A simple relationship between volcanic sulfate aerosol optical depth and surface temperature change simulated in an atmosphere-ocean general circulation model.

In this study we quantify the relationship between the aerosol optical depth increase from a volcanic eruption and the severity of the subsequent surface temperature decrease. This investigation is made by simulating 10 different sizes of eruption in a global circulation model (GCM) by changing stratospheric sulfate aerosol optical depth at each time step. The sizes of the simulated eruptions range from Pinatubo‐sized up to the magnitude of supervolcanic eruptions around 100 times the size of Pinatubo. From these simulations we find that there is a smooth monotonic relationship between the global mean maximum aerosol optical depth anomaly and the global mean temperature anomaly and we derive a simple mathematical expression which fits this relationship well. We also construct similar relationships between global mean aerosol optical depth and the temperature anomaly at every individual model grid box to produce global maps of best‐fit coefficients and fit residuals. These maps are used with caution to find the eruption size at which a local temperature anomaly is clearly distinct from the local natural variability and to approximate the temperature anomalies which the model may simulate following a Tambora‐sized eruption. To our knowledge, this is the first study which quantifies the relationship between aerosol optical depth and resulting temperature anomalies in a simple way, using the wealth of data that is available from GCM simulations.

Daily thin-ice thickness maps from modis thermal infrared imagery

Accurate knowledge of ice-production rates within the marginal ice zones of the Arctic Ocean requires monitoring of the thin-ice distribution within polynyas. The thickness of the ice layer controls the heat loss and hence the new-ice formation. An established thinice algorithm using high-resolution MODIS data allows deriving the ice-thickness distribution within polynyas. The average uncertainty is ±4.7 cm for ice thicknesses below 0.2 m. In this study, the ice-thickness distributions within the Laptev Sea polynya for the two winter seasons 2007/08 and 2008/09 are calculated. Then, a new method is applied to determine a daily MODIS thin-ice product.

A VEGETATION RECONSTRUCTION OF UNION COUNTY, PENNSYLVANIA DURING THE EARLY HISTORICAL PERIOD (1755-1855)

This thesis assesses relationships between vegetation and topography and the impact of human tree-cutting on the vegetation of Union County during the early historical era (1755-1855). I use early warrant maps and forestry maps from the Pennsylvania historical archives and a warrantee map from the Union County courthouse depicting the distribution of witness trees and non-tree surveyed markers (posts and stones) in early European settlement land surveys to reconstruct the vegetation and compare vegetation by broad scale (mountains and valleys) and local scale (topographic classes with mountains and valleys) topography. I calculated marker density based on 2 km x 2 km grid cells to assess tree-cutting impacts. Valleys were mostly forests dominated by white oak (Quercus alba) with abundant hickory (Carya spp.), pine (Pinus spp.), and black oak (Quercus velutina), while pine dominated what were mostly pine-oak forests in the mountains. Within the valleys, pine was strongly associated with hilltops, eastern hemlock (Tsuga canadensis) was abundant on north slopes, hickory was associated with south slopes, and riparian zones had high frequencies of ash (Fraxinus spp.) and hickory. In the mountains, white oak was infrequent on south slopes, chestnut (Castanea dentata) was more abundant on south slopes and ridgetops than north slopes and mountain coves, and white oak and maple (Acer spp.) were common in riparian zones. Marker density analysis suggests that trees were still common over most of the landscape by 1855. The findings suggest there were large differences in vegetation between valleys and mountains due in part to differences in elevation, and vegetation differed more by topographic classes in the valleys than in the mountains. Possible areas of tree-cutting were evenly distributed by topographic classes, suggesting Europeans settlers were clearing land and harvesting timber in most areas of Union County.

