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Funder: Agua Salud Project, Funder: U.S. Department of Energy; Id: http://dx.doi.org/10.13039/100000015, Funder: CAPES; Id: http://dx.doi.org/10.13039/501100002322, 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.

Trait databases have become important resources for large-scale comparative studies in ecology and evolution. Here we introduce the AnimalTraits database, a curated database of body mass, metabolic rate and brain size, in standardised units, for terrestrial animals. The database has broad taxonomic breadth, including tetrapods, arthropods, molluscs and annelids from almost 2000 species and 1000 genera. All data recorded in the database are sourced from their original empirical publication, and the original metrics and measurements are included with each record. This allows for subsequent data transformations as required. We have included rich metadata to allow users to filter the dataset. The additional R scripts we provide will assist researchers with aggregating standardised observations into species-level trait values. Our goals are to provide this resource without restrictions, to keep the AnimalTraits database current, and to grow the number of relevant traits in the future.

Startup plants include seedlings and basal and epicormic resprouts. It has long been held that startups have different strategies from adult plants, but theory for what trait differences to expect is limited and not yet quantitatively tested. Three applicable concepts are analogous to human startup firms, R-shift, and trait-growth theory. All three suggest startups should be built with lower construction costs than established plants. This appears to be almost always true in terms of leaf mass per area (LMA), though many comparisons are complicated by the startups growing in lower light. Trait-growth theory predicts LMA should increase progressively with height or total leaf area, driven by higher conductive-pathway costs associated with each unit leaf area, and by greater reward from slowing leaf turnover. Basal resprouts often have somewhat higher LMA than seedlings, but possibly this is simply because they are larger. A number of eminently testable questions are identified. Prospects are good for a theoretically cogent and field-tested body of knowledge about plant startups.