Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

The Getting-Out-of-Bed (GoB) scale: a measure of motivation and life outlook in older adults with cancer

OBJECTIVE: To develop and evaluate the psychometric properties of a measure of motivation and life outlook (Getting-Out-of-Bed [GoB]). DESIGN: Secondary analysis of baseline and 6-month data from a longitudinal follow-up study of older breast cancer survivors. PARTICIPANTS: Women (N = 660) diagnosed with primary breast cancer stage I-IIIA disease, age >or=65 years, and permission to contact from an attending physician in four geographic regions in the United States (city-based Los Angeles, California; statewide in Minnesota, North Carolina, and Rhode Island). MEASUREMENT: Data were collected over 6-months of follow-up from consenting patients' medical records and telephone interviews with patients. Data collected included the 4-item GoB, health-related quality of life (HRQoL), breast cancer, sociodemographic, and health-related characteristics. RESULTS: Factor analysis produced, as hypothesized, one principal component with eigen values of 2.74(baseline) and 2.91(6-months) which explained 68.6%(baseline) and 72.7%(6-months) of total variance. In further psychometric analyses, GoB exhibited good construct validity (divergent: low nonstatistically significant correlations with unrelated constructs; convergent: moderate statistically significant correlations with related constructs; discriminant: distinguished high HRQoL groups with a high level of significance), excellent internal reliability (Cronbach's alpha 0.84(baseline), 0.87(6-months)), and produced stable measurements over 6-months. Women with GoB scores >or=50 at baseline were more likely at 6-months to have good HRQoL, good self-perceived health, and report regular exercise, indicating good predictive ability. CONCLUSION: GoB demonstrated overall good psychometric properties in this sample of older breast cancer survivors, suggestive of a promising tool for assessing motivation and life outlook in older adults. Nevertheless, because it was developed and initially evaluated in a select sample, using measures with similar but not exact content overlap further evaluation is needed before it can be recommended for widespread use.

Towards a spatial understanding of trade-offs in sustainable development: A meso-scale analysis of the nexus between land use, poverty, and environment in the Lao PDR

In land systems, equitably managing trade-offs between planetary boundaries and human development needs represents a grand challenge in sustainability oriented initiatives. Informing such initiatives requires knowledge about the nexus between land use, poverty, and environment. This paper presents results from Lao PDR, where we combined nationwide spatial data on land use types and the environmental state of landscapes with village-level poverty indicators. Our analysis reveals two general but contrasting trends. First, landscapes with paddy or permanent agriculture allow a greater number of people to live in less poverty but come at the price of a decrease in natural vegetation cover. Second, people practising extensive swidden agriculture and living in intact environments are often better off than people in degraded paddy or permanent agriculture. As poverty rates within different landscape types vary more than between landscape types, we cannot stipulate a land use–poverty–environment nexus. However, the distinct spatial patterns or configurations of these rates point to other important factors at play. Drawing on ethnicity as a proximate factor for endogenous development potentials and accessibility as a proximate factor for external influences, we further explore these linkages. Ethnicity is strongly related to poverty in all land use types almost independently of accessibility, implying that social distance outweighs geographic or physical distance. In turn, accessibility, almost a precondition for poverty alleviation, is mainly beneficial to ethnic majority groups and people living in paddy or permanent agriculture. These groups are able to translate improved accessibility into poverty alleviation. Our results show that the concurrence of external influences with local—highly contextual—development potentials is key to shaping outcomes of the land use–poverty–environment nexus. By addressing such leverage points, these findings help guide more effective development interventions. At the same time, they point to the need in land change science to better integrate the understanding of place-based land indicators with process-based drivers of land use change.

Export-Led Growth and Geographic Distribution of the Poultry Meat Industry in Brazil

This paper includes an examination of the sustainability of recent high growth in the poultry meat industry in Brazil. In addition, an assessment is made of the impact of increased production of poultry meat products on the development of local industries. Comparative studies of leading companies in the United States, Mexico, and Brazil reveal competitive advantages in the low costs of feedstuff and labor as well as disadvantages in the scale of business and management efficiency in the Brazilian poultry sector. Increases in domestic and foreign demand for Brazilian poultry meat have promoted development of the Brazilian poultry sector in local areas. The formation of industrial clusters is observed using regional data related to the location of slaughterhouses and the number of chickens farmed. Statistical analyses support observations made in this paper.

