Serum alpha-fetoprotein and neural tube defects in the first trimester of pregnancy

As part of the Medical Research Council randomized trial of vitamin supplementation in the prevention of neural tube defects (NTDs), maternal serum alpha-fetoprotein (AFP) was available for 19 NTD pregnancies. Each of these was matched with four unaffected controls, by maternal age, participating centre, and duration of sample storage. The samples came from women whose gestational age ranged from 6 to 14 completed weeks. The median AFP level in the affected pregnancies was 1·2 multiples of the median value in unaffected pregnancies of the same gestational age (95 per cent confidence interval (CI) 0·83–1·59). This confirmed the view that serum AFP measurement is of no practical value in the detection of NTDs in the first trimester of pregnancy. The study also showed that folic acid supplementation, used as a method of preventing NTDs, had no effect on the concentrations of maternal serum AFP up to 14 weeks of pregnancy.     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

Structure and Content of the Discourse on Climate Change in the Blogosphere: The Big Picture

Based on the texts of 1.3 million blog posts and the structure of the links between the blogs in which these posts appeared, this study presents an analysis of the discourse on climate change in the English-language blogosphere. Our approach combines community detection with probabilistic topic modeling to show how topics related to climate change are discussed across various parts of the blogosphere. We find that there is one community of predominantly climate skeptical blogs but several accepter communities. The topic analysis reveals a series of issues that are characteristic of the climate change discourse in the blogosphere. Two topics, one related to climate change science and one related to climate change politics, are particularly important for characterizing the discourse. We also find that the distribution of topics over the communities cuts across the divide between skeptics and non-skeptics (accepters) and that there are differences in the patterns of interactions between the skeptics and different groups of accepters.     

Using air quality modeling to study source–receptor relationships between nitrogen oxides emissions and ozone exposures over the United States

Human exposure to ambient ozone (O₃) has been linked to a variety of adverse health effects. The ozone level at a location is contributed by local production, regional transport, and background ozone. This study combines detailed emission inventory, air quality modeling, and census data to investigate the source–receptor relationships between nitrogen oxides (NO_x) emissions and population exposure to ambient O₃ in 48 states over the continental United States. By removing NO_x emissions from each state one at a time, we calculate the change in O₃ exposures by examining the difference between the base and the sensitivity simulations. Based on the 49 simulations, we construct state-level and census region-level source–receptor matrices describing the relationships among these states/regions. We find that, for 43 receptor states, cumulative NO_x emissions from upwind states contribute more to O₃ exposures than the state's own emissions. In-state emissions are responsible for less than 15% of O₃ exposures in 90% of U.S. states. A state's NO_x emissions can influence 2 to 40 downwind states by at least a 0.1 ppbv change in population-averaged O₃ exposure. The results suggest that the U.S. generally needs a regional strategy to effectively reduce O₃ exposures. But the current regional emission control program in the U.S. is a cap-and-trade program that assumes the marginal damage of every ton of NO_x is equal. In this study, the average O₃ exposures caused by one ton of NO_x emissions ranges from ? 2.0 to 2.3 ppm-people-hours depending on the state. The actual damage caused by one ton of NO_x emissions varies considerably over space.     

Projected twenty-first-century changes in the Central American mid-summer drought using statistically downscaled climate projections

Regional Environmental Change - In addition to periodic long-term drought, much of Central America experiences a rainy season with two peaks separated by a dry period of weeks to over a month in...     

