Definition of a list of fish diseases to aid health management in Spain

Trabajo presentado en la 14th EAFP International Conference (European Association of Fish Pathologists), celebrada en Praga (República Checa), del 14 al 19 de septiembre de 2009An expert working group used a risk ranking technique to compile a list of fish disease hazards (pathogens) of relevance to Spanish aquaculture. It was possible to divide the list into three groups: I-high national risk; II-regional risk; III-low risk. The three groups were as follows: Group I (high risk) Aphanomyces invadans (EUS)**, spring viraemia of carp virus (SVCV), koi herpes virus (KHV)¿ and infectious haematopoietic necrosis virus (IHNV)¿ Group II (regional risk) Enteromyxum spp. (leei and scophthalmi), Aquabirnaviridae (incl. IPNV), viral encephalopathy and retinopathy virus (VERV), Streptococcus iniae, Philasterides dicentrarchi and Aeromonas salmonicida (in the marine environment). Group III (low risk) Sparicotyle chrysophrii/Microcotylidae, Flavobacterium maritimus, Photobacterium piscicida, Togaviridae, Sphaerospora testicularis, Edwardsiella tarda, Birnavirus (no-EVE), Lactococcus garviae, viral haemorrhagic septicaemia virus (VHSV)¿, Tenacibaculum maritimum, epizootic haematopoietic necrosis virus (EHNV)**, Renibacterium salmoninarum (BKD) and Gyrodactylus salaris. The exercise formed part of a project concerning aquaculture health management (Jacumar-GESAC¿) in Spain and is being used to help define sampling plans for disease monitoring using epidemiological and risk-based criteria. **The diseases caused by these pathogens are notifiable and exotic according to Directive 2006/88/EC ¿The diseases caused by these pathogens are notifiable and non-exotic according to Directive 2006/88/EC ¿Plan Nacional de Cultivos Marinos; Gestión sanitaria de la acuicultura: Adaptación a la nueva normativa (GESAC) ¿ financed by the Junta Nacional Asesora de Cultivos Marinos (Jacumar

Graph based study of allergen cross-reactivity of plant lipid transfer proteins (LTPs) using microarray in a multicenter study.

The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.Fil: Abdurro'Uf, null. Academia Sinica, Institute Of Astronomy And Astrophysics; ChinaFil: Accetta, Katherine. Prynceton University, ; Estados UnidosFil: Aerts, Conny. Katholikie Universiteit Leuven; BélgicaFil: Silva Aguirre, Víctor. Aarhus University. Department of Bioscience; DinamarcaFil: Ahumada, Romina. Universidad Católica del Norte; ChileFil: Ajgaonkar, Nikhil. University of Kentucky; Estados UnidosFil: Filiz Ak, N.. Erciyes University; TurquíaFil: Alam, Shadab. University of Edinburgh; Reino UnidoFil: Allende Prieto, Carlos. Instituto de Astrofísica de Canarias, Tenerife; EspañaFil: Almeida, Andrés. University of Virginia; Estados UnidosFil: Anders, Friedrich. Leibniz-Institut fur Astrophysik Potsdam; AlemaniaFil: Anderson, Scott F.. University of Washington; Estados UnidosFil: Andrews, Brett H.. University of Pittsburgh; Estados UnidosFil: Anguiano, Borja. University of Virginia; Estados UnidosFil: Aquino Ortiz, Erik. Universidad Nacional Autónoma de México; MéxicoFil: Aragón Salamanca, Alfonso. University of Nottingham; Estados UnidosFil: Argudo Fernández, Maria. Pontificia Universidad Católica de Valparaíso; ChileFil: Ata, Metin. University of Tokyo; JapónFil: Aubert, Marie. Aix Marseille Université; FranciaFil: Avila Reese, Vladimir. Universidad Nacional Autónoma de México; MéxicoFil: Badenes, Carles. University of Pittsburgh; Estados UnidosFil: Barbá, Rodolfo. Universidad de La Serena; ChileFil: Barger, Kat. Texas Christian University; Estados UnidosFil: Barrera Ballesteros, Jorge K,. Universidad Nacional Autónoma de México; MéxicoFil: Beaton, Rachael L.. Princeton University; Estados UnidosFil: Beers, Timothy C.. University of Notre Dame; Estados UnidosFil: Belfiore, Francesco. Istituto Nazionale di Astrofisica; ItaliaFil: Bender, Chad F.. University of Arizona; Estados UnidosFil: Bernardi, Mariangela. State University of Pennsylvania; Estados UnidosFil: Bershady, Matthew A.. University of Wisconsin; Estados UnidosFil: Monachesi, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentina. Universidad de La Serena; ChileFil: Padilla, Nelson David. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentin

