Nuevos registros para la flora vascular de Colombia presentes en la Orinoquia y reseña histórica de las expediciones botánicas a la región

18 new records to the vascular flora of Colombia found in the Orinoquia region are recorded: Duguetia riberensis Aristeg. ex Maas & Boon, Trigynaea duckei (R .E. Fr.) R. E. Fr. (Annonaceae); Tassadia medinae (Morillo) Morillo (Apocynaceae); Jaracanda orinocensis Sandw. (Bignoniaceae); Polycarpaea corymbosa (L.) Lam. var. brasiliensis (Cambess.) Chodat & Hassl. (Caryophyllaceae); Murdannia burchellii (C. B. Clarke) M. Pell. y M. aff. triquetra (Wall. ex C. B. Clarke) G.Brückn (Commelinaceae); Enterolobium barinense L. Cárdenas & Rodr.-Carr., Machaerium tovarense Pittier, Muellera crucisrubierae (Pittier) M. Sousa, and Tachigali davidsei Zarucchi & Herend. (Leguminosae); Nectandra bartlettiana Lasser (Lauraceae); Lindernia brachyphylla Pennell ex Steyerm. (Linderniaceae); Campomanesia aromatica (Aubl.) Griseb. (Myrtaceae); Christiana africana DC. (Malvaceae); Dulacia cyanocarpa Sleumer (Olacaceae); Phyllanthus microphyllus Kunth (Phyllanthaceae), and Gouania wurdackii Steyerm. (Rhamnaceae). These species were collected in the states of Arauca and Vichada in Colombia. Aspects related with the taxonomy and nomenclature of these new records, geographical distributions, and affinities with the flora of the Llanos of Venezuela as well as other regions with floristic similarities are discussed, and information about the exploration in the region is documented.Se registran 18 novedades para la flora vascular de Colombia a partir de ejemplares recolectados en la región dela Orinoquia. Los nuevos registros corresponden a: Duguetia riberensis Aristeg. ex Maas & Boon, Trigynaeaduckei (R. E. Fr.) R. E. Fr. (Annonaceae); Tassadia medinae (Morillo) Morillo (Apocynaceae); Jaracandaorinocensis Sandw. (Bignoniaceae); Polycarpaea corymbosa (L.) Lam. var. brasiliensis (Cambess.) Chodat &Hassl. (Caryophyllaceae); Murdannia burchellii (C. B. Clarke) M. Pell. y M. aff. triquetra (Wall. ex C. B. Clarke)G. Brückn (Commelinaceae); Enterolobium barinense L. Cárdenas & Rodr.-Carr., Machaerium tovarense Pittier,Muellera crucisrubierae (Pittier) M. Sousa y Tachigali davidsei Zarucchi & Herend. (Leguminosae), Nectandrabartlettiana Lasser (Lauraceae); Lindernia brachyphylla Pennell ex Steyerm. (Linderniaceae); Campomanesiaaromatica (Aubl.) Griseb. (Myrtaceae); Christiana africana DC. (Malvaceae); Dulacia cyanocarpa Sleumer(Olacaceae); Phyllanthus microphyllus Kunth (Phyllanthaceae) y Gouania wurdackii Steyerm. (Rhamnaceae).Estas especies fueron recolectadas en los departamentos de Arauca y Vichada. Se discuten aspectos relacionadoscon la taxonomía y nomenclatura de estos nuevos registros, su distribución geográfica, sus afinidades con la florapresente en la Orinoquia venezolana y regiones con características florísticas similares. Se agrega una reseñahistórica de las exploraciones en los llanos colombianos

Nuevos registros para la flora vascular de Colombia presentes en la Orinoquia y reseña histórica de las expediciones botánicas a la región

Se registran 18 novedades para la flora vascular de Colombia a partir de ejemplares recolectados en la región de la Orinoquia. Los nuevos registros corresponden a: Duguetia riberensis Aristeg. ex Maas & Boon, Trigynaea duckei (R. E. Fr.) R. E. Fr. (Annonaceae); Tassadia medinae (Morillo) Morillo (Apocynaceae); Jaracanda orinocensis Sandw. (Bignoniaceae); Polycarpaea corymbosa (L.) Lam. var. brasiliensis (Cambess.) Chodat & Hassl. (Caryophyllaceae); Murdannia burchellii (C. B. Clarke) M. Pell. y M. aff. triquetra (Wall. ex C. B. Clarke) G. Brückn (Commelinaceae); Enterolobium barinense L. Cárdenas & Rodr.-Carr., Machaerium tovarense Pittier, Muellera crucisrubierae (Pittier) M. Sousa y Tachigali davidsei Zarucchi & Herend. (Leguminosae), Nectandra bartlettiana Lasser (Lauraceae); Lindernia brachyphylla Pennell ex Steyerm. (Linderniaceae); Campomanesia aromatica (Aubl.) Griseb. (Myrtaceae); Christiana africana DC. (Malvaceae); Dulacia cyanocarpa Sleumer (Olacaceae); Phyllanthus microphyllus Kunth (Phyllanthaceae) y Gouania wurdackii Steyerm. (Rhamnaceae). Estas especies fueron recolectadas en los departamentos de Arauca y Vichada. Se discuten aspectos relacionados con la taxonomía y nomenclatura de estos nuevos registros, su distribución geográfica, sus afinidades con la flora presente en la Orinoquia venezolana y regiones con características florísticas similares. Se agrega una reseña histórica de las exploraciones en los llanos colombianos

