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Does biomass partitioning differ between plant
functional types? Analysis of a global biomass and
allometry database (BAAD)
Remko Duursma, Daniel Falster
The importance of biomass partitioning
• The distribution of biomass between plant components (‘partitioning’) is of
fundamental importance for
• lifetime of carbon in the ecosystem
• carbon and nutrient cycling
• Global Vegetation Models (GVMs) all contain an allocation submodel, a very
important model component (e.g. Friend et al. 2014 PNAS)
• These models are highly simplified and based on very sparse input data or
often 'best guesses'
• We need data
Questions
• How does biomass partitioning (leaf vs.
stem) differ between
• Angiosperms vs. Gymnosperms
• Deciduous vs. Evergreen
• Does higher leaf mass per area (LMA) lead
to higher plant leaf mass, or lower leaf
area?
• Does biomass partitioning depend on
climate (mean annual rainfall, mean annual
temperature)?
0.25-0.75 quantiles
Data: GlopNET (Wright et al. 2004, Nature)
Leaf lifespan increases with LMA
If all else equal, longer-lived foliage implies higher total
foliage biomass
The Biomass and Allometry Database (BAAD)
• data from published and unpublished sources, containing biomass and
size metrics for woody plants
• Authors were contacted directly, and were asked for raw data + metadata
• Individual plants, destructive harvest (not from allometric estimates)
Raw data
 Manipulate data (if needed)
 Extract variables included in BAAD (and assign unified variable names)
 Add new data (e.g. latitude, longitude, species)
 Store metadata (methods for data collection)
 Store study contacts
Clean data • Repeat for each separate study
• Combine all clean datasets
• Post-process (calculate derived
variables, check species names
against databases, etc.)
BAAD
See also our post on https://ropensci.org/blog/
See also our post on https://ropensci.org/blog/
BAAD in numbers
20950 individual woody plants
176 published or unpublished studies
674 species from 120 taxonomic families
Height range from <1cm to 112m,
weight from <1g to >300t.
Falster et al. 2015 (Ecology)
MAP and MAT of studies in BAAD compared to global land cover
Duursma & Falster in revision
Komiyama et al. 2002, 2003
Komiyama et al., Japan
Ribeiro et al. 2011
Australia
Canada
Spain
Malaysia
Congo Estonia
Spain Argentina
Also : N content, wood density by component (limited)
Different scaling for leaf and woody biomass with plant height
Duursma & Falster in revision
Sequioa
sempervirens
Eucalyptus
regnans
Terminology
• We here considered aboveground biomass only
(Analysis of root data showed no differences between PFTs)
Leaf Mass Fraction (LMF) = leaf mass / aboveground biomass
Leaf Area Ratio (LAR) = leaf area / aboveground biomass
Leaf Mass per Area (LMA) = leaf mass / leaf area
Least-square means
Leaf mass fraction : proportional to leaf mass per area across PFTs
PFTs have similar
leaf area per unit
biomass
 Leaf area ratio does not differ between PFTs
Duursma & Falster in revision
• LMF and LAR are strongly dependent
on height
• Leaf mass fraction can be further
decomposed into
where AS is basal stem area
• Similar to LMF, foliage biomass per
unit stem area was proportional to
LMA
• These variables are only very weakly
dependent on plant height
Weak and inconsistent effects of climate
• Either by biome (boreal, temperate, tropical) or
MAP and MAT
Duursma & Falster in revision
Conclusions
• Three plant functional types differ strongly in leaf mass supported at a
total aboveground biomass or basal stem area
• At given plant height, LMF was proportional to LMA across PFTs
• This also to some extent across species, although there is much
variation within PFTs not accounted for
• As a result, leaf area ratio was not different between PFTs
• No clear effects of climate on biomass partitioning
• These results can be used to constrain biomass partitioning estimates in
global vegetation models, which routinely predict differences between
PFTs
Getting BAAD and future contributions
• Data is released as an Ecology data paper (Falster et al. 2015), you can
download it without restrictions
• The code repository (including all raw data and workflow) is also publicly
available, as a github repository
• New data can be added and released publicly
Acknowledgments
Thanks to all 86 co-authors who contributed raw data,
and provided answers to many data queries
BAAD Team:
Daniel Falster Project lead, programming, workflow
Remko Duursma Data quality, programming, analysis
Masae Ishihara Japanese compilation
Diego R. Barneche Data ingestion, programming
Rich G. FitzJohn Workflow, programming
Angelica Vårhammar Data ingestion, metadata, etc.
