A case study in catchment hydrochemistry: Conflicting interpretations from hydrological and chemical observations

Soil water, stream water, groundwater and rain water were sampled through a storm event in a moorland catchment. Samples were analysed for major ions and deuterium. Chloride and deuterium are used as tracers to enable separation of the stream runoff hydrograph into three components: rain, soil and groundwater. The results indicate that rain water arrives in the stream quickly during the event and contributes a significant volume to the runoff peak. The chemical signal in the rain water is, however, significantly damped, apparently due to mixing with soil water held in the catchment before the event. This is further modified before reaching the stream, apparently through mixing with a deeper groundwater component. Interpretation of tracer, chemistry and hydrological data to present an integrated picture of catchment hydrochemical response is difficult due to problems in the chemical and conceptual definition of the flow components.     

UBVRIJH photometry of two new luminous δ Scuti stars and the discovery of δ Scuti pulsation in the most evolved Ap star known

Time-series photometry of the Hipparcos variable stars HD 199434 and 21190 is reported. Both stars are pulsators of the δ Scuti type. Reclassifications of the MK types of the stars, based on new spectrograms, are given. HD 21190 is found to be F2III SrEuSi:, making it the most evolved Ap star known. Its Strömgren photometric indices support the peculiar spectral type. It is also one of the most evolved δ Scuti stars known. Its combined Ap– δ Scuti nature makes it an important test of models of pulsation in peculiar stars recently developed by Turcotte et al., although it is more extreme than any model they examined. Physical parameters of both stars are estimated from Strömgren and H β photometry, and Hipparcos absolute magnitudes. We attempt mode identifications based on amplitude ratios and phase differences from our photometry. The dominant pulsation of HD 21190 may be an overtone radial mode. The model fits for HD 199434 are even less satisfactory, but favour an ℓ=2 mode. Given the good quality and wavelength coverage of our data, the poor results from the application of the photometric theory of mode identification may call into question the use of that technique.     

Environmental Influences on Faecal Indicator Organisms in Coastal Waters and Their Accumulation in Bivalve Shellfish

Shellfish production areas are often located in shallow estuarine and coastal systems impacted by fluxes of faecal indicator organisms (FIOs) that exhibit extreme spatial and temporal variability. FIO abundance and distribution in the marine environment are determined by the combined effects of light intensity, water mixing, sewage content and suspended particulate matter. Favourable conditions for FIO survival are low solar radiation, low temperature, low salinity, low densities of micro-predators and high levels of organic matter. Rainfall is the parameter most commonly associated with peak levels of FIOs. Resuspension of contaminated sediments in the water column dominates FIO distribution in shallow and depositional estuaries during storm conditions. Water/flesh FIO ratios may differ between shellfish growing waters because salinities and water temperatures also influence filter-feeding activity. Data are lacking on the role of biological processes on FIOs uptake and clearance in shellfish, particularly during periods of good water quality. FIO accumulation is usually of higher magnitude in mussels and cockles than in oysters and surf clams. It is proposed that differences in FIO accumulation rates are associated with the biological activity and the position of shellfish in the water column in relation to the location of impacting pollution sources. Accurate information on catchment hydrology, land uses, FIO loads from sewerage-related sources and livestock production areas are required to adequately characterise the microbiological status of shellfisheries.     

Making our neighborhoods,making our selves

In this paper, we explore a “grassroots” neighborhood revitalization effort engendered at the national scale without regard to local geographies of race and class. Specifically, we examine the Harambee Great Neighborhood Initiative, convened by the well-known nonprofit Habitat for Humanity together with Milwaukee’s Local Initiatives Support Corporation, in Milwaukee, Wisconsin. Drawing from participant observation, analysis of print and digital media, volunteer surveys, and interviews with area residents and local nonprofit representatives, we demonstrate the ways in which the six-year program of planning and neighborhood development was conceived and driven by an extra-local nonprofit with significant blind spots to local and organizational politics of race and without sufficient collaboration with the Harambee community. Our analysis points to the importance of race in nonprofit governance and community revitalization efforts. Moreover, we contribute to urban geographic scholarship on nonprofit governance by examining the dynamics of privilege, inclusion, and exclusion as they relate to practices of engagement and volunteerism in nonlocal “grassroots” projects.     

Multiscale Segregation: Multilevel Modeling of Dissimilarity—Challenging the Stylized Fact That Segregation Is Greater the Finer the Spatial Scale

A very large literature has explored the intensity of urban residential segregation using the index of dissimilarity. Several recent studies have undertaken such analyses at multiple spatial scales, invariably reaching the conclusion that the finer grained the spatial scale, the greater the segregation. Such findings, however, overstate the intensity of segregation at finer spatial scales because they fail to take into account an argument made by Duncan et al. some sixty years ago that indexes derived from fine-scale analyses must necessarily incorporate those from coarser scales, with the consequence that finer scale segregation is invariably overestimated. Moreover, most studies ignore stochastic variation that results in upward bias in the estimates of segregation. This article demonstrates the importance of a recently developed multilevel modeling procedure that identifies the “true” intensity of segregation at every level in a spatial hierarchy net of its intensity at other levels and also net of stochastic variation This is illustrated by both a simulated data set and an empirical study of an English city, with the latter raising important substantive issues regarding the interpretation of segregation patterns and the processes underlying them. Key Words: dissimilarity, multilevel modeling, scale, segregation.