Estudio de la adsorción de As(V) en régimen batch y en continuo, empleando hidroxiapatita bovina como material adsorbente.

Se estudió la factibilidad de emplear hidroxiapatita bovina como material adsorbente de As(V) presente en soluciones acuosas modelo. Las características del material fueron determinadas mediante las técnicas de Espectrofotometría Infrarroja por Transformada de Fourier (FTIR), las isotermas de adsorción de nitrógeno según el método convencional BET [1,2], y la Microscopía Electrónica de Barrido (SEM). En los espectros infrarrojos, se pudieron apreciar señales características de la hidroxiapatita [3]. En las micrografías SEM se destacó la presencia de partículas de tamaño diferente, de forma irregular con bordes suaves, y superficies muy lisas para una resolución de 2 µm. Estos hechos, sumado a los valores relativamente bajos de superficie específica de BET (1,5 m2 .g-1) y de volumen total de poros (4,4.10-3 m3.g-1) obtenidos, daría indicio de que se trataría de un material esencialmente no poroso. La adsorción fue estudiada tanto en régimen discontinuo como continuo. Las concentraciones iniciales de las soluciones se encontraron en el rango que va de los 2 a los 9 mg.L-1 de As(V). Se llevaron a cabo ensayos batch de soluciones acuosas de contaminante, con el material adsorbente en cuestión. La cantidad de soluto removida se calculó a partir de las diferencias de concentración entre la solución inicial y la remanente. El método de valoración de As empleado fue la de Fluorescencia de Rayos X con Geometría de Reflexión Total (TXRF). A fin de definir una dosis óptima de sólido a emplear (1,0 g por cada 50 mL de solución) se desarrolló una curva de dosificación. Las condiciones de equilibrio fueron estudiadas a través de la elaboración de las isotermas de adsorción, las cuales fueron representadas mediante siete modelos diferentes: tres de dos parámetros (Langmuir, Freundlich, y Temkin), y cuatro de tres parámetros (RedlichPeterson, Radke-Prausnitz, Sips, y Toth) [4,5]. El ajuste más satisfactorio fue el brindado por el modelo de isoterma de Freundlich. El análisis de la influencia del tiempo sobre la capacidad de remoción del sistema se realizó llevando a cabo estudios cinéticos [6,7]. En este caso, cuatro modelos fueron utilizados: Lagergren, Ho, Órdenes Combinados, y Elovich, resultando este último el más satisfactorio para representar los datos experimentales. Además, se estudió el desempeño del material adsorbente en régimen de flujo continuo, mediante el desarrollo de ensayos de adsorción en columna rellena de lecho fijo. Para caracterizar la fluidodinámica a través del lecho, se realizó un ensayo de estímulo-respuesta [8,9], utilizando un lecho inerte y perturbándolo con un escalón de determinada concentración de As. El análisis de datos consistió en el cálculo del tiempo medio de residencia y la aplicación del modelo de dispersión axial. Luego, se procedió estudiar la capacidad de adsorción de la columna rellena de hidroxiapatita, desarrollando una curva de ruptura. A través de ella, se determinó la masa de As(V) total adsorbida; se aplicaron los modelos de Thomas, Bohart-Adams, y Yoon-Nelson para describir el sistema. Se estimó el tiempo transcurrido hasta alcanzar el punto de ruptura, característico de estos ensayos [10]. Los tres modelos resultaron ser igualmente adecuados para describir el sistema.Fil: García, Juan Ignacio, Boeykens, Susana. Facultad de Ingeniería, Universidad de Buenos Aires (Laboratorio de Química de Sistemas Heterogéneos). ArgentinaFil: Beraldi, Agustina; Melitón, Laura; de Celis, Jorge P. Facultad Regional Avellaneda. UTN (Laboratorio de Investigación y Desarrollo en Ingeniería Química, (LIDIQ). Dto. Ingeniería Química). ArgentinaFil: Cerchietti, Luciana. Comisión Nacional de Energía Atómica (Gerencia Química). ArgentinaFil: Ozols, Andrés. Facultad de Ingeniería. UBA (Instituto de Ingeniería Biomédica). ArgentinaPeer Reviewe