E-Book Usage on a Global Scale: Patterns, Trends, and Opportunities

This study examines worldwide usage of over 600,000 e-books from Ebook Library (EBL) and ebrary. Using multiple modes of analysis, the study shows that there are variations in usage by geographic region as well as by subject. The study examines usage in relation to availability of titles, different types of usage per session, usage of the top ten percent of titles, and intensive and extensive use. These patterns can be used for benchmarking and as a model for local e-book studies.

Population differentiation in the banana leaf spot pathogen Mycosphaerella musicola, examined at a global scale

Single-copy restriction fragment length polymorphism (RFLP) markers were used to determine the genetic structure of the global population of Mycosphaerella musicola, the cause of Sigatoka (yellow Sigatoka) disease of banana. The isolates of M. musicola examined were grouped into four geographic populations representing Africa, Latin America and the Caribbean, Australia and Indonesia. Moderate levels of genetic diversity were observed for most of the populations (H = 0.22-0.44). The greatest genetic diversity was found in the Indonesian population (H = 0.44). Genotypic diversity was close to 50% in all populations. Population differentiation tests showed that the geographic populations of Africa, Latin America and the Caribbean, Australia and Indonesia were genetically different populations. Using F-ST tests, very high levels of genetic differentiation were detected between all the population pairs (F-ST > 0.40), with the exception of the Africa and Latin America-Caribbean population pair. These two populations differed by only 3% (F-ST = 0.03), and were significantly different (P < 0.05) from all other population pairs. The high level of genetic diversity detected in Indonesia in comparison to the other populations provides some support for the theory that M. musicola originated in South-east Asia and that M. musicola populations in other regions were founded by isolates from the South-east Asian region. The results also suggest the migration of M. musicola between Africa and the Latin America-Caribbean region.

The genetic structure of Australian populations of Mycosphaerella musicola suggests restricted gene flow at the continental scale

Mycosphaerello musicolo causes Sigatoka disease of banana and is endemic to Australia. The population genetic structure of M. musicola in Australia was examined by applying single-copy restriction fragment length polymorphism probes to hierarchically sampled populations collected along the Australian cast coast. The 363 isolates studied were from 16 plantations at 12 sites in four different regions, and comprised 11 populations. These populations displayed moderate levels of gene diversity (H = 0.142 to 0.369) and similar levels of genotypic richness and evenness. Populations were dominated by unique genotypes, but isolates sharing the same genotype (putative clones) were detected. Genotype distribution was highly localized within each population, and the majority of putative clones were detected for isolates sampled from different sporodochia in the same lesion or different lesions on a plant. Multilocus gametic disequilibrium tests provided further evidence of a degree of clonality within the populations at the plant scale. A complex pattern of population differentiation was detected for M. musicola in Australia. Populations sampled from plantations outside the two major production areas were genetically very different to all other populations. Differentiation was much lower between populations of the two major production areas, despite their geographic separation of over 1,000 km. These results suggest low gene flow at the continental scale due to limited spore dispersal and the movement of infected plant material.

Coding together at scale:GitHub as a collaborative social network

GitHub is the most popular repository for open source code (Finley 2011). It has more than 3.5 million users, as the company declared in April 2013, and more than 10 million repositories, as of December 2013. It has a publicly accessible API and, since March 2012, it also publishes a stream of all the events occurring on public projects. Interactions among GitHub users are of a complex nature and take place in different forms. Developers create and fork repositories, push code, approve code pushed by others, bookmark their favorite projects and follow other developers to keep track of their activities. In this paper we present a characterization of GitHub, as both a social network and a collaborative platform. To the best of our knowledge, this is the first quantitative study about the interactions happening on GitHub. We analyze the logs from the service over 18 months (between March 11, 2012 and September 11, 2013), describing 183.54 million events and we obtain information about 2.19 million users and 5.68 million repositories, both growing linearly in time. We show that the distributions of the number of contributors per project, watchers per project and followers per user show a power-law-like shape. We analyze social ties and repository-mediated collaboration patterns, and we observe a remarkably low level of reciprocity of the social connections. We also measure the activity of each user in terms of authored events and we observe that very active users do not necessarily have a large number of followers. Finally, we provide a geographic characterization of the centers of activity and we investigate how distance influences collaboration.

