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Borneo is the centre of diversity of the palm genusPinanga. At least 13 understory species have been recorded in the Ulu Temburong National Park in Brunei, but little is known of their persistence. Changes in populations ofPinangaunderstory palms may be indicative of more widespread changes due to climate change, such as changes in rainfall, which may be important for the palm diversity in the protected area. However, we know little about the population dynamics of these palms, how persistent their populations are or if they behave similarly over long time frames. In 1998, populations of five co-occurring species ofPinangaat several locations in the Ulu Temburong National Park were documented. This project aimed to undertake a comprehensive resurvey of the original fivePinangapalm species populations in order to assess if they showed similar population changes across sites and species after two decades. Overall, most species maintained their population size in the surveyed region but not consistently among sites, and one species significantly declined in abundance. There was considerable variation in population growth rate (R) within and among species and sites that was significantly correlated with density and the percentage of multi-stemmed plants. There was evidence of pulsed recruitment in some species and or sites rather than steady or exponential patterns of population growth.

Future biodiversity outcomes are expect to vary across Shared Socioeconomic Pathways (SSPs) of climate and land-use change. We modelled 1476 tree species distributions in Southeast Asia, classified them into 12 spatially associated groups, and projected distributional changes under four SSPs. The sustainable pathway, SSP1-2.6, led to the best outcomes for tree distributions. However, there was no clear second-best pathway for both climate and biodiversity. Distribution outcomes were generally worst for intermediate pathways of climate mitigation because they involved greater land-use change, while the second-best distribution outcome was under the least-sustainable climate pathway. Furthermore, the second-best pathway varied starkly across species groups, such that the second-best pathway for one group was also the worst for another. We demonstrate how halfway measures to mitigate climate change can lead to worse biodiversity outcomes, and that deviating from the sustainable pathway will involve trade-offs. We emphasise that policymakers must prioritise the most sustainable pathway.

Discovery rates of new plant species need to be accelerated because many species will be extinct before they are formally described. Current studies have focused on where new species may occur and their characteristics. However, who will actually discover and describe these new species has received limited attention. Here, we used 31 576 vascular plant species distributed and described in China as a case study to explore the temporal patterns of the nationalities of the taxonomists. We found that most recently described species are endemic species, and there has been an increasing proportion of species descriptions by resident Chinese taxonomists over time. The proportion of species described by resident taxonomists reached an average of 80.8% between 1977 and 2018. By contrast, species discoveries by non-resident experts, often non-endemic species, showed signs of levelling off. Our study underscores an urgent need for training of, support for and collaboration with resident taxonomists in megadiverse countries with a high potential of discovering undescribed plant species.

Complex distribution data can be summarised by grouping species with similar or overlapping distributions to unravel patterns in species distributions and separate trends (e.g., of habitat loss) among spatially unique groups. However, such classifications are often heuristic, lacking the transparency, objectivity, and data-driven rigour of quantitative methods, which limits their interpretability and utility. Here, we develop and illustrate the clustering of spatially associated species, a methodological framework aimed at statistically classifying species using explicit measures of interspecific spatial association. We investigate several association indices and clustering algorithms and show how these methodological choices engender substantial variations in clustering outcome and performance. To facilitate robust decision making, we provide guidance on choosing methods appropriate to the study objective(s). As a case study, we apply the framework to model tree distributions in Borneo to evaluate the impact of land-cover change on separate species groupings. We identified 11 distinct clusters that unravelled ecologically meaningful patterns in Bornean tree distributions. These clusters then enabled us to quantify trends of habitat loss tied to each of those specific clusters, allowing us to discern particularly vulnerable species clusters and their distributions. This study demonstrates the advantages of adopting quantitatively derived clusters of spatially associated species and elucidates the potential of resultant clusters as a spatially explicit framework for investigating distribution-related questions in ecology, biogeography, and conservation. By adopting our methodological framework and publicly available codes, practitioners can leverage the ever-growing abundance of distribution data to better understand complex spatial patterns among species distributions and the disparate effects of global changes on biodiversity.Statement of authorshipSEHP and ELW conceived the idea and designed methodology. SEHP conducted all analyses and developed the methodological framework with key inputs from ELW, JWFS, and DZ. All authors contributed to the interpretation of the results. SEHP and ELW wrote the first draft of the manuscript. All authors provided feedback on the writing.