Food in the Anthropocene: the EAT-Lancet Commission on healthy diets from sustainable food systems

PRIFPRI3; ISI; 2 Promoting Healthy Diets and Nutrition for all; 1 Fostering Climate-Resilient and Sustainable Food Supply; UNFSSDG

Immune Response to SARS-CoV-2 Third Vaccine in Patients With Rheumatoid Arthritis Who Had No Seroconversion After Primary 2-Dose Regimen With Inactivated or Vector-Based Vaccines

Objective. The aim of this study was to assess the immune response after a third dose of SARS-CoV-2 vaccine in patients with rheumatoid arthritis (RA) with undetectable antibody titers after the primary regimen of 2 doses. Methods. Patients with RA with no seroconversion after 2 doses of SARS-CoV-2 vaccine and who received a third dose of either an mRNA or vector-based vaccine were included. Anti-SARS-CoV-2 IgG antibodies, neutralizing activity, and T cell responses were assessed after the third dose. Results. A total of 21 nonresponder patients were included. At the time of vaccination, 29% were receiving glucocorticoids and 85% biologic disease-modifying antirheumatic drugs (including 6 taking abatacept [ABA] and 4 taking rituximab [RTX]). The majority (95%) received the BNT162b2 vaccine and only one of them received the ChAdOx1 nCoV-19 vaccine. After the third dose, 91% of the patients presented detectable anti-SARS-CoV-2 IgG and 76% showed neutralizing activity. Compared to other treatments, ABA and RTX were associated with the absence of neutralizing activity in 4 out of 5 (80%) patients and lower titers of neutralizing antibodies (median 3, IQR 0-20 vs 8, IQR 4-128; P = 0.20). Specific T cell response was detected in 41% of all patients after the second dose, increasing to 71% after the third dose. The use of ABA was associated with a lower frequency of T cell response (33% vs 87%, P = 0.03). Conclusion. In this RA cohort, 91% of patients who failed to seroconvert after 2 doses of SARS-CoV-2 vaccine presented detectable anti-SARS-CoV-2 IgG after a third dose. The use of ABA was associated with a lower frequency of specific T cell response.Fil: Isnardi, Carolina A.. No especifíca;Fil: Cerda, Osvaldo L.. No especifíca;Fil: Landi, Margarita. Austral University Hospital; LiberiaFil: Cruces, Leonel Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; ArgentinaFil: Schneeberger, Emilce E.. No especifíca;Fil: Montoro, Claudia Calle. Austral University Hospital; LiberiaFil: Alfaro, María Agustina. No especifíca;Fil: Roldán, Brian M.. No especifíca;Fil: Gómez Vara, Andrea B.. No especifíca;Fil: Giorgis, Pamela. No especifíca;Fil: Ezquer, Roberto Alejandro. No especifíca;Fil: Crespo Rocha, María G. No especifíca;Fil: Reyes Gómez, Camila R.. No especifíca;Fil: de Los Ángeles Correa, Mária. No especifíca;Fil: Rosemffet, Marcos G.. No especifíca;Fil: Abarza, Virginia Carrizo. No especifíca;Fil: Pellet, Santiago Catalan. Austral University Hospital; LiberiaFil: Perandones, Miguel. No especifíca;Fil: Reimundes, Cecilia. Austral University Hospital; LiberiaFil: Longueira, Yesica Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; ArgentinaFil: Turk, Gabriela Julia Ana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; ArgentinaFil: Quiroga, María Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; ArgentinaFil: Laufer, Natalia Lorna. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; ArgentinaFil: Quintana, Rosana Maris. No especifíca;Fil: de la Vega, María Celina. No especifíca;Fil: Kreplak, Nicolás. No especifíca;Fil: Pifano, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Maid, Pablo. Austral University Hospital; LiberiaFil: Pons Estel, Guillermo J.. No especifíca;Fil: Citera, Gustavo. No especifíca

Biogeography in the deep : hierarchical population genomic structure of two beaked whale species

