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Biodiversity Investigation Essay Sample

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Biodiversity Investigation Essay Sample

Defining the Problem and Selecting Variables

Research Question: How does the plant biodiversity of the terrestrial ecosystem between the shore of the Links pond and 10 feet away from the shore differ?

Aim: The aim of this investigation is to determine plant biodiversity of both land next to the pond and land away from the pond to discover what the different in plant biodiversity will be. The degree of biodiversity achieved using the Simpson’s Biodiversity Index.

Hypothesis: Although the samples of land in the area are quite close to each other (10 feet apart) and belong to the same ecosystem, there should be a difference in biodiversity between the two samples of land; the land near the water having greater biodiversity. This hypothesis is suggested due to the land next to the shore having close access to a supply of water and it being a submarine environment, compared to land that is 10 feet further away from the shore.

Independent Variable:

-The various locations of the area

-The season in which data is sampled

-The time of day in which the data is sampled

Dependent Variable:

-The biodiversity of the land samples; measuring the abundance and quantity of different species within the area

Aspect 2

Controlling Variables

The Controlled Variables:

-Control of Quadrats

-The quadrats’ length is 100 centimetres by 100 centimetres and is used for sampling all the directed areas to sample

-Quadrats are also set consistently in the same position to ensure uniformity; determined by the middle 50 cm point facing the shoreline direction

-Quantitative counting within the quadrat of different species and the quantity of the given species

-Control of Sampling/Measuring Area

-Determined circumference of the lake; assigned every metre (location) around the lake to a numerical value; ten random locations were determined with a random number generator, which was the land to be sampled.

-Distance between two quadrats was set at 10 feet, hence after completion with the first quadrat; we measured the distance of 10 feet perpendicular to the pond to determine the location that was 10 feet away.

Aspect 3

Developing a Method for Collecting Data

Materials:

-One Quadrat that measures 100 cm by 100 cm

-Ruler capable of measuring 10 feet

-Camera

-Pencil

-Paper

-Tape

-Random Number Generator

-Specie Book

Procedure:

Background Setup

1. Determine the circumference of the Links pond digitally by Google Earth, or by using the distance measurer and walking around the pond.

2. Mark the quadrat’s 50 cm point (the middle) on one side of the square. That will be the point that is used later to place the quadrat on.

3. Then, use a random number integer generator, with a range from zero all the way to the circumference length in order to find where you will place the quadrat. Do this 10 times.

Actual Investigation

4. Using the numbers obtained, determine placement of the quadrats, the numbers being the distance from the starting point. For example, a value of 27 means that you should place your quadrat 27 metres from the starting point (zero). Use a distance measurer to determine how many metres that you have passed.

5. Hence, place the quadrat’s middle point that you marked in step 2 to place the quadrat on the area. The middle point should be the side that is adjacent and right next to the water’s edge.

6. Determine the plant species and quantity of each species that exist within the quadrat.

7. When complete, use a ruler to take the distance from the middle point mark to 10 feet up ground. The ruler should be perpendicular to the water’s surface.

8. The 10 feet mark of the ruler will be where you place your quadrat on. Make sure that the 10 feet mark of the ruler corresponds to the middle point mark on the quadrat.

9. Repeat the procedure of finding plant species and quantity in the new location of the quadrat.

10. When done, use the next value obtained from the random number generator. Hence, repeat steps 5 through 9 for the remaining values.

After Investigation

11. After all raw data is calculated, tabulate it onto a table. For each of the quadrats, do the following steps, which will help plug in values to the variables on the Diversity Index (reproduced below). Take care to differentiate between the two areas; the samples next to the pond (henceforth known as Region A) and samples 10 feet away (henceforth known as Region B).

a. To find N, which is total number of organisms of all species found, tabulate the total number of each organism that exists within the quadrat. Do that for every quadrat; adding them all up; then averaging them will determine a grand total for the variable “N.”

b. To find n, which is the number of individuals of a particular species, determine the sum of all individuals of a particular species. Add them all up with other quadrats within the same region, then averaging them to determine the grand total for the variable “n.”

c. Use the formula for the index to determine the diversity index value.

12. Compare and Contrast the different diversity index values, if they are different, between the two regions, A and B.

Part 2: Data Collection and Processing

Aspect 1

Recording Raw Data

Figure 1.1 – Raw Data obtained from counting plant species and quantity in Location 1

Location 1

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

6

Dandelions

Legumes

3

Rumex

8

Chinese Fire Weed

Mint

15

Clovers

14

Bermuda Grass

18

Figure 1.2 – Raw Data obtained from counting plant species and quantity in Location 2

Location 2

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

28

4

Dandelions

3

Legumes

43

Rumex

5

Chinese Fire Weed

Mint

Clovers

15

Bermuda Grass

Figure 1.3 – Raw Data obtained from counting plant species and quantity in Location 3

Location 3

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

2

Dandelions

1

Legumes

26

Rumex

Chinese Fire Weed

3

Mint

11

8

Clovers

14

Bermuda Grass

Figure 1.4 – Raw Data obtained from counting plant species and quantity in Location 4

Location 4

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

Dandelions

Legumes

3

Rumex

2

Chinese Fire Weed

Mint

4

21

Clovers

17

18

Bermuda Grass

Figure 1.5 – Raw Data obtained from counting plant species and quantity in Location 5

