
APES

SHARON KOLAWOLE'S LABS
Biodiversity of Leaf Litter Lab
Collaborators: Alex King, Micaela Strickland, Habiba
Introduction: Simpson's Diveristy Index is a measure of diversity. In ecology, it is often used to quantify the biodiversity of a habitat. It takes into account the number of species present, as well as the abundance of each species. Species richness is the number of species per sample is a measure of richness. Species eveness is a measure of the relative abundance of different species making up the richness of an area.
Problem: What is the biodiversity of a sample of leaf litter?
Hypothesis: If a sample of leaf litter is taken from the forest behind the school, then around 10 species will b found in the sample and there will be a lot of eveness.
Parts of the Experiment:
Control group- soil
Experimental group- leaf litter (outdoor trail/gunshers woods)
Independent variable- location of where the samples leaf litter were collected
Dependent variable- amount of biodiversity in the samples
Controlled variables- materials
Materials:
· samples of leaf litter
· samples of soil
· alcohol
· Milk jug cartons
· compound microscopes
· beakers
· lamps (source of light)
· invertebrate identification pages
Methods:
1. Collect a sample of leaf litter and a sample of soil from forested area.
2. Place your sample of leaf litter into four Berlese Funnels under the light source, as well as your sample of soil in two Berlese Funnels. Place a small beaker of alcohol under the funnel.
3. After a week, collect the entire set of beakers and examine the organisms confined inside. Place what is in the beaker on separate petri dishes and examine them under the microscopes. You will need to calculate the number of each species you have, and identify them.
4. Use the formula provided in the background information for Simpson's Index, calculate the diversity indices for all the samples.
5. Compare the diversity between the soil and the leaf litter
Data:
Simspon's Index: 2(1)+6(5)+2(1)+1(0)+2(1)+1(0)/14(13)=0.1978
Species richness: high
Species eveness: low
Data Analysis: In the sample of leaf litter, two mites, six proturans, two dipluras, only one psuedoscorpion, two springtails, and one japygid were found in the sample. In total there were six species and fourteen organisms. There were many species, so the sample was high in species richness, but there were plenty proturans and not many of anything else, so the eveness was off balance. The high Simpson's Index indicates that there is very very low biodiversity. The percent error in this lab is (10-6=4/6=66%) 66%.
Location: Wake Forest, North Carolina
Type of Community: Wooded Community
Date: N/A
Weather Description: Sunny, clear skies
Air Temperature: N/A
Soil Temperature: N/A
Relative Humidity: N/A
Time: 7:25-8 AM
Conclusion: The hypothesis predicted that 10 organisms would be found but only 6 were found in the sample. It also stated that there would be species eveness but the eveness was low for the sample.
1. The organisms moved away from the light down the funnel because they liked it better when it's damp,so when the light started the dry the leaves they had to move to somewhere more wet. Also, they like the dark better and tried to stay away from the sunlight (the lamp). This means that in the real enivironment, these organisms are deep in the soil.
2. The biodiversity of this liter is low because the index is closer to one. I think these is because of human activities and that proturan might be the indicator species. So when that species starts to decline, we will know how badly we're damaging the forest.
3.An environmental scientist would have to make more thn one measurement if he was calculating the biodiversity, becausse he will need to account for as many organisms as he can. He would take samples of a large forest by taking it piece by piece. For example: start from deep into the soil and work his way up.
Citations:
"Percentage Error." Percentage Error. N.p., n.d. Web. 04 Oct. 2014. (forgot how to do percent error)
"Leaf Litter." , ,. N.p., n.d. Web. 04 Oct. 2014. (picture)