Socio-economic atlas of Kenya: Depicting the national population census by county and sub-location

The Socio-Economic Atlas of Kenya is the first of its kind to offer high-resolution spatial depictions and analyses of data collected in the 2009 Kenya Population and Housing Census . The combination of geographic and socio-eco - nomic data enables policymakers at all levels, development experts, and other interested readers to gain a spatial understanding of dynamics affecting Kenya. Where is the informal economic sector most prominent? Which areas have adequate water and sanitation? Where is population growth being slowed effectively? How do education levels vary throughout the country? And where are poverty rates lowest? Answers to questions such as these, grouped into seven broad themes, are visually illustrated on high-resolution maps. By supplying precise information at the sub-location level and summarizing it at the county level, the atlas facilitates better planning that accounts for local contexts and needs. It is a valuable decision-support tool for government institutions at different administrative levels, educational institutions, and others. Three organizations – two in Kenya and one in Switzerland – worked together to create the atlas: the Kenya National Bureau of Statistics (KNBS), the Nanyuki-based Centre for Training and Integrated Research in ASAL Development (CETRAD), and the Centre for Development and Environment (CDE) at the University of Bern. Close cooperation between KNBS, CETRAD, and CDE maximized synergies and knowledge exchange.

An examination of the relationship between maternal and neighborhood-level characteristics and intrauterine growth retardation in Harris County, Texas, 1999--2001

The persistence of low birth weight and intrauterine growth retardation (IUGR) in the United States has puzzled researchers for decades. Much of the work that has been conducted on adverse birth outcomes has focused on low birth weight in general and not on IUGR. Studies that have examined IUGR specifically thus far have focused primarily on individual-level maternal risk factors. These risk factors have only been able to explain a small portion of the variance in IUGR. Therefore, recent work has begun to focus on community-level risk factors in addition to the individual-level maternal characteristics. This study uses Social Ecology to examine the relationship of individual and community-level risk factors and IUGR. Logistic regression was used to establish an individual-level model based on 155, 856 births recorded in Harris County, TX during 1999-2001. IUGR was characterized using a fetal growth ratio method with race/ethnic and sex specific mean birth weights calculated from national vital records. The spatial distributions of 114,460 birth records spatially located within the City of Houston were examined using choropleth, probability and density maps. Census tracts with higher than expected rates of IUGR and high levels of neighborhood disadvantage were highlighted. Neighborhood disadvantage was constructed using socioeconomic variables from the 2000 U.S. Census. Factor analysis was used to create a unified single measure. Lastly, a random coefficients model was used to examine the relationship between varying levels of community disadvantage, given the set of individual-level risk factors for 152,997 birth records spatially located within Harris County, TX. Neighborhood disadvantage was measured using three different indices adapted from previous work. The findings show that pregnancy-induced hypertension, previous preterm infant, tobacco use and insufficient weight gain have the highest association with IUGR. Neighborhood disadvantage only slightly further increases the risk of IUGR (OR 1.12 to 1.23). Although community level disadvantage only helped to explain a small proportion of the variance of IUGR, it did have a significant impact. This finding suggests that community level risk factors should be included in future work with IUGR and that more work needs to be conducted. ^

Aedes aegypti, Aedes albopictus, and Dengue virus in Harris county: An estimate of risk

