Uncertainties in measuring populations potentially impacted by sea level rise and coastal flooding

A better understanding of the impact of global climate change requires information on the locations and characteristics of populations affected. For instance, with global sea level predicted to rise and coastal flooding set to become more frequent and intense, high-resolution spatial population datasets are increasingly being used to estimate the size of vulnerable coastal populations. Many previous studies have undertaken this by quantifying the size of populations residing in low elevation coastal zones using one of two global spatial population datasets available – LandScan and the Global Rural Urban Mapping Project (GRUMP). This has been undertaken without consideration of the effects of this choice, which are a function of the quality of input datasets and differences in methods used to construct each spatial population dataset. Here we calculate estimated low elevation coastal zone resident population sizes from LandScan and GRUMP using previously adopted approaches, and quantify the absolute and relative differences achieved through switching datasets. Our findings suggest that the choice of one particular dataset over another can translate to a difference of more than 7.5 million vulnerable people for countries with extensive coastal populations, such as Indonesia and Japan. Our findings also show variations in estimates of proportions of national populations at risk range from &lt;0.1% to 45% differences when switching between datasets, with large differences predominantly for countries where coarse and outdated input data were used in the construction of the spatial population datasets. The results highlight the need for the construction of spatial population datasets built on accurate, contemporary and detailed census data for use in climate change impact studies and the importance of acknowledging uncertainties inherent in existing spatial population datasets when estimating the demographic impacts of climate change.<br/

Co-evolution of wetland landscapes, flooding, and human settlement in the Mississippi River Delta Plain

© 2016, The Author(s). River deltas all over the world are sinking beneath sea-level rise, causing significant threats to natural and social systems. This is due to the combined effects of anthropogenic changes to sediment supply and river flow, subsidence, and sea-level rise, posing an immediate threat to the 500–1,000 million residents, many in megacities that live on deltaic coasts. The Mississippi River Deltaic Plain (MRDP) provides examples for many of the functions and feedbacks, regarding how human river management has impacted source-sink processes in coastal deltaic basins, resulting in human settlements more at risk to coastal storms. The survival of human settlement on the MRDP is arguably coupled to a shifting mass balance between a deltaic landscape occupied by either land built by the Mississippi River or water occupied by the Gulf of Mexico. We developed an approach to compare 50 % L:W isopleths (L:W is ratio of land to water) across the Atchafalaya and Terrebonne Basins to test landscape behavior over the last six decades to measure delta instability in coastal deltaic basins as a function of reduced sediment supply from river flooding. The Atchafalaya Basin, with continued sediment delivery, compared to Terrebonne Basin, with reduced river inputs, allow us to test assumptions of how coastal deltaic basins respond to river management over the last 75 years by analyzing landward migration rate of 50 % L:W isopleths between 1932 and 2010. The average landward migration for Terrebonne Basin was nearly 17,000 m (17 km) compared to only 22 m in Atchafalaya Basin over the last 78 years (p \u3c 0.001), resulting in migration rates of 218 m/year (0.22 km/year) and \u3c0.5 m/year, respectively. In addition, freshwater vegetation expanded in Atchafalaya Basin since 1949 compared to migration of intermediate and brackish marshes landward in the Terrebonne Basin. Changes in salt marsh vegetation patterns were very distinct in these two basins with gain of 25 % in the Terrebonne Basin compared to 90 % decrease in the Atchafalaya Basin since 1949. These shifts in vegetation types as L:W ratio decreases with reduced sediment input and increase in salinity also coincide with an increase in wind fetch in Terrebonne Bay. In the upper Terrebonne Bay, where the largest landward migration of the 50 % L:W ratio isopleth occurred, we estimate that the wave power has increased by 50–100 % from 1932 to 2010, as the bathymetric and topographic conditions changed, and increase in maximum storm-surge height also increased owing to the landward migration of the L:W ratio isopleth. We argue that this balance of land relative to water in this delta provides a much clearer understanding of increased flood risk from tropical cyclones rather than just estimates of areal land loss. We describe how coastal deltaic basins of the MRDP can be used as experimental landscapes to provide insights into how varying degrees of sediment delivery to coastal deltaic floodplains change flooding risks of a sinking delta using landward migrations of 50 % L:W isopleths. The nonlinear response of migrating L:W isopleths as wind fetch increases is a critical feedback effect that should influence human river-management decisions in deltaic coast. Changes in land area alone do not capture how corresponding landscape degradation and increased water area can lead to exponential increase in flood risk to human populations in low-lying coastal regions. Reduced land formation in coastal deltaic basins (measured by changes in the land:water ratio) can contribute significantly to increasing flood risks by removing the negative feedback of wetlands on wave and storm-surge that occur during extreme weather events. Increased flood risks will promote population migration as human risks associated with living in a deltaic landscape increase, as land is submerged and coastal inundation threats rise. These system linkages in dynamic deltaic coasts define a balance of river management and human settlement dependent on a certain level of land area within coastal deltaic basins (L)

Specialty Training and Specialization Among Physicians Who Treat HIV/AIDS in the United States

OBJECTIVE: To assess the association of specialty training and experience in the care of HIV disease with HIV-specific knowledge, referral patterns, and HIV-related education activities. DESIGN: Cross-sectional survey. SETTING: The United States. PARTICIPANTS: Physicians caring for patients in the HIV Costs and Service Utilization Study, a study of a probability sample of HIV-infected individuals in the United States. MEASUREMENTS AND MAIN RESULTS: Measures included physicians' reports of specialty training and HIV caseload, scores on an HIV-specific knowledge test, referral patterns, and attendance rates at HIV-related educational activities. Approximately 72% (379) of the eligible physicians completed a survey. Of these, 152 (40%) had infectious disease (ID) training, and 213 (56%) were generalists; 4% of ID-trained physicians and 37% of generalist physicians did not consider themselves HIV experts. The median current caseloads were 150 and 200 patients for ID experts and generalist experts, respectively. In contrast, the median caseload for non-expert generalists was 5. Mean scores on the knowledge scale were similar for ID and generalist experts (9.0 items correct out of 11 vs 8.5; P = not significant), but lower for generalist non-experts (6.5 items correct; P < .01). Experts had attended more local and national HIV meetings than non-experts (9.3 vs 2.7; P < .01, and 2.3 vs .40; P < .01, respectively) in the past year. Fewer ID experts ever referred than generalist experts (13.0% vs 27.3%; P = .01). In multivariable models that included specialty training and caseload, physicians with caseloads of 20 to 49 and >50 were more likely to have a high knowledge score (defined as 80% or more correct, odds ratio [OR], 2.8; P = .04 and OR, 5.7; P < .001, respectively), and the effect of specialty was attenuated (OR, 2.7; P = .02 decreased from OR, 7.8; P < .001 in a model without caseload). In the models predicting referral practices, both experience (OR, .25; P < .01 and OR, .17; P < .01 for caseloads of 20 to 49 and >50, respectively) and specialty (OR, .19; P < .01 and OR, .09; P < .01 for generalist and ID experts, respectively) were significant. CONCLUSIONS: In a national sample of physicians, HIV-specific knowledge was more strongly associated with HIV caseload than with specialty training. In addition, although referral practices were related to both experience and specialty, generalist experts and ID physicians reported similar behaviors. This suggests that generalist physicians, through clinical experience and self-education, can develop specialized knowledge in HIV care