Cerebral blood flow: An experimental and clinical study of the blood flow through the cerebral cortex

Abstract Not Provided

The carbon cycle in Mexico: past, present and future of C stocks and fluxes

PublishedThe Supplement related to this article is available online at doi:10.5194/bg-13-223-2016-supplement.We modeled the carbon (C) cycle in Mexico with a process-based approach. We used different available products (satellite data, field measurements, models and flux towers) to estimate C stocks and fluxes in the country at three different time frames: present (defined as the period 2000–2005), the past century (1901–2000) and the remainder of this century (2010–2100). Our estimate of the gross primary productivity (GPP) for the country was 2137 ± 1023 TgC yr−1 and a total C stock of 34 506 ± 7483 TgC, with 20 347 ± 4622 TgC in vegetation and 14 159 ± 3861 in the soil. Contrary to other current estimates for recent decades, our results showed that Mexico was a C sink over the period 1990–2009 (+31 TgC yr−1) and that C accumulation over the last century amounted to 1210 ± 1040 TgC. We attributed this sink to the CO2 fertilization effect on GPP, which led to an increase of 3408 ± 1060 TgC, while both climate and land use reduced the country C stocks by −458 ± 1001 and −1740 ± 878 TgC, respectively. Under different future scenarios, the C sink will likely continue over the 21st century, with decreasing C uptake as the climate forcing becomes more extreme. Our work provides valuable insights on relevant driving processes of the C cycle such as the role of drought in drylands (e.g., grasslands and shrublands) and the impact of climate change on the mean residence time of soil C in tropical ecosystems.The lead author (G. Murray-Tortarolo) thanks CONACYT-CECTI, the University of Exeter and Secretaría de Educación Pública (SEP) for their funding of this project. The authors extend their thanks to Carlos Ortiz Solorio and to the Colegio de Posgraduados for the field soil data and to the Alianza Redd+ Mexico for the field biomass data. This project would not have been possible without the valuable data from the CMIP5 models. A. Arneth, G. Murray-Tortarolo, A. Wiltshire and S. Sitch acknowledge the support of the European Commission-funded project LULCC4C (grant no. 603542). A. Wiltshire was partsupported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101)

Capacity for Carbon Sequestration and Climate Change Mitigation in Different Ecologically-Distinct Zones of Sri Lanka

Vegetation has the capacity to mitigate greenhouse gas (GHG) induced climate change byabsorbing and sequestering carbon dioxide, the principal GHG, in plant biomass. Sri Lanka,an island located in the humid tropical South Asia, has a considerable range of ecologicallydistinctzones (EDZs) as a result of the spatial and temporal variation of its climate. TheseEDZs are characterised by different dominant vegetation types and ecosystems with varyingground cover. Hence, the carbon sequestration capacity which determines the strength of the„land carbon sink‟ is likely to vary in the different EDZs. Analysis of long-term climatic datahas shown that trends of climate change (i.e., increasing atmospheric temperature andpotential evapotranspiration and decreasing precipitation and soil water availability) of thedifferent climatic zones of Sri Lanka reflect the established global trends. These trends inclimate change are likely to modify the carbon sequestration capacity of different EDZs overtime. Therefore, the objective of this work is to estimate the carbon sequestration and climatechange mitigation capacity of different EDZs of Sri Lanka and its historical variation todetermine the possible impacts of climate change.Simulations from nine dynamic global vegetation models (DGVMs) were used to estimatecarbon balance parameters such as net primary productivity (NPP), heterotrophic respiration(Rh) and net biome productivity (NBP) for eight 1o(latitude)×1o(longitude) grid cellscovering Sri Lanka. Models were run over the period from 1900 to 2009 using the climateforcing data from CRU-NCEP, which were validated using data from the MeteorologyDepartment of Sri Lanka. Carbon balance parameters were calculated for six ecologicallydistinctzones of Sri Lanka (i.e., south-west, central highlands, eastern coastal plain, northwest,north-east and north) that were defined based on 1o×1o grid cells. A validation check ofthe model outputs was done by comparing simulated NPP with actual NPP for selectedvegetation types. An initial analysis of all nine DGVMs, which included models running atdifferent resolutions (3.75o×2.5o, 2.5°×2.5o and 0.5o×0.5o) showed substantial within-zonevariation and did not clearly distinguish carbon sequestration capacities of different EDZs.This was probably because of spatial averaging of outputs from coarse resolution modelsacross different EDZs. A second analysis with the four finer resolution DGVMs showedsubstantially improved results. Subsequent simulations running the fine resolution modelJULES on a finer grid of 0.5o×0.5o allowed estimation of carbon balance parameters in thirtyfive0.5o×0.5o cells, which substantially-improved the spatial resolution of estimated carbonsequestration capacities of different EDZs of Sri Lanka. Temporal and spatial trends of theestimated carbon balance parameters will be presented along with analyses of theirunderlying causes and climatic drivers.Keywords: Terrestrial carbon balance, Net primary productivity, Climate change, Sri Lank