Funding for this research was provided by the Office of Naval Research, Award numbers N000141613017 and N000142112712. ABO was supported by a partial studentship from the University of St Andrews, School of Biology; OEG by the Marine Alliance for Science and Technology for Scotland (Scottish Funding Council grant HR09011); ELC by a Rutherford Discovery Fellowship from the Royal Society of New Zealand Te Aparangi; NAS by a Ramon y Cajal Fellowship from the Spanish Ministry of Innovation; MLM by the European Union’s Horizon 2020 Research and Innovation Programme (Marie Skłodowska-Curie grant 801199); CR by the Marine Institute (Cetaceans on the Frontier) and the Irish Research Council; and MTO by the Hartmann Foundation.The deep sea is the largest ecosystem on Earth, yet little is known about the processes driving patterns of genetic diversity in its inhabitants. Here, we investigated the macro- and microevolutionary processes shaping genomic population structure and diversity in two poorly understood, globally distributed, deep-sea predators: Cuvier’s beaked whale (Ziphius cavirostris) and Blainville’s beaked whale (Mesoplodon densirostris). We used double-digest restriction associated DNA (ddRAD) and whole mitochondrial genome (mitogenome) sequencing to characterise genetic patterns using phylogenetic trees, cluster analysis, isolation-by-distance, genetic diversity and differentiation statistics. Single nucleotide polymorphisms (SNPs; Blainville’s n = 43 samples, SNPs=13988; Cuvier’s n = 123, SNPs= 30479) and mitogenomes (Blainville’s n = 27; Cuvier’s n = 35) revealed substantial hierarchical structure at a global scale. Both species display significant genetic structure between the Atlantic, Indo-Pacific and in Cuvier’s, the Mediterranean Sea. Within major ocean basins, clear differentiation is found between genetic clusters on the east and west sides of the North Atlantic, and some distinct patterns of structure in the Indo-Pacific and Southern Hemisphere. We infer that macroevolutionary processes shaping patterns of genetic diversity include biogeographical barriers, highlighting the importance of such barriers even to highly mobile, deep-diving taxa. The barriers likely differ between the species due to their thermal tolerances and evolutionary histories. On a microevolutionary scale, it seems likely that the balance between resident populations displaying site fidelity, and transient individuals facilitating gene flow, shapes patterns of connectivity and genetic drift in beaked whales. Based on these results, we propose management units to facilitate improved conservation measures for these elusive species.Publisher PDFPeer reviewe

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Expert range maps of global mammal distributions harmonised to three taxonomic authorities