Anisotropy studies around the galactic centre at EeV energies with the Auger Observatory

Data from the Pierre Auger Observatory are analyzed to search for anisotropies near the direction of the Galactic Centre at EeV energies. The exposure of the surface array in this part of the sky is already significantly larger than that of the fore-runner experiments. Our results do not support previous findings of localized excesses in the AGASA and SUGAR data. We set an upper bound on a point-like flux of cosmic rays arriving from the Galactic Centre which excludes several scenarios predicting sources of EeV neutrons from Sagittarius $A$. Also the events detected simultaneously by the surface and fluorescence detectors (the `hybrid' data set), which have better pointing accuracy but are less numerous than those of the surface array alone, do not show any significant localized excess from this direction.Comment: Matches published versio

Worldwide trends in the burden of asthma symptoms in school-aged children: Global Asthma Network Phase I cross-sectional study

Background: Asthma is the most common chronic disease in children globally. The Global Asthma Network (GAN) Phase I study aimed to determine if the worldwide burden of asthma symptoms is changing. Methods: This updated cross-sectional study used the same methods as the International study of Asthma and Allergies in Childhood (ISAAC) Phase III. Asthma symptoms were assessed from centres that completed GAN Phase I and ISAAC Phase I (1993–95), ISAAC Phase III (2001–03), or both. We included individuals from two age groups (children aged 6–7 years and adolescents aged 13–14 years) who self-completed written questionnaires at school. We estimated the 10-year rate of change in prevalence of current wheeze, severe asthma symptoms, ever having asthma, exercise wheeze, and night cough (defined by core questions in the questionnaire) for each centre, and we estimated trends across world regions and income levels using mixed-effects linear regression models with region and country income level as confounders. Findings: Overall, 119 795 participants from 27 centres in 14 countries were included: 74 361 adolescents (response rate 90%) and 45 434 children (response rate 79%). About one in ten individuals of both age groups had wheeze in the preceding year, of whom almost half had severe symptoms. Most centres showed a change in prevalence of 2 SE or more between ISAAC Phase III to GAN Phase I. Over the 27-year period (1993–2020), adolescents showed a significant decrease in percentage point prevalence per decade in severe asthma symptoms (–0·37, 95% CI –0·69 to –0·04) and an increase in ever having asthma (1·25, 0·67 to 1·83) and night cough (4·25, 3·06 to 5·44), which was also found in children (3·21, 1·80 to 4·62). The prevalence of current wheeze decreased in low-income countries (–1·37, –2·47 to –0·27], in children and –1·67, –2·70 to –0·64, in adolescents) and increased in lower-middle-income countries (1·99, 0·33 to 3·66, in children and 1·69, 0·13 to 3·25, in adolescents), but it was stable in upper-middle-income and high-income countries. Interpretation: Trends in prevalence and severity of asthma symptoms over the past three decades varied by age group, country income, region, and centre. The high worldwide burden of severe asthma symptoms would be mitigated by enabling access to effective therapies for asthma. Funding: International Union Against Tuberculosis and Lung Disease, Boehringer Ingelheim New Zealand, AstraZeneca Educational Grant, National Institute for Health Research, UK Medical Research Council, European Research Council, and Instituto de Salud Carlos III

Trends in eczema prevalence in children and adolescents: A Global Asthma Network Phase I Study