Cross-correlating Carbon Monoxide Line-intensity Maps with Spectroscopic and Photometric Galaxy Surveys

Line-intensity mapping (LIM or IM) is an emerging field of observational work, with strong potential to fit into a larger effort to probe large-scale structure and small-scale astrophysical phenomena using multiple complementary tracers. Taking full advantage of such complementarity means, in part, undertaking line-intensity surveys with galaxy surveys in mind. We consider the potential for detection of a cross-correlation signal between COMAP and blind surveys based on photometric redshifts (as in COSMOS) or based on spectroscopic data (as with the HETDEX survey of Lyman-$\alpha$ emitters). We find that obtaining $\sigma_z/(1+z)\lesssim0.003$ accuracy in redshifts and $\gtrsim10^{-4}$ sources per Mpc$^3$ with spectroscopic redshift determination should enable a CO-galaxy cross spectrum detection significance at least twice that of the CO auto spectrum. Either a future targeted spectroscopic survey or a blind survey like HETDEX may be able to meet both of these requirements.Comment: 19 pages + appendix (31 pages total), 16 figures, 6 tables; accepted for publication in Ap

What Drives the Expansion of Giant HII Regions?: A Study of Stellar Feedback in 30 Doradus

Observations show that star formation is an inefficient and slow process. This result can be attributed to the injection of energy and momentum by stars that prevents free-fall collapse of molecular clouds. The mechanism of this stellar feedback is debated theoretically: possible sources of pressure include the classical warm HII gas, the hot gas generated by shock-heating from stellar winds and supernovae, direct radiation of stars, and the dust-processed radiation field trapped inside the HII shell. In this paper, we measure observationally the pressures associated with each component listed above across the giant HII region 30 Doradus in the Large Magellanic Cloud. We exploit high-resolution, multi-wavelengh images (radio, infrared, optical, and X-ray) to map these pressures as a function of position. We find that radiation pressure dominates within 75 pc of the central star cluster, R136, while the HII gas pressure dominates at larger radii. By contrast, the dust-processed radiation pressure and hot gas pressure are generally weak and not dynamically important, although the hot gas pressure may have played a more significant role at early times. Based on the low X-ray gas pressures, we demonstrate that the hot gas is only partially confined and must be leaking out the HII shell. Additionally, we consider the implications of a dominant radiation pressure on the early dynamics of 30 Doradus.Comment: 14 pages, 17 figures; ApJ in pres

Spatiotemporal patterns of terrestrial gross primary production: A review

This is the final version of the article. Available from American Geophysical Union via the DOI in this record.There is another record for this publication in ORE at http://hdl.handle.net/10871/30934Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990-2009) from two observation-based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon-climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process-based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.European Commission's Seventh Framework Programme. Grant Numbers: 238366, 28267

Spatiotemporal patterns of terrestrial gross primary production: A review

This is the final version of the article. Available from American Geophysical Union via the DOI in this record.There is another record for this publication in ORE at http://hdl.handle.net/10871/21007Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990-2009) from two observation-based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon-climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process-based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.European Commission's Seventh Framework Programme. Grant Numbers: 238366, 28267

The depression in visual impairment trial (DEPVIT): trial design and protocol

<b>Background</b> The prevalence of depression in people with a visual disability is high but screening for depression and referral for treatment is not yet an integral part of visual rehabilitation service provision. One reason for this may be that there is no good evidence about the effectiveness of treatments in this patient group. This study is the first to evaluate the effect of depression treatments on people with a visual impairment and co morbid depression.<p></p> <b>Methods/design</b> The study is an exploratory, multicentre, individually randomised waiting list controlled trial. Participants will be randomised to receive Problem Solving Therapy (PST), a ‘referral to the GP’ requesting treatment according to the NICE’s ‘stepped care’ recommendations or the waiting list arm of the trial. The primary outcome measure is change (from randomisation) in depressive symptoms as measured by the Beck’s Depression Inventory (BDI-II) at 6 months. Secondary outcomes include change in depressive symptoms at 3 months, change in visual function as measured with the near vision subscale of the VFQ-48 and 7 item NEI-VFQ at 3 and 6 months, change in generic health related quality of life (EQ5D), the costs associated with PST, estimates of incremental cost effectiveness, and recruitment rate estimation.<p></p> <b>Discussion</b> Depression is prevalent in people with disabling visual impairment. This exploratory study will establish depression screening and referral for treatment in visual rehabilitation clinics in the UK. It will be the first to explore the efficacy of PST and the effectiveness of NICE’s ‘stepped care’ approach to the treatment of depression in people with a visual impairment.<p></p&gt

The Promise of Prevention: The Effects of Four Preventable Risk Factors on National Life Expectancy and Life Expectancy Disparities by Race and County in the United States

Majid Ezzati and colleagues examine the contribution of a set of risk factors (smoking, high blood pressure, elevated blood glucose, and adiposity) to socioeconomic disparities in life expectancy in the US population