Tree diversity in Asia's tropical and subtropical forests is central to nature-based solutions. Species vulnerability to multiple threats, which affect provision of ecosystem services, is poorly understood. We conducted a region-wide, spatially explicit assessment of the vulnerability of 63 socioeconomically important tree species to overexploitation, fire, overgrazing, habitat conversion, and climate change. Trees were selected for assessment from national priority lists, and selections were validated by an expert network representing 20 countries. We used Maxent suitability modeling to predict species distribution ranges, freely accessible spatial data sets to map threat exposures, and functional traits to estimate threat sensitivities. Species-specific vulnerability maps were created as the product of exposure maps and sensitivity estimates. Based on vulnerability to current threats and climate change, we identified priority areas for conservation and restoration. Overall, 74% of the most important areas for conservation of these trees fell outside protected areas, and all species were severely threatened across an average of 47% of their native ranges. The most imminent threats were overexploitation and habitat conversion; populations were severely threatened by these factors in an average of 24% and 16% of their ranges, respectively. Our model predicted limited overall climate change impacts, although some study species were likely to lose over 15% of their habitat by 2050 due to climate change. We pinpointed specific natural areas in Borneo rain forests as hotspots for in situ conservation of forest genetic resources, more than 82% of which fell outside designated protected areas. We also identified degraded areas in Western Ghats, Indochina dry forests, and Sumatran rain forests as hotspots for restoration, where planting or assisted natural regeneration will help conserve these species, and croplands in southern India and Thailand as potentially important agroforestry options. Our results highlight the need for regionally coordinated action for effective conservation and restoration.Especies de Árboles Valoradas y Amenazadas de Asia Tropical y Subtropical Resumen La diversidad de árboles en los bosques tropicales y subtropicales de Asia es un eje central para las soluciones basadas en la naturaleza. La vulnerabilidad de las especies ante las múltiples amenazas, las cuales afectan el suministro de servicios ambientales, es un tema poco comprendido. Realizamos una evaluación regional espacialmente explícita de la vulnerabilidad de 63 especies de árboles de importancia socioeconómica ante la sobreexplotación, incendios, sobrepastoreo, conversión del hábitat y cambio climático. Los árboles se seleccionaron para su evaluación a partir de listas nacionales de prioridades, y las selecciones fueron validadas por una red de expertos de 20 países. Usamos el modelado de idoneidad Maxent para predecir el rango de distribución de las especies, conjuntos de datos espaciales de libre acceso para mapear la exposición a las amenazas y rasgos funcionales para estimar la susceptibilidad a las amenazas. Con base en la vulnerabilidad a las amenazas actuales y al cambio climático, identificamos las áreas prioritarias para su conservación y restauración. En general, el 74% de las áreas más importantes para la conservación de estos árboles quedó fuera de las áreas protegidas y todas las especies estaban seriamente amenazadas en promedio en el 47% de su distribución nativa. Las amenazas más inminentes fueron la sobreexplotación y la conversión del hábitat; las poblaciones estuvieron seriamente amenazadas por estos factores en promedio en el 24% y 16% de su distribución, respectivamente. Nuestro modelo predijo un impacto general limitado del cambio climático, aunque algunas especies estudiadas tuvieron la probabilidad de perder más del 15% de su hábitat para el 2050 debido a este factor. Identificamos áreas naturales específicas en las selvas de Borneo como puntos calientes para la conservación in situ de los recursos genéticos forestales, más del 82% de los cuales estaban fuera de las áreas protegidas designadas. También identificamos áreas degradadas en los Ghats Occidentales, los bosques secos de Indochina y las selvas de Sumatra como puntos calientes para la restauración, en donde la siembra o la regeneración natural asistida ayudarán a conservar estas especies. Además, identificamos campos de cultivo al sur de India y Tailandia como potenciales opciones importantes de agrosilvicultura. Nuestros resultados resaltan la necesidad de acciones regionales coordinadas para la conservación y restauración efectivas.【摘要】保护亚洲热带和亚热带森林的树木多样性是基于自然的解决方案的关注重点。物种面对多种威胁的脆弱性会影响生态系统服务的供给, 但目前人们对此仍知之甚少。我们对63种具有社会经济意义的树种面对过度开发、火灾、过度放牧、栖息地转换和气候变化的脆弱性进行了全区域空间显式评估。我们进行评估的树种来自国家优先保护名录, 树种的选择得到代表 20个国家的专家网络的认可。研究使用Maxent适宜性模型预测了物种分布范围, 并用可获取的空间数据集绘制了威胁暴露情况, 用功能特征估计了威胁敏感性。我们利用暴露地图和敏感性估计结果得到了物种特异的脆弱性地图, 并根据物种对当前威胁和气候变化的脆弱性, 确定了保护和恢复的优先区域。总的来说, 对这些树种的保护最重要的区域有 74%在保护区之外, 所有树种平均在其原生分布区 47%的范围内受到严重威胁。最紧迫的威胁是过度开发和栖息地转换;树木种群平均在其 24%和16%的范围内受到这些因素的严重威胁。我们的模型预测得到的气候变化整体影响有限, 尽管一些物种到2050年可能会因气候变化而失去超过15%的栖息地。我们发现婆罗洲雨林中特定的自然区域应作为森林遗传资源原地保护的热点地区, 该区域82%以上的面积位于已有保护区之外。我们还确定了西高止山、中南半岛旱林和苏门答腊雨林的退化地区为恢复热点地区, 在这些地区种植树木或辅助自然再生将有助于保护树种, 而印度南部和泰国的耕地则是潜在的重要农林地。我们的结果强调了为有效保护和恢复而采取区域性协调行动的必要性。【翻译: 胡怡思;审校: 聂永刚】.