Social construction of Geographic Information Systems. (Volumes I and II)

Geographic Information Systems (GIS) is an emerging information technology (IT) which promises to have large scale influences in how spatially distributed resources are managed. It has had applications in the management of issues as diverse as recovering from the disaster of Hurricane Andrew to aiding military operations in Desert Storm. Implementation of GIS systems is an important issue because there are high cost and time involvement in setting them up. An important component of the implementation problem is the "meaning" different groups of people who are influencing the implementation give to the technology. The research was based on the theory of (theoretical stance to the problem was based on the) "Social Construction of Knowledge" systems which assumes knowledge systems are subject to sociological analysis both in usage and in content. An interpretive research approach was adopted to inductively derive a model which explains how the "meanings" of a GIS are socially constructed. The research design entailed a comparative case analysis over two county sites which were using the same GIS for a variety of purposes. A total of 75 in-depth interviews were conducted to elicit interpretations of GIS. Results indicate that differences in how geographers and data-processors view the technology lead to different implementation patterns in the two sites.

Analysis of fractured terrain using remote sensing and geographic information systems : establishing a correlation between fracture network properties and vegetation

This research analyzed the spatial relationship between a mega-scale fracture network and the occurrence of vegetation in an arid region. High-resolution aerial photographs of Arches National Park, Utah were used for digital image processing. Four sets of large-scale joints were digitized from the rectified color photograph in order to characterize the geospatial properties of the fracture network with the aid of a Geographic Information System. An unsupervised landcover classification was carried out to identify the spatial distribution of vegetation on the fractured outcrop. Results of this study confirm that the WNW-ESE alignment of vegetation is dominantly controlled by the spatial distribution of the systematic joint set, which in turn parallels the regional fold axis. This research provides insight into the spatial heterogeneity inherent to fracture networks, as well as the effects of jointing on the distribution of surface vegetation in desert environments.

UTILIZATION OF GIS AND SPATIAL ANALYSIS TECHNIQUES IN ARTISANAL AND SMALL SCALE MINING TO LOCATE A CENTRALIZED PROCESSING CENTRE

One of the global phenomena with threats to environmental health and safety is artisanal mining. There are ambiguities in the manner in which an ore-processing facility operates which hinders the mining capacity of these miners in Ghana. These problems are reviewed on the basis of current socio-economic, health and safety, environmental, and use of rudimentary technologies which limits fair-trade deals to miners. This research sought to use an established data-driven, geographic information (GIS)-based system employing the spatial analysis approach for locating a centralized processing facility within the Wassa Amenfi-Prestea Mining Area (WAPMA) in the Western region of Ghana. A spatial analysis technique that utilizes ModelBuilder within the ArcGIS geoprocessing environment through suitability modeling will systematically and simultaneously analyze a geographical dataset of selected criteria. The spatial overlay analysis methodology and the multi-criteria decision analysis approach were selected to identify the most preferred locations to site a processing facility. For an optimal site selection, seven major criteria including proximity to settlements, water resources, artisanal mining sites, roads, railways, tectonic zones, and slopes were considered to establish a suitable location for a processing facility. Site characterizations and environmental considerations, incorporating identified constraints such as proximity to large scale mines, forest reserves and state lands to site an appropriate position were selected. The analysis was limited to criteria that were selected and relevant to the area under investigation. Saaty’s analytical hierarchy process was utilized to derive relative importance weights of the criteria and then a weighted linear combination technique was applied to combine the factors for determination of the degree of potential site suitability. The final map output indicates estimated potential sites identified for the establishment of a facility centre. The results obtained provide intuitive areas suitable for consideration