Aim: Comprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW). Location: Global. Taxon: All extant mammal species. Methods: Range maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species). Results: Range maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use. Main conclusion: Expert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control.Fil: Marsh, Charles J.. Yale University; Estados UnidosFil: Sica, Yanina. Yale University; Estados UnidosFil: Burguin, Connor. University of New Mexico; Estados UnidosFil: Dorman, Wendy A.. University of Yale; Estados UnidosFil: Anderson, Robert C.. University of Yale; Estados UnidosFil: del Toro Mijares, Isabel. University of Yale; Estados UnidosFil: Vigneron, Jessica G.. University of Yale; Estados UnidosFil: Barve, Vijay. University Of Florida. Florida Museum Of History; Estados UnidosFil: Dombrowik, Victoria L.. University of Yale; Estados UnidosFil: Duong, Michelle. University of Yale; Estados UnidosFil: Guralnick, Robert. University Of Florida. Florida Museum Of History; Estados UnidosFil: Hart, Julie A.. University of Yale; Estados UnidosFil: Maypole, J. Krish. University of Yale; Estados UnidosFil: McCall, Kira. University of Yale; Estados UnidosFil: Ranipeta, Ajay. University of Yale; Estados UnidosFil: Schuerkmann, Anna. University of Yale; Estados UnidosFil: Torselli, Michael A.. University of Yale; Estados UnidosFil: Lacher, Thomas. Texas A&M University; Estados UnidosFil: Wilson, Don E.. National Museum of Natural History; Estados UnidosFil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Aguirre, Luis F.. Universidad Mayor de San Simón; BoliviaFil: Arroyo Cabrales, Joaquín. Instituto Nacional de Antropología E Historia, Mexico; MéxicoFil: Astúa, Diego. Universidade Federal de Pernambuco; BrasilFil: Baker, Andrew M.. Queensland University of Technology; Australia. Queensland Museum; AustraliaFil: Braulik, Gill. University of St. Andrews; Reino UnidoFil: Braun, Janet K.. Oklahoma State University; Estados UnidosFil: Brito, Jorge. Instituto Nacional de Biodiversidad; EcuadorFil: Busher, Peter E.. Boston University; Estados UnidosFil: Burneo, Santiago F.. Pontificia Universidad Católica del Ecuador; EcuadorFil: Camacho, M. Alejandra. Pontificia Universidad Católica del Ecuador; EcuadorFil: de Almeida Chiquito, Elisandra. Universidade Federal do Espírito Santo; BrasilFil: Cook, Joseph A.. University of New Mexico; Estados UnidosFil: Cuéllar Soto, Erika. Sultan Qaboos University; OmánFil: Davenport, Tim R. B.. Wildlife Conservation Society; TanzaniaFil: Denys, Christiane. Muséum National d'Histoire Naturelle; FranciaFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Eldridge, Mark D. B.. Australian Museum; AustraliaFil: Fernandez Duque, Eduardo. University of Yale; Estados UnidosFil: Francis, Charles M.. Environment And Climate Change Canada; CanadáFil: Frankham, Greta. Australian Museum; AustraliaFil: Freitas, Thales. Universidade Federal do Rio Grande do Sul; BrasilFil: Friend, J. Anthony. Conservation And Attractions; AustraliaFil: Giannini, Norberto Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; ArgentinaFil: Gursky-Doyen, Sharon. Texas A&M University; Estados UnidosFil: Hackländer, Klaus. Universitat Fur Bodenkultur Wien; AustriaFil: Hawkins, Melissa. National Museum of Natural History; Estados UnidosFil: Helgen, Kristofer M.. Australian Museum; AustraliaFil: Heritage, Steven. University of Duke; Estados UnidosFil: Hinckley, Arlo. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Holden, Mary. American Museum of Natural History; Estados UnidosFil: Holekamp, Kay E.. Michigan State University; Estados UnidosFil: Humle, Tatyana. University Of Kent; Reino UnidoFil: Ibáñez Ulargui, Carlos. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Jackson, Stephen M.. Australian Museum; AustraliaFil: Janecka, Mary. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Jenkins, Paula. Natural History Museum; Reino UnidoFil: Juste, Javier. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Leite, Yuri L. R.. Universidade Federal do Espírito Santo; BrasilFil: Novaes, Roberto Leonan M.. Universidade Federal do Rio de Janeiro; BrasilFil: Lim, Burton K.. Royal Ontario Museum; CanadáFil: Maisels, Fiona G.. Wildlife Conservation Society; Estados UnidosFil: Mares, Michael A.. Oklahoma State University; Estados UnidosFil: Marsh, Helene. James Cook University; AustraliaFil: Mattioli, Stefano. Università degli Studi di Siena; ItaliaFil: Morton, F. Blake. University of Hull; Reino UnidoFil: Ojeda, Agustina Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Ordóñez Garza, Nicté. Instituto Nacional de Biodiversidad; EcuadorFil: Pardiñas, Ulises Francisco J.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Pavan, Mariana. Universidade de Sao Paulo; BrasilFil: Riley, Erin P.. San Diego State University; Estados UnidosFil: Rubenstein, Daniel I.. University of Princeton; Estados UnidosFil: Ruelas, Dennisse. Museo de Historia Natural, Lima; PerúFil: Schai-Braun, Stéphanie. Universitat Fur Bodenkultur Wien; AustriaFil: Schank, Cody J.. University of Texas at Austin; Estados UnidosFil: Shenbrot, Georgy. Ben Gurion University of the Negev; IsraelFil: Solari, Sergio. Universidad de Antioquia; ColombiaFil: Superina, Mariella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Tsang, Susan. American Museum of Natural History; Estados UnidosFil: Van Cakenberghe, Victor. Universiteit Antwerp; BélgicaFil: Veron, Geraldine. Université Pierre et Marie Curie; FranciaFil: Wallis, Janette. Kasokwa-kityedo Forest Project; UgandaFil: Whittaker, Danielle. Michigan State University; Estados UnidosFil: Wells, Rod. Flinders University.; AustraliaFil: Wittemyer, George. State University of Colorado - Fort Collins; Estados UnidosFil: Woinarski, John. Charles Darwin University; AustraliaFil: Upham, Nathan S.. University of Yale; Estados UnidosFil: Jetz, Walter. University of Yale; Estados Unido