Location 5

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

5

Dandelions

14

Legumes

Rumex

4

Chinese Fire Weed

Mint

3

18

Clovers

Bermuda Grass

Figure 1.6 – Raw Data obtained from counting plant species and quantity in Location 6

Location 6

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

6

Dandelions

Legumes

15

Rumex

3

Chinese Fire Weed

Mint

14

Clovers

22

Bermuda Grass

4

Figure 1.7 – Raw Data obtained from counting plant species and quantity in Location 7

Location 7

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

14

Dandelions

12

6

Legumes

23

Rumex

Chinese Fire Weed

Mint

Clovers

2

Bermuda Grass

Figure 1.8 – Raw Data obtained from counting plant species and quantity in Location 8

Location 8

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

2

18

Dandelions

2

8

Legumes

13

2

Rumex

Chinese Fire Weed

Mint

16

Clovers

Bermuda Grass

Figure 1.9 – Raw Data obtained from counting plant species and quantity in Location 9

Location 9

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

Dandelions

4

5

Legumes

56

23

Rumex

1

8

Chinese Fire Weed

Mint

Clovers

Bermuda Grass

Figure 2.0 – Raw Data obtained from counting plant species and quantity in Location 10

Location 10

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

2

23

Dandelions

2

2

Legumes

34

5

Rumex

2

Chinese Fire Weed

Mint

Clovers

Bermuda Grass

18

Aspect 2

Processing Raw Data

Figure 3.0 – Raw Data obtained from the sum of all quadrats’ data totaled up together

All Locations Combined

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

38

72

Dandelions

38

21

Legumes

187

44

Rumex

27

0

Chinese Fire Weed

3

0

Mint

33

77

Clovers

53

49

Bermuda Grass

0

40

Figure 4.0 – Sum of all data divided by 10 (to be equal to “one quadrat”)

All Locations Combined

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

Rye Grass

3.80

7.20

Dandelions

3.80

2.10

Legumes

18.7

4.40

Rumex

2.70

0.000

Chinese Fire Weed

0.30

0.000

Mint

3.30

7.70

Clovers

5.30

4.90

Bermuda Grass

0.000

4.00

Figure 4.1 – Plugging in numbers for the Simpson’s Diversity Index

All Locations Combined

Region A (Quadrats next to the pond)

Region B (Quadrats 10 feet away)

N

37.9

30.3

N(N-1)

1398.51

887.79

?n(n-1)

389.73

144.61

D

Figure 4.2A – Region A’s Simpson’s Diversity Index Formula; plugging in numbers

Figure 4.2B – Region B’s Simpson’s Diversity Index Formula; plugging in numbers

Aspect 3

Presenting Processed Data

Figure 4.3 – Graph depicting values of biodiversity in Region A and Region B

Part 3: Discussion, Evaluation, and Conclusion

Aspect 1

Discussion & Reviewing

We discover that Region B, which has an index value of 6.14, is has higher levels of plant biodiversity compared to Region A, which has an index value of 3.59. The range between the two regions is 2.55. Yet, what’s really important to focus on is – what really is diversity? Diversity is measured by the abundance of different species combined with the numbers of individuals within such species, which in turn are plugged in to the formula in order to derive what the value of biodiversity is.

If we take a closer look at the processed data table of Figure 4.0, we discover that Region A consisted of 7 species, while Region B consisted of only 6 species. Yet, why does Region B’s diversity prevail over Region A? Notice that for Region B, the distribution of individuals within species are within range of each other; the minimum being 2.1 individuals within a specie while the maximum being 7.7 individuals within a specie; without any outliers. On the other hand, notice that Region A’s diversity ranges from 0.3 individuals per specie all the way to 18.7 individuals per specie. While those are certainly outliers, many of the species in between are rather distributed widely, hence making the diversity of Region A lower; since the diversity index favours abundance balanced with a moderate distribution of individuals within species. Hence, we can see why Region B’s plant diversity is higher than Region A.

Aspect 2

Evaluating Procedures and suggesting Improvements

Although this investigation was a solid attempt at determining biodiversity between two distinct regions, it was not without its issues. In an actual experiment, ten samples were grossly insufficient to truly represent the actual diversity of an ecosystem. It is almost certain that some plant species were underrepresented, or even omitted from the sampling. Another problem is that the two different regions are on different gradients, since the land 10 feet away from the water is generally upstream; hence the different occurrence of plants. A possible limitation, that luckily did not occur in this experiment, was estimation of plant abundance, if the given amount of plants were simply too high to count manually. That would greatly limit the accuracy of the findings. Another possible issue was human error; that is, there may have been two distinct plant species or subspecies that was simply counted as the same species. Another weakness was that different samples were taken on different days, possibly skewing the data since data collection would not be uniform.

The investigation could be greatly enhanced by simply having a greater amount of sampling in order to reduce the rate of error. Another improvement could be also increase the size of the quadrat in order to get greater surface area to evaluate. Finally, taking all data collection on the same day will in turn make the data uniform. Another concept of improvement is to increase regions of collections; perhaps having a 20 feet from the water away region for example will improve the data and allow us to view trends from 0 feet, 10 feet, and finally 20 feet away.

Aspect 3

Conclusion

In conclusion, the hypothesis that land nearer the water has greater biodiversity was not supported by the data collected. In reality, land further away had greater biodiversity.

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