Investigation Plan
Introduction
I will be conducting an experiment which involves burning a forest to test the progression of the forest fire in relation to the high density of trees in the forest. The general hypothesis in this case would suggest the higher the density of trees, the further the fire would progress. I will be conducting various tests to test this hypothesis. The variable that I will be changing is the population of trees within the forest. To carry out this experiment I will be using a simulation which is created by the use of a Net Logo environment.
Method
To carry out this experiment I will use various tree densities to test how much of the forest will burn. I will be using the ticks to see how long it would take for
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The results are showing that as the density is decreasing so is the percentage being burnt. This time the ticks increased showing the time taken to burn has increased. However, in this table I have got an outlier. This outlier could have been caused by human fault. The outlier shows that this piece of result wasn’t accurate as it is totally different from the rest of the repeats.
Density Repeat % Burnt Ticks
50%
1 2.0% 295 2 1.8% 260 3 3.4% 190 4 2.5% 199 5 2.6% 175 Average 1.5% 223.8
The table above shows that an average of 1.5% of the trees got burnt when the tree density was 50%. These results show a significant drop in the percentage of the trees burnt. In addition, the ticks have also decreased.
Density Repeat % Burnt Ticks
25%
1 0.5% 35 2 0.6% 46 3 0.7% 39 4 0.5% 39 5 0.7% 43 Average 0.6% 40.4
The table above shows that the average percentage of the tree’s being burnt is 0.6% when the tree density was only 25%. The ticks show an average of 40.4. If you compare this table to the table with a density of 99% you can see there has been a significant drop in the percentage burnt as well as the ticks.
The density of trees from 60% to 50% shows a significant change in the percentage burnt as well as ticks. The average percentage burnt for the density 60% was 66.9% whereas for the density 50% the percentage burnt was an average of 1.5%. This
On September 17th, 2015 our group went on the Orange Trail of the State Botanical Garden of Georgia in Athens, Georgia to collect data for our lab. The biome of this area that we explored fit a temperate deciduous forest type. We walked along the trail and picked random spots to start measuring our transects. We measured DBH size and canopy coverage at 10, 20, 30, and 40 meters respectively along each transect for a total of six transects. We used a densitometer to measure the percent of canopy coverage of the tree closest to the center of the sampling points along each of the transects. We used a measuring tape to measure out 10, 20, 30, and 40 meters respectively along each of the six
Based on the current conditions of the area, we hypothesis that tree survivability will be highest in elevations above 3,000 feet and below 3,300 feet, highest in slopes between 0 - 45 degrees, and highest in aspects between 0 - 33 degrees. Tree survivability will also be highest in area with the best soil, water quality, and forest health conditions for successful tree sapling growth.
As minutes pass by, a beaver comes upon the Red Maple. Luckily for the Red Maple, its chemicals act as a repellant. As the beaver walks away, the Red Maple continues on its work. As if the wind was a messenger, the tree knew that it had only a short amount of time left before it would rain. The leaves of the Maple begins to droop as the clouds begin to cover the sky. But also covering the sky was truck exhaust. To the left and right of the Red Maple, trees were being cut down. Deforestation has come with urbanization, a rate of 1.02%. Deforestation has caused habitat destruction, forcing many animals to be moved. The biodiversity of the dead forest is not
Species richness is the number of tree species. The species richness was 7 for the burned side of Coal Road compared to 11 for the unburned side. Species evenness is calculated using Shannon’s diversity index by dividing Shannon's diversity index ‘H’ by the natural logarithm of species richness. On the burned side of Coal Road, the species evenness was 0.0205 while on the unburned side of Coal Road the species evenness was 0.0411. The combination of greater species richness and evenness confirms the unburned side of Coal Road is more diverse than the burned side of Coal Road. Thus, our hypothesis is incorrect that the burned region would produce more species diversity while the unburned region would exhibit less species
In addition, the results of this study may be used by the U.S. Forest Service to promote and thus improve forest fire prevention projects. The U.S. Forest Service manages large quantities of land, however they may not all be adequately maintained to prevent the severity of wildfires. Seeing the impacts that the Rough Fire caused can be motivation for improving the thinning of the forest to prevent intense fire from occurring hence save money in combatting wildfires in the long run.
