Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

First Latin American clinical practice guidelines for the treatment of systemic lupus erythematosus: Latin American Group for the Study of Lupus (GLADEL, Grupo Latino Americano de Estudio del Lupus)-Pan-American League of Associations of Rheumatology (PANLAR)

Systemic lupus erythematosus (SLE), a complex and heterogeneous autoimmune disease, represents a significant challenge for both diagnosis and treatment. Patients with SLE in Latin America face special problems that should be considered when therapeutic guidelines are developed. The objective of the study is to develop clinical practice guidelines for Latin American patients with lupus. Two independent teams (rheumatologists with experience in lupus management and methodologists) had an initial meeting in Panama City, Panama, in April 2016. They selected a list of questions for the clinical problems most commonly seen in Latin American patients with SLE. These were addressed with the best available evidence and summarised in a standardised format following the Grading of Recommendations Assessment, Development and Evaluation approach. All preliminary findings were discussed in a second face-to-face meeting in Washington, DC, in November 2016. As a result, nine organ/system sections are presented with the main findings; an 'overarching' treatment approach was added. Special emphasis was made on regional implementation issues. Best pharmacologic options were examined for musculoskeletal, mucocutaneous, kidney, cardiac, pulmonary, neuropsychiatric, haematological manifestations and the antiphospholipid syndrome. The roles of main therapeutic options (ie, glucocorticoids, antimalarials, immunosuppressant agents, therapeutic plasma exchange, belimumab, rituximab, abatacept, low-dose aspirin and anticoagulants) were summarised in each section. In all cases, benefits and harms, certainty of the evidence, values and preferences, feasibility, acceptability and equity issues were considered to produce a recommendation with special focus on ethnic and socioeconomic aspects. Guidelines for Latin American patients with lupus have been developed and could be used in similar settings.Fil: Pons Estel, Bernardo A.. Centro Regional de Enfermedades Autoinmunes y Reumáticas; ArgentinaFil: Bonfa, Eloisa. Universidade de Sao Paulo; BrasilFil: Soriano, Enrique R.. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Cardiel, Mario H.. Centro de Investigación Clínica de Morelia; MéxicoFil: Izcovich, Ariel. Hospital Alemán; ArgentinaFil: Popoff, Federico. Hospital Aleman; ArgentinaFil: Criniti, Juan M.. Hospital Alemán; ArgentinaFil: Vásquez, Gloria. Universidad de Antioquia; ColombiaFil: Massardo, Loreto. Universidad San Sebastián; ChileFil: Duarte, Margarita. Hospital de Clínicas; ParaguayFil: Barile Fabris, Leonor A.. Hospital Angeles del Pedregal; MéxicoFil: García, Mercedes A.. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; ArgentinaFil: Amigo, Mary Carmen. Centro Médico Abc; MéxicoFil: Espada, Graciela. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Catoggio, Luis J.. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Sato, Emilia Inoue. Universidade Federal de Sao Paulo; BrasilFil: Levy, Roger A.. Universidade do Estado de Rio do Janeiro; BrasilFil: Acevedo Vásquez, Eduardo M.. Universidad Nacional Mayor de San Marcos; PerúFil: Chacón Díaz, Rosa. Policlínica Méndez Gimón; VenezuelaFil: Galarza Maldonado, Claudio M.. Corporación Médica Monte Sinaí; EcuadorFil: Iglesias Gamarra, Antonio J.. Universidad Nacional de Colombia; ColombiaFil: Molina, José Fernando. Centro Integral de Reumatología; ColombiaFil: Neira, Oscar. Universidad de Chile; ChileFil: Silva, Clóvis A.. Universidade de Sao Paulo; BrasilFil: Vargas Peña, Andrea. Hospital Pasteur Montevideo; UruguayFil: Gómez Puerta, José A.. Hospital Clinic Barcelona; EspañaFil: Scolnik, Marina. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Pons Estel, Guillermo J.. Centro Regional de Enfermedades Autoinmunes y Reumáticas; Argentina. Hospital Provincial de Rosario; ArgentinaFil: Ugolini Lopes, Michelle R.. Universidade de Sao Paulo; BrasilFil: Savio, Verónica. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Drenkard, Cristina. University of Emory; Estados UnidosFil: Alvarellos, Alejandro J.. Hospital Privado Universitario de Córdoba; ArgentinaFil: Ugarte Gil, Manuel F.. Universidad Cientifica del Sur; Perú. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Babini, Alejandra. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Cavalcanti, André. Universidade Federal de Pernambuco; BrasilFil: Cardoso Linhares, Fernanda Athayde. Hospital Pasteur Montevideo; UruguayFil: Haye Salinas, Maria Jezabel. Hospital Privado Universitario de Córdoba; ArgentinaFil: Fuentes Silva, Yurilis J.. Universidad de Oriente - Núcleo Bolívar; VenezuelaFil: Montandon De Oliveira E Silva, Ana Carolina. Universidade Federal de Goiás; BrasilFil: Eraso Garnica, Ruth M.. Universidad de Antioquia; ColombiaFil: Herrera Uribe, Sebastián. Hospital General de Medellin Luz Castro de Gutiérrez; ColombiaFil: Gómez Martín, DIana. