Centimeter to decimeter hollow concretions and voids in Gale Crater sediments, Mars

Voids and hollow spheroids between ∼1 and 23 cm in diameter occur at several locations along the traverse of the Curiosity rover in Gale crater, Mars. These hollow spherical features are significantly different from anything observed in previous landed missions. The voids appear in dark-toned, rough-textured outcrops, most notably at Point Lake (sols 302-305) and Twin Cairns Island (sol 343). Point Lake displays both voids and cemented spheroids in close proximity; other locations show one or the other form. The spheroids have 1-4 mm thick walls and appear relatively dark-toned in all cases, some with a reddish hue. Only one hollow spheroid (Winnipesaukee, sol 653) was analyzed for composition, appearing mafic (Fe-rich), in contrast to the relatively felsic host rock. The interior surface of the spheroid appears to have a similar composition to the exterior with the possible exceptions of being more hydrated and slightly depleted in Fe and K. Origins of the spheroids as Martian tektites or volcanic bombs appear unlikely due to their hollow and relatively fragile nature and the absence of in-place clearly igneous rocks. A more likely explanation to both the voids and the hollow spheroids is reaction of reduced iron with oxidizing groundwater followed by some re-precipitation as cemented rind concretions at a chemical reaction front. Although some terrestrial concretion analogs are produced from a precursor siderite or pyrite, diagenetic minerals could also be direct precipitates for other terrestrial concretions. The Gale sediments differ from terrestrial sandstones in their high initial iron content, perhaps facilitating a higher occurrence of such diagenetic reactions

Rockport Comprehensive Plan

This document was developed and prepared by Texas Target Communities (TxTC) at Texas A&M University in partnership with the City of Rockport, Texas Sea Grant, Texas A&M University - Corpus Christi, Texas A&M University - School of Law and Texas Tech University.Founded in 1871, the City of Rockport aims to continue growing economically and sustainably. Rockport is a resilient community dedicated to sustainable growth and attracting businesses to the area. Rockport is a charming town that offers a close-knit community feel and is a popular tourist destination for marine recreation, fairs, and exhibitions throughout the year. The Comprehensive Plan 2020-2040 is designed to guide the city of Rockport for its future growth. The guiding principles for this planning process were Rockport's vision statement and its corresponding goals, which were crafted by the task force. The goals focus on factors of growth and development including public participation, development considerations, transportation, community facilities, economic development, parks, and housing and social vulnerability

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

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

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

Strengthening climate services for the food security sector

The Global Framework for Climate Services (GFCS) enables vulnerable sectors and populations to better manage climate variability and adapt to climate change. How? By developing and incorporating science-based climate information into planning, policy and practice. The GFCS places the decision context and information needs of “users” at the centre of the design process. The development of such climate services alters the dynamic between the “user” and the “provider,” valuing each actor's knowledge and engaging them both in a co-production process. This approach challenges the conventional linear supply chain for weather and climate information, in which data are generated, information produced, a product designed, and handed over to the user for consumption, without a real understanding of whether this information is useful for decision-making. In late 2013, with support from the Norwegian Ministry of Foreign Affairs, the GFCS embarked on a multi-agency1 proof of concept. The GFCS Adaptation Programme for Africa aimed to increase the resilience of those most vulnerable to the impacts of weather and climate-related hazards, through the development of more effective climate services in Tanzania and Malawi. It focused in particular on the sectors that address food security, health and disaster risk reduction. This article outlines the learning generated through the food security component of the project. The component was jointly led by the World Food Programme (WFP) and CGIAR Research Programme on Climate Change, Agriculture and Food Security (CCAFS), with activities implemented with the Tanzania Meteorological Agency (TMA), Malawian Department of Climate Change and Meteorological Services (DCCMS), and a range of national and local partners

Effects of a novel implantable elastomer device for lung volume reduction surgery in a rabbit model of elastase-induced emphysema.

ObjectivesThere is intense interest in lung volume reduction surgery (LVRS) for treatment of severe symptomatic emphysema. LVRS results in objective and subjective improvement in lung function in selected patients. However, LVRS is complicated by substantial morbidity, including prolonged pulmonary air leak associated with resection of emphysematous lung tissue. In this study, we investigated the use of a novel implanted silicone elastomer device that reduces lung volume without surgical resection, in a previously reported emphysematous animal model. The purpose of this investigation was to determine the applicability, physiologic effects, complications, and air-leak results of this lung volume reducer (LVR) approach.DesignControlled, randomized, prospective animal study. Emphysema was induced in 20 New Zealand white rabbits with three nebulizations of 10,000 U of porcine elastase. After 6 weeks, the animals were randomized to control sham surgery (n = 10) vs implanted silicone elastomer LVR (n = 10) treatment groups. Lung function, including helium-dilution lung volumes, static respiratory system compliance curves, and diffusion capacity of the lung for carbon monoxide (DLCO), was measured at baseline, following emphysema induction (week 6), and when the animals were killed (1 week after LVR or sham surgery). Histologic evaluation was performed in all lung specimens after fixation.ResultsModerate emphysema developed after elastase nebulization, assessed by lung function and postmortem histology. Functional residual capacity (FRC) and an upward shift of lung compliance curves was observed with development of emphysema at 6 weeks (p < 0.05). Following LVR, FRC decreased (p = 0.005) and compliance curves shifted back downward (p = 0.002), without reduction in DLCO. There was no change in control sham animals. DLCO did not change in either group.ConclusionsIn this short-term, randomized, controlled animal model study, the implantable LVR approach produced safe and effective lung volume reduction without tissue resection in the treated animals. The implant procedure produced minimal morbidity, no mortality, and no observed air-leak complications in the treated animals. Limitations include the short-term follow-up and moderate degree of emphysema in this animal model. Further research is required to assess long-term effects and complications of this method for lung volume reduction