A key issue in large-area inventories is defining a suitable sampling design and the effort required to obtain reliable estimates of species richness and forest attributes, especially in species-diverse forests. To address this issue, data from 418 systematically distributed 0.4 ha plots were collected. Estimators of nonparametric species richness were employed to assess the floristic representativeness of data collected in three forest types in the Brazilian Atlantic Forest. The sampling sufficiency of forest attributes was evaluated as a function of sample size. Altogether, 831 tree/shrub species were recorded. The data acquired through the systematic sampling design were representative of both species richness and basal area. The confidence intervals’ length would not substantially decrease by using more than 70 % of the reference sample (n = 364), thereby reaching a length of ∼5 % of the sample mean. Nevertheless, reliable estimates of species richness for diverse forests demand a thorough sampling approach far more exacting so as to achieve acceptable population estimates of forest attributes. Though the study area is regarded as a biodiversity hotspot, the forest stands showed diminished species richness, basal area, stem volume and biomass when compared to old-growth stands. As regards species richness, the data provided evidence of contrasting great γ-diversity (at the forest type level) and small α-diversity (at the forest stand level). Amongst anthropic impacts, illegal logging and extensive cattle grazing within stands are undoubtedly key factors that threaten forest conservation in the study area.

Wood density ( $\rho$ ) is a trait involved in forest biomass estimates, forest ecology, prediction of stand stability, wood science, and engineering. Regardless of its importance, data on $\rho$ 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 $\rho$ (kg m⁻³) 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 $\rho$ value assigned to each one of them based on local determinations and on a global database; (iii) the means and standard deviations of $\rho$ for 477 permanent sample plots located in the subtropical Atlantic Forest, covering ∼95,000 km². The mean $\rho$ over the 153 sampled species is 538.6 kg m⁻³ (standard deviation = 120.5 kg m⁻³), and the mean $\rho$ per sample plot, considering the three forest types, is 525.0 kg m⁻³ (standard error = 1.8 kg m⁻³). 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.

Plant functional traits have been incorporated in studies of vegetation ecology to better understand the mechanisms of ecological processes. For this reason, a global effort has been made to collect functional traits data for as many species as possible. In light of this, we identified the most common species of an area of 15,335 km² inserted in the subtropical Atlantic Rain Forest in Southern Brazil. Then, we compiled functional trait information mostly from field samples, but also from herbarium and literature. The dataset presents traits of leaf, branch, maximum potential height, seed mass, and dispersion syndrome of 117 species, including trees, tree ferns, and palms. We also share images of anatomical features of branches used to measure wood traits. Data tables present mean trait values at individual and species level. Images of wood and stomatal features may be useful to assess other anatomical traits that were not covered in the data tables for the anatomical determination of species and/or for educational purposes.

Forests are the largest biological reservoir of biomass and carbon on the planet. This fact turns them into the main tool to neutralise the CO2 emitted by human activities. Despite such importance, the uncertainties associated with biomass estimates in forests, especially in (sub)tropical forests, are enormous. Facing this scenario, the objectives of this study were (1) to quantify through destructive sampling the aboveground biomass (AGB) of 105 trees of 47 species occurring in a secondary subtropical evergreen rainforest in Brazil; (2) to investigate the AGB distribution in different tree compartments; and (3) to fit tree-level models to improve biomass estimates for the referred forest type. The results revealed that most of the AGB was stored in the compartments stem and large branches (diameter ≥ 5 cm). There was an increase in the proportion of biomass – in relation to the total tree AGB (kg) – allocated in the large branches as tree diameter at breast height (DBH) increased; this pattern was not ob...