A new global fAPAR and LAI dataset derived from optimal albedo estimates: comparison with MODIS products

We present the first comparison between new fAPAR and LAI products derived from the GlobAlbedo dataset and the widely-used MODIS fAPAR and LAI and products. The GlobAlbedo derived products are produced using a 1D two-stream radiative transfer (RT) scheme designed explicitly for global parameter retrieval from albedo, with consistency between RT model assumptions and observations, as well as with typical large-scale land surface model RT schemes. The approach does not require biome-specific structural assumptions (e.g. cover, clumping, understory), unlike more detailed 3D RT model approaches. GlobAlbedo-derived values of fAPAR and LAI are compared with MODIS values over 2002-2011 at multiple flux tower sites within selected biomes, over 1200 × 1200 km regions and globally. GlobAlbedo-derived fAPAR and LAI values are temporally more stable than the MODIS values due to (1) the smoothness of the underlying albedo, derived via optimal estimation (assimilation) using an a priori estimate of albedo derived from an albedo ‘climatology’ (composited multi-year albedo observations) and (2) space-time invariant prior information in the inversion of the two-stream RT scheme. Parameters agree closely in timing but with GlobAlbedo values consistently lower than MODIS, particularly for LAI. Larger differences occur in winter (when values are lower) and in the Southern hemisphere. Globally, we find that: GlobAlbedo-derived fAPAR is ~0.9- 1.01 × MODIS fAPAR with an offset of ~0.03; GlobAlbedo-derived LAI is ~0.6 × MODIS LAI with an offset of ~0.2. Differences arise due to the RT model assumptions underlying the products, meaning care is required in interpreting either set of values, particularly when comparing to finescale ground-based estimates. We present global calibrations between GlobAlbedo-derived and MODIS products.JRC.H.5-Land Resources Managemen

The prevalence of posttraumatic stress disorder in pregnancy and after birth: A systematic review and meta-analysis

BACKGROUND: Previous reviews have provided preliminary insights into risk factors and possible prevalence of Post-traumatic Stress Disorder (PTSD) postpartum with no attempt to examine prenatal PTSD. This study aimed to assess the prevalence of PTSD during pregnancy and after birth, and the course of PTSD over this time. METHODS: PsychINFO, PubMed, Scopus and Web of Science were searched using PTSD terms crossed with perinatal terms. Studies were included if they reported the prevalence of PTSD during pregnancy or after birth using a diagnostic measure. RESULTS: 59 studies (N =24267) met inclusion criteria: 35 studies of prenatal PTSD and 28 studies of postpartum PTSD (where 4 studies provided prevalence of PTSD in pregnancy and postpartum). In community samples the mean prevalence of prenatal PTSD was 3.3% (95%, CI 2.44-4.54). The majority of postpartum studies measured PTSD in relation to childbirth with a mean prevalence of 4.0% (95%, CI 2.77-5.71) in community samples. Women in high-risk groups were at more risk of PTSD with a mean prevalence of 18.95% (95%, CI 10.62-31.43) in pregnancy and 18.5% (95%, CI 10.6-30.38) after birth. Using clinical interviews was associated with lower prevalence rates in pregnancy and higher prevalence rates postpartum. LIMITATIONS: Limitations include use of stringent diagnostic criteria, wide variability of PTSD rates, and inadequacy of studies on prenatal PTSD measured in three trimesters. CONCLUSIONS: PTSD is prevalent during pregnancy and after birth and may increase postpartum if not identified and treated. Assessment and treatment in maternity services is recommended

First study on data collection on 'Visegrad' countries and ECO countries

SIGLEAvailable from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, Duesternbrook Weg 120, D-24105 Kiel / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Does disgust increase parasympathetic activation in individuals with a history of fainting? A psychophysiological analysis of disgust stimuli with and without blood-injection- injury association.

People with blood-injection-injury fear can faint when being confronted with blood, injections or injuries. Page (1994) holds that people with blood-injury phobia faint, because they are disgust sensitive and disgust facilitates fainting by eliciting parasympathetic activity. We tested the following two hypotheses: (1) Disgusting pictures elicit more disgust in blood-injection-injury anxious people with a history of fainting than they do in controls. (2) Disgust causes parasympathetic activation. Subjects were 24 participants with high blood-injection-injury fear and a history of fainting in anxiety relevant situations and 24 subjects with average blood-injection-injury fear and no fainting history. We analyzed self-reported feelings of disgust, anxiety and faintness and reactions in heart rate, skin conductance, blood pressure and respiratory sinus arrhythmia during the confrontation with disgusting pictures with and without blood content.We did not find any evidence that the blood-injection-injury anxious subjects were more disgust sensitive than the control subjects and we also did not find any evidence that disgust elicits parasympathetic activation

Observing the continental-scale carbon balance: assessment of sampling complementarity and redundancy in a terrestrial assimilation system by means of quantitative network design

International audienceThis paper investigates the relationship between the heterogeneity of the terrestrial carbon cycle and the optimal design of observing networks to constrain it. We combine the methods of quantitative network design and carbon-cycle data assimilation to a hierarchy of increasingly heterogeneous descriptions of the European terrestrial biosphere as indicated by increasing diversity of plant functional types. We employ three types of observations, flask measurements of CO2 concentrations, continuous measurements of CO2 and pointwise measurements of CO2 flux. We show that flux measurements are extremely efficient for relatively homogeneous situations but not robust against increasing or unknown complexity. Here a hybrid approach is necessary, and we recommend its use in the development of integrated carbon observing systems

Using SMOS soil moisture data combining CO₂ flask samples to constrain carbon fluxes during 2010-2015 within a Carbon Cycle Data Assimilation System (CCDAS)

The terrestrial carbon cycle is an important component of the global carbon budget due to its large gross exchangefluxes with the atmosphere and their sensitivity to climate change. Terrestrial biosphere models showlarge uncertainties in simulating carbon fluxes, which impact global carbon budget assessments. The land surfacecarbon cycle is tightly controlled by soil moisture through plant physiological processes. Accurate soilmoisture observations thereby have the potential to improve the modeling of carbon fluxes in a model-datafusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate six years ofsurface soil moisture provided by the SMOS satellite in combination with global-scale observations of atmosphericCO2 concentrations. We find that assimilation of SMOS soil moisture exhibits better performance on soilhydrology modeling at both global and site-level than only assimilating atmospheric CO2 concentrations, and itimproves the soil moisture simulation particularly in mid- to high-latitude regions where the plants suffer fromwater stress frequently. The optimized model also shows good agreements with inter-annual variability in simulatedNet Primary Productivity (NEP) and Gross Primary Productivity (GPP) from an atmospheric inversion(Jena CarboScope) and the up-scaled eddy covariance flux product (FLUXNET-MTE), respectively. Correlationbetween SIF (Solar Induced Fluorescence) and optimized GPP also shows to be the highest when soil moistureand atmospheric CO2 are simultaneously assimilated. In general, CCDAS obtains smaller annual mean NEPvalues (1.8 PgC/yr) than the atmospheric inversion and an ensemble of Dynamic Global Vegetation Models(DGVMs), but larger GPP values (167.8 PgC/yr) than the up-scaled eddy covariance dataset (FLUXNET-MTE)and the MODIS based GPP product for the years 2010 to 2015. This study demonstrates the high potential ofconstraining simulations of the terrestrial biosphere carbon cycle on inter-annual time scales using long-termmicrowave observations of soil moisture