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Contrary to popular belief, the roots of American country music do not lie solely on southern farms or in mountain hollows. Rather, much of this music recorded before World War II emerged from the bustling cities and towns of the Piedmont South. No group contributed more to the commercialization of early country music than southern factory workers. InLinthead Stomp, Patrick Huber explores the origins and development of this music in the Piedmont's mill villages.Huber offers vivid portraits of a colorful cast of Piedmont millhand musicians, including Fiddlin' John Carson, Charlie Poole, Dave McCarn, and the Dixon Brothers, and considers the impact that urban living, industrial work, and mass culture had on their lives and music. Drawing on a broad range of sources, including rare 78-rpm recordings and unpublished interviews, Huber reveals how the country music recorded between 1922 and 1942 was just as modern as the jazz music of the same era.Linthead Stompcelebrates the Piedmont millhand fiddlers, guitarists, and banjo pickers who combined the collective memories of the rural countryside with the upheavals of urban-industrial life to create a distinctive American music that spoke to the changing realities of the twentieth-century South.

\"Moving from the Italian Piedmont to the Maremma and then to Le Marche, chef Teresa Lust interweaves portraits of the people who served as her culinary guides with cultural and natural history in this charming exploration of authentic Italian cuisine. We learn how to prepare bagna cauda--a robust dipping sauce of anchovies, garlic, and olive oil--with Lust's relatives outside Torino. We learn about making hand-stretched grissini, Italy's iconic breadstick, the secrets of whipping up zabaione, a classic dessert of ethereal foam made with egg yolks, sugar, and marsala. Then there is acquacotta, a rustic soup that nourished generations of the area's shepherds and cowhands. In the town of Camerano, an eighty-year-old woman reveals the art of hand-rolling pasta with a three-foot rolling pin. Underpinning Lust's travels is our journey from chef to cook, mirroring the fact that Italians have been masters of home cooking for generations, so they are an obvious source of inspiration. Today, more and more people are rediscovering the pleasures of cooking at home, and Lust's account--and wonderful recipes--will help readers bring an Italian sensibility to their home tables.\"--Amazon.com.

This book provides a new conceptual framework for understanding how the Indian nations of the early American South emerged from the ruins of a precolonial, Mississippian world. A broad regional synthesis that ranges over much of the Eastern Woodlands, its focus is on the Indians of the Carolina Piedmont - the Catawbas and their neighbors - from 1400 to 1725. Using an 'eventful' approach to social change, Robin Beck argues that the collapse of the Mississippian world was fundamentally a transformation of political economy, from one built on maize to one of guns, slaves and hides. The story takes us from first encounters through the rise of the Indian slave trade and the scourge of disease to the wars that shook the American South in the early 1700s. Yet the book's focus remains on the Catawbas, drawing on their experiences in a violent, unstable landscape to develop a comparative perspective on structural continuity and change.

The Shanxi Graben System exhibits high seismic activity and significant destructive potential. Previous studies in this region have primarily focused on geological methods such as seismology, geological surveys, and trench excavations, with limited research in the field of geophysics. In this study, we collected two magnetotelluric profiles crossing the central segment of the Shanxi Graben System, including the fault system and the Hongdong–Linfen seismic zone. Through qualitative analysis and inversion calculations, we constructed a three-dimensional electrical model of the study area. The seismogenic environment was studied by integrating the deformation field, recent seismic geological data, and geophysical survey results of the study area and its surroundings. The Luoyunshan Piedmont Fault and the Huoshan Piedmont Fault are likely two main faults in the central segment of the Shanxi Graben System. These faults span the entire crustal scale and serve as basement faults separating the Ordos Block and the Taihangshan Block. They exhibit patterns of activity. The western side of the Shanxi Graben System, represented by the Ordos Block, exhibits a stable tectonic environment, while the eastern side, represented by the Taihangshan Block, experiences severe lithospheric destruction and thinning. The results of the magnetotelluric (MT) survey support the 1303 Hongdong earthquake as an event that occurred on the Huoshan Piedmont Fault and provide geophysical evidence for the possible dominance of the Luoyunshan Piedmont Fault in the 1695 Linfen earthquake. Multiple factors controlled the seismogenic environments of these two earthquakes. The continuous upwelling of asthenospheric material in the lower-middle crust on the eastern side of the Linfen Basin possibly leads to the regional extension of the North China Block. This, in turn, triggers inclined sliding along the Huoshan Piedmont Fault and the Luoyunshan Piedmont Fault, which may be the main controlling factors for major earthquakes in the region.

