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29 result(s) for "Berg, Alexis M."
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Large influence of soil moisture on long-term terrestrial carbon uptake
Although the terrestrial biosphere absorbs about 25 per cent of anthropogenic carbon dioxide (CO 2 ) emissions, the rate of land carbon uptake remains highly uncertain, leading to uncertainties in climate projections 1 , 2 . Understanding the factors that limit or drive land carbon storage is therefore important for improving climate predictions. One potential limiting factor for land carbon uptake is soil moisture, which can reduce gross primary production through ecosystem water stress 3 , 4 , cause vegetation mortality 5 and further exacerbate climate extremes due to land–atmosphere feedbacks 6 . Previous work has explored the impact of soil-moisture availability on past carbon-flux variability 3 , 7 , 8 . However, the influence of soil-moisture variability and trends on the long-term carbon sink and the mechanisms responsible for associated carbon losses remain uncertain. Here we use the data output from four Earth system models 9 from a series of experiments to analyse the responses of terrestrial net biome productivity to soil-moisture changes, and find that soil-moisture variability and trends induce large CO 2 fluxes (about two to three gigatons of carbon per year; comparable with the land carbon sink itself 1 ) throughout the twenty-first century. Subseasonal and interannual soil-moisture variability generate CO 2 as a result of the nonlinear response of photosynthesis and net ecosystem exchange to soil-water availability and of the increased temperature and vapour pressure deficit caused by land–atmosphere interactions. Soil-moisture variability reduces the present land carbon sink, and its increase and drying trends in several regions are expected to reduce it further. Our results emphasize that the capacity of continents to act as a future carbon sink critically depends on the nonlinear response of carbon fluxes to soil moisture and on land–atmosphere interactions. This suggests that the increasing trend in carbon uptake rate may not be sustained past the middle of the century and could result in accelerated atmospheric CO 2 growth. Earth system models suggest that soil-moisture variability and trends will induce large carbon releases throughout the twenty-first century.
Land–atmosphere feedbacks exacerbate concurrent soil drought and atmospheric aridity
Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land–atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture–precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land–atmosphere feedbacks is projected to increase in the 21st century. Importantly, land–atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.
Soil moisture–atmosphere feedbacks mitigate declining water availability in drylands
Global warming alters surface water availability (precipitation minus evapotranspiration, P–E) and hence freshwater resources. However, the influence of land–atmosphere feedbacks on future P–E changes and the underlying mechanisms remain unclear. Here we demonstrate that soil moisture (SM) strongly impacts future P–E changes, especially in drylands, by regulating evapotranspiration and atmospheric moisture inflow. Using modelling and empirical approaches, we find a consistent negative SM feedback on P–E, which may offset ~60% of the decline in dryland P–E otherwise expected in the absence of SM feedbacks. The negative feedback is not caused by atmospheric thermodynamic responses to declining SM; rather, reduced SM, in addition to limiting evapotranspiration, regulates atmospheric circulation and vertical ascent to enhance moisture transport into drylands. This SM effect is a large source of uncertainty in projected dryland P–E changes, underscoring the need to better constrain future SM changes and improve the representation of SM–atmosphere processes in models.Surface water availability will change under climate change and is impacted by feedbacks between the land and atmosphere. Soil moisture exerts a negative feedback on water availability in drylands, offsetting some of the expected decline.
Soil moisture–atmosphere feedback dominates land carbon uptake variability
Year-to-year changes in carbon uptake by terrestrial ecosystems have an essential role in determining atmospheric carbon dioxide concentrations 1 . It remains uncertain to what extent temperature and water availability can explain these variations at the global scale 2 – 5 . Here we use factorial climate model simulations 6 and show that variability in soil moisture drives 90 per cent of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture–atmosphere feedback amplifies temperature and humidity anomalies and enhances the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate that soil moisture has a dominant role 4 , which is not readily apparent from land surface model simulations and observational analyses 2 , 5 . These findings highlight the need to account for feedback between soil and atmospheric dryness when estimating the response of the carbon cycle to climatic change globally 5 , 7 , as well as when conducting field-scale investigations of the response of the ecosystem to droughts 8 , 9 . Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects that are controlled by soil moisture. Factorial climate model simulations show that 90% of the inter-annual variability in global land carbon uptake is driven by soil moisture and its atmospheric feedback on temperature and air humidity.
High-resolution (1 km) Köppen-Geiger maps for 1901–2099 based on constrained CMIP6 projections
We introduce Version 2 of our widely used 1-km Köppen-Geiger climate classification maps for historical and future climate conditions. The historical maps (encompassing 1901–1930, 1931–1960, 1961–1990, and 1991–2020) are based on high-resolution, observation-based climatologies, while the future maps (encompassing 2041–2070 and 2071–2099) are based on downscaled and bias-corrected climate projections for seven shared socio-economic pathways (SSPs). We evaluated 67 climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and kept a subset of 42 with the most plausible CO 2 -induced warming rates. We estimate that from 1901–1930 to 1991–2020, approximately 5% of the global land surface (excluding Antarctica) transitioned to a different major Köppen-Geiger class. Furthermore, we project that from 1991–2020 to 2071–2099, 5% of the land surface will transition to a different major class under the low-emissions SSP1-2.6 scenario, 8% under the middle-of-the-road SSP2-4.5 scenario, and 13% under the high-emissions SSP5-8.5 scenario. The Köppen-Geiger maps, along with associated confidence estimates, underlying monthly air temperature and precipitation data, and sensitivity metrics for the CMIP6 models, can be accessed at www.gloh2o.org/koppen .
