Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Multivariate Analysis of Woody Species in the Duke Forest Mid-Piedmont Region: Durham, North Carolina Brian Wang December 5, 2005 Biology 112-001 Introduction The vegetative structure of a community is determined by the combination of three interacting factors: species composition, environmental influences, and historical past. Through the analysis of these three components, the varying patterns and processes that affect the composition of a plant community can be looked at in more detail. Different environmental variables can be examined separately and in groups, in order to determine if they drive noticeable patterns in the plant community (Jacobs, 2004). Also, it is important to achieve a more thorough knowledge of plant communities because it allows ecologists to predict their future patterns of growth and changing diversity. The goal of this study was to analyze and classify the vegetative, woody species community of the Duke Forest. The vegetation community of this particular area was examined through indirect gradient analysis or ordination. In this approach to vegetation analysis, the different community types of the area were identified in terms of the vegetation, and the underlying influences of the environmental factors were applied the various sectors of the community. In the first part of the study, an ordination was applied to both the species data and environmental data of Duke Forest. This allowed particular objects of interest such as species, samples, plots, and soil characteristics to be grouped together according to their similarities. In the second phase of this investigation, the various groups of the vegetation data were identified and were grouped to the ordination analysis. The final part of the study defined and classified the groups of the study using the method of indicator species analysis. Methods The initial part of the vegetative analysis of the Duke Forest dealt with the simple grouping of the species, samples, plots, quadrants, and soil data from the area. First, a step-down ordination was applied to the data to identify the best number of axes to use for the focal run. In this step, a NMS ordination was run on the species data, and the stress and instability were calculated. The measure of distance for the ordination was Sorensen (Bray-Curtis). The dimension for which the stress levels off was found to be three. This numerical dimension was then used for the focal NMS ordination of the data. Next, the woody species data was opened for both the main and second matrix of the ordination. This ordination was then graphed, with the species data overlaid as a biplot. Then another ordination was conducted, with the species data as the main matrix and the environmental factors of the Duke Forest as the second matrix. This ordination was also graphed, with the environmental variable overlaid as the biplot. The second component of the analysis identified the different groups of the previous ordination data based on species composition. First, a cluster analysis was used to group the main and second matrix of species data. This was followed by another cluster analysis of the main matrix species data and second matrix of environmental variables. With the application of the cluster analysis, grouping levels were added to both data files in order for them to be used as second matrixes to display ordination with the groups in the biplot. The cluster dendrogram was formed from this data analysis to identify the groups and their corresponding plots. Next, the groups were qualitatively examined in biplots using the focal ordination results from the first phase of the study. The species data was used as the main matrix, with the species and groups data from the first phase being used as the second matrix. With this data being collectively graphed, the ordination results form the first phase are displayed along with the color coding of the various plots, allowing the various species of each group to be identified. In the final section of the data analysis, the groups of the study were defined and classified using the indicator species analysis. To determine the correct number of groupings to use, the indicator species analysis was applied to the four different species and group data sets. Then the p-value data for each group was imported into an excel data file, in which the p-values were organized in ascending value, their average p-values were calculated, and the number of indicators (below 0.05) for each group were recorded. The 3rd grouping level found to be the best level of grouping because it was identified to have the lowest average p-value and the highest number of indicators. Finally, using this specific level of grouping, the abundance, frequency, and indicator values was found for each group. Results/Data The first part of the vegetative analysis produced graphs of the species and the environmental variables. In figures 1 and 2, the 2:1 axis format shows that the location and distribution of Liquidambar styraciflua, Carpinus carolininiana, and Ulmus alata are heavily influenced by the concentrations of soil Mg-A and Ca-A, with these species being distributed in a close proximity to these soil nutrients. Also, these three species seem to be slightly affected by the soil PH and Mn concentration, with them being closely located to these factors as well. From these same graphs it can also be interpreted that the location and distribution of the Acer rubrum and Quercus pinus is influenced by the soil concentration of aluminum, while the species Oxydendrum arboretum is related to the elevation of the environment and white oak is affected by the location of water sources. The graphs of the species and environmental variables, figures 3 and 4, in the 3:1 axis format show that the location and distribution of Fagus grandifolia, Juniperus virginiana, Liriodendron tulipifera, and Quercus stellata are slightly influenced by the amount of Ca-A and Mn in the soil, as well as the soil