Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
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

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...
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...

Back to Top