Stephen J. Walsh

Modeling floodplain inundation using an integrated GIS with radar and optical remote sensing

Abstract Synthetic aperture radar images from multitemporal L-band JERS-1 and C-band ERS-1 satellites, a Landsat Thematic Mapper (TM) time-series, and GIS coverages were used in an integrative approach to model the potential of flood inundation within the lower Roanoke River floodplain, North Carolina. A digital elevation model (DEM) with one-meter vertical resolution was developed for the region from scan-digitized mylar separates of contour lines on USGS 7.5-min quadrangles. Several models representing potential wetness and potential flood inundation were generated from the DEMs using both raster (grid) and vector (network) analyses. The potential inundation surfaces were derived from regression models that related known flood elevations to river position and floodplain location. The GIS models were assessed by comparison to classifications of flood change-detection achieved through the radar data. Statistical results indicate that the GIS-derived models successfully identified flooded areas as mapped by the radar change-detections. Further, statistical tests assessed the ability of individual radar and optical (Landsat TM) images to discriminate flooding as predicted by the GIS models. Both JERS-1 and ERS-1 images identified areas of inundation at different flood levels.

Immediate and delayed effects of cognitive interventions in healthy elderly: a review of current literature and future directions.

Research on the potential effects of cognitive intervention in healthy elderly has been motivated by (1) the apparent effectiveness of cognitive rehabilitation in Alzheimers disease (AD) patients; (2) the face validity of bolstering skills eventually burdened by disease; (3) interest in low‐cost/noninvasive methods of preventing or delaying onset of disease; (4) the epidemiologic research suggesting protective effects of educational attainment and lifelong participation in cognitively stimulating activities; (5) the burgeoning industry of brain training products and requisite media attention; and (6) the aging world population.

An overview of scale, pattern, process relationships in geomorphology; a remote sensing and GIS perspective

Abstract Satellite remote sensing and geographic information systems are emerging technologies in geomorphology. They offer the opportunity to gain fresh insights into biophysical systems through the spatial, temporal, spectral, and radiometric resolutions of remote sensing systems and through the analytical and data integration capability of GIS. The two technologies can be linked together into a synergistic system that is particularly well suited to the examination of landscape conditions through the interrelationships of scale, pattern, and process, a paradigm that has gained prominence in the fields of biogeography and landscape ecology. In this study, we apply optical and microwave remote sensing systems and GIS methodologies to case studies framed within the fluvial and alpine environments. We use the scale, pattern, and process paradigm to explore landscape relationships in those environments. Satellite image processing, change-detection analyses, digital elevation models, GIS-derived geomorphic indices and variables, composition and pattern metrics of landscape organization, and scale-dependent analyses are described and related to the study of river channel abandonment and the alpine treeline ecotone. We describe appropriate remote sensing and GIS techniques for geomorphic research, and demonstrate the use of such techniques in the application of the scale, pattern, and processes perspective in geomorphic studies.

The Association Between Vitamin D and Inflammation with the 6-Minute Walk and Frailty in Patients with Heart Failure

OBJECTIVES: To identify relationships between anabolic hormones, inflammatory markers, and physical function.

Alpine treeline of western North America; linking organism-to-landscape dynamics

Although the ecological dynamics of the alpine treeline ecotone are influenced by climate, it is an imperfect indicator of climate change. Mechanistic processes that shape the ecotone—seed rain, seed germination, seedling establishment and subsequent tree growth form, or, conversely tree dieback—depend on microsite patterns. Growth forms affect wind and snow, and so develop positive and negative feedback loops that create these microsites. As a result, complex landscape patterns are generated at multiple spatial scales. Although these mechanistic processes are fundamentally the same for all forest-tundra ecotones across western North America, factors such as prior climate, underlying geology and geomorphology, and genetic constraints of dominant tree species lead to geographic differences in the responses of particular ecotones to climate change.

