Abstract/Summary

Motivation Leaf traits represent an important component of plant functional strategies, and those related to carbon fixation and nutrient acquisition form the leaf economics spectrum. However, observations of functional leaf traits are underrepresented in tropical regions in comparison with those in temperate areas. Brazil, a country with continental scale and vast biodiversity is a timely example, where many biomes are impacted by human activities and climate change. However, leaf traits relevant to understand vegetation responses to these impacts remain poorly quantified for many species found in the country. We compiled an extensive data set of four functional leaf traits for native woody species occurring in the Brazilian territory. In addition to trait observations, sampling dates and geo-references were compiled and climatic parameters and soil properties of each sampling site were extracted from several databases. Main types of variables contained The LT-Brazil data set contains 3,479, 1,216, 775 and 775 clean observations of leaf mass per area, leaf nitrogen (N) concentration per unit mass, leaf phosphorus (P) concentration per unit mass, and leaf N : P ratio, respectively, from native woody species, encompassing information of biome, vegetation, taxonomic data, geographical coordinates, climatic parameters, as well as soil properties. Spatial location and grain We compiled trait observations from 223 sites under native vegetation distributed in all main biomes (i.e., Amazônia, Caatinga, Cerrado, Mata Atlântica, Pampa and Pantanal) across the Brazilian territory. Time period and grain The data represent information published and/or sampled during the last 25 years. Major taxa and level of measurement Our compilation was focused on trait data observed for native woody species, excluding monocots, palm trees, herbs, and hemiparasitic plants. Thus, 108, 478 and 1,321 botanical families, genera and species were included, covering c. 9% of the woody angiosperm flora of Brazil. Software format Data are provided as comma-separated value (.csv) files.