Javascript must be enabled to continue!
A global map of wood density
View through CrossRef
Abstract
Wood density influences how quickly woody plants grow, how long they live and how much carbon they store, yet its global variation remains poorly mapped. Here we combined 109,626 wood density measurements from 16,829 species with 300,949 vegetation plots to produce a km-scale map of community-weighted wood density for every woody biome. Our model led to a prediction accuracy 32–51 % higher than previous global products, and a 1.8–3.7-fold wider wood density range (0.28–1.00 g cm
−3
; global mean: 0.57 g cm
−3
) than previously assumed. Spatial cross-validation showed low bias (±2.5 % of the mean), and uncertainties decreased from 20% in poorly sampled drylands and boreal regions to 5% in data-rich temperate forests. Mean annual temperature was the best predictor of community-weighted mean wood density, increasing by 0.01 g cm
−3
for every 1°C change. We deliver a low-bias, high-resolution wood density layer for Earth system models, together with spatially explicit error maps. This study represents a major step forward for carbon accounting and trait-based forecasts of vegetation change.
openRxiv
Fabian Jörg Fischer
Jérôme Chave
Amy Zanne
Tommaso Jucker
Alex Fajardo
Adeline Fayolle
Renato Augusto Ferreira de Lima
Ghislain Vieilledent
Hans Beeckman
Wannes Hubau
Tom De Mil
Daniel Wallenus
Ana María Aldana
Esteban Alvarez-Dávila
Luciana F. Alves
Deborah M. G. Apgaua
Fátima Arcanjo
Jean-François Bastin
Andrii Bilous
Philippe Birnbaum
Volodymyr Blyshchyk
Joli Borah
Vanessa Boukili
J. Julio Camarero
Luisa Casas
Roberto Cazzolla Gatti
Jeffrey Q. Chambers
Ezequiel Chimbioputo Fabiano
Brendan Choat
Edgar Cifuentes
Georgina Conti
David Coomes
Will Cornwell
Javid Ahmad Dar
Ashesh Kumar Das
Magnus Dobler
Dao Dougabka
David P. Edwards
Urs Eggli
Robert Evans
Daniel Falster
Philip Fearnside
Olivier Flores
Nikolaos Fyllas
Jean Gérard
Rosa C. Goodman
Daniel Guibal
L. Francisco Henao-Diaz
Vincent Hervé
Peter Hietz
Jürgen Homeier
Thomas Ibanez
Jugo Ilic
Steven Jansen
Rinku Moni Kalita
Tanaka Kenzo
Liana Kindermann
Subashree Kothandaraman
Martyna Kotowska
Yasuhiro Kubota
Patrick Langbour
James Lawson
André Luiz Alves de Lima
Roman Mathias Link
Anja Linstädter
Rosana López
Cate Macinnis-Ng
Luiz Fernando S. Magnago
Adam R. Martin
Ashley M. Matheny
James K. McCarthy
Regis B. Miller
Arun Jyoti Nath
Bruce Walker Nelson
Marco Njana
Euler Melo Nogueira
Alexandre Oliveira
Rafael Oliveira
Mark Olson
Yusuke Onoda
Keryn Paul
Daniel Piotto
Phil Radtke
Onja Razafindratsima
Tahiana Ramananantoandro
Jennifer Read
Sarah Richardson
Enrique G. de la Riva
Oris Rodríguez-Reyes
Samir G. Rolim
Victor Rolo
Julieta A. Rosell
Sassan Saatchi
Roberto Salguero-Gómez
Nadia S. Santini
Bernhard Schuldt
Luitgard Schwendenmann
Arne Sellin
Timothy Staples
Pablo R Stevenson
Somaiah Sundarapandian
Masha T van der Sande
Hans ter Steege
Shengli Tao
Bernard Thibaut
David Yue Phin Tng
José Marcelo Domingues Torezan
Boris Villanueva
Aaron Weiskittel
Jessie Wells
S. Joseph Wright
Kasia Zieminska
Alexander Zizka
Title: A global map of wood density
Description:
Abstract
Wood density influences how quickly woody plants grow, how long they live and how much carbon they store, yet its global variation remains poorly mapped.
