305 research outputs found

    The Effects of Targeted Triclopyr Application on Habitat Quality in Boreal Saskatchewan Transmission Rights-of-Way

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    Vegetation management along transmission rights-of-way in remote northern forests across Canada is challenging. Mechanical removal of vegetation is often ineffective as many boreal species regenerate rapidly upon physical disturbance. Limited information on herbicide impacts in northern regions and on boreal vegetation makes communicating risks and benefits to local stakeholders and Indigenous communities difficult. Herbicides directly enter the ecosystem through deposition on vegetation and soils following application. Treated vegetation can be a vector of contamination to browsing herbivores, and herbicides can indirectly enter the soil ecosystem upon leaf abscission. Litter decomposition is critical to soil nutrient cycling and ultimately ecosystem health. The indirect effects of herbicides on habitat quality in boreal ecoregions remains poorly understood. Working in collaboration with SaskPower and the Lac La Ronge Indian Band, the influence of targeted applications of the herbicides, Garlon RTU and Garlon XRT (active ingredient triclopyr) were studied in northern Saskatchewan. Triclopyr drift and dissipation in foliage were assessed following a targeted low-volume foliar (Garlon XRT) or basal bark (Garlon RTU) application. Greater drift concentrations localized at the stem base were observed with basal bark treatments. These effects may be exacerbated with high stem density, especially in conjunction with sandy soil prevalent in northern Saskatchewan which increases the potential of herbicide mobility and off-target effects. Concentrations in foliage were higher following low-volume foliar applications but dissipated to 50% of initial concentrations within a week (DT50 = 5.7 days and DT90 = 34.6 days). A hazard quotient risk assessment for moose (Alces alces) and snowshoe hare (Lepus americanus) indicates browsing on triclopyr treated foliage with the residues detected in this study are unlikely to result in acute toxicity (extrapolated from concentrations that caused 50% mortality in rats and rabbits, respectively); however, long-term browsing may cause adverse chronic effects (extrapolated from the concentration with no observable effects in a two-generation reproduction rat study with a safety factor of 100). Basal bark application is ideal when stem density is lower and toxic effects for herbivores is of concern, and low-volume foliar applications are best suited in areas with higher stem density when off-target herbicide deposition is less acceptable. The indirect impacts of triclopyr on habitat quality were also examined through litter mass loss and quality (carbon:nitrogen ratios) as was the response of boreal invertebrates (Folsomia candida and Oppia nitens) in microcosms and avoidance tests. Higher concentrations of nitrogen (lower carbon:nitrogen) were observed in field treated foliage resulting from triclopyr repression of natural leaf senescence processes. Litter breakdown rates were not significantly different within a year of treatment despite nitrogen profile differences between field treated and untreated samples. Triclopyr concentrations entering the ecosystem upon leaf abscission were below conservative avoidance endpoints for boreal invertebrates. The triclopyr concentrations that caused 50% of tested F. candida and O. nitens to avoid treated litter were above field application rates. At field application concentrations there were no differences in survival and reproduction rates of F. candida. Therefore, field application rates of triclopyr are not expected to impair ecosystem services and habitat quality based on the parameters evaluated in these studies. The results from these studies suggest the overall risk of targeted triclopyr use in northern Saskatchewan rights-of-way is low. These findings have improved our knowledge concerning triclopyr use in boreal ecosystems to support risk communication and informed integrative vegetation management decisions

    LIPIcs, Volume 274, ESA 2023, Complete Volume

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    LIPIcs, Volume 274, ESA 2023, Complete Volum

