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This is the final version of the article. Available from Wiley via the DOI in this record. ; Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height. Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement. Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with biomass estimates using field measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches. Our results indicate that even limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample. ; This paper is a product of the RAINFOR, AfriTRON and T-FORCES networks, for which we are indebted to the hundreds of institutions, field assistants and local communities across many countries that have supported and hosted fieldwork. The three networks have been supported by the Natural Environment Research Council (NERC) Urgency Grants and NERC Consortium Grants "AMAZONICA" (NE/F005806/1), "TROBIT" (NE/D005590/1) and "BIO-RED" (NE/N012542/1), a NERC New Investigators Grant, a European Research Council grant ("Tropical Forests in the Changing Earth System"), the Gordon and Betty Moore Foundation, the David and Lucile Packard Foundation, the European Union's Seventh Framework Programme (283080, "GEOCARBON"; 282664, "AMAZALERT"), the Royal Society and Gabon's National Parks Agency (ANPN). R.J.W.B. is funded by a NERC research fellowship (grant ref: NE/I021160/1). S.L.L. was supported by a Royal Society University Research Fellowship, ERC Advanced Grant and a Phillip Leverhulme Prize. O.L.P. is supported by an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. L.F.B. was supported by a NERC studentship, RGS-IBG Henrietta Hutton Grant and Royal Society Dudley Stamp Award. R.H. and M.C. were supported through the long-term research development project no. RVO 67985939 and a KBFSC research fellowship (2011, to R.H.). M. Svátek was funded by the Ministry of Education, Youth and Sports of the Czech Republic (grant number INGO II LG15051). We thank Georgia Pickavance for assistance with database curation, and Natacha Nssi Bengone, Sylvester Chenikan, Eric Chezeaux, Armandu Daniels, Jean-Louis Doucet, Kath Jeffery, Edi Mirmanto, Abel Monteagudo-Mendoza, Faustin Mpanya Lukasu, Reuben Nilus, Guido Pardo, Lourens Poorter, Sylvester Tan, Marisol Toledo, Armando Torres-Lezama, John Tshibamba Mukendi, Richard Tshombe, Geertje van der Heijden, Lee White, Hannsjoerg Woell and John Woods, Gabon's National Parks Agency (ANPN), the Forest Development Authority of Liberia and Wildlife Conservation Society-Democratic Republic of Congo for assistance with access to datasets. We thank an anonymous reviewer for constructive comments on this manuscript.

This paper is a product of the T-FORCES forest monitoring network (Tropical Forests in the Changing Earth System), supported by an ERC Advanced Grant to O.L.P. and by many institutions, NGOs, government agencies and local communities in Malaysia, Brunei, and Indonesia. We are grateful for historical plot data contributed by the Center for Tropical Forest Science (CTFS; two LAM plots and one BEL plot), the Global Ecosystem Monitoring network (GEM; two LAM plots), Institute for Biodiversity and Environmental Research, Universiti Brunei Darussalam (Brunei plots), Kagoshima University (KIS and KIU plots), Forest Department Sarawak (BKO, LAM, MER and GMU plots), Forest Research Centre, Sabah Forestry Department (SEP plots), the Tropenbos Kalimantan project (ITCI plots), Project Barito Ulu, supported by Indonesian Institute of Sciences (LIPI) (BUL plots), and the STREK project, supported by CIRAD, The Ministry of Forestry of Indonesia, and INHUTANI I (STR plots). We are indebted to a great many individuals who contributed to historical data collection. Contemporary fieldwork was supported by a grant from the ERC (T-FORCES) and from NERC (grants NER/A/S/2000/00532, NE/B503384/1, NE/N012542/1). L.Q. was supported by T-FORCES, CIFOR and NERC NE/P00363X/1. S.L.L. was supported by a Royal Society University Research Fellowship, T-FORCES and a Phillip Leverhulme Prize. O.L.P. is supported by T-FORCES and a Royal Society Wolfson Research Merit Award. M.J.P.S. is supported by T-FORCES and NERC NE/N012542/1. L.F.B. was supported by a NERC studentship to the University of Leeds and a RGS-IBG Henrietta Hutton grant. R.H. was supported by a University of Brunei Darussalam Research Fellowship (2011) and a long-term research project RVO 67985939 from the Czech Academy of Sciences. S.L. received additional support from Primate Conservation Inc. M.S. was supported by a Ministry of Education, Youth and Sports grant of the Czech Republic INGO II LG15051. R.R.E.V. was supported by the Netherlands Foundation for the Advancement of Tropical Research (WOTRO, grant No. W76-217). We thank Forest Department Sarawak, Sabah Biodiversity Centre, Sabah Forestry Department, Forest Department Brunei, Institute for Biodiversity and Environmental Research, University of Brunei Darussalam and Indonesia Ministry of Research, Technology, and Higher Education for research permissions. We thank Bako National Park, Lambir Hills National Park, Gunung Mulu National Park, Kuala Belalong Field Study Centre (KBFSC), Glen Reynolds (SEARRP), Danum Valley Conservation Area, Rainforest Discovery Centre Sepilok, Sepilok Laut Reception Centre, Borneo Orangutan Survival Foundation (BOSF), Sungai Wain Protection Forest Management Unit, WWF East Kalimantan and PT. ITCIKU East Kalimantan for logistical support for fieldwork. We thank Timothy Baker, Roel Brienen, Emanuel Gloor, Adriane Esquivel Muelbert and Nicolas Labrière for comments on the manuscript. We thank our deceased colleagues, John Proctor and Suriantata, for their invaluable contributions to both historical work and our wider understanding of tropical forest ecology. ; Peer reviewed ; Publisher PDF