Background: Eczema (atopic dermatitis) is a major global public health issue with high prevalence and morbidity. Our goal was to evaluate eczema prevalence over time, using standardized methodology. Methods: The Global Asthma Network (GAN) Phase I study is an international collaborative study arising from the International Study of Asthma and Allergies in Children (ISAAC). Using surveys, we assessed eczema prevalence, severity, and lifetime prevalence, in global centres participating in GAN Phase I (2015–2020) and one/ both of ISAAC Phase I (1993–1995) and Phase III (2001–2003). We fitted linear mixed models to estimate 10-yearly prevalence trends, by age group, income, and region. Results: We analysed GAN Phase I data from 27 centres in 14 countries involving 74,361 adolescents aged 13–14 and 47,907 children aged 6–7 (response rate 90%, 79%). A median of 6% of children and adolescents had symptoms of current eczema, with 1.1% and 0.6% in adolescents and children, respectively, reporting symptoms of severe eczema. Over 27 years, after adjusting for world region and income, we estimated small overall 10-year increases in current eczema prevalence (adolescents: 0.98%, 95% CI 0.04%–1.92%; children: 1.21%, 95% CI 0.18%–2.24%), and severe eczema (adolescents: 0.26%, 95% CI 0.06%–0.46%; children: 0.23%, 95% CI 0.02%–0.45%) with larger increases in lifetime prevalence (adolescents: 2.71%, 95% CI 1.10%–4.32%; children: 3.91%, 95% CI 2.07%–5.75%). There was substantial heterogeneity in 10-year change between centres (standard deviations 2.40%, 0.58%, and 3.04%), and strong evidence that some of this heterogeneity was explained by region and income level, with increases in some outcomes in high-income children and middle-income adolescents. Conclusions: There is substantial variation in changes in eczema prevalence over time by income and region. Understanding reasons for increases in some regions and decreases in others will help inform prevention strategies

The Updated BaSTI Stellar Evolution Models and Isochrones: I. Solar Scaled Calculations

We present an updated release of the BaSTI (a Bag of Stellar Tracks and Isochrones) stellar model and isochrone library for a solar scaled heavy element distribution. The main input physics changed from the previous BaSTI release include the solar metal mixture, electron conduction opacities, a few nuclear reaction rates, bolometric corrections, and the treatment of the overshooting efficiency for shrinking convective cores. The new model calculations cover a mass range between 0.1 and 15 Msun, 22 initial chemical compositions between [Fe/H]=-3.20 and +0.45, with helium to metal enrichment ratio dY /dZ=1.31. The isochrones cover an age range between 20 Myr and 14.5 Gyr, take consistently into account the pre-main sequence phase, and have been translated to a large number of popular photometric systems. Asteroseismic properties of the theoretical models have also been calculated. We compare our isochrones with results from independent databases and with several sets of observations, to test the accuracy of the calculations. All stellar evolution tracks, asteroseismic properties and isochrones are made available through a dedicated Web site

Shells and humans: molluscs and other coastal resources from the earliest human occupations at the Mesolithic shell midden of El Mazo (Asturias, Northern Spain)

Human populations exploited coastal areas with intensity during the Mesolithic in Atlantic Europe, resulting in the accumulation of large shell middens. Northern Spain is one of the most prolific regions, and especially the so-called Asturian area. Large accumulations of shellfish led some scholars to propose the existence of intensification in the exploitation of coastal resources in the region during the Mesolithic. In this paper, shell remains (molluscs, crustaceans and echinoderms) from stratigraphic units 114 and 115 (dated to the early Mesolithic c. 9 kys cal BP) at El Mazo cave (Asturias, northern Spain) were studied in order to establish resource exploitation patterns and environmental conditions. Species representation showed that limpets, top shells and sea urchins were preferentially exploited. One-millimetre mesh screens were crucial in establishing an accurate minimum number of individuals for sea urchins and to determine their importance in exploitation patterns. Environmental conditions deduced from shell assemblages indicated that temperate conditions prevailed at the time of the occupation and the morphology of the coastline was similar to today (rocky exposed shores). Information recovered relating to species representation, collection areas and shell biometry reflected some evidence of intensification (reduced shell size, collection in lower areas of exposed shores, no size selection in some units and species) in the exploitation of coastal resources through time. However, the results suggested the existence of changes in collection strategies and resource management, and periods of intense shell collection may have alternated with times of shell stock recovery throughout the Mesolithic.This research was performed as part of the project “The human response to the global climatic change in a littoral zone: the case of the transition to the Holocene in the Cantabrian coast (10,000–5000 cal BC) (HAR2010-22115-C02-01)” funded by the Spanish Ministry of Economy and Competitiveness. AGE was funded by the University of Cantabria through a predoctoral grant and IGZ was funded by the Spanish Ministry of Economy and Competitiveness through a Juan de la Cierva grant. We also would like to thank the University of Cantabria and the IIIPC for providing support, David Cuenca-Solana, Alejandro García Moreno and Lucia Agudo Pérez for their help. We also thank Jennifer Jones for correcting the English. Comments from two anonymous reviewers helped to improve the paper