Aim: Here we examine the functional profile of regional tree species pools across the latitudinal distribution of Neotropical moist forests, and test trait–climate relationships among local communities. We expected opportunistic strategies (acquisitive traits, small seeds) to be overrepresented in species pools further from the equator, but also in terms of abundance in local communities in currently wetter, warmer and more seasonal climates. Location: Neotropics. Time period: Recent. Major taxa studied: Trees. Methods: We obtained abundance data from 471 plots across nine Neotropical regions, including c. 100,000 trees of 3,417 species, in addition to six functional traits. We compared occurrence-based trait distributions among regional species pools, and evaluated single trait–climate relationships across local communities using community abundance-weighted means (CWMs). Multivariate trait–climate relationships were assessed by a double-constrained correspondence analysis that tests both how CWMs relate to climate and how species distributions, parameterized by niche centroids in climate space, relate to their traits. Results: Regional species pools were undistinguished in functional terms, but opportunistic strategies dominated local communities further from the equator, particularly in the Northern Hemisphere. Climate explained up to 57% of the variation in CWM traits, with increasing prevalence of lower-statured, light-wooded and softer-leaved species bearing smaller seeds in more seasonal, wetter and warmer climates. Species distributions were significantly but weakly related to functional traits. Main conclusions: Neotropical moist forest regions share similar sets of functional strategies, from which local assembly processes, driven by current climatic conditions, select for species with different functional strategies. We can thus expect functional responses to climate change driven by changes in relative abundances of species already present regionally. Particularly, equatorial forests holding the most conservative traits and large seeds are likely to experience the most severe changes if climate change triggers the proliferation of opportunistic tree species.

The Miocene convergence of the Sunda shelf, Sahul shelf and Wallacea facilitated the exchange of previously isolated floras across the Sunda–Sahul Convergence Zone (SSCZ). The SSCZ is a hotspot of biogeographical research; however, phytogeographical patterns across the region remain poorly understood. We conducted multivariate analysis on a comprehensive species checklist of SSCZ vascular plants to quantify the extent of exchange, characterize phytogeographical patterns and investigate their abiotic drivers. We found that Lydekker’s and Wallace’s Lines are not reflected in floristic composition at any taxonomic level, with 46% of genera distributed across these biogeographical lines. In contrast, environment is significantly correlated with floristic composition, with annual rainfall and seasonality being the strongest correlates. Mainland Asia, Borneo, the Philippines, New Guinea and Australia were major routes of exchange throughout the Cenozoic, possibly because these areas have been persistent landmasses throughout the entire period of convergence. We conclude that Sunda–Sahul floristic exchange has substantially influenced the assembly of the regional flora and that modern phytogeographical patterns have been influenced more by environmental variables and available landmass (i.e. establishment conditions) than by putative barriers to movement such as Wallace’s and Lydekker’s Lines (i.e. vagility).

