Abstract
Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.
| Original language | English |
|---|---|
| Pages (from-to) | 5254-5268 |
| Number of pages | 15 |
| Journal | Global Change Biology |
| Volume | 28 |
| Issue number | 17 |
| Early online date | 2022 |
| DOIs | |
| Publication status | Published - Sept 2022 |
Bibliographical note
Funding Information:We are indebted to the countless researchers and field assistants who helped collect the field data compiled in the database and without whom this work would not have been possible. T.J. was supported by a UK NERC Independent Research Fellowship (grant: NE/S01537X/1). J.Ch. acknowledges an ‘Investissement d'Avenir’ grant managed by the Agence Nationale de la Recherche (CEBA grant: ANR‐10‐LABX‐25‐01 and TULIP grant: ANR‐10‐LABX‐0041). A.A. is currently supported by Hebei University (grant: 521100221033) and was previously supported by the Jiangsu Science and Technology Special Project (grant: BX2019084) and Metasequoia Faculty Research Startup Funding at Nanjing Forestry University (grant: 163010230). G.J.L.P. was supported by projects DynAfFor (grant: CZZ1636.01D) and P3FAC (grant: CZZ1636.02D) and by the International Foundation for Science (grant: D/5822‐1). T.R.F. was funded by NERC (grant: NE/N011570/1). L.F.A was supported by CAPES and ABC‐CNPq (grant: 004/96). B.B.L. was supported by COMPASS‐FME, a multi‐institutional project supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Environmental System Science Program. M.v.B. acknowledges funding from the Agua Salud Project, a collaboration between the Smithsonian Tropical Research Institute (STRI), the Panama Canal Authority (ACP) and the Ministry of the Environment of Panama (MiAmbiente), the Smithsonian Institution Forest Global Earth Observatory (ForestGEO), Heising‐Simons Foundation, HSBC Climate Partnership, Stanley Motta, Small World Institute Fund, Frank and Kristin Levinson, the Hoch family, the U Trust, the Working Land and Seascapes Program of the Smithsonian, the National Science Foundation (grant: EAR‐1360391), Singapore's Ministry of Education and Yale–NUS College (grant: IG16‐LR004). J.D. and H.L. were supported by the National Natural Science Foundation of China (grants: 41790422 and 42161144008). K.D. was supported by the African Forest Forum, and the DAAD within the framework of ClimapAfrica (Climate Research for Alumni and Postdocs in Africa) with funds of the Federal Ministry of Education and Research of Germany (grant: 91785431). E.R.L. was supported by a UKRI Future Leaders Fellowship (grant: MR/T019832/1). E.M. was supported by Swedish Energy Agency (grant: 35586‐1). J.A.M. was supported by Consejo Nacional de Ciencia y Tecnología (CONACYT; grant: CB‐2009‐01‐128136) and Universidad Nacional Autónoma de México (DGAPA‐PAPIIT; grants: IN218416 and IN217620). J.M.D‐. acknowledges funding from Reinforcing REDD+ and the South–South Cooperation Project, CONAFOR and USFS. S.C.R. acknowledges funding from FAPEMIG (grant: CAG2327‐07), DAAD/CAPES and CNPq. G.S. acknowledges funding by Manchester Metropolitan University's Environmental Science Research Centre. M.S. was funded by a grant from the Ministry of Education, Youth and Sports of the Czech Republic (grant: INTER‐TRANSFER LTT19018). A.T.T. acknowledges funding from the NSF (grant: 2003205). M.A.Z. thanks the MAPA‐Spain for granting access to the Spanish Forest Inventory data. We thank Prof Kristina Anderson‐Teixeira, Dr Anping Chen and an anonymous reviewer for their feedback which helped us improve our paper. Dr Abd Rahman Kassim, who contributed data to this project, sadly passed away before this paper was completed. Tallo
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© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.