The aquatic and semi-aquatic plant communities of Utah Lake, Utah County, Utah are discussed. This discussion includes the methods of describing and delimiting the major vascular plant communities, the descriptions of the present existent communities, and the determination of the vegetational changes, particularly since 1925. The vegetation around Utah Lake is divided into plant communities. Each community is discussed using: (a) quantitative data, (b) field observations, (c) general and specific locations of the community, and (d) interrelationships and trends of the community. Historical vegetational changes of Utah Lake plant communities are discussed. In this discussion, the plant communities described by Cottam in 1925 are examined in broad outline and then in detail. In 1968, twenty-nine plant communities had developed from fifty-six per cent of the associations and twenty-nine per cent of the societies that were described by Cottam in 1925.

Thesis (M.S.)--Indiana University, 2009. / Department of Geography, Indiana University-Purdue University Indianapolis (IUPUI). Advisor(s): Jeffrey S. Wilson, Lenore P. Tedesco, Daniel P. Johnson. Includes vitae. Includes bibliographical references (leaves 71-77).

M.Sc. (Botany) / In South Africa, controlling and eradicating Azolla filiculoides and Eichhornia crassipes cost annually approximately US$ 60 million to the national budget. However, the success of these operations is mixed because invasive aquatic plants often spread very rapidly either before they are spotted or before decisions are taken to implement control actions. This limitation is further exacerbated by difficulties in determining the invasion potential of newly introduced or unknown aquatic plants, as well as difficulties inherent to species identification. Resolving these drawbacks requires pre-emptive actions such as identifying areas that are most vulnerable to invasion by alien plants. In this study, I first explore whether molecular technique such as DNA barcoding can be useful to: i) overcome potential limitation of morphology-based identification of invasive aquatic plants; and ii) establish successful control of these invasives. For this purpose, I tested the utility of official DNA barcodes (rbcLa + matK or core barcodes), trnH-psbA, and the core barcode + trnH-psbA to identify invasive aquatic plants of South Africa’s freshwaters. Second, I use the technique of ecological niche modeling to identify most vulnerable freshwater systems to species invasion under current and climatic conditions. My analysis indicates that the core barcodes and matK regions perform poorer compared to trnH-psbA, which provides 100% successful identification alone or in combination with the core barcodes. This study therefore validates trnH-psbA as single best DNA barcode for invasive alien aquatic plants of freshwater systems in South Africa. Using this DNA region in BLAST analysis to screen plants species sold in aquarium market in Johannesburg, I found surprisingly that some prohibited species are already in circulation in the market. These include Hydrilla verticillata, egeria densa, Myriophyllum spicatum, and Echinodorus cordifolius. Furthermore, based on climatic parameters, I explored the distribution of the "bad five" aquatic species in South Africa, i.e. the most damaging invaders of freshwater systems. I found distinct distribution potentials for these species under current climatic conditions. Overall, 38% of all South Africa’s dams occur in areas climatically vulnerable to the invasion by the bad five with the Western Cape Province being the most vulnerable. However, under predicted climate change scenario, I found evidence for contrasting shifts in species range: species such as Azolla filiculoides, Eichhornia crassipes, Salvinia molesta might increase their range by at most 2% whilst the ranges of Myriophyllum aquaticum and Pistia stratiotes might contract by at most 5%. This range contraction and expansion will result in some dams currently vulnerable to invasion becoming resilient whilst others that are currently resilient might become vulnerable owing to climate change. This result demonstrates not only the utility of DNA barcoding in implementing control measures, but also provides ways of prioritising control/management efforts.

Resource managers need to be able to quickly and accurately map aquatic plants in freshwater lakes and ponds for regulatory purposes, to monitor the health of native species and to monitor the spread of invasive species. Site surveys and transects are expensive and time consuming, and low resolution imagery is not detailed enough to map multiple, small lakes spread out over large areas. This study evaluated methods for mapping aquatic plants using high resolution Quickbird satellite imagery obtained in 2007 and 2008. The study area included nine lakes in northern Indiana chosen because they are used for recreation, have residential development along their shorelines, support a diverse wildlife population, and are susceptible to invasive species. An unsupervised classification was used to develop two levels of classification. The Level I classification divided the vegetation into detailed classes of emergent and submerged vegetation based on plant structure. In the Level II classification, these classes were combined into more general categories. Overall accuracy of the Level I classification was 68% for the 2007 imagery and 58% for the 2008 imagery. The overall accuracy of the Level II classification was higher for both the 2007 and 2008 imagery at 75% and 74%, respectively. Classes containing bulrushes were the least accurately mapped in the Level I classification. In the Level II classification, the least accurately mapped class was submerged vegetation. Water and man-made surfaces were mapped with the highest degree of accuracy in both classification schemes. Overhanging trees and shore vegetation contributed to classification error. Overall, results of this research suggest that high resolution imagery provides useful information for natural resource managers. It is most applicable to mapping general aquatic vegetation categories, such as submerged and emergent vegetation, and providing general estimates of plant coverage in lakes. Better methods for mapping individual species, species assemblages, and submerged vegetation constitute areas for further research. / Indiana University-Purdue University Indianapolis (IUPUI)