International audience; Over the past decade, several global maps of above-ground biomass (AGB) have been produced, but they exhibit significant differences that reduce their value for climate and carbon cycle modelling, and also for national estimates of forest carbon stocks and their changes. The number of such maps is anticipated to increase because of new satellite missions dedicated to measuring AGB. Objective and consistent methods to estimate the accuracy and uncertainty of AGB maps are therefore urgently needed. This paper develops and demonstrates a framework aimed at achieving this. The framework provides a means to compare AGB maps with AGB estimates from a global collection of National Forest Inventories and research plots that accounts for the uncertainty of plot AGB errors. This uncertainty depends strongly on plot size, and is dominated by the combined errors from tree measurements and allometric models (inter-quartile range of their standard deviation (SD) = 30–151 Mg ha−1). Estimates of sampling errors are also important, especially in the most common case where plots are smaller than map pixels (SD = 16–44 Mg ha−1). Plot uncertainty estimates are used to calculate the minimum-variance linear unbiased estimates of the mean forest AGB when averaged to 0.1∘. These are used to assess four AGB maps: Baccini (2000), GEOCARBON (2008), GlobBiomass (2010) and CCI Biomass (2017). Map bias, estimated using the differences between the plot and 0.1∘ map averages, is modelled using random forest regression driven by variables shown to affect the map estimates. The bias model is particularly sensitive to the map estimate of AGB and tree cover, and exhibits strong regional biases. Variograms indicate that AGB map errors have map-specific spatial correlation up to a range of 50–104 km, which increases the variance of spatially aggregated AGB map estimates compared to when pixel errors are independent. After bias adjustment, total pantropical AGB and its associated SD are derived for the four map epochs. This total becomes closer to the value estimated by the Forest Resources Assessment after every epoch and shows a similar decrease. The framework is applicable to both local and global-scale analysis, and is available at https://github.com/arnanaraza/PlotToMap. Our study therefore constitutes a major step towards improved AGB map validation and improvement.

Extremely old trees have important roles in providing insights about historical climatic events and supporting cultural values. Yet there has been limited work on the global distribution and conservation of these trees. We extracted information on 197,855 tree cores at 4,854 sites, and combined it with other tree age data from a further 156 sites, to determine the age of the world's oldest trees and quantify the factors influencing their global distribution. We found that extremely old trees1,000 years are rare. Among 30 individual trees that exceeded 2,000 years old, 27 occurred in high mountains. Our model suggests that many of the existing oldest trees occur in high-elevation, cold and arid mountains with limited human disturbance. This pattern is markedly different from that of the tallest trees, which are more likely to occur in more mesic and productive locations. Global warming and expansion of human activities may induce rapid population declines of extremely old trees. New strategies, including targeted establishment of conservation reserves in remote regions, especially those in western Table 1 parts of China and USA, are required to protect these trees. This article is protected by copyright. All rights reserved.

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness., Proceedings of the National Academy of Sciences of the United States of America, 119 (6), ISSN:0027-8424, ISSN:1091-6490

Funding: We acknowledge funding from the following organizations: Norwegian Agency for Development Cooperation (Norad); Norwegian International Climate and Forest Initiative (NICFI); International Climate Initiative (IKI) of the German; Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB); CGIAR Research Program on Forests, Trees and Agroforestry (CRP‐FTA) with financial support from the CGIAR Fund Donors; EU Horizon 2020 project VERIFY (776810); European Space Agency GlobBiomass project (ESRIN Contract No. 4000113100/14/I-NB); European Research Council (ERC) Advanced Grants T-FORCES (291585) and PANTROP (834775); JAXA (RA-6, EO-RA2); UK Natural Environment Research Council (NERC; including NE/F005806/, NE/D005590/1, NE/T01279X/1, NE/P008755/1 and NE/N012542/1); agreement PR140015 between NERC and the National Centre for Earth Observation; Gordon and Betty Moore Foundation; CNPq (National Council of Science and Technology, Brazil), Grants #401279/2014‐4 (PVE) and #441244/2016‐5 (PELD); Doris Duke Charitable Foundation; the Children's Investment 309 Fund Foundation; COmON Foundation and Good Energies Foundation. For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0-7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps. Publisher PDF

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers. 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.

