Brazil currently has one of the fastest growing SARS-CoV-2 epidemics in the world. Owing to limited available data, assessments of the impact of non-pharmaceutical interventions (NPIs) on virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1–1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within-state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average travelled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil, and provide evidence that current interventions remain insufficient to keep virus transmission under control in the country.

Byrsonima is the third largest genus (about 200 species) in the Malpighiaceae family, and one of the most common in Brazilian savannas. However, there is no molecular phylogeny available for the genus and taxonomic uncertainties at the generic and family level still remain. Herein, we sequenced the complete chloroplast genome of B. coccolobifolia and B. crassifolia, the first ones described for Malpighiaceae, and performed comparative analyses with sequences previously published for other families in the order Malpighiales. The chloroplast genomes assembled had a similar structure, gene content and organization, even when compared with species from other families. Chloroplast genomes ranged between 160,212 bp in B. crassifolia and 160,329 bp in B. coccolobifolia, both containing 115 genes (four ribosomal RNA genes, 28 tRNA genes and 83 protein-coding genes). We also identified sequences with high divergence that might be informative for phylogenetic inferences in the Malpighiales order, Malpighiaceae family and within the genus Byrsonima. The phylogenetic reconstruction of Malpighiales with these regions highlighted their utility for phylogenetic studies. The comparative analyses among species in Malpighiales provided insights into the chloroplast genome evolution in this order, including the presence/absence of three genes (infA, rpl32 and rps16) and two pseudogenes (ycf1 and rps19).

Brazil currently has one of the fastest growing SARS-CoV-2 epidemics in the world. Due to limited available data, assessments of the impact of non-pharmaceutical interventions (NPIs) on virus transmission and epidemic spread remain challenging. We investigate the impact of NPIs in Brazil using epidemiological, mobility and genomic data. Mobility-driven transmission models for Sao Paulo and Rio de Janeiro cities show that the reproduction number (Rt) reached below 1 following NPIs but slowly increased to values between 1 to 1.3 (1.0 - -1.6). Genome sequencing of 427 new genomes and analysis of a geographically representative genomic dataset from 21 of the 27 Brazilian states identified >100 international introductions of SARS-CoV-2 in Brazil. We estimate that three clades introduced from Europe emerged between 22 and 27 February 2020, and were already well-established before the implementation of NPIs and travel bans. During this first phase of the epidemic establishment of SARS-CoV-2 in Brazil, we find that the virus spread mostly locally and within-state borders. Despite sharp decreases in national air travel during this period, we detected a 25% increase in the average distance travelled by air passengers during this time period. This coincided with the spread of SARS-CoV-2 from large urban centers to the rest of the country. In conclusion, our results shed light on the role of large and highly connected populated centres in the rapid ignition and establishment of SARS-CoV-2, and provide evidence that current interventions remain insufficient to keep virus transmission under control in Brazil.

Despite the importance of climate‐adjusted provenancing to mitigate the effects of environmental change, climatic considerations alone are insufficient when restoring highly degraded sites. Here we propose a comprehensive landscape genomic approach to assist the restoration of moderately disturbed and highly degraded sites. To illustrate it we employ genomic data sets comprising thousands of single nucleotide polymorphisms from two plant species suitable for the restoration of iron‐rich Amazonian Savannas. We first use a subset of neutral loci to assess genetic structure and determine the genetic neighbourhood size. We then identify genotype‐phenotype‐environment associations, map adaptive genetic variation, and predict adaptive genotypes for restoration sites. Whereas local provenances were found optimal to restore a moderately disturbed site, a mixture of genotypes seemed the most promising strategy to recover a highly degraded mining site. We discuss how our results can help define site‐adjusted provenancing strategies, and argue that our methods can be more broadly applied to assist other restoration initiatives.

Despite the importance of climate-adjusted provenancing to mitigate the effects of climate change, climatic considerations alone are insufficient when restoring highly degraded sites. Here we employ a comprehensive landscape genomic approach to assist the restoration of moderately disturbed and highly degraded sites. Relying on genotyping-by-sequencing we identified thousands of single nucleotide polymorphisms in two plant species of special interest for the restoration of iron-rich Amazon Savannas from the Eastern Amazon. We first used a subset of neutral loci to assess genetic structure and determine the genetic neighborhood size, and then combined uni-variate and multivariate methods to identify genotype-environment and genotype-phenotype associations, representing local adaptations. We then mapped adaptive genetic variation and predicted adaptive genotypes for both restoration sites. Whereas local provenances where found optimal to restore the moderately disturbed site, a mixture of genotypes was the most promising strategy to recover a highly degraded mining site, to which local provenances were not adapted. We discuss how our results can help define site-adjusted provenancing strategies and argue that our methods can be more broadly applied to assist other restoration and rehabilitation initiatives.