The significance of our study was to determine whether or not solar radiation is a key to the size of leaves. With the results of the experiment our group was able to conclude that our alternative hypothesis was correct, implying that the shade leaves of the burr oak (Q. macrocarpa) are generally larger that its sun leaves. One way the group could have improved our study was to use the actual leaves from the tree. Instead we used photocopied leaves, which limited our actual data to a scale of what the actual leaves would have weighed. Another possibility to improve our study would have been to increase our sample size. Instead of using four leaves of each type we could have increased our sample
Table 2 shows the health of each individual Bald Cypress accounted for in the experiment. The scale at which the saplings were judged by is listed below Graph 2 named “Bald Cypress Sapling Health Rating Scale”. Graph 2 corresponds with Table 2 as well.
The lands that burned during this fire were mainly comprised of a mixed-conifer forest. The main tree species found before and after the fire are Douglas- fir, grand fir, Pinus ponderosa (ponderosa pine; PIPO), and Pinus contorta (lodgepole pine; PICO). Other species found include other varieties of spruce, pine, and larch. In some areas of the site a rich understory has formed or still exists; these were dominated by Salix scouleriana (Scouler’s willow; SASC) with a limited variety of forbs present beneath the shrubs. Post-fire management tactics included salvage logging and grass seeding. This seeding of native grasses was spread across burned areas in combination with mulch in the form of agriculture straw as well as shredded wood strips (Robichaud, 2009).
The null hypothesis for this study assumes that the dispersion of oaks is random. The comparison of observed and expected oak trees through a Poisson analysis will determine the actual dispersion of oaks. Therefore, the statistical hypothesis is, if the observed oak tree dispersion is equal to the expected distribution of oaks it will be determined through the Poisson function.
The first question to be addressed in this study is, will there be varying tree seedling species diversity in relation to varying levels of burn severity? My hypothesis for this question is that we will see the highest tree species diversity where we see a moderate level of burn severity. The second question of the study asks, did the presence of salvage logging lead to a difference in the tree seedling densities as compared to unlogged sites? My hypothesis for this question is that there will be a greater density of tree species in the salvage logged site than the unlogged site.
Fire has long been used as a management tool all over the world. In our study we designed 2 experiments to investigate the affect fire has on both organic soil layers and Pinus palustris (Longleaf pine) saplings. For this study, a sapling is a youth Longleaf pine less than 2m in height in addiction to one you can wrap your fingers around. The organic soil layer is made of undecomposed plant matter (litter). Samples were taken from 2 different forests located behind the UNCW campus. A prescribed burn was conducted in Forest B in 2011 and Forest C has not been burned since the 1980’s. In the analysis of our collected data, we expected more Pinus palustris saplings in the recently burned forest and a deeper organic layer in the unburned forest. Quadrats and soil sample cores were used to compile the data. As predicted, there were more Pinus palustris saplings in the recently burned forest. However, organic soil layers greatly varied throughout both forests, and overall there was not a significant difference between the two. Many components could have factored in the mixed depths including temperature, weather, moisture, and slope. However, in many studies on this matter, it is concluded that generally speaking, prescribed burns do not have a significant affect on the organic soil layer unless it was burned within the year.
This creates a risk to neighboring forests and civilizations near by these pines because of the quickes rates these fires spread and increase putting all areas surrounding them in
A controlled or endorsed consume, otherwise called danger diminishment burning,blowback, swailing, or a consume off,is a procedure at times utilized as a part of backwoods administration, cultivating, prairie rebuilding or ozone depleting substance decrease. Fire is a characteristic piece of both woodland and field biology and controlled fire can be an instrument for foresters. Danger diminishment or controlled consuming is directed amid the cooler months to lessen fuel development and decline the probability of genuine more smoking fires.Controlled consuming fortifies the germination of some attractive backwoods trees, and uncovers soil mineral layers which builds seedling essentialness, in this manner reestablishing the woodland. A
My purpose is to see whether there is any relationship between the height of saplings in the Waitutu Forest and the diameter at
Modern methods of forest management should be practised. A forest is a very vulnerable asset. The slight neglect or unscientific working can rapidly deplete and may even annihilate it after which reforesting of the area may not be economically feasible.