Nuevos registros para la flora vascular de Colombia presentes en la Orinoquia y reseña histórica de las expediciones botánicas a la región

18 new records to the vascular flora of Colombia found in the Orinoquia region are recorded: Duguetia riberensis Aristeg. ex Maas & Boon, Trigynaea duckei (R .E. Fr.) R. E. Fr. (Annonaceae); Tassadia medinae (Morillo) Morillo (Apocynaceae); Jaracanda orinocensis Sandw. (Bignoniaceae); Polycarpaea corymbosa (L.) Lam. var. brasiliensis (Cambess.) Chodat & Hassl. (Caryophyllaceae); Murdannia burchellii (C. B. Clarke) M. Pell. y M. aff. triquetra (Wall. ex C. B. Clarke) G.Brückn (Commelinaceae); Enterolobium barinense L. Cárdenas & Rodr.-Carr., Machaerium tovarense Pittier, Muellera crucisrubierae (Pittier) M. Sousa, and Tachigali davidsei Zarucchi & Herend. (Leguminosae); Nectandra bartlettiana Lasser (Lauraceae); Lindernia brachyphylla Pennell ex Steyerm. (Linderniaceae); Campomanesia aromatica (Aubl.) Griseb. (Myrtaceae); Christiana africana DC. (Malvaceae); Dulacia cyanocarpa Sleumer (Olacaceae); Phyllanthus microphyllus Kunth (Phyllanthaceae), and Gouania wurdackii Steyerm. (Rhamnaceae). These species were collected in the states of Arauca and Vichada in Colombia. Aspects related with the taxonomy and nomenclature of these new records, geographical distributions, and affinities with the flora of the Llanos of Venezuela as well as other regions with floristic similarities are discussed, and information about the exploration in the region is documented.Se registran 18 novedades para la flora vascular de Colombia a partir de ejemplares recolectados en la región dela Orinoquia. Los nuevos registros corresponden a: Duguetia riberensis Aristeg. ex Maas & Boon, Trigynaeaduckei (R. E. Fr.) R. E. Fr. (Annonaceae); Tassadia medinae (Morillo) Morillo (Apocynaceae); Jaracandaorinocensis Sandw. (Bignoniaceae); Polycarpaea corymbosa (L.) Lam. var. brasiliensis (Cambess.) Chodat &Hassl. (Caryophyllaceae); Murdannia burchellii (C. B. Clarke) M. Pell. y M. aff. triquetra (Wall. ex C. B. Clarke)G. Brückn (Commelinaceae); Enterolobium barinense L. Cárdenas & Rodr.-Carr., Machaerium tovarense Pittier,Muellera crucisrubierae (Pittier) M. Sousa y Tachigali davidsei Zarucchi & Herend. (Leguminosae), Nectandrabartlettiana Lasser (Lauraceae); Lindernia brachyphylla Pennell ex Steyerm. (Linderniaceae); Campomanesiaaromatica (Aubl.) Griseb. (Myrtaceae); Christiana africana DC. (Malvaceae); Dulacia cyanocarpa Sleumer(Olacaceae); Phyllanthus microphyllus Kunth (Phyllanthaceae) y Gouania wurdackii Steyerm. (Rhamnaceae).Estas especies fueron recolectadas en los departamentos de Arauca y Vichada. Se discuten aspectos relacionadoscon la taxonomía y nomenclatura de estos nuevos registros, su distribución geográfica, sus afinidades con la florapresente en la Orinoquia venezolana y regiones con características florísticas similares. Se agrega una reseñahistórica de las exploraciones en los llanos colombianos

