Horace Greeley High School Biodiversity Assessment

Transcription

1 Horace Greeley High School Biodiversity Assessment Hannah Byrne, Adin Witt and Sam Platt May/June

2 Table of Contents: Introduction...Page 3 Comparative Studies....Page 4 Methodology.Pages 4-6 Mapping..Pages 6-7 Results..Page 7-8 Conclusion...Pages 8-9 Appendix Part A (Images).....Pages Appendix Part B (Field Notes)...Pages

3 Introduction: Despite all the negative impacts on the environment, mostly caused by the human race, there also are some positive impacts. Although humans are known for hurting the environment through deforestation and harmful practices, humans are also capable of fixing the damage they created. They are able to plant trees, recreate animal s habitats, and change their daily lives to practice healthy treatment of the environment. Upon human arrival on this planet and after research done by scientists for decades, humans found ways to measure how much they harm the environment. The practice of measuring biodiversity was useful in teaching humans to be more able to protect the environment and potentially heal the harm that was caused. Knowing the health and prosperity potential of forests, even the small ones, allows humans to have a very small grasp on helping and saving the environment through planting native gardens and protecting our native species. A key way to find the health and prosperity of a certain forest area is to calculate its biodiversity. Biodiversity is the number of species in a certain location. The biodiversity can be calculated in terms of plant and tree species or animal species. An environment with many different species is a sign of a very biodiverse and healthy environment. An environment with not a lot of diverse species and certain species dominating others is a sign of a non biodiverse and an unhealthy environment. There are many steps in calculating biodiversity. A brief description of one way to do this is as follows: Develop a methodology, map the area, generate sample points, measure the distance between the sample points and the trees, measure the circumference and identify each tree. After these measurements are taken, the data should be analyzed to find average frequency, distance and DBH for each species and in total. Comparative studies of similar forest biodiversity: 3

4 The Black Mountain State Forest biodiversity assessment appears to have been done both in a similar atmosphere to the forest at HGHS, and had very reliable and organized information. The study was conducted by Peter J. Bowman in April 2005 in New Hampshire. An overview of the entire process of assessing the biodiversity was given From the methodology to the results. The methodology of this study was split into three sections: Landscape analysis, field survey and data analysis and management. The landscape analysis showed which areas of the forest had something that spiked curiosity or seemed like an outlier, and therefore helped determine which areas of the forest needed to be assessed. The field survey was an organized map of data that was collected in the forest. The data analysis and management was a sum up of the data collected along with an analysis of the data found and any patterns and/or outliers. This study helped determine the methodology, and showed the negative and positive factors of dividing up out methods in a way such as the one used in this study. The research done, following the assessment of this study, guided a decision on a methodology more similar to initial ideas instead of what was found in other studies. The differentiation from study to study showed that a simple, yet clear methodology would be the best way to approach a biodiversity assessment. Methodology: Here is the methodology: 1. Find out where the section is 2. Identify the trees within this section 3. Use meter sticks to create coordinates and use a random number generator to choose the coordinates and begin there 4. Face north and decide which quadrant is which 5. Then for each quadrant, find the closest tree 6. Measure the distance to the tree 7. Go to that tree and measure the diameter at breast height, DBH 8. Repeat this for each quadrant 9. Create a table with the measurements for each quadrant with the distance and DBH 10. Go over all our data and record the averages and totals 4

5 Another study was the North Castle Biodiversity Plan. This was not a biodiversity assessment, but rather a plan for an upcoming assessment. The methodology in this plan revolved more around assessing the species count and biodiversity in terms of animals, but the method of fieldwork and data collection are the same as the Black Mountain State Forest biodiversity assessment in that they both have a focal point of outliers and extinctions and/or species relocation due to habitat loss or other natural / human environmental impacts. When developing this methodology, much time was spent taking other biodiversity assessment methodologies into consideration, such as the Black Mountain State Forest biodiversity assessment and the North Castle biodiversity plan. These plans showed other biodiversity assessments of large areas, and showed how to split up the steps in an organized way so that the frequency, distance and DBH calculations would be accurate. For starters, a grid was created on the area of the forest, and then a random number generator was used to find 15 points with an x and y coordinate. These points were plotted in the application ArcGIS, and once in the forest with our meter sticks, tree identification book, field notebook and measuring tape, the navigation feature gave guidance to the plotted points. One by one, a quadratic plane facing North was set up on each point, and then the distance to the nearest tree was measured along with its circumference, and it was identified. Using these numbers, forms were created in Google sheets. From this, frequencies of tree species and average distances were calculated, and circumferences were converted to diameters / DBH, and averages for DBH and distance were found. The distances and DBH were found to be able to calculate how much room a certain species takes up and how dispersed each species of tree is. Lastly, percentages for frequency, DBH and distances were found. These percentages represented the individual tree species average in comparison to the total average (i.e. Yellow Birch has a frequency of 7, and the total frequency is 53, so one would divide 7 by 53 to get a frequency percentage of 13%, while the frequency for perfect biodiversity would be 9.09%). Overall, when 5