Influence of snow patterns and snow avalanches on the alpine treeline ecotone

Snow avalanches, snow accumulation, and snow ablation patterns were mapped and analyzed to assess their impact on the three-dimensional position, composition (closed canopy forest, open canopy forest, meadow, krummholz, and non-vegetated surfaces), and spatial structure of the Alpine Treeline Ecotone (ATE) in a portion of Glacier National Park, Montana, USA. Multitemporal Landsat Multispectral Scanner data were processed to derive snow accumulation and ablation patterns throughout a snow season. Landsat Thematic Mapper data were processed and combined with aerial photo interpre- tations for discerning and characterizing snow avalanche paths. Transition matrices were used to assess the change in the state of snow cover conditions, whereas multiple regression analy- ses were used to examine the position and character of snow avalanche paths. The analyses were framed and implemented within a geographic information system (GIS) approach. Re- sults indicate a snowmelt pattern progressing from zonal to azonal; influence of local site and situation factors in snow accumulation and ablation patterns; and the importance of topography, geologic structure, and lithology in defining the starting elevation and source area of snow avalanche paths. Finally, a conceptual process is presented where sites affected by stresses and disturbances are analyzed at a local spatial scale for analysis through a deterministic model, whereas regional stresses and disturbances are assessed through remote sensing and GIS approaches for analysis through empirical models.

Land use change: complexity and comparisons

Research on the determinants of land use change and its relationship to vulnerability (broadly defined), biotic diversity and ecosystem services (e.g. Gullison et al. 2007), health (e.g. Patz et al. 2004) and climate change (e.g. van der Werf et al. 2004) has accelerated. Evidence of this increased interest is demonstrated by several examples. Funding agencies in the US (National Institutes of Health, National Science Foundation, National Aeronautics and Space Administration and National Oceanic and Atmospheric Administration) and around the world have increased their support of land use science. In addition to research papers in disciplinary journals, there have been numerous edited volumes and special issues of journals recently (e.g. Gutman et al. 2004; Environment & Planning B 2005; Environment & Planning A 2006; Lambin and Geist 2006; Kok, Verburg and Veldkamp 2007). And in 2006, the Journal of Land Use Science was launched. Land use science is now at a crucial juncture in its maturation process. Much has been learned, but the array of factors influencing land use change, the diversity of sites chosen for case studies, and the variety of modeling approaches used by the various case study teams have all combined to make two of the hallmarks of science, generalization and validation, difficult within land use science. This introduction and the four papers in this themed issue grew out of two workshops which were part of a US National Institutes of Health (NIH) ‘Roadmap’ project. The general idea behind the NIH Roadmap initiative was to stimulate scientific advances by bringing together diverse disciplines to tackle a common, multi-disciplinary scientific problem. The specific idea behind our Roadmap project was to bring together seven multi-disciplinary case study teams, working in areas that could be broadly classified as inland frontiers, incorporating social, spatial and biophysical sciences, having temporal depth on both the social and biophysical sides, and having had long-term funding. Early in our Roadmap project, the crucial importance of modeling, particularly agent-based modeling, for the next phase of land-use science became apparent and additional modelers not affiliated with any of the seven case studies were brought into the project. Since agent-based simulations attempt to explicitly capture human behavior and interaction, they were of special interest. At the risk of oversimplification, it is worth briefly reviewing selected key insights in land use science in the past two decades to set the stage for the papers in this themed issue. One of the earliest realizations, and perhaps most fundamental, was accepting the crucial role that humans play in transforming the landscape, and concomitantly the distinction drawn between land cover (which can be seen remotely) and land use (which, in most circumstances, requires in situ observation; e.g. Turner, Meyer and Skole 1994). The complexity of factors influencing land use change became apparent and led to a variety of ‘box and arrow’ diagrams as conceptual frameworks, frequently put together by committees rarely agreeing with one another on all details, but agreeing among themselves that there were many components (social and biophysical) whose role needed to be measured and understood. A series of case studies emerged, recognizing the wide array of variables that needed to be incorporated, and typically doing so by assembling a multidisciplinary team (Liverman, Moran, Rindfuss and Stern 1998; Entwisle and Stern 2005). The disciplinary make-up of the team strongly influenced what was measured and how it was measured (see Rindfuss, Walsh, Turner, Fox and Mishra 2004; Overmars and Verburg 2005), with limited, if any, coordination across case studies (see Moran and Ostrom 2005 for an exception). In large part, the focus on case studies reflected the infancy of theory in land use science. Teams combined their own theoretical knowledge of social, spatial and ecological change with an inductive approach to understanding land use change – starting from a kitchen sink of variables and an in-depth knowledge of the site to generate theory on the interrelationships between variables and the importance of contextual effects. This lack of coordination in methods, documentation and theory made it very difficult to conduct meta-analyses of the driving factors of land use change across all the case studies to identify common patterns and processes (Geist and Lambin 2002; Keys and McConnell 2005). Recognizing that important causative factors were affecting the entire site of a case study (such as a new road which opens an entire area) and that experimentation was not feasible, computational, statistical and spatially explicit modeling emerged as powerful tools to understand the forces of land use change at a host of space–time scales (Veldkamp and Lambin 2001; Parker, Manson, Janssen, Hoffmann, and Deadman 2003; Verburg, Schot, Dijst and Veldkamp 2004). Increasingly, in recognition of the crucial role of humans in land use change, modeling approaches that represent those actors as agents have emerged as an important, and perhaps the dominant, modeling approach at local levels (Matthews, Gilbert, Roach, Polhil and Gotts 2007). In this introductory paper we briefly discuss some of the major themes that emerged in the workshops that brought together scientists from anthropology, botany, demography, developmental studies, ecology, economics, environmental science, geography, history, hydrology, meteorology, remote sensing, geographic information science, resource management, and sociology. A central theme was the need to measure and model behavior and interactions among actors, as well as between actors and the environment. Many early agent-based models focused on representing individuals and households (e.g. Deadman 1999), but the importance of other types of actors (e.g. governmental units at various levels, businesses, and NGOs) was a persistent theme. ‘Complexity’ was a term that peppered the conversation, and it was used with multiple meanings. But the dominant topic to emerge was comparison and generalization: with multiple case studies and agent-based models blooming, how do we compare across them and move towards generalization? We return to the generalization issue at the end of this introductory paper after a brief discussion of the other themes.

