Comparison of Topographic Surveying Techniques in Streams

Fine-scale resolution digital elevation models (DEMs) created from data collected using high precision instruments have become ubiquitous in fluvial geomorphology. They permit a diverse range of spatially explicit analyses including hydraulic modeling, habitat modeling and geomorphic change detection. Yet, the intercomparison of survey technologies across a diverse range of wadeable stream habitats has not yet been examined. Additionally, we lack an understanding regarding the precision of DEMs derived from ground-based surveys conducted by different, and inherently subjective, observers. This thesis addresses current knowledge gaps with the objectives i) to intercompare survey techniques for characterizing instream topography, and ii) to characterize observer variability in instream topographic surveys. To address objective i, we used total station (TS), real-time kinematic (rtk) GPS, terrestrial laser scanner (TLS), and infrared airborne laser scanning (ALS) topographic data from six sites of varying complexity in the Lemhi River Basin, Idaho. The accuracy of derived bare earth DEMs was evaluated relative to higher precision TS point data. Significant DEM discrepancies between pairwise techniques were calculated using propagated DEM errors thresholded at a 95% confidence interval. Mean discrepancies between TS and rtkGPS DEMs were relatively low (≤ 0.05 m), yet TS data collection time was up to 2.4 times longer than rtkGPS. ALS DEMs had lower accuracy than TS or rtkGPS DEMs, but ALS aerial coverage and floodplain topographic representation was superior to all other techniques. The TLS bare earth DEM accuracy and precision were lower than other techniques as a result of vegetation returns misinterpreted as ground returns. To address objective ii, we used a case study where seven field crews surveyed the same six sites to quantify the magnitude and effect of observer variability on DEMs interpolated from the survey data. We modeled two geomorphic change scenarios and calculated net erosion and deposition volumes at a 95% confidence interval. We observed several large magnitude elevation discrepancies across crews, however many of these i) tended to be highly localized, ii) were due to systematic errors, iii) did not significantly affect DEM-derived metric precision, and iv) can be corrected post-hoc

Geomorphic mapping and taxonomy of fluvial landforms

Fluvial geomorphologists use close to a 100 different terms to describe the landforms that make up riverscapes. We identified 68 of these existing terms that describe truly distinctive landforms, in which form is maintained under characteristic conditions and fluvial processes. Clear topographic definitions for these landforms to consistently identify and map them are lacking. With the explosion of continuous, high-resolution topography and digital elevation models, we have plenty of new basemaps in which these landforms are clearly visible, but very few examples of manual or automated classification of fluvial landforms. Fluvial landforms are the building blocks of a river and are variously referred to as geomorphic units, morphological units, habitat units, and channel units. We present a tiered framework for describing geomorphic units, with tier 1 differentiating units on the basis of their stage, tier 2 separating shape (e.g., concave, convex, or planar), tier 3 using particular key attributes to narrow in on the likely specific geomorphic unit type, and tier 4 differentiating those types on the basis of vegetative or roughness modifiers. Information on the assemblage and configuration of geomorphic units can be used to inform process-based interpretations of the range of river behavior. The accuracy and transferability of such analyses is fundamentally tied to the taxonomy we assign to these discrete building blocks. In this paper we clarify the terminology and definitions relating to the identification and delineation of geomorphic units, margins, and structural elements. We establish a set of procedures that can be used to manually map and identify these features. The proposed framework provides a rigorous and repeatable approach to identification of topographically defined features of riverscapes. We demonstrate the application of these systematic yet flexible procedures with a series of maps from rivers in differing valley settings.23 page(s

Type 2 Diabetes Interacts With Alzheimer Disease Risk Factors to Predict Functional Decline

ObjectiveThe current study examined the interactive effect of type 2 diabetes and Alzheimer disease (AD) risk factors on the rate of functional decline in cognitively normal participants from the Alzheimer's Disease Neuroimaging Initiative.MethodsParticipants underwent annual assessments that included the Functional Activities Questionnaire, an informant-rated measure of everyday functioning. Multilevel modeling, controlling for demographic variables and ischemic risk, examined the interactive effects of diabetes status (diabetes, n=69; no diabetes, n=744) and AD risk factors in the prediction of 5-year longitudinal change in everyday functioning. One model was run for each AD risk factor, including: objectively-defined subtle cognitive decline (Obj-SCD), and genetic susceptibility [apolipoprotein E ε4 (APOE ε4) as well as cerebrospinal fluid β-amyloid (Aβ), total tau (tau), and hyperphosphorylated tau (p-tau).ResultsThe 3-way diabetes×AD risk factor×time interaction predicted increased rates of functional decline in models that examined Obj-SCD, APOE ε4, tau, and p-tau positivity, but not Aβ positivity.ConclusionsParticipants with both diabetes and at least 1 AD risk factor (ie, Obj-SCD, APOE ε4, tau, and p-tau positivity) demonstrated faster functional decline compared with those without both risk factors (diabetes or AD). These findings have implications for early identification of, and perhaps earlier intervention for, diabetic individuals at risk for future functional difficulty