6 summing up the data, the developed methodology was a very helpful and strategic way to go about assessing the HGHS Forest Biodiversity. Map: To be able to map a forest, one needs to choose the area in which they are assessing biodiversity. Programs such as Google Earth and ArcGIS can be used to draw the section of the study area. When mapping the area to assess, one needs to create a grid with even space in between the lines, so that there is a place to plot the points. Next, one uses this grid to plot the sample points. Over the entire area in which you are assessing the biodiversity, you must create a grid, possibly by intervals of ten. The coordinates of the sample points were chosen using a random number generator, and then plotted on the X and Y axis of the grid. The size of the area determines the number of sample points Bigger areas require more sample points to make the final number more accurate. After going over the size of the area, that 15 sample points gave the most accurate biodiversity. Once all of the sample points were drawn on the map, the points were placed where they were located on the printed map. By putting these points into the program, the navigation feature gave guidance to the points. The app registered the current location, and when walking, it gave guidance to the point. Once guided to the point, two meter sticks were put on the ground to lay out the quadratic plane facing north. From that point on, the methodology was followed. Here is the map. The green pin points are the sample points. 6

7 Results: Conclusions: From the sample points, 11 different species of trees were identified. In the forest studied, 9.09% frequency for tree species would be perfect biodiversity. High distance numbers indicate that the trees 7

8 were farther away from the sample points, which indicates lower density of that tree species in the ecosystem. High DBH numbers mean that the tree species is large and takes up a lot of space in the forest. Swamp White Oak had good frequency of 5.66%. It s distance was 47.39% which is one of the lower numbers from all of the species. This indicates a fairly high density of Swamp White Oak in this ecosystem, but the trees were not very large with a DBH of 48.49%. Red Maple had the same frequency as Swamp White Oak. Red Maple s were very far apart with a distance of %, but the trees were fairly large with a DBH of 75.02%. Black Oak trees had the highest frequency at 18.88%, and had about average distance at 97.75%, but had the smallest DBH at 11.63%. In all of the samples there was only one Sugar Maple tree but it had the highest DBH at %. American Elm was much lower than the perfect biodiversity number with a frequency of 3.77%. It had fairly high distance at %, but also a high DBH at %. Norway spruce is an invasive species to this ecosystem, but had an almost perfect frequency at 9.43%. The trees were pretty close to the sample points with a distance at 54.73% and the trees had about average DBH at 80.51%. Shagbark Hickory had the same frequency and a distance at 70.82%, but had a low DBH at 21.96%. There were a lot of Tupelo trees with a frequency at 13.21%. Tupelo had almost perfect distance and DBH at 91.06% and 99.72%. Chestnut Oak had a frequency at 7.55% and a distance at 83.43%, but a fairly low DBH at 43.73%. Yellow Birch had a fairly high frequency of 13.21%, but an about average distance and DBH at 58.71% and 52.79%. American Beech had the second highest frequency at 16.98%. The distance and DBH were slightly above average at 60.99% and 59.1%. The Simpson s Biodiversity Index for this ecosystem is.89. Simpson s Biodiversity Index is on a scale from indicates very poor biodiversity and 1 indicates extremely good biodiversity. Highly impacted areas with a lot of pollution generally have and biodiversity index closer to 0. An ecosystem like the Amazon Rainforest has a biodiversity index of about 1. The Simpson s Biodiversity Index of other 8

9 groups in our class were.905,.88, and.76. All of these numbers mean that the ecosystem that was studies has pretty good biodiversity. Most of these numbers are fairly similar because there was a lot of overlap in the areas that each group sampled. The points were not more similar because each sample area has different species and characteristics. All of the sample points had some degree of variation. The numbers would have been more accurate and similar if we used more sample points. Appendix: Part A Images: 9

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11 Part B Field Notes: Sample 1: Sample is located in a fairly open space Trees are not very large 1 Chestnut Oak 76 in 10 2 Yellow Birch Swamp White Oak Red Maple Sample 2: Trees are far apart A few dead trees in the area Trees are pretty big High DBH 1 Black Oak Dead Sugar Maple American Elm Sample 3: Trees are fairly close together Many spruce trees in the area Fairly low DBH 1 Norway Spruce Black Oak

12 3 American Beech Norway Spruce Sample 4: High density of trees A lot of diversity in tree species Large black oak tree 1 Black Oak American Beech Black Oak Shagbark Hickory Sample 5: One dead, two black oak and a norway spruce Many norway spruce s around this one Trees were relatively far from the point 1 Black Oak Black Oak Norway Spruce Dead Sample 6: All tupelo 2 of them were similar distanced from each other, the other 2 were further Very different circumferences 1 Tupelo

13 2 Tupelo Tupelo Tupelo Sample 7: 2 american beech One of them was very close, the rest of the trees were much further 1 American Beech Tupelo Black Oak American Beech Sample 8: Two yellow birches All were relatively close except the red maple Trees were all pretty skinny and tall 1 Yellow Birch Black Oak Yellow Birch Red Maple Sample 9: One was dead All were pretty far from the quadratic plane American Elm had the biggest circumference 13

14 1 Norway Spruce Dead American Elm Swamp White Oak Sample 10: All different trees All were very far from the plane and each other 1 American Beech Red Maple Black Oak Shagbark Hickory Sample 11: One dead, the rest different species Yellow birch was 14 feet away but the rest were around 5 feet away Circumferences were almost the same for all 1 Dead Yellow Birch Tupelo Black Oak Sample 12: 2 american beech 2 american white birch All around 10 feet from the plane and not far from each other All not very thick trunks 14

15 1 American Beech American Beech Yellow Birch Yellow Birch Sample 13: Two dead American beech was very close Circumferences were exactly the same for both live trees 1 Swamp White Oak Dead Dead American Beech Sample 14: 3 chestnut oak trees All chestnut oaks were very close except one Circumferences were very similar for all chestnut oaks except the circumferences for the yellow birch which was much smaller 1 Chestnut Oak Chestnut Oak Chestnut Oak Yellow Birch

16 1 Norway Spruce Tupelo Chestnut Oak Red Maple Sample 15: All different species All very different distances and circumferences 16