Cost-Effectiveness of Group-Based Outpatient Physical Therapy After Total Knee Replacement: Results From the Economic Evaluation Alongside the ARENA Multicenter Randomized Controlled Trial

Objective To assess the cost-utility and cost-effectiveness of a group-based outpatient physical therapy intervention delivered six-weeks after primary total knee replacement (TKR) compared with usual care, alongside the Activity-orientated REhabilitation following kNee Arthroplasty (ARENA) multi-centre randomised controlled trial. Methods The economic analyses were performed from the perspective of the health and social care payer. We collected resource use for health and social care and productivity losses, and patient outcomes for 12 months after surgery to derive costs and quality-adjusted life-years (QALYs). Results were expressed in incremental cost-effectiveness ratios (ICERs), and incremental net monetary benefit statistics (INMBs) for a society willing-to-pay £20,000 per QALY gained, with sensitivity analyses to model specification and perspective. Results ARENA physical therapy classes cost, on average, £179 (SD=£39) per patient. Treatment in the year following surgery cost, on average, £1,739 (95%CI -£742, £4,221) per patient in the intervention group (n=89), an additional £346 (95%CI £38, £653) compared with usual care (n=91, £1,393;95%CI -£780, £3568). QALY benefits were 0.0506 higher (95%CI 0.009, 0.09) in the intervention group, corresponding to an additional 19 days in perfect health. The ICER for the intervention was £6,842 per QALY gained and the INMB was £665 (, 95%CI £139, £1,191) with a 92% probability of being cost-effective, and no less than 73% in all sensitivity analysis scenarios. Conclusion The addition of group-based outpatient physical therapy classes to usual care improves quality-of-life and is a cost-effective treatment option following TKR for a society willing-to-pay £20,000 per QALY gained

Multicentre observational study on multisystem inflammatory syndrome related to COVID-19 in Argentina

