Diversity indices confound two components: species richness and evenness. Community structure should therefore be evaluated by employing separate measures of the number of species and their relative abundances. However, the relative abundances of species are dependent on the abundance measure used. Although the use of biomass or productivity is recommended by theory, in practice a surrogate measure is more often used. Frequency (local or relative) and point-quadrat cover provide two objective measures of abundance which are fast, less destructive and avoid problems associated with distinguishing individuals. However, both give discrete bounded data which may further alter the relative abundances of species. These measures have a long history of use and, as the need for objective information on biodiversity becomes more pressing, their use is likely to become more widespread. Consequently, it seems appropriate to investigate the effect of these abundance measures, and the resolution at which they are used, on calculated evenness. Field, artificial and simulated data were used to investigate the effect of abundance measure and resolution on evidence for community structure. The field data consisted of seventeen sites. Sites from four vegetation types (saltmeadow, geothermal, ultramafic and high-altitude meadow) were sampled in three biogeographical regions. Most of the indices of community structure (species richness, diversity and evenness) detected differences between the different vegetation types, and different niche-apportionment models were fitted to the field data from saltmeadow and geothermal vegetation. Estimates of community structure based on local frequency and point-quadrat data differed. Local frequency tended to give higher calculated evenness; whereas point-quadrat data tended to fit to niche apportionment models where local frequency data failed. The effect of resolution on the eighteen evenness indices investigated depended on community species richness and the particular index used. The investigated evenness indices were divided into three groups (symmetric, continuous and traditional indices) based on how they ranked real and artificially constructed communities. Contrary to Smith and Wilson�s recommendation the symmetric indices E[VAR] and E[Q] proved unsuitable for use with most types of plant data. In particular, E[Q] tends to assign most communities low values and has a dubious relationship with intrinsic evenness. The continuous indices, E[MS] and E[2,1], were the indices best able to discriminate between field, artificial and simulated communities, and their use should be re-evaluated. Traditional indices used with low resolution tended to elevate the calculated evenness, especially in species-rich communities. The relativized indices, E[Hurlbert] and EO[dis], were an exception, as they were always able to attain the minimum of zero; however, they were more sensitive to changes in resolution, particularly when resolution was low. Overall, traditional indices based on Hill�s ratios, including E[1/D] (=E[2,0]), and G[2,1] gave the best performance, while the general criticism of the use of Pielou�s J� as an index of evenness was further substantiated by this study. As a final recommendation, ecologists are implored to investigate their data and the likely effects that sampling and analysis have had on the calculated values of their indices.

Many ecological populations can be interpreted as response surfaces; the spatial patterns of the population vary in response to changes in the spatial patterns of environmental explanatory variables. Collection of a probability sample from the population provides unbiased estimates of the population parameters using design based estimation. When information is available for the environmental explanatory variables, model based procedures are available that provide more precise estimates of population parameters in some cases. In practice, not all of these environmental explanatory variables will be known. When the spatial coordinates of the population units are available, a spatial model can be used as a surrogate for the unknown, spatially patterned explanatory variables. Design based and model based procedures will be compared for estimating parameters of the population of Acid Neutralizing Capacity (ANC) of lakes in the Adirondack Mountains in New York. Results from the analysis of this population will be used to elucidate some general principles for model based estimation of parameters of spatial populations. Results indicate that using model based estimates of population parameters provide more precise estimates than design based estimates in some cases. In addition, including spatial information as a surrogate for spatially patterned missing covariates improves the precision of the estimates in some cases, the degree to which depends upon the model chosen to represent the spatial pattern. When the probability sample is selected from the spatial population is a stratified sample, differences in stratum variances need to be accounted for when residual spatial covariance estimation is desired for the entire population. This can be accomplished by scaling residuals by their estimated stratum standard deviation functions, and calculating the residual covariance using these scaled residuals. Results here demonstrate that the form of scaling influences the estimated strength of the residual correlation and the estimated correlation range. / Graduation date: 1997

Thesis (M.S.)--University of Wisconsin--Stevens Point, 2009. / Submitted in partial fulfillment of the requirements of the degree Master of Science in Natural Resources (Fisheries), College of Natural Resources. Includes bibliographical references (leaves 176-190).

