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Wearable sensing technologies are having a worldwide impact on the creation of novel business opportunities and application services that are benefiting the common citizen. By using these technologies, people have transformed the way they live, interact with each other and their surroundings, their daily routines, and how they monitor their health conditions. We review recent advances in the area of wearable sensing technologies, focusing on aspects such as sensor technologies, communication infrastructures, service infrastructures, security, and privacy. We also review the use of consumer wearables during the coronavirus disease 19 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and we discuss open challenges that must be addressed to further improve the efficacy of wearable sensing systems in the future.

Climate change velocity is a vector depiction of the rate of climate displacement used for assessing climate change impacts. Interpreting velocity requires an assumption that climate trajectory length is proportional to climate change exposure; longer paths suggest greater exposure. However, distance is an imperfect measure of exposure because it does not quantify the extent to which trajectories traverse areas of dissimilar climate. Here we calculate velocity and minimum cumulative exposure (MCE) in degrees Celsius along climate trajectories for North America. We find that velocity is weakly related to MCE; each metric identifies contrasting areas of vulnerability to climate change. Notably, velocity underestimates exposure in mountainous regions where climate trajectories traverse dissimilar climates, resulting in high MCE. In contrast, in flat regions velocity is high where MCE is low, as these areas have negligible climatic resistance to movement. Our results suggest that mountainous regions are more climatically isolated than previously reported. Climate change velocity describes organism exposure to a modified climate, but as a distance-based metric, fails to consider that trajectories traverse dissimilar environments. Here, the authors calculate minimum cumulative exposure, finding that mountainous regions are particularly vulnerable.

The conventional approach of policy interventions in water management that focus on the portions of the system that directly relate to water often lead to unintended consequences that potentially exacerbate water scarcity issues and present challenges to the future viability of many rural agricultural communities. This paper deploys a system dynamics model to illustrate how expanding the policy space of hydrology models to include socioeconomic feedbacks could address these challenges. In this regard, policies that can potentially mitigate general water scarcity in a region of the American Southwest in southern New Mexico are examined. We selected and tested policies with the potential to diminish water scarcity without compromising the system’s economic performance. These policies included supporting choices that reduce or limit the expansion of water-intensive crops, promoting workforce participation, encouraging investment in capital, and regulating land use change processes. The simulation results, after the proposed boundary expansion, unveiled intervention options not commonly exercised by water decision-makers, bolstering the argument that integrated approaches to water research that include socioeconomic feedbacks are crucial for the study of agricultural community resilience.

Secondary forests comprise an increasing area of the tropics and play an important role in global carbon cycling. We compare above-ground biomass accumulation of both planted and naturally regenerating trees, as well as C in the top soil layer, in three restoration treatments replicated at 14, six to eight year old restoration sites in southern Costa Rica. Restoration strategies include: control (no planting), planting tree islands, and conventional, mixed-species tree plantations. We evaluate the importance of past land-use, soil nutrients, understory cover, and surrounding forest cover in explaining variation in above-ground biomass accumulation (ABA) rate across sites. Total ABA and planted tree ABA rate were highest in plantations, intermediate in islands, and lowest in control treatments, whereas ABA rate of naturally regenerating trees did not differ across treatments. Most ABA in plantations (89%) and islands (70%) was due to growth of planted trees. Soil carbon did not change significantly over the time period of the study in any treatment. The majority of across-site variation in both total and planted tree ABA rate was explained by duration of prior pasture use. Tree growth in the first two years after planting explained approximately two-thirds of the variation in ABA rate after 6-8. years. Soil nutrient concentrations explained relatively little of the variation in planted or naturally recruiting ABA rate. Our results show that planting trees substantially increases biomass accumulation during the first several years of forest recovery in former agricultural lands and that past-land use has a strong effect on the rate of biomass accumulation. Planting tree islands is a cost-effective strategy for increasing ABA and creating more heterogeneous habitat conditions than tree plantations. We recommend small scale planting trials to quickly assess potential biomass accumulation and prioritize sites for ecosystem service payments for carbon sequestration. © 2014 Elsevier B.V.