Biogeography in the deep: hierarchical population genomic structure of two beaked whale species

The deep sea is the largest ecosystem on Earth, yet little is known about the processes driving patterns of genetic diversity in its inhabitants. Here, we investigated the macro- and microevolutionary processes shaping genomic population structure and diversity in two poorly understood, globally distributed, deep-sea predators: Cuvier’s beaked whale (Ziphius cavirostris) and Blainville’s beaked whale (Mesoplodon densirostris). We used double-digest restriction associated DNA (ddRAD) and whole mitochondrial genome (mitogenome) sequencing to characterise genetic patterns using phylogenetic trees, cluster analysis, isolation-by-distance, genetic diversity and differentiation statistics. Single nucleotide polymorphisms (SNPs; Blainville’s n=43 samples, SNPs=13988; Cuvier’s n=123, SNPs= 30479) and mitogenomes (Blainville’s n=27; Cuvier’s n=35) revealed substantial hierarchical structure at a global scale. Both species display significant genetic structure between the Atlantic, Indo-Pacific and in Cuvier’s, the Mediterranean Sea. Within major ocean basins, clear differentiation is found between genetic clusters on the east and west sides of the North Atlantic, and some distinct patterns of structure in the Indo-Pacific and Southern Hemisphere. We infer that macroevolutionary processes shaping patterns of genetic diversity include biogeographical barriers, highlighting the importance of such barriers even to highly mobile, deep-diving taxa. The barriers likely differ between the species due to their thermal tolerances and evolutionary histories. On a microevolutionary scale, it seems likely that the balance between resident populations displaying site fidelity, and transient individuals facilitating gene flow, shapes patterns of connectivity and genetic drift. Based on these results, we propose management units to facilitate improved conservation measures for these elusive species

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global disparities in surgeons’ workloads, academic engagement and rest periods: the on-calL shIft fOr geNEral SurgeonS (LIONESS) study

: The workload of general surgeons is multifaceted, encompassing not only surgical procedures but also a myriad of other responsibilities. From April to May 2023, we conducted a CHERRIES-compliant internet-based survey analyzing clinical practice, academic engagement, and post-on-call rest. The questionnaire featured six sections with 35 questions. Statistical analysis used Chi-square tests, ANOVA, and logistic regression (SPSS® v. 28). The survey received a total of 1.046 responses (65.4%). Over 78.0% of responders came from Europe, 65.1% came from a general surgery unit; 92.8% of European and 87.5% of North American respondents were involved in research, compared to 71.7% in Africa. Europe led in publishing research studies (6.6 ± 8.6 yearly). Teaching involvement was high in North America (100%) and Africa (91.7%). Surgeons reported an average of 6.7 ± 4.9 on-call shifts per month, with European and North American surgeons experiencing 6.5 ± 4.9 and 7.8 ± 4.1 on-calls monthly, respectively. African surgeons had the highest on-call frequency (8.7 ± 6.1). Post-on-call, only 35.1% of respondents received a day off. Europeans were most likely (40%) to have a day off, while African surgeons were least likely (6.7%). On the adjusted multivariable analysis HDI (Human Development Index) (aOR 1.993) hospital capacity > 400 beds (aOR 2.423), working in a specialty surgery unit (aOR 2.087), and making the on-call in-house (aOR 5.446), significantly predicted the likelihood of having a day off after an on-call shift. Our study revealed critical insights into the disparities in workload, access to research, and professional opportunities for surgeons across different continents, underscored by the HDI