Net primary productivity and litter decomposition rates in two distinct Amazonian peatlands

Measurements of net primary productivity (NPP) and litter decomposition from tropical peatlands are severely lacking, limiting our ability to parameterise and validate models of tropical peatland development and thereby make robust predictions of how these systems will respond to future environmental and climatic change. Here, we present total NPP (i.e., above- and below-ground) and decomposition data from two floristically and structurally distinct forested peatland sites within the Pastaza Marañón Foreland Basin, northern Peru, the largest tropical peatland area in Amazonia: (1) a palm (largely Mauritia flexuosa) dominated swamp forest and (2) a hardwood dominated swamp forest (known as ‘pole forest’, due to the abundance of thin-stemmed trees). Total NPP in the palm forest and hardwood-dominated forest (9.83 ± 1.43 and 7.34 ± 0.84 Mg C ha⁻¹ year⁻¹, respectively) was low compared with values reported for terra firme forest in the region (14.21–15.01 Mg C ha⁻¹ year⁻¹) and for tropical peatlands elsewhere (11.06 and 13.20 Mg C ha⁻¹ year⁻¹). Despite the similar total NPP of the two forest types, there were considerable differences in the distribution of NPP. Fine root NPP was seven times higher in the palm forest (4.56 ± 1.05 Mg C ha⁻¹ year⁻¹) than in the hardwood forest (0.61 ± 0.22 Mg C ha⁻¹ year⁻¹). Above-ground palm NPP, a frequently overlooked component, made large contributions to total NPP in the palm-dominated forest, accounting for 41% (14% in the hardwood-dominated forest). Conversely, Mauritia flexuosa litter decomposition rates were the same in both plots: highest for leaf material, followed by root and then stem material (21%, 77% and 86% of mass remaining after 1 year respectively for both plots). Our results suggest potential differences in these two peatland types' responses to climate and other environmental changes and will assist in future modelling studies of these systems

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