Post on 18-Aug-2015
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• carbon and nutrient cycling• lifetime of carbon in the ecosystem• plant growth
• 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• These models are highly simplified, outdated, and based on very sparse input data or often 'best guesses'
• We need data
Some key knowledge gaps
• How does biomass partitioning (leaf vs. stem) differ between • Angiosperms vs. Gymnosperms• Deciduous vs. Evergreen
• Does higher leaf mass per area (lower SLA) lead to higher plant leaf mass, or lower leaf area?
• Does biomass partitioning depend on climate (mean annual rainfall, mean annual temperature)?
Data: GlopNET (Wright et al. 2004, Nature)
Leaf lifespan increases with LMAIf 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• data from published and unpublished sources, containing biomass and size metrics for woody plants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/
BAAD in numbers 20950 individual woody plants176 published or unpublished studies674 species from 120 taxonomic families
Height range from <1cm to 112m, weight from <1g to >300t.
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
Duursma & Falster in revision
Weak and inconsistent effects of climate
• Biome and MAP or MAT tested
Duursma & Falster in revision
• 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
Conclusions
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
AcknowledgmentsThanks to all 86 co-authors who contributed raw data, and provided answers to many data queries
BAAD Team:Daniel Falster Project lead, programming, workflowRemko Duursma Data quality, programming, analysisMasae Ishihara Japanese compilationDiego R. Barneche Data ingestion, programmingRich G. FitzJohn Workflow, programmingAngelica 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