Background: The impact of the pediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS) in low- and middle-income countries remains poorly understood. Our aim was to understand the characteristics and outcomes of PIMS-TS in Argentina. Methods: This observational, prospective, and retrospective multicenter study enrolled patients younger than 18 years-old manifesting PIMS-TS, Kawasaki disease (KD) or Kawasaki shock syndrome (KSS) between March 2020 and May 2021. Patients were followed-up until hospital discharge or death (one case). The primary outcome was pediatric intensive care unit (PICU) admission. Multiple logistic regression was used to identify variables predicting PICU admission. Results: Eighty-one percent, 82%, and 14% of the 176 enrolled patients fulfilled the suspect case criteria for PIMS-TS, KD, and KSS, respectively. Temporal association with SARS-CoV-2 was confirmed in 85% of the patients and 38% were admitted to the PICU. The more common clinical manifestations were fever, abdominal pain, rash, and conjunctival injection. Lymphopenia was more common among PICU-admitted patients (87% vs. 51%, p < 0.0001), who also showed a lower platelet count and higher plasmatic levels of inflammatory and cardiac markers. Mitral valve insufficiency, left ventricular wall motion alterations, pericardial effusion, and coronary artery alterations were observed in 30%, 30%, 19.8%, and 18.6% of the patients, respectively. Days to initiation of treatment, rash, lymphopenia, and low platelet count were significant independent contributions to PICU admission. Conclusion: Rates of severe outcomes of PIMS-TS in the present study agreed with those observed in high-income countries. Together with other published studies, this work helps clinicians to better understand this novel clinical entity.Fil: Vainstein, Eduardo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Baleani, Silvia. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Urrutia, Luis. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Affranchino, Nicolás. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Ackerman, Judith. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños Pedro Elizalde (ex Casa Cuna); ArgentinaFil: Cazalas, Mariana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Goldsman, Alejandro. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Sardella, Angela. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Tolin, Ana Laura. Gobierno de la Provincia de Mendoza. Hospital Pediátrico Humberto Notti; ArgentinaFil: Goldaracena, Pablo. Provincia de Buenos Aires. Ministerio de Salud. Hospital de Niños "Sor María Ludovica" de La Plata; ArgentinaFil: Fabi, Mariana. Provincia de Buenos Aires. Ministerio de Salud. Hospital de Niños "Sor María Ludovica" de La Plata; ArgentinaFil: Cosentino, Mariana. Hospital Británico de Buenos Aires; ArgentinaFil: Magliola, Ricardo. Hospital Británico de Buenos Aires; ArgentinaFil: Roggiero, Gustavo. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic; ArgentinaFil: Manso, Paula. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic; ArgentinaFil: Triguy, Jésica. Gobierno de la Provincia de Mendoza. Hospital Pediátrico Humberto Notti; ArgentinaFil: Ballester, Celeste. Gobierno de la Provincia de Mendoza. Hospital Pediátrico Humberto Notti; ArgentinaFil: Cervetto, Vanesa. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños Pedro Elizalde (ex Casa Cuna); ArgentinaFil: Vaccarello, María. Sanatorio de la Trinidad; ArgentinaFil: De Carli, Domingo Norberto. Clínica del Niño de Quilmes; ArgentinaFil: De Carli, Maria Estela. Clínica del Niño de Quilmes; ArgentinaFil: Ciotti, Ana Laura. Hospital Nacional Profesor Alejandro Posadas; ArgentinaFil: Sicurello, María Irene. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Rios Leiva, Cecilia. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Villalba, Claudia. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Hortas, María. Sanatorio de la Trinidad; ArgentinaFil: Peña, Sonia. Gobierno de la Provincia de Mendoza. Hospital Pediátrico Humberto Notti; ArgentinaFil: González, Gabriela. Gobierno de la Provincia de Mendoza. Hospital Pediátrico Humberto Notti; ArgentinaFil: Zold, Camila Lidia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; ArgentinaFil: Murer, Mario Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; ArgentinaFil: Grippo, M.. No especifíca;Fil: Vázquez, H.. No especifíca;Fil: Morós, C.. No especifíca;Fil: Di Santo, M.. No especifíca;Fil: Villa, A.. No especifíca;Fil: Lazota, P.. No especifíca;Fil: Foti, M.. No especifíca;Fil: Napoli, N.. No especifíca;Fil: Katsikas, M. M.. No especifíca;Fil: Tonello, L.. No especifíca;Fil: Peña, J.. No especifíca;Fil: Etcheverry, M.. No especifíca;Fil: Iglesias, D.. No especifíca;Fil: Alcalde, A. L.. No especifíca;Fil: Bruera, M.J.. No especifíca;Fil: Bruzzo, V.. No especifíca;Fil: Giordano, P.. No especifíca;Fil: Pena Acero, F.. No especifíca;Fil: Netri Pelandi, G.. No especifíca;Fil: Pastaro, D.. No especifíca;Fil: Bleiz, J.. No especifíca;Fil: Rodríguez, M. F.. No especifíca;Fil: Laghezza, L.. No especifíca;Fil: Molina, M. B.. No especifíca;Fil: Patynok, N.. No especifíca;Fil: Chatelain, M. S.. No especifíca;Fil: Aguilar, M. J.. No especifíca;Fil: Gamboa, J.. No especifíca;Fil: Cervan, M.. No especifíca;Fil: Ruggeri, A.. No especifíca;Fil: Marinelli, I.. No especifíca;Fil: Checcacci, E.. No especifíca;Fil: Meregalli, C.. No especifíca;Fil: Damksy Barbosa, J.. No especifíca;Fil: Fernie, L.. No especifíca;Fil: Fernández, M. J.. No especifíca;Fil: Saenz Tejeira, M.M.. No especifíca;Fil: Cereigido, C.. No especifíca;Fil: Nunell, A.. No especifíca;Fil: Villar, D.. No especifíca;Fil: Mansilla, A. D.. No especifíca;Fil: Darduin, M. D.. No especifíca

Understanding unsuccessful attempts to quit smoking: a social phenomenology approach