Intrauterine manometry: Technique and application to fetal pathology

A technique is described for measuring pressure within the amniotic cavity and within fetal vessels and/or body compartments. Two saline-filled catheters were connected at one end to needles inserted during indicated invasive procedures and at the other to silicon strain gauge transducers. In 36 pregnancies with normal liquor volume, stable intra-amniotic pressure (IAP, range 1–14 mmHg) increased with gestation (r=0·48, p<0·01). In pregnancies complicated by severe oligohydramnios, IAP was ≤ 1 mm Hg and rose to normal levels with saline amnioinfusion. Raised IAP (range 17–26 mm Hg), found in pregnancies with gross polyhydramnios, fell with drainage of amniotic fluid. Subtraction manometry was used to determine supra-amniotic pressure within the intervillus space, umbilical vein, umbilical artery, abdominal and thoracic cavities, and the urinary tract in normal and/or pathological fetuses. Low intravesical and intrapelvicalyceal pressures (median 6·5, range 2–10 mmHg) were noted in fetuses with obstructive uropathies. Intrauterine subtraction manometry appears to be a useful tool in the understanding of fetal pathophysiology and may be of clinical benefit in the therapeutic drainage and infusion of amniotic fluid and in the assessment of certain fetal disease states.     

Estimating the vulnerability of fifteen tree species under changing climate in Northwest North America

In the Pacific northwestern (PNW) region of North America, climatic conditions have significantly warmed since a predominantly cool phase of the Pacific North American circulation patterns between 1950 and 1975. What are the implications of this shift in climate for the vulnerability of native tree species? To address this question, we combined mechanistic and statistical models to assess where a variety of native tree species might be more vulnerable within their recorded ranges and where they might potentially migrate. For long-lived species that are well adapted to compete, seasonal differences in photosynthesis and water use offer insights helpful in predicting their distributions. To evaluate the general response of conifers to climatic variation across the region, we previously applied a process-based model (3-PG), to simulate the growth and maximum leaf area index that Douglas-fir could attain within recognized forested areas. We then constructed automated decision tree models to define and map the ecological distributions of 15 tree species based on differences in how photosynthesis was constrained by drought, daytime temperatures, high evaporative demand, and the frequency of frost. For the baseline climate period (1950-1975), the decision tree models predicted presence and absence of each species at ∼23,000 observations with an average accuracy of 81%, with an average kappa statistic of 0.74. In this paper the same models were run annually for the period between 1976 and 2006 for each species, and the areas defined as remaining suitable or becoming vulnerable to disturbance were identified based on whether more or less than half of the years fell within the originally defined limits. Based on these criteria, 70% of the species recorded ranges remained suitable, with 30% deemed vulnerable. Results varied notably by species with western red cedar and western hemlock remaining highly adapted, with potential for range expansion in area of up to 50% relative to the baseline period. In contrast, ponderosa pine, lodgepole pine, grand, and noble fir were classified as vulnerable with potential net contractions in their ranges. The analysis was extended through the rest of the 21st century using climatic projections from the Canadian global circulation model with a high fossil fuel emission scenario (A2) and compared to other previously published species range predictions.     

A field experiment characterizing variable detection rates during plant surveys

Surveys aimed at finding threatened and invasive species can be challenging due to individual rarity and low and variable individual detection rates. Detection rate in plant surveys typically varies due to differences among observers, among the individual plants being surveyed (targets), and across background environments. Interactions among these 3 components may occur but are rarely estimated due to limited replication and control during data collection. We conducted an experiment to investigate sources of variation in detection of 2 Pilosella species that are invasive and sparsely distributed in the Alpine National Park, Australia. These species are superficially similar in appearance to other yellow-flowered plants occurring in this landscape. We controlled the presence and color of flowers on target Pilosella plants and controlled their placement in plots, which were selected for their variation in cover of non-target yellow flowers and dominant vegetation type. Observers mimicked Pilosella surveys in the plots and reported 1 categorical and 4 quantitative indicators of their survey experience level. We applied survival analysis to detection data to model the influence of both controlled and uncontrolled variables on detection rate. Orange- and yellow-flowering Pilosella in grass- and heath-dominated vegetation were detected at a higher rate than nonflowering Pilosella. However, this detection gain diminished as the cover of other co-occurring yellow-flowering species increased. Recent experience with Pilosella surveys improved detection rate. Detection experiments are a direct and accessible means of understanding detection processes and interpreting survey data for threatened and invasive species. Our detection findings have been used for survey planning and can inform progress toward eradication. Interaction of target and background characteristics determined detection rate, which enhanced predictions in the Pilosella eradication program and demonstrated the difficulty of transferring detection findings into untested environments.