In the Excel worksheet, one of the columns will represent the ID of the species while the attribute values of the quadrats were represented by the other three columns. Consequently, the preparation of the data is to import ArcMap so as to combine with the quadrats. After the creation of the quadrat before, the attribute table is opened in the next step for the quadrat layer and FT_ID that is a new field is added to assign each quadrat with an ID. The quadrat layer is right clicked from the table of contents to select the ‘join’ option from the pop-down menu.
The parameters of the join data window are assigned and due to the joining process being temporary, the quadrat will be exported as a new shape file denoted as Qudrant_N. After joining, the final Quadrat_N attribute table is shown below. In finding out the minimum sample size founded on the relationship between the number of species and the areas, drawing the species area curve is vital. Nonetheless, a small quadrat should be drawn first such as 0.5 meters cubic and the number of species in the quadrat counted.
Gradually, the size of the quadrat is increased, and the number of each species for each quadrat is recorded. This process is continued until there is the stability of the species. By plotting a graph of the area size against the species number, the area of the sample can be determined. Due to the fact that a graph had not been drawn in the field, the sample that was used was 100 meters squared. The extent of how that results will be affected would be determined during the performance of quadrant analysis. The variance mean ratio (VMR) can be calculated by use of statistical summaries to extract the number of cells that have the same values.
The simplest method is to obtain quadrat counts and use them. This step is vital and would be used in the entire quadrat table. The species 1 will be first selected from the header, and then the information will be summarized and saved as a text table with a specific name as VMR1, the same process is done with species 2 and species 3 with the outputs of VMR2 and the VMR3 respectively. The VMR can describe the randomness of the distribution and the distribution of species on the campus.
Moreover, the VMR can be used to test the pattern of the species against 1 which can be determined by dividing the variance by the mean. If the VMR is less than 1, that indicates regularity, when the VMR is greater than 1, it indicates clustering. A chi-square
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