AIM: A better understanding of plant communities can be achieved by incorporating data of traits and dynamics into surveys. Wood density is a good predictor for growth and mortality in trees, but to date, no studies of lianas include all three. We examine how liana communities respond to environmental gradients and forest fragmentation in terms of abundance, diversity, size structure, mortality, relative growth rate and wood density, and tested how the latter three are related to each other in liana species. LOCATION: Xishuangbanna, SW China. METHODS: We repeated a survey of lianas (stems >0.5 cm diameter) in 47 plots, distributed in forest fragments of various size, on different bedrock (limestone or sandstone), over an elevational range and across different topographic elements (ridge, slope, valley). We gathered wood density data for 116 of 166 species, covering 90% of all surveyed stems. We also determined relative growth rate, mortality, stem diameter and basal area. RESULTS: At the species level, liana mortality and relative growth rate were lower at higher wood density, and mortality was higher with greater relative growth rate. At the plot level, liana communities in valleys had high relative growth and mortality rates as well as high abundance and diversity. Forest on limestone hosted few species but more large‐stemmed liana individuals, and communities had higher wood density weighted by basal area. Liana abundance, relative growth rates and mortality were greater and average wood density lower towards fragment edges, but the explanatory power of these models was low. CONCLUSION: Habitat was the major factor shaping liana communities, whereas fragmentation was not an important predictor in our study. Resource‐rich environments such as valleys harbour diverse liana communities with high mortality and relative growth rates. This pattern matches earlier studies on survival/growth trade‐offs among plant species. The relationship between growth rates, mortality and wood density in lianas follows the same trade‐offs as found in trees.

AIM: Why some lineages are species‐rich and widespread, while others are species‐poor and localized, is a fundamental question in evolutionary biology and ecology. Diversification and range expansion relate to lineage‐specific niche characters, but this link has seldom been quantified across multiple lineages and environments. This study explored the link between local dominance and soil niche in rain forest plants, and tested the hypothesis that local soil niche patterns can be used to predict the global diversity and occupancy of equal‐aged plant lineages. LOCATION: The study was carried out in Brunei Darussalam (Borneo) and projected worldwide. METHODS: Our approach involved the subdivision of vascular plants into the lineages found 120 Mya, a time preceding the explosive radiation of the eudicots. We quantified the representation of the 120 Mya lineages in different forest types associated with dramatically different soils, but sharing the same climatic conditions. The forest types included primary and secondary lowland rain forest, flooded and nutrient‐impoverished inland forests, and mangroves. Niche breadth and position, estimated from the soil types that a lineage occupied, were used to predict global diversity and occupancy patterns, after accounting for relatedness to the dominant eudicots. RESULTS: Despite marked differences in soil characteristics among the forest types, three eudicot lineages (Malvidae, Fabidae, Asteridae) were consistently dominant over the other 28 lineages present. A broad, intermediate soil niche, relatedness to eudicots, and the interaction between these factors were found to be strong predictors of global diversity and occupancy. MAIN CONCLUSIONS: We show that vegetation plot data from one of the world's most diverse regions (in terms of plant species richness and ancient lineage representation) can be used to successfully predict lineage diversity and occupancy on a global scale. However, because lineage dominance likely depends on the interaction between soil niche and above‐ground factors, including above‐ground niche features should improve the accuracy of predicting global distribution and diversity—particularly when explaining eudicot dominance.

AIM: Small, old‐growth forest fragments generally have more small‐seeded plants than large patches, due to the disappearance of large seed dispersing vertebrates. This pattern may differ for secondary forest fragments where differential migration ability rather than persistence of seed dispersers may be driving plant community assembly. In this study, we investigated the effect of habitat fragmentation on seed dispersers and plant community structure in regenerating forests. LOCATION: The Thousand Island Lake, China. TAXON: Plants, birds and mammals. METHODS: We compiled diversity and abundance data for birds and mammals on islands in the Thousand Island Lake, China. We also surveyed the secondary plant communities and measured seed dispersal traits. RESULTS: Community‐weighted mean seed size of woody plants decreased with island size. This pattern was related to compositional difference of the dispersers. We found that mammal diversity and abundance was only weakly or not related to island size; whereas bird diversity and abundance increased strongly with island size. Density of bird‐dispersed plants was significantly positively related with island size. Since birds tend to disperse smaller seeds than mammals, the trend in seed size may have been a consequence of the shift in relative abundance of the two disperser guilds. MAIN CONCLUSIONS: Differential responses of seed dispersers to habitat fragmentation may lead to pervasive shifts in the plant community structure of regenerating forest fragments. Our study highlights the importance of keeping large continuous forests in order to retain mammals and their dispersal capabilities.