BAAD : data contributors
Masahiro Aiba, Makoto Ando, Niels Anten, Jennifer L. Baltzer, Christopher Baraloto, John J. Battles,
Benjamin Bond-Lamberty, Michiel van Breugel, Yves Claveau, Lluís Coll, Masako Dannoura, Sylvain
Delagrange, Jean-Christophe Domec, Farrah Fatemi, Wang Feng, Veronica Gargaglione, Akio
Hagihara, Jefferson S. Hall, Steve Hamilton, Degi Harja, Tsutom Hiura, Robert Holdaway, Lindsay
Hutley, Tomoaki Ichie, Eric J Jokela, Anu Kantola, Jeff W. G. Kelly, Tanaka Kenzo, David King, Brian D
Kloeppel, Takashi Kohyama, Akira Komiyama, Jean-Paul Laclau, Christopher H. Lusk, Doug
Maguire, Guerric le Maire, Annikki Mäkelä, Lars Markesteijn, John Marshall, Katherine McCulloh,
Itsuo Miyata, Karel Mokany, Shigeta Mori, Randall W. Myster, Masahiro Nagano, Shawna Naidu,
Yann Nouvellon, Anthony P. O’Grady, Kevin L. O’Hara, Toshiyuki Ohtsuka, Noriyuki Osada,
Olusegun O. Osunkoya, Pablo Luis Peri, Any Mary Petritan, Lourens Poorter, Angelika Portsmuth,
Catherine Potvin, Johannes Ransijn, Douglas Reid, Sabina C. Ribeiro, Scott D. Roberts, Ignacio
Santa-Regina Rodríguez, Rolando Rodríguez, Angela Saldaña-Acosta, Kaichiro Sasa, N. Galia Selaya,
Stephen C. Sillett, Frank Sterck, Kentaro Takagi, Takeshi Tange, Hiroyuki Tanouchi, David Tissue,
Tohru Umehara, Hajime Utsugi, Matthew A. Vadeboncoeur, Fernando Valladares, Petteri
Vanninen, Jian R. Wang, Elizabeth Wenk, Dick Williams, Fabiano de Aquino Ximenes, Atsushi
Yamaba, Toshihiro Yamada, Takuo Yamakura, Ruth Yanai, Robert A. York
Does biomass partitioning differ between plant functional types? Analysis of BAAD.
Does biomass partitioning differ between plant functional types? Analysis of BAAD.
Does biomass partitioning differ between plant functional types? Analysis of BAAD.

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Does biomass partitioning differ between plant functional types? Analysis of BAAD.

  • 1. Does biomass partitioning differ between plant functional types? Analysis of a global biomass and allometry database (BAAD) Remko Duursma, Daniel Falster
  • 2. The importance of biomass partitioning • The distribution of biomass between plant components (‘partitioning’) is of fundamental importance for • lifetime of carbon in the ecosystem • carbon and nutrient cycling • Global Vegetation Models (GVMs) all contain an allocation submodel, a very important model component (e.g. Friend et al. 2014 PNAS) • These models are highly simplified and based on very sparse input data or often 'best guesses' • We need data
  • 3. Questions • How does biomass partitioning (leaf vs. stem) differ between • Angiosperms vs. Gymnosperms • Deciduous vs. Evergreen • Does higher leaf mass per area (LMA) lead to higher plant leaf mass, or lower leaf area? • Does biomass partitioning depend on climate (mean annual rainfall, mean annual temperature)? 0.25-0.75 quantiles
  • 4. Data: GlopNET (Wright et al. 2004, Nature) Leaf lifespan increases with LMA If all else equal, longer-lived foliage implies higher total foliage biomass
  • 5. The Biomass and Allometry Database (BAAD) • data from published and unpublished sources, containing biomass and size metrics for woody plants • Authors were contacted directly, and were asked for raw data + metadata • Individual plants, destructive harvest (not from allometric estimates) Raw data  Manipulate data (if needed)  Extract variables included in BAAD (and assign unified variable names)  Add new data (e.g. latitude, longitude, species)  Store metadata (methods for data collection)  Store study contacts Clean data • Repeat for each separate study • Combine all clean datasets • Post-process (calculate derived variables, check species names against databases, etc.) BAAD See also our post on https://ropensci.org/blog/
  • 6. See also our post on https://ropensci.org/blog/
  • 7. BAAD in numbers 20950 individual woody plants 176 published or unpublished studies 674 species from 120 taxonomic families Height range from <1cm to 112m, weight from <1g to >300t.
