A global map of root biomass across the world’s forests

Root plays a key role in plant growth and functioning. Here we combine 10307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially-explicit global high-resolution (~ 1km) root biomass dataset, including fine and coarse roots. In total, 142 ± 32 Pg of live dry matter biomass is stored below-ground, that is a global average root:shoot biomass ratio of 0.25 ± 0.10. Our estimations of total root biomass in tropical, temperate and boreal forests are 44-226% smaller than earlier studies1–3. The smaller estimation is attributable to the updated forest area, spatially explicit above-ground biomass density used to predict the patterns of root biomass, new root measurements and upscaling methodology. We show specifically that the root shoot allometry is one underlying driver that leads to methodological overestimation of root biomass in previous estimations.

[1]  M. Herold,et al.  The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations , 2021, Earth System Science Data.

[2]  G. Heuvelink,et al.  SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty , 2021, SOIL.

[3]  M. Herold,et al.  The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations , 2020 .

[4]  Z. Ouyang,et al.  A review of biomass equations for China's tree species , 2020 .

[5]  Tyler J. Lark,et al.  Harmonized global maps of above and belowground biomass carbon density in the year 2010 , 2019, Scientific Data.

[6]  S. Niu,et al.  Global soil acidification impacts on belowground processes , 2019, Environmental Research Letters.

[7]  P. Ciais,et al.  The global forest age dataset and its uncertainties (GFADv1.1) , 2019 .

[8]  M. Santoro GlobBiomass - global datasets of forest biomass , 2018 .

[9]  F. Kraxner,et al.  Improved Estimates of Biomass Expansion Factors for Russian Forests , 2018, Forests.

[10]  Nadejda A. Soudzilovskaia,et al.  Mapping local and global variability in plant trait distributions , 2017, Proceedings of the National Academy of Sciences.

[11]  R. Bailey,et al.  Description of the Ecoregions of the United States , 2017 .

[12]  R. Houghton,et al.  Tropical forests are a net carbon source based on aboveground measurements of gain and loss , 2017, Science.

[13]  Stephen E. Fick,et al.  WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas , 2017 .

[14]  Ying Fan,et al.  Hydrologic regulation of plant rooting depth , 2017, Proceedings of the National Academy of Sciences.

[15]  Jens Kattge,et al.  A global Fine-Root Ecology Database to address below-ground challenges in plant ecology. , 2017, The New phytologist.

[16]  Limei Wang,et al.  Pattern and control of biomass allocation across global forest ecosystems , 2017, Ecology and evolution.

[17]  Steffen Fritz,et al.  A dataset of forest biomass structure for Eurasia , 2017, Scientific Data.

[18]  Shilong Piao,et al.  Mapping spatial distribution of forest age in China , 2017 .

[19]  J. Powers,et al.  Overlooking what is underground: Root:shoot ratios and coarse root allometric equations for tropical forests , 2017 .

[20]  Zhenghui Xie,et al.  Incorporation of a dynamic root distribution into CLM4.5: Evaluation of carbon and water fluxes over the Amazon , 2016, Advances in Atmospheric Sciences.

[21]  Jin Liu,et al.  Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data , 2016, Remote. Sens..

[22]  Liang Feng,et al.  The decadal state of the terrestrial carbon cycle: Global retrievals of terrestrial carbon allocation, pools, and residence times , 2016, Proceedings of the National Academy of Sciences.

[23]  Stephanie A. Bohlman,et al.  Dominance of the suppressed: Power-law size structure in tropical forests , 2016, Science.

[24]  Urs Wegmüller,et al.  Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR , 2015 .

[25]  C. Bettigole,et al.  Mapping tree density at a global scale , 2015, Nature.

[26]  Hendrik Poorter,et al.  How does biomass distribution change with size and differ among species? An analysis for 1200 plant species from five continents , 2015, The New phytologist.

[27]  Michael J. Aspinwall,et al.  BAAD: a Biomass And Allometry Database for woody plants , 2015 .

[28]  Matthew F. McCabe,et al.  Recent reversal in loss of global terrestrial biomass , 2015 .

[29]  A. Finzi,et al.  Are above- and below-ground phenology in sync? , 2015, The New phytologist.

[30]  P. Reich,et al.  Temperature drives global patterns in forest biomass distribution in leaves, stems, and roots , 2014, Proceedings of the National Academy of Sciences.

[31]  Mao Ning Tuanmu,et al.  A global 1‐km consensus land‐cover product for biodiversity and ecosystem modelling , 2014 .

[32]  Hua Yuan,et al.  A global soil data set for earth system modeling , 2014 .

[33]  C. Schmullius,et al.  Carbon stock and density of northern boreal and temperate forests , 2014 .

[34]  F. Woodward,et al.  Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2 , 2013, Proceedings of the National Academy of Sciences.

[35]  C. Justice,et al.  High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.

[36]  B. Taylor,et al.  Sampling volume in root studies: the pitfalls of under-sampling exposed using accumulation curves. , 2013, Ecology letters.