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1714977115/-/DCSupplemental. ; Knowledge about the biogeographic affinities of the world's tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world's tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests. ; European Union's Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie Grant Agreement 660020, Instituto Bem Ambiental (IBAM), Myr Projetos Sustentáveis, IEF, and CNPq, CAPES FAPEMIG, German Research Foundation (DFG; Grants CRC 552, CU127/3-1, HO 3296/2-2, HO3296/4-1, and RU 816), UNAM-PAPIIT IN218416 and Semarnat-CONACYT 128136, Conselho Nacional de Desenvolvimento Científico e Tecnoloógico (CNPq, Brazil), Fundação Grupo Boticário de Proteção à Natureza/Brazil, PAPIIT-DGAPA-UNAM (Project IN-204215), National Geographic Society, National Foundation for Scientific and Technology Development Vietnam (Grant 106.11-2010.68), Operation Wallacea, and core funding for Crown Research Institutes from the New Zealand Ministry of Business, Innovation and Employment's Science and Innovation Group. ; Peer-reviewed ; Publisher Version

Background: The COVID-19 pandemic has disrupted routine hospital services globally. This study estimated the total number of adult elective operations that would be cancelled worldwide during the 12 weeks of peak disruption due to COVID-19. Methods: A global expert response study was conducted to elicit projections for the proportion of elective surgery that would be cancelled or postponed during the 12 weeks of peak disruption. A Bayesian β-regression model was used to estimate 12-week cancellation rates for 190 countries. Elective surgical case-mix data, stratified by specialty and indication (surgery for cancer versus benign disease), were determined. This case mix was applied to country-level surgical volumes. The 12-week cancellation rates were then applied to these figures to calculate the total number of cancelled operations. Results: The best estimate was that 28 404 603 operations would be cancelled or postponed during the peak 12 weeks of disruption due to COVID-19 (2 367 050 operations per week). Most would be operations for benign disease (90·2 per cent, 25 638 922 of 28 404 603). The overall 12-week cancellation rate would be 72·3 per cent. Globally, 81·7 per cent of operations for benign conditions (25 638 922 of 31 378 062), 37·7 per cent of cancer operations (2 324 070 of 6 162 311) and 25·4 per cent of elective caesarean sections (441 611 of 1 735 483) would be cancelled or postponed. If countries increased their normal surgical volume by 20 per cent after the pandemic, it would take a median of 45 weeks to clear the backlog of operations resulting from COVID-19 disruption. Conclusion: A very large number of operations will be cancelled or postponed owing to disruption caused by COVID-19. Governments should mitigate against this major burden on patients by developing recovery plans and implementing strategies to restore surgical activity safely.