Friday, April 3, 2020

Ecology Essays - Physical Quantities, Physics, Measurement

Ecology 1. The main purpose of this exercise is to see if College Woods Natural Area is experiencing succession, and to observe and document the tree community structure. Other purposes of this exercise are to examine College Woods and measure the densities of different species of trees as well as diameters of stems, and use these measurements to determine if the varying measurements lead to varying information about this tree community. Another purpose is to determine all species present, as well as the abundance of each species. We will also analyze the size structures of the trees to predict future change in College Woods Natural Area. 2.a. The extent of the estimation of absolute density from absolute dominance is variable when looking at figures two and three. Figure two would not be a good example of a good estimator of absolute density estimated from absolute dominance. The R-squared value, which tells how close the measurements are to the resulting fit line, is equal to 0.027 (where as an R-squared value of 1.0 equals a perfect fit). This shows that there is a very small relationship between absolute density of the Hemlock and absolute dominance of the Hemlock. Figure three would be a good example of an estimator of absolute density from absolute dominance. The R-squared value is equal to 0.609, which is significantly higher then that in figure 2 (0.027). The higher the R-squared value, the stringer the relationship, in this case, of absolute density of Black Birch and the absolute dominance of Black Birch. The fact that in one case the ability to estimate absolute density from absolute dominance is great (Birch), and in the other is low (Hemlock), suggests that this is not a reliable method of estimating. There must be alternate factors to take into consideration to estimate absolute density. As seen in figures one and four, the estimation of absolute density from relative density, has more merit then that of absolute density from absolute dominance. Figure one has an R-squared value of 0.229, which suggest a relationship between absolute density of Hemlock to relative density of Hemlock, but hardly a significant one. Figure four is a better example of a relationship between absolute density and relative density. Here the R-squared value is 0.697. This suggests that the estimation of absolute density from relative density has more of a relationship to each other and therefore is a better estimator of absolute density from relative density, then that of absolute density from absolute dominance, but still not a solid, reliable method of estimating. Both cases seem to differ from each other enough to make it an unusable method of estimating. 2.b. The relationships between absolute density and relative density and between absolute dominance and absolute density are weak due to the different arrays of measurements with the different species. The wider the range of measurements the more room there is for variation, which in turn, makes it harder to find relationships Figures one and two deal with the species, Hemlock. Hemlock had the largest ranges in all cases, absolute density (5-23), relative density (60-83.3) and absolute dominance (0.044-1.059). These figures had the lowest R-squares (1: 0.229, 2: 0.027) due to this high amount of varying measurements. The Hemlock was the most prevalent species, therefore having the widest range of measurements due to the simple abundance of trees, as well as the different DBHs (diameter breast height). This information suggests that the higher abundance and dominance result in a lower relationship between different factors. The relationships between absolute density and absolute dominance, and relative density and absolute density of the black birch also support this conclusion. The range of measurement dealing with the black birch is much smaller then that dealing with Hemlock, resulting in a closer relationship between factors. As seen in figure three and four, dealing with the black birch, the ranges are significantly smaller, absolute density (0-7), absolute dominance (0-0.212) and relative density (0-31.25), resulting in larger r-squared values of 0.609(figure three) and 0.697(figure four). When the ranges are small there is less space for the measurements to be spread out. The smaller range results in similar measurements and less room for variation, resulting in a tighter fit line and greater R-squared value. 2.c.i. The abundance measurement to use