Tropical rainforests play important roles in carbon sequestration and are hot spots for biodiversity. Tropical forests are being replaced by rubber (Hevea brasiliensis) plantations, causing widespread concern of a crash in biodiversity. Such changes in aboveground vegetation might have stronger impacts on belowground biodiversity. We studied tropical rainforest fragments and derived rubber plantations at a network of sites in Xishuangbanna, China, hypothesizing a major decrease in diversity with conversion to plantations. We used metabarcoding of the 18S rRNA gene and recovered 2313 OTUs, with a total of 449 OTUs shared between the two land-use types. The most abundant phyla detected were Annelida (66.4% reads) followed by arthropods (15.5% reads) and nematodes (8.9% reads). Of these, only annelids were significantly more abundant in rubber plantation. Taken together, α- and β-diversity were significantly higher in forest than rubber plantation. Soil pH and spatial distance explained a significant portion of the variability in phylogenetic community structure for both land-use types. Community assembly was primarily influenced by stochastic processes. Overall it appears that forest replacement by rubber plantation results in an overall loss and extensive replacement of soil micro- and mesofaunal biodiversity, which should be regarded as an additional aspect of the impact of forest conversion.

Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191ha) and quantified tree palm (i.e., ≥10cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.

Banks-Leite et al. (2021) claim that our suggestion of preserving ≥40% forest cover lacks evidence and can be problematic. We find these claims unfounded, and discuss why conservation planning urgently requires valuable, well-supported, and feasible general guidelines like the 40% criterion. Using region-specific thresholds worldwide is unfeasible and potentially harmful.

Heath forest ecosystems in Brunei are threatened as they are highly vulnerable to fire and converted for land development. On top of this, Acacia mangium, a non-native Australian tree species, has successfully invaded disturbed heath forest in Brunei. This species is now so common in disturbed heath forests that it shows potential as a disturbance indicator. To test this, we investigated how well Acacia dominance correlated with total basal area, canopy openness, species richness and stem density of heath forests. A total of 20 plots (400 ​m2 each) were established in heath forests with three different disturbance types; old-growth, old-regenerating and recent regenerating plots. Regression analyses were performed on Acacia dominance against the four variables. High Acacia dominance correlated strongly and positively with greater canopy openness but negatively with basal area, species richness and stem density. Acacia dominance was also strongly correlated with species composition. Our study finds that 1) Acacia mangium dominance can be used to determine the disturbance stage of heath forest, and as such provides an easy to measure indicator of heath forest health, and 2) that the most cost efficient way to eradicate Acacia mangium is fire prevention so that natural succession will provide the shaded conditions that prevent Acacia mangium establishment and population maintenance.

White sand heath forests (WS) or kerangas, an unusual variant of tropical forests in Borneo, characterized by open scrubby vegetation, low productivity, and distinctive plant species composition and soil microbial community, are regarded as a stressful low-pH and/or nutrient environment. We investigated whether the functional soil metagenome also shows a predicted set of indicators of stressful conditions in WS. Based on stress-tolerant strategies exhibited by larger organisms, we hypothesized that genes for stress tolerance, dormancy, sporulation, and nutrient processing are more abundant in the soil microbiota of WS. We also hypothesized that there is less evidence of biotic interaction in white sand soils, with lower connectivity and fewer genes related to organismic interactions. In Brunei, we sampled soils from a WS and a normal primary dipterocarp forest, together with an inland heath, an intermediate forest type. Soil DNA was extracted, and shotgun sequencing was performed using Illumina HiSeq platform, with classification by the Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST). The results, on one hand, supported our hypothesis (on greater abundance of dormancy, virulence, and sporulation-related genes). However, some aspects of our results showed no significant difference (specifically in stress tolerance, antibiotic resistance, viruses, and clustered regularly interspaced short palindrome repeats (CRISPRs)). It appears that in certain respects, the extreme white sand environment produces the predicted strategy of less biotic interaction, but exhibits high soil microbiota connectivity and functional diversity.