  • 8. Falster et al. 2015 (Ecology)
  • 9. MAP and MAT of studies in BAAD compared to global land cover Duursma & Falster in revision
  • 10. Komiyama et al. 2002, 2003
  • 11.
  • 12.
  • 13.
  • 18. Also : N content, wood density by component (limited)
  • 19. Different scaling for leaf and woody biomass with plant height Duursma & Falster in revision Sequioa sempervirens Eucalyptus regnans
  • 20. Terminology • We here considered aboveground biomass only (Analysis of root data showed no differences between PFTs) Leaf Mass Fraction (LMF) = leaf mass / aboveground biomass Leaf Area Ratio (LAR) = leaf area / aboveground biomass Leaf Mass per Area (LMA) = leaf mass / leaf area
  • 21. Least-square means Leaf mass fraction : proportional to leaf mass per area across PFTs PFTs have similar leaf area per unit biomass  Leaf area ratio does not differ between PFTs Duursma & Falster in revision
  • 22. • LMF and LAR are strongly dependent on height • Leaf mass fraction can be further decomposed into where AS is basal stem area • Similar to LMF, foliage biomass per unit stem area was proportional to LMA • These variables are only very weakly dependent on plant height
  • 23. Weak and inconsistent effects of climate • Either by biome (boreal, temperate, tropical) or MAP and MAT Duursma & Falster in revision
  • 24. Conclusions • Three plant functional types differ strongly in leaf mass supported at a total aboveground biomass or basal stem area • At given plant height, LMF was proportional to LMA across PFTs • This also to some extent across species, although there is much variation within PFTs not accounted for • As a result, leaf area ratio was not different between PFTs • No clear effects of climate on biomass partitioning • These results can be used to constrain biomass partitioning estimates in global vegetation models, which routinely predict differences between PFTs
  • 25. Getting BAAD and future contributions • Data is released as an Ecology data paper (Falster et al. 2015), you can download it without restrictions • The code repository (including all raw data and workflow) is also publicly available, as a github repository • New data can be added and released publicly
  • 26. Acknowledgments Thanks to all 86 co-authors who contributed raw data, and provided answers to many data queries BAAD Team: Daniel Falster Project lead, programming, workflow Remko Duursma Data quality, programming, analysis Masae Ishihara Japanese compilation Diego R. Barneche Data ingestion, programming Rich G. FitzJohn Workflow, programming Angelica Vårhammar Data ingestion, metadata, etc.
  • 27. BAAD : data contributors Masahiro Aiba, Makoto Ando, Niels Anten, Jennifer L. Baltzer, Christopher Baraloto, John J. Battles, Benjamin Bond-Lamberty, Michiel van Breugel, Yves Claveau, Lluís Coll, Masako Dannoura, Sylvain Delagrange, Jean-Christophe Domec, Farrah Fatemi, Wang Feng, Veronica Gargaglione, Akio Hagihara, Jefferson S. Hall, Steve Hamilton, Degi Harja, Tsutom Hiura, Robert Holdaway, Lindsay Hutley, Tomoaki Ichie, Eric J Jokela, Anu Kantola, Jeff W. G. Kelly, Tanaka Kenzo, David King, Brian D Kloeppel, Takashi Kohyama, Akira Komiyama, Jean-Paul Laclau, Christopher H. Lusk, Doug Maguire, Guerric le Maire, Annikki Mäkelä, Lars Markesteijn, John Marshall, Katherine McCulloh, Itsuo Miyata, Karel Mokany, Shigeta Mori, Randall W. Myster, Masahiro Nagano, Shawna Naidu, Yann Nouvellon, Anthony P. O’Grady, Kevin L. O’Hara, Toshiyuki Ohtsuka, Noriyuki Osada, Olusegun O. Osunkoya, Pablo Luis Peri, Any Mary Petritan, Lourens Poorter, Angelika Portsmuth, Catherine Potvin, Johannes Ransijn, Douglas Reid, Sabina C. Ribeiro, Scott D. Roberts, Ignacio Santa-Regina Rodríguez, Rolando Rodríguez, Angela Saldaña-Acosta, Kaichiro Sasa, N. Galia Selaya, Stephen C. Sillett, Frank Sterck, Kentaro Takagi, Takeshi Tange, Hiroyuki Tanouchi, David Tissue, Tohru Umehara, Hajime Utsugi, Matthew A. Vadeboncoeur, Fernando Valladares, Petteri Vanninen, Jian R. Wang, Elizabeth Wenk, Dick Williams, Fabiano de Aquino Ximenes, Atsushi Yamaba, Toshihiro Yamada, Takuo Yamakura, Ruth Yanai, Robert A. York