This study uses data from a 2001 survey of Great Plains farmers to explore the adoption, usage patterns, and perceived benefits of computers and the Internet. Adoption results suggest that exposure to the technology through college, outside employment, friends, and family is ultimately more influential than farmer age and farm size. Notably, about half of those who use the Internet for farm-related business report zero economic benefits from it. Whether a farmer perceives that the Internet generates economic benefits depends primarily on how long the farmer has used the Internet for farm business and for what purposes.

AbstractIonospheric irregularities can adversely affect the performance of Global Navigation Satellite System (GNSS). However, this opens the possibility of using GNSS as an effective ionospheric remote sensing tool. Despite ionospheric monitoring has been undertaken for decades, these irregularities in multiple spatial and temporal scales are still not fully understood. This paper reviews Virginia Tech’s recent studies on multi-scale ionospheric irregularities using ground-based and space-based GNSS observations. First, the relevant background of ionospheric irregularities and their impact on GNSS signals is reviewed. Next, three topics of ground-based observations of ionospheric irregularities for which GNSS and other ground-based techniques are used simultaneously are reviewed. Both passive and active measurements in high-latitude regions are covered. Modelling and observations in mid-latitude regions are considered as well. Emphasis is placed on the increased capability of assessing the multi-scale nature of ionospheric irregularities using other traditional techniques (e.g., radar, magnetometer, high frequency receivers) as well as GNSS observations (e.g., Total-Electron-Content or TEC, scintillation). Besides ground-based observations, recent advances in GNSS space-based ionospheric measurements are briefly reviewed. Finally, a new space-based ionospheric observation technique using GNSS-based spacecraft formation flying and a differential TEC method is demonstrated using the newly developed Virginia Tech Formation Flying Testbed (VTFFTB). Based on multi-constellation multi-band GNSS, the VTFFTB has been developed into a hardware-in-the-loop simulation testbed with external high-fidelity global ionospheric model(s) for 3-satellite formation flying, which can potentially be used for new multi-scale ionospheric measurement mission design.

Abstract. Bruker™ EM27/SUN instruments are commercial mobile solar-viewing near-IR spectrometers. They show promise for expanding the global density of atmospheric column measurements of greenhouse gases and are being marketed for such applications. They have been shown to measure the same variations of atmospheric gases within a day as the high-resolution spectrometers of the Total Carbon Column Observing Network (TCCON). However, there is little known about the long-term precision and uncertainty budgets of EM27/SUN measurements. In this study, which includes a comparison of 186 measurement days spanning 11 months, we note that atmospheric variations of Xgas within a single day are well captured by these low-resolution instruments, but over several months, the measurements drift noticeably. We present comparisons between EM27/SUN instruments and the TCCON using GGG as the retrieval algorithm. In addition, we perform several tests to evaluate the robustness of the performance and determine the largest sources of errors from these spectrometers. We include comparisons of XCO2, XCH4, XCO, and XN2O. Specifically we note EM27/SUN biases for January 2015 of 0.03, 0.75, –0.12, and 2.43 % for XCO2, XCH4, XCO, and XN2O respectively, with 1σ running precisions of 0.08 and 0.06 % for XCO2 and XCH4 from measurements in Pasadena. We also identify significant error caused by nonlinear sensitivity when using an extended spectral range detector used to measure CO and N2O.

127-154 The regional controls of biodiversity patterns have been traditionally evaluated using structural and compositional components at the species level, but evaluation of the functional component at the ecosystem level is still scarce. During the last decades, the role of ecosystem functioning in management and conservation has increased. Our aim was to use satellite-derived Ecosystem Functional Types (EFTs, patches of the land-surface with similar carbon gain dynamics) to characterize the regional patterns of ecosystem functional diversity and to evaluate the environmental and human controls that determine EFT richness across natural and human-modified systems in temperate South America. The EFT identification was based on three descriptors of carbon gain dynamics derived from seasonal curves of the MODIS Enhanced Vegetation Index (EVI) : annual mean (surrogate of primary production), seasonal coefficient of variation (indicator of seasonality) and date of maximum EVI (descriptor of phenology). As observed for species richness in the southern hemisphere, water availability, not energy, emerged as the main climatic driver ofEFT richness in natural areas of temperate South America. In anthropogenic areas, the role of both water and energy decreased and increasing human intervention increased richness at low levels of human influence, but decreased richness at high levels of human influence.