Browsing by Subject "Time series analysis"

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    The Vulnerability of Northern High-Latitude Ecosystems to Climate and Disturbance-Induced Change
    (2018-06) Pastick, Neal
    Arctic and boreal regions have experienced unprecedented changes in recent decades as the result of climate change. Increasing air temperatures have led to widespread warming and degradation of permafrost, significant shifts in vegetation composition and productivity, and increases in disturbance frequency and extent that can have profound impacts on ecosystems and human populations across the globe. Despite a legacy of studies describing the heightened sensitivity of arctic and boreal ecosystems to change, there has not been a comprehensive assessment of historical and projected trends in landscape properties, disturbances, and drivers of change throughout all of Alaska. Such an assessment is immensely challenging because of spatially-heterogeneous dynamics and interactions among numerous factors that influence ecosystems throughout the State. Consequently, additional research is needed to better characterize permafrost-affected landscapes and their potential response to further perturbations. This dissertation presents important improvements in the mechanistic understanding and characterization capabilities of changing permafrost landscapes by combining field measurements, time series analyses, climate reanalysis data, and remote sensing into an integrated modeling framework. The primary goal is to improve understanding of how and why globally significant permafrost landscapes are changing by means of: (1) Characterizing climate, permafrost, disturbance, and vegetation dynamics that exert strong controls on energy, water, and biogeochemical cycling; (2) Quantifying underlying drivers of change related to contemporary trends in land and water surfaces observed by remote sensing; and; (3) Providing novel approaches and baseline information to fill critical observational gaps identified by the remote sensing community and permafrost and ecosystem scientists. This research supports the science priorities of federal agencies (e.g. United States Geological Survey, National Aeronautics and Space Administration) and techniques and results are highly relevant to climatic, hydrologic, ecologic, topographic, and cryospheric studies. This research provides critically needed information on the temporal and regional distribution of landscape properties and conditions, which is instrumental in determining the vulnerability and resilience of northern high-latitudes regions to climate and disturbance-induced change, and benefits both the research community and the policy community in the management of Arctic and boreal landscapes.
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    What do trees remember? Disentangling climate, biological, and ecological signals from tree-ring time series
    (2022-10) McPartland, Mara
    Dendrochronology, the study of tree rings, uses variation in the annual growth patterns of trees to make inferences about the past. Most commonly used as records of past climate, tree ring analysis has built our understanding of how the climate has varied during the Common Era. Tree rings are also physical records of tree growth, and are often used in ecosystem science to understand how climate and environment influence the health of forests. In order to use tree rings to infer past changes in environment and ecosystems, researchers must content with the complexity of exogenous (climatic and environmental) and endogenous (biological) signals contained within annual tree rings. A range of statistical and data processing techniques are used to filter tree-ring time series to extract specific signals and discard unwanted sources of variance, but these techniques are imperfect and may result in biased estimates of the relationship between climate and tree growth through time. In my dissertation, I evaluate how assumptions made about the sources of variance contained within tree rings, as well as choices made during data development and analysis, influence the outcome of tree-ring studies. I explore these themes through three separate case studies, described in four chapters. In my first chapter, I compared different data processing methods commonly used by dendrochronologists to determine their effects on final chronologies. In my second and third chapters, I investigate the relationship between drought and radial growth patterns, and explore whether drought should be thought of following a classic ‘disturbance’ model, or as an ongoing climatic phenomenon. In my final chapter, I analyzed whether evidence of anthropogenic warming is visible in tree-ring series from Minnesota – a region where trees are not typically considered sensitive to variations in climate.