Diversity of Stream Organisms Methods


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1 Stream Diversity 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.
2 Stream Diversity 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 45 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. The socalled 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 on the horizontal axis of your graph. Take the next most common species and call that species 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 is the percentage of all individuals who fall into species i, then: 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
3 Stream Diversity 3 Percentage of individuals Rank of Species (,, n) Geometric Figure. Relative abundance of species Lognormal 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 basic forms of the species abundance curve, 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. 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 moreorless 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 ( ) as described above and then plug those values into this equation: 3
4 Stream Diversity 4 s H = [ ln( pi )] i= 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 5 clean streams are sampled, then sampled again five years later. Then the 5 earlier samples can be compared with the 5 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 ). Species Number Sampling Effort Figure. 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 994). Use the following equations to estimate the total species number and its variance: 4
5 Stream Diversity 5 S total σ S total a = Sobserved + b 4 a / b a = b + 4 b 3 a / b + 4 In these Equations S total is the total number of species in the community, which is what we are trying the estimate. S observed 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 individuals doubleons. If a= 0 or b= 0, substitute a= or b=. σ is the variance of S total. For example, suppose we sample a marine fish community with a trawl, and count the following numbers of individuals from our trawl: Species Number of Individuals anchovies 75 surf perch 5 rock bass 8 ling cod amberjack sculpin flatfish porcupine fish For these data the S observed 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, because there are species represented by individuals each (ling cod and amberjack). From the equations, the estimate of S total is 0.5, and the estimate of variance is 7.9. 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 S total? 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 00 individuals and 4 tree species: 5
6 Stream Diversity 6 Species Community Community sugar maple 5 97 red maple 5 red oak 5 paper birch 5 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 ShannonWiener 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 97). 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 PIE = N i= ( ) : In this formula, N is the total number of individuals in the collection, S is the number of species, and 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 : Species n i i sugar maple red maple red oak paper birch N = 00 = 0.5 PIE =
7 Stream Diversity 7 Community : Species n i i sugar maple red maple red oak paper birch N = 00 = 0.94 PIE = Thus, in the first community, the probability that two randomly selected trees will represent different species is 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 Use PIE to estimate the diversity your stream samples. References: Hulbert, S. H. 97. The nonconcept of species diversity: a critique and alternative parameters. Ecology 5: Colwell, R. K. and J. A. Coddington 994. Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society of London B 345:08. 7
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