Gas exchange at whole plant level shows that a less conservative water use is linked to a higher performance in three ecologically distinct pine species

Increasing temperatures and decreasing precipitation in large areas of the planet as a consequence of global warming will affect plant growth and survival. However, the impact of climatic conditions will differ across species depending on their stomatal response to increasing aridity, as this will ultimately affect the balance between carbon assimilation and water loss. In this study, we monitored gas exchange, growth and survival in saplings of three widely distributed European pine species (Pinus halepensis, P. nigra and P. sylvestris) with contrasting distribution and ecological requirements in order to ascertain the relationship between stomatal control and plant performance. The experiment was conducted in a common garden environment resembling rainfall and temperature conditions that two of the three species are expected to encounter in the near future. In addition, gas exchange was monitored both at the leaf and at the whole-plant level using a transient-state closed chamber, which allowed us to model the response of the whole plant to increased air evaporative demand (AED). P. sylvestris was the species with lowest survival and performance. By contrast, P. halepensis showed no mortality, much higher growth (two orders of magnitude), carbon assimilation (ca. 14 fold higher) and stomatal conductance and water transpiration (ca. 4 fold higher) than the other two species. As a consequence, P. halepensis exhibited higher values of water-use efficiency than the rest of the species even at the highest values of AED. Overall, the results strongly support that the weaker stomatal control of P. halepensis, which is linked to lower stem water potential, enabled this species to maximize carbon uptake under drought stress and ultimately outperform the more water conservative P. nigra and P. sylvestris. These results suggest that under a hotter drought scenario P. nigra and P. sylvestris would very likely suffer increased mortality, whereas P. halepensis could maintain gas exchange and avoid water-induced growth limitation. This might ultimately foster an expansion of P. halepensis to higher latitudes and elevations.This work was supported by the projects ECOLPIN (AGL2011–24296) and Remedinal 3 (S2013/ MAE- 2719) of the Madrid Government, by a FPU fellowship from the Spanish Ministry of Education, Culture and Sport (FPU13/03410) to DS and by EU Marie Curie (FP7–2013-IOF-625988) fellowship to EPSC

Quantifying Sources of Variability in Infancy Research Using the Infant-Directed-Speech Preference

Psychological scientists have become increasingly concerned with issues related to methodology and replicability, and infancy researchers in particular face specific challenges related to replicability: For example, high-powered studies are difficult to conduct, testing conditions vary across labs, and different labs have access to different infant populations. Addressing these concerns, we report on a large-scale, multisite study aimed at (a) assessing the overall replicability of a single theoretically important phenomenon and (b) examining methodological, cultural, and developmental moderators. We focus on infants’ preference for infant-directed speech (IDS) over adult-directed speech (ADS). Stimuli of mothers speaking to their infants and to an adult in North American English were created using seminaturalistic laboratory-based audio recordings. Infants’ relative preference for IDS and ADS was assessed across 67 laboratories in North America, Europe, Australia, and Asia using the three common methods for measuring infants’ discrimination (head-turn preference, central fixation, and eye tracking). The overall meta-analytic effect size (Cohen’s d) was 0.35, 95% confidence interval = [0.29, 0.42], which was reliably above zero but smaller than the meta-analytic mean computed from previous literature (0.67). The IDS preference was significantly stronger in older children, in those children for whom the stimuli matched their native language and dialect, and in data from labs using the head-turn preference procedure. Together, these findings replicate the IDS preference but suggest that its magnitude is modulated by development, native-language experience, and testing procedure

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Modeling burned area in Europe with the Community Land Model

In this study, we present simulations of a burned area at a European scale for the period 1990-2009 conducted with the Community Land Model (CLM). By using statistics on fire counts and mean fire suppression time from the European Fire Database, we refined the parameterization of the functions describing human ignition/suppression, and we modified the description of biomass availability for fires. The results obtained with the modified model show an improvement of the description of the spatial an interannual variability of the burned area: the model bias is reduced by 45%, and the explained variance is increased by about 9% compared to the original parameterization of the model. The observed relationships between burned area, climate (temperature and precipitation), and aboveground biomass are also reproduced more accurately by the modified model. This is particularly relevant for the applicability of the model to simulate future fire regimes under different climate conditions. However, results showed an overestimation of the burned area for some European countries (e.g., Spain and France) and an underestimation in years with an extreme fire season in Mediterranean countries. Our results highlight the need for refining the parameterization of human ignition/suppression and fuel availability for regional application of fire models implemented in land surface models