Title from title page of PDF (University of Missouri--St. Louis, viewed February 23, 2010). Includes bibliographical references.

We use metapopulation models based on a classic competition-colonization trade-off in order to (1) study community responses to spatially structured habitat loss on dynamic landscapes when species are assembled by ecological (biogeographic) processes; and (2) to study how species are assembled into communities by evolutionary mechanisms. In the first part of our study we show how the response of species richness to habitat destruction in dynamic landscapes can be driven by the existence of either the spatial structure of habitat dynamics or by life-history trade-offs among species. In the second part of our study we confirm that competitive trade-off models predict runaway evolution towards stochastic extinction, making it impossible for stable multispecies assemblages to evolve. We demonstrate that by relaxing the strict deterministic nature of competitive exclusion in such models species can avoid selection towards extinction, allowing for the possibility of species co-evolution resulting in stable multispecies assemblages.

Diversity indices confound two components: species richness and evenness. Community structure should therefore be evaluated by employing separate measures of the number of species and their relative abundances. However, the relative abundances of species are dependent on the abundance measure used. Although the use of biomass or productivity is recommended by theory, in practice a surrogate measure is more often used. Frequency (local or relative) and point-quadrat cover provide two objective measures of abundance which are fast, less destructive and avoid problems associated with distinguishing individuals. However, both give discrete bounded data which may further alter the relative abundances of species. These measures have a long history of use and, as the need for objective information on biodiversity becomes more pressing, their use is likely to become more widespread. Consequently, it seems appropriate to investigate the effect of these abundance measures, and the resolution at which they are used, on calculated evenness. Field, artificial and simulated data were used to investigate the effect of abundance measure and resolution on evidence for community structure. The field data consisted of seventeen sites. Sites from four vegetation types (saltmeadow, geothermal, ultramafic and high-altitude meadow) were sampled in three biogeographical regions. Most of the indices of community structure (species richness, diversity and evenness) detected differences between the different vegetation types, and different niche-apportionment models were fitted to the field data from saltmeadow and geothermal vegetation. Estimates of community structure based on local frequency and point-quadrat data differed. Local frequency tended to give higher calculated evenness; whereas point-quadrat data tended to fit to niche apportionment models where local frequency data failed. The effect of resolution on the eighteen evenness indices investigated depended on community species richness and the particular index used. The investigated evenness indices were divided into three groups (symmetric, continuous and traditional indices) based on how they ranked real and artificially constructed communities. Contrary to Smith and Wilson�s recommendation the symmetric indices E[VAR] and E[Q] proved unsuitable for use with most types of plant data. In particular, E[Q] tends to assign most communities low values and has a dubious relationship with intrinsic evenness. The continuous indices, E[MS] and E[2,1], were the indices best able to discriminate between field, artificial and simulated communities, and their use should be re-evaluated. Traditional indices used with low resolution tended to elevate the calculated evenness, especially in species-rich communities. The relativized indices, E[Hurlbert] and EO[dis], were an exception, as they were always able to attain the minimum of zero; however, they were more sensitive to changes in resolution, particularly when resolution was low. Overall, traditional indices based on Hill�s ratios, including E[1/D] (=E[2,0]), and G[2,1] gave the best performance, while the general criticism of the use of Pielou�s J� as an index of evenness was further substantiated by this study. As a final recommendation, ecologists are implored to investigate their data and the likely effects that sampling and analysis have had on the calculated values of their indices.

Thesis (Ph.D.)--University of Western Australia, 2004.

Thesis (Ph. D.)--University of Nevada, Reno, 2008. / "December, 2008." Includes bibliographical references). Online version available on the World Wide Web.

Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (leaves [78]-88).

Thesis (Ph. D.)--Wildlife and Fisheries Sciences Dept., South Dakota State University, 2009. / Includes bibliographical references. Also available via the World Wide Web.