Recent outbreaks of dengue fever (DF) along the United States/Mexico border, coupled with the high number of reported cases in Mexico suggest that there is the possibility for DF emergence in Houston, Texas1,2. To determine the presence of DF, populations of Aedes aegypti and Aedes albopictus were identified and tested for dengue virus. Maps were created to identify "hot spots" (Figure 1) based on historical data on Ae. aegypti and Ae. albopictus, demographic information, and locations of human cases of dengue fever. BG Sentinel Traps®, in conjunction with BG Lure® attractant, octanol and dry ice, were used to collect mosquitoes, which were then tested for presence of dengue virus using ELISA techniques. All samples tested were negative for dengue virus (DV). Survival of DV ultimately comes down to whether or not it will be vectored by a mosquito to a susceptible human host. The presence of infected humans and contact with the mosquito vectors are two critical factors necessary in the establishment of DF. Historical records indicate the presence of Ae. aegypti and Ae. albopictus in Harris County, which would support localized dengue transmission if infected individuals are present.^ (1) Brunkard JM, Robles-Lopez JL, Ramirez J, Cifuentes E, Rothenberg SJ, Hunsperger EA, Moore CG, Brussolo RM, Villarreal NA, Haddad BM, 2007. Dengue fever seroprevalence and risk factors, Texas-Mexico border, 2004. Emerg Infect Dis 13: 1477-1483. (2) Ramos MM, Mohammed H, Zielinski-Gutierrez E, Hayden MH, Lopez JL, Fournier M, Trujillo AR, Burton R, Brunkard JM, Anaya-Lopez L, Banicki AA, Morales PK, Smith B, Munoz JL, Waterman SH, 2008. Epidemic dengue and dengue hemorrhagic fever at the Texas-Mexico Border: results of a household-based seroepidemiologic survey, December 2005. Am J Trop Med Hyg 78: 364-369.^

Burden of invasive pneumococcal disease in Harris County, Texas (2003--2010) and the implication for enhanced public health surveillance of isolates

Invasive pneumococcal disease (IPD) causes significant health burden in the US, is responsible for the majority of bacterial meningitis, and causes more deaths than any other vaccine preventable bacterial disease in the US. The estimated National IPD rate is 14.3 cases per 100,000 population with a case-fatality rate of 1.5 cases per 100,000 population. Although cases of IPD are routinely reported to the local health department in Harris County Texas, the incidence (IR) and case-fatality (CFR) rates have not been reported. Additionally, it is important to know which serotypes of S. pneumoniae are circulating in Harris County Texas and to determine if ‘replacement disease’ is occurring. ^ This study reported incidence and case-fatality rates from 2003 to 2009, and described the trends in IPD, including the IPD serotypes circulating in Harris County Texas during the study period, particularly in 2008 and 2010. Annual incidence rates were calculated and reported for 2003 to 2009, using complete surveillance-year data. ^ Geographic information system (GIS) software was used to create a series of maps of the data reported during the study period. Cluster and outlier analysis and hot spot analysis were conducted using both case counts by census tract and disease rate by census tract. ^ IPD age- and race-adjusted IR for Harris County Texas and their 95% confidence intervals (CIs) were 1.40 (95% CI 1.0, 1.8), 1.71 (95% CI 1.24, 2.17), 3.13 (95% CI 2.48, 3.78), 3.08 (95% CI 2.43, 3.74), 5.61 (95% CI 4.79, 6.43), 8.11 (95% CI 7.11, 9.1), and 7.65 (95% CI 6.69, 8.61) for the years 2003 to 2009, respectively (rates were age- and race-adjusted to each year's midyear US population estimates). A Poisson regression model demonstrated a statistically significant increasing trend of about 32 percent per year in the IPD rates over the course of the study period. IPD age- and race-adjusted case-fatality rates (CFR) for Harris County Texas were also calculated and reported. A Poisson regression model demonstrated a statistically significant increasing trend of about 26 percent per year in the IPD case-fatality rates from 2003 through 2009. A logistic regression model associated the risk of dying from IPD to alcohol abuse (OR 4.69, 95% CI 2.57, 8.56) and to meningitis (OR 2.42, 95% CI 1.46, 4.03). ^ The prevalence of non-vaccine serotypes (NVT) among IPD cases with serotyped isolates was 98.2 percent. In 2008, the year with the sample more geographically representative of all areas of Harris County Texas, the prevalence was 96 percent. Given these findings, it is reasonable to conclude that ‘replacement disease’ is occurring in Harris County Texas, meaning that, the majority of IPD is caused by serotypes not included in the PCV7 vaccine. Also in conclusion, IPD rates increased during the study period in Harris County Texas.^

