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Soil diversity, taxonomic classification and binning of BGCsNonpareil analysis estimated an abundance-weighted coverage of 85.3% for the 44.4 Gb used in the long-read assembly. To achieve 95% and 99% coverage, respectively, 250 Gb and 1.6 Tb of sequencing were predicted to be necessary. Alpha diversity was estimated at Nd = 21.6. Contigs were binned using CONCOCT, MaxBin2 and MetaBAT2, consensus bins were generated using metaWRAP refine and classified using GTDB-Tk. This yielded 114 bacterial bins with CheckM completeness  > 50% and contamination  More

If an endpoint of continued circulation (endemicity rather than eradication) seems likely, this still leaves us with questions about the range of outbreak sizes, their intensity and seasonality. Surprisingly, some basic epidemiological parameters for predicting these dynamical features are still uncertain. For example, R0, the reproductive number, which captures the infectiousness of the pathogen, is typically measured from the growth of the epidemic and is harder to estimate once non-pharmaceutical interventions (NPIs) are in place. Similarly, changes to R0 for evolved SARS- CoV-2 variants are difficult to ascertain given simultaneous changes to behaviour and interventions. It is not yet clear whether there is an evolutionary limit to strain infectiousness. To date, structural changes to the SARS-CoV-2 spike furin cleavage site7 as well as enhanced binding of the receptor binding domain to the human ACE2 receptor8 have been associated with enhanced transmissibility in variant strains, but in the longer term, transmission increases may saturate and viral evolution may modulate other aspects of disease transmission including host susceptibility. Nevertheless, any present or future changes to R0 will affect long-term epidemic dynamics, including the intensity of outbreaks and the age-structure of infections.The transmission of many respiratory pathogens varies seasonally, driven either by climatic factors or seasonal changes in behaviour such as schooling. The role of climate in driving transmission of SARS-CoV-2 is currently unclear: high susceptibility during the early pandemic likely limited any climate effect9, and statistical analyses of the climate-SARS-CoV-2 link have been confounded by trends in the data and regional differences in reporting and control measures. This has not been helped by the relatively short case time series (that is, just over a year’s worth of data) compared to typical climate–disease studies that look for climate links over many seasons. An alternative line of evidence comes from the four endemic coronaviruses, which exhibit seasonal wintertime outbreaks. It is possible that SARS-CoV-2 will follow suit. Disentangling the climate drivers of SARS-CoV-2 will become easier over time as both longer time series are available, and susceptibility declines9.A further question is the extent to which SARS-CoV-2 endemic dynamics will be affected by interactions with other circulating pathogens, including the endemic coronaviruses. Both modelling and laboratory work implies a degree of cross-immunity between coronaviruses10,11,12. The NPIs put in place to limit the spread of SARS-CoV-2 have also limited the circulation of many other pathogens, such that infection interactions have not been observed in current case trajectories13. However, as NPIs are relaxed, signatures of cross-species interactions will likely become increasingly visible.Beyond cross-immunity with other pathogens, the longitudinal trajectory of immunity, as depicted in Fig. 1, will play a crucial role in determining SARS-CoV-2 endemic dynamics14. For immunizing infections, susceptibility is driven by birth rates, and infections may be concentrated in younger age groups. For infections with waning immunity or antigenic evolution, susceptibility is driven by the rate at which immunity wanes or the rate the pathogen evolves as well as characteristics of secondary infections. The disease dynamics of pathogens with high rates of antigenic evolution are particularly hard to predict: evolved strains may have variable transmission rates and manifest variable immune responses. An analogy can be made with influenza, where the size and intensity of the seasonal influenza peak is typically very difficult to forecast15.The future course of SARS-CoV-2 remains uncertain. The next few months to a year represents a critical time where we will begin to develop an understanding of key parameters, such as the strength and duration of vaccinal and natural immunity, the seasonality of transmission and the possible interaction of SARS-CoV-2 with other circulating pathogens. In combination, these parameters will allow improved prediction of both long-term SARS-CoV-2 epidemic dynamics, as well as the likelihood of elimination and eradication. An area of particular focus will be the rate of antigenic evolution and the extent to which vaccines remain protective against evolved strains. In all scenarios, rapid and equitable distribution of vaccines presents the greatest hope for minimizing future severe outbreaks. More

Climate change mitigation and adaptation, including through nature-based measures, are urgently needed. Now mapping and valuation of global vegetated coastal and marine blue carbon ecosystems shows how interlinked countries are when dealing with climate change.Towards the end of the eighteenth century, Adam Smith’s famous The Wealth of Nations highlighted the role of the different aspects comprising a country’s wealth, including its natural resources or natural capital. Today, the ‘inclusive wealth’ concept, encompassing the different forms of capital which constitute the wealth of a country (natural, manufactured, human and social capital), expands this idea6. Blue carbon ecosystems are valuable natural capital assets. One way to value their worth is using the social cost of carbon (SCC), which is estimated through complex models that include physical and economic variables. The SCC values the ‘marginal’ damaging effects of an additional ton of CO2 emissions in the atmosphere, or the benefit of a removed ton of CO2 emissions, for society7. Greenhouse gas emissions to the atmosphere are a global problem; therefore, the SCC is a global estimate. Based on the assumption that climate change effects are felt differently in different countries, in 2018, Ricke et al.8 elaborated a new model to calculate these damages at the national level through the country-specific SCC (CSCC). To value blue carbon assets, the extent of each ecosystem, and how much carbon it sequesters and stores, have to be known. The areal extent is multiplied by the carbon burial rate of the blue carbon ecosystems in a specific geographical region — the precise species of mangroves, saltmarshes and seagrasses also plays a role in terms of carbon sequestration and storage rate — and by the chosen SCC. Uncertainty surrounding these factors is high because of the current lack of data on the precise extent of worldwide vegetated coastal and marine ecosystems, as well as their carbon sequestration and storage rates, and because of the uncertainty surrounding some of the chosen physical and economic variables used in the models estimating the SCC9. More

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