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Robaina Sevrini, Ricardo. Universidad de la República; UruguayFil: Quintana, Rosana M.. Hospital Provincial de Rosario; Argentina. Centro Regional de Enfermedades Autoinmunes y Reumáticas; ArgentinaFil: Gordon, Sergio. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Fragoso Loyo, Hilda. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Rosario, Violeta. Hospital Docente Padre Billini; República DominicanaFil: Saurit, Verónica. Hospital Privado Universitario de Córdoba; ArgentinaFil: Appenzeller, Simone. Universidade Estadual de Campinas; BrasilFil: Dos Reis Neto, Edgard Torres. Universidade Federal de Sao Paulo; BrasilFil: Cieza, Jorge. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: González Naranjo, Luis A.. Universidad de Antioquia; ColombiaFil: González Bello, Yelitza C.. Ceibac; MéxicoFil: Collado, María Victoria. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Sarano, Judith. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Retamozo, Maria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; ArgentinaFil: Sattler, María E.. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Gamboa Cárdenas, Rocio V.. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Cairoli, Ernesto. Universidad de la República; UruguayFil: Conti, Silvana M.. Hospital Provincial de Rosario; ArgentinaFil: Amezcua Guerra, Luis M.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Silveira, Luis H.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Borba, Eduardo F.. Universidade de Sao Paulo; BrasilFil: Pera, Mariana A.. Hospital Interzonal General de Agudos General San Martín; ArgentinaFil: Alba Moreyra, Paula B.. Universidad Nacional de Córdoba. Facultad de Medicina; ArgentinaFil: Arturi, Valeria. Hospital Interzonal General de Agudos General San Martín; ArgentinaFil: Berbotto, Guillermo A.. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Gerling, Cristian. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Gobbi, Carla Andrea. Universidad Nacional de Córdoba. Facultad de Medicina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gervasoni, Viviana L.. Hospital Provincial de Rosario; ArgentinaFil: Scherbarth, Hugo R.. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Brenol, João C. Tavares. Hospital de Clinicas de Porto Alegre; BrasilFil: Cavalcanti, Fernando. Universidade Federal de Pernambuco; BrasilFil: Costallat, Lilian T. Lavras. Universidade Estadual de Campinas; BrasilFil: Da Silva, Nilzio A.. Universidade Federal de Goiás; BrasilFil: Monticielo, Odirlei A.. Hospital de Clinicas de Porto Alegre; BrasilFil: Seguro, Luciana Parente Costa. Universidade de Sao Paulo; BrasilFil: Xavier, Ricardo M.. Hospital de Clinicas de Porto Alegre; BrasilFil: Llanos, Carolina. Universidad Católica de Chile; ChileFil: Montúfar Guardado, Rubén A.. Instituto Salvadoreño de la Seguridad Social; El SalvadorFil: Garcia De La Torre, Ignacio. Hospital General de Occidente; MéxicoFil: Pineda, Carlos. Instituto Nacional de Rehabilitación; MéxicoFil: Portela Hernández, Margarita. Umae Hospital de Especialidades Centro Medico Nacional Siglo Xxi; MéxicoFil: Danza, Alvaro. Hospital Pasteur Montevideo; UruguayFil: Guibert Toledano, Marlene. Medical-surgical Research Center; CubaFil: Reyes, Gil Llerena. Medical-surgical Research Center; CubaFil: Acosta Colman, Maria Isabel. Hospital de Clínicas; ParaguayFil: Aquino, Alicia M.. Hospital de Clínicas; ParaguayFil: Mora Trujillo, Claudia S.. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: Muñoz Louis, Roberto. Hospital Docente Padre Billini; República DominicanaFil: García Valladares, Ignacio. Centro de Estudios de Investigación Básica y Clínica; MéxicoFil: Orozco, María Celeste. Instituto de Rehabilitación Psicofísica; ArgentinaFil: Burgos, Paula I.. Pontificia Universidad Católica de Chile; ChileFil: Betancur, Graciela V.. Instituto de Rehabilitación Psicofísica; ArgentinaFil: Alarcón, Graciela S.. Universidad Peruana Cayetano Heredia; Perú. University of Alabama at Birmingahm; Estados Unido

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

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

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

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

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'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. 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 (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 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

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

Author correction: One sixth of Amazonian tree diversity is dependent on river floodplains

In the version of the article initially published, the affiliation of Edgardo Manuel Latrubesse was incorrect and has now been amended to Environmental Sciences Graduate Program-CIAMB, Federal University of Goiás, Goiânia, Brazil in the HTML and PDF versions of the article