Considerations for using potential surrogate endpoints in cancer screening trials
The requirement of large-scale expensive cancer screening trials spanning decades creates considerable barriers to the development, commercialisation, and implementation of novel screening tests. One way to address these problems is to use surrogate endpoints for the ultimate endpoint of interest, cancer mortality, at an earlier timepoint. This Review aims to highlight the issues underlying the choice and use of surrogate endpoints for cancer screening trials, to propose criteria for when and how we might use such endpoints, and to suggest possible candidates. We present the current landscape and challenges, and discuss lessons and shortcomings from the therapeutic trial setting. It is hugely challenging to validate a surrogate endpoint, even with carefully designed clinical studies. Nevertheless, we consider whether there are candidates that might satisfy the requirements defined by research and regulatory bodies.
Interannual Coupling between Summertime Surface Temperature and Precipitation over Land
Widespread negative correlations between summertime-mean temperatures and precipitation over land regions are a well-known feature of terrestrial climate. This behavior has generally been interpreted in the context of soil moisture–atmosphere coupling, with soil moisture deficits associated with reduced rainfall leading to enhanced surface sensible heating and higher surface temperature. The present study revisits the genesis of these negative temperature–precipitation correlations using simulations from the Global Land–Atmosphere Coupling Experiment–phase 5 of the Coupled Model Intercomparison Project (GLACE-CMIP5) multimodel experiment. The analyses are based on simulations with five climate models, which were integrated with prescribed (noninteractive) and with interactive soil moisture over the period 1950–2100. While the results presented here generally confirm the interpretation that negative correlations between seasonal temperature and precipitation arise through the direct control of soil moisture on surface heat flux partitioning, the presence of widespread negative correlations when soil moisture–atmosphere interactions are artificially removed in at least two out of five models suggests that atmospheric processes, in addition to land surface processes, contribute to the observed negative temperature–precipitation correlation. On longer time scales, the negative correlation between precipitation and temperature is shown to have implications for the projection of climate change impacts on near-surface climate: in all models, in the regions of strongest temperature–precipitation anticorrelation on interannual time scales, long-term regional warming is modulated to a large extent by the regional response of precipitation to climate change, with precipitation increases (decreases) being associated with minimum (maximum) warming. This correspondence appears to arise largely as the result of soil moisture–atmosphere interactions.
Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits
Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene–trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2 , known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits. Many genetic variants identified in genome-wide association studies are associated with gene expression. Here, Porcu et al. propose a transcriptome-wide summary statistics-based Mendelian randomization approach (TWMR) that, applied to 43 human traits, uncovers hundreds of previously unreported gene–trait associations.
Identification of post-cardiac arrest blood pressure thresholds associated with outcomes in children: an ICU-Resuscitation study
Introduction Though early hypotension after pediatric in-hospital cardiac arrest (IHCA) is associated with inferior outcomes, ideal post-arrest blood pressure (BP) targets have not been established. We aimed to leverage prospectively collected BP data to explore the association of post-arrest BP thresholds with outcomes. We hypothesized that post-arrest systolic and diastolic BP thresholds would be higher than the currently recommended post-cardiopulmonary resuscitation BP targets and would be associated with higher rates of survival to hospital discharge. Methods We performed a secondary analysis of prospectively collected BP data from the first 24 h following return of circulation from index IHCA events enrolled in the ICU-RESUScitation trial (NCT02837497). The lowest documented systolic BP (SBP) and diastolic BP (DBP) were percentile-adjusted for age, height and sex. Receiver operator characteristic curves and cubic spline analyses controlling for illness category and presence of pre-arrest hypotension were generated exploring the association of lowest post-arrest SBP and DBP with survival to hospital discharge and survival to hospital discharge with favorable neurologic outcome (Pediatric Cerebral Performance Category of 1–3 or no change from baseline). Optimal cutoffs for post-arrest BP thresholds were based on analysis of receiver operator characteristic curves and spline curves. Logistic regression models accounting for illness category and pre-arrest hypotension examined the associations of these thresholds with outcomes. Results Among 693 index events with 0–6 h post-arrest BP data, identified thresholds were: SBP > 10th percentile and DBP > 50th percentile for age, sex and height. Fifty-one percent ( n  = 352) of subjects had lowest SBP above threshold and 50% ( n  = 346) had lowest DBP above threshold. SBP and DBP above thresholds were each associated with survival to hospital discharge (SBP: aRR 1.21 [95% CI 1.10, 1.33]; DBP: aRR 1.23 [1.12, 1.34]) and survival to hospital discharge with favorable neurologic outcome (SBP: aRR 1.22 [1.10, 1.35]; DBP: aRR 1.27 [1.15, 1.40]) (all p  < 0.001). Conclusions Following pediatric IHCA, subjects had higher rates of survival to hospital discharge and survival to hospital discharge with favorable neurologic outcome when BP targets above a threshold of SBP > 10th percentile for age and DBP > 50th percentile for age during the first 6 h post-arrest.