Anthropogenic disturbance in tropical forests can double biodiversity loss from deforestation

Concerted political attention has focused on reducing deforestation1,2,3, and this remains the cornerstone of most biodiversity conservation strategies4,5,6. However, maintaining forest cover may not reduce anthropogenic forest disturbances, which are rarely considered in conservation programmes6. These disturbances occur both within forests, including selective logging and wildfires7,8, and at the landscape level, through edge, area and isolation effects9. Until now, the combined effect of anthropogenic disturbance on the conservation value of remnant primary forests has remained unknown, making it impossible to assess the relative importance of forest disturbance and forest loss. Here we address these knowledge gaps using a large data set of plants, birds and dung beetles (1,538, 460 and 156 species, respectively) sampled in 36 catchments in the Brazilian state of Pará. Catchments retaining more than 69–80% forest cover lost more conservation value from disturbance than from forest loss. For example, a 20% loss of primary forest, the maximum level of deforestation allowed on Amazonian properties under Brazil’s Forest Code5, resulted in a 39–54% loss of conservation value: 96–171% more than expected without considering disturbance effects. We extrapolated the disturbance-mediated loss of conservation value throughout Pará, which covers 25% of the Brazilian Amazon. Although disturbed forests retained considerable conservation value compared with deforested areas, the toll of disturbance outside Pará’s strictly protected areas is equivalent to the loss of 92,000–139,000 km2 of primary forest. Even this lowest estimate is greater than the area deforested across the entire Brazilian Amazon between 2006 and 2015 (ref. 10). Species distribution models showed that both landscape and within-forest disturbances contributed to biodiversity loss, with the greatest negative effects on species of high conservation and functional value. These results demonstrate an urgent need for policy interventions that go beyond the maintenance of forest cover to safeguard the hyper-diversity of tropical forest ecosystems

Second rate or a second chance? Assessing biomass and biodiversity recovery in regenerating Amazonian forests

© 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. Secondary forests (SFs) regenerating on previously deforested land account for large, expanding areas of tropical forest cover. Given that tropical forests rank among Earth’s most important reservoirs of carbon and biodiversity, SFs play an increasingly pivotal role in the carbon cycle and as potential habitat for forest biota. Nevertheless, their capacity to regain the biotic attributes of undisturbed primary forests (UPFs) remains poorly understood. Here, we provide a comprehensive assessment of SF recovery, using extensive tropical biodiversity, biomass, and environmental datasets. These data, collected in 59 naturally regenerating SFs and 30 co-located UPFs in the eastern Amazon, cover >1,600 large- and small-stemmed plant, bird, and dung beetles species and a suite of forest structure, landscape context, and topoedaphic predictors. After up to 40 years of regeneration, the SFs we surveyed showed a high degree of biodiversity resilience, recovering, on average among taxa, 88% and 85% mean UPF species richness and composition, respectively. Across the first 20 years of succession, the period for which we have accurate SF age data, biomass recovered at 1.2% per year, equivalent to a carbon uptake rate of 2.25 Mg/ha per year, while, on average, species richness and composition recovered at 2.6% and 2.3% per year, respectively. For all taxonomic groups, biomass was strongly associated with SF species distributions. However, other variables describing habitat complexity—canopy cover and understory stem density—were equally important occurrence predictors for most taxa. Species responses to biomass revealed a successional transition at approximately 75 Mg/ha, marking the influx of high-conservation-value forest species. Overall, our results show that naturally regenerating SFs can accumulate substantial amounts of carbon and support many forest species. However, given that the surveyed SFs failed to return to a typical UPF state, SFs are not substitutes for UPFs

SARS-CoV-2 antibody dynamics in blood donors and COVID-19 epidemiology in eight Brazilian state capitals: A serial cross-sectional study