Resource managers need to be able to quickly and accurately map aquatic plants in freshwater lakes and ponds for regulatory purposes, to monitor the health of native species and to monitor the spread of invasive species. Site surveys and transects are expensive and time consuming, and low resolution imagery is not detailed enough to map multiple, small lakes spread out over large areas. This study evaluated methods for mapping aquatic plants using high resolution Quickbird satellite imagery obtained in 2007 and 2008. The study area included nine lakes in northern Indiana chosen because they are used for recreation, have residential development along their shorelines, support a diverse wildlife population, and are susceptible to invasive species. An unsupervised classification was used to develop two levels of classification. The Level I classification divided the vegetation into detailed classes of emergent and submerged vegetation based on plant structure. In the Level II classification, these classes were combined into more general categories. Overall accuracy of the Level I classification was 68% for the 2007 imagery and 58% for the 2008 imagery. The overall accuracy of the Level II classification was higher for both the 2007 and 2008 imagery at 75% and 74%, respectively. Classes containing bulrushes were the least accurately mapped in the Level I classification. In the Level II classification, the least accurately mapped class was submerged vegetation. Water and man-made surfaces were mapped with the highest degree of accuracy in both classification schemes. Overhanging trees and shore vegetation contributed to classification error. Overall, results of this research suggest that high resolution imagery provides useful information for natural resource managers. It is most applicable to mapping general aquatic vegetation categories, such as submerged and emergent vegetation, and providing general estimates of plant coverage in lakes. Better methods for mapping individual species, species assemblages, and submerged vegetation constitute areas for further research. / Indiana University-Purdue University Indianapolis (IUPUI)

Resource managers need to be able to quickly and accurately map aquatic plants in freshwater lakes and ponds for regulatory purposes, to monitor the health of native species and to monitor the spread of invasive species. Site surveys and transects are expensive and time consuming, and low resolution imagery is not detailed enough to map multiple, small lakes spread out over large areas. This study evaluated methods for mapping aquatic plants using high resolution Quickbird satellite imagery obtained in 2007 and 2008. The study area included nine lakes in northern Indiana chosen because they are used for recreation, have residential development along their shorelines, support a diverse wildlife population, and are susceptible to invasive species. An unsupervised classification was used to develop two levels of classification. The Level I classification divided the vegetation into detailed classes of emergent and submerged vegetation based on plant structure. In the Level II classification, these classes were combined into more general categories. Overall accuracy of the Level I classification was 68% for the 2007 imagery and 58% for the 2008 imagery. The overall accuracy of the Level II classification was higher for both the 2007 and 2008 imagery at 75% and 74%, respectively. Classes containing bulrushes were the least accurately mapped in the Level I classification. In the Level II classification, the least accurately mapped class was submerged vegetation. Water and man-made surfaces were mapped with the highest degree of accuracy in both classification schemes. Overhanging trees and shore vegetation contributed to classification error. Overall, results of this research suggest that high resolution imagery provides useful information for natural resource managers. It is most applicable to mapping general aquatic vegetation categories, such as submerged and emergent vegetation, and providing general estimates of plant coverage in lakes. Better methods for mapping individual species, species assemblages, and submerged vegetation constitute areas for further research. / Indiana University-Purdue University Indianapolis (IUPUI)

Resource managers need to be able to quickly and accurately map aquatic plants in freshwater lakes and ponds for regulatory purposes, to monitor the health of native species and to monitor the spread of invasive species. Site surveys and transects are expensive and time consuming, and low resolution imagery is not detailed enough to map multiple, small lakes spread out over large areas. This study evaluated methods for mapping aquatic plants using high resolution Quickbird satellite imagery obtained in 2007 and 2008. The study area included nine lakes in northern Indiana chosen because they are used for recreation, have residential development along their shorelines, support a diverse wildlife population, and are susceptible to invasive species. An unsupervised classification was used to develop two levels of classification. The Level I classification divided the vegetation into detailed classes of emergent and submerged vegetation based on plant structure. In the Level II classification, these classes were combined into more general categories. Overall accuracy of the Level I classification was 68% for the 2007 imagery and 58% for the 2008 imagery. The overall accuracy of the Level II classification was higher for both the 2007 and 2008 imagery at 75% and 74%, respectively. Classes containing bulrushes were the least accurately mapped in the Level I classification. In the Level II classification, the least accurately mapped class was submerged vegetation. Water and man-made surfaces were mapped with the highest degree of accuracy in both classification schemes. Overhanging trees and shore vegetation contributed to classification error. Overall, results of this research suggest that high resolution imagery provides useful information for natural resource managers. It is most applicable to mapping general aquatic vegetation categories, such as submerged and emergent vegetation, and providing general estimates of plant coverage in lakes. Better methods for mapping individual species, species assemblages, and submerged vegetation constitute areas for further research. / Indiana University-Purdue University Indianapolis (IUPUI)

