Tallo: A global tree allometry and crown architecture database.
Journal Article (Journal Article)
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.
- Jucker, T; Fischer, FJ; Chave, J; Coomes, DA; Caspersen, J; Ali, A; Loubota Panzou, GJ; Feldpausch, TR; Falster, D; Usoltsev, VA; Adu-Bredu, S; Alves, LF; Aminpour, M; Angoboy, IB; Anten, NPR; Antin, C; Askari, Y; Muñoz, R; Ayyappan, N; Balvanera, P; Banin, L; Barbier, N; Battles, JJ; Beeckman, H; Bocko, YE; Bond-Lamberty, B; Bongers, F; Bowers, S; Brade, T; van Breugel, M; Chantrain, A; Chaudhary, R; Dai, J; Dalponte, M; Dimobe, K; Domec, J-C; Doucet, J-L; Duursma, RA; Enríquez, M; van Ewijk, KY; Farfán-Rios, W; Fayolle, A; Forni, E; Forrester, DI; Gilani, H; Godlee, JL; Gourlet-Fleury, S; Haeni, M; Hall, JS; He, J-K; Hemp, A; Hernández-Stefanoni, JL; Higgins, SI; Holdaway, RJ; Hussain, K; Hutley, LB; Ichie, T; Iida, Y; Jiang, H-S; Joshi, PR; Kaboli, H; Larsary, MK; Kenzo, T; Kloeppel, BD; Kohyama, T; Kunwar, S; Kuyah, S; Kvasnica, J; Lin, S; Lines, ER; Liu, H; Lorimer, C; Loumeto, J-J; Malhi, Y; Marshall, PL; Mattsson, E; Matula, R; Meave, JA; Mensah, S; Mi, X; Momo, S; Moncrieff, GR; Mora, F; Nissanka, SP; O'Hara, KL; Pearce, S; Pelissier, R; Peri, PL; Ploton, P; Poorter, L; Pour, MJ; Pourbabaei, H; Dupuy-Rada, JM; Ribeiro, SC; Ryan, C; Sanaei, A; Sanger, J; Schlund, M; Sellan, G; Shenkin, A; Sonké, B; Sterck, FJ; Svátek, M; Takagi, K; Trugman, AT; Ullah, F; Vadeboncoeur, MA; Valipour, A; Vanderwel, MC; Vovides, AG; Wang, W; Wang, L-Q; Wirth, C; Woods, M; Xiang, W; Ximenes, FDA; Xu, Y; Yamada, T; Zavala, MA
- September 2022
Volume / Issue
- 28 / 17
Start / End Page
- 5254 - 5268
Pubmed Central ID
Electronic International Standard Serial Number (EISSN)
International Standard Serial Number (ISSN)
Digital Object Identifier (DOI)