PH, with their distribution being further away from these variables. However, the two tree species Acer rubrum and Quercus pinus seem to be more impacted by the soil concentration of Al, with a close proximity to this nutrient in the area. Figure 1 Figure 2 Figure 3 Figure 4 In second analysis section, the different various groups of the vegetation data were identified and were grouped to the ordination analysis. The dendrogram, in figure 5, illustrates the groups by color coding and ordering the plot numbers by group. Figure 5 ENVLONG:wk2 Distance (Objective Function) 1.6E-02 5.1E+00 100 75 1E+01 1.5E+01 2E+01 25 0 Information Remaining (%) 00001 PSP37 00018 00021 00574 00004 00008 00014 00002 00005 00007 00509 00520 00016 00024 00023 00033 00010 00031 00020 00042 00019 00069 00517 PSP36 00555 00581 00598 00589 00571 00579 00009 00012 00011 00015 00017 00022 00067 00618 00513 00514 00620 00537 00619 00501 00504 00524 00502 PSP88 PSP86 00508 PSP87 00617 PSP35 PSP34 00081 00606 00590 00510 00596 00512 00511 00607 00621 00608 00609 00003 00612 00616 00611 00614 00615 00622 00624 00575 00593 00582 00013 00029 PSP44 PSP61 00503 00507 00025 00026 00583 00584 00585 00032 00505 00506 00625 PSP10 00027 00587 00518 00588 00602 00515 PSP43 00028 00516 00030 00610 00613 00623 50 Group6 1 3 12 36 37 87 When the ordination results from the first section were combined with the color coding of this section, ordination graphs were created that showed the different color coded groups along with their corresponding environmental variables. In figures 6, 7, and 8, the graphs of these groups are displayed in the various axis combinations. Figure 6 TLwk1 Group6 1 3 12 36 37 87 LIST Axis 2 CACR ULAL ACRU QUPR OXAR QUAL Axis 1 Figure 7 TLwk1 Group6 1 3 12 36 37 87 QUST Axis 3 JUVI QUPR ACRU LITU FAGR Axis 1 Figure 8 TLwk1 Group6 1 3 12 36 37 87 QUST Axis 3 JUVI QUAL ULAL LIST OXAR CACR LITU FAGR Axis 2 The red group (group 1) is comprised of woody trees species whose distribution and location seem to be greatly influenced by the environmental variable of H2O and slightly influenced by the habitat elevation, with these trees distributions increasing in their vicinity. This particular group seems to be composed of the species Quercus alba, Oxydendrum arboretum, Quercus stellata, and Juniperus virginiana. The green group (group 3) is made up of species that seem to be affected by the concentrations of magnesium and calcium in the soil. From the different ordination graphs it looks as if this group is dominated by the species Liquidambar styraciflua. The species of the turquoise group (group 12) is influenced by the pH of the soil and also by the soil concentration of Mn. The species of this group are Carpinus caroliniana and Ulmus alata. The pink group (group 36) is composed of species whose distribution is shaped by the soil concentration of Aluminum. The species of this group seem to be Acer rubrum and Quercus pinus. The blue group (group 37) is made up of species that are affected by the soil PH and soil concentration of calcium. The final group, group 87 (yellow) is comprised of species that seem to not be directly affected by any of the corresponding environmental variables in this vegetation analysis. However, this group might be influenced by a particular combination of variables. In the third part of the vegetative analysis an excel worksheet, figure 9, was created using the indicator species analysis to determine the abundance, frequency, and indicator values for each woody tree species in the Duke Forest. Figure 9 Species ACNE ACRU ACSA AMAR BENI CACR CACA CACO CAGL CAOL CAOV CAPA CATO CECA CEOC COFL CRMA CRUN CRAT DIVI FAGR FRAX ILAM ILDE ILOP JUNI JUVI LIST LITU MATR MORU NYSY OSVI OXAR PITA PIEC PIVI PLOC PRAM PRSE QUAL QUCO QUFA QUMA QUMI QUNI QUPH QUPR QURU Abundance 0 45 0 15 0 0 0 0 24 14 0 100 27 0 0 10 0 88 0 58 0 0 88 0 35 0 3 2 14 0 15 21 3 47 25 66 33 0 0 18 23 86 19 94 0 0 0 99 9 Frequency 3 96 16 6 4 31 1 6 62 35 48 7 66 23 8 89 4 4 3 27 34 53 6 11 16 6 53 53 59 3 41 88 26 71 27 27 26 3 1 44 78 25 21 11 5 2 9 37 55 IV 3 32 8 2 4 21 1 6 22 15 22 6 23 12 5 30 3 3 3 11 19 25 3 7 8 6 28 25 22 3 18 29 12 26 12 10 9 3 1 16 30 14 8 6 4 1 6 33 21 p-value 0.158 0.095 0.073 0.626 0.058 0.001 0.733 0.019 0.235 0.02 0.193 0.009 0.155 0.202 0.142 0.106 0.173 0.063 0.12 0.049 0.001 0.202 0.198 0.052 0.106 0.026 0.001 0.001 0.003 0.168 0.013 0.719 0.195 0.017 0.046 0.324 0.344 0.066 0.598 0.531 0.001 0.002 0.36 0.04 0.098 0.545 0.093 0.001 0.169 QUSH QUST QUVE SAAL ULAL ULAM ULRU 0 7 31 56 0 0 0 3 33 60 15 26 7 14 3 20 22 5 14 7 12 0.183 0.001 0.047 0.576 0.019 0.023 0.004 This excel worksheet shows the rank of each tree species within each group. According to the importance values, Quercus alba is a strong indicator of the red group, Liquidambar styraciflua of the green group, Carpinus caroliniana of the turquoise group, Quercus pinus of the pink group, and Quercus stellata of the yellow group. Discussion Through the various methods of vegetative analysis conducted in this study, it has been found that there are strong correlations between the environmental variables of the Duke Forest and the woody tree species found within it. Strong indicator species of calcium, magnesium, and water can be found in axes 2 and 1, and indicators of aluminum in axes 3 and 1. The axes 3 and 2 also contained indicators of water, elevation, magnesium, and calcium. However, no strong indicator species were found to have a direct correlation with pH and manganese, which may have resulted from the insufficient abundance of these corresponding indicator species in the area of study. Further studies researching the historical history of the land can be conducted on the distribution of woody tree species in the Duke Forest. Correlations may be discovered between the previous land uses of plots in the past and their current composition of vegetation. Literary Works Cited Jacobs, L. 2004. Multivariate Analysis of High Elevation Red Oak Communities: A Reassessment of Current Community Classifications.