[37]  Y. Fan,et al.  Global Patterns of Groundwater Table Depth , 2013, Science.

[38]  Alessandro Anav,et al.  Global Data Sets of Vegetation Leaf Area Index (LAI)3g and Fraction of Photosynthetically Active Radiation (FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011 , 2013, Remote. Sens..

[39]  Ronggao Liu,et al.  Retrospective retrieval of long-term consistent global leaf area index (1981-2011) from combined AVHRR and MODIS data , 2012 .

[40]  T. Booth,et al.  Root:shoot ratios across China's forests: Forest type and climatic effects , 2012 .

[41]  A. Baccini,et al.  Mapping forest canopy height globally with spaceborne lidar , 2011 .

[42]  S. Levin,et al.  The Global Extent and Determinants of Savanna and Forest as Alternative Biome States , 2011, Science.

[43]  R. B. Jackson,et al.  A Large and Persistent Carbon Sink in the World’s Forests , 2011, Science.

[44]  Sophie Graefe,et al.  Elevation effects on the carbon budget of tropical mountain forests (S Ecuador): the role of the belowground compartment , 2011 .

[45]  W. Salas,et al.  Benchmark map of forest carbon stocks in tropical regions across three continents , 2011, Proceedings of the National Academy of Sciences.

[46]  Richard A. Birdsey,et al.  Age structure and disturbance legacy of North American forests , 2010 .

[47]  D. Robinson Implications of a large global root biomass for carbon sink estimates and for soil carbon dynamics , 2007, Proceedings of the Royal Society B: Biological Sciences.

[48]  M. G. Ryan,et al.  Carbon allocation in forest ecosystems , 2007 .

[49]  Brian J. Enquist,et al.  Consistency between an allometric approach and optimal partitioning theory in global patterns of plant biomass allocation , 2007 .

[50]  Karl J Niklas,et al.  A phyletic perspective on the allometry of plant biomass-partitioning patterns and functionally equivalent organ-categories. , 2006, The New phytologist.

[51]  A. Prokushkin,et al.  Critical analysis of root : shoot ratios in terrestrial biomes , 2006 .

[52]  Olivier Hagolle,et al.  Quality assessment and improvement of temporally composited products of remotely sensed imagery by combination of VEGETATION 1 and 2 images , 2005 .

[53]  K. Niklas Modelling below- and above-ground biomass for non-woody and woody plants. , 2005, Annals of botany.

[54]  D. Ruppert The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .

[55]  D. Robinson Scaling the depths: below‐ground allocation in plants, forests and biomes , 2004 .

[56]  Karl J Niklas,et al.  On the Vegetative Biomass Partitioning of Seed Plant Leaves, Stems, and Roots , 2002, The American Naturalist.

[57]  Karl J Niklas,et al.  Global Allocation Rules for Patterns of Biomass Partitioning in Seed Plants , 2002, Science.

[58]  Campbell O. Webb,et al.  Sizing Up the Shape of Life , 2002, Science.

[59]  E. Dinerstein,et al.  The Global 200: Priority ecoregions for global conservation , 2002 .

[60]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[61]  James H. Brown,et al.  A general model for the structure and allometry of plant vascular systems , 1999, Nature.

[62]  R. B. Jackson,et al.  A global budget for fine root biomass, surface area, and nutrient contents. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[63]  Eileen H. Helmer,et al.  Root biomass allocation in the world's upland forests , 1997, Oecologia.

[64]  James H. Brown,et al.  A General Model for the Origin of Allometric Scaling Laws in Biology , 1997, Science.

[65]  R. B. Jackson,et al.  A global analysis of root distributions for terrestrial biomes , 1996, Oecologia.

[66]  R. Colwell Remote sensing of the environment , 1980, Nature.

[67]  S. Ferrari,et al.  Author contributions , 2021 .

[68]  S. Roxburgh,et al.  Tree size and climatic water deficit control root to shoot ratio in individual trees globally. , 2017, The New phytologist.

[69]  Jitendra Kumar,et al.  Root structural and functional dynamics in terrestrial biosphere models--evaluation and recommendations. , 2015, The New phytologist.

[70]  J. Tailleur,et al.  Global Patterns of Groundwater Table Depth , 2013 .

[71]  O. Hagollea,et al.  Quality assessment and improvement of temporally composited products of remotely sensed imagery by combination of VEGETATION 1 and 2 images , 2009 .

[72]  K. Niklas,et al.  Above- and below-ground biomass relationships across 1534 forested communities. , 2007, Annals of botany.

[73]  H. Shaffer,et al.  Annual review of ecology, evolution, and systematics , 2003 .

[74]  Harold A. Mooney,et al.  Terrestrial Global Productivity , 2001 .

[75]  H. Mooney,et al.  23 – Estimations of Global Terrestrial Productivity: Converging toward a Single Number? , 2001 .

[76]  Ed B. Wiken Terrestrial ecozones of Canada , 1986 .