Abstract OBJECTIVE The aim of this paper is to understand the experience of smokers in view of unsuccessful attempts to quit smoking. METHOD This study is based on social phenomenology. Between November and December of 2014, nine interviews were conducted with people that had attempted to quit smoking. The content of these interviews was analyzed and discussed based on the related literature. RESULTS Unsuccessful attempts to quit smoking are related to tobacco addiction; cigarettes are seen as a support to cope with everyday stressful situations. Attempts to quit the smoking habits were based on the need of health improvement and insistence of family and friends. Smokers reported the use of habit cessation strategies learned in support groups, but they also express expectation of specialized psychological support. CONCLUSION The study points out the need to expand the strategies of approaching smokers, and reinforcing psychological support in order to achieve success in the attempt to quit smoking

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Geographic patterns of tree dispersal modes in Amazonia and their ecological correlates

Aim: To investigate the geographic patterns and ecological correlates in the geographic distribution of the most common tree dispersal modes in Amazonia (endozoochory, synzoochory, anemochory and hydrochory). We examined if the proportional abundance of these dispersal modes could be explained by the availability of dispersal agents (disperser-availability hypothesis) and/or the availability of resources for constructing zoochorous fruits (resource-availability hypothesis). Time period: Tree-inventory plots established between 1934 and 2019. Major taxa studied: Trees with a diameter at breast height (DBH) ≥ 9.55 cm. Location: Amazonia, here defined as the lowland rain forests of the Amazon River basin and the Guiana Shield. Methods: We assigned dispersal modes to a total of 5433 species and morphospecies within 1877 tree-inventory plots across terra-firme, seasonally flooded, and permanently flooded forests. We investigated geographic patterns in the proportional abundance of dispersal modes. We performed an abundance-weighted mean pairwise distance (MPD) test and fit generalized linear models (GLMs) to explain the geographic distribution of dispersal modes. Results: Anemochory was significantly, positively associated with mean annual wind speed, and hydrochory was significantly higher in flooded forests. Dispersal modes did not consistently show significant associations with the availability of resources for constructing zoochorous fruits. A lower dissimilarity in dispersal modes, resulting from a higher dominance of endozoochory, occurred in terra-firme forests (excluding podzols) compared to flooded forests. Main conclusions: The disperser-availability hypothesis was well supported for abiotic dispersal modes (anemochory and hydrochory). The availability of resources for constructing zoochorous fruits seems an unlikely explanation for the distribution of dispersal modes in Amazonia. The association between frugivores and the proportional abundance of zoochory requires further research, as tree recruitment not only depends on dispersal vectors but also on conditions that favour or limit seedling recruitment across forest types

Geography and ecology shape the phylogenetic composition of Amazonian tree communities

AimAmazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types.LocationAmazonia.TaxonAngiosperms (Magnoliids; Monocots; Eudicots).MethodsData for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran's eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny.ResultsIn the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R2 = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R2 = 28%). A greater number of lineages were significant indicators of geographic regions than forest types.Main ConclusionNumerous tree lineages, including some ancient ones (&gt;66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions

Geography and ecology shape the phylogenetic composition of Amazonian tree communities

Aim: Amazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types. Location: Amazonia. Taxon: Angiosperms (Magnoliids; Monocots; Eudicots). Methods: Data for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran\u27s eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny. Results: In the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R$^{2}$ = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R$^{2}$ = 28%). A greater number of lineages were significant indicators of geographic regions than forest types. Main Conclusion: Numerous tree lineages, including some ancient ones (>66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

Constraints on the structure and seasonal variations of Triton's atmosphere from the 5 October 2017 stellar occultation and previous observations