Co-limitation towards lower latitudes shapes global forest diversity gradients

Funding Information: The team collaboration and manuscript development are supported by the web-based team science platform: science-i.org, with the project number 202205GFB2. We thank the following initiatives, agencies, teams and individuals for data collection and other technical support: the Global Forest Biodiversity Initiative (GFBI) for establishing the data standards and collaborative framework; United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program; University of Alaska Fairbanks; the SODEFOR, Ivory Coast; University Félix Houphouët-Boigny (UFHB, Ivory Coast); the Queensland Herbarium and past Queensland Government Forestry and Natural Resource Management departments and staff for data collection for over seven decades; and the National Forestry Commission of Mexico (CONAFOR). We thank M. Baker (Carbon Tanzania), together with a team of field assistants (Valentine and Lawrence); all persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3); the French National Forest Inventory (NFI campaigns (raw data 2005 and following annual surveys, were downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159 ; site accessed on 1 January 2015)); the Italian Forest Inventory (NFI campaigns raw data 2005 and following surveys were downloaded by GFBI at https://inventarioforestale.org/ ; site accessed on 27 April 2019); Swiss National Forest Inventory, Swiss Federal Institute for Forest, Snow and Landscape Research WSL and Federal Office for the Environment FOEN, Switzerland; the Swedish NFI, Department of Forest Resource Management, Swedish University of Agricultural Sciences SLU; the National Research Foundation (NRF) of South Africa (89967 and 109244) and the South African Research Chair Initiative; the Danish National Forestry, Department of Geosciences and Natural Resource Management, UCPH; Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES, grant number 88881.064976/2014-01); R. Ávila and S. van Tuylen, Instituto Nacional de Bosques (INAB), Guatemala, for facilitating Guatemalan data; the National Focal Center for Forest condition monitoring of Serbia (NFC), Institute of Forestry, Belgrade, Serbia; the Thünen Institute of Forest Ecosystems (Germany) for providing National Forest Inventory data; the FAO and the United Nations High Commissioner for Refugees (UNHCR) for undertaking the SAFE (Safe Access to Fuel and Energy) and CBIT-Forest projects; and the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network (AfriTRON) and the ForestPlots.net initiative for their contributions from Amazonian and African forests. The Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment are provided by the New Zealand National Vegetation Survey Databank https://nvs.landcareresearch.co.nz/. We thank the International Boreal Forest Research Association (IBFRA); the Forestry Corporation of New South Wales, Australia; the National Forest Directory of the Ministry of Environment and Sustainable Development of the Argentine Republic (MAyDS) for the plot data of the Second National Forest Inventory (INBN2); the National Forestry Authority and Ministry of Water and Environment of Uganda for their National Biomass Survey (NBS) dataset; and the Sabah Biodiversity Council and the staff from Sabah Forest Research Centre. All TEAM data are provided by the Tropical Ecology Assessment and Monitoring (TEAM) Network, a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors, with thanks to all current and previous TEAM site manager and other collaborators that helped collect data. We thank the people of the Redidoti, Pierrekondre and Cassipora village who were instrumental in assisting with the collection of data and sharing local knowledge of their forest and the dedicated members of the field crew of Kabo 2012 census. We are also thankful to FAPESC, SFB, FAO and IMA/SC for supporting the IFFSC. This research was supported in part through computational resources provided by Information Technology at Purdue, West Lafayette, Indiana.This work is supported in part by the NASA grant number 12000401 ‘Multi-sensor biodiversity framework developed from bioacoustic and space based sensor platforms’ (J. Liang, B.P.); the USDA National Institute of Food and Agriculture McIntire Stennis projects 1017711 (J. Liang) and 1016676 (M.Z.); the US National Science Foundation Biological Integration Institutes grant NSF‐DBI‐2021898 (P.B.R.); the funding by H2020 VERIFY (contract 776810) and H2020 Resonate (contract 101000574) (G.