Ecology and morphology of the dwarf bromeliad boa Ungaliophis panamensis (Squamata, Boidae, Ungaliophiinae) in Costa Rica and Panama

Ecological and morphological data on Ungaliophis panamensis is extremely limited as this species is rarely encountered. These knowledge gaps have been advanced in this study where data was analysed from a small sample of snakes collected in two tropical forested environments in Costa Rica and Pana-ma. Standardised major axis testing and a Bayesian latent variable ordination revealed that the species is sexually dimorphic, closely associated with tree trunks in natural forested areas, and occasionally discovered in rural buildings. Although further investigation into its natural history is warranted, this study shows that even with just a few individuals it is possible to elucidate ecological information that is relevant to the conservation of snake species

Association between rheumatoid arthritis disease activity, progression of functional limitation and long-term risk of orthopaedic surgery : Combined analysis of two prospective cohorts supports EULAR treat to target DAS thresholds

Objectives: To examine the association between disease activity in early rheumatoid arthritis (RA), functional limitation and long-term orthopaedic episodes. Methods: Health Assessment Questionnaire (HAQ) disability scores were collected from two longitudinal early RA inception cohorts in routine care; Early Rheumatoid Arthritis Study and Early Rheumatoid Arthritis Network from 1986 to 2012. The incidence of major and intermediate orthopaedic surgical episodes over 25 years was collected from national data sets. Disease activity was categorised by mean disease activity score (DAS28) annually between years 1 and 5; remission (RDAS≤2.6), low (LDAS>2.6-3.2), low-moderate (LMDAS≥3.2-4.19), high-moderate (HMDAS 4.2-5.1) and high (HDAS>5.1). Results: Data from 2045 patients were analysed. Patients in RDAS showed no HAQ progression over 5 years, whereas there was a significant relationship between rising DAS28 category and HAQ at 1 year, and the rate of HAQ progression between years 1 and 5. During 27 986 person-years follow-up, 392 intermediate and 591 major surgeries were observed. Compared with the RDAS category, there was a significantly increased cumulative incidence of intermediate surgery in HDAS (OR 2.59 CI 1.49 to 4.52) and HMDAS (OR 1.8 CI 1.05 to 3.11) categories, and for major surgery in HDAS (OR 2.48 CI 1.5 to 4.11), HMDAS (OR 2.16 CI 1.32 to 3.52) and LMDAS (OR 2.07 CI 1.28 to 3.33) categories. There was no significant difference in HAQ progression or orthopaedic episodes between RDAS and LDAS categories. Conclusions: There is an association between disease activity and both poor function and long-term orthopaedic episodes. This illustrates the far from benign consequences of persistent moderate disease activity, and supports European League Against Rheumatism treat to target recommendations to secure low disease activity or remission in all patients.Peer reviewedFinal Published versio

Do provisioning ecosystem services change along gradients of increasing agricultural production?

Context: Increasing agricultural production shapes the flow of ecosystem services (ES), including provisioning services that support the livelihoods and nutrition of people in tropical developing countries. Although our broad understanding of the social-ecological consequences of agricultural intensification is growing, how it impacts provisioning ES is still unknown. Objectives: We examined the household use of provisioning ES across a gradient of increasing agricultural production in seven tropical countries (Bangladesh, Burkina Faso, Cameroon, Ethiopia, Indonesia, Nicaragua and Zambia). We answered two overarching questions: (1) does the use of provisioning ES differ along gradients of agriculture production ranging from zones of subsistence to moderate and to high agriculture production? and (2) are there synergies and/or trade-offs within and among groups of ES within these zones? Methods: Using structured surveys, we asked 1900 households about their assets, livestock, crops, and collection of forest products. These questions allowed us to assess the number of provisioning ES households used, and whether the ES used are functionally substitutable (i.e., used similarly for nutrition, material, and energy). Finally, we explored synergies and trade-offs among household use of provisioning ES. Results: As agricultural production increased, provisioning ES declined both in total number and in different functional groups used. We found more severe decreases in ES for relatively poorer households. Within the functional groups of ES, synergistic relationships were more often found than trade-offs in all zones, including significant synergies among livestock products (dairy, eggs, meat) and fruits. Conclusions: Considering landscape context provides opportunities to enhance synergies among provisioning services for households, supporting resilient food systems and human well-being

