Towards the Fulfillment of a Knowledge Gap: Wood Densities for Species of the Subtropical Atlantic Forest

Laio Zimermann Oliveira, Heitor Felippe Uller, Aline Renata Klitzke, Jackson Roberto Eleotério and Alexander Christian Vibrans
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Laio Zimermann Oliveira: Departamento de Engenharia Florestal, Universidade Regional de Blumenau, Blumenau 89030-000, Santa Catarina, Brazil
Heitor Felippe Uller: Departamento de Engenharia Florestal, Universidade Regional de Blumenau, Blumenau 89030-000, Santa Catarina, Brazil
Aline Renata Klitzke: Planejamento Florestal, Klabin S.A., Otacílio Costa 88540-000, Santa Catarina, Brazil
Jackson Roberto Eleotério: Departamento de Engenharia Florestal, Universidade Regional de Blumenau, Blumenau 89030-000, Santa Catarina, Brazil
Alexander Christian Vibrans: Departamento de Engenharia Florestal, Universidade Regional de Blumenau, Blumenau 89030-000, Santa Catarina, Brazil

Data, 2019, vol. 4, issue 3, 1-10

Abstract: Wood density ( ρ ) is a trait involved in forest biomass estimates, forest ecology, prediction of stand stability, wood science, and engineering. Regardless of its importance, data on ρ 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 ρ (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 ρ value assigned to each one of them based on local determinations and on a global database; (iii) the means and standard deviations of ρ for 477 permanent sample plots located in the subtropical Atlantic Forest, covering ∼95,000 km 2 . The mean ρ over the 153 sampled species is 538.6 kg m −3 (standard deviation = 120.5 kg m −3 ), and the mean ρ 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.

Keywords: rainforest; wood specific gravity; aboveground biomass; functional traits (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
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