The Hospital Study of the City of Houston and Harris County

In 1941 the Texas Legislature appropriated $500,000 to the Board of Regents of the University of Texas to establish a cancer research hospital. The M. D. Anderson Foundation offered to match the appropriation with a grant of an equal sum and to provide a permanent site in Houston. In August, 1942 the Board of Regent of the University and the Trustees of the Foundation signed an agreement to embark on this project. This institution was to be the first one in the medical center, which was incorporated in October, 1945. The Board of Trustees of the Texas Medical Center commissioned a hospital survey to: - Define the needed hospital facilities in the area - Outline an integrated program to meet these needs - Define the facilities to be constructed - Prepare general recommendations for efficient progress The Hospital Study included information about population, hospitals, and other health care and education facilities in Houston and Harris County at that time. It included projected health care needs for future populations, education needs, and facility needs. It also included detailed information on needs for chronic illnesses, a school of public health, and nursing education. This study provides valuable information about the general population and the state of medicine in Houston and Harris County in the 1940s. It gives a unique perspective on the anticipated future as civic leaders looked forward in building the city and region. This document is critical to an understanding of the Texas Medical Center, Houston and medicine as they are today. SECTIONS INCLUDE: Abstract The Abstract was a summary of the 400 page document including general information about the survey area, community medical assets, and current and projected medical needs which the Texas Medical Center should meet. The 123 recommendations were both general (e.g., 12. “That in future planning, the present auxiliary department of the larger hospitals be considered inadequate to carry an added teaching research program of any sizable scope.”) and specific (e.g., 22. That 14.3% of the total acute bed requirement be allotted for obstetric care, reflecting a bed requirement of 522 by 1950, increasing to 1,173 by 1970.”) Section I: Survey Area This section basically addressed the first objective of the survey: “define the needed hospital facilities in the area.” Based on the admission statistics of hospitals, Harris County was included in the survey, with the recognition that growth from out-lying regional areas could occur. Population characteristics and vital statistics were included, with future trends discussed. Each of the hospitals in the area and government and private health organizations, such as the City-County Welfare Board, were documented. Statistics on the facilities use and capacity were given. Eighteen recommendations and observations on the survey area were given. Section II: Community Program This section basically addressed the second objective of the survey: “outline an integrated program to meet these needs.” The information from the Survey Area section formed the basis of the plans for development of the Texas Medical Center. In this section, specific needs, such as what medical specialties were needed, the location and general organization of a medical center, and the academic aspects were outlined. Seventy-four recommendations for these plans were provided. Section III: The Texas Medical Center The third and fourth objectives are addressed. The specific facilities were listed and recommendations were made. Section IV: Special Studies: Chronic Illness The five leading causes of death (heart disease, cancer, “apoplexy”, nephritis, and tuberculosis) were identified and statistics for morbidity and mortality provided. Diagnostic, prevention and care needs were discussed. Recommendations on facilities and other solutions were made. Section IV: Special Studies: School of Public Health An overview of the state of schools of public health in the US was provided. Information on the direction and need of this special school was also provided. Recommendations on development and organization of the proposed school were made. Section IV: Special Studies: Needs and Education Facilities for Nurses Nursing education was connected with hospitals, but the changes to academic nursing programs were discussed. The needs for well-trained nurses in an expanded medical environment were anticipated to result in significant increased demands of these professionals. An overview of the current situation in the survey area and recommendations were provided. Appendix A Maps, tables and charts provide background and statistical information for the previous sections. Appendix B Detailed census data for specific areas of the survey area in the report were included. Sketches of each of the fifteen hospitals and five other health institutions showed historical information, accreditations, staff, available facilities (beds, x-ray, etc.), academic capabilities and financial information.