Fall, Recovery and Characterization of the Novato L6 Chondrite Breccia

The Novato L6 chondrite fragmental breccia fell in California on 17 October 2012, and was recovered after the Cameras for Allsky Meteor Surveillance (CAMS) project determined the meteor's trajectory between 95 and 45 km altitude. The final fragmentation at 33 1 km altitude was exceptionally well documented by digital photographs. The first sample was recovered before rain hit the area. First results from a consortium study of the meteorite's characterization, cosmogenic and radiogenic nuclides, origin and conditions of the fall are presented. Some meteorites did not retain fusion crust and show evidence of spallation. Before entry, the meteoroid was 35+/-5 cm in diameter (mass 80+/-35 kg) with a cosmic ray exposure age of 9+/-1 Ma, if it had a one-stage exposure history. However, based on the cosmogenic nuclide inventory, a two-stage exposure history is more likely, with lower shielding in the last few Ma. Thermoluminescence data suggest a collision event within the last approx. 0.1 Ma. Novato likely belonged to the class of shocked L chondrites that have a common shock age of 470 Ma, based on the U,Th-He age of 460+/-220 Ma. The measured orbits of Novato, Jesenice and Innisfree are consistent with a proposed origin of these shocked L chondrites in the Gefion asteroid family, but leave open the possibility that they came to us directly from the 5:2 mean motion resonance with Jupiter. Novato experienced a stronger compaction than did other L6 chondrites of shock-stage S4. Despite this, a freshly broken surface shows a wide range of organic compounds

A methodological approach for assessing cross-site landscape change: understanding socio-ecological systems

The expansion of agriculture has resulted in large-scale habitat loss, the fragmentation of forests, significant losses in biological diversity and negative impacts on many ecosystem services. In this paper, we highlight the Agrarian Change Project, a multi-disciplinary research initiative, that applies detailed socio-ecological methodologies in multi-functional landscapes, and assess the subsequent implications for conservation, livelihoods and food security. Specifically, the research focuses on land use impacts in locations which exhibit various combinations of agricultural modification/change across a forest transition gradient in six tropical landscapes, in Zambia, Burkina Faso, Cameroon, Ethiopia, Indonesia and Bangladesh. These methods include integrated assessments of the perceptions of ecosystem service provision, tree cover loss and gain, relative poverty, diets and agricultural patterns of change. Although numerous surveys on rural livelihoods are undertaken each year, often at great cost, many are hampered by weaknesses in methods and thus may not reflect rural realities. We attempt to highlight how integrating broader socio-ecological methods can be used to fill in those gaps and ensure such realities are indeed captured. Early findings suggest that the transition from a forested landscape to a more agrarian dominated system does not necessarily result in better livelihood outcomes and there may be unintended consequences of forest and tree cover removal. These include the loss of access to grazing land, loss of dietary diversity and the loss of ecosystem services/forest products

EgoActive: Integrated wireless wearable sensors for capturing infant egocentric auditory-visual statistics and autonomic nervous system function ‘in the wild’

There have been sustained efforts toward using naturalistic methods in developmental science to measure infant behaviors in the real world from an egocentric perspective because statistical regularities in the environment can shape and be shaped by the developing infant. However, there is no user-friendly and unobtrusive technology to densely and reliably sample life in the wild. To address this gap, we present the design, implementation and validation of the EgoActive platform, which addresses limitations of existing wearable technologies for developmental research. EgoActive records the active infants’ egocentric perspective of the world via a miniature wireless head-mounted camera concurrently with their physiological responses to this input via a lightweight, wireless ECG/acceleration sensor. We also provide software tools to facilitate data analyses. Our validation studies showed that the cameras and body sensors performed well. Families also reported that the platform was comfortable, easy to use and operate, and did not interfere with daily activities. The synchronized multi-modal data from the EgoActive platform can help tease apart complex processes that are important for child development to further our understanding of areas ranging from executive function to emotion processing and social learning

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages