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

AimEcological 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?LocationGlobal.Time period1990-2017.Major taxa studiedTrees.MethodsWe 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.ResultsCommunity 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 conclusionsBy 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.

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 Conservac & atilde;o da Natureza. FCT-UIDB/04033/2020. GFBi plot data collection in the S & atilde;o Francisco de Paula National Forest, Rio Grande do Sul, Brazil was financed by Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) (project 520053/1998-2). ReVaTene project is funded by the Education and Research Ministry of Cote 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 Kaffeewalder). GFBI data from Atlantic Forest, Brazil, was funded by the State of S & atilde;o 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 Espanola de Cooperacion Internacional para el Desarrollo (AECID)] and Fundacion 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 Espanola de Cooperacion Internacional para el Desarrollo (AECID)] and Fundacion Biodiversidad, in cooperation with the Universidad Mayor de San Simon (UMSS), the FOMABO (Manejo Forestal en las Tierras Tropicales de Bolivia) project and CIMAL (Compania 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.r 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, ). We thank the the Ministere des Forets, de la Faune et des Parcs du Quebec 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 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 (site accessed on 1 January 2015); the Italian Forest Inventory (2005 and 2015) was downloaded by GFBI at . Financial support from the Czech Science Foundation (project no. 21-26883S). Open access funding provided by Eidgenossische Technische Hochschule Zurich.