International audience; Natural history collections and tropical tree diversity are both treasure troves of biological and evolutionary information, but their accessibility for scientific study is impeded by a number of properties. DNA in historical specimens is generally highly fragmented, complicating the recovery of high-grade genetic material. Furthermore, our understanding of hyperdiverse, wide-spread tree assemblages is obstructed by extensive species ranges, fragmented knowledge of tropical tree diversity and phenology, and a widespread lack of species-level diagnostic characters, prohibiting the collecting of readily identifiable specimens which can be used to build, revise or strengthen taxonomic frameworks. This, in turn, delays the application of downstream conservation action. A sizable component of botanical collections are sterile-thus eluding identification and are slowing down progress in systematic treatments of tropical biodiversity. With rapid advances in genomics and bioinformatic approaches to biodiversity research, museomics is emerging as a new field breathing life into natural collections that have been built up over centuries. Using MIGseq (multiplexed ISSR genotyping by sequencing), we generated 10,000s of short loci, for both freshly collected materials and museum specimens (aged > 100 years) of Lithocarpus-a widespread tropical tree genus endemic to the Asian tropics. Loci recovery from historical and recently collected samples was not affected by sample age and preservation history of the study material, underscoring the reliability and flexibility of the MIGseq approach. Phylogenomic inference and biogeographic reconstruction across insular Asia, highlights repeated migration and diversification patterns between continental regions and islands. Results indicate that co-occurring insular species at the extremity of the distribution range are not monophyletic, raising the possibility of multiple independent dispersals along the outer edge of Wallacea. This suggests that dispersal of large seeded tree genera throughout Malesia and across Wallacea may have been less affected by large geographic distances and the presence of marine barriers than generally assumed. We demonstrate the utility of MIGseq in museomic studies using non-model taxa, presenting the first range-wide genomic assessment of Lithocarpus and tropical Fagaceae as a proof-of-concept. Our study shows the potential for developing innovative genomic approaches to improve the capture of novel evolutionary signals using valuable natural history collections of hyperdiverse taxa.

Background The Sunda-Sahul Convergence Zone, defined here as the area comprising Australia, New Guinea, and Southeast Asia (Indonesia to Myanmar), straddles the Sunda and Sahul continental shelves and is one of the most biogeographically famous and important regions in the world. Floristically, it is thought to harbour a large amount of the world’s diversity. Despite the importance of the area, a checklist of the flora has never before been published. Here we present the first working checklist of vascular plants for the Sunda-Sahul Convergence Zone. The list was compiled from 24 flora volumes, online databases and unpublished plot data. Taxonomic nomenclature was updated, and each species was coded into nested biogeographic regions. The list includes 60,415 species in 5,135 genera and 363 families of vascular plants. New information This is the first species-level checklist of the region and presents an updated census of the region’s floristic biodiversity. The checklist confirms that species richness of the SSCZ is comparable to that of the Neotropics, and highlights areas in need of further documentation and taxonomic work. This checklist provides a novel dataset for studying floristic ecology and evolution in this biogeographically important region of very high global biodiversity.

Urban areas are home to more than half the world’s population, but also habitats for a wide range of plant and animal species. While street trees in urban areas have been recognized as important for human well-being, however, how they can contribute to wildlife conservation is less explored. Here we compiled a database of street tree inventories in China, that included species diversity, abundance and origin information of street trees from 59 cities to explore how different cities rank with regards to the use of native and diversity of street trees, which are both considered beneficial to urban biodiversity. We found the most abundant species contributed an average of 35.8% of all street trees in the studied cities, and non-native species contributed an average of 40.6% of the street trees. Most cities are dominated by only a few species of trees, and a large proportion of these trees are non-native tree species, indicating that streetscapes are likely not friendly to biodiversity. Our proposed ranking schedule provides an easy tool for classifying cities according to their street tree wildlife friendliness, while also providing clear management directions on how to improve city tree composition for biodiversity conservation. To build a sustainable society in which nature and humans can coexist, we recommend that city planners should consider biodiversity conservation as a core value of urban planning. Specifically, we encourage the planting of more native trees and use of a more diverse set of species capable of attracting wildlife, thus promoting biodiversity in cities. Furthermore, awareness of biodiversity friendly tree planting systems needs special attention in developing regions and densely populated areas. We emphasize that more regional research needs to go into identifying local species that can be used as street trees while simultaneously functioning as wildlife attractants.

Significance Identifying and explaining regional differences in tropical forest dynamics, structure, diversity, and composition are critical for anticipating region-specific responses to global environmental change. Floristic classifications are of fundamental importance for these efforts. Here we provide a global tropical forest classification that is explicitly based on community evolutionary similarity, resulting in identification of five major tropical forest regions and their relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. African and American forests are grouped, reflecting their former western Gondwanan connection, while Indo-Pacific forests range from eastern Africa and Madagascar to Australia and the Pacific. The connection between northern-hemisphere Asian and American forests is confirmed, while Dry forests are identified as a single tropical biome., 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.