birch
ni
97
1
1
1
N = 100
i
1
2
3
4
pi
0.97
0.01
0.01
0.01
pi2
0.9409
0.0001
0.0001
0.0001
∑ = 0.9412
PIE = 0.0594
Thus, in the first community, the probability that two randomly selected trees will
represent different species is 0.7576. In contrast, for the second community, most trees
randomly selected will be sugar maples, so the probability of randomly selecting two
different species is only 0.0594.
Use PIE to estimate the diversity your stream samples.
References:
Hulbert, S. H. 1971. The nonconcept of species diversity: a critique and alternative
parameters. Ecology 52:577-585.
Colwell, R. K. and J. A. Coddington 1994. Estimating terrestrial biodiversity through
extrapolation. Philosophical Transactions of the Royal Society of London B 345:101118.
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