Conservation agricultural systems have a long history of development and use in the southeastern United States, but they are still not the norm on the landscape. Literature from the region suggests that a diversity of soil properties can be improved with cover cropping and conservation tillage, but results are not always consistent. Our objectives were to (a) review recent research on conservation tillage and cover cropping in the region and (b) compile and synthesize recent data from a diversity of farms along a conventional to conservation gradient. As part of recent on‐farm trials focused on soil N availability, we analyzed soil organic C and N fractions and routine soil nutrient characteristics from a total of 196 fields in corn (Zea mays L.), wheat (Triticum aestivum L.), and barley (Hordeum vulgare L.) production in three physiographic regions of the Coastal Plain (n = 71 fields), Piedmont (n = 77 fields), and Appalachians (n = 48 fields) in North Carolina, South Carolina, Pennsylvania, and Virginia. These data allowed us to establish first estimates of threshold optima for soil organic C and N fractions and other inorganic nutrients. On‐farm data confirmed the literature review that conservation tillage resulted in greater stratification of soil organic C and N and nutrient concentrations. Soil health improvement could be inferred along the gradient from inversion tillage to no tillage without cover cropping to no tillage with cover cropping. This collection of recent literature and on‐farm data can be a useful starting point for establishing target limits and assessing soil health conditions on farms in the region. Core Ideas There was significant improvement in soil organic C and N and inorganic nutrients with no‐till and covers. Soil health improved with adoption of no‐till compared with inversion tillage. There was weak evidence for soil health improvement with multi‐species covers compared to single species. Soil‐test biological activity and net N mineralization are effective indicators of soil health.

In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling.

The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species’ cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01–900 m². Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15–70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly, bivariate tests provide evidence of scale-dependence among predictors, such that remotely-sensed variables significantly predict plant richness only at spatial scales that sufficiently subsume geolocational imprecision between remotely-sensed and field data, and best align with stand components including plant size and density, as well as canopy gaps and understory growth patterns. Beyond their insights into the scale-dependent patterns and drivers of plant diversity in Piedmont forests, these results highlight the potential of remotely-sensible essential biodiversity variables for mapping and monitoring landscape floristic diversity from air- and space-borne platforms.

The Regional Plan of Mining Activities (PRAE), adopted in December 2022, represents the strategic regulation instrument pursuing the balance between environmental sustainability and economic development produced by mining activity at a regional scale. The paper proposes an overview of the main regional in-force instrument for surface and ground-water planning and management (PAI and PTA) and how these intersect with the introduced PRAE. Besides, the interaction between mining activities and the geomorphological and hydrogeological contexts in which they are located is described, defining the resulting constraints regarding their interaction with extraction areas. A significant portion of the quarries are located in the floodplain, falling both in river bands of medium–high probability of flooding and in areas involving aquifers bodies, hence these extractive sites are heavily restricted both in terms of excavation depths, never exceeding the base of the surface aquifer. The depth of the water table and the base of the aquifer represent the two fundamental parameters on which new restrictions have been defined in the PRAE in terms of the possibility of developing new quarry areas.

Questions: Can forest structure significantly predict tree species diversity in the forests of the North Carolina Piedmont? If so, which structural attributes are most correlated with it, and how effective are they when used in concert in a generalized predictive model of tree species diversity? Location: North Carolina Piedmont, USA. Methods: Using a set of geographically distributed Forest inventory and analysis (FIA) plots (n = 972), we analysed Spearman correlations between 15 measures of forest structure and five indices of tree species diversity. We predict tree species diversity based on structural predictors using support vector regression (SVR) models, assessing model fit via ten-fold cross-validation. Results: Results show a consistent and significant relationship between most structural attributes and indices of tree species diversity. Among all structural predictors, maximum height, basal area size inequality (basal area Gini coefficient) and skewness of the basal area distribution (Weibull shape) exhibited the strongest correlations with indices of tree species diversity. Predictive SVR models trained solely with structural attributes explained of the variance in tree species diversity in the full Piedmont data set, and 22-71% of the variance in subsets defined by stand origin and forest type. Conclusions: Results confirm that forest structure alone was able to predict a substantial portion of the variance in tree species diversity without accounting for other known predictors of diversity in the North Carolina Piedmont, such as environment, soil conditions and site history. Beyond the theoretical implications of unravelling primary patterns underlying tree species diversity, these findings highlight the empirical basis and potential for utilizing forest structure in predictive models of tree species diversity over large geographic regions.