Novel sampling and modeling approaches for studying soils during and after wildfires

Wildfire transforms soil physical, chemical, and biological properties. These changes are integral soil processes in fire-prone terrestrial ecosystems around the world. Although methods for estimating fire energy and impacts aboveground have progressed in recent decades, there remain major challenges in characterizing soil heating and associated effects belowground. Overcoming these challenges is crucial for understanding how fire influences soil carbon storage, biogeochemical cycling, and ecosystem recovery after fires. The work in chapter one explores nitrogen (N) cycling in soils from a case study on the Walker Fire in Northern California, 2019. Previous work has shown that N cycling is transformed by fire but variability in the magnitude and direction of those changes makes generalizing between and within fires challenging. These studies are often complicated by the lack of prefire samples and verified control areas that did not burn. In this case study, I analyzed N cycling in samples from immediately prefire, immediately postfire, and up to nine months after the fire, in both burned and control areas. The burned sampling locations ranged from low to extreme severity. I found that in this system, fire severity and soil moisture interact to control levels of N cycling and availability. These synergistic effects would have been difficult to discern with traditional sampling designs that rely on postfire measurements and space-for-time substitutions to approximate prefire conditions because of the uncertainties inherent from spatial heterogeneity. This work increases our understanding of factors driving N cycling in Sierra Nevada forests and suggests that, when possible, this sampling design should be employed to study future fires. Chapter two proposes a model for soil heating during wildfires. Previous work has shown that the extent and duration of soil heating determines the immediate fire effects on soils. However, measuring soil temperatures during fires is logistically complicated. The resulting dearth of temperature data makes elucidating mechanisms and direct relationships between heating and fire effects challenging. In this chapter, I describe and validate a new field method, called iStakes, that addresses many of the current constraints in measuring soil temperatures. I also explain and validate a modelling framework I designed, called SheFire, which can predict soil temperature over time across soil depths during wildfires. The modeling framework also includes functions to summarize soil heating in a variety of manners and extends soil heating to biological impacts with functions that model soil organism survival at different soil depths. I use data from a case study to demonstrate the utility of iStakes and SheFire. This field method and model make studying the direct effects of fire on soil more streamlined and will help researchers characterize belowground processes that are transformed by fire

Probable Sociological Reasons for the Increase in Suicide in Contemporary Ireland.

Why would an individual want to kill himself or herself? This continues to be a difficult question to understand, not to mention answer. Why not seek help when support and care is available? Why? Is the question the bereaved of those who take their lives by suicide constantly ask. Why has the value of life completely lost its appeal for a small number of people who appear to be healthy, when the opportunity is there to change course, to enjoy life to the full and to look into the extraordinary abyss of how little we know? There are people around us who may be perceived as having many reasons to kill themselves and yet do everything in the power to live, and there are those who may appear to have every reason for living and yet kill themselves. Such is the enigma of suicid

Probable Sociological Reasons for the Increase in Suicide in Contemporary Ireland.

Why would an individual want to kill himself or herself? This continues to be a difficult question to understand, not to mention answer. Why not seek help when support and care is available? Why? Is the question the bereaved of those who take their lives by suicide constantly ask. Why has the value of life completely lost its appeal for a small number of people who appear to be healthy, when the opportunity is there to change course, to enjoy life to the full and to look into the extraordinary abyss of how little we know? There are people around us who may be perceived as having many reasons to kill themselves and yet do everything in the power to live, and there are those who may appear to have every reason for living and yet kill themselves. Such is the enigma of suicid

Construction of work sheets to accompany the third grade arithmetic guide of Newton, Massachusetts.

Thesis (M.A.)--Boston Universit

Being a Teacher: Towards an Existentialist Account

Against the current grain of teacher accountability, this thesis aims to reconceptualise how we might account for teaching through an engagement with Jean-Paul Sartre’s early existentialist thought. In Part I, I will begin by situating the issue in relation to school self-evaluation policy in the Republic of Ireland. This policy exemplifies three connected fallacies in accounting for the practices of teaching – firstly, the perceived need to balance accountability and autonomy; secondly, the focus on building capacities for the use of communication norms couched within the language of effectiveness; and thirdly, the emphasis on a reductive understanding of ‘evidence’ in such accounts. Above all, these fallacies portray teaching as a ‘technicist’ endeavour and are ultimately based on problematic assumptions about the experience of being a teacher. Part II turns to the demanding account of being a human in Sartre’s thought. Here, it is argued that the classroom serves as a microcosm where many of these ideas can be explored. By paying close attention to everyday examples of teaching, I aim to build upon Sartre’s key concepts related to the self, freedom, bad faith, and the Other, such that they might open up new ways of thinking about the practices of teaching. Part III considers how to account for teaching in light of this. Since so much of teacher accountability is embedded within the paradigm of ‘effectiveness’, the current focus is often on how to measure or ‘prove’ our accounts of teaching in neat, accurate forms. But given the everyday complexities that underpin teaching, as well as the vulnerabilities and uncertainty that it so often involves, I argue for the creation of a space in which to reimagine forms of accounting that move from technicist ways of thinking to existential sensitivity in relation to one’s practice as a teacher

Scales of Captivity

Mary Pat Brady traces the figure of the captive and cast-off child over 150 years of Latinx/Chicanx literature as a critique of colonial modernity and the forms of confinement that underpin racialized citizenship

Acceleration and Parallelization of ZENO/Walk-on-Spheres

AbstractThis paper describes our on-going work to accelerate ZENO, a software tool based on Monte Carlo methods (MCMs), used for computing material properties at nanoscale. ZENO employs three main algorithms: (1) Walk on Spheres (WoS), (2) interior sampling, and (3) surface sampling. We have accelerated the first two algorithms. For the sake of brevity, the paper will discuss our work on the first one only as it is the most commonly used and the acceleration techniques were similar in both cases.WoS is a Brownian motion MCM for solving a class of partial differential equations (PDEs). It provides a stochastic solution to a PDE by estimating the probability that a random walk, which started at infinity, will hit the surface of the material under consideration. WoS is highly effective when the problem's geometry is additive, as this greatly reduces the number of walk steps needed to achieve accurate results. The walks start on the surface of an enclosing sphere and can make much larger jumps than in a direct simulation of Brownian motion. Our current implementation represents the molecular structure of nanomaterials as a union of possibly overlapping spheres. The core processing bottleneck in WoS is a Computational Geometry one, as the algorithm repeatedly determines the distance from query point to the material surface in each step of the random walk.In this paper, we present results from benchmarking spatial data structures, including several open-source implementations of k-D trees, for accelerating WoS algorithmically. The paper also presents results from our multicore and cluster parallel implementation to show that it exhibits linear strong scaling with the number of cores and compute nodes; this implementation delivers up to 4 orders of magnitude speedup compared to the original FORTRAN code when run on 8 nodes (each with dual 6-core Intel Xeon CPUs) with 24 threads per node