Biodiversity Lab Essay

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Biodiversity Lab

Biodiversity is a measurement of species richness or more specifically stated; it is the number of species present in a defined geographical unit (Begon, et al. , 2005). In this study we will measure and compare species diversity for five habitats. We will also analyze their ability to support rare species. It is important to consider biodiversity when studying habitat sustainability because from an evolutionary standpoint the more diverse an area, the more viable and adept at adapting to environmental changes. Simply, the more genetically diverse an area, the more fit the population.

It is especially important to study local populations when developing land areas to be sure there are minimal affects on the local ecology and that changes to current habitats will not wipe out species of plants or animals. ‘Species richness is a fundamental measurement. . . and underlies many ecological models and conservation strategies’ (Gotelli, Colwell, 2001). Methods and Materials For this study we used a variety of beans to represent the species present in a populous. We used a random sampling method to select 300 representatives from our population and then recorded the numbers of species in our draw.

We also used a random sampling method for varied draws of 100, 150, 200, 250, and 300 for our 5 habitats. We graphed Rank Abundance plots to compare species richness in our sampled populations to our total population. We also used Shannon-Wiener Index and evenness calculations to look at species density because only looking at variety of species does not give much information on sustainability. Finally we used rarefaction calculations to estimate the number of species expected in a random sample to address the common issue of comparing data of different sample sizes. Results

From our RA plots we found that the sampled populations do follow the same trend as the total population in terms of species abundance (Figure 1, 2, 3). The shape of the curve indicates that as speciation increases there are overall lower abundances of each species (McGill et al. 2007). Although species abundance follows the same trend, in our sampling not all species were represented. Some samples showed no representatives of certain species which demonstrates the weakness of only looking at RA plots; they do not address species density within a population, so smaller sample sizes may not even represent all species in existence.

To evaluate species richness based on density we did Shannon-Weiner calculations and evenness calculations and graphed our data set. When looking at variation in abundance among species we found that samples for both consistent and varied sampling followed the same trend as for our total population with an average H’ of 2. 6 +/- 0. 1 (Figure 4, Table 1). The only potential discrepancy was in our samples for Population 2 our density estimates were within +/- 0. 2. Our total population showed more variation in species density than our samples for that population. Our evenness data also showed the same trend with values of .

85 +/- . 04 (Figure 5, Table 2). Our evenness calculations showed similar distribution of species in the population. To get a better picture of species richness we rarefied our data for our varied sampling. Rarefaction is important in cases of uneven sampling because it presents a more accurate picture of species richness by essentially ‘standardizing’ the data. In the case of our varied sampling we rarefied the data to 101 samples as it was below the minimum sampling we did of 103 individuals for Population 1. Our rarefied data for varied sampling was slightly lower than data collected for our total and sampled populations.

Rather than 21 different species our rarefied data for our varied data set reported between 18. 6 and 19. 9 (Table 3). Though similar to the total when considering calculated variance, the species totals are still lower. The overall discrepancy in species richness found between sampling and total populations for Population 2 is an indicator of either a lower density throughout the habitat or clustering in an area depending on food and or predation conditions. Discussion Though these analyses give us a snapshot of species numbers and population densities they do not give a completely accurate view of what influences biodiversity of an area.

Calculations done on data collected to determine species richness and evenness only give us a base picture of an area, but do not really show the factors influencing species richness and density, or how adept a population will be at handling environmental changes. Species diversity is influenced by both primary and secondary factors. Primary factors are environmental and include geographical factors such as, latitude, altitude, depth, climate variability, energy input, environmental ‘age’ or ‘harshness’ (Begon, et al. , 2005).

Secondary factors include predation, competition, heterogeneity and community success. In determining the viability of a habitat looking at species richness and density are important, but they should not be the only bits of information considered when deciding whether to develop an adjacent area. Though few primary factors would change in land development, depending on how a species is distributed developing one area could greatly affect a vital environmental predator that keeps certain species in check. Development could be destroying a highly rich food source causing uneven distribution.

It is the secondary factors that are far more important to determining the success of a population and experimentation on species fitness and factors involved in its maintenance is vital to conservation efforts. Figures and Tables Figure 1. Rank –Abundance plot of total population. Figure 2. Rank –Abundance plot of samples of 300 individuals from population. Figure 3. Rank –Abundance plot of samples varying numbers of individuals from population. Figure 4. Diversity Index of species between total populations and same and varied samples. H’ Values Pop 1 Pop 2 Pop 3 Pop 4 Pop 5 Total Pop 2. 65 2. 64 2.

59 2. 53 2. 64 Same N 2. 67 2. 48 2. 66 2. 59 2. 61 Varied N 2. 65 2. 59 2. 63 2. 64 2. 71 Table 1. Shannon-Weiner Index (H’) values for total, same and varied population samples. Figure 5. Eveness of species between total populations and same and varied samples. E Values Pop 1 Pop 2 Pop 3 Pop 4 Pop 5 Total Pop 0. 87 0. 87 0. 85 0. 83 0. 87 Same N 0. 88 0. 81 0. 87 0. 85 0. 86 Varied N 0. 87 0. 85 0. 86 0. 87 0. 89 Table 2. Evenness (E) values for total, same and varied population samples. Figure 6. Graphical analysis of rarefied data from varied sampling. Species Estimates Pop 1 Pop 2 Pop 3 Pop 4 Pop 5

Total Pop 21 21 21 21 21 Same N 20. 2 17. 3 20. 8 20. 2 20 Varied N (101 Rarefied) 19. 9 18. 6 19. 7 19. 2 19. 3 Table 3. Species estimates compared to rarefied data from random sampling. References Begon, M. ; Harper, J. L. ; Townsend, C. R. (2005). Ecology: From Individuals to Ecosystems, 4th Edition. Blackwell Science Ltd. Gotelli, Nicholas; Colwell, Robert. (2001). Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness, Ecology Letters, (4), 379-391. Hughes, Jennifer; et al. (2001). Counting the Uncountable: Statistical Approaches to Estimating

Microbial Diversity. American Society for Microbiology, 67(10), 4399–4406. Retrieved Mar 29, 2009 from http://www. pubmedcentral. nih. gov/articlerender. fcgi? artid=93182 McGill, Brian, et al. (2007). Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework, Ecology Letters, (10), 995-1015. Retrieved Mar 29,2009 from http://biology. uoregon. edu/people/green/publications/McGIll%20et%20al%202007. pdf. Author, A. A. (Year of publication). Title of work: Capital letter also for subtitle. Location: Publisher.

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