Two “pillars” of cold-water coral reefs along Atlantic European margins: Prevalent association of Madrepora oculata with Lophelia pertusa, from reef to colony scale

The scleractinian coral Lophelia pertusa has been the focus of deep-sea research since the recognition of the vast extent of coral reefs in North Atlantic waters two decades ago, long after their existence was mentioned by fishermen. These reefs where shown to provide habitat, concentrate biomass and act as feeding or nursery grounds for many species, including those targeted by commercial fisheries. Thus, the attention given to this cold-water coral (CWC) species from researchers and the wider public has increased. Consequently, new research programs triggered research to determine the full extent of the corals geographic distribution and ecological dynamics of “Lophelia reefs”. The present study is based on a systematic standardised sampling design to analyse the distribution and coverage of CWC reefs along European margins from the Bay of Biscay to Iceland. Based on Remotely Operated Vehicle (ROV) image analysis, we report an almost systematic occurrence of Madrepora oculata in association with L. pertusa with similar abundances of both species within explored reefs, despite a tendency of increased abundance of L. pertusa compared to M. oculata toward higher latitudes. This systematic association occasionally reached the colony scale, with “twin” colonies of both species often observed growing next to each other when isolated structures were occurring off-reefs. Finally, several “false chimaera” were observed within reefs, confirming that colonial structures can be “coral bushes” formed by an accumulation of multiple colonies even at the inter-specific scale, with no need for self-recognition mechanisms. Thus, we underline the importance of the hitherto underexplored M. oculata in the Eastern Atlantic, re-establishing a more balanced view that both species and their yet unknown interactions are required to better elucidate the ecology, dynamics and fate of European CWC reefs in a changing environment.

Social relations and dynamics shaping the implementation of the voluntary guidelines on small-scale fisheries (SSF guidelines) in South Africa

Integral to achieving the SSF Guidelines goal of targeting the most vulnerable and marginalized persons and eliminating discrimination is the need to have adequate understanding of the power relations and intersectionalities that shape access to and control over marine and other resources according to gender, age, race, ethnicity, labour and migratory status, disability, geographic location and other characteristics relevant in each national contexts. This monograph identifies and explores the key social relations and dynamics in the SSF fisheries sector in South Africa impacting the implementation of the SSF Guidelines. The monograph will be useful for researchers, scientists, fishworker organizations, environmentalists and anyone interested in the protection of marine biodiversity and the promotion of sustainable fisheries management.

Digital revision of USGS 1:500,000-scale New Jersey state base map /

Shows stages and operations undertaken in revising the New Jersey state base map.

Sensitivity of fine-scale species distribution models to locational uncertainty in occurrence data across multiple sample sizes

To generate realistic predictions, species distribution models require the accurate coregistration of occurrence data with environmental variables. There is a common assumption that species occurrence data are accurately georeferenced; however, this is often not the case. This study investigates whether locational uncertainty and sample size affect the performance and interpretation of fine-scale species distribution models. This study evaluated the effects of locational uncertainty across multiple sample sizes by subsampling and spatially degrading occurrence data. Distribution models were constructed for kelp (Ecklonia radiata), across a large study site (680 km2) off the coast of southeastern Australia. Generalized additive models were used to predict distributions based on fine-resolution (2·5 m cell size) seafloor variables, generated from multibeam echosounder data sets, and occurrence data from underwater towed video. The effects of different levels of locational uncertainty in combination with sample size were evaluated by comparing model performance and predicted distributions. While locational uncertainty was observed to influence some measures of model performance, in general this was small and varied based on the accuracy metric used. However, simulated locational uncertainty caused changes in variable importance and predicted distributions at fine scales, potentially influencing model interpretation. This was most evident with small sample sizes. Results suggested that seemingly high-performing, fine-scale models can be generated from data containing locational uncertainty, although interpreting their predictions can be misleading if the predictions are interpreted at scales similar to the spatial errors. This study demonstrated the need to consider predictions across geographic space rather than performance alone. The findings are important for conservation managers as they highlight the inherent variation in predictions between equally performing distribution models, and the subsequent restrictions on ecological interpretations.