Resource managers need to be able to quickly and accurately map aquatic plants in freshwater lakes and ponds for regulatory purposes, to monitor the health of native species and to monitor the spread of invasive species. Site surveys and transects are expensive and time consuming, and low resolution imagery is not detailed enough to map multiple, small lakes spread out over large areas. This study evaluated methods for mapping aquatic plants using high resolution Quickbird satellite imagery obtained in 2007 and 2008. The study area included nine lakes in northern Indiana chosen because they are used for recreation, have residential development along their shorelines, support a diverse wildlife population, and are susceptible to invasive species. An unsupervised classification was used to develop two levels of classification. The Level I classification divided the vegetation into detailed classes of emergent and submerged vegetation based on plant structure. In the Level II classification, these classes were combined into more general categories. Overall accuracy of the Level I classification was 68% for the 2007 imagery and 58% for the 2008 imagery. The overall accuracy of the Level II classification was higher for both the 2007 and 2008 imagery at 75% and 74%, respectively. Classes containing bulrushes were the least accurately mapped in the Level I classification. In the Level II classification, the least accurately mapped class was submerged vegetation. Water and man-made surfaces were mapped with the highest degree of accuracy in both classification schemes. Overhanging trees and shore vegetation contributed to classification error. Overall, results of this research suggest that high resolution imagery provides useful information for natural resource managers. It is most applicable to mapping general aquatic vegetation categories, such as submerged and emergent vegetation, and providing general estimates of plant coverage in lakes. Better methods for mapping individual species, species assemblages, and submerged vegetation constitute areas for further research. / Indiana University-Purdue University Indianapolis (IUPUI)

Resource managers need to be able to quickly and accurately map aquatic plants in freshwater lakes and ponds for regulatory purposes, to monitor the health of native species and to monitor the spread of invasive species. Site surveys and transects are expensive and time consuming, and low resolution imagery is not detailed enough to map multiple, small lakes spread out over large areas. This study evaluated methods for mapping aquatic plants using high resolution Quickbird satellite imagery obtained in 2007 and 2008. The study area included nine lakes in northern Indiana chosen because they are used for recreation, have residential development along their shorelines, support a diverse wildlife population, and are susceptible to invasive species. An unsupervised classification was used to develop two levels of classification. The Level I classification divided the vegetation into detailed classes of emergent and submerged vegetation based on plant structure. In the Level II classification, these classes were combined into more general categories. Overall accuracy of the Level I classification was 68% for the 2007 imagery and 58% for the 2008 imagery. The overall accuracy of the Level II classification was higher for both the 2007 and 2008 imagery at 75% and 74%, respectively. Classes containing bulrushes were the least accurately mapped in the Level I classification. In the Level II classification, the least accurately mapped class was submerged vegetation. Water and man-made surfaces were mapped with the highest degree of accuracy in both classification schemes. Overhanging trees and shore vegetation contributed to classification error. Overall, results of this research suggest that high resolution imagery provides useful information for natural resource managers. It is most applicable to mapping general aquatic vegetation categories, such as submerged and emergent vegetation, and providing general estimates of plant coverage in lakes. Better methods for mapping individual species, species assemblages, and submerged vegetation constitute areas for further research. / Indiana University-Purdue University Indianapolis (IUPUI)

Resource managers need to be able to quickly and accurately map aquatic plants in freshwater lakes and ponds for regulatory purposes, to monitor the health of native species and to monitor the spread of invasive species. Site surveys and transects are expensive and time consuming, and low resolution imagery is not detailed enough to map multiple, small lakes spread out over large areas. This study evaluated methods for mapping aquatic plants using high resolution Quickbird satellite imagery obtained in 2007 and 2008. The study area included nine lakes in northern Indiana chosen because they are used for recreation, have residential development along their shorelines, support a diverse wildlife population, and are susceptible to invasive species. An unsupervised classification was used to develop two levels of classification. The Level I classification divided the vegetation into detailed classes of emergent and submerged vegetation based on plant structure. In the Level II classification, these classes were combined into more general categories. Overall accuracy of the Level I classification was 68% for the 2007 imagery and 58% for the 2008 imagery. The overall accuracy of the Level II classification was higher for both the 2007 and 2008 imagery at 75% and 74%, respectively. Classes containing bulrushes were the least accurately mapped in the Level I classification. In the Level II classification, the least accurately mapped class was submerged vegetation. Water and man-made surfaces were mapped with the highest degree of accuracy in both classification schemes. Overhanging trees and shore vegetation contributed to classification error. Overall, results of this research suggest that high resolution imagery provides useful information for natural resource managers. It is most applicable to mapping general aquatic vegetation categories, such as submerged and emergent vegetation, and providing general estimates of plant coverage in lakes. Better methods for mapping individual species, species assemblages, and submerged vegetation constitute areas for further research. / Indiana University-Purdue University Indianapolis (IUPUI)