    On Multilevel Methods Based on Non-Nested Meshes

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    This thesis is concerned with multilevel methods for the efficient solution of partial differential equations in the field of scientific computing. Further, emphasis is put on an extensive study of the information transfer between finite element spaces associated with non-nested meshes. For the discretization of complicated geometries with a finite element method, unstructured meshes are often beneficial as they can easily be adjusted to the shape of the computational domain. Such meshes, and thus the corresponding discrete function spaces, do not allow for straightforward multilevel hierarchies that could be exploited to construct fast solvers. In the present thesis, we present a class of "semi-geometric" multilevel iterations, which are based on hierarchies of independent, non-nested meshes. This is realized by a variational approach such that the images of suitable prolongation operators in the next (finer) space recursively determine the coarse level spaces. The semi-geometric concept is of very general nature compared with other methods relying on geometric considerations. This is reflected in the relatively loose relations of the employed meshes to each other. The specific benefit of the approach based on non-nested meshes is the flexibility in the choice of the coarse meshes, which can, for instance, be generated independently by standard methods. The resolution of the boundaries of the actual computational domain in the constructed coarse level spaces is a characteristic feature of the devised class of methods. The flexible applicability and the efficiency of the presented solution methods is demonstrated in a series of numerical experiments. We also explain the practical implementation of the semi-geometric ideas and concrete transfer concepts between non-nested meshes. Moreover, an extension to a semi-geometric monotone multigrid method for the solution of variational inequalities is discussed. We carry out the analysis of the convergence and preconditioning properties, respectively, in the framework of the theory of subspace correction methods. Our technical considerations yield a quasi-optimal result, which we prove for general, shape regular meshes by local arguments. The relevant properties of the operators for the prolongation between non-nested finite element spaces are the H1-stability and an L2-approximation property as well as the locality of the transfer. This thesis is a contribution to the development of fast solvers for equations on complicated geometries with focus on geometric techniques (as opposed to algebraic ones). Connections to other approaches are carefully elaborated. In addition, we examine the actual information transfer between non-nested finite element spaces. In a novel study, we combine theoretical, practical and experimental considerations. A thourough investigation of the qualitative properties and a quantitative analysis of the differences of individual transfer concepts to each other lead to new results on the information transfer as such. Finally, by the introduction of a generalized projection operator, the pseudo-L2-projection, we obtain a significantly better approximation of the actual L2-orthogonal projection than other approaches from the literature.Nicht-geschachtelte Gitter in Multilevel-Verfahren Diese Arbeit beschäftigt sich mit Multilevel-Verfahren zur effizienten Lösung von Partiellen Differentialgleichungen im Bereich des Wissenschaftlichen Rechnens. Dabei liegt ein weiterer Schwerpunkt auf der eingehenden Untersuchung des Informationsaustauschs zwischen Finite-Elemente-Räumen zu nicht-geschachtelten Gittern. Zur Diskretisierung von komplizierten Geometrien mit einer Finite-Elemente-Methode sind unstrukturierte Gitter oft von Vorteil, weil sie der Form des Rechengebiets einfacher angepasst werden können. Solche Gitter, und somit die zugehörigen diskreten Funktionenräume, besitzen im Allgemeinen keine leicht zugängliche Multilevel-Struktur, die sich zur Konstruktion schneller Löser ausnutzen ließe. In der vorliegenden Arbeit stellen wir eine Klasse "semi-geometrischer" Multilevel-Iterationen vor, die auf Hierarchien voneinander unabhängiger, nicht-geschachtelter Gitter beruhen. Dabei bestimmen in einem variationellen Ansatz rekursiv die Bilder geeigneter Prolongationsoperatoren im jeweils folgenden (feineren) Raum die Grobgitterräume. Das semi-geometrische Konzept ist sehr allgemeiner Natur verglichen mit anderen Verfahren, die auf geometrischen Überlegungen beruhen. Dies zeigt sich in der verhältnismäßig losen Beziehung der verwendeten Gitter zueinander. Der konkrete Nutzen des Ansatzes mit nicht-geschachtelten Gittern ist die Flexibilität der Wahl der Grobgitter. Diese können beispielsweise unabhängig mit Standardverfahren generiert werden. Die Auflösung des Randes des tatsächlichen Rechengebiets in den konstruierten Grobgitterräumen ist eine Eigenschaft der entwickelten Verfahrensklasse. Die flexible Einsetzbarkeit und die Effizienz der vorgestellten Lösungsverfahren zeigt sich in einer Reihe von numerischen Experimenten. Dazu geben wir Hinweise zur praktischen Umsetzung der semi-geometrischen Ideen und konkreter Transfer-Konzepte zwischen nicht-geschachtelten Gittern. Darüber hinaus wird eine Erweiterung zu einem semi-geometrischen monotonen Mehrgitterverfahren zur Lösung von Variationsungleichungen untersucht. Wir führen die Analysis der Konvergenz- bzw. Vorkonditionierungseigenschaften im Rahmen der Theorie der Teilraumkorrekturmethoden durch. Unsere technische Ausarbeitung liefert ein quasi-optimales Resultat, das wir mithilfe lokaler Argumente für allgemeine, shape-reguläre Gitterfamilien beweisen. Als relevante Eigenschaften der Operatoren zur Prolongation zwischen nicht-geschachtelten Finite-Elemente-Räumen erweisen sich die H1-Stabilität und eine L2-Approximationseigenschaft sowie die Lokalität des Transfers. Diese Arbeit ist ein Beitrag zur Entwicklung schneller Löser für Gleichungen auf komplizierten Gebieten mit Schwerpunkt auf geometrischen Techniken (im Unterschied zu algebraischen). Verbindungen zu anderen Ansätzen werden sorgfältig aufgezeigt. Daneben untersuchen wir den Informationsaustausch zwischen nicht-geschachtelten Finite-Elemente-Räumen als solchen. In einer neuartigen Studie verbinden wir theoretische, praktische und experimentelle Überlegungen. Eine sorgfältige Prüfung der qualitativen Eigenschaften sowie eine quantitative Analyse der Unterschiede verschiedener Transfer-Konzepte zueinander führen zu neuen Ergebnissen bezüglich des Informationsaustauschs selbst. Schließlich erreichen wir durch die Einführung eines verallgemeinerten Projektionsoperators, der Pseudo-L2-Projektion, eine deutlich bessere Approximation der eigentlichen L2-orthogonalen Projektion als andere Ansätze aus der Literatur

