DOI: 10.5061/dryad.31zcrjf1k
title: The Tervuren xylarium Wood Density Database (TWDD)

description: Wood density is a key plant property, indispensable for estimating forest
 biomass. Yet, despite tropical regions' substantial contributions to
 global tree diversity and carbon cycling, they remain underrepresented in
 wood density datasets such as the CIRAD and Global Wood Density Database
 (GWDD). To address this gap, we present the ‘Tervuren xylarium Wood
 Density Database’ (TWDD), containing 13,332 samples from 2,994 species,
 1,022 genera, and 156 plant families across six continents (72% from
 Africa). TWDD offers direct measurements of oven-dry (oven-dry
 mass/oven-dry volume, all samples), air-dry (air-dry mass/air-dry volume,
 6,408 samples), green (green mass/green volume, 1,657 samples), and basic
 wood density (oven-dry mass/green volume, 1,686 samples). Basic density
 was estimated for the remaining 11,646 samples via conversion from
 oven-dry density. TWDD closes a substantial wood density data gap,
 especially in Africa, adding 1,164 new species, 160 new genera, and 8 new
 plant families not included in GWDD or CIRAD datasets. The TWDD provides a
 critical resource for advancing research on forest community dynamics,
 ecosystem functioning, carbon cycling, and trait-based ecology worldwide.
description: # The Tervuren xylarium Wood Density Database (TWDD) Dataset DOI:
 [10.5061/dryad.31zcrjf1k](https://doi.org/10.5061/dryad.31zcrjf1k) ##
 Description of the data and file structure The ‘Tervuren xylarium Wood
 Density Database’ (TWDD) contains 13,332 samples from 2,994 species, 1,022
 genera, and 156 plant families across six continents (72% from Africa).
 TWDD offers direct measurements of oven-dry (oven-dry mass/oven-dry
 volume, all samples), air-dry (air-dry mass/air-dry volume, 6,408
 samples), green (green mass/green volume, 1,657 samples), and basic wood
 density (oven-dry mass/green volume, 1,686 samples). Basic density was
 estimated for the remaining 11,646 samples via conversion from oven-dry
 density. TWDD closes a substantial wood density data gap, especially in
 Africa, adding 1,164 new species, 160 new genera, and 8 new plant families
 not included in GWDD or CIRAD datasets. ### Files and variables #### File:
 OvenDryingExperiment.csv **Description:** This csv file contains the data
 of the oven-drying time experiment, with the mass, volume, and density of
 wood samples in air-dry conditions (columns: m_airdry, V_airdry, and
 WD_airdry) and after oven-drying for 24h (columns: m_ovendry_24h, V\_
 ovendry_24h, and WD_ovendry_24h) and 48h (columns: m_ovendry_48h,
 V_ovendry_48h, and WD_ovendry_48h). This was shown for each of the four
 classes representing low and high wood density and volume (column:
 Category). ##### Variables * Category: The category of wood density (high
 or low) and sample volume (high or low) * Tw: The unique identified number
 of the Tervuren xylarium. * m_airdry: Air-dry mass of the wood (g). *
 m_ovendry_24h: Oven-dry mass of the wood after 24h oven-drying at 104°C
 (g). * m_ovendry_48h: Oven-dry mass of the wood after 48h oven-drying at
 104°C (g). * V_airdry: Air-dry volume of the wood (cm^3). *
 V_ovendry_24h: Oven-dry volume of the wood after 24h oven-drying at 104°C
 (cm^3). * V_ovendry_48h: Oven-dry volume of the wood after 48h oven-drying
 at 104°C (cm^3). * WD_airdry: Air-dry wood density of the wood (g/cm^3). *
 WD_ovendry_24h: Oven-dry volume of the wood after 24h oven-drying at 104°C
 (g/cm^3). * WD_ovendry_48h: Oven-dry volume of the wood after 48h
 oven-drying at 104°C (g/cm^3). #### File: TWDD_code.R **Description:** The
 R file creates all figures and statistics reported in this paper. To
 generate a map of the provinces of the Democratic Republic of Congo, we
 used shapefiles downloaded from [Download Democratic Republic of the Congo
 GIS
 data](https://www.igismap.com/download-democratic-republic-of-the-congo-administrative-boundary-shapefiles-provinces-districts-and-more/). Furthermore, to assess the consistency of our wood density data with other databases, we used the Global Wood Density Database ([https://doi.org/10.5061/dryad.234](https://doi.org/10.5061/dryad.234)) and CIRAD datasets ([https://doi.org/10.18167/DVN1/KRVF0E](https://doi.org/10.18167/DVN1/KRVF0E) and [https://doi.org/10.18167/DVN1/CDHU51](https://doi.org/10.18167/DVN1/CDHU51)). #### File: TWDD.xlsx **Description:** The TWDD dataset is stored in an Excel file with the following three sheets: * ‘Legend’: contains a description of the columns of the dataset. - ‘TWDD’: contains the wood density data and metadata.  * ‘Overview Table’: contains an overview of the regional geographic and taxonomic coverage of the dataset. ## Code/software R version 4.4.2\ R working packages: readxl, ggplot2, ggpubr, ggpmisc, EnvStats, tidyr, dplyr, readr, sp, sf, tidytext, stringr, viridis, ggh4x, ggridges, smatr, WorldFlora, cowplot, forcats, Metrics ## Access information Data was derived from the following sources: * Shapefiles for mapping provinces in the Democratic Republic of the Congo: [Download Democratic Republic of the Congo GIS data](https://www.igismap.com/download-democratic-republic-of-the-congo-administrative-boundary-shapefiles-provinces-districts-and-more/) * Wood density data from the Global Wood Density Database (https://doi.org/10.5061/dryad.234) and the CIRAD datasets ([https://doi.org/10.18167/DVN1/KRVF0E](https://doi.org/10.18167/DVN1/KRVF0E) and [https://doi.org/10.18167/DVN1/CDHU51](https://doi.org/10.18167/DVN1/CDHU51)).