Dengue transmission risk maps of the continental United States

Dengue fever is a strictly human and non-human primate disease characterized by a high fever, thrombocytopenia, retro-orbital pain, and severe joint and muscle pain. Over 40% of the world population is at risk. Recent re-emergence of dengue outbreaks in Texas and Florida following the re-introduction of competent Aedes mosquito vectors in the United States have raised growing concerns about the potential for increased occurrences of dengue fever outbreaks throughout the southern United States. Current deficiencies in vector control, active surveillance and awareness among medical practitioners may contribute to a delay in recognizing and controlling a dengue virus outbreak. Previous studies have shown links between low-income census tracts, high population density, and dengue fever within the United States. Areas of low-income and high population density that correlate with the distribution of Aedes mosquitoes result in higher potential for outbreaks. In this retrospective ecologic study, nine maps were generated to model U.S. census tracts’ potential to sustain dengue virus transmission if the virus was introduced into the area. Variables in the model included presence of a competent vector in the county and census tract percent poverty and population density. Thirty states, 1,188 counties, and 34,705 census tracts were included in the analysis. Among counties with Aedes mosquito infestation, the census tracts were ranked high, medium, and low risk potential for sustained transmission of the virus. High risk census tracts were identified as areas having the vector, ≥20% poverty, and ≥500 persons per square mile. Census tracts with either ≥20% poverty or ≥500 persons per square mile and have the vector present are considered moderate risk. Census tracts that have the vector present but have <20% poverty and <500 persons per square mile are considered low risk. Furthermore, counties were characterized as moderate risk if 50% or more of the census tracts in that county were rated high or moderate risk, and high risk if 25% or greater were rated high risk. Extreme risk counties, which were primarily concentrated in Texas and Mississippi, were considered having 50% or greater of the census tracts ranked as high risk. Mapping of geographic areas with potential to sustain dengue virus transmission will support surveillance efforts and assist medical personnel in recognizing potential cases. ^

Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

Maps and acoustic profiles of free gas distribution, Western Baltic Sea and Kattgat-Skagerrak area

A shallow gas depth-contour map covering the Skagerrak-western Baltic Sea region has been constructed using a relatively dense grid of existing shallow seismic lines. The digital map is stored as an ESRI shape file in order to facilitate comparison with other data from the region. Free gas usually occurs in mud and sandy mud but is observed only when sediment thickness exceeds a certain threshold value, depending on the water depth of the area in question. Gassy sediments exist at all water depths from approx. 20 m in the coastal waters of the Kattegat to 360 m in the Skagerrak. In spite of the large difference in water depths, the depth of free gas below seabed varies only little within the region, indicating a relatively fast movement of methane in the gas phase towards the seabed compared to the rate of diffusion of dissolved methane. Seeps of old microbial methane occur in the northern Kattegat where a relatively thin cover of sandy sediments exists over shallow, glacially deformed Pleistocene marine sediments. Previous estimates of total methane escape from the area may be correct but the extrapolation of local methane seepage rate data to much larger areas on the continental shelf is probably not justified. Preliminary data on porewater chemistry were compared with the free gas depth contours in the Aarhus Bay area, which occasionally suffers from oxygen deficiency, in order to examine if acoustic gas mapping may be used for monitoring the condition of the bay.

The International Bathymetric Chart of the Southern Ocean (IBCSO) Version 1.0

The International Bathymetric Chart of the Southern Ocean (IBCSO) Version 1.0 is a new digital bathymetric model (DBM) portraying the seafloor of the circum-Antarctic waters south of 60° S. IBCSO is a regional mapping project of the General Bathymetric Chart of the Oceans (GEBCO). IBCSO Version 1.0 DBM has been compiled from all available bathymetric data collectively gathered by more than 30 institutions from 15 countries. These data include multibeam and single beam echo soundings, digitized depths from nautical charts, regional bathymetric gridded compilations, and predicted bathymetry. Specific gridding techniques were applied to compile the DBM from the bathymetric data of different origin, spatial distribution, resolution, and quality. The IBCSO Version 1.0 DBM has a resolution of 500 x 500 m, based on a polar stereographic projection, and is publicly available together with a digital chart for printing from the project website (http://www.ibcso.org) and from the two data sets shown at the bottom of this page.