1. Biodiversity and Measuring Abundance Lab Manual Chapters 3, 7, and 13

2. Diversity Indices A mathematical measure of species diversity in a community. Reveals important information regarding rarity and commonness of species in a community.

3. Measuring Biodiversity The simplest measure of biodiversity is the number of species – called species richness. –Usually only count resident species, and not accidental or temporary immigrants Another concept of species diversity is heterogeneity: Community 1Community 2 Species A9950 Species B150 Heterogeneity is higher in a community where there are more species and when the species are more equally abundant.

4. Shannon-Wiener Diversity Index (H) Variables associated with the Shannon-Weiner Diversity index:  S – total number of species in the community (richness)  p i – proportion of S made up of the i th species  H max = ln(S)  E H – equitability (evenness; b/t 0 and 1) = H / H max H = -  p i (lnp i )  Larger H = more diversity

5. Species richness and equitability affect the Shannon Wiener index.

6. Simpson’s Index N = total number of individuals p i = proportion of each species Simpson’s Index of Diversity = 1 – D –Ranges from 0 to 1  Low to high diversity D =D = 1 -  p i 2 ranges from 0 to 1

7. Species richness and equitability affect Simpson’s index.

8. Estimating Abundance Weight Sub-sample Used to estimate total number in a sample Method: –Weigh a known number of individuals to get a mean weight –Weigh the entire sample, then divide the total weight by mean weight to get total number of individuals. Example: –10 individuals weigh 68g, so mean weight = 68 / 10 = 6.8 –Total weight = 528, so total number = 528 / 6.8 = 77.6 individuals

9. Quadrat Estimation Individuals spread over a known area Use a known area quadrant to sample Determine the mean number per square area Multiply times total area to get total number of individuals Variance to mean ratio indicates type of distribution: Uniform, Random, or Aggregated

10. Uniform Distribution S 2 /X < 1.0 Random Distribution S 2 /X  1.0 Aggregated Distribution S 2 /X > 1.0 The more uniformly distributed, the less the variance. Variance to mean ration gives us a metric to compare distributions.

11. Quadrat Sampling Randomly select plots and count all individuals in that plot. Each quadrat = 200m 2. Can calculate density as #/m 2 then multiply by total area to estimate the total # of trees. 60,703 m 2 = 15 acres

12. Transect Sample Randomly select a transect of known area and count every tree in that transect. Each transect = 90m 2. Can calculate density for each tree species. 60,703 m 2 = 15 acres

13. Average Size Measure all trees in a transect or quadrat. Produce a size-frequency histogram to show the size distribution. Can also calculate the average size tree.

14. Capture-recapture Method Important tool for estimating density, birth rate, and death rate for mobile animals. Method: –Collect a sample of individuals, mark them, and then release them –After a period, collect more individuals from the wild and count the number that have marks –We assume that a sample, if random, will contain the same proportion of marked individuals as the population does –Estimate population density

15. Marked animals in second sample (R) Total caught in second sample (C) Marked animals in first sample (M) Total population size (N) = 5 20N 16 =N = 64 Peterson Method – Single Census = Proportions

16. Assumptions For All Capture- Recapture Studies Marked and unmarked animals are captured randomly. Marked animals are subject to the same mortality rates as unmarked animals. The Peterson method assumes no mortality during the sampling period. Marked animals are neither lost or overlooked.

17. Example A fish biologist goes out and samples (sample 1) a population of trout. A total of 109 (M) trout were marked and released. At this time, a proportion of fish in the total population has a mark and we assume that this proportion remains constant. On a second sampling trip (sample 2), the biologist collected 177 (C) trout and 57 (R) of those were marked from the initial sample. How large is the population (N)? R/C = M/N  N=MC/R  N = (109)(177)/57  N=338