Soy proteins and isoflavones affect bone mineral density in older women: a randomized controlled trial

BACKGROUND Soy foods contain several components (isoflavones and amino acids) that potentially affect bone. Few long-term, large clinical trials of soy as a means of improving bone mineral density (BMD) in late postmenopausal women have been conducted. OBJECTIVE Our goal was to evaluate the long-term effect of dietary soy protein and/or soy isoflavone consumption on skeletal health in late postmenopausal women. DESIGN We conducted a randomized, double-blind, placebo-controlled clinical trial in 131 healthy ambulatory women aged >60 y. Ninety-seven women completed the trial. After a 1-mo baseline period, subjects were randomly assigned into 1 of 4 intervention groups: soy protein (18 g) + isoflavone tablets (105 mg isoflavone aglycone equivalents), soy protein + placebo tablets, control protein + isoflavone tablets, and control protein + placebo tablets. RESULTS Consumption of protein powder and isoflavone pills did not differ between groups, and compliance with the study powder and pills was 80-90%. No significant differences in BMD were observed between groups from baseline to 1 y after the intervention or in BMD change between equol and non-equol producers. However, there were significant negative correlations between total dietary protein (per kg) and markers of bone turnover (P < 0.05). CONCLUSIONS Because soy protein and isoflavones (either alone or together) did not affect BMD, they should not be considered as effective interventions for preserving skeletal health in older women. The negative correlation between dietary protein and bone turnover suggests that increasing protein intakes may suppress skeletal turnover. This trial was registered at ClinicalTrials.gov as NCT00668447.

Functional Impact of Relative Versus Absolute Sarcopenia in Healthy Older Women

OBJECTIVES: To determine whether adjustment of muscle mass for height2 or for body mass represents a more‐relevant predictor of physical performance.

Measurement of muscle disease by quantitative second-harmonic generation imaging.

Determining the health of muscle cells by in vivo imaging could impact the diagnosis and monitoring of a large number of congenital and acquired muscular or cardiac disorders. However, currently used technologies are hampered by insufficient resolution, lack of specificity, or invasiveness. We have combined intrinsic optical second-harmonic generation from sarcomeric myosin with a novel mathematical treatment of striation pattern analysis, to obtain measures of muscle contractile integrity that correlate strongly with the neuromuscular health of mice suffering from genetic, acquired, and age-related decline in skeletal muscle function. Analysis of biopsies from a pilot group of human volunteers suggests a similar power in quantifying sarcopenic changes in muscle integrity. These results provide the first strong evidence that quantitative image analysis of sarcomere pattern can be correlated with physiological function, and they invite the application of SHG imaging in clinical practice, either in biopsy samples or via microendoscopy.