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Dominance and rarity in tree communities across the globe: Patterns, predictors and threats

  • Iris Hordijk*
  • , Lalasia Bialic-Murphy
  • , Thomas Lauber
  • , Devin Routh
  • , Lourens Poorter
  • , Malin C. Rivers
  • , Hans ter Steege
  • , Jingjing Liang
  • , Peter B. Reich
  • , Sergio de-Miguel
  • , Gert Jan Nabuurs
  • , Javier G.P. Gamarra
  • , Han Y.H. Chen
  • , Mo Zhou
  • , Susan K. Wiser
  • , Hans Pretzsch
  • , Alain Paquette
  • , Nicolas Picard
  • , Bruno Hérault
  • , Jean Francois Bastin
  • Giorgio Alberti, Meinrad Abegg, Yves C. Adou Yao, Angelica M. Almeyda Zambrano, Braulio V. Alvarado, Esteban Alvarez-Davila, Patricia Alvarez-Loayza, Luciana F. Alves, Christian Ammer, Clara Antón-Fernández, Alejandro Araujo-Murakami, Luzmila Arroyo, Valerio Avitabile, Gerardo A. Aymard Corredor, Timothy Baker, Olaf Banki, Jorcely Barroso, Meredith L. Bastian, Luca Birigazzi, Philippe Birnbaum, Robert Bitariho, Pascal Boeckx, Frans Bongers, Olivier Bouriaud, Pedro H.S. Brancalion, Susanne Brandl, Roel Brienen, Eben N. Broadbent, Helge Bruelheide, Filippo Bussotti, Roberto Cazzolla Gatti, Ricardo G. Cesar, Goran Cesljar, Robin Chazdon, Chelsea Chisholm, Emil Cienciala, Connie J. Clark, David B. Clar, Gabriel Colletta, David Coomes, Fernando Cornejo Valverde, Jose J. Corral-Rivas, Philip Crim, Jonathan Cumming, Selvadurai Dayanandan, André L. de Gasper, Mathieu Decuyper, Géraldine Derroire, Ben DeVries, Ilija Djordjevic, Amaral Iêda, Aurélie Dourdain, Jiri Dolezal, Nestor Laurier Engone Obiang, Brian Enquist, Teresa Eyre, Adandé Belarmain Fandohan, Tom M. Fayle, Leandro V. Ferreira, Ted R. Feldpausch, Leena Finér, Markus Fischer, Christine Fletcher, Lorenzo Frizzera, Damiano Gianelle, Henry B. Glick, David Harris, Andrew Hector, Andreas Hemp, Geerten Hengeveld, John Herbohn, Annika Hillers, Eurídice N. Honorio Coronado, Cang Hui, Hyunkook Cho, Thomas Ibanez, Ilbin Jung, Nobuo Imai, Andrzej M. Jagodzinski, Bogdan Jaroszewicz, Vivian Johannsen, Carlos A. Joly, Tommaso Jucker, Viktor Karminov, Kuswata Kartawinata, Elizabeth Kearsley, David Kenfack, Deborah Kennard, Sebastian Kepfer-Rojas, Gunnar Keppel, Mohammed Latif Khan, Timothy Killeen, Hyun Seok Kim, Kanehiro Kitayama, Michael Köhl, Henn Korjus, Florian Kraxner, Diana Laarmann, Mait Lang, Simon Lewis, Huicui Lu, Natalia Lukina, Brian Maitner, Yadvinder Malhi, Eric Marcon, Beatriz Schwantes Marimon, Ben Hur Marimon-Junior, Andrew Robert Marshall, Emanuel Martin, Olga Martynenko, Jorge A. Meave, Omar Melo-Cruz, Casimiro Mendoza, Cory Merow, Stanislaw Miscicki, Abel Monteagudo Mendoza, Vanessa Moreno, Sharif A. Mukul, Philip Mundhenk, Maria G. Nava-Miranda, David Neill, Victor Neldner, Radovan Nevenic, Michael Ngugi, Pascal A. Niklaus, Jacek Oleksyn, Petr Ontikov, Edgar Ortiz-Malavasi, Yude Pan, Alexander Parada-Gutierrez, Elena Parfenova, Minjee Park, Marc Parren, Narayanaswamy Parthasarathy, Pablo L. Peri, Sebastian Pfautsch, Oliver L. Phillips, Maria Teresa Piedade, Daniel Piotto, Nigel C.A. Pitman, Irina Polo, Axel Dalberg Poulsen, John R. Poulsen, Freddy Ramirez Arevalo, Zorayda Restrepo-Correa, Mirco Rodeghiero, Samir Rolim, Anand Roopsind, Francesco Rovero, Ervan Rutishauser, Purabi Saikia, Christian Salas-Eljatib, Peter Schall, Dmitry Schepaschenko, Michael Scherer-Lorenzen, Bernhard Schmid, Jochen Schöngart, Eric B. Searle, Vladimír Seben, Josep M. Serra-Diaz, Douglas Sheil, Anatoly Shvidenko, Javier Silva-Espejo, Marcos Silveira, James Singh, Plinio Sist, Ferry Slik, Bonaventure Sonké, Alexandre F. Souza, Krzysztof Stereńczak, Jens Christian Svenning, Miroslav Svoboda, Ben Swanepoel, Natalia Targhetta, Nadja Tchebakova, Raquel Thomas, Elena Tikhonova, Peter Umunay, Vladimir Usoltsev, Renato Valencia, Fernando Valladares, Fons van der Plas, Tran Van Do, Michael E. Van Nuland, Rodolfo Vasquez Martinez, Hans Verbeeck, Helder Viana, Alexander C. Vibrans, Simone Vieira, Klaus von Gadow, Hua Feng Wang, James Watson, Gijsbert D.A. Werner, Florian Wittmann, Verginia Wortel, Roderick Zagt, Tomasz Zawila-Niedzwiecki, Chunyu Zhang, Xiuhai Zhao, Zhi Xin Zhu, Irie Casimir Zo-Bi, Daniel S. Maynard, Thomas W. Crowther
*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Aim: Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species?. Location: Global. Time period: 1990–2017. Major taxa studied: Trees. Methods: We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated. Results: Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large-scale land degradation. Main conclusions: By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large-scale management and conservation practices.

Original languageEnglish
Article numbere13889
JournalGlobal Ecology and Biogeography
Volume33
Issue number10
DOIs
StatePublished - Oct 2024

Bibliographical note

Publisher Copyright:
© 2024 The Author(s). Global Ecology and Biogeography published by John Wiley & Sons Ltd.

Funding

This research has been funded by a grant from DOB Ecology. Swiss National Science Foundation, Ambizione grant #PZ00P3_193612 to DSM. JCS considers this work a contribution to Center for Ecological Dynamics in a Novel Biosphere (ECONOVO), funded by Danish National Research Foundation (grant DNRF173), and his VILLUM Investigator project “Biodiversity Dynamics in a Changing World”, funded by VILLUM FONDEN (grant 16549). The GFBI data from New Zealand were drawn from the Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment and sourced from the New Zealand National Vegetation Survey Databank’. Russian Science Foundation Project 21-46-07002 for the plot data collected in the Krasnoyarsk region. Instituto de Conservação da Natureza. FCT—UIDB/04033/2020. GFBi plot data collection in the São Francisco de Paula National Forest, Rio Grande do Sul, Brazil was financed by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (project 520053/1998-2). ReVaTene project is funded by the Education and Research Ministry of Côte d'Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD. GFBI data from southern Ethiopia were collected with funding from the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMU) (IKI-1 project number 09 II 066ETH A Kaffeewälder). GFBI data from Atlantic Forest, Brazil, was funded by the State of São Paulo Research Foundation (FAPESP 03/12595-7) as part of the BIOTA Program. COTEC/IF 41.065/2005 and IBAMA/CGEN 093/2005 granted permits to establish the permanent plots and collect data. The Exploratory plots of FunDivEUROPE (with sites in Germany, Finland, Poland, Romania, Italy and Spain) received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement 265171. Permission to work in the MAWAS region of Indonesia: the BOS Foundation, the Indonesian Institute of Sciences (LIPI), the Direktorat Fasilitasi Organisasi Politik dan Kemasyarakatan, Departamen Dalam Negri and the BKSDA Palangkaraya. Funding sources: The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (Grant No. 0452995) and the Wenner-Gren Foundation for Anthropological Research (Grant No. 7330). This study was supported by National Natural Science Foundation of China (31800374), Shandong Provincial Natural Science Foundation (ZR2019BC083). The Spanish Agency for International Development Cooperation [Agencia Española de Cooperación Internacional para el Desarrollo (AECID)] and Fundación Biodiversidad, in cooperation with the governments of Syria and Lebanon. Projects D/9170/07, D/018222/08, D/023225/09 and D/032548/10 funded by the Spanish Agency for International Development Cooperation [Agencia Española de Cooperación Internacional para el Desarrollo (AECID)] and Fundación Biodiversidad, in cooperation with the Universidad Mayor de San Simón (UMSS), the FOMABO (Manejo Forestal en las Tierras Tropicales de Bolivia) project and CIMAL (Compañía Industrial Maderera Ltda.). All persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3). Research was supported by APVV 20-0168 from the Slovak Research and Development Agency. E.C. acknowledges funding from 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); We acknowledge collaboration with the International Boreal Forest Research Association (IBFRA, http://ibfra.org). We thank the the Ministère des Forêts, de la Faune et des Parcs du Québec for access to their database of permanent sample plots. We thank the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network, and the ForestPlots.net initiative for their contributions from Amazonian and African forests. These were supported by many projects including an ERC Advanced Grant 291585 (“T-FORCES”) and a Royal Society Wolfson Research Merit Award to O.L.P.; RAINFOR plots were additionally supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council (NERC), notably NERC Consortium Grants AMAZONICA (NE/F005806/1), TROBIT (NE/D005590/1), and BIO- RED (NE/N012542/1). This study was supported by GACR project 21-27454S from the Czech Science Foundation. Financial support from DBT, Govt. of India, through the project ‘Mapping and quantitative assessment of geographic distribution and population status of plant resources of Eastern Himalayan region’ is highly acknowledged (Reference no. BT/PR7928/NDB/52/9/2006 dated 29.09.2006). GFBI data from Mexico was funded by many projects including the National Forestry Commission (CONAFOR), Council of Science and Technology of the State of Durango (COCYTED), the Natural Environment Research Council, UK (NERC; NE/T011084/1), and local support of Ejidos and Comunidades. The French National Forest Inventory (NFI campaigns, raw data 2005 and following annual surveys) was downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159 (site accessed on 1 January 2015); the Italian Forest Inventory (2005 and 2015) was downloaded by GFBI at https://inventarioforestale.org/. Financial support from the Czech Science Foundation (project no. 21-26883S). Open access funding provided by Eidgenossische Technische Hochschule Zurich. This research has been funded by a grant from DOB Ecology. Swiss National Science Foundation, Ambizione grant #PZ00P3_193612 to DSM. JCS considers this work a contribution to Center for Ecological Dynamics in a Novel Biosphere (ECONOVO), funded by Danish National Research Foundation (grant DNRF173), and his VILLUM Investigator project “Biodiversity Dynamics in a Changing World”, funded by VILLUM FONDEN (grant 16549). The GFBI data from New Zealand were drawn from the Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment and sourced from the New Zealand National Vegetation Survey Databank’. Russian Science Foundation Project 21‐46‐07002 for the plot data collected in the Krasnoyarsk region. Instituto de Conservação da Natureza. FCT—UIDB/04033/2020. GFBi plot data collection in the São Francisco de Paula National Forest, Rio Grande do Sul, Brazil was financed by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (project 520053/1998‐2). ReVaTene project is funded by the Education and Research Ministry of Côte d'Ivoire, as part of the Debt Reduction‐Development Contracts (C2Ds) managed by IRD. GFBI data from southern Ethiopia were collected with funding from the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMU) (IKI‐1 project number 09 II 066ETH A Kaffeewälder). GFBI data from Atlantic Forest, Brazil, was funded by the State of São Paulo Research Foundation (FAPESP 03/12595‐7) as part of the BIOTA Program. COTEC/IF 41.065/2005 and IBAMA/CGEN 093/2005 granted permits to establish the permanent plots and collect data. The Exploratory plots of FunDivEUROPE (with sites in Germany, Finland, Poland, Romania, Italy and Spain) received funding from the European Union Seventh Framework Programme (FP7/2007‐2013) under grant agreement 265171. Permission to work in the MAWAS region of Indonesia: the BOS Foundation, the Indonesian Institute of Sciences (LIPI), the Direktorat Fasilitasi Organisasi Politik dan Kemasyarakatan, Departamen Dalam Negri and the BKSDA Palangkaraya. Funding sources: The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (Grant No. 0452995) and the Wenner‐Gren Foundation for Anthropological Research (Grant No. 7330). This study was supported by National Natural Science Foundation of China (31800374), Shandong Provincial Natural Science Foundation (ZR2019BC083). The Spanish Agency for International Development Cooperation [Agencia Española de Cooperación Internacional para el Desarrollo (AECID)] and Fundación Biodiversidad, in cooperation with the governments of Syria and Lebanon. Projects D/9170/07, D/018222/08, D/023225/09 and D/032548/10 funded by the Spanish Agency for International Development Cooperation [Agencia Española de Cooperación Internacional para el Desarrollo (AECID)] and Fundación Biodiversidad, in cooperation with the Universidad Mayor de San Simón (UMSS), the FOMABO (Manejo Forestal en las Tierras Tropicales de Bolivia) project and CIMAL (Compañía Industrial Maderera Ltda.). All persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3). Research was supported by APVV 20‐0168 from the Slovak Research and Development Agency. E.C. acknowledges funding from 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); We acknowledge collaboration with the International Boreal Forest Research Association (IBFRA, http://ibfra.org ). We thank the the Ministère des Forêts, de la Faune et des Parcs du Québec for access to their database of permanent sample plots. We thank the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network, and the ForestPlots.net initiative for their contributions from Amazonian and African forests. These were supported by many projects including an ERC Advanced Grant 291585 (“T‐FORCES”) and a Royal Society Wolfson Research Merit Award to O.L.P.; RAINFOR plots were additionally supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council (NERC), notably NERC Consortium Grants AMAZONICA (NE/F005806/1), TROBIT (NE/D005590/1), and BIO‐ RED (NE/N012542/1). This study was supported by GACR project 21‐27454S from the Czech Science Foundation. Financial support from DBT, Govt. of India, through the project ‘Mapping and quantitative assessment of geographic distribution and population status of plant resources of Eastern Himalayan region’ is highly acknowledged (Reference no. BT/PR7928/NDB/52/9/2006 dated 29.09.2006). GFBI data from Mexico was funded by many projects including the National Forestry Commission (CONAFOR), Council of Science and Technology of the State of Durango (COCYTED), the Natural Environment Research Council, UK (NERC; NE/T011084/1), and local support of Ejidos and Comunidades. The French National Forest Inventory (NFI campaigns, raw data 2005 and following annual surveys) was downloaded by GFBI at https://inventaire‐forestier.ign.fr/spip.php?rubrique159 (site accessed on 1 January 2015); the Italian Forest Inventory (2005 and 2015) was downloaded by GFBI at https://inventarioforestale.org/ . Financial support from the Czech Science Foundation (project no. 21‐26883S). Open access funding provided by Eidgenossische Technische Hochschule Zurich.