    Developing biodiversity indicators and economic valuations for created grasslands in the UK

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    The thesis is an investigation in to a quick and easy means of establishing the ecosystem service provision of a created grassland and applying an economic value to these services. Biodiversity indicators are first explored in a literature review. Common statistical techniques are then employed to identify relevant bio-indicators of created grasslands from first-hand data collected from sourced fieldwork study sites. Economic values of ecosystem service provision in grasslands are then extracted from papers sourced from a systematic review. These values, and their explanatory variables, are modelled to establish variation in economic estimates. Benchmarking figures of goal grassland ecosystem service provision are established based on theory. Crucially, a link between ecological data and economic values is ascertained. This allows an Excel model to be designed allowing users to estimate economic value of grasslands based on on-site recordings of identified bio-indicators

    Bayesian Computation with Application to Spatial Models and Neuroimaging

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    Analysis of Neuroimaging data has experienced great strides over the last few decades. Two key aspects of Neuroimaging data are its high-dimensionality and complex spatio-temporal autocorrelation. Classical approaches are somewhat limited in dealing with these two issues, as a result, Bayesian approaches are being utilized more frequently due to their flexibility. Despite their flexibility, there are several challenges for Bayesian approaches with respect to the required computation. First, the need for an efficient posterior computation method is paramount. Second, even in conjugate models, statistical accuracy in Bayesian computation may be hard to achieve. Since accuracy is of primary concern when studying the human brain, a careful and innovative exploration of Bayesian models and computation is necessary. In this dissertation, we address some of these issues by looking at various Bayesian computational algorithms in terms of both accuracy and speed in the context of Neuroimaging data. The algorithms we study are the Hamiltonian Monte Carlo (HMC), Variational Bayes (VB), and integrated nested Laplace approximation (INLA) algorithms. HMC is a MCMC method that's particularly powerful for sampling in high-dimensional space with highly correlated parameters. It's robust and accurate, yet not as fast as some approximate Bayesian methods, for example, Variational Bayes (VB). However, since there is no theoretical guarantee that the resulting posterior derived from VB is accurate, its performance has to be analyzed on a case-by-case basis. INLA is another extremely fast method based on numerical integration with Laplace approximations but, like VB, there are no generally applicable theoretical guarantees of accuracy. In Chapter II we focus on a particular spatial point process model, namely the log Gaussian Cox Process (LGCP), and consider applications to ecological and neuroimaging data. Inference for the LGCP is challenging due to its non-conjugacy and doubly stochastic property. We develop HMC and VB algorithms for the LGCP model and make comparisons with INLA. In Chapter III, we turn our focus to the general linear model with autoregressive errors (GLM-AR) which is widely used in analyzing fMRI single subject data. We derive an HMC algorithm and compare it with the VB algorithm and the mass univariate approach using the Statistical Parametric Mapping (SPM) software program. In Chapter IV, we extend the original GLM-AR model to a new model where the order of the AR coefficients can varying spatially across the brain and call it GLM with spatially varying autoregressive orders (SVARO). Using simulations and real data we compare our SVARO model with GLM-AR model implemented under both our MCMC sampler and the SPM VB algorithm. Our results shed light on several important issues. While HMC almost always yields the most accurate results, the performance of VB is strongly model specific. INLA is a fast alternative to MCMC methods but we observe some limitations when examining its accuracy in certain settings. Furthermore, our new SVARO model performs better than the GLM-AR model in a number of ways. Not surprisingly, more accurate algorithms generally require more computational time. By systematically evaluating the pros and cons of each method, we believe our work to be practically useful for those researchers considering the use of these methods.PHDBiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138616/1/tengming_1.pd
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