Prediabetes Is Associated With Brain Hypometabolism and Cognitive Decline in a Sex-Dependent Manner: A Longitudinal Study of Nondemented Older Adults

Although type 2 diabetes is a well-known risk factor for Alzheimer's disease (AD), little is known about how its precursor-prediabetes-impacts neuropsychological function and brain health. Thus, we examined the relationship between prediabetes and AD-related biological and cognitive/clinical markers in a well-characterized sample drawn from the Alzheimer's Disease Neuroimaging Initiative. Additionally, because women show higher rates of AD and generally more atherogenic lipid profiles than men, particularly in the context of diabetes, we examined whether sex moderates any observed associations. The total sample of 911 nondemented and non-diabetic participants [normal control = 540; mild cognitive impairment (MCI) = 371] included 391 prediabetic (fasting blood glucose: 100-125 mg/dL) and 520 normoglycemic individuals (age range: 55-91). Linear mixed effects models, adjusted for demographics and vascular and AD risk factors, examined the independent and interactive effects of prediabetes and sex on 2-6 year trajectories of FDG-PET measured cerebral metabolic glucose rate (CMRglu), hippocampal/intracranial volume ratio (HV/IV), cerebrospinal fluid phosphorylated tau-181/amyloid-β1-42 ratio (p-tau181/Aβ1-42), cognitive function (executive function, language, and episodic memory) and the development of dementia. Analyses were repeated in the MCI subsample. In the total sample, prediabetic status had an adverse effect on CMRglu across time regardless of sex, whereas prediabetes had an adverse effect on executive function across time in women only. Within the MCI subsample, prediabetic status was associated with lower CMRglu and poorer executive function and language performance across time within women, whereas these associations were not seen within men. In the total sample and MCI subsample, prediabetes did not relate to HV/IV, p-tau181/Aβ1-42, memory function or dementia risk regardless of sex; however, among incident dementia cases, prediabetic status related to earlier age of dementia onset in women but not in men. Results suggest that prediabetes may affect cognition through altered brain metabolism, and that women may be more vulnerable to the negative effects of glucose intolerance

Objective subtle cognitive difficulties predict future amyloid accumulation and neurodegeneration

ObjectiveTo determine the temporal sequence of objectively defined subtle cognitive difficulties (Obj-SCD) in relation to amyloidosis and neurodegeneration, the current study examined the trajectories of amyloid PET and medial temporal neurodegeneration in participants with Obj-SCD relative to cognitively normal (CN) and mild cognitive impairment (MCI) groups.MethodA total of 747 Alzheimer's Disease Neuroimaging Initiative participants (305 CN, 153 Obj-SCD, 289 MCI) underwent neuropsychological testing and serial amyloid PET and structural MRI examinations. Linear mixed effects models examined 4-year rate of change in cortical 18F-florbetapir PET, entorhinal cortex thickness, and hippocampal volume in those classified as Obj-SCD and MCI relative to CN.ResultAmyloid accumulation was faster in the Obj-SCD group than in the CN group; the MCI and CN groups did not significantly differ from each other. The Obj-SCD and MCI groups both demonstrated faster entorhinal cortical thinning relative to the CN group; only the MCI group exhibited faster hippocampal atrophy than CN participants.ConclusionRelative to CN participants, Obj-SCD was associated with faster amyloid accumulation and selective vulnerability of entorhinal cortical thinning, whereas MCI was associated with faster entorhinal and hippocampal atrophy. Findings suggest that Obj-SCD, operationally defined using sensitive neuropsychological measures, can be identified prior to or during the preclinical stage of amyloid deposition. Further, consistent with the Braak neurofibrillary staging scheme, Obj-SCD status may track with early entorhinal pathologic changes, whereas MCI may track with more widespread medial temporal change. Thus, Obj-SCD may be a sensitive and noninvasive predictor of encroaching amyloidosis and neurodegeneration, prior to frank cognitive impairment associated with MCI