Context. A stellar occultation by Neptune's main satellite, Triton, was observed on 5 October 2017 from Europe, North Africa, and the USA. We derived 90 light curves from this event, 42 of which yielded a central flash detection. Aims. We aimed at constraining Triton's atmospheric structure and the seasonal variations of its atmospheric pressure since the Voyager 2 epoch (1989). We also derived the shape of the lower atmosphere from central flash analysis. Methods. We used Abel inversions and direct ray-tracing code to provide the density, pressure, and temperature profiles in the altitude range similar to 8 km to similar to 190 km, corresponding to pressure levels from 9 mu bar down to a few nanobars. Results. (i) A pressure of 1.18 +/- 0.03 mu bar is found at a reference radius of 1400 km (47 km altitude). (ii) A new analysis of the Voyager 2 radio science occultation shows that this is consistent with an extrapolation of pressure down to the surface pressure obtained in 1989. (iii) A survey of occultations obtained between 1989 and 2017 suggests that an enhancement in surface pressure as reported during the 1990s might be real, but debatable, due to very few high S/N light curves and data accessible for reanalysis. The volatile transport model analysed supports a moderate increase in surface pressure, with a maximum value around 2005-2015 no higher than 23 mu bar. The pressures observed in 1995-1997 and 2017 appear mutually inconsistent with the volatile transport model presented here. (iv) The central flash structure does not show evidence of an atmospheric distortion. We find an upper limit of 0.0011 for the apparent oblateness of the atmosphere near the 8 km altitude.J.M.O. acknowledges financial support from the Portuguese Foundation for Science and Technology (FCT) and the European Social Fund (ESF) through the PhD grant SFRH/BD/131700/2017. The work leading to these results has received funding from the European Research Council under the European Community's H2020 2014-2021 ERC grant Agreement nffi 669416 "Lucky Star". We thank S. Para who supported some travels to observe the 5 October 2017 occultation. T.B. was supported for this research by an appointment to the National Aeronautics and Space Administration (NASA) Post-Doctoral Program at the Ames Research Center administered by Universities Space Research Association (USRA) through a contract with NASA. We acknowledge useful exchanges with Mark Gurwell on the ALMA CO observations. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium).Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. J.L.O., P.S.-S., N.M. and R.D. acknowledge financial support from the State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa" award to the Instituto de Astrofisica de Andalucia (SEV-2017-0709), they also acknowledge the financial support by the Spanish grant AYA-2017-84637-R and the Proyecto de Excelencia de la Junta de Andalucia J.A. 2012-FQM1776. The research leading to these results has received funding from the European Union's Horizon 2020 Research and Innovation Programme, under Grant Agreement no. 687378, as part of the project "Small Bodies Near and Far" (SBNAF). P.S.-S. acknowledges financial support by the Spanish grant AYA-RTI2018-098657-J-I00 "LEO-SBNAF". The work was partially based on observations made at the Laboratorio Nacional de Astrofisica (LNA), Itajuba-MG, Brazil. The following authors acknowledge the respective CNPq grants: F.B.-R. 309578/2017-5; R.V.-M. 304544/2017-5, 401903/2016-8; J.I.B.C. 308150/2016-3 and 305917/2019-6; M.A. 427700/20183, 310683/2017-3, 473002/2013-2. This study was financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior -Brasil (CAPES) -Finance Code 001 and the National Institute of Science and Technology of the e-Universe project (INCT do e-Universo, CNPq grant 465376/2014-2). G.B.R. acknowledges CAPES-FAPERJ/PAPDRJ grant E26/203.173/2016 and CAPES-PRINT/UNESP grant 88887.571156/2020-00, M.A. FAPERJ grant E26/111.488/2013 and A.R.G.Jr. FAPESP grant 2018/11239-8. B.E.M. thanks CNPq 150612/2020-6 and CAPES/Cofecub-394/2016-05 grants. Part of the photometric data used in this study were collected in the frame of the photometric observations with the robotic and remotely controlled telescope at the University of Athens Observatory (UOAO; Gazeas 2016). The 2.3 m Aristarchos telescope is operated on Helmos Observatory by the Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens. Observations with the 2.3 m Aristarchos telescope were carried out under OPTICON programme. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 730890. This material reflects only the authors views and the Commission is not liable for any use that may be made of the information contained therein. The 1. 2m Kryoneri telescope is operated by the Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens. The Astronomical Observatory of the Autonomous Region of the Aosta Valley (OAVdA) is managed by the Fondazione Clement Fillietroz-ONLUS, which is supported by the Regional Government of the Aosta Valley, the Town Municipality of Nus and the "Unite des Communes valdotaines Mont-Emilius". The 0.81 m Main Telescope at the OAVdA was upgraded thanks to a Shoemaker NEO Grant 2013 from The Planetary Society. D.C. and J.M.C. acknowledge funds from a 2017 'Research and Education' grant from Fondazione CRT-Cassa di Risparmio di Torino. P.M. acknowledges support from the Portuguese Fundacao para a Ciencia e a Tecnologia ref. PTDC/FISAST/29942/2017 through national funds and by FEDER through COMPETE 2020 (ref. POCI010145 FEDER007672). F.J. acknowledges Jean Luc Plouvier for his help. S.J.F. and C.A. would like to thank the UCL student support observers: Helen Dai, Elise Darragh-Ford, Ross Dobson, Max Hipperson, Edward Kerr-Dineen, Isaac Langley, Emese Meder, Roman Gerasimov, Javier Sanjuan, and Manasvee Saraf. We are grateful to the CAHA, OSN and La Hita Observatory staffs. This research is partially based on observations collected at Centro Astronomico HispanoAleman (CAHA) at Calar Alto, operated jointly by Junta de Andalucia and Consejo Superior de Investigaciones Cientificas (IAA-CSIC). This research was also partially based on observation carried out at the Observatorio de Sierra Nevada (OSN) operated by Instituto de Astrofisica de Andalucia (CSIC). This article is also based on observations made with the Liverpool Telescope operated on the island of La Palma by Liverpool John Moores University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias with financial support from the UK Science and Technology Facilities Council. Partially based on observations made with the Tx40 and Excalibur telescopes at the Observatorio Astrofisico de Javalambre in Teruel, a Spanish Infraestructura Cientifico-Tecnica Singular (ICTS) owned, managed and operated by the Centro de Estudios de Fisica del Cosmos de Aragon (CEFCA). Tx40 and Excalibur are funded with the Fondos de Inversiones de Teruel (FITE). A.R.R. would like to thank Gustavo Roman for the mechanical adaptation of the camera to the telescope to allow for the observation to be recorded. R.H., J.F.R., S.P.H. and A.S.L. have been supported by the Spanish projects AYA2015-65041P and PID2019-109467GB-100 (MINECO/FEDER, UE) and Grupos Gobierno Vasco IT1366-19. Our great thanks to Omar Hila and their collaborators in Atlas Golf Marrakech Observatory for providing access to the T60cm telescope. TRAPPIST is a project funded by the Belgian Fonds (National) de la Recherche Scientifique (F.R.S.-FNRS) under grant PDR T.0120.21. TRAPPIST-North is a project funded by the University of Liege, and performed in collaboration with Cadi Ayyad University of Marrakesh. E.J. is a FNRS Senior Research Associate

Estimating the global conservation status of more than 15,000 Amazonian tree species

Estimates of extinction risk for Amazonian plant and animal species are rare and not often incorporated into land-use policy and conservation planning. We overlay spatial distribution models with historical and projected deforestation to show that at least 36% and up to 57% of all Amazonian tree species are likely to qualify as globally threatened under International Union for Conservation of Nature (IUCN) Red List criteria. If confirmed, these results would increase the number of threatened plant species on Earth by 22%. We show that the trends observed in Amazonia apply to trees throughout the tropics, and we predict thatmost of the world’s >40,000 tropical tree species now qualify as globally threatened. A gap analysis suggests that existing Amazonian protected areas and indigenous territories will protect viable populations of most threatened species if these areas suffer no further degradation, highlighting the key roles that protected areas, indigenous peoples, and improved governance can play in preventing large-scale extinctions in the tropics in this century