Governments have committed to conserving ≥17% of terrestrial and ≥10% of marine environments globally, especially “areas of particular importance for biodiversity” through “ecologically representative” Protected Area (PA) systems or other “area‐based conservation measures”, while individual countries have committed to conserve 3–50% of their land area. We estimate that PAs currently cover 14.6% of terrestrial and 2.8% of marine extent, but 59–68% of ecoregions, 77–78% of important sites for biodiversity, and 57% of 25,380 species have inadequate coverage. The existing 19.7 million km2 terrestrial PA network needs only 3.3 million km2 to be added to achieve 17% terrestrial coverage. However, it would require nearly doubling to achieve, cost‐efficiently, coverage targets for all countries, ecoregions, important sites, and species. Poorer countries have the largest relative shortfalls. Such extensive and rapid expansion of formal PAs is unlikely to be achievable. Greater focus is therefore needed on alternative approaches, including community‐ and privately managed sites and other effective area‐based conservation measures.

Birds have been comprehensively assessed on the International Union for Conservation of Nature (IUCN) Red List more times than any other taxonomic group. However, to date, generation lengths have not been systematically estimated to scale population trends when undertaking assessments, as required by the criteria of the IUCN Red List. We compiled information from major databases of published life-history and trait data for all birds and imputed missing life-history data as a function of species traits with generalized linear mixed models. Generation lengths were derived for all species, based on our modeled values of age at first breeding, maximum longevity, and annual adult survival. The resulting generation lengths varied from 1.42 to 27.87 years (median 2.99). Most species (61%) had generation lengths <3.33 years, meaning that the period of 3 generations-over which population declines are assessed under criterion A-was <10 years, which is the value used for IUCN Red List assessments of species with short generation times. For these species, our trait-informed estimates of generation length suggested that 10 years is a robust precautionary value for threat assessment. In other cases, however, for whole families, genera, or individual species, generation length had a substantial impact on their estimated extinction risk, resulting in higher extinction risk in long-lived species than in short-lived species. Although our approach effectively addressed data gaps, generation lengths for some species may have been underestimated due to a paucity of life-history data. Overall, our results will strengthen future extinction-risk assessments and augment key databases of avian life-history and trait data.

Introduction The diagnosis of COVID-19 is normally based on the qualitative detection of viral nucleic acid sequences. Properties of the host response are not measured but are key in determining outcome. Although metabolic profiles are well suited to capture host state, most metabolomics studies are either underpowered, measure only a restricted subset of metabolites, compare infected individuals against uninfected control cohorts that are not suitably matched, or do not provide a compact predictive model. Objectives Here we provide a well-powered, untargeted metabolomics assessment of 120 COVID-19 patient samples acquired at hospital admission. The study aims to predict the patient’s infection severity (i.e., mild or severe) and potential outcome (i.e., discharged or deceased). Methods High resolution untargeted UHPLC-MS/MS analysis was performed on patient serum using both positive and negative ionization modes. A subset of 20 intermediary metabolites predictive of severity or outcome were selected based on univariate statistical significance and a multiple predictor Bayesian logistic regression model was created. Results The predictors were selected for their relevant biological function and include deoxycytidine and ureidopropionate (indirectly reflecting viral load), kynurenine (reflecting host inflammatory response), and multiple short chain acylcarnitines (energy metabolism) among others. Currently, this approach predicts outcome and severity with a Monte Carlo cross validated area under the ROC curve of 0.792 (SD 0.09) and 0.793 (SD 0.08), respectively. A blind validation study on an additional 90 patients predicted outcome and severity at ROC AUC of 0.83 (CI 0.74–0.91) and 0.76 (CI 0.67–0.86). Conclusion Prognostic tests based on the markers discussed in this paper could allow improvement in the planning of COVID-19 patient treatment.

Biodiversity is declining, with direct and indirect effects on ecosystem functions and services that are poorly quantified. Here, we develop the first global assessment of trends in pollinators, focusing on pollinating birds and mammals. A Red List Index for these species shows that, overall, pollinating bird and mammal species are deteriorating in status, with more species moving toward extinction than away from it. On average, 2.5 species per year have moved one Red List category toward extinction in recent decades, representing a substantial increase in the extinction risk across this set of species. This may be impacting the delivery of benefits that these species provide to people. We recommend that the index be expanded to include taxonomic groups that contribute more significantly to pollination, such as bees, wasps, and butterflies, thereby giving a more complete picture of the state of pollinating species worldwide.

Organic agriculture promotes sustainability compared to conventional agriculture. However, the multifunctional sustainability benefits of organic farms might be mediated by landscape context. Assessing how landscape context affects sustainability may aid in targeting organic production to landscapes that promote high biodiversity, crop yields, and profitability. We addressed this using a meta-analysis spanning 60 crop types on six continents that assessed whether landscape context affected biodiversity, yield, and profitability of organic vs. conventional agroecosystems. We considered landscape metrics reflecting landscape composition (percent cropland), compositional heterogeneity (number and diversity of cover types), and configurational heterogeneity (spatial arrangement of cover types) across our study systems. Organic sites had greater biodiversity (34%) and profits (50%) than conventional sites, despite lower yields (18%). Biodiversity gains increased as average crop field size in the landscape increased, suggesting organic farms provide a “refuge” in intensive landscapes. In contrast, as crop field size increased, yield gaps between organic and conventional farms increased and profitability benefits of organic farming decreased. Profitability of organic systems, which we were only able to measure for studies conducted in the United States, varied across landscapes in conjunction with production costs and price premiums, suggesting socioeconomic factors mediated profitability. Our results show biodiversity benefits of organic farming respond differently to landscape context compared to yield and profitability benefits, suggesting these sustainability metrics are decoupled. More broadly, our results show that the ecological, but not the economic, sustainability benefits of organic agriculture are most pronounced in more intensive agricultural landscapes.