APPLICATION OF HIERARCHICAL SPECIES DISTRIBUTION MODELS TO AVIAN SPECIES OF SOUTH DAKOTA AND THE UPPER MISSOURI RIVER BASIN

Recognizing the distributional patterns of species can inform management actions and increase scientific knowledge about species. Habitat Suitability Models (HSMs) are valuable tools in modeling species’ niches and effects of climate change and anthropogenic and natural disturbances on species’ distributions and abundances. In this dissertation, I expanded the application of hierarchical HSMs for a rare bird (Virginia’s warbler) and an economically valuable bird (ring-necked pheasant) in South Dakota. Also, we developed multiscale HSMs for grassland birds in the Upper Missouri River Basin (UMRB) to quantify current habitat associations and predict the influences of climate and landcover change associated with the implementation of bioenergy with carbon capture and storage (BECCS) and other carbon mitigation scenarios. We found that applying an Ensemble of Small Models (ESMs) approach within a hierarchical framework can lead to detailed information about niches of rare species, limiting factors at each habitat selection order, and potential distribution, which could help inform multiscale management. At the broadest habitat selection order, Virginia’s warbler had a narrow climatic niche. The importance of environmental variables changed across finer orders, such that at broader orders many covariates were important whereas at finer orders certain covariates became more important than others. For the model of pheasant abundance, my results showed that our hierarchical Bayesian approach allows for simultaneous selection of variables and scales of effect. I found that pheasant abundance was positively affected by intermediate levels of grassland cover. Scales of effect and spatiotemporal variation influenced predictor variable impacts on pheasant abundance. For the modeling of grassland birds across the UMRB, my results showed that the influence of climate change on abundance, distribution and species richness of grassland species is more pronounced than the influence of landcover changes due to implementing BECCS scenarios. This finding implies that regardless of landcover and land-use changes, climate change may limit or expand abundance and distribution of grassland bird species in the UMRB. Further, we found that grassland birds will be more affected by regional increases in temperature than decreases in precipitation

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.Siirretty Doriast

A comparison of spatially explicit and classic regression modelling of live coral cover using hyperspectral remote-sensing data in the Al Wajh lagoon, Red Sea

Live coral is a key component of the Al Wajh marine reserve in the Red Sea. The management of this reserve is dependent on a sound understanding of the existing spatial distribution of live coral cover and the environmental factors influencing live coral at the landscape scale. This study uses remote-sensing techniques to develop ordinary least squares and spatially lagged autoregressive explanatory models of the distribution of live coral cover inside the Al Wajh lagoon, Saudi Arabia. Live coral was modelled as a response to environmental controls such as water depth, the concentration of suspended sediment in the water column and exposure to incident waves. Airborne hyperspectral data were used to derive information on live coral cover as a response (dependent) variable at the landscape scale using linear spectral unmixing. Environmental controls (explanatory variables) were derived from a physics-based inversion of the remote-sensing dataset and validated against field-collected data. For spatial regression, cases referred to geographical locations that were explicitly drawn on in the modelling process to make use of the spatially dependent nature of coral cover controls. The transition from the ordinary least squares model to the spatially lagged model was accompanied by a marked growth in explanatory power (R 2 = 0.26 to 0.76). The theoretical implication that follows is that neighbourhood context interactions play an important role in determining live coral cover. This provides a persuasive case for building geographical considerations into studies of coral distribution

Visuelle Analyse großer Partikeldaten

Partikelsimulationen sind eine bewährte und weit verbreitete numerische Methode in der Forschung und Technik. Beispielsweise werden Partikelsimulationen zur Erforschung der Kraftstoffzerstäubung in Flugzeugturbinen eingesetzt. Auch die Entstehung des Universums wird durch die Simulation von dunkler Materiepartikeln untersucht. Die hierbei produzierten Datenmengen sind immens. So enthalten aktuelle Simulationen Billionen von Partikeln, die sich über die Zeit bewegen und miteinander interagieren. Die Visualisierung bietet ein großes Potenzial zur Exploration, Validation und Analyse wissenschaftlicher Datensätze sowie der zugrundeliegenden Modelle. Allerdings liegt der Fokus meist auf strukturierten Daten mit einer regulären Topologie. Im Gegensatz hierzu bewegen sich Partikel frei durch Raum und Zeit. Diese Betrachtungsweise ist aus der Physik als das lagrange Bezugssystem bekannt. Zwar können Partikel aus dem lagrangen in ein reguläres eulersches Bezugssystem, wie beispielsweise in ein uniformes Gitter, konvertiert werden. Dies ist bei einer großen Menge an Partikeln jedoch mit einem erheblichen Aufwand verbunden. Darüber hinaus führt diese Konversion meist zu einem Verlust der Präzision bei gleichzeitig erhöhtem Speicherverbrauch. Im Rahmen dieser Dissertation werde ich neue Visualisierungstechniken erforschen, welche speziell auf der lagrangen Sichtweise basieren. Diese ermöglichen eine effiziente und effektive visuelle Analyse großer Partikeldaten

The Ecological Value of Spruce Plantations in Massachusetts

The establishment of monoculture plantations of exotic tree species is common practice for supplementing native timber stocks. Such plantations typically provide inferior habitat for wildlife compared to native forest, which may result in a net reduction in biodiversity. However, some studies report that plantations may increase net biodiversity at the landscape scale by introducing novel habitats or supplementing existing natural forests. Using point count surveys, I examined six mature Norway spruce (Picea abies) plantations in western Massachusetts in 2016 and 2017 to evaluate bird use of these habitats relative to native forest stands. Count data were analyzed using N-mixture models to correct for imperfect detection, providing more accurate estimates of true abundance. Our findings showed that overall species richness for spruce plantations was not significantly lower than that of native forest habitats. Red-breasted nuthatch (Sitta canadensis) and golden-crowned kinglet (Regulus satrapa) were most abundant in spruce plantations. Conifer dependent species such as Blackburnian warbler (Setophaga fusca) and brown creeper (Certhia americana), were significantly more abundant in spruce plantations relative to native deciduous, hemlock, and mixed stands. Species that heavily associate with broadleaf habitat were rarely observed in spruce plantations. Species that associate with eastern hemlock habitat, such as Blue-headed vireo (Vireo solitarious) and black-throated green warbler (Setophaga virens) were observed using spruce plantations at similar levels as eastern hemlock stands. These results demonstrate that Norway spruce plantations can provide suitable habitat for native species associated with conifers, which is significant given projected continued decline of eastern hemlock in response to the hemlock wooly adelgid (Adelges tsugae). Although large-scale conversion of native forest to plantations would likely lead to a loss in biodiversity, land managers could be justified in allowing small-scale plantations to persist without suffering negative impacts to native biodiversity