| Summary: | Wood density (<inline-formula> <math display="inline"> <semantics> <mi>ρ</mi> </semantics> </math> </inline-formula>) is a trait involved in forest biomass estimates, forest ecology, prediction of stand stability, wood science, and engineering. Regardless of its importance, data on <inline-formula> <math display="inline"> <semantics> <mi>ρ</mi> </semantics> </math> </inline-formula> are scarce for a substantial number of species of the vast Atlantic Forest phytogeographic domain. Given that, the present paper describes a dataset composed of three data tables: (i) determinations of <inline-formula> <math display="inline"> <semantics> <mi>ρ</mi> </semantics> </math> </inline-formula> (kg m<sup>−3</sup>) for 153 species growing in three forest types within the subtropical Atlantic Forest, based on wood samples collected throughout the state of Santa Catarina, southern Brazil; (ii) a list of 719 tree/shrub species observed by a state-level forest inventory and a <inline-formula> <math display="inline"> <semantics> <mi>ρ</mi> </semantics> </math> </inline-formula> value assigned to each one of them based on local determinations and on a global database; (iii) the means and standard deviations of <inline-formula> <math display="inline"> <semantics> <mi>ρ</mi> </semantics> </math> </inline-formula> for 477 permanent sample plots located in the subtropical Atlantic Forest, covering ∼95,000 km<sup>2</sup>. The mean <inline-formula> <math display="inline"> <semantics> <mi>ρ</mi> </semantics> </math> </inline-formula> over the 153 sampled species is 538.6 kg m<sup>−3</sup> (standard deviation = 120.5 kg m<sup>−3</sup>), and the mean <inline-formula> <math display="inline"> <semantics> <mi>ρ</mi> </semantics> </math> </inline-formula> per sample plot, considering the three forest types, is 525.0 kg m<sup>−3</sup> (standard error = 1.8 kg m<sup>−3</sup>). The described dataset has potential to underpin studies on forest biomass, forest ecology, alternative uses of timber resources, as well as to enlarge the coverage of global datasets.
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