Search

In recent years, the availability of airborne imaging spectroscopy (hyperspectral) data has expanded dramatically. The high spatial and spectral resolution of these data uniquely enable spatially explicit ecological studies including species mapping, assessment of drought mortality and foliar trait distributions. However, we have barely begun to unlock the potential of these data to use direct mapping of vegetation characteristics to infer subsurface properties of the critical zone. To assess their utility for Earth systems research, imaging spectroscopy data acquisitions require integration with large, coincident ground-based datasets collected by experts in ecology and environmental and Earth science. Without coordinated, well-planned field campaigns, potential knowledge leveraged from advanced airborne data collections could be lost. Despite the growing importance of this field, documented methods to couple such a wide variety of disciplines remain sparse. We coordinated the first National Ecological Observatory Network Airborne Observation Platform (AOP) survey performed outside of their core sites, which took place in the Upper East River watershed, Colorado. Extensive planning for sample tracking and organization allowed field and flight teams to update the ground-based sampling strategy daily. This enabled collection of an extensive set of physical samples to support a wide range of ecological, microbiological, biogeochemical and hydrological studies. We present a framework for integrating airborne and field campaigns to obtain high-quality data for foliar trait prediction and document an archive of coincident physical samples collected to support a systems approach to ecological research in the critical zone. This detailed methodological account provides an example of how a multi-disciplinary and multi-institutional team can coordinate to maximize knowledge gained from an airborne survey, an approach that could be extended to other studies. The coordination of imaging spectroscopy surveys with appropriately timed and extensive field surveys, along with high-quality processing of these data, presents a unique opportunity to reveal new insights into the structure and dynamics of the critical zone. To our knowledge, this level of co-aligned sampling has never been undertaken in tandem with AOP surveys and subsequent studies utilizing this archive will shed considerable light on the breadth of applications for which imaging spectroscopy data can be leveraged.

In 2010, when the National Alliance for Advanced Biofuels and Bioproducts (NAABB) consortium began, little was known about the molecular basis of algal biomass or oil production. Very few algal genome sequences were available and efforts to identify the best-producing wild species through bioprospecting approaches had largely stalled after the U.S. Department of Energy's Aquatic Species Program. This lack of knowledge included how reduced carbon was partitioned into storage products like triglycerides or starch and the role played by metabolite remodeling in the accumulation of energy-dense storage products. Furthermore, genetic transformation and metabolic engineering approaches to improve algal biomass and oil yields were in their infancy. Genome sequencing and transcriptional profiling were becoming less expensive, however; and the tools to annotate gene expression profiles under various growth and engineered conditions were just starting to be developed for algae. It was in this context that an integrated algal biology program was introduced in the NAABB to address the greatest constraints limiting algal biomass yield. This review describes the NAABB algal biology program, including hypotheses, research objectives, and strategies to move algal biology research into the twenty-first century and to realize the greatest potential of algae biomass systems to produce biofuels.

Alies Coenders,1 Cindy Chapman,2 Patricia Hannaford,3 Tiina Jaaniste,2,3 Wen Qiu,2 David Anderson,2 Maline Glogauer,2 Evelyn Goodison-Farnsworth,2 Marianne McCormick,2 David Champion2,31University of Groningen, Groningen, The Netherlands; 2Department of Anaesthesia and Pain Medicine, Sydney Children's Hospital, Randwick, NSW, Australia; 3University of New South Wales, Kensington, NSW, AustraliaObjectives: This study was designed to investigate whether an individual and parental history of functional pain syndromes (FPS) is found more often in adolescents suffering from chronic pain than in their pain-free peers.Methods: Our case–control study involved 101 adolescents aged 10–18 years. Cases were 45 patients of the Chronic Pain Clinic at Sydney Children's Hospital with diverse chronic pain disorders. Controls consisted of 56 adolescent volunteers who did not have chronic pain. Adolescents and their parents filled out questionnaires assessing demographic data as well as known and potential risk factors for chronic pain. A history of FPS was assessed by questionnaire, including restless legs syndrome (RLS). Chi-squared tests and t-tests were used to investigate univariate associations between chronic pain in adolescents and lifetime prevalence of FPS. Logistic regression was used to test multivariate associations, while controlling for possible confounders.Results: Migraine, non-migraine headaches, recurrent abdominal pain (RAP), and RLS were reported significantly more frequently in cases than controls (P-values of 0.01,

In this paper a pure rotational Raman lidar (PRR) was established for the atmospheric temperature measurements from 5 km to 40 km over Wuhan, China (30.5°N, 114.5°E). To extract the expected PRR signals and simultaneously suppress the elastically backscattered light, a high-spectral resolution polychromator for light splitting and filtering was designed. Observational results revealed that the temperature difference measured by PRR lidar and the local radiosonde below 30 km was less than 3.0 K. The good agreement validated the reliability of the PRR lidar. With the 1-h integration and 150-m spatial resolution, the statistical temperature error for PRR lidar increases from 0.4 K at 10 km up to 4 K at altitudes of about 30 km. In addition, the whole night temperature profiles were obtained for study of the long-term observation of atmospheric fluctuations.