Synthesizing tree biodiversity data to understand global patterns and processes of vegetation. (13th May 2021)

• Record Type: Journal Article
• Authors: Keppel, Gunnar; Craven, Dylan; Weigelt, Patrick; Smith, Stephen A.; van der Sande, Masha T.; Sandel, Brody; Levin, Sam C.; Kreft, Holger; Knight, Tiffany M.
• Editors: Pärtel, Meelis
• Is Part Of: Journal of vegetation science. Volume 32:Number 3(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-05-13
• Subjects: biodiversity -- biological databases -- conservation -- data integration and synthesis -- forests -- functional traits -- IUCN Red List -- macroecology -- species distribution -- tree diversity -- vegetation -- woodlands; Plant ecology -- Periodicals; Plant communities -- Periodicals; Plant populations -- Periodicals; 581.7
• DOI: 10.1111/jvs.13021
• Languages: English
• ISSNs: 1100-9233

Abstract

Abstract: Aims: Trees dominate the biomass in many ecosystems and are essential for ecosystem functioning and human well‐being. They are also one of the best‐studied functional groups of plants, with vast amounts of biodiversity data available in scattered sources. We here aim to illustrate that an efficient integration of these data could produce a more holistic understanding of vegetation. Methods: To assess the extent of potential data integration, we use key databases of plant biodiversity to: (a) obtain a list of tree species and their distributions; (b) identify coverage of and gaps in different aspects of tree biodiversity data; and (c) discuss large‐scale patterns of tree biodiversity in relation to vegetation. Results: Our global list of trees included 58, 044 species. Taxonomic coverage varies in three key databases, with data on the distribution, functional traits, and molecular sequences for about 84%, 45% and 44% of all tree species, which is >10% greater than for plants overall. For 28% of all tree species, data are available in all three databases. However, less data are digitally accessible about the demography, ecological interactions, and socio‐economic role of tree species. Integrating and imputing existing tree biodiversity data, mobilization of non‐digitized resources and targeted data collection, especially in tropical countries, could help closing some of the remaining data gaps. Conclusions: Due to their key ecosystem roles and having large amounts of accessible data, trees are a good model group for understanding vegetation patterns. Indeed, tree biodiversity data are already beginning to elucidate the community dynamics, functional diversity, evolutionary history and ecological interactions of vegetation, with great potential for future applications. An interoperable and openly accessible framework linking various databases would greatly benefit future macroecological studies and should be linked to a platform that makes information readily accessible to end users in biodiversity conservation and management. Abstract : Trees are one of the best‐studied plant groups. We show that integrating and imputing available biodiversity data for trees can produce a more holistic understanding of vegetation patterns and processes. Closing remaining data gaps and making data more accessible could further enhance the great potential of trees as a model group for macroecological studies.