-J.N.); the TEAM project in Uganda supported by the Moore foundation and Buffett Foundation through Conservation International (CI) and Wildlife Conservation Society (WCS); the Danish Council for Independent Research | Natural Sciences (TREECHANGE, grant 6108-00078B) and VILLUM FONDEN grant number 16549 (J.-C.S.); the Natural Environment Research Council of the UK (NERC) project NE/T011084/1 awarded to J.A.-G. and NE/ S011811/1; ERC Advanced Grant 291585 (‘T-FORCES’) and a Royal Society-Wolfson Research Merit Award (O.L.P.); RAINFOR plots supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council, notably NERC Consortium Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘BIO-RED’ (NE/N012542/1); CIFOR’s Global Comparative Study on REDD+ funded by the Norwegian Agency for Development Cooperation, the Australian Department of Foreign Affairs and Trade, the European Union, the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) and donors to the CGIAR Fund; AfriTRON network plots funded by the local communities and NERC, ERC, European Union, Royal Society and Leverhume Trust; a grant from the Royal Society and the Natural Environment Research Council, UK (S.L.L.); National Science Foundation CIF21 DIBBs: EI: number 1724728 (A.C.C.); National Natural Science Foundation of China (31800374) and Shandong Provincial Natural Science Foundation (ZR2019BC083) (H.L.). UK NERC Independent Research Fellowship (grant code: NE/S01537X/1) (T.J.); a Serra-Húnter Fellowship provided by the Government of Catalonia (Spain) (S.d.-M.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.A.S.); a grant from the Franklinia Foundation (D.A.C.); Russian Science Foundation project number 19-77-300-12 (R.V.); the Takenaka Scholarship Foundation (A.O.A.); the German Research Foundation (DFG), grant number Am 149/16-4 (C.A.); the Romania National Council for Higher Education Funding, CNFIS, project number CNFIS-FDI-2022-0259 (O.B.); Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-05109 and STPGP506284) and the Canadian Foundation for Innovation (36014) (H.Y.H.C.); the project SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797) (E.C.); Consejo de Ciencia y Tecnología del estado de Durango (2019-01-155) (J.J.C.-R.); Science and Engineering Research Board (SERB), New Delhi, Government of India (file number PDF/2015/000447)—‘Assessing the carbon sequestration potential of different forest types in Central India in response to climate change ’ (J.A.D.); Investissement d’avenir grant of the ANR (CEBA: ANR-10-LABEX-0025) (G.D.); National Foundation for Science & Technology Development of Vietnam, 106-NN.06-2013.01 (T.V.D.); Queensland government, Department of Environment and Science (T.J.E.); a Czech Science Foundation Standard grant (19-14620S) (T.M.F.); European Union Seventh Framework Program (FP7/2007–2013) under grant agreement number 265171 (L. Finer, M. Pollastrini, F. Selvi); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (J.F.); CNPq productivity grant number 311303/2020-0 (A.L.d.G.); DFG grant HE 2719/11-1,2,3; HE 2719/14-1 (A. Hemp); European Union’s Horizon Europe research project OpenEarthMonitor grant number 101059548, CGIAR Fund INIT-32-MItigation and Transformation Initiative for GHG reductions of Agrifood systems RelaTed Emissions (MITIGATE+) (M.H.); General Directorate of the State Forests, Poland (1/07; OR-2717/3/11; OR.271.3.3.2017) and the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (A.M.J.); Czech Science Foundation 18-10781 S (S.J.); Danish of Ministry of Environment, the Danish Environmental Protection Agency, Integrated Forest Monitoring Program—NFI (V.K.J.); State of São Paulo Research Foundation/FAPESP as part of the BIOTA/FAPESP Program Project Functional Gradient-PELD/BIOTA-ECOFOR 2003/12595-7 & 2012/51872-5 (C.A.J.); Danish Council for Independent Research—social sciences—grant DFF 6109–00296 (G.A.K.); Russian Science Foundation project 21-46-07002 for the plot data collected in the Krasnoyarsk region (V.K.); BOLFOR (D.K.K.); Department of Biotechnology, New Delhi, Government of India (grant number BT/PR7928/NDB/52/9/2006, dated 29 September 2006) (M.L.K.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (J.N.K.); Korea Forest Service (2018113A00-1820-BB01, 2013069A00-1819-AA03, and 2020185D10-2022-AA02) and Seoul National University Big Data Institute through the Data Science Research Project 2016 (H.S.K.