Future global productivity will be affected by plant trait response to climate

Nima Madani, John S. Kimball, Ashley P. Ballantyne, David L.R. Affleck, Peter M. Van Bodegom, Peter B. Reich, Jens Kattge, Anna Sala, Mona Nazeri, Matthew O. Jones, Maosheng Zhao, Steven W. Running

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Plant traits are both responsive to local climate and strong predictors of primary productivity. We hypothesized that future climate change might promote a shift in global plant traits resulting in changes in Gross Primary Productivity (GPP). We characterized the relationship between key plant traits, namely Specific Leaf Area (SLA), height, and seed mass, and local climate and primary productivity. We found that by 2070, tropical and arid ecosystems will be more suitable for plants with relatively lower canopy height, SLA and seed mass, while far northern latitudes will favor woody and taller plants than at present. Using a network of tower eddy covariance CO2 flux measurements and the extrapolated plant trait maps, we estimated the global distribution of annual GPP under current and projected future plant community distribution. We predict that annual GPP in northern biomes (≥45 °N) will increase by 31% (+8.1 ± 0.5 Pg C), but this will be offset by a 17.9% GPP decline in the tropics (-11.8 ± 0.84 Pg C). These findings suggest that regional climate changes will affect plant trait distributions, which may in turn affect global productivity patterns.

Original languageEnglish (US)
Article number2870
JournalScientific reports
Volume8
Issue number1
DOIs
StatePublished - Dec 1 2018

Bibliographical note

Funding Information:
This study was conducted with funding provided by NASA (NNX15AB59G, NNX14AI50G). Additional support was provided by the TRY initiative on plant traits (http://www.try-db.org). This work used eddy covariance data acquired by the FLUXNET community. For their roles in producing, coordinating, and making available the CMIP5 model output, we acknowledge the climate modeling groups (listed in table S1 of this paper), the World Climate Research Programme’s (WCRP) Working Group on Coupled Modelling (WGCM), and the Global Organization for Earth System Science Portals (GO-ESSP).

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