Here we combined 109,626 wood density measurements from 16,829 species with 300,949 vegetation plots to produce a km-scale map of community-weighted wood density for every woody biome.
Our model led to a prediction accuracy 32–51 % higher than previous global products, and a 1.
8–3.
7-fold wider wood density range (0.
28–1.
00 g cm
−3
; global mean: 0.
57 g cm
−3
) than previously assumed.
Spatial cross-validation showed low bias (±2.
5 % of the mean), and uncertainties decreased from 20% in poorly sampled drylands and boreal regions to 5% in data-rich temperate forests.
Mean annual temperature was the best predictor of community-weighted mean wood density, increasing by 0.
01 g cm
−3
for every 1°C change.
We deliver a low-bias, high-resolution wood density layer for Earth system models, together with spatially explicit error maps.
This study represents a major step forward for carbon accounting and trait-based forecasts of vegetation change.
Related Results
Linking White‐Tailed Deer Density, Nutrition, and Vegetation in a Stochastic Environment
Linking White‐Tailed Deer Density, Nutrition, and Vegetation in a Stochastic Environment
ABSTRACT
Density‐dependent behavior underpins white‐tailed deer (
Odocoileus virginianus
) theory and...
Properties of Wood–Plastic Composites Manufactured from Two Different Wood Feedstocks: Wood Flour and Wood Pellets
Properties of Wood–Plastic Composites Manufactured from Two Different Wood Feedstocks: Wood Flour and Wood Pellets
Driven by the motive of minimizing the transportation costs of raw materials to manufacture wood–plastic composites (WPCs), Part I and the current Part II of this paper series expl...
QUALITY OF WOOD RESIDUE AND USED WOOD IN THE FUNCTION OF SUSTAINABLE WOOD FUEL PRODUCTION
QUALITY OF WOOD RESIDUE AND USED WOOD IN THE FUNCTION OF SUSTAINABLE WOOD FUEL PRODUCTION
This study presents the results of an analysis of relevant EU standards and regulations related to the quality of wood residue from the wood processing industry and used wood. The ...
Fundamental Concepts and Methodology for the Analysis of Animal Population Dynamics, with Particular Reference to Univoltine Species
Fundamental Concepts and Methodology for the Analysis of Animal Population Dynamics, with Particular Reference to Univoltine Species
This paper presents some concepts and methodology essential for the analysis of population dynamics of univoltine species. Simple stochastic difference equations, comprised of endo...
The Burden of Road Traffic Injuries: A Global Perspective
The Burden of Road Traffic Injuries: A Global Perspective
Introduction Road Traffic Injury (RTI) pose a significant health challenge. It represents the eighth leading cause of death globally, prompting the UN to designate 2011-2020 as...
PEMAHAMAN GURU IPA DALAM STRATEGI PEMBELAJARAN PETA PIKIRAN (MIND MAP)
PEMAHAMAN GURU IPA DALAM STRATEGI PEMBELAJARAN PETA PIKIRAN (MIND MAP)
Abstract. This researchs were conducted in Salatiga primary high school, Central Java and the subject of were taken from 23 science teachers which used interview and observation te...
Intra- and interspecific variation in wood density and fine-scale spatial distribution of stand-level wood density in a northern Thai tropical montane forest
Intra- and interspecific variation in wood density and fine-scale spatial distribution of stand-level wood density in a northern Thai tropical montane forest
Abstract:Tropical tree wood density is often related to other species-specific functional traits, e.g. size, growth rate and mortality. We would therefore expect significant associ...
Large Wood in Rivers
Large Wood in Rivers
Large wood consists of downed, dead pieces of wood. Although different size definitions have been proposed, the most widely used is pieces ³ 10 cm diameter and 1 m length. Many wor...