BACKGROUND: The COVID-19 situation in Brazil is complex due to large differences in the shape and size of regional epidemics. Understanding these patterns is crucial to understand future outbreaks of SARS-CoV-2 or other respiratory pathogens in the country. METHODS: We tested 97,950 blood donation samples for IgG antibodies from March 2020 to March 2021 in 8 of Brazil's most populous cities. Residential postal codes were used to obtain representative samples. Weekly age- and sex-specific seroprevalence were estimated by correcting the crude seroprevalence by test sensitivity, specificity, and antibody waning. RESULTS: The inferred attack rate of SARS-CoV-2 in December 2020, before the Gamma variant of concern (VOC) was dominant, ranged from 19.3% (95% credible interval [CrI] 17.5-21.2%) in Curitiba to 75.0% (95% CrI 70.8-80.3%) in Manaus. Seroprevalence was consistently smaller in women and donors older than 55 years. The age-specific infection fatality rate (IFR) differed between cities and consistently increased with age. The infection hospitalisation rate increased significantly during the Gamma-dominated second wave in Manaus, suggesting increased morbidity of the Gamma VOC compared to previous variants circulating in Manaus. The higher disease penetrance associated with the health system's collapse increased the overall IFR by a minimum factor of 2.91 (95% CrI 2.43-3.53). CONCLUSIONS: These results highlight the utility of blood donor serosurveillance to track epidemic maturity and demonstrate demographic and spatial heterogeneity in SARS-CoV-2 spread. FUNDING: This work was supported by Itaú Unibanco 'Todos pela Saude' program; FAPESP (grants 18/14389-0, 2019/21585-0); Wellcome Trust and Royal Society Sir Henry Dale Fellowship 204311/Z/16/Z; the Gates Foundation (INV- 034540 and INV-034652); REDS-IV-P (grant HHSN268201100007I); the UK Medical Research Council (MR/S0195/1, MR/V038109/1); CAPES; CNPq (304714/2018-6); Fundação Faculdade de Medicina; Programa Inova Fiocruz-CE/Funcap - Edital 01/2020 Number: FIO-0167-00065.01.00/20 SPU N°06531047/2020; JBS - Fazer o bem faz bem

Pervasive gaps in Amazonian ecological research.

This is the final version. Available from Elsevier via the DOI in this record. Data and code availability: • Metadata have been deposited at Zenodo and are publicly available as of the date of publication. DOIs are listed in the key resources table. • All original code has been deposited at Zenodo and is publicly available as of the date of publication. DOIs are listed in the key resources table. • Any additional information required to reanalyse the data reported in this paper is available from the lead contact upon request.Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%-18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost.Conselho Nacional de Desenvolvimento Científico (CNPq)Conselho Nacional de Desenvolvimento Científico (CNPq)São Paulo Research Foundation (FAPESP)São Paulo Research Foundation (FAPESP)São Paulo Research Foundation (FAPESP)São Paulo Research Foundation (FAPESP)Natural Environment Research Council (NERC)University of Bristol (PolicyBristol)University of Bristol Climate and Net Zero Impact AwardsUniversity of Bristol Elizabeth Blackwell Institute Rapid Research FundingNatural Environment Research Council (NERC)European Union’s Horizon 202

Poor prospects for avian biodiversity in amazonian oil palm

Expansion of oil palm plantations across the humid tropics has precipitated massive loss of tropical forest habitats and their associated speciose biotas. Oil palm plantation monocultures have been identified as an emerging threat to Amazonian biodiversity, but there are no quantitative studies exploring the impact of these plantations on the biome’s biota. Understanding these impacts is extremely important given the rapid projected expansion of oil palm cultivation in the basin. Here we investigate the biodiversity value of oil palm plantations in comparison with other dominant regional land-uses in Eastern Amazonia. We carried out bird surveys in oil palm plantations of varying ages, primary and secondary forests, and cattle pastures. We found that oil palm plantations retained impoverished avian communities with a similar species composition to pastures and agrarian land-uses and did not offer habitat for most forest-associated species, including restricted range species and species of conservation concern. On the other hand, the forests that the oil palm companies are legally obliged to protect hosted a relatively species-rich community including several globally-threatened bird species. We consider oil palm to be no less detrimental to regional biodiversity than other agricultural land-uses and that political pressure exerted by large landowners to allow oil palm to count as a substitute for native forest vegetation in private landholdings with forest restoration deficits would have dire consequences for regional biodiversity

Predicting SARS-CoV-2 variant spread in a completely seropositive population using semi-quantitative antibody measurements in blood donors

SARS-CoV-2 serologic surveys estimate the proportion of the population with antibodies against historical variants, which nears 100% in many settings. New approaches are required to fully exploit serosurvey data. Using a SARS-CoV-2 anti-Spike (S) protein chemiluminescent microparticle assay, we attained a semi-quantitative measurement of population IgG titers in serial cross-sectional monthly samples of blood donations across seven Brazilian state capitals (March 2021–November 2021). Using an ecological analysis, we assessed the contributions of prior attack rate and vaccination to antibody titer. We compared anti-S titer across the seven cities during the growth phase of the Delta variant and used this to predict the resulting age-standardized incidence of severe COVID-19 cases. We tested ~780 samples per month, per location. Seroprevalence rose to >95% across all seven capitals by November 2021. Driven by vaccination, mean antibody titer increased 16-fold over the study, with the greatest increases occurring in cities with the highest prior attack rates. Mean anti-S IgG was strongly correlated (adjusted R2 = 0.89) with the number of severe cases caused by Delta. Semi-quantitative anti-S antibody titers are informative about prior exposure and vaccination coverage and may also indicate the potential impact of future SARS-CoV-2 variants