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.K.); CSIR, New Delhi, government of India (grant number 38(1318)12/EMR-II, dated: 3 April 2012) (S.K.); Department of Biotechnology, New Delhi, government of India (grant number BT/ PR12899/ NDB/39/506/2015 dated 20 June 2017) (A.K.); Coordination for the Improvement of Higher Education Personnel (CAPES) #88887.463733/2019-00 (R.V.L.); National Natural Science Foundation of China (31800374) (H.L.); project of CEPF RAS ‘Methodological approaches to assessing the structural organization and functioning of forest ecosystems’ (AAAA-A18-118052590019-7) funded by the Ministry of Science and Higher Education of Russia (N.V.L.); Leverhulme Trust grant to Andrew Balmford, Simon Lewis and Jon Lovett (A.R.M.); Russian Science Foundation, project 19-77-30015 for European Russia data processing (O.M.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (M.T.E.M.); the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (S.M.); the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund (A. Morera); Queensland government, Department of Environment and Science (V.J.N.); Pinnacle Group Cameroon PLC (L.N.N.); Queensland government, Department of Environment and Science (M.R.N.); the Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05201) (A.P.); the Russian Foundation for Basic Research, project number 20-05-00540 (E.I.P.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 778322 (H.P.); Science and Engineering Research Board, New Delhi, government of India (grant number YSS/2015/000479, dated 12 January 2016) (P.S.); the Chilean Government research grants Fondecyt number 1191816 and FONDEF number ID19 10421 (C.S.-E.); the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 Biodiversity Exploratories (P.S.); European Space Agency projects IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) (D. Schepaschenko); FunDivEUROPE, European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 265171 (M.S.-L.); APVV 20-0168 from the Slovak Research and Development Agency (V.S.); Manchester Metropolitan University’s Environmental Science Research Centre (G.S.); the project ‘LIFE+ ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques’ which is co-funded by the EU Life Plus programme (contract number LIFE13 ENV/PL/000048) and the National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D) (K.J.S.); Global Challenges Research Fund (QR allocation, MMU) (M.J.P.S.); Czech Science Foundation project 21-27454S (M.S.); the Russian Foundation for Basic Research, project number 20-05-00540 (N. Tchebakova); Botanical Research Fund, Coalbourn Trust, Bentham Moxon Trust, Emily Holmes scholarship (L.A.T.); the programmes of the current scientific research of the Botanical Garden of the Ural Branch of Russian Academy of Sciences (V.A.U.); FCT—Portuguese Foundation for Science and Technology—Project UIDB/04033/2020. Inventário Florestal Nacional—ICNF (H. Viana); Grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (C.W.); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (B.W.); ATTO project (grant number MCTI-FINEP 1759/10 and BMBF 01LB1001A, 01LK1602F) (F.W.); ReVaTene/PReSeD-CI 2 is funded by the Education and Research Ministry of Côte d’Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD (I.C.Z.-B.); the National Research Foundation of South Africa (NRF, grant 89967) (C.H.). The Tropical Plant Exploration Group 70 1 ha plots in Continental Cameroon Mountains are supported by Rufford Small Grant Foundation, UK and 4 ha in Sierra Leone are supported by the Global Challenge Research Fund through Manchester Metropolitan University, UK; the National Geographic Explorer Grant, NGS-53344R-18 (A.C.-S.); University of KwaZulu-Natal Research Office grant (M.J.L.); Universidad Nacional Autónoma de México, Dirección General de Asuntos de Personal Académico, Grant PAPIIT IN-217620 (J.A.M.). Czech Science Foundation project 21-24186M (R.T., S. Delabye). Czech Science Foundation project 20-05840Y, the Czech Ministry of Education, Youth and Sports (LTAUSA19137) and the long-term research development project of the Czech Academy of Sciences no. RVO 67985939 (J.A.). The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (grant number 0452995) and the Wenner-Gren Foundation for Anthropological Research (grant number 7330) (M.B.). Research grants from Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq, Brazil) (309764/2019; 311303/2020) (A.C.V., A.L.G.). The Project of Sanya Yazhou Bay Science and Technology City (grant number CKJ-JYRC-2022-83) (H.-F.W.). The Ugandan NBS was supported with funds from the Forest Carbon Partnership Facility (FCPF), the Austrian Development Agency (ADC) and FAO. FAO’s UN-REDD Program, together with the project on ‘Native Forests and Community’ Loan BIRF number 8493-AR UNDP ARG/15/004 and the National Program for the Protection of Native Forests under UNDP funded Argentina’s INBN2. Publisher Copyright: © 2022, The Author(s), under exclusive licence to Springer Nature Limited.Peer reviewedPostprin