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors

Phylogenetic diversity of Amazonian tree communities

This is the peer reviewed version of the following article: Honorio Coronado, E. N., Dexter, K. G., Pennington, R. T., Chave, J., Lewis, S. L., Alexiades, M. N., Alvarez, E., Alves de Oliveira, A., Amaral, I. L., Araujo-Murakami, A., Arets, E. J. M. M., Aymard, G. A., Baraloto, C., Bonal, D., Brienen, R., Cerón, C., Cornejo Valverde, F., Di Fiore, A., Farfan-Rios, W., Feldpausch, T. R., Higuchi, N., Huamantupa-Chuquimaco, I., Laurance, S. G., Laurance, W. F., López-Gonzalez, G., Marimon, B. S., Marimon-Junior, B. H., Monteagudo Mendoza, A., Neill, D., Palacios Cuenca, W., Peñuela Mora, M. C., Pitman, N. C. A., Prieto, A., Quesada, C. A., Ramirez Angulo, H., Rudas, A., Ruschel, A. R., Salinas Revilla, N., Salomão, R. P., Segalin de Andrade, A., Silman, M. R., Spironello, W., ter Steege, H., Terborgh, J., Toledo, M., Valenzuela Gamarra, L., Vieira, I. C. G., Vilanova Torre, E., Vos, V., Phillips, O. L. (2015), Phylogenetic diversity of Amazonian tree communities. Diversity and Distributions, 21: 1295–1307. doi: 10.1111/ddi.12357, which has been published in final form at 10.1111/ddi.12357Aim: To examine variation in the phylogenetic diversity (PD) of tree communities across geographical and environmental gradients in Amazonia. Location: Two hundred and eighty-three c. 1 ha forest inventory plots from across Amazonia. Methods: We evaluated PD as the total phylogenetic branch length across species in each plot (PDss), the mean pairwise phylogenetic distance between species (MPD), the mean nearest taxon distance (MNTD) and their equivalents standardized for species richness (ses.PDss, ses.MPD, ses.MNTD). We compared PD of tree communities growing (1) on substrates of varying geological age; and (2) in environments with varying ecophysiological barriers to growth and survival. Results: PDss is strongly positively correlated with species richness (SR), whereas MNTD has a negative correlation. Communities on geologically young- and intermediate-aged substrates (western and central Amazonia respectively) have the highest SR, and therefore the highest PDss and the lowest MNTD. We find that the youngest and oldest substrates (the latter on the Brazilian and Guiana Shields) have the highest ses.PDss and ses.MNTD. MPD and ses.MPD are strongly correlated with how evenly taxa are distributed among the three principal angiosperm clades and are both highest in western Amazonia. Meanwhile, seasonally dry tropical forest (SDTF) and forests on white sands have low PD, as evaluated by any metric. Main conclusions: High ses.PDss and ses.MNTD reflect greater lineage diversity in communities. We suggest that high ses.PDss and ses.MNTD in western Amazonia results from its favourable, easy-to-colonize environment, whereas high values in the Brazilian and Guianan Shields may be due to accumulation of lineages over a longer period of time. White-sand forests and SDTF are dominated by close relatives from fewer lineages, perhaps reflecting ecophysiological barriers that are difficult to surmount evolutionarily. Because MPD and ses.MPD do not reflect lineage diversity per se, we suggest that PDss, ses.PDss and ses.MNTD may be the most useful diversity metrics for setting large-scale conservation priorities.FINCyT - PhD studentshipSchool of Geography of the University of LeedsRoyal Botanic Garden EdinburghNatural Environment Research Council (NERC)Gordon and Betty Moore FoundationEuropean Union's Seventh Framework ProgrammeERCCNPq/PELDNSF - Fellowshi

Phylogenetic diversity of Amazonian tree communities

Aim: To examine variation in the phylogenetic diversity (PD) of tree communities across geographical and environmental gradients in Amazonia. Location: Two hundred and eighty-three c. 1 ha forest inventory plots from across Amazonia. Methods: We evaluated PD as the total phylogenetic branch length across species in each plot (PDss), the mean pairwise phylogenetic distance between species (MPD), the mean nearest taxon distance (MNTD) and their equivalents standardized for species richness (ses.PDss, ses.MPD, ses.MNTD). We compared PD of tree communities growing (1) on substrates of varying geological age; and (2) in environments with varying ecophysiological barriers to growth and survival. Results: PDss is strongly positively correlated with species richness (SR), whereas MNTD has a negative correlation. Communities on geologically young- and intermediate-aged substrates (western and central Amazonia respectively) have the highest SR, and therefore the highest PDss and the lowest MNTD. We find that the youngest and oldest substrates (the latter on the Brazilian and Guiana Shields) have the highest ses.PDss and ses.MNTD. MPD and ses.MPD are strongly correlated with how evenly taxa are distributed among the three principal angiosperm clades and are both highest in western Amazonia. Meanwhile, seasonally dry tropical forest (SDTF) and forests on white sands have low PD, as evaluated by any metric. Main conclusions: High ses.PDss and ses.MNTD reflect greater lineage diversity in communities. We suggest that high ses.PDss and ses.MNTD in western Amazonia results from its favourable, easy-to-colonize environment, whereas high values in the Brazilian and Guianan Shields may be due to accumulation of lineages over a longer period of time. White-sand forests and SDTF are dominated by close relatives from fewer lineages, perhaps reflecting ecophysiological barriers that are difficult to surmount evolutionarily. Because MPD and ses.MPD do not reflect lineage diversity per se, we suggest that PDss, ses.PDss and ses.MNTD may be the most useful diversity metrics for setting large-scale conservation priorities

The number of tree species on Earth

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. Please note an (erratum/corrigendum) for this article is available via https://www.pnas.org/doi/10.1073/pnas.220278411

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

Evolutionary Heritage Influences Amazon Tree Ecology

Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change