FundersFunder number
Fundación Biodiversidad
African Tropical Rainforest Observation Network
Departamen Dalam Negri
Education and Research Ministry of Côte d'Ivoire
Fundação para a Ciência e a Tecnologia
International Climate Initiative
DOB Ecology
American Society of Primatologists
Leakey Foundation
IKI
Ministère des Forêts, de la Faune et des Parcs
Universidad Mayor de San Simón
CIMAL
British Orthodontic Society Foundation
National Forestry Commission
Instituto de Conservação da Natureza
Duke University
Eidgenössische Technische Hochschule Zürich
FOMABO
Amazon Forest Inventory Network
European Commission
BKSDA
European Union Seventh Framework Programme
Italian Forest Inventory
Direktorat Fasilitasi Organisasi Politik dan Kemasyarakatan
Agencia Española de Cooperación Internacional para el Desarrollo
Lembaga Ilmu Pengetahuan Indonesia
LUCAS programme for the New Zealand Ministry for the Environment
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety
Institut de recherche pour le développement
Compañía Industrial Maderera Ltda
International Boreal Forest Research Association
Royal Society
Comisión Nacional Forestal
GFBI
Manejo Forestal en las Tierras Tropicales de Bolivia
New Zealand National Vegetation Survey Databank’
Gordon and Betty Moore Foundation
Russian Science Foundation21-46-07002
Agentúra na Podporu Výskumu a VývojaCZ.02.1.01/0.0/0.0/16_019/0000797, 20‐0168
National Natural Science Foundation of China31800374
Department of Biotechnology, Ministry of Science and Technology, IndiaBT/PR7928/NDB/52/9/2006 dated 29.09.2006
Conselho Nacional de Desenvolvimento Científico e Tecnológico520053/1998‐2
European Research Council291585
Natural Environment Research CouncilNE/T011084/1, NE/F005806/1
Villum Fonden16549
Wenner-Gren Foundation7330
TROBITNE/D005590/1, NE/N012542/1
Consejo de Cíencia y Tecnología del Estado de Durango21‐26883S
Grantová Agentura České Republiky21‐27454S
Binzhou Medical University09 II 066ETH
Fundação de Amparo à Pesquisa do Estado de São Paulo03/12595‐7, COTEC/IF 41.065/2005
Natural Science Foundation of Shandong ProvinceD/018222/08, D/032548/10, ZR2019BC083, D/9170/07, D/023225/09
Seventh Framework Programme265171
Danmarks GrundforskningsfondDNRF173
National Science Foundation0452995

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 15 - Life on Land
      SDG 15 Life on Land

    Keywords

    • community
    • dominance
    • environmental predictors
    • forests
    • macroecology
    • rarity
    • species abundance
    • species population threats

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