Empirically Derived Sensitivity of Vegetation to Climate across Global Gradients of Temperature and Precipitation

The natural composition of terrestrial ecosystems can be shaped by climate to take advantage of local environmental conditions. Ecosystem functioning (e.g., interaction between photosynthesis and temperature) can also acclimate to different climatological states. The combination of these two factors thus determines ecological–climate interactions. A global empirical map of the sensitivity of vegetation to climate is derived using the response of satellite-observed greenness to interannual variations in temperature and precipitation. Mechanisms constraining ecosystem functioning are inferred by analyzing how the sensitivity of vegetation to climate varies across climate space. Analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate at large spatial scales. In hot and wet locations, vegetation is greener in warmer years despite temperatures likely exceeding thermally optimum conditions. However, sunlight generally increases during warmer years, suggesting that the increased stress from higher atmospheric water demand is offset by higher rates of photosynthesis. The sensitivity of vegetation transitions in sign (greener when warmer or drier to greener when cooler or wetter) along an emergent line in climate space with a slope of about 59 mm yr^(−1) °C^(−1), twice as steep as contours of aridity. The mismatch between these slopes is evidence at a global scale of the limitation of both water supply due to inefficiencies in plant access to rainfall and plant physiological responses to atmospheric water demand. This empirical pattern can provide a functional constraint for process-based models, helping to improve predictions of the global-scale response of vegetation to a changing climate

Primary care blood tests before cancer diagnosis: National Cancer Diagnosis Audit data

Background: Blood tests can support the diagnostic process but how often they are used in cancer patients is unclear. Aim: To explore use of common blood tests before cancer diagnosis in primary care. Design and setting: English National Cancer Diagnosis Audit data on 39,752 cancer patients diagnosed in 2018. Methods: We assessed common blood test use (full blood count (FBC), urea and electrolytes (U&Es), and liver function tests (LFTs)), related variation by patient and symptom group, and associations with the primary care and the diagnostic intervals (PCI, DI). Results: At least one common blood test was used in 41% of cancer patients. Among tested patients, FBC was used in 95%, U&Es in 88% and LFTs in 74%) Blood testing was less common in women (adjusted odds ratio (aOR) vs men: 0.92, 95%CI: 0.87-0.98) and non-white patients (0.89, 0.82-0.97 vs white) and more common in older patients (1.12, 1.06-1.18 for 70+ vs 50-69 years). Test use varied greatly by cancer-site, (melanoma: 2%, leukaemia 84%). Fewer patients presenting with alarm symptoms alone were tested (24%) than those with non-alarm symptoms alone (50%). Median PCI and DI were longer in tested than non-tested patients (PCI: 10 vs 0; DI: 49 vs 32 days, respectively, p<0.001 for both), including among tested patients with alarm symptoms (PCI: 4 vs 0; DI: 41 vs 22). Conclusions: Two-fifths of patients subsequently diagnosed with cancer have primary care blood tests. Given variable test use, research is needed on the clinical context in which blood tests are ordered

A mixed-methods approach to assessing implementers’ readiness to adopt digital health interventions (RADHI)

Background: Despite being the primary setting for HIV prevention among men who have sex with men (MSM) since the start of the epidemic, community-based organizations (CBOs) struggle to reach this historically stigmatized and largely hidden population with face-to-face interventions. HIV researchers have readily turned to the internet to deliver critical HIV education to this group, with evidence of high effectiveness and acceptability across studies. However, implementation outside of research contexts has been limited and not well studied. We aimed to assess HIV CBOs' readiness to adopt digital health interventions and identify contextual factors that may contribute to differing levels of readiness. Methods: We recruited 22 CBOs across the US through a pragmatic request-for-proposals process to deliver Keep It Up! (KIU!), an evidence-based eHealth HIV prevention program. We used mixed methods to examine CBO readiness to adopt digital health interventions (RADHI). Before implementation, CBO staff completed a 5-item RADHI scale (scored 0-4) that demonstrated concurrent and predictive validity. We interviewed CBO staff using semi-structured questions guided by the Consolidated Framework for Implementation Research and compared RADHI score groups on determinants identified from the interviews. Results: Eighty-five staff (range = 1-10 per CBO) completed the RADHI. On average, CBOs reported moderate-to-great readiness (2.74) to adopt KIU!. High RADHI CBOs thought KIU! was a top priority and an innovative program complementary to their existing approaches for their clients. Low RADHI CBOs expressed concerns that KIU! could be a cultural mismatch for their clients, was lower priority than existing programs and services, relied on clients' own motivation, and might not be suitable for clients with disabilities. Value, appeal, and limitations did not differ by RADHI group. Conclusions: While HIV CBOs are excited for the opportunities and advantages of digital interventions, additional pre-implementation and implementation support may be needed to increase perceived value and usability for different client populations. Addressing these limitations is critical to effective digital prevention interventions for HIV and other domains such as mental health, chronic disease management, and transitions in care. Future research can utilize our novel, validated measure of CBOs' readiness to adopt digital health interventions. Trial registration: NCT03896776. clinicaltrials.gov, 1 April 2019.</p

Transition from suppressed to active convection modulated by a weak-temperature gradient derived large-scale circulation

Numerical simulations are performed to assess the influence of the large-scale circulation on the transition from suppressed to active convection. As a model tool, we used a coupled-column model. It consists of two cloud-resolving models which are fully coupled via a large-scale circulation which is derived from the requirement that the instantaneous domain-mean potential temperature profiles of the two columns remain close to each other. This is known as the weak-temperature gradient approach. The simulations of the transition are initialized from coupled-column simulations over non-uniform surface forcing and the transition is forced within the dry column by changing the local and/or remote surface forcings to uniform surface forcing across the columns. As the strength of the circulation is reduced to zero, moisture is recharged into the dry column and a transition to active convection occurs once the column is sufficiently moistened to sustain deep convection. Direct effects of changing surface forcing occur over the first few days only. Afterward, it is the evolution of the large-scale circulation which systematically modulates the transition. Its contributions are approximately equally divided between the heating and moistening effects. A transition time is defined to summarize the evolution from suppressed to active convection. It is the time when the rain rate within the dry column is halfway to the mean value obtained at equilibrium over uniform surface forcing. The transition time is around twice as long for a transition that is forced remotely compared to a transition that is forced locally. Simulations in which both local and remote surface forcings are changed produce intermediate transition times

Airships: A New Horizon for Science

The "Airships: A New Horizon for Science" study at the Keck Institute for Space Studies investigated the potential of a variety of airships currently operable or under development to serve as observatories and science instrumentation platforms for a range of space, atmospheric, and Earth science. The participants represent a diverse cross-section of the aerospace sector, NASA, and academia. Over the last two decades, there has been wide interest in developing a high altitude, stratospheric lighter-than-air (LTA) airship that could maneuver and remain in a desired geographic position (i.e., "station-keeping") for weeks, months or even years. Our study found considerable scientific value in both low altitude (< 40 kft) and high altitude (> 60 kft) airships across a wide spectrum of space, atmospheric, and Earth science programs. Over the course of the study period, we identified stratospheric tethered aerostats as a viable alternative to airships where station-keeping was valued over maneuverability. By opening up the sky and Earth's stratospheric horizon in affordable ways with long-term flexibility, airships allow us to push technology and science forward in a project-rich environment that complements existing space observatories as well as aircraft and high-altitude balloon missions.Comment: This low resolution version of the report is 8.6 MB. For the high resolution version see: http://kiss.caltech.edu/study/airship

Intercomparison of methods of coupling between convection and large-scale circulation: 1. Comparison over uniform surface conditions

As part of an international intercomparison project, a set of single column models (SCMs) and cloud-resolving models (CRMs) are run under the weak temperature gradient (WTG) method and the damped gravity wave (DGW) method. For each model, the implementation of the WTG or DGW method involves a simulated column which is coupled to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. The simulated column has the same surface conditions as the reference state and is initialized with profiles from the reference state. We performed systematic comparison of the behavior of different models under a consistent implementation of the WTG method and the DGW method and systematic comparison of the WTG and DGW methods in models with different physics and numerics. CRMs and SCMs produce a variety of behaviors under both WTG and DGW methods. Some of the models reproduce the reference state while others sustain a large-scale circulation which results in either substantially lower or higher precipitation compared to the value of the reference state. CRMs show a fairly linear relationship between precipitation and circulation strength. SCMs display a wider range of behaviors than CRMs. Some SCMs under the WTG method produce zero precipitation. Within an individual SCM, a DGW simulation and a corresponding WTG simulation can produce different signed circulation. When initialized with a dry troposphere, DGW simulations always result in a precipitating equilibrium state. The greatest sensitivities to the initial moisture conditions occur for multiple stable equilibria in some WTG simulations, corresponding to either a dry equilibrium state when initialized as dry or a precipitating equilibrium state when initialized as moist. Multiple equilibria are seen in more WTG simulations for higher SST. In some models, the existence of multiple equilibria is sensitive to some parameters in the WTG calculations